Image Title

Search Results for NTT:

Shahid Ahmed, NTT | MWC Barcelona 2023


 

(inspirational music) >> theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (uplifting electronic music) (crowd chattering in background) >> Hi everybody. We're back at the Fira in Barcelona. Winding up our four day wall-to-wall coverage of MWC23 theCUBE has been thrilled to cover the telco transformation. Dave Vellante with Dave Nicholson. Really excited to have NTT on. Shahid Ahmed is the Group EVP of New Ventures and Innovation at NTT in from Chicago. Welcome to Barcelona. Welcome to theCUBE. >> Thank you for having me over. >> So, really interesting title. You have, you know, people might not know NTT you know, huge Japan telco but a lot of other businesses, explain your business. >> So we do a lot of things. Most of us are known for our Docomo business in Japan. We have one of the largest wireless cellular carriers in the world. We serve most of Japan. Outside of Japan, we are B2B systems, integration, professional services company. So we offer managed services. We have data centers, we have undersea cables. We offer all kinds of outsourcing services. So we're a big company. >> So there's a narrative out there that says, you know, 5G, it's a lot of hype, not a lot of adoption. Nobody's ever going to make money at 5G. You have a different point of view, I understand. You're like leaning into 5G and you've actually got some traction there. Explain that. >> So 5G can be viewed from two lenses. One is just you and I using our cell phones and we get 5G coverage over it. And the other one is for businesses to use 5G, and we call that private 5G or enterprise grade 5G. Two very separate distinct things, but it is 5G in the end. Now the big debate here in Europe and US is how to monetize 5G. As a consumer, you and I are not going to pay extra for 5G. I mean, I haven't. I just expect the carrier to offer faster, cheaper services. And so would I pay extra? Not really. I just want a reliable network from my carrier. >> Paid up for the good camera though, didn't you? >> I did. (Dave and Dave laughing) >> I'm waiting for four cameras now. >> So the carriers are in this little bit of a pickle at the moment because they've just spent billions of dollars, not only on spectrum but the infrastructure needed to upgrade to 5G, yet nobody's willing to pay extra for that 5G service. >> Oh, right. >> So what do they do? And one idea is to look at enterprises, companies, industrial companies, manufacturing companies who want to build their own 5G networks to support their own use cases. And these use cases could be anything from automating the surveyor belt to cameras with 5G in it to AGVs. These are little carts running around warehouses picking up products and goods, but they have to be connected all the time. Wifi doesn't work all the time there. And so those businesses are willing to pay for 5G. So your question is, is there a business case for 5G? Yes. I don't think it's in the consumer side. I think it's in the business side. And that's where NTT is finding success. >> So you said, you know, how they going to make money, right? You very well described the telco dilemma. We heard earlier this week, you know, well, we could tax the OTT vendors, like Netflix of course shot back and said, "Well, we spent a lot of money on content. We're driving a lot of value. Why don't you help us pay for the content development?" Which is incredibly expensive. I think I heard we're going to tax the developers for API calls on the network. I'm not sure how well that's going to work out. Look at Twitter, you know, we'll see. And then yeah, there's the B2B piece. What's your take on, we heard the Orange CEO say, "We need help." You know, maybe implying we're going to tax the OTT vendors, but we're for net neutrality, which seems like it's completely counter-posed. What's your take on, you know, fair share in the network? >> Look, we've seen this debate unfold in the US for the last 10 years. >> Yeah. >> Tom Wheeler, the FCC chairman started that debate and he made great progress and open internet and net neutrality. The thing is that if you create a lane, a tollway, where some companies have to pay toll and others don't have to, you create an environment where the innovation could be stifled. Content providers may not appear on the scene anymore. And with everything happening around AI, we may see that backfire. So creating a toll for rich companies to be able to pay that toll and get on a faster speed internet, that may work some places may backfire in others. >> It's, you know, you're bringing up a great point. It's one of those sort of unintended consequences. You got to be be careful because the little guy gets crushed in that environment, and then what? Right? Then you stifle innovation. So, okay, so you're a fan of net neutrality. You think the balance that the US model, for a change, maybe the US got it right instead of like GDPR, who sort of informed the US on privacy, maybe the opposite on net neutrality. >> I think so. I mean, look, the way the US, particularly the FCC and the FTC has mandated these rules and regulation. I think it's a nice balance. FTC is all looking at big tech at the moment, but- >> Lena Khan wants to break up big tech. I mean for, you know, you big tech, boom, break 'em up, right? So, but that's, you know- >> That's a whole different story. >> Yeah. Right. We could talk about that too, if you want. >> Right. But I think that we have a balanced approach, a measured approach. Asking the content providers or the developers to pay for your innovative creative application that's on your phone, you know, that's asking for too much in my opinion. >> You know, I think you're right though. Government did do a good job with net neutrality in the US and, I mean, I'm just going to go my high horse for a second, so forgive me. >> Go for it. >> Market forces have always done a better job at adjudicating, you know, competition. Now, if a company's a monopoly, in my view they should be, you know, regulated, or at least penalized. Yeah, but generally speaking, you know the attack on big tech, I think is perhaps misplaced. I sat through, and the reason it's relevant to Mobile World Congress or MWC, is I sat through a Nokia presentation this week and they were talking about Bell Labs when United States broke up, you know, the US telcos, >> Yeah. >> Bell Labs was a gem in the US and now it's owned by Nokia. >> Yeah. >> Right? And so you got to be careful about, you know what you wish for with breaking up big tech. You got AI, you've got, you know, competition with China- >> Yeah, but the upside to breaking up Ma Bell was not just the baby Bells and maybe the stranded orphan asset of Bell Labs, but I would argue it led to innovation. I'm old enough to remember- >> I would say it made the US less competitive. >> I know. >> You were in junior high school, but I remember as an adult, having a rotary dial phone and having to pay for that access, and there was no such- >> Yeah, but they all came back together. The baby Bells are all, they got all acquired. And the cable company, it was no different. So I don't know, do you have a perspective of this? Because you know this better than I do. >> Well, I think look at Nokia, just they announced a whole new branding strategy and new brand. >> I like the brand. >> Yeah. And- >> It looks cool. >> But guess what? It's B2B oriented. >> (laughs) Yeah. >> It's no longer consumer, >> Right, yeah. >> because they felt that Nokia brand phone was sort of misleading towards a lot of business to business work that they do. And so they've oriented themselves to B2B. Look, my point is, the carriers and the service providers, network operators, and look, I'm a network operator, too, in Japan. We need to innovate ourselves. Nobody's stopping us from coming up with a content strategy. Nobody's stopping a carrier from building a interesting, new, over-the-top app. In fact, we have better control over that because we are closer to the customer. We need to innovate, we need to be more creative. I don't think taxing the little developer that's building a very innovative application is going to help in the long run. >> NTT Japan, what do they have a content play? I, sorry, I'm not familiar with it. Are they strong in content, or competitive like Netflix-like, or? >> We have relationships with them, and you remember i-mode? >> Yeah. Oh yeah, sure. >> Remember in the old days. I mean, that was a big hit. >> Yeah, yeah, you're right. >> Right? I mean, that was actually the original app marketplace. >> Right. >> And the application store. So, of course we've evolved from that and we should, and this is an evolution and we should look at it more positively instead of looking at ways to regulate it. We should let it prosper and let it see where- >> But why do you think that telcos generally have failed at content? I mean, AT&T is sort of the exception that proves the rule. I mean, they got some great properties, obviously, CNN and HBO, but generally it's viewed as a challenging asset and others have had to diversify or, you know, sell the assets. Why do you think that telcos have had such trouble there? >> Well, Comcast owns also a lot of content. >> Yeah. Yeah, absolutely. >> And I think, I think that is definitely a strategy that should be explored here in Europe. And I think that has been underexplored. I, in my opinion, I believe that every large carrier must have some sort of content strategy at some point, or else you are a pipe. >> Yeah. You lose touch with a customer. >> Yeah. And by the way, being a dump pipe is okay. >> No, it's a lucrative business. >> It's a good business. You just have to focus. And if you start to do a lot of ancillary things around it then you start to see the margins erode. But if you just focus on being a pipe, I think that's a very good business and it's very lucrative. Everybody wants bandwidth. There's insatiable demand for bandwidth all the time. >> Enjoy the monopoly, I say. >> Yeah, well, capital is like an organism in and of itself. It's going to seek a place where it can insert itself and grow. Do you think that the questions around fair share right now are having people wait in the wings to see what's going to happen? Because especially if I'm on the small end of creating content, creating services, and there's possibly a death blow to my fixed costs that could be coming down the line, I'm going to hold back and wait. Do you think that the answer is let's solve this sooner than later? What are your thoughts? >> I think in Europe the opinion has been always to go after the big tech. I mean, we've seen a lot of moves either through antitrust, or other means. >> Or the guillotine! >> That's right. (all chuckle) A guillotine. Yes. And I've heard those directly. I think, look, in the end, EU has to decide what's right for their constituents, the countries they operate, and the economy. Frankly, with where the economy is, you got recession, inflation pressures, a war, and who knows what else might come down the pipe. I would be very careful in messing with this equilibrium in this economy. Until at least we have gone through this inflation and recessionary pressure and see what happens. >> I, again, I think I come back to markets, ultimately, will adjudicate. I think what we're seeing with chatGPT is like a Netscape moment in some ways. And I can't predict what's going to happen, but I can predict that it's going to change the world. And there's going to be new disruptors that come about. That just, I don't think Amazon, Google, Facebook, Apple are going to rule the world forever. They're just, I guarantee they're not, you know. They'll make it through. But there's going to be some new companies. I think it might be open AI, might not be. Give us a plug for NTT at the show. What do you guys got going here? Really appreciate you coming on. >> Thank you. So, you know, we're showing off our private 5G network for enterprises, for businesses. We see this as a huge opportunities. If you look around here you've got Rohde & Schwarz, that's the industrial company. You got Airbus here. All the big industrial companies are here. Automotive companies and private 5G. 5G inside a factory, inside a hospital, a warehouse, a mining operation. That's where the dollars are. >> Is it a meaningful business for you today? >> It is. We just started this business only a couple of years ago. We're seeing amazing growth and I think there's a lot of good opportunities there. >> Shahid Ahmed, thanks so much for coming to theCUBE. It was great to have you. Really a pleasure. >> Thanks for having me over. Great questions. >> Oh, you're welcome. All right. For David Nicholson, Dave Vellante. We'll be back, right after this short break, from the Fira in Barcelona, MWC23. You're watching theCUBE. (uplifting electronic music)

Published Date : Mar 2 2023

SUMMARY :

that drive human progress. Shahid Ahmed is the Group EVP You have, you know, We have one of the largest there that says, you know, I just expect the carrier to I did. So the carriers are in but they have to be We heard earlier this week, you know, in the US for the last 10 years. appear on the scene anymore. You got to be be careful because I mean, look, the way the I mean for, you know, you We could talk about that too, if you want. or the developers to pay and, I mean, I'm just going to at adjudicating, you know, competition. US and now it's owned by Nokia. And so you got to be Yeah, but the upside the US less competitive. And the cable company, Well, I think look at Nokia, just But guess what? and the service providers, I, sorry, I'm not familiar with it. Remember in the old days. I mean, that was actually And the application store. I mean, AT&T is sort of the also a lot of content. And I think that has been underexplored. And if you start to do a lot that could be coming down the line, I think in Europe the and the economy. And there's going to be new that's the industrial company. and I think there's a lot much for coming to theCUBE. Thanks for having me over. from the Fira in Barcelona, MWC23.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
AmazonORGANIZATION

0.99+

Dave NicholsonPERSON

0.99+

David NicholsonPERSON

0.99+

FCCORGANIZATION

0.99+

AppleORGANIZATION

0.99+

ComcastORGANIZATION

0.99+

GoogleORGANIZATION

0.99+

FacebookORGANIZATION

0.99+

Tom WheelerPERSON

0.99+

Dave VellantePERSON

0.99+

CNNORGANIZATION

0.99+

EuropeLOCATION

0.99+

NokiaORGANIZATION

0.99+

Lena KhanPERSON

0.99+

HBOORGANIZATION

0.99+

JapanLOCATION

0.99+

Shahid AhmedPERSON

0.99+

FTCORGANIZATION

0.99+

ChicagoLOCATION

0.99+

NetflixORGANIZATION

0.99+

USLOCATION

0.99+

NTTORGANIZATION

0.99+

Bell LabsORGANIZATION

0.99+

AT&TORGANIZATION

0.99+

EUORGANIZATION

0.99+

AirbusORGANIZATION

0.99+

DavePERSON

0.99+

OrangeORGANIZATION

0.99+

BarcelonaLOCATION

0.99+

Dell TechnologiesORGANIZATION

0.99+

TwitterORGANIZATION

0.99+

DocomoORGANIZATION

0.99+

MWC23EVENT

0.99+

OneQUANTITY

0.98+

four dayQUANTITY

0.98+

earlier this weekDATE

0.98+

billions of dollarsQUANTITY

0.98+

this weekDATE

0.98+

two lensesQUANTITY

0.98+

one ideaQUANTITY

0.98+

telcoORGANIZATION

0.98+

GDPRTITLE

0.97+

USORGANIZATION

0.97+

Mobile World CongressEVENT

0.97+

telcosORGANIZATION

0.97+

United StatesLOCATION

0.96+

NTT JapanORGANIZATION

0.95+

oneQUANTITY

0.95+

MWCEVENT

0.95+

todayDATE

0.94+

FiraLOCATION

0.93+

Barcelona,LOCATION

0.91+

5GORGANIZATION

0.91+

four camerasQUANTITY

0.9+

Two very separate distinct thingsQUANTITY

0.89+

Rohde & SchwarzORGANIZATION

0.89+

last 10 yearsDATE

0.88+

NetscapeORGANIZATION

0.88+

couple of years agoDATE

0.88+

theCUBEORGANIZATION

0.85+

New Ventures and InnovationORGANIZATION

0.73+

Ma BellORGANIZATION

0.71+

Charu Kapur, NTT Data & Rachel Mushahwar, AWS & Jumi Barnes, Goldman Sachs | AWS re:Invent 2022


 

>>Hey everyone. Hello from Las Vegas. Lisa Martin here with you, and I'm on the show floor at Reinvent. But we have a very special program series that the Cube has been doing called Women of the Cloud. It's brought to you by aws and I'm so pleased to have an excellent panel of women leaders in technology and in cloud to talk about their tactical recommendations for you, what they see as found, where they've helped organizations be successful with cloud. Please welcome my three guests, Tara Kapor, president and Chief Revenue Officer, consulting and Digital Transformations, NTT Data. We have Rachel Mu, aws, head of North America, partner sales from aws, and Jimmy Barnes joins us as well, managing director, investment banking engineering at Goldman Sachs. It is so great to have you guys on this power panel. I love it. Thank you for joining me. >>Thank >>You. Let's start with you. Give us a little bit of, of your background at NTT Data and I, and I understand NTT has a big focus on women in technology and in stem. Talk to us a little bit about that and then we'll go around the table. >>Perfect, thank you. Thank you. So brand new role for me at Entity Data. I started three months back and it's a fascinating company. We are about 22 billion in size. We work across industries on multiple innovative use cases. So we are doing a ton of work on edge analytics in the cloud, and that's where we are here with aws. We are also doing a ton of work on the private 5G that we are rolling out and essentially building out industry-wide use cases across financial services, manufacturing, tech, et cetera. Lots of women identity. We essentially have women run cloud program today. We have a gal called Nore Hanson who is our practice leader for cloud. We have Matine who's Latifa, who's our AWS cloud leader. We have Molly Ward who leads up a solutions on the cloud. We have an amazing lady in Mona who leads up our marketing programs. So a fantastic plethora of diverse women driving amazing work identity on cloud. >>That's outstanding to hear because it's one of those things that you can't be what you can't see. Right. We all talk about that. Rachel, talk a little bit about your role and some of the focus that AWS has. I know they're big customer obsession, I'm sure obsessed with other things as well. >>Sure. So Rachel Muir, pleased to be here again. I think this will be my third time. So a big fan of the Cube. I'm fortunate enough to lead our North America partner and channel business, and I'll tell you, I've been at AWS for a little under two years, and honestly, it's been probably the best two years of my career. Just in terms of where the cloud is, where it's headed, the business outcomes that we can deliver with our customers and with our partners is absolutely remarkable. We get to, you know, make the impossible possible every day. So I'm, I'm thrilled to be here and I'm thrilled to, to be part of this inaugural Women of the Cloud panel. >>Oh, I'm prepared to have all three of you. One of the things that feedback, kind of pivoting off what, Rachel, one of the things that you said that one of our guests, some of several of our guests have said is that coming out of Adams keynote this morning, it just seems limitless what AWS can do and I love that it gives me kind of chills what they can do with cloud computing and technology, with its ecosystem of partners with its customers like Goldman Sachs. Jimmy, talk to us a little bit about you, your role at Goldman Sachs. You know, we think of Goldman Sachs is a, is a huge financial institution, but it's also a technology company. >>Yeah. I mean, since the age of 15 I've been super passionate about how we can use technology to transform business and simplify modernized business processes. And it's, I'm so thrilled that I have the opportunity to do that at Goldman Sachs as an engineer. I recently moved about two years ago into the investment banking business and it's, you know, it's best in class, one of the top companies in terms of mergers and acquisitions, IPOs, et cetera. But what surprised me is how technology enables all the businesses across the board. Right? And I get to be leading the digital platform for building out the digital platform for in the investment banking business where we're modernizing and transforming existing businesses. These are not new businesses. It's like sometimes I liken it to trying to change the train while it's moving, right? These are existing businesses, but now we get to modernize and transform on the cloud. Right. Not just efficiency for the business by efficiency for technologists as >>Well. Right, right. Sticking with you, Jimmy. I wanna understand, so you've been, you've been interested in tech since you were young. I only got into tech and accidentally as an adult. I'm curious about your career path, but talk to us about that. What are some of the recommendations that you would have for other women who might be looking at, I wanna be in technology, but I wanna work for some of the big companies and they don't think about the Goldman Sachs or some of the other companies like Walmart that are absolutely technology driven. What's your advice for those women who want to grow their career? >>I also, growing up, I was, I was interested in various things. I, I loved doing hair. I used to do my own hair and I used to do hair for other students at school and I was also interested in running an entertainment company. And I used actually go around performing and singing and dancing with a group of friends, especially at church. But what amazed me is when I landed my first job at a real estate agent and everything was being done manually on paper, I was like, wow, technology can bring transformation anywhere and everywhere. And so whilst I have a myriad of interest, there's so many ways that technology can be applied. There's so many different types of disciplines within technology. It's not, there's hands on, like I'm colder, I like to code, but they're product managers, there are business analysts, there are infrastructure specialist. They're a security specialist. And I think it's about pursuing your passion, right? Pursuing your passion and identifying which aspects of technology peak your interest. And then diving in. >>Love that. Diving in. Rachel, you're shaking your head. You definitely are in alignment with a lot of what >>Duties I am. So, you know, interesting enough, I actually started my career as a civil engineer and eventually made it into, into technology. So very similar. I saw in, you know, heavy highway construction how manual some of these processes were. And mind you, this was before the cloud. And I sat down and wrote a little computer program to automate a lot of these manual tasks. And for me it was about simplification of the customer journey and really figuring out how do you deliver value. You know, on fast forward, say 20 plus years, here I am with AWS who has got this amazing cloud platform with over 200 services. And when I think about what we do in tech, from business transformation to modernizing to helping customers think about how do they create new business models, I've really found, I've really found my sweet spot, and I'll say for anyone who wants to get into tech or even switch careers, there's just a couple words of advice that I have. And it's really two words, just start. >>Yes, >>That's it. Just start. Because sometimes later becomes never. And you know, fuel your passion, be curious, think about new things. Yes. And just >>Start, I love that. Just start, you should get t-shirts made with that. Tell me a little bit about some of your recommendations. Obviously just start is great when follow your passion. What would you say to those out there looking to plan the letter? >>So, you know, my, my story's a little bit like jus because I did not want to be in tech. You know, I wanted an easy life. I did well in school and I wanted to actually be an air hostess. And when I broke that to my father, you know, the standard Indian person, now he did, he, you know, he wanted me to go in and be an engineer. Okay? So I was actually push into computer engineering, graduated. But then really two things today, right? When I look back, really two pieces, two areas I believe, which are really important for success. One is, you know, we need to be competent. And the second is we need to be confident, right? Yes, yes. It's so much easier to be competent because a lot of us diverse women, diverse people tend to over rotate on knowing their technical skills, right? Knowing technical skills important, but you need to know how to potentially apply those to business, right? Be able to define a business roi. And I see Julie nodding because she wants people to come in and give her a business ROI for programs that you're executing at Goldman Sachs. I presume the more difficult part though is confidence. >>Absolutely. It's so hard, especially when, when we're younger, we don't know. Raise your hand because I guarantee you either half the people in the, in the room or on the zoom these days weren't listening or have the same question and are too afraid to ask because they don't have the confidence. That's right. Give me, let's pivot on confidence for a minute, Jim, and let's go back to how would you advise your younger self to find your confidence? >>That's, that's a tough one because I feel like even this older self is still finding exercise to, to be real. But I think it's about, I would say it's not praise. I think it's about praising yourself, like recognizing your accomplishments. When I think about my younger self, I think I, I like to focus more on what I didn't do or what I didn't accomplish, instead of majoring and focusing on all the accomplishments and the achievements and reminding myself of those day after day after day. And I think it's about celebrating your wins. >>I love that. Celebrating your wins. Do you agree, Rachel? >>I do. Here's the hard part, and I look around this table of amazing business leaders and I can guarantee that every single one of us sometime this year woke up and said, oh my gosh, I don't know how to do that. Oh >>Yeah. But >>What we haven't followed that by is, I don't know how to do that yet. Right. And here's the other thing I would tell my younger self is there will be days where every single one of us falls apart. There will be days when we feel like we failed at work. There will be days when you feel like you failed as a parent or you failed as a spouse. There'll be days where you have a kid in the middle of target screaming and crying while you're trying to close a big business deal and you just like, oh my gosh, is this really my life? But what I would tell my younger self is, look, the crying, the chaos, the second guessing yourself, the successes, every single one of those are milestones. And it's triumphant, it's tragic, but every single thing that we have been through is fiercely worthwhile. And it's what got us >>Here. Absolutely. Absolutely. Think of all the trials and tribulations and six and Zacks that got you to this table right now. Yep. So Terry, you brought up confidence. How would you advise the women out there won't say you're gonna know stuff. The women out there now that are watching those that are watching right there. Hi. How would you advise them to really find their, their ability to praise themselves, recognize all of the trials and the tribulations as milestones as Rachel said, and really give themselves a seat at the table, raise their hand regardless of who else is in the room? >>You know, it's a, it's a more complex question just because confidence stems from courage, right? Confidence also stems from the belief that you're going to be treated fairly right now in an organization for you to be treated fairly. You need to have, be surrounded by supporters that are going to promote your voice. And very often women don't invest enough in building that support system around them. Yeah. Right. We have mentors, and mentors are great because they come in and they advise us and they'll tell us what we need to go out and do. We really need a team of sponsors Yes. Who come in and support us in the moment in the business. Give us the informal channel because very often we are not plugged into the informal channel, right. So we don't get those special projects or assignments or even opportunities to prove that we can do the tough task. Yeah. So, you know, my, my advice would be to go out and build a network of sponsors. Yes. And if you don't have one, be a sponsor for someone else. That's right. I love that. Great way to win sponsorship is by extending it todos. >>And sometimes too, it's about, honestly, I didn't even know the difference between a mentor and a sponsor until a few years ago. And I started thinking, who are I? And then I started realizing who they were. That's right. And some of the conversations that we've had on the cube about women in technology, women of the cloud with some of the women leaders have said, build, and this is kind of like, sort of what you were saying, build your own personal board of directors. Yeah. And that, oh, it gives me chills. It's just, it's so important for, for not just women, but anybody, for everybody. But it's so important to do that. And if you, you think about LinkedIn as an example, you have a network, it's there, utilize it, figure out who your mentors are, who your sponsors are, who are gonna help you land the next thing, start building that reputation. But having that board of directors that you can kind of answer to or have some accountability towards, I think is hugely very >>Important. Yeah. >>Very important. I think, you know, just for, just for those that are listening, a really important distinction for me was mentors are people that you have that help you with, Hey, here's the situation that you were just in. They advise you on the situation. Sponsors are the people that stick up for you when you're not in the room to them. Right. Sponsors are the ones that say, Hey, I think so and so not only needs to have a seat at the table, but they need to build the table. And that's a really important delineation. Yeah. Between mentors and sponsors. And everybody's gotta have a sponsor both within their company and outside of their company. Someone that's advocating for them on their behalf when they don't even know it. Yeah. Yeah. >>I love that you said that. Build the table. It reminds me of a quote that I heard from Will I am, I know, very random. It was a podcast he did with Oprah Winfrey on ai. He's very into ai and I was doing a panel on ai, so I was doing a lot of research and he said, similar for Rachel to build the table, don't wait for a door to open. You go build a door. And I just thought, God, that is such brilliant advice. It is. It's hard to do. It is. Especially when, you know, the four of us in this room, there's a lot of women around here, but we are in an environment where we are the minority women of color are also the minority. What do you guys think where tech is in terms of de and I and really focusing on De and I as as really a very focused strategic initiative. Turner, what do you think? >>So, you know, I just, I, I spoke earlier about the women that we have at Entity Data, right? We have a fabulous team of women. And joining this team has been a moment of revelation for me coming in. I think to promote dni, we all need to start giving back, right? Yes. So today, I would love to announce that we at Entity would like to welcome all of you out there. You know, folks that have diverse ideas, you know, ISV, partners with diverse solutions, thought leaders out there who want to contribute into the ecosystem, right? Customers out there who want to work with companies that are socially responsible, right? We want to work with all of you, come back, reach out to us and be a part of the ecosystem because we can build this together, right? AWS has an amazing platform that gives us an opportunity to do things differently. Yes. Right. Entity data is building a women powered cloud team. And I want to really extend that out to everyone else to be a part this ecosystem, >>But a fantastic opportunity. You know, when we talk about diversity and inclusion and equity, it needs to be intentional for organization. It sounds very intentional at ntt. I know that that intention is definitely there at AWS as well. What are your thoughts on where tech is with respect to diversity? Even thought diversity? Because a lot of times we tend to go to our comfort zones. We do. And so we tend to start creating these circles of kind of like, you know, think tanks and they think alike people to go outside of that comfort zone. It's part of building the table, of building the, is the table and getting people from outside your comfort zone to come in and bring in diverse thought. Because can you imagine the potential of technology if we have true thought diversity in an organization? >>Right? It's, it's incredible. So one of the things that I always share with my team is we've got the opportunity to really change the outcome, right? As you know, you talked about Will I am I'm gonna talk about Bono from you too, right? One of, one of his favorite quotes is, we are the people we've been waiting for. Oh, I love that. And when you think about that, that is us. There is no one else that's gonna change the outcome and continue to deliver some of the business outcomes and the innovation that we are if we don't continue to raise our hand and we don't continue to, to inspire the next generation of leaders to do the same thing. And what I've found is when you start openly sharing what your innovation ideas are or how you're leveraging your engineering background, your stories and your successes, and, and frankly, some of your failures become the inspiration for someone you might not even know. Absolutely. And that's the, you know, that's the key. You're right. Inclusion, diversity, equity and accessibility, yes. Have to be at the forefront of every business decision. And I think too often companies think that, you know, inclusion, diversity, equity and accessibility is one thing, and business outcomes are another. And they're not. No, they are one in the same. You can't build business outcomes without also focusing on inclusion, diversity, equity, accessibility. That's the deliberate piece. >>And, and it has to be deliberate. Jimmy, I wanna ask you, we only have a couple of minutes left, but you're a woman in tech, you're a woman of color. What was that like for you? You, you were very intentional knowing when you were quite young. Yeah. What you wanted to do, but how have you navigated that? Because I can't imagine that was easy. >>It wasn't. I remember, I always tell the story and the, the two things that I really wanted to emphasize today when I thought about this panel is rep representation matters and showing up matters, right? And there's a statement, there's a flow, I don't know who it's attributed to, but be the change you want to see. And I remember walking through the doors of Goldman Sachs 15 years ago and not seeing a black female engineer leader, right? And at that point in time, I had a choice. I could be like, oh, there's no one look like, there's no one that looks like me. I don't belong here. Or I could do what I actually did and say, well, I'm gonna be that person. >>Good, >>Right? I'm going to be the chain. I'm going to show up and I am going to have a seat at the table so that other people behind me can also have a seat at the table. And I think that I've had the privilege to work for a company who has been inclusive, who has had the right support system, the right structures in place, so that I can be that person who is the first black woman tech fellow at Goldman Sachs, who is one of the first black females to be promoted up the rank as a, from analysts to managing director at the company. You know, that was not just because I determined that I belong here, but because the company ensure that I felt that I belong. >>Right. >>That's a great point. They ensure that you felt that. Yeah. You need to be able to feel that. Last question, we've only got about a minute left. 2023 is just around the corner. What comes to your mind, Jimmy will stick with you as you head into the new year. >>Sorry, can you repeat >>What comes to mind priorities for 2023 that you're excited about? >>I'm excited about the democratization of data. Yeah. I'm excited about a lot of the announcements today and I, I think there is a, a huge shift going on with this whole concept of marketplaces and data exchanges and data sharing. And I think both internally and externally, people are coming together more. Companies are coming together more to really de democratize and make data available. And data is power. But a lot of our businesses are running, running on insights, right? And we need to bring that data together and I'm really excited about the trends that's going on in cloud, in technology to actually bring the data sets together. >>Touro, what are you most excited about as we head to 2023? >>I think I'm really excited about the possibilities that entity data has right here, right now, city of Las Vegas, we've actually rolled out a smart city project. So saving citizens life, using data edge analytics, machine learning, being able to predict adverse incidents before they happen, and then being able to take remediation action, right? So that's technology actually working in real time to give us tangible results. We also sponsor the Incar races. Lots of work happening there in delivering amazing customer experience across the platform to millions of users real time. So I think I'm just excited about technology coming together, but while that's happening, I think we really need to be mindful at this time that we don't push our planet into per right. We need to be sustainable, we need to be responsible. >>Absolutely. Rachel, take us out. What are you most excited about going into 2023? >>So, you know, there are so many trends that are, that we could talk about, but I'll tell you at aws, you know, we're big. We, we impact the world. So we've gotta be really thoughtful and humble about what it is that we do. So for me, what I'm most excited about is, you know, one of our leadership principles is about, you know, with what broad responsibility brings, you know, you've got to impact sustainability and many of those other things. And for me, I think it's about waking up every day for our customers, for our partners, and for the younger generations. And being better, doing better, and making better for this planet and for, you know, the future generations to come. So >>I think your tag line just start applies to all of that. It does. It has been an absolute pleasure. And then really an honor to talk to you on the program. Thank you all for joining me, sharing your experiences, sharing what you've accomplished, your recommendations for those others who might be our same generation or older or younger. All really beautiful advice. Thank you so much for your time and your insights. We appreciate it. >>Thank you. Thank you. >>For my guests, I'm Lisa Martin. You're watching The Cube, the leader in live enterprise and emerging tech coverage. Thanks for watching.

Published Date : Nov 30 2022

SUMMARY :

It is so great to have you guys on this power panel. Talk to us a little bit about that and then we'll go around the table. So we are doing a ton of work on edge analytics in the That's outstanding to hear because it's one of those things that you can't be what you can't see. the business outcomes that we can deliver with our customers and Jimmy, talk to us a little bit about you, your role at Goldman Sachs. And I get to be leading the digital platform What are some of the recommendations that you would have for other And I think it's about pursuing Rachel, you're shaking your head. So, you know, interesting enough, I actually started my career as a And you know, fuel your passion, be curious, What would you say to And when I broke that to my father, you know, the standard Indian Give me, let's pivot on confidence for a minute, Jim, and let's go back to how would you advise your And I think it's about celebrating your wins. Do you agree, Rachel? don't know how to do that. And here's the other thing I would tell my younger self is there and Zacks that got you to this table right now. And if you don't have one, be a sponsor for someone else. some of the women leaders have said, build, and this is kind of like, sort of what you were saying, build your own personal board Yeah. Sponsors are the people that stick up for you when you're not in the room I love that you said that. You know, folks that have diverse ideas, you know, ISV, And so we tend to start creating these circles of kind of like, you know, think tanks and they think alike And when you think about that, that What you wanted to do, but how have you navigated that? but be the change you want to see. And I think that I've Jimmy will stick with you as you head into the new year. And I think both internally and We need to be sustainable, we need to be responsible. What are you most excited about going into 2023? this planet and for, you know, the future generations to come. And then really an honor to talk to you on the program. Thank you. and emerging tech coverage.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
AWSORGANIZATION

0.99+

Lisa MartinPERSON

0.99+

JuliePERSON

0.99+

RachelPERSON

0.99+

Tara KaporPERSON

0.99+

TerryPERSON

0.99+

Rachel MuPERSON

0.99+

WalmartORGANIZATION

0.99+

Goldman SachsORGANIZATION

0.99+

JimmyPERSON

0.99+

JimPERSON

0.99+

TurnerPERSON

0.99+

Molly WardPERSON

0.99+

NTTORGANIZATION

0.99+

Entity DataORGANIZATION

0.99+

Rachel MuirPERSON

0.99+

Las VegasLOCATION

0.99+

NTT DataORGANIZATION

0.99+

Oprah WinfreyPERSON

0.99+

Jimmy BarnesPERSON

0.99+

Charu KapurPERSON

0.99+

todayDATE

0.99+

2023DATE

0.99+

millionsQUANTITY

0.99+

two yearsQUANTITY

0.99+

first jobQUANTITY

0.99+

two piecesQUANTITY

0.99+

LinkedInORGANIZATION

0.99+

two wordsQUANTITY

0.99+

The CubeTITLE

0.99+

Rachel MushahwarPERSON

0.99+

over 200 servicesQUANTITY

0.99+

Nore HansonPERSON

0.99+

two thingsQUANTITY

0.99+

20 plus yearsQUANTITY

0.99+

third timeQUANTITY

0.99+

EntityORGANIZATION

0.99+

threeQUANTITY

0.99+

three guestsQUANTITY

0.99+

firstQUANTITY

0.99+

oneQUANTITY

0.99+

OneQUANTITY

0.99+

fourQUANTITY

0.98+

secondQUANTITY

0.98+

sixQUANTITY

0.98+

three months backDATE

0.98+

TouroPERSON

0.98+

bothQUANTITY

0.98+

two areasQUANTITY

0.97+

North AmericaLOCATION

0.97+

about 22 billionQUANTITY

0.97+

LatifaPERSON

0.97+

under two yearsQUANTITY

0.96+

this yearDATE

0.95+

Eric Clark, NTT | Upgrade 2020 The NTT Research Summit


 

>>from around the globe. It's the Cube covering upgrade 2020 The NTT Research Summit presented by NTT Research. >>Hi, I'm stupid, man. And this is the Cubes coverage of Upgrade 2020 the global research Summit for NTT and always happy when we get to talk about digital transformation. Happy to welcome to the program First time guests on the program. Eric Clark. He is the chief digital officer with NTT Data. Thanks so much for joining us. Thank >>you. Glad to be here. >>All right, so let's start, you know, CDOs. First of all, there there's lots of studios. We've done lots of events with the chief data officers, which I'm sure we'll talk a little bit about data. But the digital officers, of course, digital so important in general. And even more so in 2020. But let's understand your role is as chief digital officer. What's your charter where you sit in York? What you're responsible for? >>Yeah, definitely. And you know, it's a good question. I often start conversations with our customers by talking about exactly that, because Chief Digital officer means something different toe different companies. So for us, it's primarily market facing. Onda What that means is I spend most of my time looking at research, looking at R and D, looking at what our competitors are doing in the market and looking at where trends. We're going to make sure that we have the right offerings and capabilities to bring to our customers to make sure that they will remain competitive in their markets. >>That's great. You know, We've been talking for years about the, you know, the digital transformations that companies have been going through. One of our definitions have been. If you're not at the end of it, more data driven, you probably haven't done the right thing. But Eric, this year with 2020 you know, anecdotally we talked to a lot of customers, and obviously there's certain initiatives that get frozen or, you know, uh, we'll take a little bit longer. But those digital initiatives, which are supposed to rely on data and help us move fast and be more agile, seem to be at the top of the list and are accelerating because if I can't respond to you know, the daily and weekly changes that have been great in 2020 you know, I might have a tough time surviving. So what are you seeing? You know, how does that live in your world? >>Yeah, you're exactly right. And that's what we're seeing from our client base as well. So early on in the pandemic, there was a lot of freeze, you know, hold everything. Stop. Stop spending. And let's figure out where we are and where this is going. But very quickly that turn to we've got to react. We're gonna be living with this for a while and we can't. We can't afford to sit back and wait and see where it goes. We've got to react, and we've got to direct our our future. And very often the way that comes out is with digital. So you know, customers are looking for opportunities to leverage digital, to grow revenue, to improve customer engagement and to drive more of their revenue through digital channels. >>Interested in one thing I didn't here and there, but I'm sure is part of it. What about the employees themselves? One of the big things, of course, is that we've made this wonderful corporate environment. You've got the great great Internet there, and now wait. Everybody's at home and scrambling as to what they do. So so how about the kind of the the e x to go along with the C X? Yeah, >>exactly. And that was actually one of the first places that we focused as a company, because we do a lot of you know what we refer to as workplace services. So making sure that our customers employees have the tools they need to do their job successfully. Eso immediately. When when officers started closing and people started going home, our big challenge was Let's make sure that our customers can connect from anywhere from wherever they need to be working from and have access to the applications and the tools and the products that they need to perform their jobs remotely. And that's really turned into a significant business of its own of, you know, really addressing those needs not only for our customers but also for our employee base. You know, we have 50,000 people that we sent home more than 90% of overnight, and you know, many of these are our employees that are interacting with our customer based on a daily basis, So we had to make sure not only that they had connective, >>but >>he had to be secure. So it was a very big switch. And I think I personally was really impressed. Not only with what we did, but what we saw. The industry. Dutilleux make that transition very safely and seamlessly. >>Well, let's Eric, I love you to expand a little bit on that. You know which pieces of that that full solution, Uh, is NTT offering? And how do you and your partner's, uh, you know, help your customers through. You know, those rapid options that they need? >>Yeah, so So So we're a full suite provider. So we're focused on digital operations, which is, you know, digitizing your back office from your workplace services to your hybrid infrastructure network, etcetera, all the way through bringing. You know what? We refer to his journey to the cloud. So how do we help you identify what applications and what data you need in the cloud? Um uh, c X and E x. Very big focuses for us. In fact, we take a lot of pride in while we do go to market and sell c X specifically, we consider c x part of everything we do so if we're talking about workplace services or hybrid infrastructure or security. We want the employee experience to be solid, and we want the employee experience to be consistent across all of those things. So way think that our customers should not expect to have different interfaces and different portals and different user experiences when they do work with us across infrastructure and application and cloud etcetera. >>That's excellent, Eric. You know, we spent the last six months talking about how do we react to the pandemic? And now, at least, you know, here in the U. S. Uh, the Children are back in school. If they're back, though, it tends to be ah, hybrid model. And when we look at work, often we know we're gonna have this elongated kind of new abnormal, if you will. So, yes, you might be back in the office some, but chances are you will spend some time remote and therefore it's not work from home or back toe work. It's work from anywhere, is what I need to be able to do. So how are you preparing? How are you helping your customers through that? Because, you know, it's one thing if it was just, you know, a switch that says I'm either here or there, but it z changing and it's very fluid. >>Yeah, and you're exactly right. It is work from anywhere, but there are some of our customers that don't have the luxury of work from anywhere. So when you think about manufacturing facilities and different hospitality companies, um, there there are people that need to go into physical places. We do a lot in the healthcare space. We need doctors in the hospitals. So we've done a lot to help our customers figure out safe ways to return to the work. Recently, we've seen universities and, as you mentioned, you know, high schools and elementary schools all going back with varying degrees of success, right? Some of them have failed, and they've had to take a pause and and figure out how they're going to restart. We've also seen professional sports leagues and now college sports leagues. Andi, When we see them having issues, we see protocols adjusting and we see them looking for what can we do to make this safer, more effective and more successful for whether it's our sports team, our school or our business. So we've taken a very active approaching that, and we're leveraging technology and creating I P. That starts with pre arrival, you know, registering in advance and, you know, opting in for things like tracking social distancing and tracking the use of mask, then using cameras and facilities to monitor it, to make sure people that are are adhering to social distancing and adhering to wearing masks. Andi In the event that they aren't we can send instant notifications to their phone. If we have repeat violators, Weaken. Prohibit them from coming back to the office so we can have very strict controls and adherence to whatever the protocols. Maybe as the protocols change. And then the other thing that allows us to do is in the event someone would test positive with co vid, we will know exactly who they've been within 6 ft of without a mask over the past X number of days. All that is stored in the cloud for us to, you know, use for reference and use for audit purposes so that gives us the ability to then use are apt to direct all the people that the person that was positive was in contact with, let them go, get tested, come back with a negative test before they return to the office. So So, basically, what we've done is we've created all kinds of technology using automation and AI and facial recognition to bring MAWR safety and more security to the workplace. Whatever that work placement might be, whether again, school, university manufacturing facility or a hotel >>Really interesting topic. You know, tracking and tracing so critically important we've seen in many countries around the world. That's really help them get their arms around and control that. You know, we talked to the top of the interview about, you know, digital means leveraging the data. And if I don't have the data, I can't respond to what's happening there. Um, here in the US, I haven't heard as much about the tracking and tracing. Is this a company by company thing do they have is the expense all on them to do it? And of course, it raises the concerns about Well, I'm concerned about my privacy and that that balance between the public interest on my right to privacy, how do you help your customer sort through some of those issues >>Well, privacy is definitely a big issue. And, you know, you noticed that when I was explaining that I said in pre pre arrival, you opt in. So the way we've approached it is it is an opt in. So those that don't wanna opt into that kind of tracking and tracing, um won't won't be those that will be allowed to come back to the office. And that goes back to your other point of work from anywhere. Many of those people can still successfully work from anywhere but those that feel like they're more effective, more successful or have a need to be in an office or need to be physically again in a manufacturing facility or a hotel. We have a way to do that safely, >>right? Well, Eric, one of the things I love about research events like yours is a little peek in tow. What's coming on down the road? So any other things you'd like toe, you know, share about, You know, some of the things that are exciting. You some things we should be looking at a little bit further down the road. >>Well, I think you know for us, as you know, We spend a significant amount of money each year on research, and and we really get excited about thes thes opportunities in these showcases. So you'll see ah, lot of exciting information and a lot of what's coming in the future. Um, a lot of it right now, obviously, because of the times you'll see themes of safety and security. Um, but you're also going to see just ah, whole lot of really thought provoking forward thinking technology. >>Always take the opportunity. Even when there are crisis is out there. There's the opportunity for innovation and acceleration off. What's happening? Eric, Thanks so much pleasure talking with you and definitely looking forward to hearing more from from the event. >>Great. Thank you. Enjoyed it. >>Stay with us for more coverage from upgrade 2020 times to minimum. Thanks as always, for watching cute with

Published Date : Sep 29 2020

SUMMARY :

from around the globe. He is the chief digital officer Glad to be here. All right, so let's start, you know, CDOs. And you know, it's a good question. and are accelerating because if I can't respond to you know, the daily and weekly changes that there was a lot of freeze, you know, hold everything. So so how about the kind of the the e x to go along with the C X? and you know, many of these are our employees that are interacting with our customer based on a daily basis, he had to be secure. And how do you and your partner's, uh, you know, help your customers through. So how do we help you identify what applications And now, at least, you know, here in the U. S. Uh, the Children are back in school. I P. That starts with pre arrival, you know, registering in advance we talked to the top of the interview about, you know, digital means leveraging the data. And, you know, you noticed that when I was explaining you know, share about, You know, some of the things that are exciting. Well, I think you know for us, as you know, We spend a significant amount of money Eric, Thanks so much pleasure talking with you and definitely looking forward to hearing more from for watching cute with

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Eric ClarkPERSON

0.99+

EricPERSON

0.99+

USLOCATION

0.99+

2020DATE

0.99+

50,000 peopleQUANTITY

0.99+

YorkLOCATION

0.99+

NTT DataORGANIZATION

0.99+

NTTORGANIZATION

0.99+

more than 90%QUANTITY

0.99+

First timeQUANTITY

0.99+

oneQUANTITY

0.98+

NTT ResearchORGANIZATION

0.98+

CubesORGANIZATION

0.98+

OneQUANTITY

0.98+

6 ftQUANTITY

0.98+

U. S.LOCATION

0.97+

each yearQUANTITY

0.97+

C XTITLE

0.97+

one thingQUANTITY

0.97+

e xTITLE

0.97+

pandemicEVENT

0.96+

NTT Research SummitEVENT

0.96+

FirstQUANTITY

0.95+

MAWRORGANIZATION

0.95+

last six monthsDATE

0.93+

this yearDATE

0.86+

CubeORGANIZATION

0.82+

DutilleuxORGANIZATION

0.8+

first placesQUANTITY

0.78+

cTITLE

0.74+

AndiPERSON

0.69+

Upgrade 2020EVENT

0.68+

research SummitEVENT

0.45+

Kazuhiro Gomi & Yoshihisa Yamamoto | Upgrade 2020 The NTT Research Summit


 

>> Announcer: From around the globe, it's theCUBE. Covering the UPGRADE 2020, the NTT Research Summit. Presented by NTT research. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. Welcome back to our ongoing coverage of UPGRADE 2020. It's the NTT Research Labs Summit, and it's all about upgrading reality. Heavy duty basic research around a bunch of very smart topics. And we're really excited to have our next guest to kind of dive in. I promise you, it'll be the deepest conversation you have today, unless you watch a few more of these segments. So our first guest we're welcoming back Kazuhiro Gomi He's the president and CEO of NTT research, Kaza great to see you. >> Good to see you. And joining him is Yoshi Yamamoto. He is a fellow for NTT Research and also the director of the Physics and Informatics Lab. Yoshi, great to meet you as well. >> Nice to meet you. >> So I was teasing the crew earlier, Yoshi, when I was doing some background work on you and I pulled up your Wikipedia page and I was like, okay guys, read this thing and tell me what a, what Yoshi does. You that have been knee deep in quantum computing and all of the supporting things around quantum heavy duty kind of next gen computing. I wonder if you can kind of share a little bit, you know, your mission running this labs and really thinking so far in advance of what we, you know, kind of experience and what we work with today and this new kind of basic research. >> NTT started the research on quantum computing back in 1986 87. So it is already more than 30 years. So, the company invested in this field. We have accumulated a lot of sort of our ideas, knowledge, technology in this field. And probably, it is the right time to establish the connection, close connection to US academia. And in this way, we will jointly sort of advance our research capabilities towards the future. The goal is still, I think, a long way to go. But by collaborating with American universities, and students we can accelerate NTT effort in this area. >> So, you've been moving, you've been working on quantum for 30 years. I had no idea that that research has been going on for such a very long time. We hear about it in the news and we hear about it a place like IBM and iSensor has a neat little demo that they have in the new sales force period. What, what is, what makes quantum so exciting and the potential to work so hard for so long? And what is it going to eventually open up for us when we get it to commercial availability? >> The honest answer to that question is we don't know yet. Still, I think after 30 years I think of hard working on quantum Physics and Computing. Still we don't know clean applications are even, I think we feel that the current, all the current efforts, are not necessarily, I think, practical from the engineering viewpoint. So, it is still a long way to go. But the reason why NTT has been continuously working on the subject is basically the very, sort of bottom or fundamental side of the present day communication and the computing technology. There is always a quantum principle and it is very important for us to understand the quantum principles and quantum limit for communication and computing first of all. And if we are lucky, maybe we can make a breakthrough for the next generation communication and computing technology based on quantum principles. >> Right. >> But the second, is really I think just a guess, and hope, researcher's hope and nothing very solid yet. >> Right? Well, Kazu I want to go, go to you cause it really highlights the difference between, you know, kind of basic hardcore fundamental research versus building new applications or building new products or building new, you know, things that are going to be, you know, commercially viable and you can build an ROI and you can figure out what the customers are going to buy. It really reflects that this is very different. This is very, very basic with very, very long lead times and very difficult execution. So when, you know, for NTT to spend that money and invest that time and people for long, long periods of time with not necessarily a clean ROI at the end, that really, it's really an interesting statement in terms of this investment and thinking about something big like upgrading reality. >> Yeah, so that's what this, yeah, exactly that you talked about what the basic research is, and from NTT perspective, yeah, we feel like we, as Dr. Yamamoto, he just mentioned that we've been investing into 30 plus years of a time in this field and, you know, and we, well, I can talk about why this is important. And some of them is that, you know, that the current computer that everybody uses, we are certainly, well, there might be some more areas of improvement, but we will someday in, I don't know, four years, five years, 10 years down the road, there might be some big roadblock in terms of more capacity, more powers and stuff. We may run into some issues. So we need to be prepared for those kinds of things. So, yes we are in a way of fortunate that we are, we have a great team to, and a special and an expertise in this field. And, you know, we have, we can spend some resource towards that. So why not? We should just do that in preparation for that big, big wall so to speak. I guess we are expecting to kind of run into, five, 10 years down the road. So let's just looking into it, invest some resources into it. So that's where we are, we're here. And again, I I'm, from my perspective, we are very fortunate that we have all the resources that we can do. >> It's great. Right, as they give it to you. Dr. Yamamoto, I wonder if you can share what it's like in terms of the industry and academic working together. You look at the presentations that are happening here at the event. All the great academic institutions are very well represented, very deep papers. You at NTT, you spend some time at Stanford, talk about how it is working between this joint development with great academic institutions, as well as the great company. >> Traditionally in the United States, there has been always two complementary opportunities for training next generation scientists and engineers. One opportunity is junior faculty position or possible position in academia, where main emphasis is education. The other opportunity is junior researcher position in industrial lab where apparently the focus emphasis is research. And eventually we need two types of intellectual leaders from two different career paths. When they sort of work together, with a strong educational background and a strong research background, maybe we can make wonderful breakthrough I think. So it is very important to sort of connect between two institutions. However, in the recent past, particularly after Better Lab disappeared, basic research activity in industrial lab decreases substantially. And we hope MTT research can contribute to the building of fundamental science in industry side. And for that purpose cross collaboration with research Universities are very important. So the first task we have been working so far, is to build up this industry academia connection. >> Huge compliment NTT to continue to fund the basic research. Cause as you said, there's a lot of companies that were in it before and are not in it any more. And when you often read the history of, of, of computing and a lot of different things, you know, it goes back to a lot of times, some basic, some basic research. And just for everyone to know what we're talking about, I want to read a couple of, of sessions that you could attend and learn within Dr. Yamamoto space. So it's Coherent nonlinear dynamics combinatorial optimization. That's just one session. I love it. Physics successfully implements Lagrange multiplier optimization. I love it. Photonics accelerators for machine learning. I mean, it's so it's so interesting to read basic research titles because, you know, it's like a micro-focus of a subset. It's not quantum computing, it's all these little smaller pieces of the quantum computing stack. And then obviously very deep and rich. Deep dives into those, those topics. And so, again, Kazu, this is the first one that's going to run after the day, the first physics lab. But then you've got the crypto cryptography and information security lab, as well as the medical and health information lab. You started with physics and informatics. Is that the, is that the history? Is that the favorite child you can lead that day off on day two of the event. >> We did throw a straw and Dr. Yamamoto won it Just kidding (all laugh) >> (indistinct), right? It's always fair. >> But certainly this quantum, Well, all the topics certainly are focuses that the basic research, that's definitely a commonality. But I think the quantum physics is in a way kind of very symbolic to kind of show that the, what the basic research is. And many people has a many ideas associated with the term basic research. But I think that the quantum physics is certainly one of the strong candidates that many people may think of. So well, and I think this is definitely a good place to start for this session, from my perspective. >> Right. >> Well, and it almost feels like that's kind of the foundational even for the other sessions, right? So you talk about medical or you talk about cryptography in information, still at the end of the day, there's going to be compute happening to drive those processes. Whether it's looking at, at, at medical slides or trying to do diagnosis, or trying to run a bunch of analysis against huge data sets, which then goes back to, you know, ultimately algorithms and ultimately compute, and this opening up of this entirely different set of, of horsepower. But Dr. Yamamoto, I'm just curious, how did you get started down this path of, of this crazy 30 year journey on quantum computing. >> The first quantum algorithm was invented by David Deutsch back in 1985. These particular algorithm turned out later the complete failure, not useful at all. And he spent seven years, actually, to fix loophole and invented the first successful algorithm that was 1992. Even though the first algorithm was a complete failure, that paper actually created a lot of excitement among the young scientists at NTT Basic Research Lab, immediately after the paper appeared. And 1987 is actually, I think, one year later. So this paper appeared. And we, sort of agreed that maybe one of the interesting future direction is quantum information processing. And that's how it started. It's it's spontaneous sort of activity, I think among young scientists of late twenties and early thirties at the time. >> And what do you think Dr. Yamamoto that people should think about? If, if, if again, if we're at a, at a cocktail party, not with not with a bunch of, of people that, that intimately know the topic, how do you explain it to them? How, how should they think about this great opportunity around quantum that's kept you engaged for decades and decades and decades. >> The quantum is everywhere. Namely, I think this world I think is fundamentally based on and created from quantum substrate. At the very bottom of our, sort of world, consist of electrons and photons and atoms and those fundamental particles sort of behave according to quantum rule. And which is a very different from classical reality, namely the world where we are living every day. The relevant question which is also interesting is how our classical world or classical reality surfaces from the general or universal quantum substrate where our intuition never works. And that sort of a fundamental question actually opens the possibility I think by utilizing quantum principle or quantum classical sort of crossover principle, we can revolutionize the current limitation in communication and computation. That's basically the start point. We start from quantum substrate. Under classical world the surface is on top of quantum substrate exceptional case. And we build the, sort of communication and computing machine in these exceptional sort of world. But equally dig into quantum substrate, new opportunities is open for us. That's somewhat the fundamental question. >> That's great. >> Well, I'm not, yeah, we can't get too deep cause you'll lose me, you'll lose me long before, before you get to the bottom of the, of the story, but, you know, I really appreciate it. And of course back to you this is your guys' first event. It's a really bold statement, right? Upgrade reality. I just wonder if, when you look at the, at the registrant's and you look at the participation and what do you kind of anticipate, how much of the anticipation is, is kind of people in the business, you know, kind of celebrating and, and kind of catching up to the latest research and how much of it is going to be really inspirational for those next, you know, early 20 somethings who are looking to grab, you know, an exciting field to hitch their wagon to, and to come away after this, to say, wow, this is something that really hooked me and I want to get down and really kind of advance this technology a little bit, further advance this research a little bit further. >> So yeah, for, from my point of view for this event, I'm expecting, there are quite wide range of people. I'm, I'm hoping that are interested in to this event. Like you mentioned that those are the, you know, the business people who wants to know what NTT does, and then what, you know, the wider spectrum of NTT does. And then, and also, especially like today's events and onwards, very specific to each topic. And we go into very deep dive. And, and so to, to this session, especially in a lot of participants from the academia's world, for each, each subject, including students, and then some other, basically students and professors and teachers and all those people as well. So, so that's are my expectations. And then from that program arrangement perspective, that's always something in my mind that how do we address those different kind of segments of the people. And we all welcoming, by the way, for those people. So to me to, so yesterday was the general sessions where I'm kind of expecting more that the business, and then perhaps some other more and more general people who're just curious what NTT is doing. And so instead of going too much details, but just to give you the ideas that the what's that our vision is and also, you know, a little bit of fla flavor is a good word or not, but give you some ideas of what we are trying to do. And then the better from here for the next three days, obviously for the academic people, and then those who are the experts in each field, probably day one is not quite deep enough. Not quite addressing what they want to know. So day two, three, four are the days that designed for that kind of requirements and expectations. >> Right? And, and are most of the presentations built on academic research, that's been submitted to journals and other formal, you know, peer review and peer publication types of activities. So this is all very formal, very professional, and very, probably accessible to people that know where to find this information. >> Mmh. >> Yeah, it's great. >> Yeah. >> Well, I, I have learned a ton about NTT and a ton about this crazy basic research that you guys are doing, and a ton about the fact that I need to go back to school if I ever want to learn any of this stuff, because it's, it's a fascinating tale and it's it's great to know as we've seen these other basic research companies, not necessarily academic but companies kind of go away. We mentioned Xerox PARC and Bell Labs that you guys have really picked up that mantle. Not necessarily picked it up, you're already doing it yourselves. but really continuing to carry that mantle so that we can make these fundamental, basic building block breakthroughs to take us to the next generation. And as you say, upgrade the future. So again, congratulations. Thanks for sharing this story and good luck with all those presentations. >> Thank you very much. >> Thank you. >> Thank you. Alright, Yoshi, Kazu I'm Jeff, NTT UPGRADE 2020. We're going to upgrade the feature. Thanks for watching. See you next time. (soft music)

Published Date : Sep 29 2020

SUMMARY :

the NTT Research Summit. It's the NTT Research Labs Summit, and also the director of the and all of the supporting things And probably, it is the right time to establish the connection, and the potential to and the computing technology. But the second, is that are going to be, you that the current computer that are happening here at the event. So the first task we Is that the favorite child and Dr. Yamamoto won it It's always fair. that the basic research, that's for the other sessions, right? and invented the first successful that intimately know the topic, At the very bottom of our, sort of world, And of course back to you this and then what, you know, the And, and are most of that you guys have really See you next time.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Yoshi YamamotoPERSON

0.99+

YoshiPERSON

0.99+

Kazuhiro GomiPERSON

0.99+

Jeff FrickPERSON

0.99+

1985DATE

0.99+

YamamotoPERSON

0.99+

1992DATE

0.99+

David DeutschPERSON

0.99+

IBMORGANIZATION

0.99+

seven yearsQUANTITY

0.99+

NTTORGANIZATION

0.99+

NTT Basic Research LabORGANIZATION

0.99+

10 yearsQUANTITY

0.99+

Bell LabsORGANIZATION

0.99+

five yearsQUANTITY

0.99+

fiveQUANTITY

0.99+

1987DATE

0.99+

NTT ResearchORGANIZATION

0.99+

30 yearQUANTITY

0.99+

JeffPERSON

0.99+

first algorithmQUANTITY

0.99+

30 yearsQUANTITY

0.99+

two institutionsQUANTITY

0.99+

Yoshihisa YamamotoPERSON

0.99+

KazuPERSON

0.99+

one year laterDATE

0.99+

United StatesLOCATION

0.99+

yesterdayDATE

0.99+

more than 30 yearsQUANTITY

0.99+

one sessionQUANTITY

0.99+

four yearsQUANTITY

0.99+

Xerox PARCORGANIZATION

0.99+

two typesQUANTITY

0.99+

NTT researchORGANIZATION

0.99+

30 plus yearsQUANTITY

0.99+

first guestQUANTITY

0.98+

NTT Research SummitEVENT

0.98+

threeQUANTITY

0.98+

One opportunityQUANTITY

0.98+

first taskQUANTITY

0.98+

first eventQUANTITY

0.98+

first successful algorithmQUANTITY

0.98+

NTT Research Labs SummitEVENT

0.97+

secondQUANTITY

0.97+

each subjectQUANTITY

0.97+

iSensorORGANIZATION

0.97+

todayDATE

0.97+

Dr.PERSON

0.97+

fourQUANTITY

0.97+

30 yearsQUANTITY

0.96+

oneQUANTITY

0.96+

first oneQUANTITY

0.96+

late twentiesDATE

0.96+

Physics and Informatics LabORGANIZATION

0.96+

eachQUANTITY

0.96+

a tonQUANTITY

0.95+

each topicQUANTITY

0.95+

day twoQUANTITY

0.95+

2020DATE

0.93+

Better LabORGANIZATION

0.92+

each fieldQUANTITY

0.92+

first physics labQUANTITY

0.87+

USLOCATION

0.86+

1986 87DATE

0.86+

decades andQUANTITY

0.85+

first quantumQUANTITY

0.83+

UPGRADE 2020EVENT

0.79+

StanfordORGANIZATION

0.79+

two complementaryQUANTITY

0.79+

KazaPERSON

0.78+

Mary Edwards, NTT | Upgrade 2020 The NTT Research Summit


 

>> Narrator: From around the globe, it's theCUBE, covering the Upgrade 2020, the NTT research summit, presented by NTT research. >> Welcome back. I'm Stu Miniman, and this is theCUBEs, coverage of Upgrade 2020. Of course, it's NTT's Global Research Summit. Really excited, we're going to be able to dig into healthcare, the health system of course, something that's been, top of mind for everyone around the globe this year, so happy to welcome you to the program. First time guest Mary Edwards. She is the president of provider at NTT DATA Services. Mary, welcome to the program, saying thanks so much for joining us. >> Hi, Stu. Glad to be here. >> All right. So why don't we start, as I tee it up. We're going to be talking about health care there, just a little bit of your background, your group inside of NTT DATA Services. >> Sure. So I've been at NTT DATA Services for a year, just about a year on the knows. Really glad to be here. I've been healthcare, all of my career over 30 years. At first in the Blues, in underwriting actuarial and strategy, then hop to consulting. I was a partner with Accenture for 20, well, yeah, I think 22 years, I was at Accenture. and then, I was leading a commercial markets portion of a platform as a service company for a couple of years, and then NTT called and I was really impressed with what I learned about NTT and delighted to join the firm as the president of provider. >> Well, Mary, I've got a little bit of background in some of the health I love, I go to innovation conferences, and they're like, "We have the opportunity to really transform markets, but it's so tough to make change." Well, you've been there for a year, and the last year, there's been a force in function to change the advent of telehealth and telemedicine. I've done plenty of interviews, and heck, me and my family have been to doctors, using those services, which, at the beginning of this year, I wouldn't have thought was possible. Some of these might be long term changes in impact on what's happening, but bring us inside, your customers, what are some of the pressing challenges they're facing? And it's been a little bit this, there obviously, are huge challenges, but there's also been an opportunity to make some rapid changes. >> Great question. Well, first of all, there's no place I'd rather be right now, than serving the health systems across the US, and certainly we have impact globally. It's dynamic time, lots of change, and as you say, with change comes opportunity. But also, it's a time of deep fragility, and a time when these clients really need help, not just from NTT, but from a variety of partners. And I know, I feel and my team feels, that it's a privilege to work in supporting them, through this very difficult time. And when I say difficult time, I mean, think about it, even before the pandemic, Chartists research was talking about the fact that likely 25% of rural hospitals would fail. Fast forward only a couple of months from that, research being published and across the industry, outpatient revenues are down 11% year over year, inpatient revenue down as well, labor expenses up by nearly 18%. And so there's a lot of pressures on the industry right now. And that's what I mean by just a very significant time to be in the industry and position to help. There's a huge recovery, that needs to happen from what our clients have experienced. First and foremost, top line. We've got to get the revenue back into the hospitals. The CARES Act funding doesn't last forever, and certainly, brings with it some obligations. So bringing in that top line growth, virtual health, which you mentioned, is a big part of that strategy. At the same time, they've got to deal with all the new delivery models or working models, work from anywhere is something that all businesses have to face, and incredibly, an incredible challenge for our health systems. Because of course, it's not just about how we do our individual work, but the interactions that they have to have in conducting the work that they do. So care from anywhere and work from anywhere, are huge concerns of our health system clients now. And you have to do that in industrialized ways, because you don't know where you're working day to day, you have to be able to have fast switching, right? Because we're not in control of where we work. Cities and states are telling us, what we have to do on a day in day out basis. There's a huge concept - >> Human. >> Oh, go ahead. Sure. >> Yeah, no, I just say, as you say, obviously, healthcare is rightly so a heavily regulated industry. So bring us inside a little bit, what are some of those opportunities, some of those innovations that providers are being able to take advantage? And have we opened the gates a little bit to help things move a little bit faster here in 2020, due to necessity? >> Yeah. Well, virtual care, you mentioned that earlier, has exploded. There's a lot of dialogue right now in the industry about whether that's forever. It will never go back to the low single digits that it was prior to the pandemic. I mean, prior to the pandemic health systems were happy if they could get to 10%. Overnight, virtual care went to 40%, 50%, increase overnight, and just continue to grow. CEOs across the industry prior to the pandemic, were really focused on digital front door strategies, the ability to enable consumers to enter the healthcare system, digitally and virtually. And so probably for the 18 months before the pandemic, most large system CEOs that I talked to, were working on those strategies. They're doubling down on those strategies, because the industry is reshaping around that digital future state. The cost pressures that we're seeing in health care, at the same time, require that they think about new operating and delivery models, certainly the industry will restructure, based on what we've gone through and continue to experience. And that will mean certainly changes in consolidation in the healthcare industry, right? As certainly certain systems will fail, right. Can't support what's happening around the economics of the industry. But also within our delivery and operations, there will be and we're already seeing a trend toward more pervasive outsourcing, moving offshore, taking particularly back office functions, whether it's IT or business processes, and looking for the help that can drive down the cost structure, better automate, and innovate on those processes and delivery models, and accelerate their journey to the digital future state of health. >> So Mary, help us understand NTT DATA Services, and NTT broader, what are the solutions? How are you helping your customers with everything we've discussed here? >> Sure, well, you can't enable those digital front door strategies unless you do things like get your applications to the cloud. You've got to be able to open up your environment to trade, if I say it that way, right? To exchange more broadly, even within your own ecosystem, within your own walls, the ability to connect doctors with doctors that before the pandemic didn't have a need to connect in the same way becomes important. So at NTT, we do everything, journey to the cloud. Certainly the security that's so important to those journey and also the digital future of health care. RPA, the introduction of bots and AI to workflows and operations in order to reduce cost. In my division in provider, we worked for nearly the last year on something we call, nucleus for healthcare, which is that digital front door enabled by digital foundation and which delivers through pre-selected capabilities scheduling, through virtual care visits to care coordination and payment, all integrated across the digital fabric, in order to accelerate the industry and certainly our health system partners achievement of that digital front door vision and the full digital future for healthcare. >> I love you talked about RPA automation, has been one of the top things we've been hearing this year. It's just a top sea level priority. We love coming to events like this, a lot of discussion of research looking a little bit forward down the road. What are some of the items here at Upgrade 2020, you want to make sure our audience get a little peek into? >> Yeah, well, you talk about automation, and I said a moment ago about offshore, we're thinking about no shore, right? So when you think about the application of automation and advanced analytics AI into business processes, it's not about moving business processes to a lower cost geography, it's about automating, and enabling through bots and whatnot, the ability to not have hands touch it, and really conserving your resources for the more complex things that have to happen. So I love that concept of no shoring, and really using technology to position humans for their best possible work, solving the harder problems that we face as an industry. I think about innovations in patient monitoring, and what we can take in terms of IoT, from other industries. And for instance, at NTT, we've been doing smart city with the city of Las Vegas, for a couple of years now. And we've got lots of AI around movement, heat, light, the physical context of things. You think about how you move that into healthcare. And it's certainly about patient observation, and creating safe spaces, where doctors and nurses don't have to travel in and out of rooms when there's a high contagion rate, but it's also about using AI, not just to watch the room, but to allow AI to alert when there's something very significant happening, what kind of movement in the bed, what does that infer in terms of what's happening in the patient's room, and alerting on that basis versus a visual monitor, if you will. There are other innovations. Oh, go ahead, Stu. >> Oh, no, so sorry, I thought you had said, please finish. >> Well, I was just about to say there are other innovations that we're working on, that are really about patient well being, patient companion. I think about the work we're doing at NTT disruption around something called Jibo, which is a robotics, very cool little guy who we've had some experience using it in our children's hospitals, right. It becomes like a really a companion of sorts. There are lots of applications for that kind of technology, especially in a pandemic time, when most of our patients are isolated and craving some human interaction and these capabilities can be like that, they can be companions, and they can provide the social interaction that really lead to health and well being. >> Well, so many important topics. Mary, thank you so much for joining us. Great to hear your automation, robotics in the people, at the center, of course, of what we look at in healthcare. Great to talk to you. Thanks so much for joining us. >> Thank you. Bye bye. >> Stay tuned for more coverage from Upgrade 2020. I'm Stu Miniman, thank you for watching theCUBE. (upbeat music)

Published Date : Sep 29 2020

SUMMARY :

the globe, it's theCUBE, so happy to welcome you to the program. We're going to be talking At first in the Blues, "We have the opportunity to and position to help. Oh, go ahead. able to take advantage? the ability to enable consumers the ability to connect a little bit forward down the road. the ability to not have hands touch it, you had said, please finish. that really lead to health and well being. Great to hear your automation, Thank you. you for watching theCUBE.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
NTTORGANIZATION

0.99+

AccentureORGANIZATION

0.99+

MaryPERSON

0.99+

Mary EdwardsPERSON

0.99+

NTT DATA ServicesORGANIZATION

0.99+

StuPERSON

0.99+

40%QUANTITY

0.99+

Las VegasLOCATION

0.99+

Stu MinimanPERSON

0.99+

2020DATE

0.99+

10%QUANTITY

0.99+

22 yearsQUANTITY

0.99+

NTT DATA ServicesORGANIZATION

0.99+

25%QUANTITY

0.99+

50%QUANTITY

0.99+

11%QUANTITY

0.99+

pandemicEVENT

0.99+

USLOCATION

0.99+

last yearDATE

0.99+

20QUANTITY

0.99+

FirstQUANTITY

0.99+

CARES ActTITLE

0.99+

this yearDATE

0.98+

over 30 yearsQUANTITY

0.98+

a yearQUANTITY

0.97+

nearly 18%QUANTITY

0.97+

ChartistsORGANIZATION

0.97+

oneQUANTITY

0.96+

NTT Research SummitEVENT

0.94+

Upgrade 2020EVENT

0.94+

NTTEVENT

0.94+

First timeQUANTITY

0.94+

Global Research SummitEVENT

0.93+

NTT researchEVENT

0.91+

pandemic timeEVENT

0.81+

about a yearQUANTITY

0.81+

JiboORGANIZATION

0.8+

beginningDATE

0.68+

18 monthsQUANTITY

0.64+

of yearsQUANTITY

0.63+

NTTLOCATION

0.63+

firstQUANTITY

0.6+

monthsQUANTITY

0.57+

singleQUANTITY

0.52+

coupleQUANTITY

0.49+

2020OTHER

0.44+

yearsQUANTITY

0.36+

Alex Bennett, NTT | Upgrade 2020 The NTT Research Summit


 

>> Narrator: From around the globe, It's theCUBE! Covering the Upgrade 2020, the NTT Research Summit presented by NTT Research. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. Welcome back to our ongoing coverage of Upgrade 2020. It's the NTT Research Summit covering a lot of really deep topics around a lot of the basic core research that NTT is sponsoring. Kind of like the old days of Mobell or some of the other kind of core research. And we're excited to have our next guest to go. A little bit beyond the core research and actually talk about working with people today. So we'd like to welcome in Alex Bennett. He is the global senior vice president of the intelligent workplace for NTT. Alex, good morning? >> Good morning, Jeff. How are you doing. >> Terrific. So I think for a lot of people, you know, probably know the NTT name, certainly in the States, but are not familiar with, I think, you know, the degree of which you guys have this huge business around services and workplace collaboration, I wonder if you can give us kind of a high level summary of the services angle at NTT, you know, beyond just putting in communications infrastructure equipment. >> Yeah, definitely. I mean, the NTT, as you said, is it's a huge organization, Very well known in Japan and growing in last year that we brought together about 32 different brands under the entity limited brand and we have NTT data services as well. So our role is really to look at the client requirements, the business needs that they have and be able to provide end to end solutions and wrap them with our services to make sure they've got, you know, efficiency gains, but also improving employee experience and experience around, you know, improving how they connect to their customers as well. >> Right, right. So obviously COVID-19, what was, you know, kind of a light switch moment back in March has now turned into, you know, kind of an ongoing, a new normal here we are six months plus into this, into this thing, really no end in sight in the immediate term. So, you know, people were thrown into the situation where work from home, work from anywhere had to happen with no prep. You've been in the business for a long time working on solutions. So there's the obvious things like security and access, but what are some of the less obvious things that people should be thinking about when they think about supporting their employees that are not now coming into the office? >> Well, I mean, it's been interesting, right. I said I have been in the sector for a long time and a lot of the themes have been the same for the last 10, 15 years, you know, how do we improve employee experience? How do we start to look at things like wellbeing? You know, how does it have an impact on productivity? And how do you make sure that we make it simple for people to carry out their tasks? Now, something I get asked a lot is this idea of how do we make it frictionless? A lot of the time, people don't really care about the brand or the technology. They just want to be able to carry out their role from whatever industry sector they aren't doing it efficiently and do it well, but also to be able to interact. I think it's been really important. And this pandemic has brought about this view, that people haven't been able to socialize in the same way they have in the past and work is really about people, you know, the workplace is also about people and how you connect those people into customers and provide efficiencies in that area. So the conversations I've been having in the last, you know, six to seven months, it's been quite interesting that the programs they were taking 18 months, 24 months, 36 months over, have had to be accelerated and really deployed in about three months. And then that's brought about the lows of operation on policy concerns. So as you mentioned, as you start to have this new, what we're calling, you know, distributed workforce, especially those organizations which have been perhaps more enterprise specific, you know, which are going into carpeted office environments, they've been requested by governments to only work from home. And that's brought about a huge impact to how people work, but also socialize. So from a technology standpoint, you've asked people, right, you're going to work from home, actually, do you have network connectivity? Can you actually connect with a technology tool? Like, you know, collaboration to be able to speak to your customers, to speak to your GOPs. Now what device are you actually working on? So we saw this real drive around what is this sort of immediate business continuity requirement for a secure remote worker. >> Right. And that brought about other concerns as well. >> Right. So there's so many layers to this conversation. I'm psyched to dig into it. But one of the ones I want to dig in is kind of tools overload, you know, this idea of collaboration and, you know, trying to get your work done and trying to get bears removed. At the same time though, it just can't seems like we just keep getting more tools added to the palette that we have to interact with every day, whether it's lack or a sauna or Salesforce or box, or you know, the list goes on and on and on. And the other thing that just seems strange to me is that right, all of these things have a notification component. So it's almost like the noise is increasing. I don't hear a lot of people ripping out old tooling or ripping out old systems. So how do you help guide people to say, that there's all these great collaboration tools, there's all these great communication tools, but you can't have all of them firing all the time and expect people to actually have time to get work done. >> Yeah. And it's also, you know, some people are used to that, you might have a digital native who's used to using multiple tools, but you don't have others that actually haven't been taught or a learning program about how to use different tools for different applications. And that becomes that person becomes frustrated and their productivity levels can go down. I think that what we'd really try and do is understand what are the business requirements by the persona? And also if you think of that distributed worker, that's now having to work from home and go into the office for specific tasks that are allowed, are they a sales person? No. Are they actually working in HR? What do they need and what are the tasks they need? And that start to provide the right types of tools and technology specifically for them and make sure they have a learning path that's driven around how they actually enable that technology. But you're right though. I think one of the thing that COVID founder's that doesn't happen overnight, you know, that's an engagement process. COVID hit and everyone was at home straight away. So we did see this huge transition from what may have been a legacy on premise application to starting to use more cloud based applications. And almost everyone was thrown in at the deep pant. Right? Well, here you go, just get on and use it. And at the same time they had WeChat or they had no other types of applications like WhatsApp and there were all these channels were happening. And they always had an impact on things like compliance and security, because all of a sudden, you're not using a corporately approved platform and solution. And you're starting to talk about perhaps confidential information. That's not in a way that is actually retained inside of a corporate network for the compliance and regulatory components. Right. So it's been a really interesting time in the last few months. >> Right. Well, so let's just touch on security for a minute. 'Cause obviously security is a huge concern. As you said, there's a whole bunch of security. You get kind of new security issues. One is just, everybody's working from home, whether they've got to VPN or not, or they're on their... You know, whatever their cable provider. You don't know what devices they're on, right? There's so many different devices and too as these apps have proliferated all over all these devices, whether access Salesforce on my phone or on my laptop or on my computer at work. Right. All very different. So when you look at the kind of security challenge that has come from distributed workforce with this super acceleration, you know, how many customers are ready for it, it's just caused a complete, you know, kind of fire, a hair on fire reaction to get up to speed, or, you know, are a lot of the systems of the monitored system relatively well locked down. So it wasn't a giant, you know, kind of adjustment back in March. >> Really. It depends on the type of company culture it was before. You know, what we've actually seen from some research we've done very recently across 1500 different companies, those organizations that have really invested become more digital disruptors. Now that they've embedded an idea of agility, they've actually already got a distributed workforce. They've already started to move a lot of their platforms and applications to the cloud. They've started to think about these IT policies and security. Previously, they've been very successful in how they've been able to pivot and drive this business continuity. I think for others that have been, no have large installed base of employees, no have set policies in place it's been harder for them to transition. And what we've seen is that they're the organizations that have really tried to integrate some of the new technologies into the old and that that's quite difficult sometimes. So, you know, around security, out of those 1500 organizations, nearly 70% of them said that they have a higher level of risk and concern about this. You're already in compliance today than they had prior to the pandemic. >> Right. >> What also is brought about is this idea of moving from a sort of perimeter security now where you'd come into an office and you have this perimeter where the network's secure, the physical location, and security, containerize the applications. And you've got to empower employees more now because you know, people are going to be mobile. They're going to be using multiple devices in different locations, all around the world. So we're seeing this transition as people move to cloud based platform, security is starting to get embedded into the application and it goes back to that persona aspect. So you can start to initiate things like you know, data loss protection and rights management about the content an individual has based on their location or the confidentiality of that document or piece of information. So that's where we're seeing this move is sort of really accelerating to the group, take the stress away from the employee embedded into an actual system and an application. And that has the intelligence to work out the security and the compliance on behalf of the individual. >> Right. You know, where I was going to go is, you know, there's a lot of conversations now about certain companies announcing that people can just work from home for the foreseeable future, especially here in Silicon Valley. And you mentioned that, you know, for some people that were already kind of down at digital transformation path, they're in good shape. Other people, you know, weren't that far, and of course all the means on social media are, you know, what drove your digital transformation, the CEO, the CMO, or COVID. And we all know the answer to the question. So I just want to get, you know, kind of a longterm perspective. You've been in this space for a long time. I think there's going to be, you know, a significantly increased percentage of people that are working from home. A significantly increased percentage of the time, if not a hundred percent of the time. How do you see this kind of, you know, extending out and how will it impact the way that people motivate? 'Cause at the end of the day, you've written a ton of blog posts on this, you know, motivation equals profitability. And a motivated engaged people do better work and do get better results on the bottom line. How do you see this as this as (indistinct) rules for six months, 12 months, 24 months, when there's some mishmash of combination of work from home and work from the office? >> I think probably the first thing to say is that from the research we've done, we think that's going to differ by different geographies. I mean, it's interesting when you look at areas like India and perhaps South Africa where the network connectivity home is actually not as good as in Northern Europe or North America, and actually it becomes quite hard to carry out your role and task at home. And it can become really frustrating. There's also sort of health and safety components to also working at home. Now we've had a lot of people, especially the younger generation who are in shared home, shared facilities. Now who's going to pay for the internet, the bundles, you know, and actually you only have your bedroom and is it healthy to work at your bedroom all day? So when you really sort of peel back the layers of this, this is a really complex environment, and it's also dependent on the industry sector you are. You're actually driving. But at a high level, one thing we're really seeing is most people still want to have a level of human interaction. That we as humans like to like to work together and engage together. And in fact, about 80% of the respondents of our report actually said, they want to come back to the office. Now this, this speaks to this idea of choice and flexibility. 'Cause it's not just about coming back for five days a week, eight to five, it's about going actually I've got a task to carry out. It'd be really helpful if I was with my team face to face. >> Right. >> And I can come in for four hours, book my time in that physical space, carry that out, and then I can go home and do that sort of really the research based work which I can do in the safety of my own environment. So that's what we're seeing across the industry whereas before. Now, I think everyone's trying to build these really nice big offices that looked fantastic, more huge and talked about your brand. Most organizations now are repurposing space 'cause they're not going to have as many people inside of those physical locations, but they're motivating for them to come in for creative work, you know, to be social, to think about how they do cross agile team development. >> Jeff: Right. >> And that's what we're starting to see today. >> Yeah. It's really interesting you think of some young engineer that just graduated from school, gets a job at Google and you know, you get all your food there and they'll do your dry cleaning and they'll change the oil in your car and they'll, you know, take care of everything. And, and so there's this little growth in these little micro houses. Well guess what, now you don't have any of that stuff anymore. The micro house with no kitchen or kitchen that does look so attractive. And I want to shift gears a little bit more detail on NTT. You know, we've talked to lots of people about new ways to work. IBM, Citrix, you know, VM-ware has a solution and you work with big company. So how does NTT fit in, you know, kind of a transformation process big and that on the big scale, but more kind of an employee engagement and a work from anywhere type of engagement. How do you guys fit within, you know, big system integrators, like a center that are driving organizational change and, you know, kind of all this other suite of technology that they might already have in place. >> Yeah. I mean, we sort of sit in that role of a service delivery organization as well as systems integrator. So our role is to actually go into those clients and sit down with them, which is now virtually, rather than in person a lot of the time. And really understand what are those business KPIs they have and help them shape that strategy. And to do that, you've got to understand what they have today, that view of the assets. And that goes across multiple components as you said, from, you know, desktop application, security, inclusive of culture, property assets, network. And what we do is really take a holistic view of those areas that go for you to reach that business goal, that KPI, you know, this is the project that you're going to have to do. And anything around employee engagement ultimately is fed also by how good your network is and how secure that network is to deliver those applications efficiently for that employee to carry out their task in that frictionless way. So we have a very holistic view about how we then deliver Upgrade. That the core infrastructure, we do that secure by design is our sort of policy and everything we do, you know, security is embedded into what we do, and then we deliver that outcome. But then we erupt things like adoption services. I think one thing in the past, you know, people say here's a technology, go on and do it. Especially nowadays, you've got quite complex platforms. You've got to really understand how do you give information to people to self serve them, that sort of nudge technology, so they can understand how to carry it out on that idea of adoption training. Change of management is becoming ever increasingly important for our clients. >> Right. So I wan shift gears again, Alex, and talk about the show Upgrade 2020. Lot of (laughs) a lot of really heavy science going on here in healthcare, in IT, in a whole bunch of areas. Pretty exciting stuff, you know, we've talked to some other guests about some of the real details and I'm definitely going to attend some sessions and have my brain exploded I'm sure. But I'm just curious of how it fits with what your doing, you know, you've been involved, as you said, not necessarily the NTT, but you've been involved in kind of workplace collaboration tools for a long, long time. You know, how do you see, you know, kind of basic research and some of this really fundamental research, you know, kind of helping you and your customers and your solutions, you know, as we kind of moved down the road. >> Alright, hold at that. The main conversation we're having with executives today is this idea of employee wellbeing and experience is fundamental to the success of their business. 'Cause it drives customer centricity productivity gains. You've got to think about how technology can underpin that and deliver insights to you. So, you know, the new currency is data. And what I find really interesting around and what we're talking about with Upgrade 2020 is this ideas of digital twins. So when you think of this concept of a digital twin, it all is based on this idea of extensibility. So all your decisions that you're making right to today, you know, these short term decisions you having to do for business continuity, you've got to think about the longterm impact of how you're going to be able to ingest that data from all those systems into a central area, to give you insight. Now, from that insight, you've then got the, you know, the power of machine learning and artificial intelligence to actually say right, for this component how many of my employees really are? Then well, are they doing well in the productivity gains? And from my property estate, you know, how many of my properties are actually reducing the energy consumption? And are we adhering to our sustainability goals? Are they well? So the actual physical environment is safe for those employees. So all of those disparate platforms have to come together into that one area and give you insight. So that the marrying of physical space with the how humans interact all into a digital twin, I think is really interesting and something I'm speaking to clients about day in, day out. >> I love that, that is awesome. You know, we're first exposed to the digital twin concept years ago, doing some work with general electric, because they were doing a lot of digital twin work around, you know, engines on airplanes and, you know, simulate an airplane engine that's running on a plane in the Middle East, it's going to act very different than a plane that's running in Alaska. And then, you know, I love the concept of digital twin around the context of people in medicine, right. And modeling a heart or modeling a behavior system or cardiovascular system. How are you talking about digital twins? 'Cause it sounds like you're talking about kind of a combination between, you know, kind of individual people and how they're doing versus some group of people as a unit or organization. And then you even mentioned, you know, sustainability goals and buildings. So when you're talking about digital twin in this context, what are the boundaries? How are you organizing that thing that you can then do, you know, kind of tests and kind of predictive exercises to see how the real thing is going to do relative to what the digital twin did. >> Yeah. But it goes back to defining those business outcomes. And most of the discussions we're having is, yeah, obviously increased productivity, but it's also a reducing costs. A big one we've seen in my area is attraction retention of talent. You know, intellectual property is going to differentiate organizations in the future as technology sort of standardizes. But sustainability again from the research we've done is really high up on the executives agenda. You know, the idea that we, as NTT as well, we have a duty to society to actually start giving back a view of how technology can improve the sustainability goal. And in fact, we've just become the business Avenger for the UN sustainability goal, number 11, around the idea of communities and smart cities. So the clients that I'm speaking to when they're looking at those business objectives are no 10, 15% of my, my actual costs associated to my property. We've now got a new distributed workforce, but I've got a huge amount of energy going into those properties. Now we can actually connect now building management systems into now that digital twin. We can also start to look at the other platforms such as lifts, you know, also all the heating and air ventilation. And start to get the data that allows us to model and predict when certain issues may occur. So, you know, as less people start coming in, you'll have occupancy data. You'll be able to say, you're actually, this location has only been used 30% capacity. We could reduce the amount of space we have, or in fact, we don't need that space at all. And in that space, we know that we're running an HVAC system and air conditioning a hundred percent of the time. You start to actually reduce that and you can reduce energy consumption by 30%. Now goes back to this whole idea of extensibility on one building that can have a big impact, but across 500 buildings that we're NTT have, that's a significant amount of energy that we can change. >> Jeff: Right. >> And also you can then start to think about the idea of, you know, more different type of power purchasing agreement with sustainable energy going into those environments. >> So many, you know, kind of so many interesting twists and turns on this journey since, you know, that COVID hit. And it is going to be really fascinating to see kind of what sticks and, you know, and the longterm ramifications. 'Cause we're not going back to the way that it was. I think that's not even a question. Just the last thing on kind of the data, you know, we saw some really, I think not such great things early on in this thing where, you know, you get put us basically a sniffer on and you know, our people sitting in front of their computer all day. I saw some nasty thing on Twitter the other day. My boss wants me to be on Zoom calls all day long. I mean, do people get it that, you know, there's an opportunity to increase motivation, not decrease motivation by, you know, a responsible use and a good use of this data versus, you know, a potential perception of, well now they're just big brothering me to death. >> It's such a hot topic, right? I mean, even before COVID we had, you know, the GDPR compliance in Europe. But that ultimately is a global compliance and the West coast America also got a similar one now about what data you're actually keeping about me as an individual. And I should have access to that and I can not speak to my company about it. And is it big brother or actually using that data to help inform me as an individual ways of improving the way I work or working in a way that has a better balance for me as an individual. And we're having these conversations with our clients right now about how we do this, because they having to work with workers counselors in countries like Germany. Because track and trace does have that view of that sort of big brother. What, where are you? What are you doing? And how long have you been on your computer? I think it's down to the culture of your business and the purpose that you have and how you engage with your employees, that you show that data to be about all benefiting them as an individual. Now, I'm going back to that digital twin, that the view of ingesting data, then from perhaps platforms like, you know, Cisco WebEx or Office 365, and you can see how long they are actually in front of their screen. You can then start to predict and see where you may have burnout or in fact affect change where you say RHR policy should dictate, you shouldn't be working 14 hours a day. That's not good for you. It's not good for us. And actually nudge them and teach them about taking no time away from the desk and actually having a better work balance. And that's important because it all goes back to increases the productivity longterm, but it's great brand association and it's good for attraction and retention of talent. >> Right, Right. Well, I think the retention and attraction is a huge thing. You keep talking about productivity and obviously in your blog post talking about engagement, right. And engagement is such a direct tie to that. And then at the bottom line (giggles) it's kind of like diversity of opinion. It actually makes good business sense. And you actually put more money in the bank at the end of the day, when you do some of these more progressive, you know, kind of approaches to how you manage the people. 'Cause they're not machines, they're people. >> Yeah. And you should allow them to make decisions. You know, that again, distributed working, you've got to think of how to empower them with the tools that gives them the choice to make decisions. And you know, that that decision making is more democratized inside of organizations that are successful. But if you don't have the technology that allows them to do that, it goes back to a hierarchical decision making. And that takes time, it's slower to market, and then you know, you're not as successful as your competition. So we're really trying to prove that this idea of thinking about people first using the data that backs it up you know, with empirical data to show the benefits, is the way forward for organizations today. >> Yeah. Alex, great conversation. Certainly nothing but opportunity (laughs) I had for you and what you do in this really fast evolving and transformative space, which is so important. Which is how do people work? How do they feel good? How are they engaged? How are they productive and really contribute? And at the end of the day, it is good business. So exciting times, good luck on the show and some of this crazy research coming out of it on the digital twin, and we look forward to continuing to watch the story unfold. >> Thank you very much, Jeff. >> Alright. He's Alex. I'm Jeff. You're watching Upgrade 2020. The continuous coverage from theCUBE. Thanks for watching. We'll see you next time.

Published Date : Sep 29 2020

SUMMARY :

Narrator: From around the globe, around a lot of the basic core research How are you doing. a lot of people, you know, I mean, the NTT, as you said, So obviously COVID-19, what was, you know, in the last, you know, And that brought about or you know, the list that doesn't happen overnight, you know, So it wasn't a giant, you know, So, you know, around security, And that has the intelligence I think there's going to be, you know, the bundles, you know, you know, to be social, to starting to see today. and they'll, you know, I think one thing in the past, you know, kind of helping you and your And from my property estate, you know, kind of a combination between, you know, So the clients that I'm speaking to you know, more different type to see kind of what sticks and, you know, and the purpose that you have to how you manage the people. and then you know, and what you do We'll see you next time.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Alex BennettPERSON

0.99+

JeffPERSON

0.99+

JapanLOCATION

0.99+

AlaskaLOCATION

0.99+

Jeff FrickPERSON

0.99+

NTTORGANIZATION

0.99+

AlexPERSON

0.99+

IndiaLOCATION

0.99+

South AfricaLOCATION

0.99+

EuropeLOCATION

0.99+

IBMORGANIZATION

0.99+

six monthsQUANTITY

0.99+

GermanyLOCATION

0.99+

MarchDATE

0.99+

12 monthsQUANTITY

0.99+

sixQUANTITY

0.99+

36 monthsQUANTITY

0.99+

24 monthsQUANTITY

0.99+

Silicon ValleyLOCATION

0.99+

eightQUANTITY

0.99+

North AmericaLOCATION

0.99+

GoogleORGANIZATION

0.99+

COVID-19OTHER

0.99+

30%QUANTITY

0.99+

four hoursQUANTITY

0.99+

18 monthsQUANTITY

0.99+

last yearDATE

0.99+

500 buildingsQUANTITY

0.99+

1500 organizationsQUANTITY

0.99+

Middle EastLOCATION

0.99+

CitrixORGANIZATION

0.99+

CiscoORGANIZATION

0.99+

1500 different companiesQUANTITY

0.99+

NTT ResearchORGANIZATION

0.99+

fiveQUANTITY

0.99+

Northern EuropeLOCATION

0.99+

WeChatTITLE

0.99+

seven monthsQUANTITY

0.99+

NTT Research SummitEVENT

0.99+

first thingQUANTITY

0.98+

about 80%QUANTITY

0.98+

hundred percentQUANTITY

0.97+

14 hours a dayQUANTITY

0.97+

about three monthsQUANTITY

0.96+

oneQUANTITY

0.96+

todayDATE

0.96+

pandemicEVENT

0.95+

Upgrade 2020EVENT

0.95+

GDPRTITLE

0.94+

nearly 70%QUANTITY

0.94+

Upgrade 2020TITLE

0.93+

firstQUANTITY

0.93+

Office 365TITLE

0.93+

OneQUANTITY

0.91+

five days a weekQUANTITY

0.91+

10, 15%QUANTITY

0.9+

a minuteQUANTITY

0.89+

SalesforceTITLE

0.88+

one areaQUANTITY

0.85+

yearsDATE

0.84+

UNORGANIZATION

0.84+

twinQUANTITY

0.83+

WhatsAppTITLE

0.83+

COVIDOTHER

0.8+

about 32 different brandsQUANTITY

0.8+

COVIDTITLE

0.77+

Simon Walsh, NTT | Upgrade 2020 The NTT-Research Summit


 

>>from around the globe. It's the Cube covering upgrade twenty twenty, The NTT Research Summit presented by NTT Research. >>Welcome back. I'm stupid a man. And this is the Cubes coverage of Upgrade twenty twenty. Of course, it's the NTT Research Summit and happy to welcome to the program someone that watch the Cube for a long time. But first time on the program. Simon Walsh. He is the new CEO of NTT America's Simon. Great to see you and thanks so much for joining us. >>Thanks very much. Too good to be here. All right. See, >>A Zai mentioned your your previous companies that you've worked for are ones that the Cube and Cube audience are well aware of. Matter of fact, when I worked for some of those companies, NTT is one of the large global companies that I had the pleasure to interact with over the years. But if you could maybe let's start with just a little bit of your background. And as I said, it's only been a few months that you've been the CEO, so you know, what's it like coming into a role like this? You know, during the situation that we're all faced with in twenty twenty. >>Yeah, Thank you. I mean, my background is really in, You know, the platforms that enable the customers Thio run their technologies. Andi, Uh, you know, I spent some of my time in Europe and the media on then latterly the last five plus years in the Americas. I have to say I really enjoy It's a much better environment. If I think about it from a GDP and an economy perspective, it's, ah really dynamic place to work. I worked with companies headquartered from Europe running America's, and I've worked with companies that were headquartered in the Americas, running some of the European businesses. So I've crossed the continent's if you like. I recently joined NTT. I have to say, you know, it was a pretty lengthy process to explore, but that was partly, you know, interviews and due diligence because you want to make sure that, you know, you're you're buying into a company that, you know, number one, you can have ah, cultural compatibility with, but also somebody who you see really investing in technology that consult for, you know, the business agenda of the markets. So that's really a bit about my background and then, you know, joining. I mean, I literally joined last week of June, so my whole time has bean through, locked down in terms of employment. It's been very unique. Taking on a new post, exclusively remote. Andi I was a bit worried, you know, at a human level, just, you know, how do you connect with people? What I would comment is I've actually had the ability to really meet ah, lot more people in person because you can physically get to people's schedules a lot easier. So that's certainly helped, you know. And I've done my, uh, activities of meeting clients. Eso they've been very amenable to connecting talking to our business partners and spending, you know, considerable amount of time with my colleagues, uh, in the Americas and around the world. Andi, it's actually been very rewarding. I think, funnily enough, you probably physically closer because you're on a screen and you probably like twenty four inches away from each other. Whereas in a meeting room you'd be the other side of the table. So it's been unique, but so far so good. >>Well, yeah, absolutely. The the new abnormal is we. We have sometimes say what? We're all usedto looking in the screens all day talking to various people there. Uh, the impact on business, though, has been, uh, you know, obviously ah, lot of different things, depending on the company. But that discussion of digital transformation a few years ago it was like, Oh, I don't know if it's really is it a buzzword? But that the spotlight that's been shown here in twenty twenty is what Israel and what is not leveraging cloud services, giving people agility, being able to react fast because, boy in twenty twenty if we needed to react fast, so help bring us inside a little bit. And your time there, the discussion you're having with customers, that adoption moving along that journey for digital transformation, the impact that you're seeing and house NTT helping its customers as they need to accelerate and respond toe the realities that we see today. >>Yeah, so you're right into I mean, digital disruption has been ongoing for multiple years. Way used to call it technology and change, and now we call it digital disruption or digital transformation. So it's not necessarily new. I think the thing that's really accelerated in twenty twenty, You know, as a consequence of the pandemic is really the word distributed, uh, in that customers are undertaking their digital transformations understanding. You know what it is to modernize processes, you know, modernize the customer experience on Then they're finding that actually, they don't need in a board room and discuss, you know, the performance of the business so they now need to have distributed access to data on. I think the topics that we see very prevalent is the distributed nature off the workforce. Andi. Obviously there's always been a filled workforce, and we've had systems, crm systems and other systems that were built for a distributed workforce. But now we have toe think about our supply chain management systems and our HR systems, the P and L. And you know all of the activities that business undertakes with an entirely distributed workforce, and it's quite abnormal. And I think what we've learned is where is the data on how doe I amalgamate data from distributed systems. And so I see. And we're doing a lot of work with our clients relating to digital transformation, but really about how doe I join data from system a two system F in a distributed manner, most importantly, securely timely on in A in an interface that is usable on it sounds really easy is like Oh, great, yeah, it's just two different data points. Connect them together, make it secure, make it visible, create transparency. But we all know that the world is full of technical debt, legacy systems and platforms Very expensive and significant historical investments on those things Don't modernize themselves overnight. Quite often. The dollars to modernize them don't justify themselves. So we then end up layering on, you know, new technology. So you know what I'm seeing on in digital transformation is really about. How do we handle distributed data Distributed decision making on how we do that in a secure manner on through an interface that is, uh, user friendly? >>Yeah, way. Obviously know that there's had to be some prioritization. You know, the joke. I've had everybody came into twenty twenty with Okay, here. Here's what I'm gonna do for the first half of the year. Here's the objectives that I have, and we kind of throw those in the shredder rather early on Number one priority. I still hear it was probably that the number one priority coming into the year and it stays there, and you've mentioned it multiple times. Its security, you know, is absolutely front and center Still. How overall, though, How are your customers? You know, the c X So sweet. How are they adjusting their priorities? Are there certain projects that just go on hold? Are there certain ones that get front and center? Obviously, you know, that distributed work from anywhere. Telemedicine, uh, you know, teach and learn from anywhere have been top of mind. But any other key learnings you're finding or prioritization changes, some of which are gonna probably stay with us. Uh, you know, for the long term, >>Absolutely. We've definitely seems Thio customers re prioritizing. And I think there is obviously an inevitability to this, a za consequence of the pandemic. I mean, if you were undertaking a campus upgrade, you might just put that on pause for the moment. And we've absolutely seen that. But what we've really seen is a prioritization has been How do we get our information to our users? Whether the user is a customer or whether the user is an employee, you know, there's examples where there's lots of companies who are saying they've got, like, online detail, right. But now they've got to do curbside pickup because they've actually got inventory in the stores. But the stores couldn't open. So what you've seen is a re prioritization to say, Well, when we look out inventory management and the supply chain systems, are we factoring in that the inventory we have in a store could also be seen as inventory across the stores? And in fact, what we've really got now is a distributed warehouse. We've got inventory in the warehouse like wholesale, ready for distribution on. Then we've got inventory in a store retail ready for consumer consumption. What? We don't want that to be separate Infantry. We want that to be holistic on. Then how do we enable any any consumer anywhere to be able to arrange for curbside pickup, which we didn't used to do because we would come into the store or arrange for mail order? But the inventory may come from, you know, I may send something from San Francisco to somebody in Boston because it was in a storied inventory in San Francisco. Now, sure, it's got it's got some freight cost, but I've also got some other efficiency savings, and I'm reducing my working capital in my inventory expense. So we've seen prioritization for really how to take advantage of this. I come back to it. This word distributed is very simple in principle, but everything is now working on a new dynamic. So that's some of the prioritization we've seen. >>Um, you mentioned one of the things that might get put on hold is wait. If I was doing a corporate network update, that might not be the first thing. You know, we we Absolutely. We've gotten some great data on just the changing traffic patterns of the Internet, but the network is so critically important, everybody from home is, you know, dealing with Children doing their zoom classrooms while we're trying to dio video meetings. Um, NTT obviously has a strong, uh, you know, network component to what? Its businesses help us understand the services that are important there. What? What? You're working with customers. And how has this kind of transformed, uh, some of those activities? >>Yeah, Yeah, sure. Thank you. You're so right. I mean, I have to say I just like thio, pay my respects to colleagues and fellow workers around the world who are not just working from home but also home schooling in parallel. Uh, kids are fled the nest, you know, they're working for themselves now, so we don't have the extra activity of home schooling. But I can really have a lot of respect her colleagues who are trying to do both. It's a real fine art on. We've seen a lot of actually just talking of re prioritization. We've seen a lot of companies, including ourselves. You know, say to our colleagues, Look after your Children home, school them do everything you can to support your families on, then get to your work So that re prioritization. Justin behavior has been a key change that we've seen a lot of people do that flexibility to. You know, work is something you do not somewhere you go on. Therefore, as long as the work is done, we can flex around. You know your needs is a family, so that's one prioritization we've seen at, actually. But to your point on the network, it is quite amusing to me that we've been for years now talking about cloud on demand subscription services on Actually, the one asset that you need to really enable cloud is the network and its historically been the least cloudlike that you could possibly imagine Because you still need to specify a physical connection. You still need to specify a band with value you still need to specify. You know, the number of devices you get too attached to it. I think this is really a monstrous change that we're going to experience and really are experiencing the network as a service. I mean, we talk about I as has SAS. But what happened toe now, as I mean really, did we just think that everything was about computing software? The network is the underpin er on DSO. Really? We see a big change and this is where we've been very busy in the network as a service enabling customers tohave dynamic reallocation of resources on the network so that they can prioritize traffic, prioritize content, prioritize events, you know, a lot of customers are now doing activities such as hosting their own event, their own digital conference on. Do you want to prioritize what the user experience is when you host one of those events over perhaps a back office process that, quite frankly, wait a few days so we see a significant opportunity. This is where we've been very busy the last few months in really building out much more dynamic network of the service solutions. You know, the Cloud Network. And I think the whole software defined network agenda has materially accelerated. That's one major area on then. The other area has just been the phenomenal ship to I p voice on soft bone, actually almost the deletion of the phone in its entirety. Everybody using you know, teams or Skype or Google hangouts to really use as their collaboration mechanism on. Then you know, we're providing all the underlying transportation layer. But as I p voice, you know, that creates a much more integrated collaboration. Experience on git creates a cost saving because you're taking away classic voice services. >>Yeah, Simon Boy, I'm excited for that. I I remember when I got my first BlackBerry and they were trying to sell me some things. I'm like, Wait, this is an Internet endpoint. I can do all of these things there and of course you know it's taking taking it. The last dozen years. If If Ghana certain far, but and we always joke, it's like smartphones. We don't use them for phones anymore. We use them for all the messaging and all those services. So, uh, the the data and the network are so critically important, something I want to turn Thio, you know, upgrade twenty twenty. You know what? I'm excited about this. You know, we've talked about, you know, the major impacts of what's happened in twenty twenty, and we're looking at the here and now. But it's great in technology when we get to be able to look forward and look at some of the opportunities out there. So we'd love to hear from your standpoint, some of the areas. What's exciting? You what's exciting? That we can look forward to some of the areas and pockets of research that we see at the event. >>Yeah. Thank you. Strewn E. I think what I like about Aravind is the investment that we make to work with, You know, scientific community, academia, really invest in, you know, forward looking future proofing, how physics and different technologies might play a role in the future. And, you know, some of these investments and some of this research yields commercial products, and some of it doesn't. But it's still a very valuable opportunity for us to really look at you know where technology is going. I think the areas that particularly appealing to me on a personal level, just the whole thing of quantum computing. This is, uh, you know, I know we're already exploring the capabilities of quantum computing in, you know, some labs and Cem academia centers on really to understand, how can we take advantage of that? But I think if you then say and you take another area that we're exploring through the event Biosciences, if you then take the two together and you think Okay, how do we take quantum computing on? We take Biosciences on you think about health care, and then you think about the pandemic. You know? Are there things that we can do with simulations and technologies in the future that really would give us a greater comprehension and ability to accelerate understanding, understand, accelerate testing, and then really contribute to, you know, the health and welfare of society. Andi, I think that's really quite an exciting area for us. So that's a specific topic that I'm particularly interested in. I'm glad to see us doing a lot in that space quantum computing as well as you know, Biosciences. And I'd say, you know, one other area where I still think we're all trying to ascertain how it serves the business is really the area of Blockchain. I think this is, um, intriguing. I'm still mentally trying to master the subject. No amount of white papers has managed Thio overcome the topic of my brain yet, So I'm still working on it on. Then I think cryptography, I come back to the same subject security. I mean, we are dependent as citizens, businesses and nations on technology. Now, on our data is available how we secure it, How we make sure that it's encrypted is absolutely going to be critical. You see an increasing push nationally on globally to ensure that there is, you know, security of data on. I think the subject of cryptography and how we go forward with, you know, beyond one hundred and twenty eight bit is gonna be a very difficult and critical subjects. So these are the areas I'm very impressed with. >>Wonderful. Simon, I wanna give you the final word from update. Great. Twenty twenty. >>Yeah, thanks to you. Just thanks very much, Thio. Anybody that's attending what you'll find through various workshops. There's lots of insight from our strategic partners from research scientists from academia from ourselves. So thank you very much for participating. You know, we always value your feedback. So please tell us what we could do to improve the content to help you with your businesses. Onda, We look forward and hope that everybody stays safe. Thank you for connecting with us virtually >>well. Simon Walsh, Thank you so much. Great. Having a conversation and glad to have you in our cube alumni now, >>thank you very much to have a good day. >>Alright, Stay tuned. More coverage from upgrade twenty twenty. I'm still minimum. And thanks. As always, for watching the cube. Yeah,

Published Date : Sep 29 2020

SUMMARY :

It's the Cube covering upgrade Great to see you and thanks so much for joining us. Too good to be here. NTT is one of the large global companies that I had the pleasure to interact with over I have to say, you know, it was a pretty lengthy process to explore, Uh, the impact on business, though, has been, uh, you know, You know what it is to modernize processes, you know, modernize the customer Uh, you know, for the long term, But the inventory may come from, you know, I may send something from San a strong, uh, you know, network component to what? kids are fled the nest, you know, they're working for themselves now, so we don't have the You know, we've talked about, you know, the major impacts of what's happened in twenty twenty, I think the subject of cryptography and how we go forward with, you know, Twenty twenty. what we could do to improve the content to help you with your businesses. Having a conversation and glad to have you in our cube alumni now, And thanks.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Simon WalshPERSON

0.99+

EuropeLOCATION

0.99+

BostonLOCATION

0.99+

San FranciscoLOCATION

0.99+

AmericasLOCATION

0.99+

SimonPERSON

0.99+

San FranciscoLOCATION

0.99+

NTTORGANIZATION

0.99+

ThioPERSON

0.99+

twoQUANTITY

0.99+

AmericaLOCATION

0.99+

NTT ResearchORGANIZATION

0.99+

twenty four inchesQUANTITY

0.99+

Strewn E.PERSON

0.99+

SkypeORGANIZATION

0.99+

firstQUANTITY

0.99+

bothQUANTITY

0.99+

OndaPERSON

0.99+

todayDATE

0.98+

2020DATE

0.98+

first timeQUANTITY

0.98+

twenty twentyQUANTITY

0.97+

Simon BoyPERSON

0.97+

oneQUANTITY

0.97+

Twenty twentyQUANTITY

0.97+

JustinPERSON

0.96+

last week of JuneDATE

0.96+

two different data pointsQUANTITY

0.96+

GhanaLOCATION

0.96+

GoogleORGANIZATION

0.96+

first thingQUANTITY

0.95+

NTT-Research SummitEVENT

0.95+

BlackBerryORGANIZATION

0.94+

NTT Research SummitEVENT

0.94+

AndiPERSON

0.93+

pandemicEVENT

0.92+

CubesORGANIZATION

0.91+

NTT AmericaORGANIZATION

0.91+

two systemQUANTITY

0.89+

CubeCOMMERCIAL_ITEM

0.88+

one hundred and twenty eight bitQUANTITY

0.85+

last few monthsDATE

0.76+

one major areaQUANTITY

0.75+

AravindPERSON

0.74+

few years agoDATE

0.73+

one assetQUANTITY

0.72+

EuropeanOTHER

0.69+

first halfQUANTITY

0.69+

number oneQUANTITY

0.66+

last dozen yearsDATE

0.65+

yearsQUANTITY

0.63+

Number oneQUANTITY

0.63+

ThioORGANIZATION

0.62+

plus yearsQUANTITY

0.62+

ZaiPERSON

0.59+

last fiveDATE

0.57+

IsraelLOCATION

0.54+

Kazuhiro Gomi, NTT | Upgrade 2020 The NTT Research Summit


 

>> Narrator: From around the globe, it's theCUBE, covering the Upgrade 2020, the NTT Research Summit presented by NTT Research. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in Palo Alto studio for our ongoing coverage of the Upgrade 2020, it's the NTT Research conference. It's our first year covering the event, it's actually the first year for the event inaugural, a year for the events, we're really, really excited to get into this. It's basic research that drives a whole lot of innovation, and we're really excited to have our next guest. He is Kazuhiro Gomi, he is the President and CEO of NTT Research. Kazu, great to see you. >> Hi, good to see you. >> Yeah, so let's jump into it. So this event, like many events was originally scheduled I think for March at Berkeley, clearly COVID came along and you guys had to make some changes. I wonder if you can just share a little bit about your thinking in terms of having this event, getting this great information out, but having to do it in a digital way and kind of rethinking the conference strategy. >> Sure, yeah. So NTT Research, we started our operations about a year ago, July, 2019. and I always wanted to show the world that to give a update of what we have done in the areas of basic and fundamental research. So we plan to do that in March, as you mentioned, however, that the rest of it to some extent history, we needed to cancel the event and then decided to do this time of the year through virtual. Something we learned, however, not everything is bad, by doing this virtual we can certainly reach out to so many peoples around the globe at the same time. So we're taking, I think, trying to get the best out of it. >> Right, right, so you've got a terrific lineup. So let's jump into a little bit. So first thing just about NTT Research, we're all familiar, if you've been around for a little while about Bell Labs, we're fortunate to have Xerox PARC up the street here in Palo Alto, these are kind of famous institutions doing basic research. People probably aren't as familiar at least in the states around NTT basic research. But when you think about real bottom line basic research and how it contributes ultimately, it gets into products, and solutions, and health care, and all kinds of places. How should people think about basic research and its role in ultimately coming to market in products, and services, and all different things. But you're getting way down into the weeds into the really, really basic hardcore technology. >> Sure, yeah, so let me just from my perspective, define the basic research versus some other research and development. For us that the basic research means that we don't necessarily have any like a product roadmap or commercialization roadmap, we just want to look at the fundamental core technology of all things. And from the timescale perspective obviously, not that we're not looking at something new, thing, next year, next six months, that kind of thing. We are looking at five years or sometimes longer than that, potentially 10 years down the road. But you mentioned about the Bell Lab and Xerox PARC. Yeah, well, they used to be such organizations in the United States, however, well, arguably those days have kind of gone, but so that's what's going on in the United States. In Japan, NTT has have done quite a bit of basic research over the years. And so we wanted to, I think because that a lot of the cases that we can talk about the end of the Moore's laws and then the, we are kind of scary time for that. The energy consumptions on ITs We need to make some huge, big, fundamental change has to happen to sustain our long-term development of the ideas and basically for the sake of human beings. >> Right, right. >> So NTT sees that and also we've been doing quite a bit of basic research in Japan. So we recognize this is a time that the let's expand this activities and then by doing, as a part of doing so is open up the research lab in Silicon Valley, where certainly we can really work better, work easier to with that the global talents in this field. So that's how we started this endeavor, like I said, last year. And so far, it's a tremendous progress that we have made, so that's where we are. >> That's great, so just a little bit more specific. So you guys are broken down into three labs as I understand, you've got the Physics, the PHI, which is Physics and Informatics, the CIS lab Cryptography and Information Security, and the MEI lab Medical and Health Informatics, and the conference has really laid out along those same tracks, really day one is a whole lot of stuff, or excuse me, they do to run the Physics and Informatics day. The next day is really Cryptography and Information Security, and then the Medical and Health Informatics. So those are super interesting but very diverse kind of buckets of fundamental research. And you guys are attacking all three of those pillars. >> Yup, so day one, general session, is that we cover the whole, all the topics. And but just that whole general topics. I think some people, those who want to understand what NTT research is all about, joining day one will be a great day to be, to understand more holistic what we are doing. However, given the type of research topic that we are tackling, we need the deep dive conversations, very specific to each topic by the specialist and the experts in each field. Therefore we have a day two, three, and four for a specific topics that we're going to talk about. So that's a configuration of this conference. >> Right, right, and I love. I just have to read a few of the session breakout titles 'cause I think they're just amazing and I always love learning new vocabulary words. Coherent nonlinear dynamics and combinatorial optimization language multipliers, indistinguishability obfuscation from well-founded assumptions, fully deniable communications and computation. I mean, a brief history of the quasi-adaptive NIZKs, which I don't even know what that stands for. (Gomi laughing) Really some interesting topics. But the other thing that jumps out when you go through the sessions is the representation of universities and really the topflight university. So you've got people coming from MIT, CalTech, Stanford, Notre Dame, Michigan, the list goes on and on. Talk to us about the role of academic institutions and how NTT works in conjunction with academic institutions, and how at this basic research level kind of the commercial academic interests align and come together, and work together to really move this basic research down the road. >> Sure, so the working with academic, especially at the top-notch universities are crucial for us. Obviously, that's where the experts in each field of the basic research doing their super activities and we definitely need to get connected, and then we need to accelerate our activities and together with the entities researchers. So that has been kind of one of the number one priority for us to jumpstart and get some going. So as you mentioned, Jeff, that we have a lineup of professors and researchers from each top-notch universities joining to this event and talking at a generous, looking at different sessions. So I'm sure that those who are listening in to those sessions, you will learn well what's going on from the NTT's mind or NTT researchers mind to tackle each problem. But at the same time you will get to hear that top level researchers and professors in each field. So I believe this is going to be a kind of unique, certainly session that to understand what's it's like in a research field of quantum computing, encryptions, and then medical informatics of the world. >> Right. >> So that's, I am sure it's going to be a pretty great lineups. >> Oh, absolutely, a lot of information exchange. And I'm not going to ask you to pick your favorite child 'cause that would be unfair, but what I am going to do is I noticed too that you also write for the Forbes Technology Council members. So you're publishing on Forbes, and one of the articles that you publish relatively recently was about biological digital twins. And this is a topic that I'm really interested in. We used to do a lot of stuff with GE and there was always a lot of conversation about digital twins, for turbines, and motors, and kind of all this big, heavy industrial equipment so that you could get ahead of the curve in terms of anticipating maintenance and basically kind of run simulations of its lifetime. Need concept, now, and that's applied to people in biology, whether that's your heart or maybe it's a bigger system, your cardiovascular system, or the person as a whole. I mean, that just opens up so much interesting opportunities in terms of modeling people and being able to run simulations. If they do things different, I would presume, eat different, walk a little bit more, exercise a little bit more. And you wrote about it, I wonder if you could share kind of your excitement about the potential for digital twins in the medical space. >> Sure, so I think that the benefit is very clear for a lot of people, I would hope that the ones, basically, the computer system can simulate or emulate your own body, not just a generic human body, it's the body for Kazu Gomi at the age of whatever. (Jeff laughing) And so if you get that precise simulation of your body you can do a lot of things. Oh, you, meaning I think a medical professional can do a lot of thing. You can predict what's going to happen to my body in the next year, six months, whatever. Or if I'm feeling sick or whatever the reasons and then the doctor wants to prescribe a few different medicines, but you can really test it out a different kind of medicines, not to you, but to the twin, medical twin then obviously is safer to do some kind of specific medicines or whatever. So anyway, those are the kind of visions that we have. And I have to admit that there's a lot of things, technically we have to overcome, and it will take a lot of years to get there. But I think it's a pretty good goal to define, so we said we did it and I talked with a couple of different experts and I am definitely more convinced that this is a very nice goal to set. However, well, just talking about the goal, just talking about those kinds of futuristic thing, you may just end up with a science fiction. So we need to be more specific, so we have the very researchers are breaking down into different pieces, how to get there, again, it's going to be a pretty long journey, but we're starting from that, they're try to get the digital twin for the cardiovascular system, so basically the create your own heart. Again, the important part is that this model of my heart is very similar to your heart, Jeff, but it's not identical it is somehow different. >> Right, right. >> So we are looking on it and there are certainly some, we're not the only one thinking something like this, there are definitely like-minded researchers in the world. So we are gathered together with those folks and then come up with the exchanging the ideas and coming up with that, the plans, and ideas, that's where we are. But like you said, this is really a exciting goal and exciting project. >> Right, and I like the fact that you consistently in all the background material that I picked up preparing for this today, this focus on tech for good and tech for helping the human species do better down the road. In another topic, in other blog post, you talked about and specifically what are 15 amazing technologies contributing to the greater good and you highlighted cryptography. So there's a lot of interesting conversations around encryption and depending kind of commercialization of quantum computing and how that can break all the existing kind of encryption. And there's going to be this whole renaissance in cryptography, why did you pick that amongst the entire pallet of technologies you can pick from, what's special about cryptography for helping people in the future? >> Okay, so encryption, I think most of the people, just when you hear the study of the encryption, you may think what the goal of these researchers or researches, you may think that you want to make your encryption more robust and more difficult to break. That you can probably imagine that's the type of research that we are doing. >> Jeff: Right. >> And yes, yes, we are doing that, but that's not the only direction that we are working on. Our researchers are working on different kinds of encryptions and basically encryptions controls that you can just reveal, say part of the data being encrypted, or depending upon that kind of attribute of whoever has the key, the information being revealed are slightly different. Those kinds of encryption, well, it's kind of hard to explain verbally, but functional encryption they call is becoming a reality. And I believe those inherit data itself has that protection mechanism, and also controlling who has access to the information is one of the keys to address the current status. Current status, what I mean by that is, that they're more connected world we are going to have, and more information are created through IOT and all that kind of stuff, more sensors out there, I think. So it is great on the one side that we can do a lot of things, but at the same time there's a tons of concerns from the perspective of privacy, and securities, and stuff, and then how to make those things happen together while addressing the concern and the leverage or the benefit you can create super complex accessing systems. But those things, I hate to say that there are some inherently bringing in some vulnerabilities and break at some point, which we don't want to see. >> Right. >> So I think having those securities and privacy mechanism in that the file itself is I think that one of the key to address those issues, again, get the benefit of that they're connected in this, and then while maintaining the privacy and security for the future. >> Right. >> So and then that's, in the end will be the better for everyone and a better society. So I couldn't pick other (Gomi and Jeff laughing) technology but I felt like this is easier for me to explain to a lot of people. So that's mainly the reasons that I went back launching. >> Well, you keep publishing, so I'm sure you'll work your way through most of the technologies over a period of time, but it's really good to hear there's a lot of talk about security not enough about privacy. There's usually the regs and the compliance laws lag, what's kind of happening in the marketplace. So it's good to hear that's really a piece of the conversation because without the privacy the other stuff is not as attractive. And we're seeing all types of issues that are coming up and the regs are catching up. So privacy is a super important piece. But the other thing that is so neat is to be exposed not being an academic, not being in this basic research every day, but have the opportunity to really hear at this level of detail, the amount of work that's being done by big brain smart people to move these basic technologies along, we deal often in kind of higher level applications versus the stuff that's really going on under the cover. So really a great opportunity to learn more and hear from, and probably understand some, understand not all about some of these great, kind of baseline technologies, really good stuff. >> Yup. >> Yeah, so thank-you for inviting us for the first one. And we'll be excited to sit in on some sessions and I'm going to learn. What's that one phrase that I got to learn? The N-I-K-Z-T. NIZKs. (laughs) >> NIZKs. (laughs) >> Yeah, NIZKs, the brief history of quasi-adaptive NI. >> Oh, all right, yeah, yeah. (Gomi and Jeff laughing) >> All right, Kazuhiro, I give you the final word- >> You will find out, yeah. >> You've been working on this thing for over a year, I'm sure you're excited to finally kind of let it out to the world, I wonder if you have any final thoughts you want to share before we send people back off to their sessions. >> Well, let's see, I'm sure if you're watching this video, you are almost there for that actual summit. It's about to start and so hope you enjoy the summit and in a physical, well, I mentioned about the benefit of this virtual, we can reach out to many people, but obviously there's also a flip side of the coin as well. With a physical, we can get more spontaneous conversations and more in-depth discussion, certainly we can do it, perhaps not today. It's more difficult to do it, but yeah, I encourage you to, I think I encouraged my researchers NTT side as well to basic communicate with all of you potentially and hopefully then to have more in-depth, meaningful conversations just starting from here. So just feel comfortable, perhaps just feel comfortable to reach out to me and then all the other NTT folks. And then now, also that the researchers from other organizations, I'm sure they're looking for this type of interactions moving forward as well, yeah. >> Terrific, well, thank-you for that open invitation and you heard it everybody, reach out, and touch base, and communicate, and engage. And it's not quite the same as being physical in the halls, but that you can talk to a whole lot more people. So Kazu, again, thanks for inviting us. Congratulations on the event and really glad to be here covering it. >> Yeah, thank-you very much, Jeff, appreciate it. >> All right, thank-you. He's Kazu, I'm Jeff, we are at the Upgrade 2020, the NTT Research Summit. Thanks for watching, we'll see you next time. (upbeat music)

Published Date : Sep 29 2020

SUMMARY :

the NTT Research Summit of the Upgrade 2020, it's and you guys had to make some changes. and then decided to do this time and health care, and all kinds of places. of the cases that we can talk that the let's expand this and the MEI lab Medical and the experts in each field. and really the topflight university. But at the same time you will get to hear it's going to be a pretty great lineups. and one of the articles that so basically the create your own heart. researchers in the world. Right, and I like the fact and more difficult to break. is one of the keys to and security for the future. So that's mainly the reasons but have the opportunity to really hear and I'm going to learn. NIZKs. Yeah, NIZKs, the brief (Gomi and Jeff laughing) it out to the world, and hopefully then to have more in-depth, and really glad to be here covering it. Yeah, thank-you very the NTT Research Summit.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
JeffPERSON

0.99+

Kazuhiro GomiPERSON

0.99+

CalTechORGANIZATION

0.99+

NTTORGANIZATION

0.99+

Jeff FrickPERSON

0.99+

JapanLOCATION

0.99+

KazuPERSON

0.99+

Silicon ValleyLOCATION

0.99+

MarchDATE

0.99+

Palo AltoLOCATION

0.99+

threeQUANTITY

0.99+

five yearsQUANTITY

0.99+

Bell LabORGANIZATION

0.99+

GomiPERSON

0.99+

Bell LabsORGANIZATION

0.99+

Kazu GomiPERSON

0.99+

fourQUANTITY

0.99+

KazuhiroPERSON

0.99+

United StatesLOCATION

0.99+

next yearDATE

0.99+

MoorePERSON

0.99+

10 yearsQUANTITY

0.99+

NTT ResearchORGANIZATION

0.99+

GEORGANIZATION

0.99+

BerkeleyLOCATION

0.99+

Forbes Technology CouncilORGANIZATION

0.99+

last yearDATE

0.99+

Xerox PARCORGANIZATION

0.99+

StanfordORGANIZATION

0.99+

NTT Research SummitEVENT

0.99+

15 amazing technologiesQUANTITY

0.99+

July, 2019DATE

0.99+

MITORGANIZATION

0.98+

each topicQUANTITY

0.98+

NTT ResearchEVENT

0.98+

Upgrade 2020EVENT

0.98+

oneQUANTITY

0.98+

first yearQUANTITY

0.97+

each fieldQUANTITY

0.97+

todayDATE

0.97+

three labsQUANTITY

0.96+

each problemQUANTITY

0.96+

MichiganLOCATION

0.96+

next six monthsDATE

0.95+

Notre DameORGANIZATION

0.95+

first oneQUANTITY

0.95+

a year agoDATE

0.94+

one sideQUANTITY

0.91+

one phraseQUANTITY

0.9+

over a yearQUANTITY

0.9+

a yearQUANTITY

0.9+

Physics and InformaticsEVENT

0.89+

twinQUANTITY

0.87+

first thingQUANTITY

0.86+

each top-QUANTITY

0.86+

day oneQUANTITY

0.84+

CISORGANIZATION

0.83+

sixQUANTITY

0.82+

Medical and Health InformaticsORGANIZATION

0.8+

one ofQUANTITY

0.72+

ForbesORGANIZATION

0.71+

Simon Walsh, NTT | Upgrade 2020 The NTT-Research Summit


 

>> From around the globe, its theCUBE, covering the UPGRADE 2020, the NTT Research Summit presented by NTT research. >> Welcome back. I'm Stu Miniman and this is theCUBE's coverage of UPGRADE 2020. Of course, it's the NTT Research Summit and happy to welcome to the program, someone that's watched theCUBE for a long time, but first time on the program, Simon Walsh, he is the new CEO of NTT Americas. Simon, great to see you, and thanks so much for joining us. >> Thanks very much Stu, good to be here, nice to see you. >> As I mentioned, your previous companies that you've worked for are that theCUBE and theCUBE audience are well aware of. As a matter of fact, when I worked for some of those companies, NTT is one of the large global companies that I had the pleasure to interact with over the years. But if you could, maybe, let's start with just a bit of your background. And as I said, it's only been a few months that you've been the CEO. So, what's it like coming into a role like this, during the the situation that we're all faced with in 2020? >> Yeah. Thank you. My background is really in the platforms that enable the customers to run their technologies. And, I've spent some of my time in Europe and India and then lastly the last five plus years in the Americas, I have to say, I really enjoy it. It's a much better environment. And if I think about it from a GDP and an economy perspective, it's a really dynamic place to work. I've worked with companies, headquartered from Europe, running in Americas. And I've worked with companies that were headquartered in the Americas, running some of the European businesses. So, I've crossed the continents if you like. And I recently joined NTT and I have to say, it was a pretty lengthy process to explore, but that was partly, interviews and due diligence. Cause you want to make sure that, you're buying into a company that, number one, you can have a cultural compatibility with, but also somebody who you see really investing in technology that consult for the business agenda of the markets. So, that's really a bit about my background and then joining. I mean, I literally joined the last week of June, so, my whole time has been through lockdown in terms of employment. It's been very unique taking on a new post, exclusively remote, and I was a bit worried, at a human level, just, how do you connect with people? But what I would comment is I've actually had the ability to really meet a lot more people in person cause you can physically get to people's schedules a lot easier. So, that's certainly helped. And I've done my activities of meeting up clients. So, they've been very amenable to connecting, talking to our business partners and spending considerable amount of time with my colleagues in the Americas and around the world. And it's actually been very rewarding. I think, funnily enough, you probably physically closer because you're on a screen, and you're probably like 24 inches away from each other. Whereas in a meeting room you'd be the other side of a table. So, it's been unique, but so far so good. >> Oh yeah, absolutely. The new abnormal, as we've sometimes say we're all used to looking in the screens all day, talking to various people there. The impact on business though has been, obviously a lot of different things depending on the company, but that discussion of digital transformation a few years ago, it was like, "Oh, I don't know if it's real, is it a buzz word?" But that the spotlight that's been shown here in 2020 is what is real and what is not? Leveraging cloud services, giving people agility, being able to react fast because buoyant 2020th, we needed to react fast. So, help bring us inside a bit, and your time there, the discussions you're having with customers that adoption, moving along that journey for digital transformation, the impact that you're seeing and how's NTT helping its customers as they need to accelerate and respond to the realities that we see today. >> Yeah. So you're right Stu. I mean, digital disruption has been on varying for multiple years and we used to call it, technology and change and now we call it digital disruption or digital transformation. So, it's not necessarily new. I think the thing that's really accelerated in 2020, as a consequence of the pandemic is really the word distributed in that customers are undertaking their digital transformations, understanding what it is to modernize processes, modernize the customer experience. And then they're finding that actually they don't meet in a boardroom and discuss, the performance of the business. So, they now need to have distributed access to data. And I think that the topics that we see very prevalent is the distributed nature of the workforce. And obviously there's always been a field workforce and we've had systems. CRM systems and other systems that were built for a distributed workforce. But now we have to think about how supply chain management systems and our HR systems, the PNL, and, all of the activities that our business undertakes with an entirely distributed workforce. And it's quite abnormal. What I think what we've learned is where is the data and how do I amalgamate data from distributed systems? And so I see, we're doing a lot of work with our clients relating to digital transformation, but really about how do I join data from system A to System F in a distributed manner? And most importantly, securely, timely and in an interface that is usable. And it sounds really easy. It's like, Oh great. Yeah, it's just two different data points, connect them together, make it secure, make it visible, create transparency. But we all know that the world is full of technical debt, legacy systems and platforms, very expensive and significant historical investments. And those things don't modernize themselves overnight. And quite often the dollars to modernize them don't justify themselves. So, we then end up layering on new technology. So, what I'm seeing in digital transformation is really about how do we handle distributed data, distributed decision making, and how do we do that in a secure manner and through an interface that is user friendly. >> Yeah, we obviously know that there's had to be some prioritization. The joke I've had, everybody came into 2020 with, "Okay, here's what I'm going to do for the first half of the year. Here's the objectives that I have." And we kind of throw those in the shredder rather early on. Number one priority I still hear it was probably that the number one priority coming into the year and it stays there and you've mentioned it multiple times, it's security, it is absolutely front and center still. How overall though, how are your customers, the CXO suite, how are they adjusting their priorities? Are there certain projects that just go on hold? Are there certain ones that get front and center, obviously, you know, that distributed work from anywhere telemedicine, teach and learn from anywhere, have been top of mind. But any other key learnings you're finding or prioritization changes, some of which are going to probably stay with us, for the longterm. >> Absolutely. We've definitely seen customers reprioritizing. And I think there is obviously an inevitability to this as a consequence of the pandemic. I mean, if you were undertaking a campus upgrade, you might just put that on pause for the moment. And we've absolutely seen that. But what we've really seen as a prioritization has been, how do we get our information to our users, whether the user is a customer or whether the user is an employee? There's examples where there's lots of companies who say they've got like online e-tail, right? But now they've got to do curbside pickup because they've actually got inventory in the stores, but the stores couldn't open. So, what you've seen is a re-prioritization to say, well when we look at inventory management and the supply chain systems, are we factoring in the inventory we have in a store could also be seen as inventory across the stores? And in fact, what we've really got now is a distributed warehouse. We've got inventory in the warehouse like wholesale ready for distribution. And then we've got inventory in a store, retail ready for consumer consumption. What don't want that to be separate inventory. We want that to be holistic. And then how do we enable any consumer anywhere to be able to arrange for curbside pickup, which we didn't use to do because we would come into the store or arrange for mail order. But the inventory may come from you know, I may send something from San Francisco to somebody in Boston because it was in a store inventory in San Francisco. Now, sure, it's got some freight cost, but I've also got some other efficiency savings and I'm reducing my working capital or my inventory expense. So, we've seen prioritization for really how to take advantage of this. I come back to it, this word distributed is very simple in principal, but everything is now working on a new dynamic. So, that's some of the prioritization we've seen. >> You mentioned one of the things that might get put on hold is, wait if I was doing a corporate network update, that might not be the first thing, we absolutely, we've gotten some great data on just the changing traffic patterns of the internet, but the network is so critically important. Everybody from home is dealing with, you know, children doing their Zoom classrooms while we're trying to do video meetings. NTT obviously has a strong network component to what its business is. So, help us understand the services that are important there, what you're working with customers and how has this kind of transformed some of those activities? >> Yeah. Yeah, sure. Thank you. You're so right. I mean and I have to say, I just like to pay my respects to colleagues and fellow workers around the world who are not just working from home, but also homeschooling in parallel. Our kids fled the nest, either they're working for themselves now, so, we don't have the extra activity of homeschooling, but I can really have a lot of respect for colleagues who are trying to do both, it's a real fine art. And we've seen a lot of actually just talking of re-prioritization. We've seen a lot of companies including ourselves, say to our colleagues, look after your children, homeschool them, do everything you can to support your families and then get to your work. So, that re-prioritization just in behavior has been a key change that we've seen a lot of people do. That flexibility to, you know, work is something you do, not somewhere you go. And therefore, as long as the work is done, we can flex around, you know your needs as a family. So, that's one prioritization we've seen active actually. But to your point on the network, it's quite amusing to me that we've been for years now talking about cloud, on-demand subscription services. And actually the one asset that you need to really enable cloud is the network. And it's historically been the least cloud-like that you could possibly imagine because you still need to specify a physical connection. You still need to specify a bandwidth value. You still need to specify, the number of devices you've got to attach to it. I think this is really a monstrous change that we're going to experience and really are experiencing, the network as a service. I mean, we talk about IAS, PAS SAS, but what happened to NAS? I mean, really did we just think that everything was about computer and software? The networker is the underpinner. And so really we see a big change and this is where we've been very busy in the network as a service enabling customers to have, dynamic reallocation of resources on the network so that they can prioritize traffic, prioritize content, prioritize events. A lot of customers and are doing activities such as hosting their own event, their own digital conference. And you want to prioritize what the user experience is when you host one of those events over perhaps back office process that can quite frankly wait a few days. So, we see a significant opportunity. This is where we've been very busy the last few months in really building out much more dynamic network as a service solutions, the cloud network. And I think the whole software defined network agenda has materially accelerated. That's one major area. And then the other area has just been the phenomenal shift to IP voice and software and actually almost the deletion of the phone in its entirety. Everybody using, Teams or Skype or Google Hangouts to really use as their collaboration mechanism. And then, we're providing all the underlying transportation layer, but as IP voices, that creates a much more integrated collaboration experience, and it creates a cost saving cause you're taking away the classic voice services. >> Yeah. So Simon boy, I'm excited for that. I tell you, I remember when I got my first Blackberry and they were trying to sell me some things, I'm like, "Wait, this is an internet endpoint. I can do all of these things there." And of course, you know, it's taken me the last dozen years. If gone a certain far, but, and we always joke. It's like smartphones, we don't use them for phones anymore. We use them for all the messaging and all those services. So, the data and the network are so critically important. Simon, I want to turn to UPGRADE 2020, you know what I'm excited about this, we've talked about the major impacts of what's happened in 2020. And we're looking at the here and now, but it's great in technology when we get to be able to look forward and look at some of the opportunities out there. So, would love to hear from your standpoint, some of the areas, what's exciting you, what's exciting that we can look forward to some of the areas and pockets of research that we see at the event. >> Yeah, I think he's Stu. I think what I like about our event is the investment that we make to work with the scientific community, academia, and really invest in, forward-looking, future-proofing, how physics and different technologies might play a role in the future. And, some of these investments and some of this research yields, commercial products and some of it doesn't, but it's still a very valuable opportunity for us to really look at where technology is going. I think the areas that are particularly appealing to me on a personal level, just the whole thing of Quantum computing. This is, I know we're already exploring the capabilities of Quantum computing in some labs, and some academia centers and really to understanding how can we take advantage of that. But I think if you then say, and you take another area that we're exploring through the event, Biosciences. If you then take the two together and you think, okay, how do we take Quantum computing, and we take Biosciences and you think about healthcare, and then you think about the pandemic, are there things that we can do with simulations and technologies in the future that really would give us greater comprehension and ability to accelerate, understanding, accelerate testing, and then really contribute to the health and welfare of society. And I think that's really quite an exciting area for us. So, that's a specific topic that I'm particularly interested in. I'm glad to see us doing a lot in that space, Quantum computing, as well as the Biosciences. And I'd say one other area where I still think we're all trying to ascertain, how it serves the business is really the area of blockchain. I think this is intriguing. I'm still mentally trying to master the subject. No amount of white papers has managed to overcome the topic in my brain yet. So I'm still working on it. And then I think cryptography, I come back to the same subject security. I mean, we are dependent as citizens, businesses and nations on technology now, and our data is available how we secure it, how we make sure that it's encrypted is absolutely going to be critical. You see an increasing push nationally and globally to ensure that there is security of data. And I think the subject of cryptography, and how we go forward with, beyond 128 bit is going to be a very difficult and critical subject. So these are the areas I'm very impressed with. >> Wonderful. Simon, I want to give you the final word from UPGRADE 2020. >> Yeah. Thanks, Stu Just thanks very much to anybody that's attending. What you'll find through various workshops is lots of insight, from our strategic partners, from research scientists, from academia, from ourselves. So thank you very much for participating. We always value your feedback. So, please tell us what we could do to improve the content, to help you with your businesses. And we look forward and hope that everybody stays safe. Thank you for connecting with us virtually. >> Well, Simon Walsh. Thank you so much. Great having a conversation and glad to have you in our Cube alumni now. >> Thank you very much Stu. Have a good day. >> All right. And stay tuned more coverage from UPGRADE 2020 I'm Stu Miniman, and thanks as always for watching theCUBE. (upbeat music)

Published Date : Sep 25 2020

SUMMARY :

the NTT Research Summit and happy to welcome to the to be here, nice to see you. the pleasure to interact that enable the customers But that the spotlight that's And quite often the that there's had to be some But the inventory may come from you know, that might not be the first thing, the phenomenal shift to So, the data and the network and technologies in the future Simon, I want to give you the to help you with your businesses. and glad to have you Thank you very much I'm Stu Miniman, and thanks as

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
EuropeLOCATION

0.99+

SimonPERSON

0.99+

AmericasLOCATION

0.99+

Simon WalshPERSON

0.99+

2020DATE

0.99+

BostonLOCATION

0.99+

NTTORGANIZATION

0.99+

IndiaLOCATION

0.99+

Stu MinimanPERSON

0.99+

San FranciscoLOCATION

0.99+

24 inchesQUANTITY

0.99+

twoQUANTITY

0.99+

StuPERSON

0.99+

firstQUANTITY

0.99+

bothQUANTITY

0.99+

todayDATE

0.99+

NTT AmericasORGANIZATION

0.98+

128 bitQUANTITY

0.98+

first timeQUANTITY

0.98+

NTT Research SummitEVENT

0.98+

2020thDATE

0.98+

pandemicEVENT

0.98+

BlackberryORGANIZATION

0.98+

SkypeORGANIZATION

0.97+

last week of JuneDATE

0.97+

oneQUANTITY

0.96+

first thingQUANTITY

0.96+

two different data pointsQUANTITY

0.96+

UPGRADE 2020EVENT

0.94+

NTT-Research SummitEVENT

0.93+

CubeORGANIZATION

0.91+

NTT researchORGANIZATION

0.88+

CXOTITLE

0.87+

one major areaQUANTITY

0.85+

few years agoDATE

0.81+

one assetQUANTITY

0.75+

UpgradeEVENT

0.73+

GoogleORGANIZATION

0.72+

yearsQUANTITY

0.71+

EuropeanOTHER

0.66+

theCUBEORGANIZATION

0.65+

last dozen yearsDATE

0.65+

HangoutsTITLE

0.65+

halfQUANTITY

0.64+

IASTITLE

0.63+

yearDATE

0.61+

last five plus yearsDATE

0.6+

ofDATE

0.6+

last few monthsDATE

0.54+

firstDATE

0.54+

theCUBETITLE

0.53+

2020COMMERCIAL_ITEM

0.41+

UPGRADE 2020ORGANIZATION

0.39+

UPGRADEEVENT

0.3+

UPGRADEOTHER

0.27+

Eric Clark, NTT Data Services | Upgrade 2020 The NTT-Research Summit


 

>> From around the globe, it's the Cube covering the Upgrade 2020, the NTT Research Summit presented by NTT Research. >> Hi, I'm Stu Miniman, and this is the Cube's coverage of Upgrade 2020 the Global Research Summit for NTT and always happy when we get to talk about digital transformation. Happy to welcome to the program, first time guest on the program, Eric Clark. He is the Chief Digital Officer with NTT data. Eric, thanks so much for joining us. >> Thank you, glad to be here. >> All right so Eric, let's start, you know, CDOs, first of all, there's lots of CDOs. We've done lots of events with the Chief Data Officers, which I'm sure we'll talk a little bit about data, but the digital officers, of course digital so important in general and even more so in 2020. But let's understand your role as Chief Digital Officer. What's your charter? Where you sit in the work? What are you responsible for? >> Yeah, definitely, and you know, it's a good question. I often start conversations with our customers by talking about exactly that, because Chief Digital Officer means something different to different companies. So for us, it's primarily my market facing. And what that means is I spend most of my time looking at research, looking at R&D, looking at what our competitors are doing in the market and looking at where trends are going to make sure that we have the right offerings and capabilities to bring to our customers, to make sure that they will remain competitive in their markets. >> That's great, you know, we've been talking for years about the digital transformations that companies have been going through. One of our definitions has been, if you're not at the end of it, more data-driven, you probably haven't done the right thing. But Eric, this year with 2020, you know, anecdotally, we talked to a lot of customers and obviously there's certain initiatives that get frozen or will take a little bit longer, but those digital initiatives, which are supposed to rely on data and help us move fast and be more agile, seem to be at the top of the list and are accelerating because if I can't respond to the daily and weekly changes that have been great in 2020, I might have a tough time surviving. So, what are you seeing? How does that live in your world? >> Yeah, you're exactly right. And that's what we're seeing from our client base as well. So early on in the pandemic, there was a lot of freeze. You know, hold everything, stop, stop spending, and let's figure out where we are and where this is going. But very quickly that turned to, we've got to react. We're going to be living with this for awhile. And we can't afford to sit back and wait and see where it goes. We've got to react and we've got to direct our future. And very often the way that comes out is with digital. So, customers are looking for opportunities to leverage digital, to grow revenue, to improve customer engagement and to drive more of their revenue through digital channels. >> Interesting, but one thing I didn't here in there, but I'm sure is part if it, what about the employees themselves? One of the big things of course, is that we've made this wonderful corporate environment, you've got the great internet there and now way everybody's at home and scrambling as to what they do. So how about the kind of the EX to go along with the CX? >> Yeah, exactly, and that was actually one of the first places that we focused as a company, because we do a lot of what we refer to as workplace services. So making sure that our customers, employees have the tools they need to do their job successfully. So immediately when offices started closing and people started going home, our big challenge was let's make sure that our customers can connect from anywhere, from wherever they need to be working from and have access to the applications and the tools and the products that they need to perform their jobs remotely. And that's really turned into a significant business of its own, really addressing those needs, not only for our customers, but also for our employee base. We have 50,000 people that we sent home, more than 90% of overnight. And many of these are our employees that are interacting with our customer base on a daily basis. So we had to make sure not only that they had connected but they had to be secure. So it was a very big switch and I think I personally was really impressed not only with what we did, but what we saw the industry do, to make that transition very safely and seamlessly. >> Eric I'd love you to expand a little bit on that, You know, which pieces of that full solution that is NTT offering and how do you and your partners help your customers through those rapid adoptions that they need? >> Yeah, so we're a full suite provider. So, we're focused on digital operations, which is digitizing your back office from your workplace services to your hybrid infrastructure network, et cetera. All the way through bringing what we refer to as journey to the cloud. So how do we help you identify what applications and what data you need in the cloud. CX and EX very big focuses for us. In fact, we take a lot of pride in, while we do go to market and sell CX specifically, we consider CX part of everything we do. So if we're talking about workplace services or hybrid infrastructure or security, we want the employee experience to be solid, and we want the employee experience to be consistent across all of those things. So, we think that our customers should not expect to have different interfaces and different portals and different user experiences when they do work with us across infrastructure, application and cloud, et cetera. >> That's excellent Eric. You know we spent the last six months talking about how did we react to the pandemic, and now at least here in the US, the children are back in school. If they're back though, it tends to be a hybrid model. And when we look at work, often we know we're going to have this long gated, kind of new abnormal if you will. So, yes you might be back in the office some, but chances are you will spend some time remote and therefore it's not work from home or back to work, it's work from anywhere, is what I need to be able to do. So, how are you preparing? How are you helping your customers through that? Because it's one thing if it was just a switch that says, I'm either here or there, but it's changing and it's very fluid. >> Yeah, and you're exactly right, it is work from anywhere. But there are some of our customers that don't have the luxury of work from anywhere. So when you think about manufacturing facilities and different hospitality companies, there are people that need to go into physical places. We do a lot in the healthcare space. We need doctors in the hospitals. So we've done a lot to help our customers figure out safe ways to return to work. Recently, we've seen universities, and as you mentioned, high schools and elementary schools all going back with varying degrees of success, right? Some of them have failed and they've had to take a pause and figure out how they're going to restart. We've also seen professional sports leagues and now college sports leagues. And when we see them having issues, we see protocols adjusting and we see them looking for what can we do to make this safer, more effective and more successful for whether it's our sports team, our school or our business. So we've taken a very active approach in that. And we're leveraging technology and creating IP that starts with pre-arrival, registering in advance and opting in for things like tracking social distancing and tracking the use of masks. Then using cameras and facilities to monitor it, to make sure people that are adhering to social distancing and adhering to wearing mask. And in the event that they aren't, we can send instant notifications to their phone. If we have repeat violators, we can prohibit them from coming back to the office. So we can have very strict controls and adherence to whatever the protocols may be as the protocols change. And then the other thing that allows us to do is in the event, someone would test positive with COVID, we will know exactly who they've been within six feet of without a mask over the past X number of days. All of that is stored in the cloud for us to use for reference and use for audit purposes. So that gives us the ability to then use our app to direct all the people that the person that was positive was in contact with, let them go get tested, come back with a negative test before they returned to the office. So basically what we've done is we've created all kinds of technology using automation and AI and facial recognition to bring more safety and more security to the workplace, whatever that workplace might be. Whether again, school, university, manufacturing facility, or a hotel. >> Really interesting topic. Tracking and tracing, so critically important. We've seen in many countries around the world, that's really helped them get their arms around and control that. We talked at the top of the interview about digital means leveraging the data. And if I don't have the data, I can't respond to what's happening there. Here in the US, I haven't heard as much about the tracking and tracing. Is this a company by company thing? Do they have the expense all on them to do it? And of course it raises the concerns about, well, I'm concerned about my privacy and that balance between the public interest and my right to privacy. How do you help your customers sort through some of those issues? >> Well, privacy is definitely a big issue. And you notice that when I was explaining that I said in pre-arrival, you opt in. So the way we've approached it is, it is an opt in. So those that don't want to opt in to that kind of tracking and tracing, won't be those that will be allowed to come back to the office. And that goes back to your other point, I've worked from anywhere. Many of those people can still successfully work from anywhere. But those that feel like they're more effective, more successful or have a need to be in an office, or a need to be physically again in a manufacturing facility or a hotel, we have a way to do that safely. >> All right, well, Eric one of the things I love about research events lately like yours, is a little peek into what's coming on down the road. So, any other things you'd like to share about? You know, some of the things that are exciting you, some things we should be looking at a little bit further down the road? >> Well, I think, you know, for us as you know, we spend a significant amount of money each year on research, and we really get excited about these opportunities and these showcases. So you'll see a lot of exciting information and a lot of what's coming in the future. (indistinct) out of it right now obviously because of the time you'll see themes of safety and security, but you're also going to see just a whole lot of really thought provoking, forward thinking technology. >> You always take the opportunity, even when they're crisis out there. There's the opportunity for innovation and acceleration of what's happening. >> Yes. Eric, thanks so much, a pleasure talking with you and definitely looking forward to hearing more from the event. >> Great, thank you, enjoyed it. >> And stick with us for more coverage from Upgrade 2020, I'm Stu Miniman, thanks as always for watching the Cube. (upbeat music)

Published Date : Sep 22 2020

SUMMARY :

the NTT Research Summit of Upgrade 2020 the Global Research Summit but the digital officers, of and capabilities to and be more agile, seem to and to drive more of their One of the big things of course, and have access to the and what data you need in the cloud. and now at least here in the US, and more security to the workplace, and my right to privacy. And that goes back to your other point, You know, some of the things because of the time You always take the opportunity, to hearing more from the event. And stick with us for more

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Eric ClarkPERSON

0.99+

EricPERSON

0.99+

USLOCATION

0.99+

2020DATE

0.99+

Stu MinimanPERSON

0.99+

NTT Data ServicesORGANIZATION

0.99+

50,000 peopleQUANTITY

0.99+

NTT ResearchORGANIZATION

0.99+

more than 90%QUANTITY

0.99+

oneQUANTITY

0.99+

CXTITLE

0.99+

OneQUANTITY

0.98+

six feetQUANTITY

0.98+

NTTORGANIZATION

0.98+

pandemicEVENT

0.98+

CubeORGANIZATION

0.97+

first timeQUANTITY

0.97+

each yearQUANTITY

0.96+

NTT Research SummitEVENT

0.95+

NTT-Research SummitEVENT

0.94+

Global Research SummitEVENT

0.94+

Upgrade 2020EVENT

0.93+

last six monthsDATE

0.92+

one thingQUANTITY

0.91+

first placesQUANTITY

0.9+

NTT dataORGANIZATION

0.88+

EXTITLE

0.86+

this yearDATE

0.82+

UpgradeEVENT

0.72+

CubeCOMMERCIAL_ITEM

0.53+

COVIDOTHER

0.45+

Bill Baver, NTT & Michael Sherwood, City of Las Vegas | Dell Technologies World 2019


 

(energetic music) >> Live, from Las Vegas it's theCUBE covering Dell Technologies World 2019. Brought to you by Dell Technologies and it's ecosystem partners. >> Hi, welcome to theCUBE's coverage of Dell Technologies World 2019. I'm Lisa Martin with John Furrier. We're in Las Vegas and we have somebody from the city of Las Vegas here. We've got two gentlemen joining us. Bill Baver, the VP of NTT. Hey Bill, good to have you on theCUBE. >> Thank you very much, appreciate being here. >> And your partner in crime Michael Sherwood, the IT Director Las Vegas. The city of Las Vegas, where we are right now. >> Welcome. >> Thank you. >> Love having you here. >> Thank you for having us. So guys, theCUBE comes to Vegas a lot. There's a ton of shows here. You can fit a ton of people. Last year, Bill, we'll start with you, NTT and Dell Technologies announced this exciting smart cities initiative. Talk to us about, in the last year, first of all why NTT is partnering with Dell Technologies and what you've done. And then of course we're going to dig into Las Vegas as one of those smart secure cities that Michael, I can tell, is just tell dying to tell us about. So, in the last year, what's going on? >> Well, first off when you start digging let me see. I want to see how this really plays here. (laughter) So, I'm ready for that. So, yes last year we announced a partnership between Dell, NTT and Las Vegas. And it's really a three way partnership. And since then, if you ever work with city governments, how far the city of Las Vegas has come has been amazing. So within six months we installed equipment that was supposed to be there. And then started for the last six months running a system there, running it around public safety perspective, and really starting to bring true insights to what they're doing. The Dell part brings equipment on the edge and our core data center. How to go back and forth between the entire Dell family. Dell, EMC, VMware, and then the NTT family that's there. And then really the third leg of the stool is the city of Las Vegas and the insights they've allowed to us to recognize and sort of bring to them. So they can make changes in how the city is looking at and running the environment. >> And why did you decide to start this partnership with the wonderful city of Las Vegas? >> It's really around innovation. So, Michael Sherwood, and the city of Las Vegas have really become a leader in innovation around the country and they're really willing to take chances. And they have an innovation zone that allows them to do projects rather quickly. Not as quick as this sometimes, but rather quickly. Then, we can start to see results and then they can adjust and start to figure out how it's going to roll out and sustain across the city. So, it was their innovation and it was really Michael's legacy of what he's been doing so far and what his willingness to work with partners has been. So that's really a reason to do this as we went forward. >> So, how about the innovation strategy? Because, obviously, Las Vegas, a lot of people come here. Destination, public safety's been critical. Number one. I've seen the evolution of just really smart moves whether it's blocking the sidewalks from anyone driving on them to the use of video and processing video. You need AI for that. So it's probably a melting pot of interest to be on the forefront. >> Why would innovation go anywhere else other than Las Vegas, where we're the innovators of entertainment. We're the innovators of fun. So, why not be the innovators of technology and innovate with great companies like NTT and Dell. I mean you can't get any better. If you want to talk about a cube of perfection that would be it right there. You have innovation around the board surrounded by great companies. Las Vegas is innovative. We have a culture here to use technology to not only make our citizenry safer, but to insight development, to insight economic growth. So innovations not just something that is just limited to technology. It's limited to all facets of society. >> That's great culture too. You don't really have to change the culture if people are already there. What leading edge stuff are you working on now that'd be really cool to talk about? I mean smart cities, obviously, cameras on corners looking at things, so traffic, EIOT devices. What are some of the things? Share with us, open the kimono a little bit. Talk about it. >> So, first off, one thing. We do not say cameras, we say optical sensors because that's more pleasing to the ear. So, as we gather data it'll go, so go ahead. >> All right, thank you Bill. (laughter) So optical. Even I learn something every day in innovation. I mean now we have optical sensors. >> It's all optics. >> It's all optic. Let me just start with, you know public safety's very important. So we're doing some things there with our partnership with Dell and NTT. I like to call it autonomous policing. Where we're really providing real time analysis of a location. So, in the old days or current days of policing, police randomly drive around and do a patrol. That's what we call it. What we're looking at now is using cameras to provide, excuse me, optical sensors, to provide real time situational awareness to those first responders. So as they're responding to an incident, number one, there really is an incident. Because the optical sensor has validated that there is an issue there. And as the officers respond to that, they're actually able to see real time analysis from those optical sensors that's giving them a safety presence. So we're really taking policing, and really putting policing where it needs to be when it needs to be there. That's one category. The other one's mobility. We all want to get from point A to B the most convenient way possible. And what we're doing with the Dell NTT partnership and this optical sensor system, as well as analytics, is really looking at improving traffic flow, but improving traffic flow smartly. And something that's scalable that not just Las Vegas can do but any city could do across the world. Again, Las Vegas, we don't consider ourselves just a national US based innovator. We look at ourselves as world innovators. So really mobility is somewhere that can go anywhere in the world. Same with public safety. >> Talk about the architecture of innovation. How do you guys pull this off? What's the playbook? A lot of people want to be, first of all, cultural change is hard. You guys are there, like I said earlier. What's the playbook? You got to have multi-cloud architecture. You got to start thinking about getting a system set up. Either like some sort of sandbox or I've seen (mumbles) innovation zone. How do you pull it off? What's the playbook? >> I think the playbook goes down to a great team. Without a great team and great partners it doesn't matter what technology you have behind it, it's the team and partnership. That's really what makes this special. You see the bond between myself and Bill. But that goes through all levels of NTT, as far as all levels of Dell. So it's about bringing winning players and winning skill sets together, and then taking great technology and funneling around that. That is a success. Anybody can be an innovator. It's nothing special, though I'm available to help people innovate. But, I think what it really takes is understanding your business. Understanding your performance measures that you want to hit. What do you want to do? In a football team, they want to score a touchdown. In my job I want to use my resources effectively as I can and create things that are safe, and create a better Las Vegas for everybody. >> Speed is critical. It used to be the old days, months to get projects done. Then it became weeks, now it's days, hours. The shift in the time spectrum has radically changed. >> It's tough. It's tough for government. Government is traditionally not known for it's agility and speed. You know, we're changing some of that here. But we're still struggling in a couple of areas. We have some refinement to do. I think, nationwide, purchasing is hard. We want to be fair and equal to everybody. But, at the same time, we want to get these solutions out in the marketplace because it is helping the city be more effective. So, there's challenges still. But, overall, the future is very bright and the technology and expertise that our partnership has really is making, I mean, in one year I don't think any government in the US has done as much as the city of Las Vegas has with our partnership. >> I would add that Michael's being a little humble on that there's not a lot of, everybody can do innovation. We have an innovation zone that allows him the flexibility to do that. So, that's really important. And then the technology, Michael is right that it is tough. There are times that it didn't work to the schedule. But that goes back to the teamwork of everybody saying our end goal is we want to get this done, and going towards that. >> Talk about the innovation zone. Talk about the innovation zone. Is that a physical zone? is it where you can deploy new towers and test stuff? >> It's downtown Las Vegas. If you're familiar with Fremont Street, it's the big canopy area. So, it's about 80 square blocks around that area that incorporates an entertainment district, a government zone, a medical, where we basically have fiber optics. Different type of technologies and we ask partners to come in and test. But, to follow up a little bit, I'll disagree with my panelist here. You know, every city can do >> That you're not humble? (laughter) >> But every city can do innovations. It's about understanding risk and taking a little gamble and a little chance. We do that everyday in our lives, but yet when we get into out work we seem to forget about risk. >> It's a tech playground, too. You're going to attract great people when you have this kind of flexibility to just deploy. Do bake-offs, test new equipment. >> You got it. Again, so many people know Las Vegas just for what they see while they're here. Which is fun and entertainment. We want everyone to know that Las Vegas also means business. We're here to be discovered. We're here to be used. Not abused, but we're here to be used. (laughter) >> If you're bringing you equipment into you're tech zone does it stay in Vegas? (laughter) >> Everything that happens in Vegas stays in Vegas. >> It can't leave. >> Including the equipment. >> Like hotel California. >> All the equipment. Yes >> Exactly. >> I'd like to have the people remain as well. But no, I mean we're open for business. We're not just a great place to play. We're a great place to develop your products and sell product. >> So talk to us about, not just the innovation zone, but as you mentioned before, this is a challenging thing for governments and municipalities to undertake. It's expensive, right? There's a tremendous amount of people that are coming in and out of Vegas 24 by seven. When you're talking, I presume, Michael, that you're talking with you're talking with your peers in other industries about, this is why we set up an innovation zone. This is why it's so critical. Here's the advancements we've made in terms of safety in the last year. What are some of the industries that you talk to and some of your recommendations for them to take that gamble and to find the resources to make this happen? >> Well it's finding the great partners obviously is one. But two is start small. So many cities want to do, I want to replace all my street lights with smart lights. In Las Vegas that would be over a hundred thousand street lights to replace. A huge project, daunting. But why not start small? Get an understanding of the technology. Understand how it works. And then see what you like and what you don't like. And then you can go ahead and, from a small pilot, then, with the education behind you start branching out and making it bigger. And I think the key to my success is start small gain knowledge, gain success, and then build on that success. Don't try to shoot for that one shot and you're going to be a winner. >> That's great advice. What about some of those key constituents of yours, you mentioned some of the things you're doing with policing and from a government perspective. Who have been some of your key constituents to become champions of what you're doing with NTT and Dell Technologies? >> It's really the people, the people that visit here. I look at everybody as a customer. Whether you live here, play here, you're a customer of Las Vegas. And so we want you to be happy. We want you to be able to get from A to B. It doesn't do us any good if you're stuck in the car because you're not spending any money. And so, I want you excited. I want you having the best time of your life at the best restaurants. I want you having the safest experience here. I want you to return. So my objectives are no different than a private business. Except, I have the whole community. So it's when people in the community say thank you for letting us get to A to B quicker. They never thank me personally, but they're happy about it. I'm not hearing complaints about being stuck in traffic. >> Getting to A, B quicker is a lot of really long stop lights in Vegas. Any optical sensors going to help us with that? >> Taxi lights? >> You've got to come down. This year, we actually, in January we did an autonomous vehicle all the way from Mandalay Bay down to the Golden Nugget. Great technology. It worked. We're getting there. Yes, traffic is still in certain areas an issue. But come down to the innovation district. You want to drive around there it's great. >> We've got to have theCUBE there. We've got to get a tour of this. >> We've got the inside track here. >> In time. >> I know a guy in Vegas. You're out guy >> I'm your guy. (laughter) >> Guys, talk about the key learnings. You can both share some data around the journey the past couple years as technology has shifted. Obviously, apps or renaissances happening, more apps are coming over the top: Saska, cloud, partnerships or people equations happening. What's some key learnings or scar tissue that you guys have learned over the past few years that you could share to folks watching? >> I think one of the first parts is the learning is partnership and your end goal. Because, there are going to be bumps in the road as we go, and there were bumps. Things couldn't get installed as quickly. It didn't work the way we wanted. That's why we started as a proof of concept. But then the other part of the learning is start small and grow. It's not only start small in an area or even a section of the city. It's how does it grow so that you have a sustainable model for the city so they can then pay for it as they go forward. We all want to make sure that it gives us a model forward. So the openness of the NTT and Dell partnerships to allow us to have that time to do it, that was really important for us to figure a model forward. And now we're fitting into the city model a lot better. And it's making it work beyond just the innovation zone. That's where we're taking it now, and that's the key for us all. >> Mike, any learnings? >> Definitely, let me tag on to his openness. Number one is an open platform. Having a platform that's open, that your data's accessible regardless of what changes. Everybody knows technology changes rapidly. So having agility to situations. Today, right now it's mobility for me. It is public safety. But I really look to the future as curb monetization. Where we're monetizing that curb with autonomous vehicles. How do you get there? If you have a closed system that doesn't have the interface, doesn't have the agility, you can't get there. So, the open architecture is something to me that with the learning, I would have never come to that conclusion without the partnership and the learning avenues. But the open architecture is key. >> The most important question I want to ask, Michael, to you is, when the Raiders come to town, that's going to change the game big time. The Oakland Raiders, the black hole. Whole new fan base. >> I'm excited. (laughter) I'm looking for that to be, even though I live on the other side of the stadium so I have to go through there on the weekends. But I'm super excited. I'm not just excited about the game coming. I'm excited about the innovations and the new opportunities for a great city. And we have the Golden Knights you get to have a phenomenal season this year. Give them a shout out, and wait to come. I will bet you in the next year there will be some new sports franchises here. >> And the tech involvement, all kidding aside about the Raiders, it's fun to talk about because they're moving here, that's great. But the tech involved in sports is cutting edge. You've got entertainment, obviously, here inside the venues. And you've got service, managing the team, it's the same IOT problem everyone else has. >> It's in a little mini-city of it's own. It's going to have it's own IOT opportunities there. We're working closely with the stadium authority in that regard. We're sharing our experiences, sharing our partners. But, couldn't be more excited and actually, elated to have them here locally. >> Working closer to get tickets? (laughter) >> How about a suite, I was thinking suite. I'll ask for the suite. >> I'll be with the regular people. (laughter) >> Remember I'm a civil servant of the government here. Very low connections on my lane. >> Last thing, Michael for you, is we talked about the public safety issue. But, in terms of the opportunity for you to let more of the public know. There obviously have been some public incidents here that have been known the world over. It's an important message to get out to everyone. This is a global city. What are some of the opportunities that you have to share what you guys are doing with NTT and Dell Technologies so that the perspective visitors know, I'm coming into a pretty, this is a very AI enabled city that's really looking out for my best interests. >> I'm here on theCUBE. I thought if I was here >> This is it. >> everybody would know about the great things we're doing. >> That's true. >> So, beyond that though. It's part of why we're here today is to share our story and to start outreaching more. We're doing more in the community than we've done before. We're opening a great innovation center downtown. We're calling, it has many name currently now, we're trying to focus on one. But, the concept is basically a technology embassy. Where we're going around the world and sharing our story and letting companies know that they can come here and test their technology, and we can share that with the community. So, really technology is nothing without a great community that supports it. And so, a lot of what I do is sharing that message about what we're doing. We share with our partners, and we come on shows. There's only one show to come on, but this is the show, where I'm sharing what we're doing first. >> He's a quick learner. I think the thing that's been really cool for you guys to share, what NTT Dell and the city of Las Vegas are doing to turn Vegas into this AI enabled city for societal good, but it's also this whole message I think I've heard from you guys in the last 15 minutes is this is all about community, collaboration, people. We thank you both so much for giving us some time this morning on theCUBE. Now you're alumni so you've got to get stickers. And you've got to come back, 'cause this is only going in a better direction. So we're excited to hear in the next year what happens. Doug, Michael, thank you so much for your time. >> Thank you. >> Thank you. Great being here. >> Appreciate it. >> Excellent. For John Furrier I'm Lisa Martin. Can you feel the buzz of Dell Technologies World 2019. Stick around we'll be right back with our next guest. (energetic music)

Published Date : Apr 29 2019

SUMMARY :

Brought to you by Dell Technologies Hey Bill, good to have you on theCUBE. Michael Sherwood, the IT Director Las Vegas. I can tell, is just tell dying to tell us about. and really starting to bring true insights So, Michael Sherwood, and the city of Las Vegas So, how about the innovation strategy? that is just limited to technology. You don't really have to change the culture because that's more pleasing to the ear. All right, thank you Bill. And as the officers respond to that, You got to have multi-cloud architecture. I think the playbook goes down to a great team. The shift in the time spectrum and the technology and expertise that our partnership has that allows him the flexibility to do that. Talk about the innovation zone. it's the big canopy area. We do that everyday in our lives, You're going to attract great people when you have this kind of We're here to be discovered. Everything that happens in Vegas All the equipment. We're a great place to develop your products What are some of the industries that you talk to And I think the key to my success to become champions of what you're doing I want you having the best time of your life Any optical sensors going to help us with that? But come down to the innovation district. We've got to have theCUBE there. We've got the I know a guy in Vegas. I'm your guy. You can both share some data around the journey and that's the key for us all. So, the open architecture is something to me to you is, when the Raiders come to town, I'm looking for that to be, all kidding aside about the Raiders, it's fun to talk about It's going to have it's own IOT opportunities there. I'll ask for the suite. I'll be with the regular people. Remember I'm a civil servant of the government here. What are some of the opportunities that you have to share I thought if I was here is to share our story and to start outreaching more. and the city of Las Vegas are doing to turn Vegas Thank you. Can you feel the buzz of Dell Technologies World 2019.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
NTTORGANIZATION

0.99+

DellORGANIZATION

0.99+

Michael SherwoodPERSON

0.99+

Lisa MartinPERSON

0.99+

Bill BaverPERSON

0.99+

MichaelPERSON

0.99+

DougPERSON

0.99+

Mandalay BayLOCATION

0.99+

EMCORGANIZATION

0.99+

VegasLOCATION

0.99+

Dell TechnologiesORGANIZATION

0.99+

John FurrierPERSON

0.99+

VMwareORGANIZATION

0.99+

Las VegasLOCATION

0.99+

MikePERSON

0.99+

RaidersORGANIZATION

0.99+

Fremont StreetLOCATION

0.99+

BillPERSON

0.99+

last yearDATE

0.99+

Last yearDATE

0.99+

This yearDATE

0.99+

USLOCATION

0.99+

twoQUANTITY

0.99+

TodayDATE

0.99+

NTT DellORGANIZATION

0.99+

JanuaryDATE

0.99+

next yearDATE

0.99+

Oakland RaidersORGANIZATION

0.99+

six monthsQUANTITY

0.99+

one categoryQUANTITY

0.98+

Golden KnightsORGANIZATION

0.98+

Howard Elias, Dell & Jun Sawada, NTT | Dell Technologies World 2018


 

>> Narrator: Live from Las Vegas it's theCUBE. Covering Dell Technologies World 2018. Brought to you by Dell EMC and its ecosystem partners. >> And we are indeed in Las Vegas for day two of Dell Technologies World 2018. Some 14,000 strong in attendance and a show with a lot of vibrancy, a lot of energy, and certainly it's reflected in what's happening on the show floor. Along with Stu Minaman, I'm John Walls, and we're now joined by a couple of guests. It's an honor to bring to the set Howard Elias, president of services, digital and IT at Dell EMC. Howard, how are you sir? >> Great, I'm doing fantastic. As you said, the energy's super high. >> John: Absolutely, and also joining us is Jun Sawada, who is the CFO of NTT and the CEO of NTT Security. Sawada-san, nice to have you with us, sir. >> Yeah, nice to meet you, so a very exciting such a time. Thank you very much. >> You bet, thank you for being here. So Howard, let's just kick off, I'm curious. You've thought about the show. Bigger, better than ever. So many people here, so much conversation and dialogue. And how do you feel and what are you hearing from people? >> Well you know, it's our first Dell Technologies World. We continue to believe we're better together, and we're getting great energy and feedback from our customers and partners. And I couldn't be more pleased to be with Sawada-san here today. A great partner, an NTT group of companies, where we're going to talk about some interesting solutions, which is what we've been talking about with all of our customers today. >> Especially right here in Las Vegas. It's certainly no coincidence, right, the show, and then some work that the two companies have done and are announcing. Tell us a little bit about that. What is the project that involves Las Vegas and your perspective involvement? >> Well I'll let Sawada-san, but this is all about an initial POC that we're doing for the city of Las Vegas. Utilizing the IOT technologies combined between NTT group and Dell Technologies. >> Yes, and also, we want to realize the situation awareness of a city of Las Vegas. That's our issue in including three features. One, with the reactive analysis, analyzing and also a site. It may H, H. We are going to realize, such as indicating that some instance has occurred. And the second feature is a proactive analyzing that adds a center, data centers. It's been providing also a trend or investigation, or the predictions. Lastly, third feature is very interesting. It's a deployment automatically all over the ICT lethal seeds, simultaneously. So based on the several technologies. >> So we love this smart cities theme. I've had the opportunity to interview people from different cities and see governments actually getting involved. I wonder if we can get into some of the key technology pieces that are involved here between NTT and the Dell family. >> We are developing ways, actually, at Dell technologies that we call the Cognitive Foundation. It consists of two technologies, one in times for, very focused to multi, much orchestration. It's been a cover up, so March beta, March domain, March layers, lots of the March we can integrate it. The other one is a software defined ICT lethal system, based on the batchilisation technology coming from Dell Technologies, we're in warehouse. >> Howard, sounds like this fits in with a lot of themes we've been hearing at the show. IOT, of course, I would expect to be heavily involved, but maybe explain some of the Dell standpoint, where some of this fits in. >> Well that's exactly right. So as you know, our IOT strategy is a very comprehensive end-to-end one around edge, to the distributed core, to the cloud. And then, working with NTT in terms of bringing that solution to market for a particular use case, like a smart city, in Las Vegas. And we're going to learn a lot together about how all of this comes and comes to fruition. But it really is about that edge to distributed core to cloud. And it's really based on the Dell technologies around our gateways, our hyper conversion infrastructure, some of the VM-ware software foundation capabilities, together with all of the solutions that Sawada-san has talked about. >> Yeah, I would think, it seems like this is a great test case, great test bed if you will. So, where does this go from here? What are your strategic intents in terms of what you plan to learn here and how it will apply elsewhere? >> That's basically, we were starting that this proof of a concept is a form of this coming September. After the two months, we will go into a market offering with two, both companies. But basically, our business plan is a business to business to anything. In that case, the Las Vegas city is a center bean. Dell Technologies and the NTT is a fast bean, as an enabler to support the center bean. Center bean providing a barrier to the anything, anywhere. So those type of package of concepts that we want to deploy to the other United States cities, not only United States, in the world. >> Globally? >> Globally. >> Howard: Yeah, globally, including in Japan, of course. >> Of course. (laughs) I am very familiar Japan. (laughs) >> And it's great because it's not just about the IOT strategy that we've talked about, but it really is about all of the transformation strategies we have. If you think about building a smart city, it's every aspect of digital, IT, workforce, and security transformation, all coming together into a complete, comprehensive solution. >> Alright, where does it go from here? Talk about the vision for the future, as to what we see in the future, Sawada-san. >> Yeah exactly, so not only are we very focused at the time, with public safety. But both company is we can extend those solution to other solution of smart ones. For instance, education, for instance, the retails, or entertainment, including stadium solutions, or other medical. There's no leftover area that we can extend our solution. You're driving a cognitive foundation. >> Yeah, and we're going to learn a lot from the POC. We also have been working on other projects around the world. And we're going to take all of those learnings and roll that into new products and services that we can deliver to our customers. >> Yeah. >> Well, it's a fantastic laboratory, no doubt about that, Las Vegas is, and I'm sure what you learned here will be applicable, as you said, to cities, not only in the United States, in Japan and all over the world. >> All over the world. >> Great project. Gentlemen, thank you for being with us. I appreciate your, and I look forward to hearing back. Check in a year from now. >> We'll do that. >> Let's see where we are. >> Thank you. >> Thank you. >> Thank you very much. >> Thank you very much. >> Back with more from Dell Technologies World 2018. You're watching theCUBE, we're live, and we're in Las Vegas. (electronic music)

Published Date : May 2 2018

SUMMARY :

Brought to you by Dell EMC happening on the show floor. As you said, the energy's super high. Sawada-san, nice to have you with us, sir. Yeah, nice to meet you, so And how do you feel and what to be with Sawada-san here today. What is the project for the city of Las Vegas. So based on the several technologies. some of the key technology lots of the March we can integrate it. of the Dell standpoint, on the Dell technologies and how it will apply elsewhere? After the two months, we will including in Japan, of course. I am very familiar Japan. all of the transformation Talk about the vision for the future, at the time, with public safety. other projects around the world. in Japan and all over the world. Gentlemen, thank you for being with us. and we're in Las Vegas.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Stu MinamanPERSON

0.99+

twoQUANTITY

0.99+

HowardPERSON

0.99+

JapanLOCATION

0.99+

John WallsPERSON

0.99+

NTTORGANIZATION

0.99+

Dell EMCORGANIZATION

0.99+

JohnPERSON

0.99+

Las VegasLOCATION

0.99+

Dell TechnologiesORGANIZATION

0.99+

Jun SawadaPERSON

0.99+

two companiesQUANTITY

0.99+

third featureQUANTITY

0.99+

United StatesLOCATION

0.99+

DellORGANIZATION

0.99+

Howard EliasPERSON

0.99+

two technologiesQUANTITY

0.99+

Cognitive FoundationORGANIZATION

0.99+

second featureQUANTITY

0.99+

NTT SecurityORGANIZATION

0.99+

three featuresQUANTITY

0.99+

firstQUANTITY

0.99+

bothQUANTITY

0.99+

both companiesQUANTITY

0.99+

OneQUANTITY

0.99+

Dell Technologies World 2018EVENT

0.98+

MarchDATE

0.98+

oneQUANTITY

0.98+

Dell Technologies World 2018EVENT

0.97+

two monthsQUANTITY

0.97+

todayDATE

0.97+

day twoQUANTITY

0.95+

Sawada-sanPERSON

0.95+

Sawada-sanORGANIZATION

0.9+

14,000 strongQUANTITY

0.86+

Dell Technologies WorldORGANIZATION

0.85+

SeptemberDATE

0.8+

couple of guestsQUANTITY

0.72+

POCORGANIZATION

0.69+

Sawada-PERSON

0.63+

SawadaPERSON

0.62+

CFOPERSON

0.56+

CEOPERSON

0.54+

-sanORGANIZATION

0.46+

Christina Ku, NTT Docomo Ventures, Inc - Mobile World Congress 2017 - #MWC17 - #theCUBE


 

(upbeat music) >> Narrator: Live, from Silicon Valley, it's the theCUBE, covering Mobile World Congress 2017. Brought to you by Intel. >> Hey welcome back. We're here live in Palo Alto at the SiliconANGLE Media Cube studios, our new 4500 square foot office. We merged with our two offices here to have our own studio, and we're covering Mobile World Congress for two days. 8AM to 6 every day, breaking down all the analysis from the news, commentary and really breaking down the meaning and the impact of what's happening, and the trends. We're doing it here in California, bringing folks in and also calling people up in Barcelona, getting their reaction on the ground. We've got our reporters, we have analysts there but all the action's happening here in Palo Alto for our analysis. Our next guest is Christina Ku, director of NTT Docomo Ventures. Welcome to theCube, appreciate it. >> Hi. Well it was good to see you again. >> Great to see you. Obviously we've known each other for over a decade now and you've been in the investment community for a while. The first question is why aren't you there at a Mobile World Congress? Because it's changed so much, it's a telco show and some apps are now thrown in there. But there's so much more going on right now around 5G, AI, software, end to end fabrics. So it's not just "Give me more software, provision more subscribers." It's a whole other ball game. >> That's a great question. So our CEO of NTT Docomo is there, and the C-level team. But we are the innovation team. We have been here since 2005 doing research and then added business development about three years ago and then a ventures team that's been around and now we're part of NTT Docomo Ventures. What we're looking for is more services and software and this year I guess the focus is AI. And AI is, I would call it the new infrastructure. Since wireless networks are all data now, the new infrastructure is AI rules. Rules for everything, vertical and new maps. So I can talk a little bit more what we've been seeing in kind of the software and services area and how we're looking at the Bay Area as kind of the new innovation to bring back to Japan to work with NTT Docomo. >> That's awesome. Let's take a minute, Christina, if you can, just before we get started, take a minute to explain what your role is and the group that you're in at NTT Docomo here in the Bay area. What you guys are doing, the focus, and some of the things that you're involved in. >> Great yeah, thanks. So, I'm a director and I invest on behalf of two funds. One is NTT Docomo Ventures for NTT Docomo, the wireless carrier. Sixty-million subscribers, all in Japan. Our competitor is SoftBank. We're bigger in Japan, and have more market share. And also the NTT Group has a two hundred and fifty million dollar fund. They're off the 101 Freeway. There's NTT Security, i-Cube, a division of companies, as well. And the idea is to bring these technologies through start ups, through BD, to help them enter Japan. And also, to invest, a minority investment. >> That's awesome. So you have to pound the pavement, go out there and see all the action. Obviously, Silicon Valley, a lot of stuff happening here, and you've got a lot of experience here. Your thoughts on the business model, and how the AI as a service, you mentioned that, which is, we totally see the same thing. We see a confluence of old network models transforming into personal networks. We're seeing a trend where the relationship to the network, if you will, from a personal standpoint, could be the device initially, but now it's wearables. It's the watch, it's the tablet. So now people have this connection, digital connection to the network. Might not be just one network, it could be two, so now AI has to come in, and people are speculating that AI could be that nice brokering automation between all the digital services. Whether I'm jumping into an autonomous vehicle >> So if you refer to services for consumers, then the approach that we have is to offer a B to B to C business model, so in each lifestyle category. We purchased a cooking school, or a percentage of a cooking school, ABC Cooking. And then we were looking for kitchen devices, right, to offer that service, an oven, a bluetooth connected pan. I think some of these devices will be showing up at a Mobile World Congress. And then, people want a service wrapped around that. Same thing happened last year with fitness, with Fitbit, but also there's so many other devices to monitor your heartbeat and your health at the consumer level. But consumers want a service provider, someone to put that together for them. And I think AI would be in that layer. >> So when you say service, you don't mean like, network services or connections, you mean lifestyle services. You mentioned cooking. By the way, Twitch has one of the most popular shows in Korea. People watch each other eating food. It's one of the hottest live-streaming shows. But this kind of talks about that. You mentioned healthcare. Is this the kind of new software you see? And these are kind of the new digital services? Is that what you're looking at? >> That's exactly what we're looking at. I think people don't associate a carrier and services. In Asia, more so, maybe Korea, and Japan, because 5G will happen there, first. And Docomo will be the first carrier to have 5G in Japan. I think Korea, they'll have their version first. So I think with that, we have been, I guess since the days of i-mode, offering services, in a way. Because PC, and phone has been analogous, all data services have been just data in Japan. >> What's your take on 5G right now? Because obviously that's the big story at Mobile World Congress. Is it real? Is this one of the big upgrade areas? Do you see that being a catalyst? >> Yeah, I mean, we will have it for the Tokoyo Olympics. So we're working on that. >> And what kind of speeds are they talking about? Gigabit, is that what they're looking at? >> Yeah, I think it's within 30 seconds you can download a full HD movie. >> (laughs) I want that. >> For consumers like me right? >> Come on, I want that now. We had our last guest talking about that. "What am I going to do with a Gig?" I'm like, well, apps will figure it out. That's one of the beautiful things about software. What's the coolest thing that you've seen? In terms of, as you look at some of the things that are around the corner, what are some of the cool highlights that you see connecting the dots with some of these new kinds of services? What's the trends? >> Depends on if you say consumer, enterprise, or kind of core. Like I said, what's in the home is interesting. On the infrastructure side, mapping. I think new types of beyond Waze mapping, 3-D drone mapping. >> The drone thing is super hot. That is killer. >> But it requires a new data set. >> Yeah. >> Right? And if you look at, Waze is great, but if you look at it, it's almost outdated, now, right? In terms of what you can imagine, if there is a tree that comes up because of a storm, or has fallen down, you want that map to configure that. So that the drone can fly over the building, or the tree, or whatever's in the way. So you need real-time mapping, and I think that's an interesting area that we've been looking at a lot. >> And connectivity will fuel a lot of these devices, whether they're drones, or other sensors on the network. As that's, I'd imagine, the good instrumentation out there for that stuff. >> And also social data. The confluence of easy, cheap social data. And then marrying that, and stitching that in there. You know, we've found companies that will identify you through video, like computer vision, and a drone will follow you and recognize you through AI. >> That's cool. >> That's kind of, you know, there may be small increases in innovation, but without the AI and the machine learning, you can't- >> Yeah, it's interesting, you know, this lifestyle, these services. I think that's the right strategy in the right direction. Because we were just having a debate earlier this morning on theCube, here, about autonomous vehicles. Because one of the four categories of the hot trends in Mobile World Congress is autonomous vehicles, entertainment and media, smart cities, and home, automating and all that stuff. And that's all an opportunity for services. But we were debating that transportation's not going away, but I might not buy a car in the future. The differentiation might come from really cool software that allows me to take my preferences, my Spotify playlist, all my digital services that I am leveraging into an environment, whether it's a car, a theater, a park, a stadium. Whatever lifestyle I'm in, I can then move with my digital ecosystem, if you will. My personal- >> Your preferences. >> My digital aura, if you will, and not have to reboot, and connect. I mean right now, my phone works. I just associate, but you know, still, it feels clunky. So I think that's kind of a cool direction. Is that something that you see that telcos and most folks will pick up? Or is that just you guys doing that right now? >> I think what interests me about NTT Docomo when I joined was that they're kind of in the forefront, and in kind of leadership of that. And I think Korea and Japan, in Asia, are looking ahead. What do you do with unlimited data? And then kind of following you everywhere. So I think AI, uh, you know, we had SIRI, Shabette Concierge, which was, I guess, our version of SIRI a long time ago. There's a lot of voice-enabled applications. So, I guess, will that be the interface? I think another interesting concept is what will be the interface? The phone, Amazon Echo, what will be the natural interface for you to connect to these devices and preferences? >> Take us through the day to day in the life of a VC, kind of the deals that you do. What happens in your day to day life here in Silicon Valley? Take us through some of the things that you go through every day. >> Most days, I guess, just meeting with companies and trying to find, you know, the next one. There's so many great areas, and also the next trends. We also do a lot of enterprise deals. So I've been looking at security, cloud, a lot of the devops, or kind of what's around the cloud systems. Finding the right companies. And then, also intersecting with my, I have a business development team, and they connect to Tokyo, so there at night, talking to the business group leaders. And finding that balance of, what is a technology that would work in Japan? What are they interested in? And then, out here, scouting for those companies. >> Yeah, one of the sub-plots of the Mobile World Congress this year, which is consistent with pretty much the trend is that the enterprise, IT, is evolving very quickly because of the cloud. Amazon has certainly demonstrated the winning in the cloud. And security, no perimeter, API economy, these new trends are forcing IT to move from this proven operational methodology to very agile, data-driven, high-compute clouds. And security's one of the huge issues. And now you have multi-clouds, where I might have something in Azure, I might have something in Amazon, I might have something in a geographic basis around the world trying to operate globally, being a multinational, is challenging. What's your take on that? Because this is an area that is not sexy as the consumer play, but in the B-to-B space, it is really front and center. RSA conference just last week, we were talking on email about RSA. Two weeks ago, that was the number one thing. You've got the cybersecurity issues, you've got the cyber surveillance, and also just the threat detection from ransomware to just consumer phishing. What's your thoughts in this area? >> So, I guess we're looking at kind of what's the next new area, which would be using AI to analyze all this data that's coming in, from the perimeter, from the end point, on your network, right? And then what can bubble up to the surface? We've invested in two companies in this area: Centrify and Cyphort. Looking for, kind of, other companies that- >> John: Well, Centrify, they're really focused on the breech. >> They're really focused, yes. >> Tom Kemp, in fact we went to their party at the RSA, Jeff Frick and I. They had a great band. Had a good time with those guys. But they're doing extremely well. They're very focused on mobile. >> They're doing really well, yeah. >> So what is the challenge, in your mind, right now, if you're an entrepreneur out there, for the folks watching? They're looking for kind of like the white space. They're looking for some tea leaves to read. Could you share any color on just advice for the entrepreneurs out there? Because it's certainly a turbulent time in the enterprise, and just in general, the cloud market. >> It's very competitive. >> Advice for entres, where should they focus? What sort of key metrics should they be building their ventures around? >> I think it depends on if you have an idea, or have a product already, but I think it's very competitive, right? And it's hard to break out of. What's your product differentiation? On the enterprise space, I think building a product, solving the problem. And then once you've done that, built a great team, then sales. And I think in the security space, trying to get to a million ARR, right? Just getting to a certain scale- >> So tell us about Centrify. When did you guys invest in those guys? Early, was it later on, which round did you guys- >> We invested, in the last round, so, uh, we were late stage investors, but we're very happy with the investment. They're doing very well. >> Awesome. Any other cool things you're working on that you'd like to share? >> We have taken apart AI, and started to look at transportation, so I think mapping is a little bit a part of that. It's also driving different industries, like e-commerce, IoT. We've looked at IoT. >> You must get a lot of this all the time, and I've got to ask you the same question, because I always get asked, "John, what is AI?" Now, I have two answers. Oh, AI's been around for a long time, but then there's a new AI. How do you answer that question? Because AI as a service essentially is software in the world paradigm, and it certainly is happening where you're going to start to see some significant software advances. But AI in and of itself is evolving. How do you describe AI as a service? How would you describe it to the layperson out there? >> I think, maybe its early stage, it's the team, and the technology. How many PhDs, you know, what are you looking at? What type of machine learns? That's, we have the more technical team. We build services. You know, my boss' boss is the head of services and he reports to the CTO of Docomo. His team and he, they look at that. Then on the other hand, though, I think its later stage, is vertical industries. Have people taken it apart, put it together, and then are monetizing that? So I think it's- >> John: It's a lot of machine learning. A lot of data-driven, So algorithms over data, or data over algorithms? Is there a philosophy there? I mean, that's a debate that people love to talk about. >> Maybe it depends on where you're applying it, who it's for, where do you get the data, how do you train the data? And, you know, what is the result? And are people happy with the result? I think the core infrastructure, I think once an AI company becomes hot, then it gets bought, and at that point, we all know who the players are. And people are probably looking for more and more of those, so I think those are harder to find. So then, like I've said, we've taken that apart, and maybe we've looked at mapping. What are maybe more the components underneath that that we can start to say this is going to be huge in the future? >> Yeah, and I think that's a great philosophy, too. If you look at how IBM has branded Waston, you could almost look at how successful that's been because people can get a mental model around that. And they've taken a similar approach, although I would say they've done very good on the vertical packaging. And a lot of work's going on, now, I think we're seeing down in the guts of the tech. I think there's a machine learning and more going on there, which is really cool. >> Which utilizes the cloud, right, and- >> That's where the power- >> That's where the power is. >> The compute. I mean Amazon has that. At the last re-invent, they announced the machine learning as a service. You're starting to see this now, where people can take a iterative approach to leveraging this AI as a service. I'm really impressed by that. Congratulations on a great strategy. I think that should be a winner. >> Yeah. Thank you. And that's going to be probably a core business model. I think other telcos should take notice of that. But maybe we shouldn't tell them we're alive. We can't put it back. Christina, thanks so much for coming in, appreciate it. Christina Ku, here, inside theCube. Special coverage of Mobile World Congress. Doing all the investments, checking out all the new business models, and really looking at AI as a service, and that really is cutting edge. That really is consistent with the data. It's theCube, we'll be right back with more after this short break. (tech music) (digital music)

Published Date : Feb 28 2017

SUMMARY :

Brought to you by Intel. and really breaking down the meaning in the investment community for a while. in kind of the software and services area and some of the things And the idea is to and how the AI as a service, at the consumer level. It's one of the hottest I guess since the days of i-mode, Because obviously that's the big story it for the Tokoyo Olympics. you can download a full HD movie. that are around the corner, the home is interesting. That is killer. So that the drone can other sensors on the network. and a drone will follow you categories of the hot trends I just associate, but you know, still, So I think AI, uh, you know, we had SIRI, of the deals that you do. a lot of the devops, or kind of and also just the threat detection from the perimeter, from the end point, really focused on the breech. to their party at the of like the white space. On the enterprise space, I think which round did you guys- We invested, in the last round, that you'd like to share? AI, and started to look and I've got to ask you the same question, and the technology. John: It's a lot of machine learning. What are maybe more the components in the guts of the tech. At the last re-invent, they announced checking out all the new business models,

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
AmazonORGANIZATION

0.99+

JohnPERSON

0.99+

Christina KuPERSON

0.99+

JapanLOCATION

0.99+

CyphortORGANIZATION

0.99+

ChristinaPERSON

0.99+

CentrifyORGANIZATION

0.99+

NTT DocomoORGANIZATION

0.99+

Tom KempPERSON

0.99+

AsiaLOCATION

0.99+

SoftBankORGANIZATION

0.99+

IBMORGANIZATION

0.99+

CaliforniaLOCATION

0.99+

NTT Docomo Ventures, IncORGANIZATION

0.99+

Silicon ValleyLOCATION

0.99+

Palo AltoLOCATION

0.99+

BarcelonaLOCATION

0.99+

NTT Docomo VenturesORGANIZATION

0.99+

NTT GroupORGANIZATION

0.99+

two daysQUANTITY

0.99+

NTT DocomoORGANIZATION

0.99+

last yearDATE

0.99+

TwitchORGANIZATION

0.99+

two companiesQUANTITY

0.99+

TokyoLOCATION

0.99+

RSAORGANIZATION

0.99+

KoreaLOCATION

0.99+

twoQUANTITY

0.99+

two officesQUANTITY

0.99+

#MWC17EVENT

0.99+

last weekDATE

0.99+

Two weeks agoDATE

0.99+

4500 square footQUANTITY

0.99+

first questionQUANTITY

0.99+

2005DATE

0.99+

Mobile World CongressEVENT

0.99+

Bay AreaLOCATION

0.99+

EchoCOMMERCIAL_ITEM

0.99+

two answersQUANTITY

0.99+

OneQUANTITY

0.99+

two fundsQUANTITY

0.99+

RSAEVENT

0.99+

8AMDATE

0.99+

Silicon ValleyLOCATION

0.98+

two hundredQUANTITY

0.98+

6DATE

0.98+

Sixty-million subscribersQUANTITY

0.98+

Jeff FrickPERSON

0.98+

oneQUANTITY

0.98+

DocomoORGANIZATION

0.98+

101 FreewayLOCATION

0.98+

firstQUANTITY

0.98+

Mobile World Congress 2017EVENT

0.98+

NTT SecurityORGANIZATION

0.98+

Mobile World CongressEVENT

0.98+

SIRITITLE

0.97+

FitbitORGANIZATION

0.97+

IntelORGANIZATION

0.97+

four categoriesQUANTITY

0.96+

first carrierQUANTITY

0.96+

WastonORGANIZATION

0.96+

this yearDATE

0.95+

AzureTITLE

0.95+

BayLOCATION

0.94+

one networkQUANTITY

0.94+

i-CubeORGANIZATION

0.92+

Mandy Dhaliwal & Tarkan Maner, Nutanix | HPE Discover 2022


 

>> Narrator: TheCUBE presents HPE Discover 2022. Brought to you by HPE. >> Welcome back to Las Vegas. Lisa Martin and Dave Vellante here bringing you day one of theCUBE's coverage of HPE Discover 22. We've had a lot of great conversations so far. Just a few hours in. We have two of our alumni back with us. Powerhouses, two powerhouses from Nutanix. Two for the price of one. Mandy Dhaliwal joins us. The CMO of 90 days at Nutanix. It's great to see you. Congratulations on the gig. >> Thanks Lisa. It's great to be here and great to be at Nutanix. >> Isn't it? And Tarkan Maner, the Chief Commercial Officer at Nutanix. Welcome back Tarkan. >> Great to see you guys. >> So this is only day one of the the main show Tarkan. We've been hearing a lot about cloud as an operating model. We've heard your CEO Rajiv talking about it. Break that down from Nutanix's point of view. >> Yeah, look at the end, the tech conference we are talking a lot technology but at the end it is all about outcomes. I saw Keith was here earlier, you know, GreenLake's story. We were on a session earlier. Everything is about business outcomes for the customers. And obviously our partner Ecosystems, NBC all these double technologies come together and become an open model. And our customers are moving from a CAPEX model, old school model, what I call dinosaur model, into an OPEX model, subscription model. Which Nutanix basically the category creator for this, in a hybrid multi-cloud fashion. One platform, one experience, any app, any user, anytime, and make it count. Let the customers focus on business outcomes. Let us deal with infrastructure for you. >> What are some of the key outcomes that you're seeing customers achieve? We've seen so much change in the last couple of years. >> Tarkan: Right. >> A lot of acceleration. >> Tarkan: Right. >> Every company has to be a data company today to compete. >> Right. >> What are some of the outcomes that you're really proud of? >> So look, at the end of the, day's it's all about digital transformation and it's a big loaded word. But at the end of the day every company is trying to get digitized. And hybrid multicloud is the only way to get there in a cost effective way. So that cost is a big story. Highly secure. Manageable, available, reliable, total cost ownership definitely depressed and take the complexity out. Let us deal with the infrastructure for you. You focus on your time to market, and the best applications for the best users. >> So Mandy, I remember, you know you talked about your category creator Tarkan, and I remember Stu Miniman and I, were in the Wikibon offices. We were just getting started and he said, "Dave you got to come in here." And Dhiraj was on the phone. They were describing this new category and I was blown away. I'm like, wow, that's like the cloud but you know, for on-prem. So what does the, what does the cloud operating model mean to Nutanix Mandy? >> Really, what we're trying to do is become this common cloud platform across Core, Edge and Cloud. We're known for our strength in HCI on premise. We have capability across. So it's really important for us to share this story with the market. Now, also one of the reasons I joined. You know this story needs to be told in a bigger fashion. So I'm here to really help evolve this category. We've won HCI, right? What's next? So stay tuned. >> So we call that super cloud. I call it. >> Yes, I love that name. >> So it, but it needs has meaning, right? >> Right. >> It's a new layer. It's not just, oh, I run on Azure. I run an Aw or running green. >> Mandy: Right. >> It's actually a common infrastructure. >> Yes. >> Common experience across maybe and even out to the edge. >> Mandy: Right. >> Right. So is, is that, do you guys see that or do you think this is just a little buzzword that Dave made up? >> No, I think it has legs. And I think at the core of it, it's simplicity and elegance. And if you look, and, and again, I'm drinking the the champagne, right? We have that we architected for that. We've solved that problem. So we now can extend it to become ubiquitous in the market. So it's, it's an amazing place to be because we've got the the scale, frankly, and the breadth now of the technology platform to be able to go deliver that super cloud. >> And you have to do the work, right? You, you, you have to hide all the complexity- >> Mandy: Yeah. >> Of whether it's AWS, Azure, Google, GreenLake wherever you go on prem. >> Mandy: Right. >> And not only that, as you know Dave, many people think about cloud, they automatically think about public cloud. AWS, Azure, or Google. Guess what? We have customers. Some of the workloads and apps running on a local country. If you're in Singapore, on Singtel, and your, if you're in Switzerland on Swisscom, if you're in Japan on NTT, guess what? Our cloud runs also on those clouds. For those customers who want the data, gravity, local issues with the security and privacy laws in the local country then all this SI you have HCI, Emphasis VIDPro, Accenture, CAPS, JAM, and ITCS. They have also cloud services. What we build as Mandy said as the creator, make the platform run anywhere. So the customers can move data, apps, workloads from cloud to cloud. From private to public and within public, from public to public. From AWS to Singtel. From Singtel to Swisscom to Azure, doesn't matter. We want to make sure one platform one experience, any app, any user. >> And at least a lot of those guys are building on OpenStack. We don't talk about OpenStack anymore. But a lot of the local telcos they actually it's alive and well and actually growing. >> So you, you make it sound simple. So I got to ask you as the chief marketing officer how do you message that simplicity and actually make it tangible for customers? >> That's a great question. It's really about the customer story, right? How do we share that we're able to take something that took months to deploy and have it done in in days, minutes, right? So there's a lot of those kinds of stories that you'll see across the platform coming. We're getting a lot more messaging around that. We're also tightening up the message to be more easily conveyed. So that's a lot of the stuff that I'm working on right now and really super excited. You know, we've got leading retailers, financial services institutions, public sector agencies that are running on our platform. So we've got this amazing cadre of customers and their stories just need to be told. >> That voice of the customer is so powerful. >> Mandy: Yep. >> As you well know Tarkan. That's, that's the objective voice right? That is ideally articulating your value proposition. >> Yeah. >> Validating that helping other customers understand this, these are the outcomes we are achieving. >> Mandy: Right? >> You can do the same. >> Mandy: Right. >> And, and different personas. >> Mandy: Right. >> It's not one customer fits all right. You heard Home Depot, Daniel with Antonio on the keynote. The stores, the distribution center, the warehousing and their service department, their mobile app all that data has to move from place to place. And we want to make sure it's cost effective. It's secure. And not only for the system, people like Daniel but also for application developers. Dave, you talked about, you know, Open Source, OpenStack, a lot of new application development is all open source. >> Mandy: Yep. >> And we need to also gear toward them and give them a platform, a hybrid multicloud platform. So they can build applications and then run applications and manage lifecycle applications anywhere in simple ways securely. So this platform is not only for running applications but also build a new set of digital transformation driven applications. >> So what are you doing with GreenLake especially in that context, right? 'Cause that's what we're looking for. Is like are people going to build applications on top. Maybe it's the incumbents. It might not be startups, but what what are you doing there? >> Right. So look, I'll give you the highlights on this. I know you talked to Keith again we had the session earlier. We have about 2000 plus customers. Customers are moving from a CapEx model to an OPEX model. They like the subscription side of the business and basically our strategy and many is leading this globally making cloud on your terms. So you have the control, you move from CapEx to OPEX and we bring the data in cloud to you. So you can manage the data securely, privately build your applications, and then they're ready. You can move applications based on microservices capabilities we deliver to different cloud as, as you wish. >> So then what are you hearing from customers? What are they most excited about right now given the massive potential that you're about to unleash? >> It it's really about best in class, right? So you get these these amazing technologies to come together. We abstract the complexity away for the customer. So HP GreenLake brings economic benefit. Nutanix brings experience. So you couple those two. And all of a sudden they've got time to value. Like they've never had before. Add on top of that the skills gap that we've got in the market, right? The new breed of folks that are deploying and managing these applications just don't have an appetite for complexity like they did in the old world. So we've got elegance, that's underpinning our architecture and simplicity and ease of use that learn that really translates into customer delight. So that's our secret sauce. >> You talk about time to value. Sorry, Dave. Time to value is no joke as a marketer. Talk to me about what does that mean from a translation perspective? Because these days, one of the things we learned in the pandemic, other than everyone had no patience and still probably doesn't is that access to realtime data no longer a, oh, it's awesome. It's Fanta, it's, it's table stakes. It is it's, what's going to help companies succeed. And those not. So from a time to value perspective, talk a little bit more about that as really impactful to every industry. >> Right, And, and, and underpin underpinning, all of it is that simplicity and ease of use, right? So if I can pick up and have portability across all aspects of my platform, guess what? I've got a single pane of glass that's that I'm able to manage my entire infrastructure through. That's really powerful. So I don't have to waste time doing an undifferentiated heavy lifting, all of a sudden there's huge value there in simplicity and ease of use, right? So it translates for things that would take months and you know, hundreds of developers all of a sudden you can vend out infrastructure in a way that's performant, reliable, scalable and all of a sudden, right? Everybody's happy. People are not losing sleep anymore because they know they've got a reliable way of deploying and managing and running their infrastructure. >> Perfect example for you very quick. Just is very exciting. Mandy and I, were in the session, Texas Children's Hospital. >> Yeah. >> Theresa Montag. I mean, Tonthat, she's the head of infrastructure, with Keith, with us you should listen to the patient care Pediatric, you know, oncology, realtime data. Hip regulation, highly regulated industry data. Gravity is super important. State laws, city laws, healthcare laws. The data cannot go to a public cloud service but has to be cloud driven, cloud enabled and data driven and eccentric on the site. But cloud operating model, Nutanix again with GreenLake, delivers a subscription methodology, a you know, OPEX model and delivers desktop service cloud native applications, supporting all these tools like epic all happening in healthcare. >> You guys have a high net promoter score. What, what got you there? And what's going to keep you there in the future. >> It's underpinned by the technology itself and also our outstanding support team right. We hear our competitors' customers call us for support first, before they call our competitors. If you can't take that to the bank, what can you, right. It's crazy. They, our customers tell us this >> Dave: Really? >> Really. >> It's pretty validating. >> Yeah. >> Yeah, help us with has help us with this XYZ stuff. Yeah. >> And it becomes even more important with this new cloud era. >> Yes. >> As you're moving the data, the applications to different places, they want the same experience. And look as a company, we spent the investment. It's not free. >> Mandy: Yeah. >> It costs us a lot of money to make that happen. One of the best support organizations I've been in industry for 30 years, I've never seen this kind of a maniacal focus on customer service. And without that success will not come. >> Yeah, I mean, I've met a lot of Nutanix customers at the various shows over the years. Ridden in taxis bus rides, you know, cocktail parties. They're, they're an interesting bunch, right. They, they were kind of leading edge early on. They saw the light bulb went off, they adopted. >> Right. >> Right, so, and think about thinking about aligning with where they're going where are they going and how is Nutanix aligning with them? >> There's, there's so much complexity in the world, right? So we're abstracting away the complexity. Not all workloads are meant to run in an either or situation. >> Right. >> Right, and we're hearing from IDC as well in, in, by 2026, 75% of workloads are going to be misplaced. How do they have a strategic partner? That's going to help them run their organization effectively and efficiently. We become that open and neutral player in the market. That can be the trusted advisor for them to help with workload placement optimization. They're standardizing, they're consolidating they're modernizing, they're transforming. There's a lot going on right. And so how do they come to somebody? That's voice of reason that also is well networked across the ecosystem. And that interoperability is key and yes, I'm still drinking the Kool-Aid, but it, I see it. It's, it's a tremendous story. >> Switzerland with weapons. (everyone laughing) >> You said it, you said it, Dave. >> And also one other thing it's important competition makes us better not bitter. >> Yeah. >> We have the best best partner network, 10,000 plus partners but more than numbers, quality, constantly working theater. And some of our partners also are competitors. We compete with them and we deliver solutions this way. Customers don't have to forklift out forklift in Nutanix. We leverage their past investment, current investment so they can tie Nutanix in different ways for different workloads, not one size fits all. We have multiple solutions, multiple ways you know, small, medium, large, extra large D in terms of scale and different workloads from the, you know Edge to the Cloud. And to at the end of the day to data as a whole, as you heard from HP today, our strategy, our roadmaps super aligned. That's why we were having a lot of success with GreenLake as well. >> Mandy, can you talk a last question about the partner ecosystem that Tarkan mentioned? How were you leveraging that to, to modify the messaging that you talked about? You've only been here almost 90 days. >> Mandy: Right. >> How is the partner ecosystem going to be a facilitator of the Nutanix brand and messaging and the reach? >> They're, they're tremendous, right? Because we're able to now, like we're doing here, right. Be able to reach into their customer base, and showcase our stories in a purpose built way right. This is, this is reality and solutions that we're driving for the customers with like-minded problems, like-minded people so they can see that. And so we do that across the, the ecosystem and all of a sudden, we've got this rolling thunder if you will. So it's up to us to, to, to really hone in on the right narrative and hand it to them and have them run with it that there's going to be practices built on this, even in a deeper way, moving forward. I see it, you know, we've done, I've done this before in my career. And so I've got conviction that we're on the right track and, you know, watch the space. >> Dot, dot, dot, to be continued. Watch the space. You heard it here on theCUBE. Mandy, Tarkan, thank you so much for joining Dave and me talking about the power of Nutanix with HPE, what you're doing and what you're enabling customers to achieve. It's transformative and, and best of luck. You'll have to come back in the next 90 days so we can see some of those customer stories. >> Absolutely. Absolutely, would love to, thank you. >> Thanks guys. >> Mandy: Yeah. For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE live from the show floor of HPE Discover 22. Day one coverage continues after a short break.

Published Date : Jun 28 2022

SUMMARY :

Brought to you by HPE. Congratulations on the gig. It's great to be here and And Tarkan Maner, the Chief of the the main show Tarkan. but at the end it is all about outcomes. in the last couple of years. Every company has to be a So look, at the end So Mandy, I remember, you know So I'm here to really So we call that super cloud. It's a new layer. maybe and even out to the edge. So is, is that, do you breadth now of the technology wherever you go on prem. Some of the workloads and apps But a lot of the local telcos So I got to ask you as the the message to be more customer is so powerful. That's, that's the objective voice right? Validating that helping And not only for the So they can build applications So what are you doing with GreenLake of the business and basically our strategy got in the market, right? of the things we learned So I don't have to waste time Perfect example for you very quick. and eccentric on the site. What, what got you there? the technology itself Yeah, help us with has And it becomes even more important data, the applications One of the best support at the various shows over the years. complexity in the world, right? And so how do they come to somebody? Switzerland with weapons. And also one other thing to data as a whole, as you that you talked about? on the right narrative and hand back in the next 90 days Absolutely, would love to, thank you. live from the show floor

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
DavePERSON

0.99+

Dave VellantePERSON

0.99+

Lisa MartinPERSON

0.99+

Theresa MontagPERSON

0.99+

LisaPERSON

0.99+

SingaporeLOCATION

0.99+

Mandy DhaliwalPERSON

0.99+

NBCORGANIZATION

0.99+

SwitzerlandLOCATION

0.99+

KeithPERSON

0.99+

JapanLOCATION

0.99+

NutanixORGANIZATION

0.99+

DanielPERSON

0.99+

RajivPERSON

0.99+

MandyPERSON

0.99+

Tarkan ManerPERSON

0.99+

twoQUANTITY

0.99+

HPORGANIZATION

0.99+

TarkanPERSON

0.99+

SingtelORGANIZATION

0.99+

SwisscomORGANIZATION

0.99+

30 yearsQUANTITY

0.99+

Las VegasLOCATION

0.99+

TwoQUANTITY

0.99+

Stu MinimanPERSON

0.99+

Home DepotORGANIZATION

0.99+

DhirajPERSON

0.99+

Texas Children's HospitalORGANIZATION

0.99+

One platformQUANTITY

0.99+

EcosystemsORGANIZATION

0.99+

AntonioPERSON

0.99+

10,000 plus partnersQUANTITY

0.99+

one experienceQUANTITY

0.99+

AWSORGANIZATION

0.99+

OPEXORGANIZATION

0.99+

75%QUANTITY

0.99+

hundredsQUANTITY

0.99+

HPEORGANIZATION

0.99+

theCUBEORGANIZATION

0.99+

oneQUANTITY

0.98+

CapExORGANIZATION

0.98+

GoogleORGANIZATION

0.98+

90 daysQUANTITY

0.98+

TheCUBEORGANIZATION

0.98+

NTTLOCATION

0.98+

GreenLakeORGANIZATION

0.98+

Kool-AidORGANIZATION

0.98+

TonthatPERSON

0.97+

OneQUANTITY

0.97+

2026DATE

0.97+

TarkanTITLE

0.97+

AccentureORGANIZATION

0.97+

OpenStackTITLE

0.97+

one platformQUANTITY

0.97+

Lisa Lorenzin, Zscaler | AWS re:Invent 2021


 

>>Welcome to the cubes, continuing coverage of AWS reinvent 2021. I'm your host, Lisa Martin. We are running one of the industry's most important and largest hybrid tech events of the year. This year with AWS and its ecosystem partners. We have two life studios, two remote studios, and over 100 guests. So stick around as we talk about the next 10 years of cloud innovation, I'm very excited to be joined by another Lisa from Zscaler. Lisa Lorenzen is here with me, the field CTO for the Americas. She's here to talk about ZScaler's mission to make doing business and navigating change a simpler, faster, and more productive experience. Lisa, welcome to the program. >>Thank you. It's a pleasure to be here. >>So let's talk about Zscaler in AWS. Talk to me about the partnership, what you guys are doing together. >>Yeah, definitely. Z scaler is a strategic security ISV partner with AWS. So we provide AWS customers with zero trust, secure remote access to AWS, and this can improve their security posture as well as their user experience with AWS. These scaler recently announced that we are the first and only cloud security service to achieve the FedRAMP PI authorization to operate. And that FedRAMP ZPA service is built on AWS gov cloud. ZScaler's also an AWS marketplace seller where our customers can purchase our zero trust exchange services as well as request or high value security assessments. We're excited about that as we're seeing a rapid increase in customer adoption as these scaler via the AWS marketplace, we vetted our software on AWS edge services that support emerging use cases, including 5g, IOT, and OT. So for example, Zscaler runs on wavelength, outposts, snowball and snowcones, and Zscaler has strategic partnerships with leading AWS service providers and system integration partners, including Verizon NTT, BT, Accenture, Deloitte, and many of the leading national and regional AWS consulting partners. >>Great summary there. So you mentioned something I want to get more understanding on this. It sounds like it's a differentiator for CSO scale. You said that you guys recently announced to the first and only cloud security service to achieve FedRAMP high. Uh, ATO built on AWS gov cloud. Talk to me about and what the significance of that is. >>I L five authorization to operate means that we are able to protect federal assets for the department of defense, as well as for the civilian agencies. It just extends the certification of our cloud by the government to ensure that we meet all of the requirements to protect that military side of the house, as well as the civilian side of the house. >>Got it super important there, let's talk about zero trust. It's a super hot topic. We've seen so many changes to the threat landscape during the pandemic. How are some of the ways that Z scaler and AWS are helping customers tackle this together? >>Well, I'd actually like to answer that by telling a little bit of a story. Um, Growmark is one of our Z scaler and AWS success stories when they had to send everyone home to work from home overnight, the quote that we had from is the users just went home and nothing changed. ZPA made work from anywhere, just work, and they were able to maintain complete business continuity. So even though their employers might have had poor internet service at home, or, you know, 80 challenging infrastructure, if you've got kids on your wifi bunch of kids in the neighborhood doing remote school, everyone's working from home, you don't have the reliability or the, maybe the bandwidth capacity that you would when you're sitting in an office. And Zscaler private access is a cloud delivered zero trust solution that leverages dynamic resilient, TLS encrypted tunnels to connect the user to an application rather than putting an end point on a network. >>And the reason that's important is it makes for a much more reliable and resilient service, even in environments that may not have the best connectivity I live out in the county. I really, some days think that there's a hamster on a wheel somewhere in my cable modem network, and I am a consumer of this, right. I connect to Z scaler over Zscaler private access, I'm protected by Zscaler internet access. And so I access our internal applications that are running in AWS as well this way. And it makes a huge difference. Growmark really started with an SAP migration to AWS, and this was long before the pandemic. So they started out looking for that better user experience and the zero trust capability. They were able to ensure that their SAP environment was dark to the internet, even though it was running in the cloud. And that put them in this position to leverage that zero trust service when the pandemic was upon us, >>That ability or that quote that you mentioned, it just worked was absolutely critical for all of us in every industry. And I'm sure a lot of folks who were trying to manage working from home, the spouses from home kids doing, you know, school online also felt like you with the hamster on the wheel, I'm sure their internet access, but being able to have that business continuity was table-stakes especially early on for most organizations. We saw a lot of digital transformation, a lot of acceleration of it in the last 20 months during the pandemic. Talk to me about how Z scaler helps customers from a digital transformation perspective and maybe what some of the things were that you saw in the last 20 months that have accelerated >>Absolutely. Um, another example, there would be Jefferson health, and really, as we saw during the pandemic, as you say, it accelerated a lot of the existing trends of mobility, but also migration to the cloud. And when you move applications to the cloud, honestly, it's a complex environment and maybe the controls and the risk landscape is not as well. Understood. So Z scaler also has another solution, which is our cloud security posture management. And this is really ensuring that your configuration on your environment, that those workloads run in is controlled, understood correctly, coordinated and configured. So as deference and health migrated to the cloud first model, they were able to leverage the scalers workload posture to measure and control that risk. Again, it's environment where the combination of AWS and Z scaler together gives them a flexible, resilient solution that they can be confident is correctly configured and thoroughly locked down. >>And that's critical for businesses in any organization, especially as quickly as how quickly things changed in the last 20 months or so I do wonder how your customer conversations have has changed as I introduced you as the field CTO of the America's proceeds killer. I'm sure you talk with a lot of customers. How has the security posture, um, zero trust? How has that risen up within the organizational chain? Is that something that the board is concerned about? >>My gosh, yes. And zero trust really has gone through the Gartner hype cycle. You've got the introduction, the peak of interest, the trough of despair, and then really rising back into what's actually feasible. Only zero trust has done that on a timeline of over a decade. When the term was first introduced, I was working with firewall VPN enact technology, and frankly, we didn't necessarily have the flexibility, the scalability, or the resilience to offer true zero trust. You can try to do that with network security controls, but when you're really protecting a user connecting to an application, you've got an abstraction layer mismatch. What we're seeing now is the reemergence of zero trust as a priority. And this was greatly accelerated honestly by the cybersecurity executive order that came out a few months ago from the Biden administration, which made zero trust a priority for the federal government and the public sector, but also raised visibility on zero trust for the private sector as well. >>When we're looking at zero trust as a way to perhaps ward off some of these high profile breaches and outages like the colonial pipeline, whole situation that was based on some legacy technology for remote access that was exploited and led to a breach that they had to take their entire infrastructure offline to mitigate. If we can look at more modern delivery mechanisms and more sophisticated controls for zero trust, that helps the board address a number of challenges ranging from obviously risk management, but also agility and cost reduction in an environment where more than ever belts are being tightened. New ways of delivering applications are being considered. But the ability to innovate is more important than ever. >>It is more important than ever the ability to innovate, but it really changing security landscape. I'm glad to hear that you're seeing, uh, this change as a result of the executive order that president Biden put down in the summer. That's good news. It sounds like there's some progress being made there, but we saw, you mentioned colonial pipeline. We saw a lot in the last 20, 22 months or so with ransomware becoming a household word, also becoming something that is a matter of when companies in any industry get hit and versus if it's no longer kind of that choice anymore. So talk to me about some of the threats and some of the stats that Z scaler has seen particularly in the last 20, 22 months. >>Oh gosh. Well, let's see. I'm just going to focus on the last 12 months, cause that's really where we've got some of the best data. We've seen a 500% increase in ransomware delivered over encrypted channels. And what that means is it's really critical to have scalable SSL inspection that can operate at wire speed without impeding the user experience or delay in critical projects, server communications, activities that need to happen without any introduced in any additional latency. So if you think about what that takes the Z scaler internet access solution is protecting users, outbound access in the same way that Zscaler private access protects access to private resources. So we're really seeing more and more organizations seeing that both of these services are necessary to deliver a comprehensive zero trust. You have to protect and control the outbound traffic to make sure that nothing good leaks out, nothing bad sneaks in. >>And at the same time, you have to protect and control the inbound traffic and inbound is, you know, a much broader definition with apps in the data center in the cloud these days. We're also seeing that 30% of malware is delivered through trusted applications like file shares or collaboration tools. So it's no longer enough to only inspect web traffic. Now you have to be able to really inspect all flavors of traffic when you're doing that outbound protection. So another good example where Z scaler and AWS work together here is in Amazon workspaces. And there's a huge trend towards desktop as a service, for example, and organizations are starting to recognize that they need to protect both the user experience and also the connectivity onward in Amazon workspaces, the same way that they would for a traditional end user device. So we see Z scaler running in the Amazon workspaces instances to protect that outbound traffic and control that inbound traffic as well. >>Another big area is the ransomware infections are not the problem. It's the result. So over half of the ransomware infections include data theft or leakage. And that is a double whammy because you get what's called double extortion where not only do you have to pay to unlock your machines, but you have to pay not to have that stolen data exposed to the rest of the world. So it's more important than ever to be able to break that kill chain as early as possible to ensure that the or the server traffic itself isn't exposed to the initial infection vector. If you do happen to get an infection vector that sneaks through, you need to be able to control the lateral movement so that it doesn't spread in your environment. And then if both of those controls fail, you also need the outbound protection such as CASBY and DLP to ensure that even if they get into the environment, they can't exfiltrate any of the data that they find as a result. We're seeing that the largest security risk today is lateral movement inside the corporate network. And that's one of the things that makes these ransomware double extortion situations, such a problem. >>Last question for you. And we've got about a minute left. I'm curious, you said over 50% of ransomware attacks are now double extortion. How do you guys help customers combat that? So >>We really deliver a solution that eliminates a lot of the attack surface and a lot of the risks. We have no inbound listener, unlike a traditional VPN. So the outbound only connections mean you don't have the external attack surface. You can write these granular policy controls to eliminate lateral movement. And because we integrate with customer's existing identity and access management, we can eliminate the credential exposure that can lead to a larger spread in a compromised environment. We also can eliminate the problem of unpatched gateways, which led to things like colonial pipeline or some of the other major breaches we've seen recently. And we can remove that single point of failure. So you can rely on dynamic optimized traffic distribution for all of these secure services. Basically, what we're trying to do is make it simpler and more secure at the same time, >>Simpler and more secure at the same time is what everyone needs regardless of industry. Lisa, thank you for joining me today, talking about Zscaler in AWS, zero trust the threat landscape that you're seeing, and also how's the scaler and AWS together can help customers mitigate those growing risks. We appreciate your insights and your thoughtfulness. >>Thank you >>For Lisa Lorenzen. I'm Lisa Martin. You're watching the cubes coverage of AWS reinvent stick around more great content coming up next.

Published Date : Nov 30 2021

SUMMARY :

We are running one of the industry's most important and largest It's a pleasure to be here. Talk to me about the partnership, what you guys are doing together. So we provide AWS customers with zero trust, secure remote access to AWS, You said that you guys recently announced to the first and only cloud of the requirements to protect that military side of the house, as well as the civilian side of the house. We've seen so many changes to the threat landscape during the pandemic. of kids in the neighborhood doing remote school, everyone's working from home, you don't have the reliability or in this position to leverage that zero trust service when the pandemic was upon us, it in the last 20 months during the pandemic. And when you move applications to the cloud, Is that something that the board is concerned the scalability, or the resilience to offer true zero trust. But the ability to innovate is more important It is more important than ever the ability to innovate, but it really changing security landscape. of these services are necessary to deliver a comprehensive zero trust. And at the same time, you have to protect and control the inbound traffic and inbound is, ensure that the or the server traffic itself isn't I'm curious, you said over 50% of ransomware So the outbound only connections mean you don't have the Lisa, thank you for joining me today, talking about Zscaler in AWS, zero trust the threat landscape more great content coming up next.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
AWSORGANIZATION

0.99+

Lisa LorenzenPERSON

0.99+

Lisa MartinPERSON

0.99+

DeloitteORGANIZATION

0.99+

Lisa LorenzinPERSON

0.99+

BTORGANIZATION

0.99+

30%QUANTITY

0.99+

500%QUANTITY

0.99+

AccentureORGANIZATION

0.99+

two remote studiosQUANTITY

0.99+

LisaPERSON

0.99+

firstQUANTITY

0.99+

AmazonORGANIZATION

0.99+

two life studiosQUANTITY

0.99+

oneQUANTITY

0.99+

over 100 guestsQUANTITY

0.99+

bothQUANTITY

0.99+

GartnerORGANIZATION

0.99+

over 50%QUANTITY

0.99+

This yearDATE

0.99+

BidenPERSON

0.99+

first modelQUANTITY

0.98+

2021DATE

0.98+

GrowmarkORGANIZATION

0.97+

single pointQUANTITY

0.97+

ZscalerORGANIZATION

0.97+

CASBYORGANIZATION

0.97+

zero trustQUANTITY

0.97+

pandemicEVENT

0.97+

todayDATE

0.97+

over a decadeQUANTITY

0.95+

AmericasLOCATION

0.94+

Verizon NTTORGANIZATION

0.94+

AmericaLOCATION

0.94+

ZscalerTITLE

0.91+

last 12 monthsDATE

0.91+

last 20 monthsDATE

0.9+

IOTTITLE

0.89+

80 challenging infrastructureQUANTITY

0.88+

a minuteQUANTITY

0.86+

last 20DATE

0.83+

ZPATITLE

0.83+

ATOORGANIZATION

0.82+

Z scalerTITLE

0.81+

JeffersonPERSON

0.81+

ZScalerORGANIZATION

0.81+

Monica Kumar & Tarkan Maner, Nutanix | CUBEconversation


 

(upbeat music) >> The cloud is evolving. You know, it's no longer a set of remote services somewhere off in the cloud, in the distance. It's expanding. It's moving to on-prem. On-prem workloads are connecting to the cloud. They're spanning clouds in a way that hides the plumbing and simplifies deployment, management, security, and governance. So hybrid multicloud is the next big thing in infrastructure, and at the recent Nutanix .NEXT conference, we got a major dose of that theme, and with me to talk about what we heard at that event, what we learned, why it matters, and what it means to customers are Monica Kumar, who's the senior vice president of marketing and cloud go-to-market at Nutanix, and Tarkan Maner, who's the chief commercial officer at Nutanix. Guys, great to see you again. Welcome to the theCUBE. >> Great to be back here. >> Great to see you, Dave. >> Okay, so you just completed another .NEXT. As an analyst, I like to evaluate the messaging at an event like this, drill into the technical details to try to understand if you're actually investing in the things that you're promoting in your keynotes, and then talk to customers to see how real it is. So with that as a warning, you guys are all in on hybrid multicloud, and I have my takeaways that I'd be happy to share, but, Tarkan, what were your impressions, coming out of the event? >> Look, you had a great entry. Our goal, as Monica is going to outline, too, cloud is not a destination. It's an operating model. Our customers are basically using cloud as a business model, as an operating model. It's not just a bunch of techno mumbo-jumbo, as, kind of, you outlined. We want to make sure we make cloud invisible to the customer so they can focus on what they need to focus on as a business. So as part of that, we want to make sure the workloads, the apps, they can run anywhere the way the customer wants. So in that context, you know, our entire story was bringing customer workloads, use-cases, partner ecosystem with ISVs and cloud providers and service providers and ISPs we're working with like Citrix on end user computing, like Red Hat on cloud native, and also bringing the right products, both in terms of infrastructure capability and management capability for both operators and application developers. So bringing all these pieces together and make it simple for the customer to use the cloud as an operating model. That was the biggest goal here. >> Great, thank you. Monica, anything you'd add in terms of your takeaways? >> Well, I think Tarkan said it right. We are here to make cloud complexity invisible. This was our big event to get thousands of our customers, partners, our supporters together and unveil our product portfolio, which is much more simplified, now. It's a cloud platform. And really have a chance to show them how we are building an ecosystem around it, and really bringing to life the whole notion of hybrid multicloud computing. >> So, Monica, could you just, for our audience, just summarize the big news that came out of .NEXT? >> Yeah, we actually made four different announcements, and most of them were focused around, obviously, our product portfolio. So the first one was around enhancements to our cloud platform to help customers build modern, software-defined data centers to speed their hybrid multicloud deployments while supporting their business-critical applications, and that was really about the next version of our flagship, AOS six, availability. We announced the general availability of that, and key features really included things like built-in virtual networking, disaster recovery enhancements, security enhancements that otherwise would need a lot of specialized hardware, software, and skills are now built into our platform. And, most importantly, all of this functionality being managed through a single interface, right? Which significantly decreases the operational overhead. So that was one announcement. The second announcement was focused around data services and really making it easy for customers to simplify data management, also optimize big data and database workloads. We announced capability that now improves performances of database workloads by 2x, big data workloads by 3x, so lots of great stuff there. We also announced a new service called Nutanix Data Lens, which is a new unstructured data governance service. So, again, I don't want to go into a lot of details here. Maybe we can do it later. That was our second big announcement. The third announcement, which is really around partnerships, and we'll talk more about that, is with Microsoft. We announced the preview of Nutanix Clusters and Azure, and that's really taking our entire flagship Nutanix platform and running it on Azure. And so, now, we are in preview on that one, and we're super excited about that. And then, last but not least, and I know Tarkan is going to go into a lot more detail, is we announced a strategic partnership with Citrix around the whole future of hybrid work. So lots of big news coming out of it. I just gave you a quick summary. There's a lot more around this, as well. >> Okay. Now, I'd like to give you my honest take, if you guys don't mind, and, Tarkan, I'll steal one of your lines. Don't hate me, okay? So the first thing I'm going to say is I think, Nutanix, you have the absolute right vision. There's no question in my mind. But what you're doing is not trivial, and I think it's going to play out. It's going to take a number of years. To actually build an abstraction layer, which is where you're going, as I take it, as a platform that can exploit all the respective cloud native primitives and run virtually any workload in any cloud. And then what you're doing, as I see it, is abstracting that underlying technology complexity and bringing that same experience on-prem, across clouds, and as I say, that's hard. I will say this: the deep dives that I got at the analyst event, it convinced me that you're committed to this vision. You're spending real dollars on focused research and development on this effort, and, very importantly, you're sticking to your true heritage of making this simple. Now, you're not alone. All the non-hyperscalers are going after the multicloud opportunity, which, again, is really challenging, but my assessment is you're ahead of the game. You're certainly focused on your markets, but, from what I've seen, I believe it's one of the best examples of a true hybrid multicloud-- you're on that journey-- that I've seen to date. So I would give you high marks there. And I like the ecosystem-building piece of it. So, Tarkan, you could course-correct anything that I've said, and I'd love for you to pick up on your comments. It takes a village, you know, you're sort of invoking Hillary Clinton, to bring the right solution to customers. So maybe you could talk about some of that, as well. >> Look, actually, you hit all the right points, and I don't hate you for that. I love you for that, as you know. Look, at the end of the day, we started this journey about 10 years ago. The last two years with Monica, with the great executive team, and overall team as a whole, big push to what you just suggested. We're not necessarily, you know, passionate about cloud. Again, it's a business model. We're passionate about customer outcomes, and some of those outcomes sometimes are going to also be on-prem. That's why we focus on this terminology, hybrid multicloud. It is not multicloud, it's not just private cloud or on-prem and non-cloud. We want to make sure customers have the right outcomes. So based on that, whether those are cloud partners or platform partners like HPE, Dell, Supermicro. We just announced a partnership with Supermicro, now, we're selling our software. HPE, we run on GreenLake. Lenovo, we run on TruScale. Big support for Lenovo. Dell's still a great partner to us. On cloud partnerships, as Monica mentioned, obviously Azure. We had a big session with AWS. Lots of new work going on with Red Hat as an ISV partner. Tying that also to IBM Cloud, as we move forward, as Red Hat and IBM Cloud go hand in hand, and also tons of workarounds, as Monica mentioned. So it takes a village. We want to make sure customer outcomes deliver value. So anywhere, for any app, on any infrastructure, any cloud, regardless standards or protocols, we want to make sure we have an open system coverage, not only for operators, but also for application developers, develop those applications securely and for operators, run and manage those applications securely anywhere. So from that perspective, tons of interest, obviously, on the Citrix or the UC side, as Monica mentioned earlier, we also just announced the Red Hat partnership for cloud services. Right before that, next we highlighted that, and we are super excited about those two partnerships. >> Yeah, so, when I talked to some of your product folks and got into the technology a little bit, it's clear to me you're not wrapping your stack in containers and shoving it into the cloud and hosting it like some do. You're actually going much deeper. And, again, that's why it's hard. You could take advantage of those things, but-- So, Monica, you were on the stage at .NEXT with Eric Lockhart of Microsoft. Maybe you can share some details around the focus on Azure and what it means for customers. >> Absolutely. First of all, I'm so grateful that Eric actually flew out to the Bay Area to be live on stage with us. So very super grateful for Eric and Azure partnership there. As I said earlier, we announced the preview of Nutanix Clusters and Azure. It's a big deal. We've been working on it for a while. What this means is that a select few organizations will have an opportunity to get early access and also help shape the roadmap of our offering. And, obviously, we're looking forward to then announcing general availability soon after that. So that's number one. We're already seeing tremendous interest. We have a large number of customers who want to get their hands on early access. We are already working with them to get them set up. The second piece that Eric and I talked about really was, you know, the reason why the work that we're doing together is so important is because we do know that hybrid cloud is the preferred IT model. You know, we've heard that in spades from all different industries' research, by talking to customers, by talking to people like yourselves. However, when customers actually start deploying it, there's lots of issues that come up. There's limited skill sets, resources, and, most importantly, there's a disparity between the on-premises networking security management and the cloud networking security management. And that's what we are focused on, together as partners, is removing that barrier, the friction between on-prem and Azure cloud. So our customers can easily migrate their workloads in Azure cloud, do cloud disaster recovery, create a burst into cloud for elasticity if they need to, or even use Azure as an on-ramp to modernize applications by using the Azure cloud services. So that's one big piece. The second piece is our partnership around Kubernetes and cloud native, and that's something we've already provided to the market. It's GA with Azure and Nutanix cloud platform working together to build Kubernetes-based applications, container-based applications, and run them and manage them. So there's a lot more information on nutanix.com/azure. And I would say, for those of our listeners who want to give it a try and who want their hands on it, we also have a test drive available. You can actually experience the product by going to nutanix.com/azure and taking the test drive. >> Excellent. Now, Tarkan, we saw recently that you announced services. You've got HPE GreenLake, Lenovo, their Azure service, which is called TruScale. We saw you with Keith White at HPE Discover. I was just with Keith White this week, by the way, face to face. Awesome guy. So that's exciting. You got some investments going on there. What can you tell us about those partnerships? >> So, look, as we talked through this a little bit, the HPE relationship is a very critical relationship. One of our fastest growing partnerships. You know, our customers now can run a Nutanix software on any HPE platform. We call it DX, is the platform. But beyond that, now, if the customers want to use HPE service as-a-service, now, Nutanix software, the entire stack, it's not only hybrid multicloud platform, the database capability, EUC capability, storage capability, can run on HPE's service, GreenLake service. Same thing, by the way, same way available on Lenovo. Again, we're doing similar work with Dell and Supermicro, again, giving our customers choice. If they want to go to a public club partner like Azure, AWS, they have that choice. And also, as you know, I know Monica, you're going to talk about this, with our GSI partnerships and new service provider program, we're giving options to customers because, in some other regions, HPE might not be their choice or Azure not be choice, and a local telco might the choice in some country like Japan or India. So we give options and capability to the customers to run Nutanix software anywhere they like. >> I think that's a really important point you're making because, as I see all these infrastructure providers, who are traditionally on-prem players, introduce as-a-service, one of the things I'm looking for is, sure, they've got to have their own services, their own products available, but what other ecosystem partners are they offering? Are they truly giving the customers choice? Because that's, really, that's the hallmark of a cloud provider. You know, if we think about Amazon, you don't always have to use the Amazon product. You can use actually a competitive product, and that's the way it is. They let the customers choose. Of course, they want to sell their own, but, if you innovate fast enough, which, of course, Nutanix is all about innovation, a lot of customers are going to choose you. So that's key to these as-a-service models. So, Monica, Tarkan mentioned the GSIs. What can you tell us about the big partners there? >> Yeah, definitely. Actually, before I talk about GSIs, I do want to make sure our listeners understand we already support AWS in a public cloud, right? So Nutanix totally is available in general, generally available on AWS to use and build a hybrid cloud offering. And the reason I say that is because our philosophy from day one, even on the infrastructure side, has been freedom of choice for our customers and supporting as large a number of platforms and substrates as we can. And that's the notion that we are continuing, here, forward with. So to talk about GSIs a bit more, obviously, when you say one platform, any app, any cloud, any cloud includes on-prem, it includes hyperscalers, it includes the regional service providers, as well. So as an example, TCS is a really great partner of ours. We have a long history of working together with TCS, in global 2000 accounts across many different industries, retail, financial services, energy, and we are really focused, for example, with them, on expanding our joint business around mission critical applications deployment in our customer accounts, and specifically our databases with Nutanix Era, for example. Another great partner for us is HCL. In fact, HCL's solution SKALE DB, we showcased at .NEXT just yesterday. And SKALE DB is a fully managed database service that HCL offers which includes a Nutanix platform, including Nutanix Era, which is our database service, along with HCL services, as well as the hardware/software that customers need to actually run their business applications on it. And then, moving on to service providers, you know, we have great partnerships like with Cyxtera, who, in fact, was the service provider partner of the year. That's the award they just got. And many other service providers, including working with, you know, all of the edge cloud, Equinix. So, I can go on. We have a long list of partnerships, but what I want to say is that these are very important partnerships to us. All the way from, as Tarkan said, OEMs, hyperscalers, ISVs, you know, like Red Hat, Citrix, and, of course, our service provider, GSI partnerships. And then, last but not least, I think, Tarkan, I'd love for you to maybe comment on our channel partnerships as well, right? That's a very important part of our ecosystem. >> No, absolutely. You're absolutely right. Monica. As you suggested, our GSI program is one of the best programs in the industry in number of GSIs we support, new SP program, enterprise solution providers, service provider program, covering telcos and regional service providers, like you suggested, OVH in France, NTT in Japan, Yotta group in India, Cyxtera in the US. We have over 50 new service providers signed up in the last few months since the announcement, but tying all these things, obviously, to our overall channel ecosystem with our distributors and resellers, which is moving very nicely. We have Christian Alvarez, who is running our channel programs globally. And one last piece, Dave, I think this was important point that Monica brought up. Again, give choice to our customers. It's not about cloud by itself. It's outcomes, but cloud is an enabler to get there, especially in a hybrid multicloud fashion. And last point I would add to this is help customers regardless of the stage they're in in their cloud migration. From rehosting to replatforming, repurchasing or refactoring, rearchitecting applications or retaining applications or retiring applications, they will have different needs. And what we're trying to do, with Monica's help, with the entire team: choice. Choice in stage, choice in maturity to migrate to cloud, and choice on platform. >> So I want to close. First of all, I want to give some of my impressions. So we've been watching Nutanix since the early days. I remember vividly standing around the conference call with my colleague at the time, Stu Miniman. The state-of-the-art was converged infrastructure, at the time, bolting together storage, networking, and compute, very hardware centric. And the founding team at Nutanix told us, "We're going to have a software-led version of that." And you popularized, you kind of created the hyperconverged infrastructure market. You created what we called at the time true private cloud, scaled up as a company, and now you're really going after that multicloud, hybrid cloud opportunity. Jerry Chen and Greylock, they just wrote a piece called Castles on the Cloud, and the whole concept was, and I say this all the time, the hyperscalers, last year, just spent a hundred billion dollars on CapEx. That's a gift to companies that can add value on top of that. And that's exactly the strategy that you're taking, so I like it. You've got to move fast, and you are. So, guys, thanks for coming on, but I want you to both-- maybe, Tarkan, you can start, and Monica, you can bring us home. Give us your wrap up, your summary, and any final thoughts. >> All right, look, I'm going to go back to where I started this. Again, I know I go back. This is like a broken record, but it's so important we hear from the customers. Again, cloud is not a destination. It's a business model. We are here to support those outcomes, regardless of platform, regardless of hypervisor, cloud type or app, making sure from legacy apps to cloud native apps, we are there for the customers regardless of their stage in their migration. >> Dave: Right, thank you. Monica? >> Yeah. And I, again, you know, just the whole conversation we've been having is around this but I'll remind everybody that why we started out. Our journey was to make infrastructure invisible. We are now very well poised to helping our customers, making the cloud complexity invisible. So our customers can focus on business outcomes and innovation. And, as you can see, coming out of .NEXT, we've been firing on all cylinders to deliver this differentiated, unified hybrid multicloud platform so our customers can really run any app, anywhere, on any cloud. And with the simplicity that we are known for because, you know, our customers love us. NPS 90 plus seven years in a row. But, again, the guiding principle is simplicity, portability, choice. And, really, our compass is our customers. So that's what we are focused on. >> Well, I love not having to get on planes every Sunday and coming back every Friday, but I do miss going to events like .NEXT, where I meet a lot of those customers. And I, again, we've been following you guys since the early days. I can attest to the customer delight. I've spent a lot of time with them, driven in taxis, hung out at parties, on buses. And so, guys, listen, good luck in the next chapter of Nutanix. We'll be there reporting and really appreciate your time. >> Thank you so much. >> Thank you so much, Dave. >> All right, and thank you for watching, everybody. This is Dave Vellante for theCUBE, and, as always, we'll see you next time. (light music)

Published Date : Sep 23 2021

SUMMARY :

and at the recent and then talk to customers and also bringing the right products, terms of your takeaways? and really bringing to just summarize the big news So the first one was around enhancements So the first thing I'm going to say is big push to what you just suggested. and got into the technology a little bit, and also help shape the face to face. and a local telco might the choice and that's the way it is. And that's the notion but cloud is an enabler to get there, and the whole concept was, We are here to support those outcomes, Dave: Right, thank you. just the whole conversation in the next chapter of Nutanix. and, as always, we'll see you next time.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
MonicaPERSON

0.99+

DellORGANIZATION

0.99+

Monica KumarPERSON

0.99+

EricPERSON

0.99+

Dave VellantePERSON

0.99+

TarkanPERSON

0.99+

SupermicroORGANIZATION

0.99+

DavePERSON

0.99+

FranceLOCATION

0.99+

MicrosoftORGANIZATION

0.99+

Hillary ClintonPERSON

0.99+

NutanixORGANIZATION

0.99+

Stu MinimanPERSON

0.99+

Eric LockhartPERSON

0.99+

AWSORGANIZATION

0.99+

AmazonORGANIZATION

0.99+

LenovoORGANIZATION

0.99+

Keith WhitePERSON

0.99+

HPEORGANIZATION

0.99+

Tarkan ManerPERSON

0.99+

IndiaLOCATION

0.99+

Christian AlvarezPERSON

0.99+

HCLORGANIZATION

0.99+

CitrixORGANIZATION

0.99+

firstQUANTITY

0.99+

second pieceQUANTITY

0.99+

JapanLOCATION

0.99+

secondQUANTITY

0.99+

Keith WhitePERSON

0.99+

Red HatORGANIZATION

0.99+

USLOCATION

0.99+

CyxteraORGANIZATION

0.99+

HPETITLE

0.99+

3xQUANTITY

0.99+

last yearDATE

0.99+

seven yearsQUANTITY

0.99+

yesterdayDATE

0.99+

bothQUANTITY

0.99+

thousandsQUANTITY

0.99+

second announcementQUANTITY

0.99+

EquinixORGANIZATION

0.99+

TCSORGANIZATION

0.99+

AzureORGANIZATION

0.99+

Bay AreaLOCATION

0.99+

two partnershipsQUANTITY

0.99+

Nutanix ClustersORGANIZATION

0.99+

UCORGANIZATION

0.98+

one announcementQUANTITY

0.98+

over 50 new service providersQUANTITY

0.98+

Walter Bentley and Jason Smith, Red Hat | AnsibleFest 2020


 

(upbeat music) >> Narrator: From around the globe, it's theCUBE with digital coverage of Ansible Fest 2020 brought to you by Red Hat. >> Welcome back to theCUBE's coverage, Cube virtual's coverage of Ansible Fest 2020 virtual. We're not face to face this year. I'm your host John Furrier with theCube. We're virtual, this theCube virtual and we're doing our part, getting the remote interviews with all the best thought leaders experts and of course the Red Hat experts. We've got Walter Bentley, Senior Manager of Automation practice with Red Hat and Jason Smith, Vice President of North American services, back on theCube. We were in Atlanta last year in person. Guys, thanks for coming on virtually. Good morning to you. Thanks for coming on. >> Good morning John. Good morning, good morning. >> So since Ansible Fest last year a lot's happened where she's living in seems to be an unbelievable 2020. Depending on who you talk to it's been the craziest year of all time. Fires in California, crazy presidential election, COVID whole nine yards, but the scale of Cloud has just unbelievably moved some faster. I was commenting with some of your colleagues around the snowflake IBO it's built on Amazon, right? So value is changed, people are shifting, you starting to clear visibility on what these modern apps are looking like, it's Cloud native, it's legacy integrations, it's beyond lift and shift as we've been seeing in the business. So I'd love to get, Jason we'll start with you, your key points you would like people to know about Ansible Fest 2020 this year because there's a lot going on this year because there's a lot to build on and there's a tailwind for Cloud native and customers have to move fast. What's your thoughts? >> Yeah so, a lot has happened since last year and customers are looking to be a lot more selective around their automation technologies. So they're not just looking for another tool. They're really looking for an automation platform, a platform that they can leverage more of an enterprise strategy and really be able to make sure that they have something that's secure, scalable, and they can use across the enterprise to be able to bring teams together and really drive value and productivity out of their automation platform. >> What's the key points in the customers and our audience around the conversations around the learning, that's the new stuff happening in using Ansible this year? What are the key top things, Jason? Can you comment on what you're seeing the big takeaway for our audience watching? >> Yeah, so a lots change like you said, since last year. We worked with a lot of customers around the world to implement Ansible and automation at scale. So we're using our automation journeys as we talked about last year and really helping customers lay out a more prescriptive approach on how they're going to deliver automation across their enterprise. So customers are really working with us because we're working with the largest customers in the world to implement their strategies. And when we work with new customers we can bring those learnings and that experience to them. So they're not having to learn that for the first time and figure it out on their own, but they're really able to learn and leverage the experience we have through hundreds of customers and at enterprise scale and can take the value that we can bring in and help them through those types of projects much more quickly than they could on their own. >> It's interesting. We were looking at the research numbers and look at the adoption of what Ansible's doing and you guys are with Red Hat it's pretty strong. Could you share on the services side because there's a lot of services going on here? Not just network services and software services, just traditional services. What are the one or two reasons why customer engaged with Red Hat services? What would that be? >> Yeah so, like I said, I mean, we bring that experience. So customers that typically might have to spend weeks troubleshooting and making decisions on how they're going to deliver their implementations, they can work with us and we can bring those best practices in and allow them to make those decisions and implement those best practices within hours instead of weeks, and really be able to accelerate their projects. Another thing is we're a services company as part of a product company. So we're not there just to deliver services. We're really focused on the success of the customer, leveraging our technologies. So we're there to really train and mentor them through the process so that they're really getting up to speed quickly. They're taking advantage of all of the expertise that we have to be able to build their own experience and expertise. So they can really take over once we're gone and be able to support and advance that technology on their own. So they're really looking to us to not only implement those technologies for them, but really with them and be able to train and mentor them. Like I said, and take advantage of those learnings. We also help them. We don't just focus on the technologies but really look at the people in process side of things. So we're bringing in a lot of principles from DevOps and Agile on open practices and helping customers really transform and be able to do things in a new way, to be much more efficient, a lot more agile, be able to drive a lot more value out of our technology. >> Walter, I got to ask you, last year we were chatting about this, but I want to get the update. And I'd like you to just give us a quick refresh definition about the automation adoption journey because this is a real big deal. I mean, we're looking at the trends. Everyone realizes automation is super important at scale, as you think about whether it's software data, anything's about automation it's super important, but it's hard. I mean, the marketplace we were looking at the numbers. I was talking to IDC for you guys at this festival and of Ansible Fest, and they said about five to 10% of enterprises are containerized, which means this huge wave coming of containerization. This is about the automation adoption journey because you start containerizing, (laughs) right? You start looking at the workflows on the pipelinig and how the codes being released and everything. This is important stuff. Give us the update on the automation adoption journey and where it is in the portfolio. >> Well, yeah, just as you called it out, last year on main stage and Ansible fest, almost every customer expressed the need and desire to have to have a strategy as to how they drive their adoption of automation inside their enterprise. And as we've gone over the past few months of splitting this in place with many customers, what we've learned is that many customers have matured into a place where they are now looking at the end to end workflow. Instead of just looking at the tactical thing that they want to automate, they are actually looking at the full ribbon, the full workflow and determining are there changes that need to be made and adjusted to be more efficient when it comes to dealing with automation. And then the other piece as we alluded to already is the contagious nature of that adoption. We're finding that there are organizations that are picking up the automation adoption journey, and because of the momentum it creates inside of that organization we're finding other municipalities that are associated with them are now also looking to be able to take on the journey because of that contagious nature. So we can see that how it's spreading in a positive way. And we're really looking forward to being able to do more of it as the next quarter and the next year comes up. >> Yeah, and that whole sharing thing is a big part of the content theme and the community thing. So great reference on that, good thing is word of mouth and community and collaboration is a good call out there. A quick question for you, you guys recently had a big win with NTT DoCoMo and their engagement with you guys on the automation, adoption journey. Walter, what were some of the key takeaways? Jason you can chime in too I'd like to get some specifics around where it's been successful >> To me, that customer experience was one that really was really exciting, primarily because we learned very early on that they were completely embodying that open source culture and they were very excited to jump right in and even went about creating their own community of practice. We call them communities of practice. You may know them as centers of excellence. They wanted to create that very early in increment, way before we were even ready to introduce it. And that's primarily because they saw how being able to have that community of practice in place created an environment of inclusion across the organization. They had legacy tools in place already, actually, there was a home grown legacy tool in place. And they very quickly realized that it didn't need to remove that tool, they just needed to figure out a way of being able to how to optimize and streamline how they leverage it and also be able to integrate it into the Ansible automation platform. Another thing I wanted to very quickly note is that they very quickly jumped onto the idea of being able to take those large workflows that they had and breaking them up into smaller chunks. And as you already know, from last year when we spoke about it, that's a pivotal part of what the automation adoption journey brings to our organization. So to sum it all up, they were all in, automation first mindset is what that was driving them. And all of those personas, all of those personal and cultural behaviors are what really helped drive that engagement to be very successful. >> Jason, we'll get your thoughts on this because again, Walter brought up last year's reference to breaking things up into modules. We look at this year's key news it's all about collections. You're seeing content is a big focus, content being not like a blog post or a media asset. Like this is content, but code is content. It's sharing. If it's being consumed by other people, there's now community. You're seeing the steam of enabling. I mean, you're looking at successes, like you guys are having with NTT DoCoMo and others. Once people realize there's a better way and success is contagious, as Walter was saying, you are now enabling new ways to do things faster at scale and all that good stuff has been go check out the keynotes. You guys talk about it all day long with the execs. But I want to learn, right? So when you enable success, people want to be a part of it. And I could imagine there's a thirst and demand for training and the playbooks and all the business models, innovations that's going on. What are you seeing for people that want to learn? Is there training? Is there certifications? Because once you get the magic formula as Walter pointed out, and we all know once people see what success looks like, they're going to want to duplicate it. So as this wave comes, it's like having the new surfboard. I want to surf that wave. So what's the update on Ansible's training, the tools, how do I learn, it's a certification of all. Just take a minute to explain what's going on. >> Yeah, so it's been a crazy world as we've talked about over the last six, seven months here, and we've really had to adapt ourselves and our training and consulting offerings to be able to support our remote delivery models. So we very, very quickly back in the March timeframe, we're able to move our consultants to a remote work force and really implement the tools and technologies to be able to still provide the same value to customers remotely as we have in person historically. And so it's actually been really great. We've been able to make a really seamless transition and actually our C-SAT net promoter scores have actually gone up over the last six months or so. So I think we've done a great job being able to still offer the same consulting capabilities remotely as we have onsite. And so that's obviously with a real personal touch working hand in hand with our customers to deliver these solutions. But from a training perspective, we've actually had to do the same thing because customers aren't onsite, they can't do in person training. We've been able to move our training offerings to completely virtual. So we're continuing to train our customers on Ansible and our other technologies through a virtual modality. And we've also been able to take all of our certifications and now offer those remotely. So as, whereas customers historically, would have had to gone into a center and get those certifications in person, they can now do those certifications remotely. So all of our training offerings and consulting offerings are now available remotely as well as they were in person in the past and will be hopefully soon enough, but it's really not-- >> You would adopt to virtual. >> Excuse me. >> You had to adopt to the virtual model quickly for trainings. >> Exactly. >> What about the community role? What's the role of the community? You guys have a very strong community. Walter pointed out the sharing aspect. Well, I pointed out he talked about the contagious people are talking. You guys have a very robust community. What's the role of community in all of this? >> Yeah, so as Walter said, we have our communities a practice that we use internally we work with customers to build communities of practice, which are very much like a centers of excellence, where people can really come together and share ideas and share best practices and be able to then leverage them more broadly. So, whereas in the past knowledge was really kept in silos, we're really helping customers to build those communities and leverage those communities to share ideas and be able to leverage the best practices that are being adopted more broadly. >> That's awesome. Yeah, break down those silos of course. Open up the data, good things will happen, a thousand flowers bloom, as we always say. Walter, I want to get your thoughts on this collection, what that enables back to learning and integrations. So if collections are going to be more pervasive and more common place the ability to integrate, we were covering for VMware world, there's a VMware module collection, I should say. What are customers doing when you integrate in cross technology parties because now obviously customers are going to have a lot of choice and options. If I'm an integration partner, it's all about Cloud native and the kinds of things we're talking about, you're going to have a lot of integration touch points. What's the most effective way for customers integrating other technology partners into Ansible? >> And this is one of the major benefits that came out of the announcement last year with the Ansible automation platform. The Anible automation platform really enables our customers to not just be able to do automation, but also be able to connect the dots or be able to connect other tools, such as other ITM SM tools or be able to connect into other parts of their workflows. And what we're finding in breaking down really quickly is two things. Collections obviously, is a huge aspect. And not just necessarily the collections but the automation service catalog is really where the value is because that's where we're placing all of these certified collections and certified content that's certified by Red Hat now that we create alongside with these vendors and they're unavailable to customers who are consuming the automation platform. And then the other component is the fact that we're now moved into a place where we now have something called the automation hub. which is very similar to galaxy, which is the online version of it. But the automation hub now is a focus area that's dedicated to a customer, where they can store their content and store those collections, not just the ones that they pull down that are certified by Red hat, but the ones that they create themselves. And the availability of this tool, not only just as a SaaS product, but now being able to have a local copy of it, which is brand new out of the press, out of the truck, feature is huge. That's something that customers have been asking for a very long time and I'm very happy that we're finally able to supply it. >> Okay, so backup for a second, rewind, fell off the truck. What does that mean? It's downloadable. You're saying that the automation hub is available locally. Is that what-- >> Yes, Sir. >> So what does that mean for the customer? What's the impact for them? >> So what that means is that previously, customers would have to connect into the internet. And the automation hub was a SaaS product, meaning it was available via the internet. You can go there, you can sync up and pull down content. And some customers prefer to have it in house. They prefer to have it inside of their firewall, within their control, not accessible through the internet. And that's just their preferences obviously for sometimes it's for compliance or business risk reasons. And now, because of that, we were able to meet that ask and be able to make a local version of it. Whereas you can actually have automation hub locally your environment, you can still sync up data that's out on the SaaS version of automation hub, but be able to bring it down locally and have it available with inside of your firewall, as well as be able to add your content and collections that you create internally to it as well. So it creates a centralized place for you to store all of your automation goodness. >> Jason, I know you got a hard stop and I want to get to you on the IBM question. Have you guys started any joint service engages with IBM? >> Yeah, so we've been delivering a lot of engagements jointly through IBM. We have a lot of joint customers and they're really looking for us to bring the best of both Red Hat services, Red Hat products, and IBM all together to deliver joint solutions. We've actually also worked with IBM global technology services to integrate Ansible into their service offerings. So they're now really leveraging the power of Ansible to drive lower cost and more innovation with our customers and our joint customers. >> I think that's going to be a nice lift for you guys. We'll get into the IBM machinery. I mean, you guys got a great offering, you always had great reviews, great community. I mean, IBM's is just going to be moving this pretty quickly through the system, I can imagine. What's some of the the feedback so far? >> Yeah, it's been great. I mean, we have so many, a large joint customers and they're helping us to get to a lot of customers that we were never able to reach before with their scale around the world. So it's been great to be able to leverage the IBM scale with the great products and services that Red Hat offers to really be able to take that more broadly and continue to drive that across customers in an accelerated pace. >> Well, Jason, I know you've got to go. We're going to stay with Walter while you drop off, but I want to ask you one final question. For the folks watching or asynchronously coming in and out of Ansible Fest 2020 this year. What is the big takeaway that you'd like to share? What is the most important thing people should pay attention to? Well, a couple things it don't have to be one thing, do top three things. what should people be paying attention to this year? And what's the most important stories that you should highlight? >> Yeah, I think there's a lot going on, this technology is moving very quickly. So I think there's a lot of great stories. I definitely take advantage of the customer use cases and hearing how other customers are leveraging Ansible for automation. And again really looking to not use it just as a tool, but really in an enterprise strategy that can really change their business and really drive cost down and increase revenues by leveraging the innovation that Ansible and automation provides. >> Jason, thank you for taking the time. Great insight. Really appreciate the commentary and hopefully we'll see you next year in person Walter. (all talking simultaneously) Walter, let's get back to you. I want to get into this use case and some of the customer feedback, love the stories. And we look, we'd love to get the new data, we'd love to hear about the new products, but again, success is contagious, you mentioned that I want to hear the use cases. So a lot of people have their ear to the ground, they look up the virtual environments, they're learning through new ways, they're looking for signals of success. So I got to ask you what are the things that you're hearing over and over again, as you guys are spinning up engagements? What are some of the patterns that are emerging that are becoming a trend in terms of what customers are consistently doing to overcome some of their challenges around automation? >> Okay, absolutely. So what we're finding is that over time that customers are raising the bar on us. And what I mean by that is that their expectations out of being able to take on tools now has completely changed and specifically when we're talking around automation. Our customers are now leading with the questions of trying to find out, well, how do we reduce our operational costs with this automation tool? Are we able to increase revenue? Are we able to really truly drive productivity and efficiency within our organization by leveraging it? And then they dovetail into, "Well, are we able to mitigate business risk, "even associated with leveraging this automation tool?" So as I mentioned, customers are up leveling what their expectations are out of the automation tools. And what I feel very confident about is that with the launch of the Ansible automation platform we're really able to be able to deliver and show our customers how they're able to get a return on their investment, how by taking part and looking at re-working their workflows how we're able to bring productivity, drive that efficiency. And by leveraging it to be able to mitigate risks you do get the benefits that they're looking for. And so that's something that I'm very happy that we were able to rise to the occasion and so far so good. >> Last year I was very motivated and very inspired by the Ansible vision and content product progress. Just the overall vibe was good, community of the product it's always been solid, but one of the things that's happening I want to get your commentary and reaction to this is that, and we've been riffing on this on theCube and inside the community is certainly automation, no brainer, machine learning automation, I mean, you can't go wrong. Who doesn't want automation? That's like saying, "I want to watch more football "and have good food and good wifi. I mean, it's good things, right? Automation is a good thing. So get that. But the business model issues you brought up ROI from the top of the ivory tower and these companies, certainly with COVID, we need to make money and have modern apps. And if you try to make that sound simple, right? X as a service, SaaS everything is a service. That's easy to say, "Hey, Walter, make everything as a service." "Got it, boss." Well, what the hell do you do? I mean, how do you make that happen? You got Amazon, you got Multicloud, you got legacy apps. You're talking about going in and re-architecting the application development process. So you need automation for the business model of everything as a service. What's your reaction to that? Because it's very complicated. It's doable. People are getting there but the Nirvana is, everything is a service. This is a huge conversation. I mean, it's really big, but what's your reaction to that when I bring that up. >> Right. And you're right, it is a huge undertaking. And you would think that with the delivery of COVID into our worlds that many organizations would probably shy away from making changes. Actually, they're doing the opposite. Like you mentioned, they're running towards automation and trying to figure out how do they optimize and be able to scale, based on this new demand that they're having, specifically new virtual demand. I'm happy you mentioned that we actually added something to the automation adoption journey to be able to combat or be able to solve for that change. And being able to take on that large ask of everything as a service, so to speak. And increment zero at the very beginning of the automation adoption journey we added something called navigate. And what navigate is, is it's a framework where we would come in and not just evaluate what they want to automate and bring that into a new workflow, but we evaluate what they already have in place, what automation they have in place, as well as the manual tasks and we go through, and we try to figure out how do you take that very complex, large thing and stream it down into something that can be first off determined as a service and made available for your organization to consume, and as well as be able to drive the business risks or be able to drive your business objectives forward. And so that exercise that we're now stepping our customers through makes a huge difference and puts it all out in front of you so that you can make decisions and decide which way you want to go taking one step at a time. >> And you know it's interesting, great insight, great comment. I think this is really where the dots are going to connect over the next few years. Everything is as a service. You got to lay the foundation. But if you really want to get this done I got to ask you the question around Ansible's ability to integrate and implement with other products. So could you give an examples of how Ansible has integrated and implemented with other Red Hat products or other types of technology vendors products? >> Right. So one example that always pops to the top of my head and I have to give a lot of credit to one of my managing architects who was leading this effort. Was the simple fact that you when you think about a mainframe, right? So now IBM is our new family member. When you think about mainframes, you think about IBM and it just so happens that there's a huge ask and demand and push around being able to automate ZOS mainframe. And IBM had already embarked on the path of determining, well, can this be done with Ansible? And as I mentioned before, my managing architect partnered up with the folks on IBM's side, so the we're bringing in Red Hat consulting, and now we have IBM and we're working together to move that idea forward of saying, "Hey, you can automate things with the mainframe." So think about it. We're in 2020 now in the midst of a new normal. And now we're thinking about and talking about automating mainframes. So that just shows how things have evolved in such a great way. And I think that that story is a very interesting one. >> It's so funny the evolution. I'm old enough to remember. I came out of college in the 80s and I would look at the old mainframe guys who were like "You guys are going to be dinosaurs." They're still around. I mean, some of the banking apps, I mean some of them are not multi threaded and all the good stuff, but they are powering, they are managing a workload, but this is the beautiful thing about Cloud. And some of the Cloud activities is that you can essentially integrate, you don't have to replace the old to bring in the new. This has been a common pattern. This is where containers, microservices, and Cloud has been a dream state because you can essentially re layer and glue it together. This is a big deal. What's your reaction to that? >> No, it's a huge deal. And the reality is, is that we need all of it. We need the legacy behaviors around infrastructure. So we need the mainframe still because they has a distinct purpose. And like you mentioned, a lot of our FSI customers that is the core of where a lot of their data and performance comes out of. And so it's not definitely not a pull out and replace. It's more of how they integrate and how can you streamline them working together to create your end to end workflow. And as you mentioned, making it available to your organizations to consume as a service. So definitely a fan of being able to integrate and add to and everything has a purpose. Is what we're coming to learn. >> Agility, the modern application, horizontal scalability, Cloud is the new data center. Walter great insights, always great to chat with you. You always got some good commentary. I want to ask you one final question. I asked Jason before he dropped off. Jason Smith, who was our guest here and hit a hard stop. What is the most important story that people should pay attention to this year at Ansible Fest? Remember it's virtual, so there's going to be a lot of content around there, people are busy, it's asynchronous consumption. What should they pay attention to from a content standpoint, maybe some community sizes or a discord group? I mean, what should people look at in this year? What should they walk away with as a key message? Take a minute to share your thoughts. >> Absolutely. Absolutely key messages is that, kind of similar to the message that we have when it comes down to the other circumstances going on in the world right now, is that we're all in this together. As an Ansible community, we need to work together, come together to be able to share what we're doing and break down those silos. So that's the overall theme. I believe we're doing that with the new. So definitely pay attention to the new features that are coming out with the Ansible automation platform. I alluded to the on-prem automation hub, that's huge. Definitely pay attention to the new content that is being released in the service catalog. There's tons of new content that focus on the ITSM and a tool. So being able to integrate and leverage those tools then the easier math model, there's a bunch of network automation advances that have been made, so definitely pay attention to that. And the last teaser, and I won't go into too much of it, 'cause I don't want to steal the thunder. But there is some distinct integrations that are going to go on with OpenShift around containers and the SQL automation platform that you definitely are going to want to pay attention to. If anyone is running OCP in their environment they definitely going to want to pay attention to this. Cause it's going to be huge. >> Private cloud is back, OpenStack is back, OCP. You got OpenShift has done really well. I mean, again, Cloud has been just a great enabler and bringing all this together for developers and certainly creating more glue, more abstractions, more automation, infrastructure is code is here. We're excited for it Walter, great insight. Great conversation. Thank you for sharing. >> No, it's my pleasure. And thank you for having me. >> I'm John Furrier with theCube, your host for theCube virtual's, part of Ansible Fest, virtual 2020 coverage. Thanks for watching. (gentle upbeat music)

Published Date : Oct 2 2020

SUMMARY :

brought to you by Red Hat. and of course the Red Hat experts. Good morning John. and customers have to move fast. and really be able to make sure and that experience to them. and look at the adoption and really be able to and how the codes being and because of the momentum it creates and their engagement with you guys and also be able to integrate it and the playbooks and and technologies to be able to You had to adopt to What about the community role? and be able to leverage the best practices the ability to integrate, that came out of the You're saying that the automation and be able to make a local version of it. and I want to get to to drive lower cost and more innovation I mean, IBM's is just going to and continue to drive We're going to stay with And again really looking to So I got to ask you what are the things And by leveraging it to and reaction to this of everything as a service, so to speak. the dots are going to connect and I have to give a lot of credit the old to bring in the new. and add to and everything has a purpose. that people should pay attention to that are going to go on with and bringing all this And thank you for having me. I'm John Furrier with theCube,

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
JasonPERSON

0.99+

WalterPERSON

0.99+

IBMORGANIZATION

0.99+

Jason SmithPERSON

0.99+

oneQUANTITY

0.99+

AtlantaLOCATION

0.99+

JohnPERSON

0.99+

John FurrierPERSON

0.99+

AnsibleORGANIZATION

0.99+

Red HatORGANIZATION

0.99+

last yearDATE

0.99+

2020DATE

0.99+

Walter BentleyPERSON

0.99+

AmazonORGANIZATION

0.99+

MarchDATE

0.99+

Last yearDATE

0.99+

next yearDATE

0.99+

Red hatORGANIZATION

0.99+

this yearDATE

0.99+

ZOSTITLE

0.98+

two thingsQUANTITY

0.98+

first timeQUANTITY

0.98+

SQLTITLE

0.98+

next quarterDATE

0.98+

two reasonsQUANTITY

0.98+

bothQUANTITY

0.98+

Ansible FestEVENT

0.98+

CaliforniaLOCATION

0.98+

one final questionQUANTITY

0.98+

OpenStackTITLE

0.97+

4-video test


 

>>don't talk mhm, >>Okay, thing is my presentation on coherent nonlinear dynamics and combinatorial optimization. This is going to be a talk to introduce an approach we're taking to the analysis of the performance of coherent using machines. So let me start with a brief introduction to easing optimization. The easing model represents a set of interacting magnetic moments or spins the total energy given by the expression shown at the bottom left of this slide. Here, the signal variables are meditate binary values. The Matrix element J. I. J. Represents the interaction, strength and signed between any pair of spins. I. J and A Chive represents a possible local magnetic field acting on each thing. The easing ground state problem is to find an assignment of binary spin values that achieves the lowest possible value of total energy. And an instance of the easing problem is specified by giving numerical values for the Matrix J in Vector H. Although the easy model originates in physics, we understand the ground state problem to correspond to what would be called quadratic binary optimization in the field of operations research and in fact, in terms of computational complexity theory, it could be established that the easing ground state problem is np complete. Qualitatively speaking, this makes the easing problem a representative sort of hard optimization problem, for which it is expected that the runtime required by any computational algorithm to find exact solutions should, as anatomically scale exponentially with the number of spends and for worst case instances at each end. Of course, there's no reason to believe that the problem instances that actually arrives in practical optimization scenarios are going to be worst case instances. And it's also not generally the case in practical optimization scenarios that we demand absolute optimum solutions. Usually we're more interested in just getting the best solution we can within an affordable cost, where costs may be measured in terms of time, service fees and or energy required for a computation. This focuses great interest on so called heuristic algorithms for the easing problem in other NP complete problems which generally get very good but not guaranteed optimum solutions and run much faster than algorithms that are designed to find absolute Optima. To get some feeling for present day numbers, we can consider the famous traveling salesman problem for which extensive compilations of benchmarking data may be found online. A recent study found that the best known TSP solver required median run times across the Library of Problem instances That scaled is a very steep route exponential for end up to approximately 4500. This gives some indication of the change in runtime scaling for generic as opposed the worst case problem instances. Some of the instances considered in this study were taken from a public library of T SPS derived from real world Veil aside design data. This feels I TSP Library includes instances within ranging from 131 to 744,710 instances from this library with end between 6880 13,584 were first solved just a few years ago in 2017 requiring days of run time and a 48 core to King hurts cluster, while instances with and greater than or equal to 14,233 remain unsolved exactly by any means. Approximate solutions, however, have been found by heuristic methods for all instances in the VLS i TSP library with, for example, a solution within 0.14% of a no lower bound, having been discovered, for instance, with an equal 19,289 requiring approximately two days of run time on a single core of 2.4 gigahertz. Now, if we simple mindedly extrapolate the root exponential scaling from the study up to an equal 4500, we might expect that an exact solver would require something more like a year of run time on the 48 core cluster used for the N equals 13,580 for instance, which shows how much a very small concession on the quality of the solution makes it possible to tackle much larger instances with much lower cost. At the extreme end, the largest TSP ever solved exactly has an equal 85,900. This is an instance derived from 19 eighties VLSI design, and it's required 136 CPU. Years of computation normalized to a single cord, 2.4 gigahertz. But the 24 larger so called world TSP benchmark instance within equals 1,904,711 has been solved approximately within ophthalmology. Gap bounded below 0.474%. Coming back to the general. Practical concerns have applied optimization. We may note that a recent meta study analyzed the performance of no fewer than 37 heuristic algorithms for Max cut and quadratic pioneer optimization problems and found the performance sort and found that different heuristics work best for different problem instances selected from a large scale heterogeneous test bed with some evidence but cryptic structure in terms of what types of problem instances were best solved by any given heuristic. Indeed, their their reasons to believe that these results from Mexico and quadratic binary optimization reflected general principle of performance complementarity among heuristic optimization algorithms in the practice of solving heart optimization problems there. The cerise is a critical pre processing issue of trying to guess which of a number of available good heuristic algorithms should be chosen to tackle a given problem. Instance, assuming that any one of them would incur high costs to run on a large problem, instances incidence, making an astute choice of heuristic is a crucial part of maximizing overall performance. Unfortunately, we still have very little conceptual insight about what makes a specific problem instance, good or bad for any given heuristic optimization algorithm. This has certainly been pinpointed by researchers in the field is a circumstance that must be addressed. So adding this all up, we see that a critical frontier for cutting edge academic research involves both the development of novel heuristic algorithms that deliver better performance, with lower cost on classes of problem instances that are underserved by existing approaches, as well as fundamental research to provide deep conceptual insight into what makes a given problem in, since easy or hard for such algorithms. In fact, these days, as we talk about the end of Moore's law and speculate about a so called second quantum revolution, it's natural to talk not only about novel algorithms for conventional CPUs but also about highly customized special purpose hardware architectures on which we may run entirely unconventional algorithms for combinatorial optimization such as easing problem. So against that backdrop, I'd like to use my remaining time to introduce our work on analysis of coherent using machine architectures and associate ID optimization algorithms. These machines, in general, are a novel class of information processing architectures for solving combinatorial optimization problems by embedding them in the dynamics of analog, physical or cyber physical systems, in contrast to both MAWR traditional engineering approaches that build using machines using conventional electron ICS and more radical proposals that would require large scale quantum entanglement. The emerging paradigm of coherent easing machines leverages coherent nonlinear dynamics in photonic or Opto electronic platforms to enable near term construction of large scale prototypes that leverage post Simoes information dynamics, the general structure of of current CM systems has shown in the figure on the right. The role of the easing spins is played by a train of optical pulses circulating around a fiber optical storage ring. A beam splitter inserted in the ring is used to periodically sample the amplitude of every optical pulse, and the measurement results are continually read into a refugee A, which uses them to compute perturbations to be applied to each pulse by a synchronized optical injections. These perturbations, air engineered to implement the spin, spin coupling and local magnetic field terms of the easing Hamiltonian, corresponding to a linear part of the CME Dynamics, a synchronously pumped parametric amplifier denoted here as PPL and Wave Guide adds a crucial nonlinear component to the CIA and Dynamics as well. In the basic CM algorithm, the pump power starts very low and has gradually increased at low pump powers. The amplitude of the easing spin pulses behaviors continuous, complex variables. Who Israel parts which can be positive or negative, play the role of play the role of soft or perhaps mean field spins once the pump, our crosses the threshold for parametric self oscillation. In the optical fiber ring, however, the attitudes of the easing spin pulses become effectively Qantas ized into binary values while the pump power is being ramped up. The F P J subsystem continuously applies its measurement based feedback. Implementation of the using Hamiltonian terms, the interplay of the linear rised using dynamics implemented by the F P G A and the threshold conversation dynamics provided by the sink pumped Parametric amplifier result in the final state of the optical optical pulse amplitude at the end of the pump ramp that could be read as a binary strain, giving a proposed solution of the easing ground state problem. This method of solving easing problem seems quite different from a conventional algorithm that runs entirely on a digital computer as a crucial aspect of the computation is performed physically by the analog, continuous, coherent, nonlinear dynamics of the optical degrees of freedom. In our efforts to analyze CIA and performance, we have therefore turned to the tools of dynamical systems theory, namely, a study of modifications, the evolution of critical points and apologies of hetero clinic orbits and basins of attraction. We conjecture that such analysis can provide fundamental insight into what makes certain optimization instances hard or easy for coherent using machines and hope that our approach can lead to both improvements of the course, the AM algorithm and a pre processing rubric for rapidly assessing the CME suitability of new instances. Okay, to provide a bit of intuition about how this all works, it may help to consider the threshold dynamics of just one or two optical parametric oscillators in the CME architecture just described. We can think of each of the pulse time slots circulating around the fiber ring, as are presenting an independent Opio. We can think of a single Opio degree of freedom as a single, resonant optical node that experiences linear dissipation, do toe out coupling loss and gain in a pump. Nonlinear crystal has shown in the diagram on the upper left of this slide as the pump power is increased from zero. As in the CME algorithm, the non linear game is initially to low toe overcome linear dissipation, and the Opio field remains in a near vacuum state at a critical threshold. Value gain. Equal participation in the Popeo undergoes a sort of lazing transition, and the study states of the OPIO above this threshold are essentially coherent states. There are actually two possible values of the Opio career in amplitude and any given above threshold pump power which are equal in magnitude but opposite in phase when the OPI across the special diet basically chooses one of the two possible phases randomly, resulting in the generation of a single bit of information. If we consider to uncoupled, Opio has shown in the upper right diagram pumped it exactly the same power at all times. Then, as the pump power has increased through threshold, each Opio will independently choose the phase and thus to random bits are generated for any number of uncoupled. Oppose the threshold power per opio is unchanged from the single Opio case. Now, however, consider a scenario in which the two appeals air, coupled to each other by a mutual injection of their out coupled fields has shown in the diagram on the lower right. One can imagine that depending on the sign of the coupling parameter Alfa, when one Opio is lazing, it will inject a perturbation into the other that may interfere either constructively or destructively, with the feel that it is trying to generate by its own lazing process. As a result, when came easily showed that for Alfa positive, there's an effective ferro magnetic coupling between the two Opio fields and their collective oscillation threshold is lowered from that of the independent Opio case. But on Lee for the two collective oscillation modes in which the two Opio phases are the same for Alfa Negative, the collective oscillation threshold is lowered on Lee for the configurations in which the Opio phases air opposite. So then, looking at how Alfa is related to the J. I. J matrix of the easing spin coupling Hamiltonian, it follows that we could use this simplistic to a p o. C. I am to solve the ground state problem of a fair magnetic or anti ferro magnetic ankles to easing model simply by increasing the pump power from zero and observing what phase relation occurs as the two appeals first start delays. Clearly, we can imagine generalizing this story toe larger, and however the story doesn't stay is clean and simple for all larger problem instances. And to find a more complicated example, we only need to go to n equals four for some choices of J J for n equals, for the story remains simple. Like the n equals two case. The figure on the upper left of this slide shows the energy of various critical points for a non frustrated and equals, for instance, in which the first bifurcated critical point that is the one that I forget to the lowest pump value a. Uh, this first bifurcated critical point flows as symptomatically into the lowest energy easing solution and the figure on the upper right. However, the first bifurcated critical point flows to a very good but sub optimal minimum at large pump power. The global minimum is actually given by a distinct critical critical point that first appears at a higher pump power and is not automatically connected to the origin. The basic C am algorithm is thus not able to find this global minimum. Such non ideal behaviors needs to become more confident. Larger end for the n equals 20 instance, showing the lower plots where the lower right plot is just a zoom into a region of the lower left lot. It can be seen that the global minimum corresponds to a critical point that first appears out of pump parameter, a around 0.16 at some distance from the idiomatic trajectory of the origin. That's curious to note that in both of these small and examples, however, the critical point corresponding to the global minimum appears relatively close to the idiomatic projector of the origin as compared to the most of the other local minima that appear. We're currently working to characterize the face portrait topology between the global minimum in the antibiotic trajectory of the origin, taking clues as to how the basic C am algorithm could be generalized to search for non idiomatic trajectories that jump to the global minimum during the pump ramp. Of course, n equals 20 is still too small to be of interest for practical optimization applications. But the advantage of beginning with the study of small instances is that we're able reliably to determine their global minima and to see how they relate to the 80 about trajectory of the origin in the basic C am algorithm. In the smaller and limit, we can also analyze fully quantum mechanical models of Syrian dynamics. But that's a topic for future talks. Um, existing large scale prototypes are pushing into the range of in equals 10 to the 4 10 to 5 to six. So our ultimate objective in theoretical analysis really has to be to try to say something about CIA and dynamics and regime of much larger in our initial approach to characterizing CIA and behavior in the large in regime relies on the use of random matrix theory, and this connects to prior research on spin classes, SK models and the tap equations etcetera. At present, we're focusing on statistical characterization of the CIA ingredient descent landscape, including the evolution of critical points in their Eigen value spectra. As the pump power is gradually increased. We're investigating, for example, whether there could be some way to exploit differences in the relative stability of the global minimum versus other local minima. We're also working to understand the deleterious or potentially beneficial effects of non ideologies, such as a symmetry in the implemented these and couplings. Looking one step ahead, we plan to move next in the direction of considering more realistic classes of problem instances such as quadratic, binary optimization with constraints. Eso In closing, I should acknowledge people who did the hard work on these things that I've shown eso. My group, including graduate students Ed winning, Daniel Wennberg, Tatsuya Nagamoto and Atsushi Yamamura, have been working in close collaboration with Syria Ganguly, Marty Fair and Amir Safarini Nini, all of us within the Department of Applied Physics at Stanford University. On also in collaboration with the Oshima Moto over at NTT 55 research labs, Onda should acknowledge funding support from the NSF by the Coherent Easing Machines Expedition in computing, also from NTT five research labs, Army Research Office and Exxon Mobil. Uh, that's it. Thanks very much. >>Mhm e >>t research and the Oshie for putting together this program and also the opportunity to speak here. My name is Al Gore ism or Andy and I'm from Caltech, and today I'm going to tell you about the work that we have been doing on networks off optical parametric oscillators and how we have been using them for icing machines and how we're pushing them toward Cornum photonics to acknowledge my team at Caltech, which is now eight graduate students and five researcher and postdocs as well as collaborators from all over the world, including entity research and also the funding from different places, including entity. So this talk is primarily about networks of resonate er's, and these networks are everywhere from nature. For instance, the brain, which is a network of oscillators all the way to optics and photonics and some of the biggest examples or metal materials, which is an array of small resonate er's. And we're recently the field of technological photonics, which is trying thio implement a lot of the technological behaviors of models in the condensed matter, physics in photonics and if you want to extend it even further, some of the implementations off quantum computing are technically networks of quantum oscillators. So we started thinking about these things in the context of icing machines, which is based on the icing problem, which is based on the icing model, which is the simple summation over the spins and spins can be their upward down and the couplings is given by the JJ. And the icing problem is, if you know J I J. What is the spin configuration that gives you the ground state? And this problem is shown to be an MP high problem. So it's computational e important because it's a representative of the MP problems on NPR. Problems are important because first, their heart and standard computers if you use a brute force algorithm and they're everywhere on the application side. That's why there is this demand for making a machine that can target these problems, and hopefully it can provide some meaningful computational benefit compared to the standard digital computers. So I've been building these icing machines based on this building block, which is a degenerate optical parametric. Oscillator on what it is is resonator with non linearity in it, and we pump these resonate er's and we generate the signal at half the frequency of the pump. One vote on a pump splits into two identical photons of signal, and they have some very interesting phase of frequency locking behaviors. And if you look at the phase locking behavior, you realize that you can actually have two possible phase states as the escalation result of these Opio which are off by pie, and that's one of the important characteristics of them. So I want to emphasize a little more on that and I have this mechanical analogy which are basically two simple pendulum. But there are parametric oscillators because I'm going to modulate the parameter of them in this video, which is the length of the string on by that modulation, which is that will make a pump. I'm gonna make a muscular. That'll make a signal which is half the frequency of the pump. And I have two of them to show you that they can acquire these face states so they're still facing frequency lock to the pump. But it can also lead in either the zero pie face states on. The idea is to use this binary phase to represent the binary icing spin. So each opio is going to represent spin, which can be either is your pie or up or down. And to implement the network of these resonate er's, we use the time off blood scheme, and the idea is that we put impulses in the cavity. These pulses air separated by the repetition period that you put in or t r. And you can think about these pulses in one resonator, xaz and temporarily separated synthetic resonate Er's if you want a couple of these resonator is to each other, and now you can introduce these delays, each of which is a multiple of TR. If you look at the shortest delay it couples resonator wanted to 2 to 3 and so on. If you look at the second delay, which is two times a rotation period, the couple's 123 and so on. And if you have and minus one delay lines, then you can have any potential couplings among these synthetic resonate er's. And if I can introduce these modulators in those delay lines so that I can strength, I can control the strength and the phase of these couplings at the right time. Then I can have a program will all toe all connected network in this time off like scheme, and the whole physical size of the system scales linearly with the number of pulses. So the idea of opium based icing machine is didn't having these o pos, each of them can be either zero pie and I can arbitrarily connect them to each other. And then I start with programming this machine to a given icing problem by just setting the couplings and setting the controllers in each of those delight lines. So now I have a network which represents an icing problem. Then the icing problem maps to finding the face state that satisfy maximum number of coupling constraints. And the way it happens is that the icing Hamiltonian maps to the linear loss of the network. And if I start adding gain by just putting pump into the network, then the OPI ohs are expected to oscillate in the lowest, lowest lost state. And, uh and we have been doing these in the past, uh, six or seven years and I'm just going to quickly show you the transition, especially what happened in the first implementation, which was using a free space optical system and then the guided wave implementation in 2016 and the measurement feedback idea which led to increasing the size and doing actual computation with these machines. So I just want to make this distinction here that, um, the first implementation was an all optical interaction. We also had an unequal 16 implementation. And then we transition to this measurement feedback idea, which I'll tell you quickly what it iss on. There's still a lot of ongoing work, especially on the entity side, to make larger machines using the measurement feedback. But I'm gonna mostly focused on the all optical networks and how we're using all optical networks to go beyond simulation of icing Hamiltonian both in the linear and non linear side and also how we're working on miniaturization of these Opio networks. So the first experiment, which was the four opium machine, it was a free space implementation and this is the actual picture off the machine and we implemented a small and it calls for Mexico problem on the machine. So one problem for one experiment and we ran the machine 1000 times, we looked at the state and we always saw it oscillate in one of these, um, ground states of the icing laboratoria. So then the measurement feedback idea was to replace those couplings and the controller with the simulator. So we basically simulated all those coherent interactions on on FB g. A. And we replicated the coherent pulse with respect to all those measurements. And then we injected it back into the cavity and on the near to you still remain. So it still is a non. They're dynamical system, but the linear side is all simulated. So there are lots of questions about if this system is preserving important information or not, or if it's gonna behave better. Computational wars. And that's still ah, lot of ongoing studies. But nevertheless, the reason that this implementation was very interesting is that you don't need the end minus one delight lines so you can just use one. Then you can implement a large machine, and then you can run several thousands of problems in the machine, and then you can compare the performance from the computational perspective Looks so I'm gonna split this idea of opium based icing machine into two parts. One is the linear part, which is if you take out the non linearity out of the resonator and just think about the connections. You can think about this as a simple matrix multiplication scheme. And that's basically what gives you the icing Hambletonian modeling. So the optical laws of this network corresponds to the icing Hamiltonian. And if I just want to show you the example of the n equals for experiment on all those face states and the history Graham that we saw, you can actually calculate the laws of each of those states because all those interferences in the beam splitters and the delay lines are going to give you a different losses. And then you will see that the ground states corresponds to the lowest laws of the actual optical network. If you add the non linearity, the simple way of thinking about what the non linearity does is that it provides to gain, and then you start bringing up the gain so that it hits the loss. Then you go through the game saturation or the threshold which is going to give you this phase bifurcation. So you go either to zero the pie face state. And the expectation is that Theis, the network oscillates in the lowest possible state, the lowest possible loss state. There are some challenges associated with this intensity Durban face transition, which I'm going to briefly talk about. I'm also going to tell you about other types of non aerodynamics that we're looking at on the non air side of these networks. So if you just think about the linear network, we're actually interested in looking at some technological behaviors in these networks. And the difference between looking at the technological behaviors and the icing uh, machine is that now, First of all, we're looking at the type of Hamilton Ian's that are a little different than the icing Hamilton. And one of the biggest difference is is that most of these technological Hamilton Ian's that require breaking the time reversal symmetry, meaning that you go from one spin to in the one side to another side and you get one phase. And if you go back where you get a different phase, and the other thing is that we're not just interested in finding the ground state, we're actually now interesting and looking at all sorts of states and looking at the dynamics and the behaviors of all these states in the network. So we started with the simplest implementation, of course, which is a one d chain of thes resonate, er's, which corresponds to a so called ssh model. In the technological work, we get the similar energy to los mapping and now we can actually look at the band structure on. This is an actual measurement that we get with this associate model and you see how it reasonably how How? Well, it actually follows the prediction and the theory. One of the interesting things about the time multiplexing implementation is that now you have the flexibility of changing the network as you are running the machine. And that's something unique about this time multiplex implementation so that we can actually look at the dynamics. And one example that we have looked at is we can actually go through the transition off going from top A logical to the to the standard nontrivial. I'm sorry to the trivial behavior of the network. You can then look at the edge states and you can also see the trivial and states and the technological at states actually showing up in this network. We have just recently implement on a two D, uh, network with Harper Hofstadter model and when you don't have the results here. But we're one of the other important characteristic of time multiplexing is that you can go to higher and higher dimensions and keeping that flexibility and dynamics, and we can also think about adding non linearity both in a classical and quantum regimes, which is going to give us a lot of exotic, no classical and quantum, non innate behaviors in these networks. Yeah, So I told you about the linear side. Mostly let me just switch gears and talk about the nonlinear side of the network. And the biggest thing that I talked about so far in the icing machine is this face transition that threshold. So the low threshold we have squeezed state in these. Oh, pios, if you increase the pump, we go through this intensity driven phase transition and then we got the face stays above threshold. And this is basically the mechanism off the computation in these O pos, which is through this phase transition below to above threshold. So one of the characteristics of this phase transition is that below threshold, you expect to see quantum states above threshold. You expect to see more classical states or coherent states, and that's basically corresponding to the intensity off the driving pump. So it's really hard to imagine that it can go above threshold. Or you can have this friends transition happen in the all in the quantum regime. And there are also some challenges associated with the intensity homogeneity off the network, which, for example, is if one opioid starts oscillating and then its intensity goes really high. Then it's going to ruin this collective decision making off the network because of the intensity driven face transition nature. So So the question is, can we look at other phase transitions? Can we utilize them for both computing? And also can we bring them to the quantum regime on? I'm going to specifically talk about the face transition in the spectral domain, which is the transition from the so called degenerate regime, which is what I mostly talked about to the non degenerate regime, which happens by just tuning the phase of the cavity. And what is interesting is that this phase transition corresponds to a distinct phase noise behavior. So in the degenerate regime, which we call it the order state, you're gonna have the phase being locked to the phase of the pump. As I talked about non degenerate regime. However, the phase is the phase is mostly dominated by the quantum diffusion. Off the off the phase, which is limited by the so called shallow towns limit, and you can see that transition from the general to non degenerate, which also has distinct symmetry differences. And this transition corresponds to a symmetry breaking in the non degenerate case. The signal can acquire any of those phases on the circle, so it has a you one symmetry. Okay, and if you go to the degenerate case, then that symmetry is broken and you only have zero pie face days I will look at. So now the question is can utilize this phase transition, which is a face driven phase transition, and can we use it for similar computational scheme? So that's one of the questions that were also thinking about. And it's not just this face transition is not just important for computing. It's also interesting from the sensing potentials and this face transition, you can easily bring it below threshold and just operated in the quantum regime. Either Gaussian or non Gaussian. If you make a network of Opio is now, we can see all sorts off more complicated and more interesting phase transitions in the spectral domain. One of them is the first order phase transition, which you get by just coupling to Opio, and that's a very abrupt face transition and compared to the to the single Opio phase transition. And if you do the couplings right, you can actually get a lot of non her mission dynamics and exceptional points, which are actually very interesting to explore both in the classical and quantum regime. And I should also mention that you can think about the cup links to be also nonlinear couplings. And that's another behavior that you can see, especially in the nonlinear in the non degenerate regime. So with that, I basically told you about these Opio networks, how we can think about the linear scheme and the linear behaviors and how we can think about the rich, nonlinear dynamics and non linear behaviors both in the classical and quantum regime. I want to switch gear and tell you a little bit about the miniaturization of these Opio networks. And of course, the motivation is if you look at the electron ICS and what we had 60 or 70 years ago with vacuum tube and how we transition from relatively small scale computers in the order of thousands of nonlinear elements to billions of non elements where we are now with the optics is probably very similar to 70 years ago, which is a table talk implementation. And the question is, how can we utilize nano photonics? I'm gonna just briefly show you the two directions on that which we're working on. One is based on lithium Diabate, and the other is based on even a smaller resonate er's could you? So the work on Nana Photonic lithium naive. It was started in collaboration with Harvard Marko Loncar, and also might affair at Stanford. And, uh, we could show that you can do the periodic polling in the phenomenon of it and get all sorts of very highly nonlinear processes happening in this net. Photonic periodically polls if, um Diabate. And now we're working on building. Opio was based on that kind of photonic the film Diabate. And these air some some examples of the devices that we have been building in the past few months, which I'm not gonna tell you more about. But the O. P. O. S. And the Opio Networks are in the works. And that's not the only way of making large networks. Um, but also I want to point out that The reason that these Nana photonic goblins are actually exciting is not just because you can make a large networks and it can make him compact in a in a small footprint. They also provide some opportunities in terms of the operation regime. On one of them is about making cat states and Opio, which is, can we have the quantum superposition of the zero pie states that I talked about and the Net a photonic within? I've It provides some opportunities to actually get closer to that regime because of the spatial temporal confinement that you can get in these wave guides. So we're doing some theory on that. We're confident that the type of non linearity two losses that it can get with these platforms are actually much higher than what you can get with other platform their existing platforms and to go even smaller. We have been asking the question off. What is the smallest possible Opio that you can make? Then you can think about really wavelength scale type, resonate er's and adding the chi to non linearity and see how and when you can get the Opio to operate. And recently, in collaboration with us see, we have been actually USC and Creole. We have demonstrated that you can use nano lasers and get some spin Hamilton and implementations on those networks. So if you can build the a P. O s, we know that there is a path for implementing Opio Networks on on such a nano scale. So we have looked at these calculations and we try to estimate the threshold of a pos. Let's say for me resonator and it turns out that it can actually be even lower than the type of bulk Pip Llano Pos that we have been building in the past 50 years or so. So we're working on the experiments and we're hoping that we can actually make even larger and larger scale Opio networks. So let me summarize the talk I told you about the opium networks and our work that has been going on on icing machines and the measurement feedback. And I told you about the ongoing work on the all optical implementations both on the linear side and also on the nonlinear behaviors. And I also told you a little bit about the efforts on miniaturization and going to the to the Nano scale. So with that, I would like Thio >>three from the University of Tokyo. Before I thought that would like to thank you showing all the stuff of entity for the invitation and the organization of this online meeting and also would like to say that it has been very exciting to see the growth of this new film lab. And I'm happy to share with you today of some of the recent works that have been done either by me or by character of Hong Kong. Honest Group indicates the title of my talk is a neuro more fic in silica simulator for the communities in machine. And here is the outline I would like to make the case that the simulation in digital Tektronix of the CME can be useful for the better understanding or improving its function principles by new job introducing some ideas from neural networks. This is what I will discuss in the first part and then it will show some proof of concept of the game and performance that can be obtained using dissimulation in the second part and the protection of the performance that can be achieved using a very large chaos simulator in the third part and finally talk about future plans. So first, let me start by comparing recently proposed izing machines using this table there is elected from recent natural tronics paper from the village Park hard people, and this comparison shows that there's always a trade off between energy efficiency, speed and scalability that depends on the physical implementation. So in red, here are the limitation of each of the servers hardware on, interestingly, the F p G, a based systems such as a producer, digital, another uh Toshiba beautification machine or a recently proposed restricted Bozeman machine, FPD A by a group in Berkeley. They offer a good compromise between speed and scalability. And this is why, despite the unique advantage that some of these older hardware have trust as the currency proposition in Fox, CBS or the energy efficiency off memory Sisters uh P. J. O are still an attractive platform for building large organizing machines in the near future. The reason for the good performance of Refugee A is not so much that they operate at the high frequency. No, there are particular in use, efficient, but rather that the physical wiring off its elements can be reconfigured in a way that limits the funding human bottleneck, larger, funny and phenols and the long propagation video information within the system. In this respect, the LPGA is They are interesting from the perspective off the physics off complex systems, but then the physics of the actions on the photos. So to put the performance of these various hardware and perspective, we can look at the competition of bringing the brain the brain complete, using billions of neurons using only 20 watts of power and operates. It's a very theoretically slow, if we can see and so this impressive characteristic, they motivate us to try to investigate. What kind of new inspired principles be useful for designing better izing machines? The idea of this research project in the future collaboration it's to temporary alleviates the limitations that are intrinsic to the realization of an optical cortex in machine shown in the top panel here. By designing a large care simulator in silicone in the bottom here that can be used for digesting the better organization principles of the CIA and this talk, I will talk about three neuro inspired principles that are the symmetry of connections, neural dynamics orphan chaotic because of symmetry, is interconnectivity the infrastructure? No. Next talks are not composed of the reputation of always the same types of non environments of the neurons, but there is a local structure that is repeated. So here's the schematic of the micro column in the cortex. And lastly, the Iraqi co organization of connectivity connectivity is organizing a tree structure in the brain. So here you see a representation of the Iraqi and organization of the monkey cerebral cortex. So how can these principles we used to improve the performance of the icing machines? And it's in sequence stimulation. So, first about the two of principles of the estimate Trian Rico structure. We know that the classical approximation of the car testing machine, which is the ground toe, the rate based on your networks. So in the case of the icing machines, uh, the okay, Scott approximation can be obtained using the trump active in your position, for example, so the times of both of the system they are, they can be described by the following ordinary differential equations on in which, in case of see, I am the X, I represent the in phase component of one GOP Oh, Theo f represents the monitor optical parts, the district optical Parametric amplification and some of the good I JoJo extra represent the coupling, which is done in the case of the measure of feedback coupling cm using oh, more than detection and refugee A and then injection off the cooking time and eso this dynamics in both cases of CNN in your networks, they can be written as the grand set of a potential function V, and this written here, and this potential functionally includes the rising Maccagnan. So this is why it's natural to use this type of, uh, dynamics to solve the icing problem in which the Omega I J or the eyes in coping and the H is the extension of the icing and attorney in India and expect so. Not that this potential function can only be defined if the Omega I j. R. A. Symmetric. So the well known problem of this approach is that this potential function V that we obtain is very non convicts at low temperature, and also one strategy is to gradually deformed this landscape, using so many in process. But there is no theorem. Unfortunately, that granted conventions to the global minimum of There's even Tony and using this approach. And so this is why we propose, uh, to introduce a macro structures of the system where one analog spin or one D O. P. O is replaced by a pair off one another spin and one error, according viable. And the addition of this chemical structure introduces a symmetry in the system, which in terms induces chaotic dynamics, a chaotic search rather than a learning process for searching for the ground state of the icing. Every 20 within this massacre structure the role of the er variable eyes to control the amplitude off the analog spins toe force. The amplitude of the expense toe become equal to certain target amplitude a uh and, uh, and this is done by modulating the strength off the icing complaints or see the the error variable E I multiply the icing complaint here in the dynamics off air d o p. O. On then the dynamics. The whole dynamics described by this coupled equations because the e I do not necessarily take away the same value for the different. I thesis introduces a symmetry in the system, which in turn creates security dynamics, which I'm sure here for solving certain current size off, um, escape problem, Uh, in which the X I are shown here and the i r from here and the value of the icing energy showing the bottom plots. You see this Celtics search that visit various local minima of the as Newtonian and eventually finds the global minimum? Um, it can be shown that this modulation off the target opportunity can be used to destabilize all the local minima off the icing evertonians so that we're gonna do not get stuck in any of them. On more over the other types of attractors I can eventually appear, such as limits I contractors, Okot contractors. They can also be destabilized using the motivation of the target and Batuta. And so we have proposed in the past two different moderation of the target amateur. The first one is a modulation that ensure the uh 100 reproduction rate of the system to become positive on this forbids the creation off any nontrivial tractors. And but in this work, I will talk about another moderation or arrested moderation which is given here. That works, uh, as well as this first uh, moderation, but is easy to be implemented on refugee. So this couple of the question that represent becoming the stimulation of the cortex in machine with some error correction they can be implemented especially efficiently on an F B. G. And here I show the time that it takes to simulate three system and also in red. You see, at the time that it takes to simulate the X I term the EI term, the dot product and the rising Hamiltonian for a system with 500 spins and Iraq Spain's equivalent to 500 g. O. P. S. So >>in >>f b d a. The nonlinear dynamics which, according to the digital optical Parametric amplification that the Opa off the CME can be computed in only 13 clock cycles at 300 yards. So which corresponds to about 0.1 microseconds. And this is Toby, uh, compared to what can be achieved in the measurements back O C. M. In which, if we want to get 500 timer chip Xia Pios with the one she got repetition rate through the obstacle nine narrative. Uh, then way would require 0.5 microseconds toe do this so the submission in F B J can be at least as fast as ah one g repression. Uh, replicate pulsed laser CIA Um, then the DOT product that appears in this differential equation can be completed in 43 clock cycles. That's to say, one microseconds at 15 years. So I pieced for pouring sizes that are larger than 500 speeds. The dot product becomes clearly the bottleneck, and this can be seen by looking at the the skating off the time the numbers of clock cycles a text to compute either the non in your optical parts or the dog products, respect to the problem size. And And if we had infinite amount of resources and PGA to simulate the dynamics, then the non illogical post can could be done in the old one. On the mattress Vector product could be done in the low carrot off, located off scales as a look at it off and and while the guide off end. Because computing the dot product involves assuming all the terms in the product, which is done by a nephew, GE by another tree, which heights scarce logarithmic any with the size of the system. But This is in the case if we had an infinite amount of resources on the LPGA food, but for dealing for larger problems off more than 100 spins. Usually we need to decompose the metrics into ah, smaller blocks with the block side that are not you here. And then the scaling becomes funny, non inner parts linear in the end, over you and for the products in the end of EU square eso typically for low NF pdf cheap PGA you the block size off this matrix is typically about 100. So clearly way want to make you as large as possible in order to maintain this scanning in a log event for the numbers of clock cycles needed to compute the product rather than this and square that occurs if we decompose the metrics into smaller blocks. But the difficulty in, uh, having this larger blocks eyes that having another tree very large Haider tree introduces a large finding and finance and long distance start a path within the refugee. So the solution to get higher performance for a simulator of the contest in machine eyes to get rid of this bottleneck for the dot product by increasing the size of this at the tree. And this can be done by organizing your critique the electrical components within the LPGA in order which is shown here in this, uh, right panel here in order to minimize the finding finance of the system and to minimize the long distance that a path in the in the fpt So I'm not going to the details of how this is implemented LPGA. But just to give you a idea off why the Iraqi Yahiko organization off the system becomes the extremely important toe get good performance for similar organizing machine. So instead of instead of getting into the details of the mpg implementation, I would like to give some few benchmark results off this simulator, uh, off the that that was used as a proof of concept for this idea which is can be found in this archive paper here and here. I should results for solving escape problems. Free connected person, randomly person minus one spring last problems and we sure, as we use as a metric the numbers of the mattress Victor products since it's the bottleneck of the computation, uh, to get the optimal solution of this escape problem with the Nina successful BT against the problem size here and and in red here, this propose FDJ implementation and in ah blue is the numbers of retrospective product that are necessary for the C. I am without error correction to solve this escape programs and in green here for noisy means in an evening which is, uh, behavior with similar to the Cartesian mission. Uh, and so clearly you see that the scaring off the numbers of matrix vector product necessary to solve this problem scales with a better exponents than this other approaches. So So So that's interesting feature of the system and next we can see what is the real time to solution to solve this SK instances eso in the last six years, the time institution in seconds to find a grand state of risk. Instances remain answers probability for different state of the art hardware. So in red is the F B g. A presentation proposing this paper and then the other curve represent Ah, brick a local search in in orange and silver lining in purple, for example. And so you see that the scaring off this purpose simulator is is rather good, and that for larger plant sizes we can get orders of magnitude faster than the state of the art approaches. Moreover, the relatively good scanning off the time to search in respect to problem size uh, they indicate that the FPD implementation would be faster than risk. Other recently proposed izing machine, such as the hope you know, natural complimented on memories distance that is very fast for small problem size in blue here, which is very fast for small problem size. But which scanning is not good on the same thing for the restricted Bosman machine. Implementing a PGA proposed by some group in Broken Recently Again, which is very fast for small parliament sizes but which canning is bad so that a dis worse than the proposed approach so that we can expect that for programs size is larger than 1000 spins. The proposed, of course, would be the faster one. Let me jump toe this other slide and another confirmation that the scheme scales well that you can find the maximum cut values off benchmark sets. The G sets better candidates that have been previously found by any other algorithms, so they are the best known could values to best of our knowledge. And, um or so which is shown in this paper table here in particular, the instances, uh, 14 and 15 of this G set can be We can find better converse than previously known, and we can find this can vary is 100 times faster than the state of the art algorithm and CP to do this which is a very common Kasich. It s not that getting this a good result on the G sets, they do not require ah, particular hard tuning of the parameters. So the tuning issuing here is very simple. It it just depends on the degree off connectivity within each graph. And so this good results on the set indicate that the proposed approach would be a good not only at solving escape problems in this problems, but all the types off graph sizing problems on Mexican province in communities. So given that the performance off the design depends on the height of this other tree, we can try to maximize the height of this other tree on a large F p g a onda and carefully routing the components within the P G A and and we can draw some projections of what type of performance we can achieve in the near future based on the, uh, implementation that we are currently working. So here you see projection for the time to solution way, then next property for solving this escape programs respect to the prime assize. And here, compared to different with such publicizing machines, particularly the digital. And, you know, 42 is shown in the green here, the green line without that's and, uh and we should two different, uh, hypothesis for this productions either that the time to solution scales as exponential off n or that the time of social skills as expression of square root off. So it seems, according to the data, that time solution scares more as an expression of square root of and also we can be sure on this and this production show that we probably can solve prime escape problem of science 2000 spins, uh, to find the rial ground state of this problem with 99 success ability in about 10 seconds, which is much faster than all the other proposed approaches. So one of the future plans for this current is in machine simulator. So the first thing is that we would like to make dissimulation closer to the rial, uh, GOP oh, optical system in particular for a first step to get closer to the system of a measurement back. See, I am. And to do this what is, uh, simulate Herbal on the p a is this quantum, uh, condoms Goshen model that is proposed described in this paper and proposed by people in the in the Entity group. And so the idea of this model is that instead of having the very simple or these and have shown previously, it includes paired all these that take into account on me the mean off the awesome leverage off the, uh, European face component, but also their violence s so that we can take into account more quantum effects off the g o p. O, such as the squeezing. And then we plan toe, make the simulator open access for the members to run their instances on the system. There will be a first version in September that will be just based on the simple common line access for the simulator and in which will have just a classic or approximation of the system. We don't know Sturm, binary weights and museum in term, but then will propose a second version that would extend the current arising machine to Iraq off F p g. A, in which we will add the more refined models truncated, ignoring the bottom Goshen model they just talked about on the support in which he valued waits for the rising problems and support the cement. So we will announce later when this is available and and far right is working >>hard comes from Universal down today in physics department, and I'd like to thank the organizers for their kind invitation to participate in this very interesting and promising workshop. Also like to say that I look forward to collaborations with with a file lab and Yoshi and collaborators on the topics of this world. So today I'll briefly talk about our attempt to understand the fundamental limits off another continues time computing, at least from the point off you off bullion satisfy ability, problem solving, using ordinary differential equations. But I think the issues that we raise, um, during this occasion actually apply to other other approaches on a log approaches as well and into other problems as well. I think everyone here knows what Dorien satisfy ability. Problems are, um, you have boolean variables. You have em clauses. Each of disjunction of collaterals literally is a variable, or it's, uh, negation. And the goal is to find an assignment to the variable, such that order clauses are true. This is a decision type problem from the MP class, which means you can checking polynomial time for satisfy ability off any assignment. And the three set is empty, complete with K three a larger, which means an efficient trees. That's over, uh, implies an efficient source for all the problems in the empty class, because all the problems in the empty class can be reduced in Polian on real time to reset. As a matter of fact, you can reduce the NP complete problems into each other. You can go from three set to set backing or two maximum dependent set, which is a set packing in graph theoretic notions or terms toe the icing graphs. A problem decision version. This is useful, and you're comparing different approaches, working on different kinds of problems when not all the closest can be satisfied. You're looking at the accusation version offset, uh called Max Set. And the goal here is to find assignment that satisfies the maximum number of clauses. And this is from the NPR class. In terms of applications. If we had inefficient sets over or np complete problems over, it was literally, positively influenced. Thousands off problems and applications in industry and and science. I'm not going to read this, but this this, of course, gives a strong motivation toe work on this kind of problems. Now our approach to set solving involves embedding the problem in a continuous space, and you use all the east to do that. So instead of working zeros and ones, we work with minus one across once, and we allow the corresponding variables toe change continuously between the two bounds. We formulate the problem with the help of a close metrics. If if a if a close, uh, does not contain a variable or its negation. The corresponding matrix element is zero. If it contains the variable in positive, for which one contains the variable in a gated for Mitt's negative one, and then we use this to formulate this products caused quote, close violation functions one for every clause, Uh, which really, continuously between zero and one. And they're zero if and only if the clause itself is true. Uh, then we form the define in order to define a dynamic such dynamics in this and dimensional hyper cube where the search happens and if they exist, solutions. They're sitting in some of the corners of this hyper cube. So we define this, uh, energy potential or landscape function shown here in a way that this is zero if and only if all the clauses all the kmc zero or the clauses off satisfied keeping these auxiliary variables a EMS always positive. And therefore, what you do here is a dynamics that is a essentially ingredient descend on this potential energy landscape. If you were to keep all the M's constant that it would get stuck in some local minimum. However, what we do here is we couple it with the dynamics we cooperated the clothes violation functions as shown here. And if he didn't have this am here just just the chaos. For example, you have essentially what case you have positive feedback. You have increasing variable. Uh, but in that case, you still get stuck would still behave will still find. So she is better than the constant version but still would get stuck only when you put here this a m which makes the dynamics in in this variable exponential like uh, only then it keeps searching until he finds a solution on deer is a reason for that. I'm not going toe talk about here, but essentially boils down toe performing a Grady and descend on a globally time barren landscape. And this is what works. Now I'm gonna talk about good or bad and maybe the ugly. Uh, this is, uh, this is What's good is that it's a hyperbolic dynamical system, which means that if you take any domain in the search space that doesn't have a solution in it or any socially than the number of trajectories in it decays exponentially quickly. And the decay rate is a characteristic in variant characteristic off the dynamics itself. Dynamical systems called the escape right the inverse off that is the time scale in which you find solutions by this by this dynamical system, and you can see here some song trajectories that are Kelty because it's it's no linear, but it's transient, chaotic. Give their sources, of course, because eventually knowledge to the solution. Now, in terms of performance here, what you show for a bunch off, um, constraint densities defined by M overran the ratio between closes toe variables for random, said Problems is random. Chris had problems, and they as its function off n And we look at money toward the wartime, the wall clock time and it behaves quite value behaves Azat party nominally until you actually he to reach the set on set transition where the hardest problems are found. But what's more interesting is if you monitor the continuous time t the performance in terms off the A narrow, continuous Time t because that seems to be a polynomial. And the way we show that is, we consider, uh, random case that random three set for a fixed constraint density Onda. We hear what you show here. Is that the right of the trash hold that it's really hard and, uh, the money through the fraction of problems that we have not been able to solve it. We select thousands of problems at that constraint ratio and resolve them without algorithm, and we monitor the fractional problems that have not yet been solved by continuous 90. And this, as you see these decays exponentially different. Educate rates for different system sizes, and in this spot shows that is dedicated behaves polynomial, or actually as a power law. So if you combine these two, you find that the time needed to solve all problems except maybe appear traction off them scales foreign or merely with the problem size. So you have paranormal, continuous time complexity. And this is also true for other types of very hard constraints and sexual problems such as exact cover, because you can always transform them into three set as we discussed before, Ramsey coloring and and on these problems, even algorithms like survey propagation will will fail. But this doesn't mean that P equals NP because what you have first of all, if you were toe implement these equations in a device whose behavior is described by these, uh, the keys. Then, of course, T the continue style variable becomes a physical work off. Time on that will be polynomial is scaling, but you have another other variables. Oxidative variables, which structured in an exponential manner. So if they represent currents or voltages in your realization and it would be an exponential cost Al Qaeda. But this is some kind of trade between time and energy, while I know how toe generate energy or I don't know how to generate time. But I know how to generate energy so it could use for it. But there's other issues as well, especially if you're trying toe do this son and digital machine but also happens. Problems happen appear. Other problems appear on in physical devices as well as we discuss later. So if you implement this in GPU, you can. Then you can get in order off to magnitude. Speed up. And you can also modify this to solve Max sad problems. Uh, quite efficiently. You are competitive with the best heuristic solvers. This is a weather problems. In 2016 Max set competition eso so this this is this is definitely this seems like a good approach, but there's off course interesting limitations, I would say interesting, because it kind of makes you think about what it means and how you can exploit this thes observations in understanding better on a low continues time complexity. If you monitored the discrete number the number of discrete steps. Don't buy the room, Dakota integrator. When you solve this on a digital machine, you're using some kind of integrator. Um and you're using the same approach. But now you measure the number off problems you haven't sold by given number of this kid, uh, steps taken by the integrator. You find out you have exponential, discrete time, complexity and, of course, thistles. A problem. And if you look closely, what happens even though the analog mathematical trajectory, that's the record here. If you monitor what happens in discrete time, uh, the integrator frustrates very little. So this is like, you know, third or for the disposition, but fluctuates like crazy. So it really is like the intervention frees us out. And this is because of the phenomenon of stiffness that are I'll talk a little bit a more about little bit layer eso. >>You know, it might look >>like an integration issue on digital machines that you could improve and could definitely improve. But actually issues bigger than that. It's It's deeper than that, because on a digital machine there is no time energy conversion. So the outside variables are efficiently representing a digital machine. So there's no exponential fluctuating current of wattage in your computer when you do this. Eso If it is not equal NP then the exponential time, complexity or exponential costs complexity has to hit you somewhere. And this is how um, but, you know, one would be tempted to think maybe this wouldn't be an issue in a analog device, and to some extent is true on our devices can be ordered to maintain faster, but they also suffer from their own problems because he not gonna be affect. That classes soldiers as well. So, indeed, if you look at other systems like Mirandizing machine measurement feedback, probably talk on the grass or selected networks. They're all hinge on some kind off our ability to control your variables in arbitrary, high precision and a certain networks you want toe read out across frequencies in case off CM's. You required identical and program because which is hard to keep, and they kind of fluctuate away from one another, shift away from one another. And if you control that, of course that you can control the performance. So actually one can ask if whether or not this is a universal bottleneck and it seems so aside, I will argue next. Um, we can recall a fundamental result by by showing harder in reaction Target from 1978. Who says that it's a purely computer science proof that if you are able toe, compute the addition multiplication division off riel variables with infinite precision, then you could solve any complete problems in polynomial time. It doesn't actually proposals all where he just chose mathematically that this would be the case. Now, of course, in Real warned, you have also precision. So the next question is, how does that affect the competition about problems? This is what you're after. Lots of precision means information also, or entropy production. Eso what you're really looking at the relationship between hardness and cost of computing off a problem. Uh, and according to Sean Hagar, there's this left branch which in principle could be polynomial time. But the question whether or not this is achievable that is not achievable, but something more cheerful. That's on the right hand side. There's always going to be some information loss, so mental degeneration that could keep you away from possibly from point normal time. So this is what we like to understand, and this information laws the source off. This is not just always I will argue, uh, in any physical system, but it's also off algorithm nature, so that is a questionable area or approach. But China gets results. Security theoretical. No, actual solar is proposed. So we can ask, you know, just theoretically get out off. Curiosity would in principle be such soldiers because it is not proposing a soldier with such properties. In principle, if if you want to look mathematically precisely what the solar does would have the right properties on, I argue. Yes, I don't have a mathematical proof, but I have some arguments that that would be the case. And this is the case for actually our city there solver that if you could calculate its trajectory in a loss this way, then it would be, uh, would solve epic complete problems in polynomial continuous time. Now, as a matter of fact, this a bit more difficult question, because time in all these can be re scared however you want. So what? Burns says that you actually have to measure the length of the trajectory, which is a new variant off the dynamical system or property dynamical system, not off its parameters ization. And we did that. So Suba Corral, my student did that first, improving on the stiffness off the problem off the integrations, using implicit solvers and some smart tricks such that you actually are closer to the actual trajectory and using the same approach. You know what fraction off problems you can solve? We did not give the length of the trajectory. You find that it is putting on nearly scaling the problem sites we have putting on your skin complexity. That means that our solar is both Polly length and, as it is, defined it also poorly time analog solver. But if you look at as a discreet algorithm, if you measure the discrete steps on a digital machine, it is an exponential solver. And the reason is because off all these stiffness, every integrator has tow truck it digitizing truncate the equations, and what it has to do is to keep the integration between the so called stability region for for that scheme, and you have to keep this product within a grimace of Jacoby in and the step size read in this region. If you use explicit methods. You want to stay within this region? Uh, but what happens that some off the Eigen values grow fast for Steve problems, and then you're you're forced to reduce that t so the product stays in this bonded domain, which means that now you have to you're forced to take smaller and smaller times, So you're you're freezing out the integration and what I will show you. That's the case. Now you can move to increase its soldiers, which is which is a tree. In this case, you have to make domain is actually on the outside. But what happens in this case is some of the Eigen values of the Jacobean, also, for six systems, start to move to zero. As they're moving to zero, they're going to enter this instability region, so your soul is going to try to keep it out, so it's going to increase the data T. But if you increase that to increase the truncation hours, so you get randomized, uh, in the large search space, so it's it's really not, uh, not going to work out. Now, one can sort off introduce a theory or language to discuss computational and are computational complexity, using the language from dynamical systems theory. But basically I I don't have time to go into this, but you have for heart problems. Security object the chaotic satellite Ouch! In the middle of the search space somewhere, and that dictates how the dynamics happens and variant properties off the dynamics. Of course, off that saddle is what the targets performance and many things, so a new, important measure that we find that it's also helpful in describing thesis. Another complexity is the so called called Makarov, or metric entropy and basically what this does in an intuitive A eyes, uh, to describe the rate at which the uncertainty containing the insignificant digits off a trajectory in the back, the flow towards the significant ones as you lose information because off arrows being, uh grown or are developed in tow. Larger errors in an exponential at an exponential rate because you have positively up north spawning. But this is an in variant property. It's the property of the set of all. This is not how you compute them, and it's really the interesting create off accuracy philosopher dynamical system. A zay said that you have in such a high dimensional that I'm consistent were positive and negatively upon of exponents. Aziz Many The total is the dimension of space and user dimension, the number off unstable manifold dimensions and as Saddam was stable, manifold direction. And there's an interesting and I think, important passion, equality, equality called the passion, equality that connect the information theoretic aspect the rate off information loss with the geometric rate of which trajectory separate minus kappa, which is the escape rate that I already talked about. Now one can actually prove a simple theorems like back off the envelope calculation. The idea here is that you know the rate at which the largest rated, which closely started trajectory separate from one another. So now you can say that, uh, that is fine, as long as my trajectory finds the solution before the projective separate too quickly. In that case, I can have the hope that if I start from some region off the face base, several close early started trajectories, they kind of go into the same solution orphaned and and that's that's That's this upper bound of this limit, and it is really showing that it has to be. It's an exponentially small number. What? It depends on the end dependence off the exponents right here, which combines information loss rate and the social time performance. So these, if this exponents here or that has a large independence or river linear independence, then you then you really have to start, uh, trajectories exponentially closer to one another in orderto end up in the same order. So this is sort off like the direction that you're going in tow, and this formulation is applicable toe all dynamical systems, uh, deterministic dynamical systems. And I think we can We can expand this further because, uh, there is, ah, way off getting the expression for the escaped rate in terms off n the number of variables from cycle expansions that I don't have time to talk about. What? It's kind of like a program that you can try toe pursuit, and this is it. So the conclusions I think of self explanatory I think there is a lot of future in in, uh, in an allo. Continue start computing. Um, they can be efficient by orders of magnitude and digital ones in solving empty heart problems because, first of all, many of the systems you like the phone line and bottleneck. There's parallelism involved, and and you can also have a large spectrum or continues time, time dynamical algorithms than discrete ones. And you know. But we also have to be mindful off. What are the possibility of what are the limits? And 11 open question is very important. Open question is, you know, what are these limits? Is there some kind off no go theory? And that tells you that you can never perform better than this limit or that limit? And I think that's that's the exciting part toe to derive thes thes this levian 10.

Published Date : Sep 27 2020

SUMMARY :

bifurcated critical point that is the one that I forget to the lowest pump value a. the chi to non linearity and see how and when you can get the Opio know that the classical approximation of the car testing machine, which is the ground toe, than the state of the art algorithm and CP to do this which is a very common Kasich. right the inverse off that is the time scale in which you find solutions by first of all, many of the systems you like the phone line and bottleneck.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Exxon MobilORGANIZATION

0.99+

AndyPERSON

0.99+

Sean HagarPERSON

0.99+

Daniel WennbergPERSON

0.99+

ChrisPERSON

0.99+

USCORGANIZATION

0.99+

CaltechORGANIZATION

0.99+

2016DATE

0.99+

100 timesQUANTITY

0.99+

BerkeleyLOCATION

0.99+

Tatsuya NagamotoPERSON

0.99+

twoQUANTITY

0.99+

1978DATE

0.99+

FoxORGANIZATION

0.99+

six systemsQUANTITY

0.99+

HarvardORGANIZATION

0.99+

Al QaedaORGANIZATION

0.99+

SeptemberDATE

0.99+

second versionQUANTITY

0.99+

CIAORGANIZATION

0.99+

IndiaLOCATION

0.99+

300 yardsQUANTITY

0.99+

University of TokyoORGANIZATION

0.99+

todayDATE

0.99+

BurnsPERSON

0.99+

Atsushi YamamuraPERSON

0.99+

0.14%QUANTITY

0.99+

48 coreQUANTITY

0.99+

0.5 microsecondsQUANTITY

0.99+

NSFORGANIZATION

0.99+

15 yearsQUANTITY

0.99+

CBSORGANIZATION

0.99+

NTTORGANIZATION

0.99+

first implementationQUANTITY

0.99+

first experimentQUANTITY

0.99+

123QUANTITY

0.99+

Army Research OfficeORGANIZATION

0.99+

firstQUANTITY

0.99+

1,904,711QUANTITY

0.99+

oneQUANTITY

0.99+

sixQUANTITY

0.99+

first versionQUANTITY

0.99+

StevePERSON

0.99+

2000 spinsQUANTITY

0.99+

five researcherQUANTITY

0.99+

CreoleORGANIZATION

0.99+

three setQUANTITY

0.99+

second partQUANTITY

0.99+

third partQUANTITY

0.99+

Department of Applied PhysicsORGANIZATION

0.99+

10QUANTITY

0.99+

eachQUANTITY

0.99+

85,900QUANTITY

0.99+

OneQUANTITY

0.99+

one problemQUANTITY

0.99+

136 CPUQUANTITY

0.99+

ToshibaORGANIZATION

0.99+

ScottPERSON

0.99+

2.4 gigahertzQUANTITY

0.99+

1000 timesQUANTITY

0.99+

two timesQUANTITY

0.99+

two partsQUANTITY

0.99+

131QUANTITY

0.99+

14,233QUANTITY

0.99+

more than 100 spinsQUANTITY

0.99+

two possible phasesQUANTITY

0.99+

13,580QUANTITY

0.99+

5QUANTITY

0.99+

4QUANTITY

0.99+

one microsecondsQUANTITY

0.99+

first stepQUANTITY

0.99+

first partQUANTITY

0.99+

500 spinsQUANTITY

0.99+

two identical photonsQUANTITY

0.99+

3QUANTITY

0.99+

70 years agoDATE

0.99+

IraqLOCATION

0.99+

one experimentQUANTITY

0.99+

zeroQUANTITY

0.99+

Amir Safarini NiniPERSON

0.99+

SaddamPERSON

0.99+

Fully Deniable Communication and Computation


 

>>Hi. Um, and thank you for inviting me to speak at the Entity Research Summit. And congratulations for NTT for setting up the neuroses club in the area. Okay, so I'm gonna talk about fully by deniable encryption and multiply the competition. And, uh, this is joint work with park from Harvard. And Santa will bring a, uh, she structurally right now in Russia during the rest. Um, so So so consider thesis, uh, two kids, which maybe some of you still remember its violence for check the incredible kids. And they are want they want to talk to each other privately without her mother learning what talking about. So here they are using this lead pipe, which is that cannot be secure Channel and and violent can say to that track that she doesn't want to do her homework and check it was the watch movie. And she knows that the judge will understand what she says. We hear what she says, but her mother, their mother, is not going to anything because it z this lead pipe. She doesn't know what they're talking about. Um and and and we know how to implement this actually in without lead pipes in the software will Do you have encryption, which, you know, you know, for I know, uh, 40 for the last 40 years or so, but actually for many more s. Oh, this is great. Encryption gives us private communication against, uh, eavesdropping adversary. So passive adversaries s but But you know that mothers can be more than passives. What if the mother he goes and asks Pilot that? What did you talk? What do you say to judge it So you know, if valid, really said, you know, used this'll end pipe. She can say whatever she wants to say. I actually said that I was study, and then the mother goes to judge. I can ask him what did about tell you, and she said that she was studied and the mother still cannot tell anything about what happened. She doesn't know trillions. Death was sent or not. Um, in fact, even if violence said that she was studying and and Jackson said something else that you know, she said she was she rather watch movie. Even then the mother doesn't know who was right. I mean, not from the pipe music. Look them in the eye and not this way, but not from the communication she doesn't. Andi. In fact, we could go on like this, and, you know, the lead type doesn't help at all to understand what really have. And this is really another very important form off this really secure channels that it doesn't allow external parties. Course, there's, uh, certain what really happened. Even when they asked to see all the internals of all the parties. In fact, even further, the Violet Jack Jack have no way to actually convince the mother that this is what happened. Even if you want, right, they have no way of actually proving to the mother that they said this and not the other thing with this lead pipe. So the question is can be obtained a similar effects with, you know, software encryption. Uh, can we have an encryption scheme that has the same sort of properties? So we know that Peoria, the total encryption doesn't have this property. That encryption leaves traces. So there's this cipher text that that the mother of the course of seized. Then when the mother goes toe the parties and you know the ballot judge, you can ask him uh, give me. Show me your randomness. Show me all the internals. I want to see what really? How you generated the text and how you decrypted it with no money. Encryption is only one way that, but inject, checking opened the suffer text, and therefore, there is no real privacy anymore. Um, so So this is the case. So so really to do to address this issue? The this this concept of deniable encryption that was considered, uh, you know, many years ago. Andi idea here is that you wanted encryption scheme that provides, uh, protection of privacy. Uh, on ability, toe keep private. You really, really, really value. And maybe, ah, fake or lie about what you say in a convincing way, even against such a course. Uh huh. So and so? So the idea is that, you know, So they actually do you think of three types here, So there is centered in apple. So we're just going us to center off the off the message. You know how How did you encrypt the message? Show me your encryption. Andalus Suing The decryption key is public. Um, and if you go to the receiver and ask him show me your decryption key. I want to see how you decrypted. And you can also think about natural case where the course actually goes to both parties and ask them for the for the internals and compares one against the other. Right? So this is the bite inability concept. Andi, you can, of course, naturally generalize it. Not just to encryption to, say, two party competition soon here, Violent and Jack. Jack. You know, uh, maybe not even trust each other fully, But they want toe compute together, you know? Or, you know, do they actually know a kid they both know and rapes in school, Right. So, So, So violent has her own list of kids, and she knows grapes and injection to, and they want to do this to Paris ST secure competition to figure out if they keep the both. And so if they have this ideal trusted party or stay for somewhere where they can actually do the security applications uh um, securely then they can, of course, learned the answer without learning anything else. And also, if the mother comes in after the fact and ask them, you know who I see that you were trying to figure out who very school, you know. So tell me what you did. Tell me your inputs them you are supposed to give me all the randomness. And And I want to know for the kids that you know, that vaping school. So if they were using such such a physically, I didn't secure gadget then, uh, then they can say You know why? You know? So So what is the state of, I don't know, anybody Invasion did Jack this theater and I got nothing into something or nothing. Jake Jackson. Consistency and off course. Mother has no way of knowing if this is true. No. And even if, uh, injected decides to tell the truth and actually tells is really important. Really put real randomness. And, uh, no randomness here and violent tells still here. Nothing. Nothing that the mother has no way of knowing which one is like. She clearly some of one of them is language. Doesn't know which one. I mean, chicken again looked deep in the eye, but not from the communication. She cannot figure out. Um, so s so we want to get something like that for for two party competition. Uh, and and and again, eso again, again, again. The case that, you know, one is like going to the truth is still don't know. Um, so the question is there a protocol that that one is still behavior, and, uh, incredible. How do you define us? Uh, and the point is that, you know, Okay, 11 further thing toe. Think about, you know, this doesn't shouldn't end with two parties can think about three or more parties on, uh, and the same thing happens. You know, just maybe the trust structure, the consistency structure becomes more complicated. Uh, you know, you could buy groups of people which is consistent with each other and not without, um Okay, so So what are our results here? So first result is regarding encryption. So we come up with the first bite, the novel communication protocol. It's not encryption because it's three messages. Uh, so it is three messages, and it is this way need a reference string, which is like, programs in the sky. And but it's a short registering. I mean, one short programs that everybody in the world uses for the encryptions for the entire duration of time. and our assumptions are some expansion, Leo in one functions, uh, and on. But just to say that what was done previously? It was just senator deniable or receiver deniable, um, And then and nothing that we do is that actually way define and also obtained this extra property, which we call off the record inability which talks with you about the case where, as I said before, that one party, uh uh, is saying one thing and the other practicing nothing they insisted. So they cannot. There is no way for them to frame each other. Um, and the way the other result is regarding a multiparty function evaluation on Dhere, we come up with the first all deniable secure function evaluation for quote Well, you know, I mean, I mean that the protocol with the adversary or the coarser expect to see all off the transcript of the competition, including all the randomness in all the internal state of all the parties eso superiors results in this area always assumed that you know, either the course only can concourse on some of the parties or if you can force all the parties and there is some some physical gadget, uh, which is crucial information about the personnel puts and you know, nobody can see inside, so no, here, we actually that the Attackers see everything. Uh, because they think they see everything on we can still provide inability onda protocol. Also, our protocols also withstand inconsistencies. Mean the case off this off the record style that one party says one thing partisans don't think. But this is only in the case of two parties and only for functions where the input size is polynomial in play. Put size. Uh, domain. Um, so in this actually interested open question how to extend it beyond that. Uh, so just to say that this is kind of it's a surprising thing that you can even do such thing, because what it allows you to do is actually such to completely rewrite history. Eso you during your competition on. Then somebody comes, and that will show me everything that happened. All the runners, all the entire transcript, the competition from beginning to the end. And you can now tell them something else. Not something that really happened. I mean, they see, you know, the public messages they see it on thistle is un contestable, but you can show different internals that there are very different than what really happened. And still nobody can catch you. So it's really some sense. Uh, who knows what's really happened? Um, so anyway, so So this is the, uh this is the result. Let's just say a few words about fully deniable encryption. Uh, just toe give a more detailed So So So So, how do you define this? Fully deniable encryption. So first I want to say that, you know, if you just, uh if the parties have appreciate key then, uh, deniability is with these because what you know, you just in orderto cryptic message just want some part of the key. And this one temple is completely deniable, right? Because you can just take this self a text and claim that it was any message encryption off any message off your choice. But just, you know, extra it. But just coming up with the key, which is the Solvents Architects as a message of futures. So this is completely diamond by both parties, and even it's off the record because if the two parties say different things, there's no way to know what's right. So Eh, so what? But it means that, you know, the hard part is actually had to come up with this shirt key, uh, in a deniable way. So you can actually later argued that this key was an, um so s so we need kind of deniable key exchange, and then this is what we do. So we come up with this idea by by the application of what? This what this means. So it's a protocol, you know, for two parties, uh, change, keep with messages and which gives you the ability to life. Somebody asked you which was key and claim it was anything, uh, later. So more formally. So we have two parties. One You know, this is the key change protocol for one party, and this is the kitchen for the other party in each party also is equipped with this faking algorithm. This is s faking arctic. I keep, you know, Senator, receiver, Even though it's not teach change, it's affecting and breaking. Allows you to come up with fake randomness. That demonstrate kills anything and we want correctly since semantic security as usual and we want toe this s fake takes a transcript and the randomness and the old key in the nuclear that you want. Andi comes up with fake randomness such that, uh um and this is you know, that that consistent with this new key, k prime and the same for the receiver. It comes up with a new randomness. The assistant to the crime and the requirement is that, uh, the attack. I cannot tell the difference between the experiment when you know the key key was exchanged. These transcripts respecto the real key or the case where the key was exchanged, and then the faking accurately going folk What? The adversary seizes the actual transcript, but then opening to a different. So there's a distinguished group. Um, And then what if the parties that were okay then there is another requirement there that says that even if the parties you know, one of them face, the other one doesn't and they then you can't tell which one will effect in which one wants to tell the truth. Onda point is that this to this to produce properties together really give you what you would like for my dearly your channel, even with respect toe courses. Um, so just to point out that you know this, this properties hold only if the parties in the follow the protocol during the execution actually choose randomness is they should. Otherwise things does work. In fact, otherwise, there's nothing that could work because the party's chief from the beginning and just use the terroristic protocol instead of randomized or just, you know, just randomness, which is predetermined. And, of course, nothing you can do. Uh, however, you know, there are, of course, interesting situations where it is. You know, it's reasonable to trust that the parties are actually using the randomness Aziz instructed during the execution of the protocol, for instance, we're thinking about voting this something can be forced, uh, by the voting booth, but you know, other situations. But this is kind of like essentially eso maybe another minute to say a few words about, you know, just like construction. How it kind of works in, you know, in general. So So we have, like, a three months, three rounds protocols. So we have four programs, you know, two from each party don't to deal with the three messages. Then we have a faking program for each party, so the way it works, you know, first, the violent here is has this is Harris randomness and actually chooses the key that they're going Thio agree ahead of time. It inputs to the first program which is going to think of it is the office care program black box program. And there's the message. First message is basically a harsh appear f off the K and then the, uh and then the responder gets this message has its own randomness and outputs. Another message, which is the hash off the first message agronomists. And then the third message now is going to be a new encryption off the key on the hashes and the end to a previous messages. This is, ah, company encryption off this one long spring and then the fourth with the fourth program just takes the randomness off the receiver and the two messages and put it in. And then I'll put the key, which is decrypted essentially the Crips, the subtextual from here in the old checks, right? And then the faking programs. What they do, they just take those. The transcript and the cookie and the new key and the striking program here are puts a new randomness for the senator and this one There's a new randomness for the receiver and the way it does near random estrogen offering work eyes, uh, is again It's kind of fact natural a t least the face of it. It uses the seeking hidden triggers idea off, off, so high in waters for descending on the inability that, you know, trigger each one of those programs toe put actually write message even when you get this, uh, crime on eventually this k problems are Well, the problem is that this scene in triggers, you know, give you local consistency for each problem by itself. This was this was the east their goal. But there is no global consistency about those six programs together and and get the six programs together to be consistent with the fact that the key would actually keep prominent K is high in contribute. And this is something that we become the main challenge of this work. This also, I did this three messages because if you have only to then there is no way to get a double consistency. Ah, s O s. So this is, uh this is the test on just to say about, you know, the future. So definitely we want stronger than ability for for MPC. As I said, we just give partial results there on. Then there is kind of, like some very interesting questions. One is like in general, You know, we know that your is very nice, but in many cases, we actually can do things without, uh but in this situation with prosecution, but maybe the inability of one of the very few cases where actually, we don't have any other way to do things out of the Neo. Is it really essential? Can we prove it? You know, and if not, can we do without? Can we get around CRS? Can you actually do with public friend of mysterious? Uh, you know, and more generally? Uh, no. We actually, uh, sweated a lot. You know, spit blood. In order to make this thing work with Leo and because I always really hard to work with, you know, would agree toe, find some some some general set of tools to work more easily. I was there. Um, Louis, thank you very much on death's

Published Date : Sep 26 2020

SUMMARY :

So the idea is that, you know, So they actually do you think of three types here,

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
RussiaLOCATION

0.99+

two partiesQUANTITY

0.99+

JacksonPERSON

0.99+

three messagesQUANTITY

0.99+

LouisPERSON

0.99+

two messagesQUANTITY

0.99+

Jake JacksonPERSON

0.99+

twoQUANTITY

0.99+

third messageQUANTITY

0.99+

both partiesQUANTITY

0.99+

each partyQUANTITY

0.99+

two kidsQUANTITY

0.99+

first biteQUANTITY

0.99+

First messageQUANTITY

0.99+

one partyQUANTITY

0.99+

six programsQUANTITY

0.99+

NTTORGANIZATION

0.99+

fourthQUANTITY

0.99+

SantaPERSON

0.99+

LeoPERSON

0.99+

three messagesQUANTITY

0.99+

first messageQUANTITY

0.99+

JackPERSON

0.99+

AzizPERSON

0.99+

three monthsQUANTITY

0.99+

bothQUANTITY

0.99+

each problemQUANTITY

0.99+

three typesQUANTITY

0.99+

two partyQUANTITY

0.99+

first programQUANTITY

0.98+

OneQUANTITY

0.98+

oneQUANTITY

0.98+

fourth programQUANTITY

0.98+

four programsQUANTITY

0.98+

firstQUANTITY

0.97+

one wayQUANTITY

0.97+

three roundsQUANTITY

0.97+

appleORGANIZATION

0.97+

HarvardORGANIZATION

0.97+

one short programsQUANTITY

0.97+

40QUANTITY

0.96+

Entity Research SummitEVENT

0.96+

one thingQUANTITY

0.96+

one functionsQUANTITY

0.94+

threeQUANTITY

0.93+

11QUANTITY

0.93+

PeoriaORGANIZATION

0.91+

DhereORGANIZATION

0.87+

many years agoDATE

0.87+

first resultQUANTITY

0.87+

AndiPERSON

0.84+

Violet Jack JackPERSON

0.83+

HarrisPERSON

0.81+

more partiesQUANTITY

0.81+

each oneQUANTITY

0.78+

Paris STLOCATION

0.77+

doubleQUANTITY

0.75+

one templeQUANTITY

0.67+

AndalusPERSON

0.66+

trillionsQUANTITY

0.62+

last 40 yearsDATE

0.62+

CRSORGANIZATION

0.59+

eachQUANTITY

0.54+

Machine Learning Applied to Computationally Difficult Problems in Quantum Physics


 

>> My name is Franco Nori. Is a great pleasure to be here and I thank you for attending this meeting and I'll be talking about some of the work we are doing within the NTT-PHI group. I would like to thank the organizers for putting together this very interesting event. The topics studied by NTT-PHI are very exciting and I'm glad to be part of this great team. Let me first start with a brief overview of just a few interactions between our team and other groups within NTT-PHI. After this brief overview or these interactions then I'm going to start talking about machine learning and neural networks applied to computationally difficult problems in quantum physics. The first one I would like to raise is the following. Is it possible to have decoherence free interaction between qubits? And the proposed solution was a postdoc and a visitor and myself some years ago was to study decoherence free interaction between giant atoms made of superconducting qubits in the context of waveguide quantum electrodynamics. The theoretical prediction was confirmed by a very nice experiment performed by Will Oliver's group at MIT was probably so a few months ago in nature and it's called waveguide quantum electrodynamics with superconducting artificial giant atoms. And this is the first joint MIT Michigan nature paper during this NTT-PHI grand period. And we're very pleased with this. And I look forward to having additional collaborations like this one also with other NTT-PHI groups, Another collaboration inside NTT-PHI regards the quantum hall effects in a rapidly rotating polarity and condensates. And this work is mainly driven by two people, a Michael Fraser and Yoshihisa Yamamoto. They are the main driving forces of this project and this has been a great fun. We're also interacting inside the NTT-PHI environment with the groups of marandI Caltech, like McMahon Cornell, Oliver MIT, and as I mentioned before, Fraser Yamamoto NTT and others at NTT-PHI are also very welcome to interact with us. NTT-PHI is interested in various topics including how to use neural networks to solve computationally difficult and important problems. Let us now look at one example of using neural networks to study computationally difficult and hard problems. Everything we'll be talking today is mostly working progress to be extended and improve in the future. So the first example I would like to discuss is topological quantum phase transition retrieved through manifold learning, which is a variety of version of machine learning. This work is done in collaboration with Che, Gneiting and Liu all members of the group. preprint is available in the archive. Some groups are studying a quantum enhanced machine learning where machine learning is supposed to be used in actual quantum computers to use exponential speed-up and using quantum error correction we're not working on these kind of things we're doing something different. We're studying how to apply machine learning applied to quantum problems. For example how to identify quantum phases and phase transitions. We shall be talking about right now. How to achieve, how to perform quantum state tomography in a more efficient manner. That's another work of ours which I'll be showing later on. And how to assist the experimental data analysis which is a separate project which we recently published. But I will not discuss today because the experiments can produce massive amounts of data and machine learning can help to understand these huge tsunami of data provided by these experiments. Machine learning can be either supervised or unsupervised. Supervised is requires human labeled data. So we have here the blue dots have a label. The red dots have a different label. And the question is the new data corresponds to either the blue category or the red category. And many of these problems in machine learning they use the example of identifying cats and dogs but this is typical example. However, there are the cases which are also provides with there are no labels. So you're looking at the cluster structure and you need to define a metric, a distance between the different points to be able to correlate them together to create these clusters. And you can manifold learning is ideally suited to look at problems we just did our non-linearities and unsupervised. Once you're using the principle component analysis along this green axis here which are the principal axis here. You can actually identify a simple structure with linear projection when you increase the axis here, you get the red dots in one area, and the blue dots down here. But in general you could get red green, yellow, blue dots in a complicated manner and the correlations are better seen when you do an nonlinear embedding. And in unsupervised learning the colors represent similarities are not labels because there are no prior labels here. So we are interested on using machine learning to identify topological quantum phases. And this requires looking at the actual phases and their boundaries. And you start from a set of Hamiltonians or wave functions. And recall that this is difficult to do because there is no symmetry breaking, there is no local order parameters and in complicated cases you can not compute the topological properties analytically and numerically is very hard. So therefore machine learning is enriching the toolbox for studying topological quantum phase transitions. And before our work, there were quite a few groups looking at supervised machine learning. The shortcomings that you need to have prior knowledge of the system and the data must be labeled for each phase. This is needed in order to train the neural networks . More recently in the past few years, there has been increased push on looking at all supervised and Nonlinear embeddings. One of the shortcomings we have seen is that they all use the Euclidean distance which is a natural way to construct the similarity matrix. But we have proven that it is suboptimal. It is not the optimal way to look at distance. The Chebyshev distances provides better performance. So therefore the difficulty here is how to detect topological quantifies transition is a challenge because there is no local order parameters. Few years ago we thought well, three or so years ago machine learning may provide effective methods for identifying topological Features needed in the past few years. The past two years several groups are moving this direction. And we have shown that one type of machine learning called manifold learning can successfully retrieve topological quantum phase transitions in momentum and real spaces. We have also Shown that if you use the Chebyshev distance between data points are supposed to Euclidean distance, you sharpen the characteristic features of these topological quantum phases in momentum space and the afterwards we do so-called diffusion map, Isometric map can be applied to implement the dimensionality reduction and to learn about these phases and phase transition in an unsupervised manner. So this is a summary of this work on how to characterize and study topological phases. And the example we used is to look at the canonical famous models like the SSH model, the QWZ model, the quenched SSH model. We look at this momentous space and the real space, and we found that the metal works very well in all of these models. And moreover provides a implications and demonstrations for learning also in real space where the topological invariants could be either or known or hard to compute. So it provides insight on both momentum space and real space and its the capability of manifold learning is very good especially when you have the suitable metric in exploring topological quantum phase transition. So this is one area we would like to keep working on topological faces and how to detect them. Of course there are other problems where neural networks can be useful to solve computationally hard and important problems in quantum physics. And one of them is quantum state tomography which is important to evaluate the quality of state production experiments. The problem is quantum state tomography scales really bad. It is impossible to perform it for six and a half 20 qubits. If you have 2000 or more forget it, it's not going to work. So now we're seeing a very important process which is one here tomography which cannot be done because there is a computationally hard bottleneck. So machine learning is designed to efficiently handle big data. So the question we're asking a few years ago is chemistry learning help us to solve this bottleneck which is quantum state tomography. And this is a project called Eigenstate extraction with neural network tomography with a student Melkani , research scientists of the group Clemens Gneiting and I'll be brief in summarizing this now. The specific machine learning paradigm is the standard artificial neural networks. They have been recently shown in the past couple of years to be successful for tomography of pure States. Our approach will be to carry this over to mixed States. And this is done by successively reconstructing the eigenStates or the mixed states. So it is an iterative procedure where you can slowly slowly get into the desired target state. If you wish to see more details, this has been recently published in phys rev A and has been selected as a editor suggestion. I mean like some of the referees liked it. So tomography is very hard to do but it's important and machine learning can help us to do that using neural networks and these to achieve mixed state tomography using an iterative eigenstate reconstruction. So why it is so challenging? Because you're trying to reconstruct the quantum States from measurements. You have a single qubit, you have a few Pauli matrices there are very few measurements to make when you have N qubits then the N appears in the exponent. So the number of measurements grows exponentially and this exponential scaling makes the computation to be very difficult. It's prohibitively expensive for large system sizes. So this is the bottleneck is these exponential dependence on the number of qubits. So by the time you get to 20 or 24 it is impossible. It gets even worst. Experimental data is noisy and therefore you need to consider maximum-likelihood estimation in order to reconstruct the quantum state that kind of fits the measurements best. And again these are expensive. There was a seminal work sometime ago on ion-traps. The post-processing for eight qubits took them an entire week. There were different ideas proposed regarding compressed sensing to reduce measurements, linear regression, et cetera. But they all have problems and you quickly hit a wall. There's no way to avoid it. Indeed the initial estimate is that to do tomography for 14 qubits state, you will take centuries and you cannot support a graduate student for a century because you need to pay your retirement benefits and it is simply complicated. So therefore a team here sometime ago we're looking at the question of how to do a full reconstruction of 14-qubit States with in four hours. Actually it was three point three hours Though sometime ago and many experimental groups were telling us that was very popular paper to read and study because they wanted to do fast quantum state tomography. They could not support the student for one or two centuries. They wanted to get the results quickly. And then because we need to get these density matrices and then they need to do these measurements here. But we have N qubits the number of expectation values go like four to the N to the Pauli matrices becomes much bigger. A maximum likelihood makes it even more time consuming. And this is the paper by the group in Inns brook, where they go this one week post-processing and they will speed-up done by different groups and hours. Also how to do 14 qubit tomography in four hours, using linear regression. But the next question is can machine learning help with quantum state tomography? Can allow us to give us the tools to do the next step to improve it even further. And then the standard one is this one here. Therefore for neural networks there are some inputs here, X1, X2 X3. There are some weighting factors when you get an output function PHI we just call Nonlinear activation function that could be heavy side Sigmon piecewise, linear logistic hyperbolic. And this creates a decision boundary and input space where you get let's say the red one, the red dots on the left and the blue dots on the right. Some separation between them. And you could have either two layers or three layers or any number layers can do either shallow or deep. This cannot allow you to approximate any continuous function. You can train data via some cost function minimization. And then there are different varieties of neural nets. We're looking at some sequel restricted Boltzmann machine. Restricted means that the input layer speeds are not talking to each other. The output layers means are not talking to each other. And we got reasonably good results with the input layer, output layer, no hidden layer and the probability of finding a spin configuration called the Boltzmann factor. So we try to leverage Pure-state tomography for mixed-state tomography. By doing an iterative process where you start here. So there are the mixed States in the blue area the pure States boundary here. And then the initial state is here with the iterative process you get closer and closer to the actual mixed state. And then eventually once you get here, you do the final jump inside. So you're looking at a dominant eigenstate which is closest pure state and then computer some measurements and then do an iterative algorithm that to make you approach this desire state. And after you do that then you can essentially compare results with some data. We got some data for four to eight trapped-ion qubits approximate W States were produced and they were looking at let's say the dominant eigenstate is reliably recorded for any equal four, five six, seven, eight for the ion-state, for the eigenvalues we're still working because we're getting some results which are not as accurate as we would like to. So this is still work in progress, but for the States is working really well. So there is some cost scaling which is beneficial, goes like NR as opposed to N squared. And then the most relevant information on the quality of the state production is retrieved directly. This works for flexible rank. And so it is possible to extract the ion-state within network tomography. It is cost-effective and scalable and delivers the most relevant information about state generation. And it's an interesting and viable use case for machine learning in quantum physics. We're also now more recently working on how to do quantum state tomography using Conditional Generative Adversarial Networks. Usually the masters student are analyzed in PhD and then two former postdocs. So this CGANs refers to this Conditional Generative Adversarial Networks. In this framework you have two neural networks which are essentially having a dual, they're competing with each other. And one of them is called generator another one is called discriminator. And there they're learning multi-modal models from the data. And then we improved these by adding a cost of neural network layers that enable the conversion of outputs from any standard neural network into physical density matrix. So therefore to reconstruct the density matrix, the generator layer and the discriminator networks So the two networks, they must train each other on data using standard gradient-based methods. So we demonstrate that our quantum state tomography and the adversarial network can reconstruct the optical quantum state with very high fidelity which is orders of magnitude faster and from less data than a standard maximum likelihood metals. So we're excited about this. We also show that this quantum state tomography with these adversarial networks can reconstruct a quantum state in a single evolution of the generator network. If it has been pre-trained on similar quantum States. so requires some additional training. And all of these is still work in progress where some preliminary results written up but we're continuing. And I would like to thank all of you for attending this talk. And thanks again for the invitation.

Published Date : Sep 26 2020

SUMMARY :

And recall that this is difficult to do

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Michael FraserPERSON

0.99+

Franco NoriPERSON

0.99+

Yoshihisa YamamotoPERSON

0.99+

oneQUANTITY

0.99+

NTT-PHIORGANIZATION

0.99+

two peopleQUANTITY

0.99+

two layersQUANTITY

0.99+

Clemens GneitingORGANIZATION

0.99+

20QUANTITY

0.99+

MITORGANIZATION

0.99+

three hoursQUANTITY

0.99+

firstQUANTITY

0.99+

three layersQUANTITY

0.99+

fourQUANTITY

0.99+

one weekQUANTITY

0.99+

MelkaniPERSON

0.99+

14 qubitsQUANTITY

0.99+

todayDATE

0.98+

one areaQUANTITY

0.98+

first exampleQUANTITY

0.98+

Inns brookLOCATION

0.98+

six and a half 20 qubitsQUANTITY

0.98+

24QUANTITY

0.98+

four hoursQUANTITY

0.98+

Will OliverPERSON

0.98+

two centuriesQUANTITY

0.98+

Few years agoDATE

0.98+

first jointQUANTITY

0.98+

OneQUANTITY

0.98+

bothQUANTITY

0.98+

each phaseQUANTITY

0.97+

three pointQUANTITY

0.96+

Fraser YamamotoPERSON

0.96+

two networksQUANTITY

0.96+

first oneQUANTITY

0.96+

2000QUANTITY

0.96+

sixQUANTITY

0.95+

fiveQUANTITY

0.94+

14 qubitQUANTITY

0.94+

BoltzmannOTHER

0.94+

a centuryQUANTITY

0.93+

one exampleQUANTITY

0.93+

eight qubitsQUANTITY

0.92+

CaltechORGANIZATION

0.91+

NTTORGANIZATION

0.91+

centuriesQUANTITY

0.91+

few months agoDATE

0.91+

singleQUANTITY

0.9+

OliverPERSON

0.9+

two former postdocsQUANTITY

0.9+

single qubitQUANTITY

0.89+

few years agoDATE

0.88+

14-qubitQUANTITY

0.86+

NTT-PHITITLE

0.86+

eightQUANTITY

0.86+

MichiganLOCATION

0.86+

past couple of yearsDATE

0.85+

two neuralQUANTITY

0.84+

sevenQUANTITY

0.83+

eight trapped-QUANTITY

0.83+

three or so years agoDATE

0.82+

LiuPERSON

0.8+

PauliOTHER

0.79+

one typeQUANTITY

0.78+

past two yearsDATE

0.77+

some years agoDATE

0.73+

CornellPERSON

0.72+

McMahonORGANIZATION

0.71+

GneitingPERSON

0.69+

ChebyshevOTHER

0.68+

few yearsDATE

0.67+

phys revTITLE

0.65+

past few yearsDATE

0.64+

NTTEVENT

0.64+

ChePERSON

0.63+

CGANsORGANIZATION

0.61+

BoltzmannPERSON

0.57+

EuclideanLOCATION

0.57+

marandIORGANIZATION

0.5+

HamiltoniansOTHER

0.5+

eachQUANTITY

0.5+

NTTTITLE

0.44+

-PHITITLE

0.31+

PHIORGANIZATION

0.31+

Programmable Quantum Simulators: Theory and Practice


 

>>Hello. My name is Isaac twang and I am on the faculty at MIT in electrical engineering and computer science and in physics. And it is a pleasure for me to be presenting at today's NTT research symposium of 2020 to share a little bit with you about programmable quantum simulators theory and practice the simulation of physical systems as described by their Hamiltonian. It's a fundamental problem which Richard Fineman identified early on as one of the most promising applications of a hypothetical quantum computer. The real world around us, especially at the molecular level is described by Hamiltonians, which captured the interaction of electrons and nuclei. What we desire to understand from Hamiltonian simulation is properties of complex molecules, such as this iron molded to them. Cofactor an important catalyst. We desire there are ground States, reaction rates, reaction dynamics, and other chemical properties, among many things for a molecule of N Adams, a classical simulation must scale exponentially within, but for a quantum simulation, there is a potential for this simulation to scale polynomials instead. >>And this would be a significant advantage if realizable. So where are we today in realizing such a quantum advantage today? I would like to share with you a story about two things in this quest first, a theoretical optimal quantum simulation, awkward them, which achieves the best possible runtime for generic Hamiltonian. Second, let me share with you experimental results from a quantum simulation implemented using available quantum computing hardware today with a hardware efficient model that goes beyond what is utilized by today's algorithms. I will begin with the theoretically optimal quantum simulation uncle rhythm in principle. The goal of quantum simulation is to take a time independent Hamiltonian age and solve Schrodinger's equation has given here. This problem is as hard as the hardest quantum computation. It is known as being BQ P complete a simplification, which is physically reasonable and important in practice is to assume that the Hamiltonian is a sum over terms which are local. >>For example, due to allow to structure these local terms, typically do not commute, but their locality means that each term is reasonably small, therefore, as was first shown by Seth Lloyd in 1996, one way to compute the time evolution that is the exponentiation of H with time is to use the lead product formula, which involves a successive approximation by repetitive small time steps. The cost of this charterization procedure is a number of elementary steps, which scales quadratically with the time desired and inverse with the error desired for the simulation output here then is the number of local terms in the Hamiltonian. And T is the desired simulation time where Epsilon is the desired simulation error. Today. We know that for special systems and higher or expansions of this formula, a better result can be obtained such as scaling as N squared, but as synthetically linear in time, this however is for a special case, the latest Hamiltonians and it would be desirable to scale generally with time T for a order T time simulation. >>So how could such an optimal quantum simulation be constructed? An important ingredient is to transform the quantum simulation into a quantum walk. This was done over 12 years ago, Andrew trials showing that for sparse Hamiltonians with around de non-zero entries per row, such as shown in this graphic here, one can do a quantum walk very much like a classical walk, but in a superposition of right and left shown here in this quantum circuit, where the H stands for a hazard market in this particular circuit, the head Mar turns the zero into a superposition of zero and one, which then activate the left. And the right walk in superposition to graph of the walk is defined by the Hamiltonian age. And in doing so Childs and collaborators were able to show the walk, produces a unitary transform, which goes as E to the minus arc co-sign of H times time. >>So this comes close, but it still has this transcendental function of age, instead of just simply age. This can be fixed with some effort, which results in an algorithm, which scales approximately as towel log one over Epsilon with how is proportional to the sparsity of the Hamiltonian and the simulation time. But again, the scaling here is a multiplicative product rather than an additive one, an interesting insight into the dynamics of a cubit. The simplest component of a quantum computer provides a way to improve upon this single cubits evolve as rotations in a sphere. For example, here is shown a rotation operator, which rotates around the axis fi in the X, Y plane by angle theta. If one, the result of this rotation as a projection along the Z axis, the result is a co-sign squared function. That is well-known as a Ravi oscillation. On the other hand, if a cubit is rotated around multiple angles in the X Y plane, say around the fee equals zero fee equals 1.5 and fee equals zero access again, then the resulting response function looks like a flat top. >>And in fact, generalizing this to five or more pulses gives not just flattered hops, but in fact, arbitrary functions such as the Chevy chef polynomial shown here, which gets transplants like bullying or, and majority functions remarkably. If one does rotations by angle theta about D different angles in the X Y plane, the result is a response function, which is a polynomial of order T in co-sign furthermore, as captured by this theorem, given a nearly arbitrary degree polynomial there exists angles fi such that one can achieve the desired polynomial. This is the result that derives from the Remez exchange algorithm used in classical discreet time signal processing. So how does this relate to quantum simulation? Well recall that a quantum walk essentially embeds a Hamiltonian insight, the unitary transform of a quantum circuit, this embedding generalize might be called and it involves the use of a cubit acting as a projector to control the application of H if we generalize the quantum walk to include a rotation about access fee in the X Y plane, it turns out that one obtains a polynomial transform of H itself. >>And this it's the same as the polynomial in the quantum signal processing theorem. This is a remarkable result known as the quantum synchrony value transformed theorem from contrast Julian and Nathan weep published last year. This provides a quantum simulation auger them using quantum signal processing. For example, can start with the quantum walk result and then apply quantum signal processing to undo the arc co-sign transformation and therefore obtain the ideal expected Hamiltonian evolution E to the minus I H T the resulting algorithm costs a number of elementary steps, which scales as just the sum of the evolution time and the log of one over the error desired this saturates, the known lower bound, and thus is the optimal quantum simulation algorithm. This table from a recent review article summarizes a comparison of the query complexities of the known major quantum simulation algorithms showing that the cubitus station and quantum sequel processing algorithm is indeed optimal. >>Of course, this optimality is a theoretical result. What does one do in practice? Let me now share with you the story of a hardware efficient realization of a quantum simulation on actual hardware. The promise of quantum computation traditionally rests on a circuit model, such as the one we just used with quantum circuits, acting on cubits in contrast, consider a real physical problem from quantum chemistry, finding the structure of a molecule. The starting point is the point Oppenheimer separation of the electronic and vibrational States. For example, to connect it, nuclei, share a vibrational mode, the potential energy of this nonlinear spring, maybe model as a harmonic oscillator since the spring's energy is determined by the electronic structure. When the molecule becomes electronically excited, this vibrational mode changes one obtains, a different frequency and different equilibrium positions for the nuclei. This corresponds to a change in the spring, constant as well as a displacement of the nuclear positions. >>And we may write down a full Hamiltonian for this system. The interesting quantum chemistry question is known as the Frank Condon problem. What is the probability of transition between the original ground state and a given vibrational state in the excited state spectrum of the molecule, the Frank content factor, which gives this transition probability is foundational to quantum chemistry and a very hard and generic question to answer, which may be amiable to solution on a quantum computer in particular and natural quantum computer to use might be one which already has harmonic oscillators rather than one, which has just cubits. This has provided any Sonic quantum processors, such as the superconducting cubits system shown here. This processor has both cubits as embodied by the Joseph's injunctions shown here, and a harmonic oscillator as embodied by the resonant mode of the transmission cavity. Given here more over the output of this planar superconducting circuit can be connected to three dimensional cavities instead of using cubit Gates. >>One may perform direct transformations on the bull's Arctic state using for example, beam splitters, phase shifters, displacement, and squeezing operators, and the harmonic oscillator, and may be initialized and manipulated directly. The availability of the cubit allows photon number resolve counting for simulating a tri atomic two mode, Frank Condon factor problem. This superconducting cubits system with 3d cavities was to resonators cavity a and cavity B represent the breathing and wiggling modes of a Triumeq molecule. As depicted here. The coupling of these moles was mediated by a superconducting cubit and read out was accomplished by two additional superconducting cubits, coupled to each one of the cavities due to the superconducting resonators used each one of the cavities had a, a long coherence time while resonator States could be prepared and measured using these strong coupling of cubits to the cavity. And Posana quantum operations could be realized by modulating the coupling cubit in between the two cavities, the cavities are holes drilled into pure aluminum, kept superconducting by millikelvin scale. >>Temperatures microfiber, KT chips with superconducting cubits are inserted into ports to couple via a antenna to the microwave cavities. Each of the cavities has a quality factor so high that the coherence times can reach milliseconds. A coupling cubit chip is inserted into the port in between the cavities and the readout and preparation cubit chips are inserted into ports on the sides. For sake of brevity, I will skip the experimental details and present just the results shown here is the fibrotic spectrum obtained for a water molecule using the Pulsonix superconducting processor. This is a typical Frank content spectrum giving the intensity of lions versus frequency in wave number where the solid line depicts the theoretically expected result and the purple and red dots show two sets of experimental data. One taken quickly and another taken with exhaustive statistics. In both cases, the experimental results have good agreement with the theoretical expectations. >>The programmability of this system is demonstrated by showing how it can easily calculate the Frank Condon spectrum for a wide variety of molecules. Here's another one, the ozone and ion. Again, we see that the experimental data shown in points agrees well with the theoretical expectation shown as a solid line. Let me emphasize that this quantum simulation result was obtained not by using a quantum computer with cubits, but rather one with resonators, one resonator representing each one of the modes of vibration in this trial, atomic molecule. This approach represents a far more efficient utilization of hardware resources compared with the standard cubit model because of the natural match of the resonators with the physical system being simulated in comparison, if cubit Gates had been utilized to perform the same simulation on the order of a thousand cubit Gates would have been required compared with the order of 10 operations, which were performed for this post Sonic realization. >>As in topically, the Cupid motto would have required significantly more operations because of the need to retire each one of the harmonic oscillators into some max Hilbert space size compared with the optimal quantum simulation auger rhythms shown in the first half of this talk, we see that there is a significant gap between available quantum computing hardware can perform and what optimal quantum simulations demand in terms of the number of Gates required for a simulation. Nevertheless, many of the techniques that are used for optimal quantum simulation algorithms may become useful, especially if they are adapted to available hardware, moving for the future, holds some interesting challenges for this field. Real physical systems are not cubits, rather they are composed from bolt-ons and from yawns and from yawns need global anti-Semitism nation. This is a huge challenge for electronic structure calculation in molecules, real physical systems also have symmetries, but current quantum simulation algorithms are largely governed by a theorem, which says that the number of times steps required is proportional to the simulation time. Desired. Finally, real physical systems are not purely quantum or purely classical, but rather have many messy quantum classical boundaries. In fact, perhaps the most important systems to simulate are really open quantum systems. And these dynamics are described by a mixture of quantum and classical evolution and the desired results are often thermal and statistical properties. >>I hope this presentation of the theory and practice of quantum simulation has been interesting and worthwhile. Thank you.

Published Date : Sep 24 2020

SUMMARY :

one of the most promising applications of a hypothetical quantum computer. is as hard as the hardest quantum computation. the time evolution that is the exponentiation of H with time And the right walk in superposition If one, the result of this rotation as This is the result that derives from the Remez exchange algorithm log of one over the error desired this saturates, the known lower bound, The starting point is the point Oppenheimer separation of the electronic and vibrational States. spectrum of the molecule, the Frank content factor, which gives this transition probability The availability of the cubit Each of the cavities has a quality factor so high that the coherence times can reach milliseconds. the natural match of the resonators with the physical system being simulated quantum simulation auger rhythms shown in the first half of this talk, I hope this presentation of the theory and practice of quantum simulation has been interesting

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Richard FinemanPERSON

0.99+

JosephPERSON

0.99+

Isaac twangPERSON

0.99+

Seth LloydPERSON

0.99+

1996DATE

0.99+

SchrodingerPERSON

0.99+

AndrewPERSON

0.99+

TodayDATE

0.99+

fiveQUANTITY

0.99+

last yearDATE

0.99+

JulianPERSON

0.99+

MITORGANIZATION

0.99+

both casesQUANTITY

0.99+

10 operationsQUANTITY

0.99+

SecondQUANTITY

0.99+

two cavitiesQUANTITY

0.99+

Frank CondonPERSON

0.99+

each termQUANTITY

0.99+

NathanPERSON

0.99+

first halfQUANTITY

0.99+

1.5QUANTITY

0.99+

firstQUANTITY

0.98+

two setsQUANTITY

0.98+

two thingsQUANTITY

0.98+

todayDATE

0.97+

zeroQUANTITY

0.97+

OneQUANTITY

0.97+

two additional superconducting cubitsQUANTITY

0.96+

each oneQUANTITY

0.94+

3dQUANTITY

0.94+

one wayQUANTITY

0.94+

NTT research symposiumEVENT

0.93+

HamiltonianOTHER

0.92+

PosanaOTHER

0.91+

over 12 years agoDATE

0.9+

oneQUANTITY

0.89+

Each ofQUANTITY

0.88+

zero entriesQUANTITY

0.88+

GatesPERSON

0.87+

zero feeQUANTITY

0.85+

both cubitsQUANTITY

0.83+

two modeQUANTITY

0.78+

HamiltoniansPERSON

0.77+

FrankOTHER

0.73+

HamiltonianPERSON

0.72+

millisecondsQUANTITY

0.72+

one resonatorQUANTITY

0.71+

CondonPERSON

0.71+

a thousand cubit GatesQUANTITY

0.7+

BQ POTHER

0.69+

single cubitsQUANTITY

0.69+

MarPERSON

0.65+

2020DATE

0.65+

OppenheimerLOCATION

0.59+

GatesOTHER

0.59+

StatesLOCATION

0.57+

ArcticLOCATION

0.56+

HilbertPERSON

0.56+

cavitiesQUANTITY

0.53+

HamiltoniansTITLE

0.53+

HamiltonianTITLE

0.53+

ChevyORGANIZATION

0.51+

EpsilonTITLE

0.48+

TriumeqOTHER

0.48+

N AdamsOTHER

0.46+

RemezOTHER

0.45+

CupidPERSON

0.44+

PulsonixORGANIZATION

0.37+

Miniaturized System for Cell Handling and Analysis


 

>> So nice to meet you. And I'm Tetsuhiko Teshima from German branch of MEI Laboratories. I'm working at the Technische Universitat Munchen to conduct wet experiment like using chemical and biological samples. So it's great honor and pleasure for me to have a chance to share with you some topics about miniaturized biointerfaces that I have been working on over the last six or seven years, I guess. So before starting, please let me introduce myself and my background. So I started to work in this company since this March, but until the last year, I was working in NTT Basic Research Laboratories that is located in Kanagawa, Japan. And I have work on basic nanoscience research. But when going back to the further, I was originally a student studying biology especially infectious microbiology. And then I learned about the miniaturize fluidic system to manipulate single cells and MEMS technologies that is kind of a fabrication process for semiconductor devices. So, this background motivate me to start interdisciplinary work, especially about biomedical engineering at NTT Corporation. So in recent year, wearable electrodes have been developed to continuously monitor the vital data, including the heart rate, ECG, or EMG waveforms for rapid diagnosis and early stage treatment of disease. So conventionally, rigid metals or metal-plated fibers have been widely used as the electrodes but they lack flexibility and biocompatibilities, which results in the noise in obtaining data and the patient allergic reaction during the long time years. So at NTT, we are working on the research and development of the conductive composite materials. So, due to its high flexibility and hydrophilicity and biocompatibilities, so this electrodes can successfully record ECG without any rashes and itches to the skin. So now these wearable electrodes cores toy are commercially available and funds are applied for not only the medical care and rehabilitation for the patients, but also for example, remote monitoring system of the workers, integration with these sportswear and entertainment show. But this product is originated from the basic scientific findings especially on the conductive polymers, PEDOT:PSS and silk fibers. So there was some mainly conducted by two key scientists clinician doctor Tsukada, and chemist doctor, Nakashima. In order to realize this product, they try so many prototypes. And make so many effort to obtain the pharmaceutical probables for medical usage. So through this experience, we are going back to the original material science and research and making non-toxic interfaces with cells and tissues in order to seek new kind of development. So, as a next challenge, I have focused on the electrodes that work inside the bodies. So we have the tissues and organs with electrical signals like heart and brain. So if implanted electrodes can work on these tissues, this help us to increase the variety of the vital data like EEG. And also it can directly treat the targeted tissues as a surgical, too, like CRT pacing. So in this case, these biointerfaces should be populated in very humid environment and in non-toxic manner. They also should be transformed into soft, three dimensional structures, in order to fit the shape of cells and tissues because they have very complicated 3D structures. So I decided to develop the basic electrode component that meets all of these requirements that is biocompatible for example, like 3D film-electrodes. So what I tried at first is to create a non-toxic, very soft and flexible film-electrodes using the materials that are using the heatable electrodes that is silk bundles and PEDOT:PSS. So, firstly, I dissolve the silk bundle to extract a specific protein and process into a palette shape using MEMS technologies, one of my main skill. So by adding the conductive polymers, >> PEDOT: PSS little by little, the palettes will gradually become blue but maintain the high optical transparency. Through this experiment, I discover a very unique materials scientific aspect of silk fibroin. So when PEDOT:PSS got added, the molecular structure and the confirmation of silk protein dramatically change from alpha helix to the beta sheet, and I focused this structure change, leads to the increase in conductivity compared with the PEDOT:PSS pristine films. By using the lithographic fabrication process, the films can be process into very tiny shape, with same deviation as single cell Lego. So this electrode is made of the silk fibroin, the, are very cell friendly protein. So the suspender cells prefer to adhere to their surface. So after attaching the cells on a surface, I can manipulate the cells while maintain the adhesive properties and electrically simulate the cells for the cool, very weak electrical signals from the cells. So in this step we created a non-toxic, transparent, and very flexible films and film-based electrodes. But please note that the, they are 2D and they're not 3D. So in the next step, I try to investigated how to transform these same 2D film to 3D shape. So here, among two polymers I used, so I replace the PEDOT:PSS with different type of polymers, there is parylene, like this. So when the parylene is adhering to the silk fibroin layers so, the gradient of the mechanical stiffness is formed in the synchronous directions as shown here. And this gradient causes the driving force of same film folding, like this. So this is a, this is a movie of the self-folding bilayer films. And you can see these rectangular patterns spontaneously transform into the cylindrical shapes. So just before folding, I suspended the cells on top of the films that is derived from the heart muscles. So the folding films, so here can gently rub the cells inside the tubes and you can incubate them safely more than for two weeks in order to reconstitute the self-beating, fiber-shaped muscle tissues, as shown here. So also this reconstituted tissues can be manipulated like building blocks by picking up and dissolving using glass capillaries. So I believe this techniques has a potential to facilitate high-order self-assembly like artificial neural networks or tissue engineering. So I realized to transform the two different film to 3D shape. So I use this method to transform into 3D electrodes. So in the final step, instead of the silk fibroin, I focus on using extremely thin electrodes materials that is called graphene. So as I explained as extremely thin, so it consist of the only single layer of carbon atom. So since they has just a single atom thickness, it has very high optical transparency and flexibility. So when the graphene was transform to the parylene surface I found this bilayer was tightly bonded due to the strong molecular interactions and the graphene itself straight on the parylene surface and this cell film becomes three dimensional electrodes, like tubeless structures. So as you can see in this movie, like this. So just after releasing them from the service lead, I instantly undergoes a phase transition and collapse. So since, this hexagonal molecular structure of graphene is distorted due to the folding process, so electrical characteristics dramatically change from firstly metallic to the semiconductor like non-linear shape, shown here. Or interestingly, the curvature and direction of the cell folding can be well controls with number of graphene, this and it's crystalline directions. So when a merged layers graphene were transfer, the curvature radius become smaller and smaller. And when the crystal, crystal, sorry, single crystalline graphene was loaded on the surface of parylene, this bilayer was folded in one fixed same direction, especially along the arms here siding. So by simply transferring the single carbon atom layer to the parylene surface, so we achieved the self-assembly of 3D transparent electrodes. In order to demonstrate biocompatibility of this graphene electrodes, we apply for the interface with neurons. So as there was a self-folding of silk fibroin, so we suspended the neurons are encapsulated in the self-folded graphene tubes, like this. So I made it a very tiny holes on the films. So the encapsulated neurons can uptake the nutrition and oxygen through this pore. So I culture the neurons for, without any damage, to the cells, and they exhibit cell-cell contact for tissue-like structures and they elongate their nuclei and axon to the outside through this pore. Therefore, the embedded neurons properly exhibit cell-cell interaction and drive intrinsic morphologies and function, which shows achievement of biocompatibility of the graphene electrodes. So in summary, we have been working on producing tiny 3D electrodes, step-by-step, using only four materials. For example, by mixing conductive polymer, >> PEDOT: PSS with silk fibroin, I made transparent and flexible 2D electrodes. By making a bilayer with silk fibroin with parylene, I demonstrated the self-assembly from 2D film to 3D shape. Finally, by transferring the graphene to paralyene, we could assembly tiny 3D electrodes. So in the future, we will continue to work on making bioelectrodes from the material science and biological viewpoints. However, these two approaches are not sufficient for the research or the bioelectronics. And we especially needed the technology of electrochemical assessment of fabricated electrodes and the method to lead up of obtain vital data and manipulation and analysis of obtain data. Therefore, I belong to both of the TUM and NTT research, in order to achieve the four system. So when I look over the world R&D of the bioelectronics, especially implantable electronics are very active, regardless of the university and industry. So firstly, John Rogers' group in University of Illinois, in United States, started to advocate about the implantable, flexible bioelectronics, more than 10 years ago. So now the research on, about it, is rapidly growing all over the world, not only US, but the Asia and Europe. So, the industrial community also tend to participate in this field. So I really hope to contributed to the scientific achievement and the creation of industry from the German basis, by making the most of my experience and cooperation with Japan and American side. So finally, I like to introduce my colleagues in TUM. So they are loved members and he, he is supervisor, Professor Bernhard Wolfrum, especially of the electrochemistry and electrochemical engineering process for biomedical application. So I'm so happy to work with this wonderful team and also appreciated the daily support of the members in NTT research in United States. Finally, let me just conclude by acknowledging my supervisor, mentors, Professor Wolfrum, Director Tomoike, and Dr. Alexander. And also the member from NTT who always support me, especially Mr. Kikuchi, Dr. Nakashima, Tsukada fellow, Director Goto, Dr. Yamamoto, and Director Sogawa. Finally, let me thanks Professor Offenhausser from Julich, for his kind assistance and introduction to this wonderful collaboration schemes. So, that's all. And I hope this presentation was useful to you. Thank you very much.

Published Date : Sep 21 2020

SUMMARY :

So by adding the conductive polymers, So in the next step, and the method to lead

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
KikuchiPERSON

0.99+

NakashimaPERSON

0.99+

Tetsuhiko TeshimaPERSON

0.99+

TomoikePERSON

0.99+

TsukadaPERSON

0.99+

YamamotoPERSON

0.99+

AlexanderPERSON

0.99+

GotoPERSON

0.99+

SogawaPERSON

0.99+

NTTORGANIZATION

0.99+

United StatesLOCATION

0.99+

NTT Basic Research LaboratoriesORGANIZATION

0.99+

MEI LaboratoriesORGANIZATION

0.99+

TUMORGANIZATION

0.99+

last yearDATE

0.99+

Bernhard WolfrumPERSON

0.99+

two key scientistsQUANTITY

0.99+

WolfrumPERSON

0.99+

Kanagawa, JapanLOCATION

0.99+

EuropeLOCATION

0.99+

two polymersQUANTITY

0.99+

USLOCATION

0.99+

AsiaLOCATION

0.99+

bothQUANTITY

0.99+

John Rogers'PERSON

0.99+

University of IllinoisORGANIZATION

0.98+

NTT CorporationORGANIZATION

0.97+

OffenhausserPERSON

0.97+

firstlyQUANTITY

0.96+

two approachesQUANTITY

0.96+

LegoORGANIZATION

0.95+

firstQUANTITY

0.95+

Technische Universitat MunchenORGANIZATION

0.94+

single cellQUANTITY

0.94+

single atomQUANTITY

0.94+

more than 10 years agoDATE

0.93+

JulichPERSON

0.92+

two different filmQUANTITY

0.9+

single layer of carbon atomQUANTITY

0.9+

single carbon atomQUANTITY

0.88+

two weeksQUANTITY

0.87+

paryleneOTHER

0.87+

four materialsQUANTITY

0.85+

2DQUANTITY

0.84+

oneQUANTITY

0.84+

single cellsQUANTITY

0.81+

four systemQUANTITY

0.8+

3DQUANTITY

0.77+

seven yearsQUANTITY

0.77+

ibroinOTHER

0.77+

singleQUANTITY

0.73+

JapanLOCATION

0.72+

last sixDATE

0.64+

ProfessorPERSON

0.59+

three dimensionalQUANTITY

0.58+

this MarchDATE

0.57+

GermanOTHER

0.56+

yearDATE

0.51+

ECGOTHER

0.5+

AmericanLOCATION

0.48+

Neural Audio Captioning and Its Application to Stethoscopic Sounds


 

>> Hello, I'm Kunio Kashino from Biomedical Informatics Research Center of NTT Basic Research Laboratories. I'd like to talk about neural audio captioning and its application to stethoscopic sounds. First, I'd like to think about what captioning is in comparison with classification. When there is a picture of a cat, you will recognize it as a cat. This is a classification or object recognition. Captioning on the other hand is to describe what's going on in a more complex scene. This is an example of a visual case, but the same can be thought of for sound. When you hear a car on the street, you can recognize it as a car. You can also explain the sound when someones hitting a toy tambourine. Of these, the generation of explanatory notes on sounds or audio captioning is a new field of research that has just emerged. (soft music) This is an experimental system that we proposed last year. It listened to sound for two seconds and provides an explanation for the sound of that section. (soft music) Moving the slider to the left produces a short, concise description. Moving it to the right produces a longer, more detailed description. (soft music) The descriptions are not always perfect, but you can see how it works. Here are some early works in this field of study. In 2017, Drossos conducted a study that gave sound a string of words. But there are still a lot of overlap with the classification task at that time. At around the same time, Ikala who was my student at the university of Tokyo proposed a system that could express sounds in onomatopoeic terms as a sequence of phonemes. Recently more works have been reported including those describing more complex scenes in normal sentences and using sentences for sound retrieval. Let's go over the differences between classification and the captioning once again. Classification is the process of classifying or quantizing features in a fixed number of classes. Captioning on the other hand means converting the features. For example, the time series of sound features is translated into the times series of words. Classification requires that classes be determine in advance, but captioning does not. In classification relationships between classes are not usually considered but in captioning relationships between elements are important not just what is there. In the medical context classification corresponds to diagnosis while in captioning we've addressed the explanation and inference rather than diagnosis. Of course, diagnosis is an important act in medical care and neural classification neural captioning is necessarily better than the other. Captioning would be useful to express the comparisons, degree, time course and changes and the relationship between cause and effect. For example, it would be difficult to prepare a class for the situation represented by a sentence of over the past few days pneumonia has gradually spread and worsened. Therefore both of them should be utilized according to the purpose. Now let's consider the challenges of captioning. If you look at this picture everyone will say, it's a picture of a cat. Yes, it is. No one called this a grey and white animal with two round eyes and triangular ears. Similarly, when a characteristic noise is heard from the lungs as the person breathes, you may just say wrong car hire present. And wrong described the noise in detail. That is it's a good idea to use the label, if it's appropriate. As long as the person you are talking to can understand it. Another challenge with captioning is that the exact same description may or may not be appropriate depending on the situation. When you were walking down on each section and a car pops up, it's important to say it's a car and it's inappropriate to discuss the engine sound quality. But when you bring a car to a repair shop and have it checked you have to describe the engine sound in detail. Just saying that the engines running is obviously not enough. It is important to note that appropriate expressions vary and only one best answer cannot be determined. With these issues in mind, we configured a neuro audio captioning model. We call this system CSCG or Conditional Sequence-to-sequence Caption Generator. The system extracts a time series of acoustic features from biological sounds such as hard sounds converts them into a series of words and outputs them with class labels. The green parts are neuro networks. They were so trained that the system outputs both captions and labels simultaneously. The behavior of the sentence decoder is controlled by conditioning it with the auxiliarity input, in order to cope with the fact that the appropriate captions can vary. In the current experimentation we employ your parameter called Specificity. It is the amount of information contained in the words, in the entire caption. In other words the more number of words and the more infrequent or more specific words are used, the higher the variable specificity. And now our experiments the entire network was trained using a set of heart sounds. The sound samples were extracted from sound sources that collected 55 difficult cases. For each case, the signal was about one minute in length. So we extracted sound samples by windowing the signal. In one case four cycles worth of signal were work cut at the timing synchronized with the heartbeats. In another case, signals of six seconds in length were cut out at regular time intervals of three seconds. Class levels and seven kinds of explanations sentences were given manually for each case. This table shows the classification accuracy. We organized categories as general overview description of sound and presence or absence of 12 difficult heart diseases. We then prepared two to six classes for each category. As a result, we found that it is possible to classify with a fairly high accuracy of 94% or more in the case of beats synchronous windowing and 88% or more in the case of regular windowing. This graph shows the effect of the specificity control. The horizontal axis represent the specified specificity of level of detail. In the vertical axis we present the amount of information contained in the rear outfit captions. As you can see, the data is distributed along a straight line with a slope of one indicating that the specificity control is working correctly. Let's take a look at generated captions. This table shows the examples with varying specificity input for three types of sound sources, normal, large split of second sounds and coronary artery disease. If the specified specificity is small then the generator sentence is short. If the specificity value is greater you can see that detailed and long sentences are being generated. In this table, all captions are confirmed to be appropriate for the sound by humor observations. However the system does not always produce the correct output for now. Sometimes it may produce a wrong caption or a statement containing a linguistic error but generally speaking we consider the result promising. In this talk, I first discussed the problem of audio captioning in comparison with classification. It is not just a sound recognition and therefore a new topic in the research field. Then I proposed an automatic audio captioning system based on the conditional sequence-to-sequence model and tested it with heart sounds. The system features a multitasking configuration for classification then the captioning. And allows us to adjust the level of detail in the description according to the purpose. The evaluation results are promising. In the future, we intend to enrich the learning data and improve the system configuration to make it a practical system in the near future. Thank you very much.

Published Date : Sep 21 2020

SUMMARY :

is that the exact same description may

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Kunio KashinoPERSON

0.99+

2017DATE

0.99+

twoQUANTITY

0.99+

NTT Basic Research LaboratoriesORGANIZATION

0.99+

94%QUANTITY

0.99+

three secondsQUANTITY

0.99+

six secondsQUANTITY

0.99+

two secondsQUANTITY

0.99+

88%QUANTITY

0.99+

last yearDATE

0.99+

55 difficult casesQUANTITY

0.99+

six classesQUANTITY

0.99+

one caseQUANTITY

0.99+

IkalaPERSON

0.99+

each caseQUANTITY

0.99+

FirstQUANTITY

0.99+

each categoryQUANTITY

0.99+

three typesQUANTITY

0.99+

Biomedical Informatics Research CenterORGANIZATION

0.99+

seven kindsQUANTITY

0.98+

bothQUANTITY

0.98+

firstQUANTITY

0.98+

DrossosPERSON

0.97+

two round eyesQUANTITY

0.96+

12 difficult heart diseasesQUANTITY

0.95+

second soundsQUANTITY

0.95+

each sectionQUANTITY

0.94+

about one minuteQUANTITY

0.93+

four cyclesQUANTITY

0.89+

TokyoORGANIZATION

0.81+

both captionsQUANTITY

0.73+

universityORGANIZATION

0.71+

one best answerQUANTITY

0.7+

earsQUANTITY

0.59+

oneQUANTITY

0.56+

A Cardiovascular Bio Digital Twin


 

>> Hello, welcome to the final day of the NTT Research Summit Upgrade 2020. My name is Joe Alexander and I belong to the Medical and Health Informatics lab, so-called MEI lab, and I lead the development of the bio digital twin. I'd like to give you a high level overview of what we mean by bio digital twin, what some of our immediate research targets are, and a description of our overall approach. You will note that my title is not simply bio digital twin, but more specifically a cardiovascular bio digital twin and you'll soon understand why. What do we mean by digital twin? For our project, we're taking the definition on approach used in commercial aviation, mostly for predictive maintenance of jet engines. A digital twin is an up-to-date virtual representation, an electronic replica if you will. Now, if anything which gives you real-time insight into the status of the real-world asset to enable better management and to inform decision-making. It aims to merge the real and the virtual world. It enables one to design, simulate, and verify products digitally, including mechanics and multi-physics. It allows integration of complex systems. It allows for predictive maintenance through direct real-time monitoring of the health and structure of the plane parts, mitigating danger. It enables monitoring of all machines anywhere at all times. This allows feeding back insights to continuously optimize the digital twin of the product, which in turn leads to continuous improvement of the product in the real world. A robust platform is needed for digital twins to live, learn and run. Because we aim to apply these concepts to biological systems for predictive maintenance of health, we use the term bio digital twin. We're aiming for a precision medicine and predictive health maintenance. And while ultimately we intend to represent multiple organ systems and the diseases affecting them, we will start with the cardiovascular system. When we revisit concepts from the last slide, there's the one-to-one mapping as you can see on this slide. A cardiovascular bio digital twin is an up-to-date virtual representation as well, but of a cardiovascular system, which gives you real-time insight into the status of the cardiovascular system of a real world patient to enable better care management and to inform clinical decision-making. It does so by merging the real and virtual world. It enables one to design, simulate, and verify drug and device treatments digitally, including cardiovascular mechanics and multi-physics. It allows integration of complex organ systems. It allows for predictive maintenance of health care through direct real-time monitoring of the health and functional integration, or excuse me, functional integrity of body parts, mitigating danger. It enables monitoring of all patients anywhere at all times. This allows feedback to continuously optimize the digital twins of subjects, which in turn leads to continuous improvements to the health of subjects in the real world. Also a robust platform is needed for digital twins to live, learn, and run. One platform under evaluation for us is called embodied bio-sciences. And it is a cloud-based platform leveraging AWS distributed computing database and cuing solutions. There are many cardiovascular diseases that might be targeted by cardiovascular bio digital twin. We have chosen to focus on the two most common forms of heart failure, and those are ischemic heart failure and hypertensive heart failure. Ischemic heart failure is usually due to coronary artery disease and hypertensive heart failure usually is secondary to high blood pressure. By targeting heart failure, number one, it forces us to automatically incorporate biological mechanisms, common to many other cardiovascular diseases. And two, heart failure is an area of significant unmet medical need, especially given the world's aging population. The prevalence of heart failure is estimated to be one to one and a half. I'm sorry, one to 5% in the general population. Heart failure is a common cause of hospitalization. The risk of heart failure increases with age. About a third to a half of the total number of patients diagnosed with heart failure, have a normal ejection fraction. Ischemic heart failure occurs in the setting of an insult to the coronary arteries causing atherosclerosis. The key physiologic mechanisms of ischemic heart failure are increased myocardial oxygen demand in the face of a limited myocardial oxygen supply. And hypertensive heart failure is usually characterized by complex myocardial alterations resulting from the response to stress imposed by the left ventricle by a chronic increase in blood pressure. In order to achieve precision medicine or optimized and individualized therapies for heart failure, we will develop three computational platforms over a five-year period. A neuro-hormonal regulation platform, a mechanical adaptation platform and an energetics platform. The neuro-hormonal platform is critical for characterizing a fundamental feature of chronic heart failure, which is neuro-humoral activation and alterations in regulatory control by the autonomic nervous system. We will also develop a mechanical adaptation and remodeling platform. Progressive changes in the mechanical structure of the heart, such as thickening or thinning a bit muscular walls in response to changes in workloads are directly related to future deterioration in cardiac performance and heart failure. And we'll develop an energetics platform, which includes the model of the coronary circulation, that is the blood vessels that supply the heart organ itself. And will thus provide a mechanism for characterizing the imbalances between the oxygen and metabolic requirements of cardiac tissues and their lack of availability due to neuro-hormonal activation and heart failure progression. We consider it the landscape of other organizations pursuing innovative solutions that may be considered as cardiovascular bio digital twins, according to a similar definition or conceptualization as ours. Some are companies like the UT Heart, Siemens Healthineers, Computational Life. Some are academic institutions like the Johns Hopkins Institute for Computational Medicine, the Washington University Cardiac Bio Electricity and Arrhythmia Center. And then some are consortia such as echos, which stands for enhanced cardiac care through extensive sensing. And that's a consortium of academic and industrial partners. These other organizations have different aims of course, but most are focused on cardiac electrophysiology and disorders of cardiac rhythm. Most use both physiologically based and data driven methods, such as artificial intelligence and deep learning. Most are focused on the heart itself without robust representations of the vascular load, and none implement neuro hormonal regulation or mechanical adaptation and remodeling, nor aim for the ultimate realization of close loop therapeutics. By autonomous closed loop therapeutics, I mean, using the cardiovascular bio digital twin, not only to predict cardiovascular events and determine optimal therapeutic interventions for maintenance of health or for disease management, but also to actually deliver those therapeutic interventions. This means not only the need for smart sensors, but also for smart actuators, smart robotics, and various nanotechnology devices. Going back to my earlier comparisons to commercial aviation, autonomous closed loop therapeutics means not only maintenance of the plane and its parts, but also the actual flying of the plane in autopilot. In the beginning, we'll include the physician pilots in the loop, but the ultimate goal is an autonomous bio digital twin system for the cardiovascular system. The goal of realizing autonomous closed loop therapeutics in humans is obviously a more longterm goal. We're expecting to demonstrate that first in animal models. And our initial thinking was that this demonstration would be possible by the year 2030, that is 10 years. As of this month, we were planning ways of reaching this target even sooner. Finally, I would also like to add that by setting our aims at such a high ambition target, we drive the quality and accuracy of old milestones along the way. Thank you. This concludes my presentation. I appreciate your interest and attention. Please enjoy the remaining sessions, thank you.

Published Date : Sep 21 2020

SUMMARY :

of the product in the real world.

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
UT HeartORGANIZATION

0.99+

Johns Hopkins Institute for Computational MedicineORGANIZATION

0.99+

Joe AlexanderPERSON

0.99+

oneQUANTITY

0.99+

Washington University Cardiac Bio ElectricityORGANIZATION

0.99+

Siemens HealthineersORGANIZATION

0.99+

Arrhythmia CenterORGANIZATION

0.99+

AWSORGANIZATION

0.99+

10 yearsQUANTITY

0.99+

2030DATE

0.99+

Computational LifeORGANIZATION

0.99+

One platformQUANTITY

0.98+

twoQUANTITY

0.97+

bothQUANTITY

0.97+

one and a halfQUANTITY

0.97+

5%QUANTITY

0.95+

NTT Research Summit Upgrade 2020EVENT

0.95+

threeQUANTITY

0.94+

firstQUANTITY

0.93+

this monthDATE

0.92+

MEIORGANIZATION

0.9+

About a thirdQUANTITY

0.78+

atherosclerosisOTHER

0.78+

a halfQUANTITY

0.75+

two most common formsQUANTITY

0.73+

echosORGANIZATION

0.72+

platformsQUANTITY

0.71+

twinsQUANTITY

0.71+

a five-year periodQUANTITY

0.7+

twinOTHER

0.68+

twinCOMMERCIAL_ITEM

0.66+

bioOTHER

0.61+

TwinCOMMERCIAL_ITEM

0.59+

number oneQUANTITY

0.59+

twinQUANTITY

0.56+

and HealthORGANIZATION

0.49+

bio digital twinOTHER

0.48+

digital twinCOMMERCIAL_ITEM

0.46+

Incompressible Encodings


 

>> Hello, my name is Daniel Wichs, I'm a senior scientist at NTT research and a professor at Northeastern University. Today I want to tell you about incompressible encodings. This is a recent work from Crypto 2020 and it's a joint work with Tal Moran. So let me start with a question. How much space would it take to store all of Wikipedia? So it turns out that you can download Wikipedia for offline use and some reasonable version of it is about 50 gigabytes in size. So as you'd expect, it's a lot of data, it's quite large. But there's another way to store Wikipedia which is just to store the link www.wikipedia.org that only takes 17 bytes. And for all intents and purposes as long as you have a connection to the internet storing this link is as good as storing the Wikipedia data. You can access a Wikipedia with this link whenever you want. And the point I want to make is that when it comes to public data like Wikipedia, even though the data is huge, it's trivial to compress it down because it is public just by storing a small link to it. And the question for this talk is, can we come up with an incompressible representation of public data like Wikipedia? In other words can we take Wikipedia and represent it in some way such that this representation requires the full 50 gigabytes of storage store, even for someone who has the link to the underlying Wikipedia data and can get the underlying data for free. So let me actually tell you what this means in more detail. So this is the notion of incompressible encodings that we'll focus on in this work. So incompressible encoding consists of an encoding algorithm and a decoding algorithm, these are public algorithms. There's no secret key. Anybody can run these algorithms. The encoding algorithm takes some data m, let's say the Wikipedia data and encodes it in some probabilistic randomized way to derive a codeword c. And the codeword c, you can think of it as just an alternate representation of the Wikipedia data. Anybody can come and decode the codeword to recover the underlying data m. And the correctness property we want here is that no matter what data you start with, if you encode the data m and then decode it, you get back the original data m. This should hold with probably one over the randomness of the encoding procedure. Now for security, we want to consider an adversary that knows the underlying data m, let's say has a link to Wikipedia and can access the Wikipedia data for free does not pay for storing it. The goal of the adversary is to compress this codeword that we created this new randomized representation of the Wikipedia data. So the adversary consists of two procedures a compression procedure and a decompression procedure. The compression procedure takes its input the codeword c and output some smaller compressed value w and the decompression procedure takes w and its goal is to recover the codeword c. And a security property says that no efficient adversary should be able to succeed in this game with better than negligible property. So there are two parameters of interest in this problem. One is the codeword size, which we'll denote by alpha, and ideally we want the codeword size alpha to be as close as possible to the original data size. In other words we don't want the encoding to add too much overhead to the data. The second parameter is the incompressibility parameter beta and that tells us how much space, how much storage and adversary needs to use in order to store the codeword. And ideally, we want this beta to be as close as possible to the codeword size alpha, which should also be as close as possible to the original data size. So I want to mention that there is a trivial construction of incompressible encodings that achieves very poor parameters. So the trivial construction is just take the data m and add some randomness, concatenate some randomness to it and store the original data m plus the concatenated randomness as the codeword. And now even an adversary that knows the underlying data m cannot compress the randomness. So the incompressibility, so we ensure that this construction is incompressible with incompressibility parameter beta that just corresponds to the size of this randomness we added. So essentially the adversary cannot compress the red part of the codeword. So this gets us a scheme where alpha the size of the codeword, is the original data size m plus the incompressible parameter beta. And it turns out that you cannot do better than this information theoretically. So this is not what we want for this we want to focus on what I will call good incompressible encodings. So here, the codeword size should be as close as possible to the data size, should be just one plus little o one of the data size. And the incompressibility should be as essential as large as the entire codeword the adversary cannot compress the codeword almost at all, the incompressible parameter beta is one minus little o one of the data size or the codeword size. And in essence, what this means is that we're somehow want to take the randomness of the encoding procedure and spread it around in some clever way throughout the codeword in such a way that's impossible for the adversary to separate out the randomness and the data, and only store the randomness and rely on the fact that it can get the data for free. We want to make sure it's impossible that adversary accesses essentially this entire code word which contains both the randomness and data and some carefully intertwined way and cannot compress it down using the fact that it knows the data parts. So this notion of incompressible encodings was defined actually in a prior work of Damgard-Ganesh and Orlandi from crypto 2019. They defined a variant of this notion, they had a different name for it. As a tool or a building block for a more complex cryptographic primitive that they called Proofs of Replicated Storage. And I'm not going to talk about what these are. But in this context of constructing these Proofs of Replicated Storage, they also constructed incompressible encodings albeit with some major caveats. So in particular, their construction relied on the random Oracle models, the heuristic construction and it was not known whether you could do this in the standard model, the encoding and decoding time of the construction was quadratic in the data size. And in particular, here we want to apply this, we want to use these types of incompressible encodings on fairly large data like Wikipedia data, 50 gigabytes in size. So quadratic runtime on such huge data is really impractical. And lastly the proof of security for their construction was flawed or someone incompleted, didn't consider general adversaries. And the slope was actually also noticed by concurrent work of Garg-Lu and Waters. And they managed to give a fixed proof for this construction but this required actually quite a lot of effort. It was a highly non-trivial and subtle proof to proof the original construction of Damgard-Ganesh and Orlandi secure. So in our work, we give a new construction of these types of incompressible encodings, our construction already achieved some form of security in the Common Reference String Model come Random String Model without the use of Random Oracles. We have a linear encoding time, linear in the data size. So we get rid of the quadratic and we have a fairly simple proof of security. In fact, I'm hoping to show you a slightly simplified form of it and the stock. We also give some lower bounds and negative results showing that our construction is optimal in some aspects and lastly we give a new application of this notion of incompressible encodings to something called big-key cryptography. And so I want to tell you about this application, hopefully it'll give you some intuition about why incompressible encodings are interesting and useful, and also some intuition about what their real goal is or what it is that they're trying to achieve. So, the application of big-key cryptography is concerned with the problem of system compromise. So, a computer system can become compromised either because the user downloads a malware or remote attacker manages to hack into it. And when this happens, the remote attacker gains control over the system and any cryptographic keys that are stored on the system can easily be exfiltrated or just downloaded out of the system by the attacker and therefore, any security that these cryptographic keys were meant to provide is going to be completely lost. And the idea of big-key cryptography is to mitigate against such attacks by making the secret keys intentionally huge on the order of many gigabytes to even terabytes. And the idea is that by having a very large secret key it would make it harder to exfiltrate such a secret key. Either because the adversary's bandwidth to the compromised system is just not large enough to exfiltrate such a large key or because it might not be cost-effective to have to download so much data of compromised system and store so much data to be able to use the key in the future, especially if the attacker wants to do this on some mass scale or because the system might have some other mechanisms let's say firewall that would detect such large amounts of leakage out of the compromised system and block it in some way. So there's been a lot of work on this idea building big-key crypto systems. So crypto systems where the secret key can be set arbitrarily huge and these crypto systems should testify two goals. So one is security, security should hold even if a large amount of data about the secret key is out, as long as it's not the entire secret key. So when you have an attacker download let's say 90% of the data of the secret key, the security of the system should be preserved. And the second property is that even though the secret key of the system can be huge, many gigabytes or terabytes, we still want the crypto system to remain efficient even though the secret is huge. And particularly this means that the crypto system can even read the entire secret key during each cryptographic operation because that would already be too inefficient. So it can only read some small number of bits of the secret key during each operation, then it performs. And so there's been a lot of work constructing these types of crypto systems but one common problem for all these works is that they require the user to waste a lot of their storage the storage on their computer in storing this huge secret key which is useless for any other purpose, other than providing security. And users might not want to do this. So that's the problem that we address here. And the new idea in our work is let's make the secret key useful instead of just having a secret key with some useless, random data that the cryptographic scheme picks, let's have a secret key that stores let's say the Wikipedia data at which a user might want to store in their system anyway or the user's movie collection or music collection et cetera and the data that the user would want to store on their system. Anyway, we want to convert it. We want to use that as the secret key. Now we think about this for a few seconds. Well, is it a good idea to use Wikipedia as a secret key? No, that sounds like a terrible idea. Wikipedia is not secret, it's public, it's online, Anyone can access it whenever they want. So it's not what we're suggesting. We're suggesting to use an incompressible encoding of Wikipedia as a secret key. Now, even though Wikipedia is public the incompressible encoding is randomized. And therefore the accuracy does not know the value of this incompressible encoding. Moreover, because it's incompressible in order for the adversary to steal, to exfiltrate the entire secret key, it would have to download a very large amount of data out of the compromised system. So there's some hope that this could provide security and we show how to build public encryption schemes and the setting that make use of a secret key which is an incompressible coding of some useful data like Wikipedia. So the secret key is an incompressible encoding of useful data and security ensures that the adversary will need to exfiltrate almost entire key to break the security of this critical system. So in the last few minutes, let me give you a very brief overview of our construction of incompressible encodings. And for this part, we're going to pretend we have something a real beautiful cryptographic object called Lossy Trapdoor Permutations. It turns out we don't quite have an object that's this beautiful and in the full construction, we relax this notion somewhat in order to be able to get our full construction. So Lossy Trapdoor Permutation is a function f we just key by some public key pk and it maps end bits to end bits. And we can sample the public key in one of two indistinguishable modes. In injective mode, this function of fPK is a permutation, and there's in fact, a trapdoor that allows us to invert it efficiently. And in the Lossy mode, if we sample the public in Lossy mode, then if we take some value, random value x and give you fpk of x, then this loses a lot of information about x. And in particular, the image size of the function is very small, much smaller than two to the n and so fpk of x does not contain all the information about x. Okay, so using this type of Lossy Trapdoor Permutation, here's the encoding of a message m using long random CRS come random string. So the encoding just consists of sampling the public key of this Lossy Trapdoor Permutation in injected mode, along with the trapdoor. And the encoding is just going to take the message m, x over it with a common reference string, come random string and invert the trapdoor permutation on this value. And then Coding will just be the public key and the inverse x. So this is something anybody can decode by just taking fpk of x, x over it with the CRS. And that will recover the original message. Now, to add the security, we're going to in the proof, we're going to switch to choosing the value x uniformly at random. So the x component of the codeword is going to be chosen uniformly random and we're going to set the CRS to be fpk of x, x over the message. And if you look at it for a second this distribution is exactly equivalent. It's just a different way of sampling the exact same distribution. And in particular, the relation between the CRS and X is preserved. Now in the second step, we're going to switch the public key to Lossy mode. And now when we do this, then the Codeword part, sorry then the CRS fpk of x, x over m only leaks some small amount of information about the random value x. In other words, even if that resists these, the CRS then the value x and the codeword has a lot of entropy. And because it has a lot of entropy it's incompressible. So what we did here is that we actually start to show that the code word and the CRS are indistinguishable from a different way of sampling them where we placed information about the message and the CRS and the codeword actually is truly random, has a lot of real entropy. And therefore even given the CRS the Codeword is incompressible that's the main idea behind the proof. I just want to make two remarks, our full constructions rely on a relaxed notion of Lossy Trapdoor Permutations which we're able to construct from either the decisional residuoisity or the learning with errors assumption. So in particular, we don't actually know how to construct trapdoor permutations from LWE from any postquantum assumption but the relaxed notion that we need for our actual construction, we can achieve from post quantum assumptions that get post quantum security. I want to mention two caveats of the construction. So one is that in order to make this work, the CRS needs to be long essentially as long as the message size. And also this construction achieves a weak form of selective security where the adversary decides to choose the message before seeing the CRS. And we show that both of these caveats are inherent. We show this by black-box separation and one can overcome them only in the random oracle model. Unless I want to just end with an interesting open question. I think one of the most interesting open questions in this area all of the constructions of incompressible encodings from our work and prior work required the use of some public key crypto assumptions some sort of trapdoor permutations or trapdoor functions. And one of the interesting open question is can you construct and incompressible encodings without relying on public key crypto, using one way functions or just the random oracle model. We conjecture this is not possible, but we don't know. So I want to end with that open questions and thank you very much for listening.

Published Date : Sep 21 2020

SUMMARY :

in order for the adversary to steal,

SENTIMENT ANALYSIS :

ENTITIES

EntityCategoryConfidence
Daniel WichsPERSON

0.99+

second stepQUANTITY

0.99+

NTTORGANIZATION

0.99+

two caveatsQUANTITY

0.99+

17 bytesQUANTITY

0.99+

50 gigabytesQUANTITY

0.99+

two remarksQUANTITY

0.99+

bothQUANTITY

0.99+

two proceduresQUANTITY

0.99+

WikipediaORGANIZATION

0.99+

www.wikipedia.orgOTHER

0.99+

two goalsQUANTITY

0.99+

second parameterQUANTITY

0.99+

second propertyQUANTITY

0.99+

each operationQUANTITY

0.99+

two parametersQUANTITY

0.98+

oneQUANTITY

0.98+

OrlandiPERSON

0.98+

Tal MoranPERSON

0.97+

TodayDATE

0.97+

one common problemQUANTITY

0.97+

OneQUANTITY

0.97+

Garg-LuORGANIZATION

0.96+

Damgard-GaneshPERSON

0.96+

Northeastern UniversityORGANIZATION

0.96+

twoQUANTITY

0.95+

two indistinguishable modesQUANTITY

0.94+

Crypto 2020ORGANIZATION

0.94+

about 50 gigabytesQUANTITY

0.94+

each cryptographicQUANTITY

0.94+

CRSORGANIZATION

0.94+

WikipediaTITLE

0.93+

90% of the dataQUANTITY

0.89+

LWEORGANIZATION

0.89+

OracleORGANIZATION

0.84+

terabytesQUANTITY

0.83+

WatersORGANIZATION

0.79+

one wayQUANTITY

0.77+

secondsQUANTITY

0.74+

Lossy TrapdoorOTHER

0.71+

Proofs of Replicated StorageOTHER

0.64+

2019DATE

0.62+

secondQUANTITY

0.56+

muchQUANTITY

0.55+

lot ofQUANTITY

0.54+

caveatsQUANTITY

0.51+

gigabytesQUANTITY

0.48+

cryptoTITLE

0.33+