>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hey everyone and welcome back to Barcelona, Spain, it's theCUBE. We are live at MWC 23. This is day two of our coverage, we're giving you four days of coverage, but you already know that because you were here yesterday. Lisa Martin with Dave Nicholson. Dave this show is massive. I was walking in this morning and almost getting claustrophobic with the 80,000 people that are joining us. There is, seems to be at MWC 23 more interest in enterprise-class technology than we've ever seen before. What are some of the things that you've observed with that regard? >> Well I've observed a lot of people racing to the highest level messaging about how wonderful it is to have the kiss of a breeze on your cheek, and to feel the flowing wheat. (laughing) I want to hear about the actual things that make this stuff possible. >> Right. >> So I think we have a couple of guests here who can help us start to go down that path of actually understanding the real cool stuff that's behind the scenes. >> And absolutely we got some cool stuff. We've got two guests from Dell. Dave Lincoln is here, the VP of Networking and Emerging the Server Solutions, and Deania Davidson, Director Edge Server Product Planning and Management at Dell. So great to have you. >> Thank you. >> Two Daves, and a Davidson. >> (indistinct) >> Just me who stands alone here. (laughing) So guys talk about, Dave, we'll start with you the newest generation of PowerEdge servers. What's new? Why is it so exciting? What challenges for telecom operators is it solving? >> Yeah, well so this is actually Dell's largest server launch ever. It's the most expansive, which is notable because of, we have a pretty significant portfolio. We're very proud of our core mainstream portfolio. But really since the Supercompute in Dallas in November, that we started a rolling thunder of launches. MWC being part of that leading up to DTW here in May, where we're actually going to be announcing big investments in those parts of the market that are the growth segments of server. Specifically AIML, where we in, to address that. We're investing heavy in our XE series which we, as I said, we announced at Supercompute in November. And then we have to address the CSP segment, a big investment around the HS series which we just announced, and then lastly, the edge telecom segment which we're, we had the biggest investment, biggest announce in portfolio launch with XR series. >> Deania, lets dig into that. >> Yeah. >> Where we see the growth coming from you mentioned telecom CSPs with the edge. What are some of the growth opportunities there that organizations need Dell's help with to manage, so that they can deliver what they're demanding and user is wanting? >> The biggest areas being obviously, in addition the telecom has been the biggest one, but the other areas too we're seeing is in retail and manufacturing as well. And, so internally, I mean we're going to be focused on hardware, but we also have a solutions team who are working with us to build the solutions focused on retail, and edge and telecom as well on top of the servers that we'll talk about shortly. >> What are some of the biggest challenges that retailers and manufacturers are facing? And during the pandemic retailers, those that were successful pivoted very quickly to curbside delivery. >> Deania: Yeah. >> Those that didn't survive weren't able to do that digitally. >> Deania: Yeah. >> But we're seeing such demand. >> Yeah. >> At the retail edge. On the consumer side we want to get whatever we want right now. >> Yes. >> It has to be delivered, it has to be personalized. Talk a little bit more about some of the challenges there, within those two verticals and how Dell is helping to address those with the new server technologies. >> For retail, I think there's couple of things, the one is like in the fast food area. So obviously through COVID a lot of people got familiar and comfortable with driving through. >> Lisa: Yeah. >> And so there's probably a certain fast food restaurant everyone's pretty familiar with, they're pretty efficient in that, and so there are other customers who are trying to replicate that, and so how do we help them do that all, from a technology perspective. From a retail, it's one of the pickup and the online experience, but when you go into a store, I don't know about you but I go to Target, and I'm looking for something and I have kids who are kind of distracting you. Its like where is this one thing, and so I pull up the Target App for example, and it tells me where its at, right. And then obviously, stores want to make more money, so like hey, since you picked this thing, there are these things around you. So things like that is what we're having conversations with customers about. >> It's so interesting because the demand is there. >> Yeah, it is. >> And its not going to go anywhere. >> No. >> And it's certainly not going to be dialed down. We're not going to want less stuff, less often. >> Yeah (giggles) >> And as typical consumers, we don't necessarily make the association between what we're seeing in the palm of our hand on a mobile device. >> Deania: Right. >> And the infrastructure that's actually supporting all of it. >> Deania: Right. >> People hear the term Cloud and they think cloud-phone mystery. >> Yeah, magic just happens. >> Yeah. >> Yeah. >> But in fact, in order to support the things that we want to be able to do. >> Yeah. >> On the move, you have to optimize the server hardware. >> Deania: Yes. >> In certain ways. What does that mean exactly? When you say that its optimized, what are the sorts of decisions that you make when you're building? I think of this in the terms of Lego bricks. >> Yes, yeah >> Put together. What are some of the decisions that you make? >> So there were few key things that we really had to think about in terms of what was different from the Data center, which obviously supports the cloud environment, but it was all about how do we get closer to the customer right? How do we get things really fast and how do we compute that information really quickly. So for us, it's things like size. All right, so our server is going to weigh one of them is the size of a shoe box and (giggles), we have a picture with Dave. >> Dave: It's true. >> Took off his shoe. >> Its actually, its actually as big as a shoe. (crowd chuckles) >> It is. >> It is. >> To be fair, its a pretty big shoe. >> True, true. >> It is, but its small in relative to the old big servers that you see. >> I see what you're doing, you find a guy with a size 12, (crowd giggles) >> Yeah. >> Its the size of your shoe. >> Yeah. >> Okay. >> Its literally the size of a shoe, and that's our smallest server and its the smallest one in the portfolio, its the XR 4000, and so we've actually crammed a lot of technology in there going with the Intel ZRT processors for example to get into that compute power. The XR 8000 which you'll be hearing a lot more about shortly with our next guest is one I think from a telco perspective is our flagship product, and its size was a big thing there too. Ruggedization so its like (indistinct) certification, so it can actually operate continuously in negative 5 to 55 C, which for customers, or they need that range of temperature operation, flexibility was a big thing too. In meaning that, there are some customers who wanted to have one system in different areas of deployment. So can I take this one system and configure it one way, take that same system, configure another way and have it here. So flexibility was really key for us as well, and so we'll actually be seeing that in the next segment coming. >> I think one of, some of the common things you're hearing from this is our focus on innovation, purpose build servers, so yes our times, you know economic situation like in itself is tough yeah. But far from receding we've doubled down on investment and you've seen that with the products that we are launching here, and we will be launching in the years to come. >> I imagine there's a pretty sizeable day impact to the total adjustable market for PowerEdge based on the launch what you're doing, its going to be a tam, a good size tam expansion. >> Yeah, absolutely. Depending on how you look at it, its roughly we add about $30 Billion of adjustable tam between the three purposeful series that we've launched, XE, HS and XR. >> Can you comment on, I know Dell and customers are like this. Talk about, I'd love to get both of your perspective, I'm sure you have a favorite customer stories. But talk about the involvement of the customer in the generation, and the evolution of PowerEdge. Where are they in that process? What kind of feedback do they deliver? >> Well, I mean, just to start, one thing that is essential Cortana of Dell period, is it all is about the customer. All of it, everything that we do is about the customer, and so there is a big focus at our level, from on high to get out there and talk with customers, and actually we have a pretty good story around XR8000 which is call it our flagship of the XR line that we've just announced, and because of this deep customer intimacy, there was a last minute kind of architectural design change. >> Hm-mm. >> Which actually would have been, come to find out it would have been sort of a fatal flaw for deployment. So we corrected that because of this tight intimacy with our customers. This was in two Thanksgiving ago about and, so anyways it's super cool and the fact that we were able to make a change so late in development cycle, that's a testament to a lot of the speed and, speed of innovation that we're driving, so anyway that was that's one, just case of one example. >> Hm-mm. >> Let talk about AI, we can't go to any trade show without talking about AI, the big thing right now is ChatGPT. >> Yeah. >> I was using it the other day, it's so interesting. But, the growing demand for AI, talk about how its driving the evolution of the server so that more AI use cases can become more (indistinct). >> In the edge space primarily, we actually have another product, so I guess what you'll notice in the XR line itself because there are so many different use cases and technologies that support the different use cases. We actually have a range form factor, so we have really small, I guess I would say 350 ml the size of a shoe box, you know, Dave's shoe box. (crowd chuckles) And then we also have, at the other end a 472, so still small, but a little bit bigger, but we did recognize obviously AI was coming up, and so that is our XR 7620 platform and that does support 2 GPUs right, so, like for Edge infrencing, making sure that we have the capability to support customers in that too, but also in the small one, we do also have a GPU capability there, that also helps in those other use cases as well. So we've built the platforms even though they're small to be able to handle the GPU power for customers. >> So nice tight package, a lot of power there. >> Yes. >> Beside as we've all clearly demonstrated the size of Dave's shoe. (crowd chuckles) Dave, talk about Dell's long standing commitment to really helping to rapidly evolve the server market. >> Dave: Yeah. >> Its a pivotal payer there. >> Well, like I was saying, we see innovation, I mean, this is, to us its a race to the top. You talked about racing and messaging that sort of thing, when you opened up the show here, but we see this as a race to the top, having worked at other server companies where maybe its a little bit different, maybe more of a race to the bottom source of approach. That's what I love about being at Dell. This is very much, we understand that it's innovation is that is what's going to deliver the most value for our customers. So whether its some of the first to market, first of its kind sort of innovation that you find in the XR4000, or XR8000, or any of our XE line, we know that at the end of day, that is what going to propel Dell, do the best for our customers and thereby do the best for us. To be honest, its a little bit surprising walking by some of our competitors booths, there's been like a dearth of zero, like no, like it's almost like you wouldn't even know that there was a big launch here right? >> Yeah. >> Or is it just me? >> No. >> It was a while, we've been walking around and yet we've had, and its sort of maybe I should take this as a flattery, but a lot of our competitors have been coming by to our booth everyday actually. >> Deania: Yeah, everyday. >> They came by multiple times yesterday, they came by multiple times today, they're taking pictures of our stuff I kind of want to just send 'em a sample. >> Lisa: Or your shoe. >> Right? Or just maybe my shoe right? But anyway, so I suppose I should take it as an honor. >> Deania: Yeah. >> And conversely when we've walked over there we actually get in back (indistinct), maybe I need a high Dell (indistinct). (crowd chuckles) >> We just had that experience, yeah. >> Its kind of funny but. >> Its a good position to be in. >> Yeah. >> Yes. >> You talked about the involvement of the customers, talk a bit more about Dell's ecosystem is also massive, its part of what makes Dell, Dell. >> Wait did you say ego-system? (laughing) After David just. >> You caught that? Darn it! The talk about the influence or the part of the ecosystem and also some of the feedback from the partners as you've been rapidly evolving the server market and clearly your competitors are taking notice. >> Yeah, sorry. >> Deania: That's okay. >> Dave: you want to take that? >> I mean I would say generally, one of the things that Dell prides itself on is being able to deliver the worlds best innovation into the hands of our customers, faster and better that any other, the optimal solution. So whether its you know, working with our great partners like Intel, AMD Broadcom, these sorts of folks. That is, at the end of the day that is our core mantra, again its retractor on service, doing the best, you know, what's best for the customers. And we want to bring the world's best innovation from our technology partners, get it into the hands of our partners you know, faster and better than any other option out there. >> Its a satisfying business for all of us to be in, because to your point, I made a joke about the high level messaging. But really, that's what it comes down to. >> Lisa: Yeah. >> We do these things, we feel like sometimes we're toiling in obscurity, working with the hardware. But what it delivers. >> Deania: Hm-mm. >> The experiences. >> Dave: Absolutely. >> Deania: Yes. >> Are truly meaningful. So its a fun. >> Absolutely. >> Its a really fun thing to be a part of. >> It is. >> Absolutely. >> Yeah. Is there a favorite customer story that you have that really articulates the value of what Dell is doing, full PowerEdge, at the Edge? >> Its probably one I can't particularly name obviously but, it was, they have different environments, so, in one case there's like on flights or on sea vessels, and just being able to use the same box in those different environments is really cool. And they really appreciate having the small compact, where they can just take the server with them and go somewhere. That was really cool to me in terms of how they were using the products that we built for them. >> I have one that's kind of funny. It around XR8000. Again a customer I won't name but they're so proud of it, they almost kinds feel like they co defined it with us, they want to be on the patent with us so, anyways that's. >> Deania: (indistinct). >> That's what they went in for, yeah. >> So it shows the strength of the partnership that. >> Yeah, exactly. >> Of course, the ecosystem of partners, customers, CSVs, telecom Edge. Guys thank you so much for joining us today. >> Thank you. >> Thank you. >> Sharing what's new with the PowerEdge. We can't wait to, we're just, we're cracking open the box, we saw the shoe. (laughing) And we're going to be dealing a little bit more later. So thank you. >> We're going to be able to touch something soon? >> Yes, yes. >> Yeah. >> In couple of minutes? >> Next segment I think. >> All right! >> Thanks for setting the table for that guys. We really appreciate your time. >> Thank you for having us. >> Thank you. >> Alright, our pleasure. >> For our guests and for Dave Nicholson, I'm Lisa Martin . You're watching theCUBE. The leader in live tech coverage, LIVE in Barcelona, Spain, MWC 23. Don't go anywhere, we will be right back with our next guests. (gentle music)

>>Live from Orlando, Florida. It's the cube covering Microsoft ignite brought to you by Cohesity. >>Welcome back everyone. We are wrapping up three at days of wall to wall coverage of Microsoft ignite. It is a game day atmosphere on the show floor at the orange County civic center. Thank you so much to Cohesity for hosting the cube for this fantastic three days. I'm your host, Rebecca Knight along with my co host Stu Miniman. Still this is awesome. We talk about the buzz on the floor and the energy on the show and definitely guy here Cohesity always bright and activity >>in the booth and it's been a lot of fun hanging out here for the week with you Rebecca and our hosts and all, all of the guests. Yes, absolutely. So this is day three. We are starting our series of interviews, but I want to hear because you are so in this community you have a lot of connections, a lot of buddies, a lot of colleagues, former colleagues, current colleagues. What has impressed you about the show and what is missing? Let's start with the positives and it's interesting because this is only my second year coming. One of those, you know, my background networking, I've interacted with Microsoft for most of my career. I would not say I am deep in the community, but I know enough of the MVPs, have friends here and really have learned a lot in these two years. So first of all, the breadth of this show is just so impressive. >>One of the things that you and I've been talking about the last two years, years, what is the show? It started out as a windows admin show. Lot of discussion about office migration to windows 10 was the big thing last year. We haven't heard as much about this this year. Yesterday was a big developer day. Of course Azure sits at the center of everything. Lots of big announcements here. Felt like a kind of on par with what we hear at AWS. It shows with just so many announcements across the board. But really when you talk about the applications of business productivity, people come to this show. When I talk to people in the booth, I'm looking for solutions and how do I put those together? It's not some of the tech shows where you just, you're constantly down in the speeds and feeds and what they're doing and some of the competitive dynamics. >>I have a problem, my business needs something in, this is what I'm looking to solve. And Microsoft has a broad and diverse ecosystem and the word we kept coming back to the word of the week I think is of course trust. >> Absolutely. I couldn't agree more with what you've just said. That is what we hear. And the other thing about Microsoft is that at a time when big tech is really under a lot of fire, there's a lot of suspicion policymakers, regulators are bearing down on a lot of the tech CEOs. Microsoft really stands above. And when you think about antitrust, there's major presidential candidates talking about breaking up big Chuck, big tech. Microsoft is really riding above that fray. There's sort of a feeling of deja VU for Microsoft, I'm sure. But that they're really been there, done that. They're not. Yeah, I mean it was Satya Nadella to, you know, really put a pointed attack. >>He did not say it, but we all know it's Google. You know the company that was do no evil at the start. Now everybody's concerned because Google's model is primarily selling ads and while Google will say what they're doing in the enterprise, they just acquired Fitbit and said, you're not going to get ads on your Fitbit. We're not going to leverage that way, but there's not that trust built up. And then the number one competitor out there is AWS. And if you talk about the ecosystem, the concern that every AWS show is, Oh my gosh, what announcements are Amazon going to make and are they going to steal my lunch money if you were or put me out of business for the years worth of work on doing. Microsoft doesn't feel that way. They, you know, if you talk about the ecosystem I was talking, they made announcements that do compete against number the products, RPA, or was announced as part of the power platform out there. >>There's a number of RPA companies here. I talked to them there. Microsoft's a strong partner. We've been doing breakouts, we're talking with them. Yes, they are just like SAP getting into this market, but it's a Microsoft shop and it's not, you know, it is new. It's not the best of breed. They're on it. They are not concerned that they can still live in this environment. And I'd say both AWS and Azure very much about choice and ecosystem and building them out. >> So you're talking about the marketplace here. So in terms of the marketplace, what is Microsoft doing to drive business and is it effective? Well actually I'm glad you, so specifically we talk about the marketplace. So there's the ecosystem and then there's actually the marketplace. So AWS has what we really consider, it's the enterprise app store. If I want to go buy software, you know there's Salesforce and all of their connectors and everyone that uses Salesforce knows that. >>But AWS really has driven a robust ecosystem just like on amazon.com most of the products that are sold are from third parties. The AWS marketplace is mostly how I can procure and buy software. And they drive a lot of it. So a lot of the AWS adoption is through the marketplace and the ecosystem makes lots of dollars. Reminds me, we used to talk about VMware for years is for every dollar of VMware you bought you would buy, you know, 10 $20 worth of third party ecosystem. But we were talking about things like storage and like for AWS it's on procuring software and underneath on leveraging the AWS services. While Microsoft Azure has a marketplace, it is not as mature. They don't really push as many people through it. So while I've talked to a number of the partners that are, yes we're part of the marketplace, but people buy lots of different ways as opposed to AWS is trying to get everybody from a customer and an ecosystem through it. >>And part of that is to simplify the environment, how I purchase it. But it's that balance of trust and you know, ease of use out there. So when I look forward, what do I like to see from Azure is how will they mature there. I was actually something John furrier had had us digging into here and the marketplace at Azure definitely is, I would say years behind where AWS is, is there, but you know, Azure great growth, doing really well, a strong trusted ecosystem. Just some areas for improvement that I would look for going forward. >>But maybe that's part of their, their approach and their strategy is we'll work with you, we, we collaborate, we can do this together. Whereas AWS there is that, that feeling sometimes when you're at reinvent, as you said, roll out the beer, CURT's early please. My business is over. So, so, so comparing the two show, the three, the various cloud shows, and this is not just a cloud show, of course we're going to get into that more. But when you think about re-invent and you think about VM world, how does the, the feel and the energy here differ? >>Yeah. So the thing that always strikes me when I go to an AWS show, and I have been to many of them from the regional shows through the big one and reinvent, which is more than twice the size of this 26,000 person show. The customers there are always trying new things. They are open and looking for the environment that they can do new things. Here what we're talking about here feels like it's like a tweener. We had a lot of conversations about building bridges to where customers are while AWS is starting to talk hybrid more and meet you in your data center and doing outpost Microsoft, they have their windows install base, they have their own three 65 pieces. So there's a broad spectrum of from the latest and greatest autonomous systems. You want to talk about it. Microsoft has that through, you know, I'm a, you know, 20 year CIS admin and I, you know, I'm going to hold on to, you know, my servers, you know, as long as I can, they're there for you. >>So Microsoft does bam, that gamut and VMware is more, once again making that transition as we go to the cloud. So Microsoft right in the middle of that transition, we talked a bunch about digital transformation with the customers on here. So it really, it has all a lot for a lot of different people. You know is one of the things I've heard is they really ramped up some of the developer activity at this show. They just bought get hub, get hub, has their own show, get hub universe next week, which will stay very focused on that environment. But Microsoft also has a conference build and there's been some rumblings that maybe build an ignite get wrapped together. We saw that with IBM. IBM had lots of different shows and they put all the wood behind think and made that a massive show. There's pros and cons of that, seeing lots of companies that have taken a big show and put it into a 40 show around the globe. >>Now someone like Amazon has reinvented, but then they have of second tier and third tier regional shows to push that out. So lots of different ways to, to get to customers. Um, and it is interesting, you know, we spent a lot of time talking about Azure Ark. I'll be at the cube con cloud-native clown show in just two weeks and San Diego and expect that to be talked. And really it is in preview mode. So when I look at it at the end of the day is, you know, you've got red hat open shift, you have Google, you have what AWS is doing with outpost and welcome to the party. Microsoft, they have got a strong hybrid solution already because they played at both ends. But really as your arc is unifying and pulling those together so that it's not just my data center and Azure, but even AWS, they're saying, we'll see how this all plays out. >>Microsoft definitely has a strong data focus and a strong application focus. And so it be interesting to see where that adoption happens. I've been saying for a couple of weeks. Really Kubernetes just get baked in everywhere and you know, customers aren't going to have to think about it in a most Microsoft definitely strong partner focus. Just to reinforce something I've said a couple times this week, they still have a partnership with red hat. They still have a partnership with VMware. The Azure arc is not the only way to get the Kubernetes story in play into your Microsoft environment. And Microsoft's done well with that. We all know from the early days of Microsoft living on tops of lots of hardware. Now Microsoft software will live a lot of places. Yes, their cloud is large growing one of the top two choices out there. But they truly embrace that it will be multi-cloud and be able to live in lots of environments. >>So I want to talk about something that's more in my wheel, hasn't met his productivity. So we have heard a little bit about teams. I mean there was a lot of announcements. It's not exactly where we focused a lot here on the cube this week, but there were some really interesting announcements about the ways in which Microsoft is thinking about human productivity, both at individual productivity and team collaboration, the way teams interact and communicate. There are a lot of interesting new uh, characteristics and elements to what they're doing in terms of Cortana re read me my emails. Uh, I'm going to send this email but I'm actually gonna wait, it's good. It's going to be a scheduled send. It's going to send when the, when the, the person I'm sending it to is, is actually at his or her desk. Um, and so those are just some interesting things to me that really speak volumes about how Microsoft views the future of work and views the, the future of our, of our lives. And, and, and understanding how much technology has encroached in our lives because they're saying, read me my emails while I take my dog for a walk while I am actually doing, while I'm on a run first thing in the morning. I, you know, make me more productive but also give me my time back. And so I think those are some really, really interesting ways in which Microsoft, as I said, understands the technology has taken over and they're trying to give you a bit of your time back. >>It's interesting cause you know when I look back, Microsoft has a bit of a checkered history when it comes to some of those environments. We all know the office suite teams is now part of O three 65 and I hear very strong. The people that use it really do like it. But those of us look back and we said, Oh I used to like using Skype and then Microsoft got ahold of it and Oh my gosh, what a horrendous mess. Skype was for a long time when it taught to a collaborative environment. Google really jumped Microsoft with the G suite and many smaller companies were like, Oh, it's relatively easy to use and I can collaborate there. Well teams really has gone through and understand that and we talk about a collaborative environment, you know, Microsoft teams, best of breeds. I attended an enterprise connect earlier this year and I couldn't hear enough about how much that was going on. >>And you know, strong ecosystem of companies that Microsoft worked with. So it's very strong, but it's kind of, if you're a Microsoft shop, you're doing it. But they did lose many companies too free or less expensive or lighter weight options out there. And then everything from Slack ate into it. But you know, Microsoft has a good product. Absolutely. It just, some of it is the perception and some of it is the pricing. You know, they do a good job of making sure that when you get get to college, you, you want to use some of these environments. Oh yeah, the pricing is graded free. But then when you get in the real world, hopefully you'll like it. So Microsoft does a little bit about now something we focused a lot on but did hear really good things about it. And it does get lost a little bit in some of the general discussion about all the other pieces, you know, autonomous systems, AI and the leaders. This stuff of Azure take a little bit of precedent over the, some of the things that are a little bit more on just as you said, business productivity or even on the consumer side of the house for Microsoft. >>So we are, we're, we're wrapping up here but I want to hear just final thoughts, final predictions for 2020 and you've really gotten, you've, we've, we've covered a lot of ground here, this wording, but I'm interested to hear what you think is on tap for Microsoft in 2020 I'll bring >>back to something we kicked off with the jet ideal coming in here really has that that whole process of winning that bid was a fortune function from Microsoft to rapidly mature some of their environment. You talk about security and trust, you know the government is not going to give that environment if it to Microsoft, if they could not trust them. Back when AWS won a CIA deal, it was like, Oh wait, if the security is good enough for the CIA, it's probably good enough for me to consider it. So the government agencies, which historically is not who you think about when you talk about innovation in driving change today. Public sector is really interesting. Even when we were talking to some of the people about, Hey, how can we haven't heard as much about Azure stack over the years? Well, it's been a lot of service providers and government agencies that have been deploying this and therefore we'll do it. So Microsoft still has a lot of work to do contracts. They still have to get some more security clearances. They need to make sure their performance and reliability is up to snuff on because they just can't have outages. If I, if this becomes a greater and greater piece of my overall how I run my business, I can't say, oops, wait, you know the Internet's down. This is now 2019 going into 2020 and in 2020 we'll all have perfect. >>Oh, of course. Oh yes indeed. Sue, I'm looking forward to another great day of coverage with you, and thank you again to Cohesity for hosting us in this really cool booth. Uh, so please stay tuned for more of the cubes live coverage of Microsoft ignite coming up in just a little bit.

>> Live from Las Vegas, it's theCUBE covering Informatica World 2019 brought to you by Informatica. >> Welcome back everyone to theCUBE's live coverage of Informatica World. I am your host, Rebecca Knight, along with my co-host, John Furrier. We are joined by Amit Walia, President - Product and Marketing here at Informatica. Thank you for coming back on theCUBE. So we're here at Informatica World, there's a lot of buzz, a lot of energy, obviously CLAIRE is a big story, your company got great press yesterday from The Wall Street Journal teaming up with Google to tame the data. One of the themes we keep hearing is that data needs AI, but AI needs data. Elaborate on that a little bit. >> That's a great point, in fact I would extend that and say I believe, and I will talk about that today in the closing keynote, is the language that AI needs or speaks is data. Because to be honest, without data, there's no great AI. And I think something that we've known all this while, but now that AI is really becoming pervasive and has skill, you really, really need to give it relevant, good, contextual data for a Siri or a Cortana or Alexa to make some contextual decisions, right? And we see that happening a lot in the world of enterprise now. Finally enterprises are arriving at the point where they want to use AI for P-to-P use cases, not just consumer use cases that you and me are used to. And then, to your other question, AI is a part of everything that we do in data. Because, to be honest, it really helps improve productivity, automate mundane tasks. And I think we were talking before this, there is a massive skills gap. And I think you look around, the economy's kind of fully saturated with jobs, and there's still so much more work to be done with more data, different data, so AI's helping making some of those mundane activities become a lot more easier or autonomous, if I may. >> What's the use cases for CLAIRE in AI around as it grows? Because, you know, the data world, you guys have been doing it for 25 years at Informatica, private for 4 so, innovating on the products side, but it used to be, here's the data department, they handle it. The data warehousing in the fenced out area in the company, now it's strategically part of everything, right? So you guys have the MDM, you've got the Catalog, you've got all kinds of solutions. How is that role changing within your customer base? And what are some of those use cases? Because now they have to think end-to-end, you've got Cloud and On-premise, these are challenges and opportunities. But the role of data and the data teams is expanding rapidly. >> In a significant way. A significant way. I think I kind of was joking with our practitioners yesterday that they were all becoming, they were going from heroes to superheroes, if you are enjoying the Avengers movies, and that analogy. But genuinely, because if you think about it, right, I think what we are seeing in this world, we call it the data three data where the data is becoming a platform of a sort. It is getting decoupled from the data bases, from the applications, from the infrastructure, because to truly be able to leverage AI, and build applications on top, you cannot let it be siloed and be hostage to its individual infrastructure components. So we're seeing that fundamental change happening where data as a platform is coming along, and in that context the catalog becomes a very, very pivotal start, because you want to get a full view of everything. And look, you're not going to be able to move all your data in one place, it's impossible. But understanding that through metadata is where enterprises are going, and then from there, John, as Rebecca's talked about, you can have a customer experience journey with MDM. You can have a analytics journey in the Cloud with an AWS or (inaudible) or a JCP. Or you can have a complete governance and security and privacy journey understanding anomalous activity. >> So before I go any further I just want to ask you about this one point because you guys made a big bet with the Catalog >> Okay, and it's looking good. A lot of good bets. You know, AI, Catalog, Cloud, early on the Cloud, but one of the things I hear a lot is that data's at the blood stream, you want the blood flowing around the system, the body. People looking at data like an operating system kind of architecture where you got to have the data free flowing. So the Catalog seems to be a big bet there. How is that helping the AI peeps because if you can have the data flowing -- >> Yep. No I think -- >> You're going to have feeding the machine learning >> Absolutely. >> The machine learning feeds the application of AI, you got to have the data, the data's not flowing, you can't just inject it at certain times. >> The way we think about it is, you're exactly right. I would just, in fact it's so ah, interesting, the analogy I use is that data is everywhere. It's like the blood flowing through your body, right? You're not going to get all the data in one place to do any kind of analytics, right? You're going to let it be there. So we say metadata is the new OS. Bring the metadata, which is data about the data in one place. And from there let AI run on it. And what we think about AI is that, think about this. LinkedIn is a beautiful place where they leveraged the machine learning algorithm to create and social graph about you and me. So if I'm connected with John, I know now that I can be connected with you. The same thing can happen to the data layer. So when I'm doing analytics, and I'm basically searching for some report, I don't know, through that same machine learning algorithm at the catalog level, now we can tell you, you know what? This is another table. This is another report. This is another user. And so on. And we can give you back ratings within that environment for you to do what I call analytics on your fingertips at enterprise scale. So that's an extremely powerful use case of taking analytics which is the most commonly done activity in an enterprise and make it accurate at an enterprise scale. >> Well the LinkedIn example, you know, of course I have a different opinion on that. They're a siloed platform. They don't have any API's, it's only within LinkedIn. But it begs the question, since you're both that kind of consumer, look at a company like Slack, going public, very successful, their numbers are off the charts in terms of adoption, usage, a simple utility in IRC message chat room that has a great UI on it. But their success came when they integrated. >> Sure. >> Integration was a big part of their success. They wanted to have API's and let customers use the software, SAS software, with a lot of data. So they were really open. >> Yes. >> How were you guys from a business standpoint taking that concept of SAS openness connecting with other apps because I might have, bring my own app to the table as data, and integrate that piece into Informatica. How does that work? >> Very similarly. So the way we've done it is that our whole platform is fully API based. So we have opened up the API's, any application can hook on to that. So we believe that we are the Switzerland of data. So you may have any underlying infrastructure stack. On-prem, in the Cloud, multi-Cloud, whatever it is. Different applications, different Cloud applications, right? So our goal is that at the layer which is the metadata layer on which CLAIRE runs, we've opened up the API's, we've hooked to everything, and so we can consume the metadata, and there we truly provide a true data platform to our organization. So if you are running a Server Snap, a Salesforce.com, Adobe, Google, AWS, you can still bring all that stuff together and make contextual business decisions. >> One of the things you had talked about on the main stage is how the Millennials that you're hiring have higher expectations in their personal lives from the technology that they're using, and that's really pushing you to deliver different kinds of products and services that have the same level of innovation and high touch. Can you talk a little bit about that and how, and how this new generation of the workforce, and there's obviously Gen Y coming right behind it, is really pushing innovation in your company. >> Well you know, I have a fourteen-year-old, so I get a taste of that every day at home. (laughing) So you know, what they want to experience, so I, you know, I use this word, experiences are changing. And by the way they are pushing the boundary for us too. We grew up in the infrastructure software world which you know, twenty-five years ago was all, you can go down to the command line interface. Not any more. You really really have to make it simple. I think users today don't want to waste their time what I call doing mundane activities. They want to get to value fast. That's pushing the boundary for us. In fact that's where we're leveraging AI in our products to make sure we can remove the mundane clutter activities for them, for them to do value added activities. For example, I want to discover data to do some analysis. I don't want to go around discovering. Discover it for me. So that's where CLAIRE comes in and the catalog, right? Discover it for me. You know what? I don't want to figure out whether this data is accurate or not accurate. Tell me. So we are taking that philosophy, really really pushing the boundary for us, but in a good way. Because definitely those users want what I call very simplified and value added experiences. >> And that's really what SAS and consumer applications have shown us, and that's proven to be hard in the enterprise. So I got to ask you as you take this data concept to the infrastructure, a lot of enterprises are re-architecting, you hear words like multi-Cloud, hybrid Cloud, public Cloud, and you start to see a holistic new kind of persona, a Cloud architect. >> Yes. >> They're re-architecting their infrastructure to be SAS-like, to take advantage of data. >> Correct. >> That's kind of known out there, it's been reported on, we've been reporting on it. So the question is, that isn't alignment, that's not just the data people, it's data meets infrastructure. >> Absolutely. >> What's your advice to the companies out there that are doing this, because you guys have Cloud, Google, Amazon, Azure, Cloud, On-premise. You can work anywhere. What's you're advice? >> Yeah, no, I think it's a very good, it's a very topical question. Because I do think that the infra, the old days of separating different layers of the stack are are gone. Especially the old infrastructure all the way to platform as a server stack has to be very well though out together. To your point, customers running a hybrid multi-cloud world, right? So think about it, if you're in the world of improving customer experiences, I may have my marketing cloud running somewhere, I may have my sales cloud running somewhere, and a service cloud running somewhere. But to give a great experience I have to bring it all together. So you have to think about the infrastructure and the data together for enterprises to give a better experience to their customers. And I see innovative customers of companies truly think through that one and succeed. And the ones that are still lagging behind are still looking at that in silos. And then be able to have the data layer for hyper scale. Well these are all hyper scale platforms. You cannot run a little experiment over here. So we've invested in that whole concept of hyperscale, multi-cloud, hybrid cloud, and make sure it touches everything through API's. >> So we've been covering you guys for four years here at Informatica World. It's great to see the journey, nothing's really changed on the messaging and the strategy, you say you're going to do something and you keep doing it, and some little course corrections here, and acquisitions here and there to kind of accelerate it. But when we talk to your customers we hear a couple of different things. We hear platform, Informatica, when describing Informatica. You guys win the whole data thing, you're there, it's the business you're in. In the data business. But I'm hearing new words, platform. Scale. These are kind of new signals we're hearing from your customer base and some of the people here at the show. Talk about that impact, how you guys are investing in the platform, what it means for customers, and what does scale mean for your business and customers? >> No, we've heard that from our customers too. Customers said look, they all recognize that they have to invest in data as a platform. But you know, it's not like an original platform so they want it because we serve the broader state of management needs, so they want us to be like a platform. So we've invested that, couple of years ago we went completely ground-up, re-built everything, micro-services based. All API driven. Containerized. Modular. So the idea is that nobody is buying a monolithic platform. Nobody buying a platform, it just builds by itself. And they can compartmentize it, I want this now, I want that later, so like a Lego block it builds. And, you know what, through an API it also hooks into any of the existing infrastructure they have, or anything new that they want to bring in. So that really pushed the boundary for us. We invested in that. By the way, that platform today, in the Cloud, which you call IICS, runs eight trillion transactions a month. Eight trillion transactions a month. And by the way, last Informatica World, it was running two-and-a-half trillion transactions. So in one year it's gone from two-and-a-half to eight. So we are seeing that really hyper scale. >> And you, and I'm going to ask you if you believe, just, and you can answer yes or no or maybe, or answer on your own, do you believe that data is critical for SAS success? >> Oh absolutely. No doubt about it. I have not met a single customer who ever said anything different. In fact, the thing that I see is like, it's becoming more and more and more a sea-level conversation. That hey, what are we going to do with our data? How do we bring that data together to make decisions? How do we leverage AI and data together? It's truly in our sea-level discussion, whereas it was never a sea-level discussion years ago, it was more about what application am I going to use? What infrastructure am I going to use? Now they're all about, how do I manage this data? >> I wanted to talk about ethics (laughs) and this is, because recently had published a paper about Tech for Good, and it's about this idea of using AI and machine learning to help society achieve better outcomes, and then also to help us measure it's impact on our welfare beyond GDP. Because think about the value that technology brings to our lives. What's your take on this? I mean how much value do you think AI brings to the enterprise in terms of this Tech for Good idea? >> No, so, by the way one of Informatica's values is "Do good". And we are firm believers in that look, there is an economic value to everything in life. But then we all have something to give back to the society. There is something to create value out there which is outside the realm of just pure economics which is the point you were asking. And we are firm believers in that. I do think that by the way, there is a very high bar for all of us in the industry to make sure that not only, it's not just about ethics of AI also at the same time, because we cannot abuse the data. We're collecting a lot of information. You and me as consumers are giving a lot of information and I talked about that yesterday as well, that we believe that the ethics of AI are going to play a fundamental and differentiating role going forward. I think the Millennials we're talking about, they are very aware of that one. They are very purposeful. So they'll look back and say, who actually has a values system to take this technology innovation and do something better with it, not just creating money out of it. And I think I totally agree, and by the way in the very early stages, industry has to still learn that, and internalize that, then do something about it. >> Well Amit, yeah I think you're right on, early days, and I can give you an anecdotal example is that this year, University of California, Berkeley, graduated its first inaugural class of data science analytics. First! First ever class for them. They're a pioneer, they're usually having protests and doing things with revolutionary things. That shows it's so early. So the question I got to ask you is, you've got your fourteen-year-old, you know I have kids, we follow each other on Facebook. I'm always asked the question and I want to get this exposed. People are really discovering new ways to learn. Not just in school, you got YouTube videos, you've got CUBE videos, you got all kinds of great things out there. But really people are trying to figure out where to double down on, what dials to turn, what classes to take, what disciplines are going to help me. It used to be oh, go into computer science, you'll get a great job. And certainly that's still true. But there's now new opportunities for people, data's now grown from you know, programming deeply to ethics. And you don't need to have a CS degree to get in and be successful to fill the job openings or contribute to society. So what are those areas that you see that people who are watching might say hey you know what? I'm good at that, I'm good at art, I'm good at society or philosophy or I'm really good at math or, what skills do you, should people think about if they want to be successful in data? >> You know, I think it's a very foundational question. I think you're right, I think programming has become a lot easier. So I think if I'd stepped back to the days we graduated, right? It's become a lot easier so I don't think that necessarily learning programming is a differentiating, I do think that back where you were going, people who'd generally think about what to do with that. I think there is analytical skills that we all need, but I think the soft skills I believe in the society, we are kind of leaving behind, right? A little bit of the psychology of how users want to use something. Design thinking. By the way I still think that design thinking is not yet completely out there. Um, the ability to marry what I call the left brain to the right brain, I mean, I think that's key. And I do think that we cannot run away completely to the right brain, as much as I am an analytical person myself. I think marrying the left and the right, I do believe, like I, as I said I have a fourteen-year-old. My advice to all those who say, he wants to do Computer Science, is to take enough psychology or design classes to kind of have that balance. So my encouragement would be have the balance. We cannot all just be hyper-analytical. We have to kind of have the balance to see ... >> I think just be smart, balance, I mean again, I have not found one, well I guess the answers are stats and math, have the check, that's easy to say, but ... >> The emotional skills. But you need more of those, I think a little bit more of those left-brain skills also to complement them. >> Well and also for the experience, study art, music, what delights people. What inspires the passion? >> I agree with that. >> Yeah. Absolutely. Amit, always a pleasure to see you. Thank you so much. >> Thank you very much. Always a pleasure to be here. >> Great conversation. Good insight. >> I'm Rebecca Knight for John Furrier, stay tuned at theCUBE's live coverage at Informatica World. (Upbeat music)

>> Voiceover: Live, from Atlanta, Georgia, it's theCUBE, covering CITRIX Synergy, Atlanta 2019. Brought to you by: CITRIX. >> Welcome back to theCUBE. Lisa Martin with Keith Townsend coming to you live from Atlanta Georgia, our first day of coverage of Citrix Synergy 2019. Keith and I are very pleased to welcome you to theCUBE. For the first time, Bob O'Donnell, the founder and president of Technalysis. Bob, it's great to have you on theCUBE. >> Thank you. Great to be here I really appreciate it. It's my first chance to do theCUBE. It's exciting. >> We're so excited because you are no stranger to TV. Bloomberg, CNN, CNBC, Squawk Box, now theCUBE! >> Bob: And the now theCUBE! >> Keith: Most importantly- >> Bob: It completes the circle. >> He's a friend of Leo Laporte, which makes him a super star. >> All: (laughing) >> Well there you go. >> We're sitting in the presence of greatness. >> Oh, I don't know about that. But anyway, no, it's a pleasure to be here and it's nice to chat with you guys. It's a very interesting time that we're in. I mean, when we think about what's happening in the world. For years we've seen this move to cloud-based computing, and SaaS, and everything else. And everybody's excited about all of this stuff, and there's all these tools. And then on top of that, we thought, we have all these devices, right? We've got this amazing range of different devices we can use. But ironically, what it is, is we're in a state of too much of a good thing. It's too much. Even though if you think about it, you'd say, "Well, objectively, there's so much that "we could potentially do here. "I mean, we've got these tools that can do "this and this and this." But all of a sudden, "Well, except I got this one and this one, and this one. "And oh, by the way, if I want to send a message, "I can send it five different ways to Sunday, "and therefore if I want to read a message, "I have to be able to read it "five different ways from Sunday." And so, the challenge that you face is, and Citrix talked about it, I thought, quite nicely in their keynote this morning, is people get overwhelmed. And they just can't get productive with what they're trying to do. And so, what you need to do it figure out ways to turn that chaos into structure and order. And that's what they're trying to do with the workspace. And it looks pretty cool. >> Yeah, one of the offline conversations I had was you get all these tools. It's like somebody took a box of 10,000 Legos and just jumped it on your desk and said, "Build a masterpiece." And what I head this morning was the equivalent of what was like a Star Wars kid of like, "This is what you can build. Here's the directions, "and now you can start to deviate and customize it "for your environment." So one of the things that I'd love to get your input on is this concept of AI ML. This ideal of taking tasks and automating them. It's nothing new. We've tried this with macros and other areas. But the thing that was missing was, these tools were pretty dumb. >> Bob: Right. So the promise of ML AI should make these tools become real. What's your impression of the state of the technology versus what was presented today. >> Well, look, we're in very early days of AI and ML. There are some fascinating things out there. There's a lot of the high profile things that we hear about. The ImageNet and the ability to recognize every kind of dog known to mankind, and all the demos we've all seen at every other trade show. It really is, the fascinating part, exactly, to your point, is that the goal with AI and machine learning is to actually makes things understand. And it's fascinating because... I'll take a bit of a sidetrack but bring it back. When devices started to be able to recognize our words, we assumed, because we're human beings, that they recognized what we meant. But, no. There's a big jump between the words that you can transcribe, and what you actually mean. >> Yeah. That context. >> Context is everything. And context is something that, again as human beings, we take it for granted. But you can't take that for granted when it comes to technology and products. So, the beauty of AI as it starts to get deployed is how do we get the context around what it is that we're trying to do, what we meant to say. Of course, we all want that in real life: "What I meant to say was..." But, "what I meant to do was this." Or, "the task I want to do is that." So, taking that back to what Citrix is talking about is there are a lot of rote procedural things that people do in most organizations. And they gave the classic examples of proving the expense reports and this and that. So, clearly, some of those things they can pre-build. The micro apps, in a lot of ways, they really are macros. It's kind of a fancy macro. And that's fine, but the question is are they smart enough to kind of deviate, "Oh, well, there's a conditional branch "that it automatically builds in a macro "that I didn't have to think about "because it realizes in the context of what I'm doing "that it means something else." Or something like that. >> At the end of the day, I want to get the account balance, however that translates. As opposed to: take this column from row A and put it in row B. No, sometimes row A won't be the correct destination. I want the account balance. >> Right, right. >> And the other truth of the matter is we're still getting used to actually talking to our devices. We do that at home to some degree for people who have Alexas, unless they've decided to stop recording everything, and then that's a whole different subject. But, at work we don't. Interestingly, I remember when I first saw Cortana, for example, on a Windows machine. I thought, in a weird way, Cortana makes more sense because I should want... But it hasn't really happened. It hasn't played out. So there's some level of discomfort of talking to our devices and recognizing these things. So, I think there are cultural issues you still have to overcome. There are physical issues in the workplace, now. Now, when you have these open office environments, which doesn't take a rocket scientist to know that that was going to be a disaster. Whoever thought that was smart, man, let's take a look at where their degree came from. But that's the reality that people are in. So, you've got the physical environment challenges. You've got the cultural "how do I work with this?" environment. And then just starting to realize what it can actually do. And then, of course, you have the problem that it didn't recognize what it actually said. That's something stupid, and the original Siri problems that we all had. But, all of these things tie together because they're all different takes on what machine learning has the potential to do and what we think it should do, and what it can actually do. The one thing I will say is as we head towards 2020, I think we're going to start to finally see some of these things do what we thought they were going to do. They're going to start to have the context. They're going to start to have the intelligence. So, in the work space, it's going to have the ability to know what I mean when I say, "I need the account balance." Or, "I need to know where in the sales pipeline "this particular project is," or whatever task it is that I've got to deal with. And so, understanding that and then building the plumbing to do that is critical. One of the interesting things, if you look at what Citrix does, they're really all about plumbing. They have this ability to pull together all these different elements. From the beginning, what we started talking about. All these different applications over different types of network speeds and connections and make them all work. And yet, they present this very simplified, beautiful, nice little, you're like, "oh, this is great!" But, man, buried beneath there is a lot of stuff. And that's, to give them credit, that's what they're really good at doing. And companies now, the challenge is, a lot of companies have really old applications that they've got to kind of modernize in some way shape or form. And some of them are doing it on their own. They're doing the containerization and all the things we hear about as well. Some of them are wrapping them. Citrix, some of their original business, XenApp, was about app virtualization. Taking an old app and giving access in a modern way. So, again, it's doing that, but the other problem you have to bear in mind, excuse me, is that every company has a different combination of apps. They said 500 apps is normal. A lot of companies have more than that. >> Keith: Mhm. (affirmative) >> The problem is, it's not the same five hundred apps. This company has this set of 500 apps. This company has this set of 500 apps. This company has this set of 500 apps, and maybe 150 of them overlap, which means the long tail of 350 per company has to be dealt with and figured out. And that's, again, those are the problems that they're trying to solve and bring in to a unified environment. >> And also manage these growing expectations that all of us that are workers have from the consumer side of our lives. You mentioned Alexa and Siri, and we have these growing experiences that whether I'm talking to a device or I'm going on Amazon, I want it to know what I want. Don't show me something I've already purchased. And we have these expectations as humans and consumers that we want the apps when we get to work to understand the context and of course, we're asking a lot. In your opinion, where is Citrix in starting to help manage, helping their customers, rather, manage those growing expectations? >> I think Citrix has done a lot in that area. Even many, many years ago they were the first to come up with the notion of an enterprise app store. In the early days of the app store, they came out with this concept of, "We want to do an enterprise equivalent of that." When I download an app that I need to install on a work PC, make it easy to get at. So, from way back when they've been building on that. And then, the examples they gave today, the notification from the airline that your flight has changed, or whatever. Those are all the experiences that we're now used to thanks to cloud-based services. And their point is like, "Hey, why shouldn't we "have that at work, as well?" And so that's exactly what they're trying to work towards, is that notion of cloud-based notifications and services, and things, but related to the specific tasks I have to do. Because at the end of the day, they want to drive productivity. Because we all waste stupid amounts of time, and truth be told, the bigger the company you're at, the more time you waste because of just keeping up. I used to work at a big research firm of 1200 people, and literally half my day, every day, was just procedural stuff. I didn't actually work on the stuff that I thought I was hired to do, except for maybe half the day. And with a lot of people, that's very common. So, anything that can be done to reduce that and allow people to get through the procedural stuff a little bit more efficiently, and then actually let them do the work that they were hired to do and that they'd like to do, and oh, by the way, gives them more satisfaction. All of these things tie together. People tend to say, "Oh well, you know, "that's nice to do, this consumerization of IT, "that's nice." It's not just nice. It's actually practical. It's actually a real productivity enhancing capability. And I think Citrix has done an excellent job of driving that message. It's hard to to do because, again, the complexity of the plumbing necessary is super difficult. But their head and their heart are in the right place in terms of trying to achieve that. >> Well, it sounds absolutely like not a "nice to have," but business-critical. One of the stats that David Henshall, their CEO, said this morning, and Keith's been mentioning a number of times, is that he said there's 7 trillion dollars wasted on output because employees are not able to get to their functions that they were hired for in a timely manner. >> Right. >> So, there's a huge addressable market there of opportunity but also the consumerization that's personalization expectation is huge to not just making me, Lisa Martin, as an employee happy, but my business's customers that I'm dealing with. I think of a sales person, or even a call center support person. If they don't have access to that information, "She already called in about this problem 'with her cable ISP," that person is going to go turn, and go find another option that's going to fulfill their needs much better. >> That's absolutely right. And that was the interesting point that they made. And that's what they're trying to do with the intelligent work space is to move beyond just providing these apps, but actually personalizing it to each individual and being able to say, "All right, each of us are going to have a workspace." Sort of, it looks kind of like a news feed kind of a thing. Each one is going to be different though, based upon, obviously, the different tasks that we do, the order with which we do them, the manner with which we do them." So it does get personalized. The notifications, you know, I may want certain notifications that you don't really care about as much. But that's fine. We can each create that level of personalization and customization. And again, what Citrix is trying to do, and it was a key point that P.J. made, is, "Look, we're not just building an application. "We're building a platform." And that's... The significance of that is big. And remember, he came from Microsoft. He worked on Windows. He worked on Office. So, he's got a long history of working on building platform based tools that have tools that you can build on. That have APIs and ways for other people to add to. So, all of those are critical parts of how they tell that story, and how they get people enthralled enough to say, "Hey, I'm going to make the commitment to do it." Because look, it's a lot of work. Let's not kid ourselves. If I'm not a Citrix shop, but I go, "Damn, that's cool!" There's a fair amount of effort to make all this stuff actually happen. So, it's a commitment. But, once they get them hooked it's a pretty sticky type of environment. Especially as they continue to deliver value and personalization and customization. That, at the end of the day, drives productivity. And that's a pretty straight forward message: "Hey, we can save your workers time "and make them happier." Well, who doesn't want that, right? >> So, let's talk about engaging your customers. Like, I can look at this, and I can easily, say I can come to a conference like this and say, "Wow, I really want the output. I don't want "any of that employee experience stuff. "That stuff just sounds hard, "but the output I definitely want." Talk to me about the evolution of your customers as you walk them through if you want the output, here's what you have to do. And talk to me about, specifically, the success stories of where they didn't get it, and then after you've engaged them, they got it. >> Well, there's so many different variations out there. But, at the end of the day, every company out there is dealing with the fact that they have workers that work in a lot of places on a lot of devices and they have to allow them to get stuff done. And so, it's about how much are they willing to do to make that happen? But there's the psychology of it. There is the whole, "how much of this am I willing to outsource?" Versus, "I really want to keep it inside." So, it depends on the industry and the level of if they are a regulated industry, and all those things have an enormous impact on how they do this. But, if you think back, Citrix's original business was, a lot of it, was again, around desktop virtualization, and actually trying to get really old school stuff, I'm taking mainframe green screen stuff, to actually run on an old Windows PC. And that was kind of a lot of what they did, initially. And then, of course, they've built on from there. So, all along the way, you see different organizations. Citrix has been thought of more as more of the old school kind of enterprise software. Along with an SAP or an Oracle so something like that. I think they've done a particularly good job of being cloud native, cloud aware, and working with these cloud-based tools. Because early on, when we think about what happened with SaaS applications, people thought that was going to dramatically change how anybody did software. And it did, but not in the way people expected. So, I'm trying to get an answer, specifically, to your question, but I think what it is is what they're doing, and what companies who deploy it find is that they can take even these completely different types of software and services, and ServiceNow, and Salesforce, and Workday, and all these kinds of things that are dramatically different, but still, again, have overlapping functionality if I use all of them, and conflict or counteract or interact, or need to interact with other tools I already have that I'm working to change. So, again, what I think that what Citrix has done a good job is they're able to look at the wide range of stuff that people have in that 500 group of apps, or whatever it is, and be able to say, "All right, ten of those are cloud-based services. "But we've got 490 other ones we've got to deal with." And they have different levels of technologies to deal with those. So, what companies can do is they can also pick and choose. They can say, "Look, we're not going to get all 500 apps in our workspace." Maybe they just decide, "But we're going to do these twelve, "five of which are SaaS-based, "and then we've got a couple other critical ones "that we have to do, and that hits 80% of our workers." And they can tackle it that way. So, the bottom line is companies who... Look, it's a big investment up front. So the process is you have to psychologically say, "I'm willing to make an investment in," not obviously, just now, but their roadmap. What they're doing. What they're talking about. That's why they talk a lot about the future because if I buy into this ecosystem, I'm committed. Right? Again, I talking about that earlier: The stickiness question. So, companies who are doing this kind of thing, companies who are trying to make sense of all these applications have to be willing to make those big investments. It used to be, it used to have a huge Citrix server farms, as well. Obviously, with the development of the Cloud and Citrix Cloud, that's all changed. But, it's still a big investment, and they have to work to figure out ways to do this. And if they do, to finally get to, you know, they do see productivity savings. I mean, Citrix is, I don't remember the numbers, but they can qualify actual time saved when their solutions are installed, and that's the benefits that these companies get. So, they have to measure how much is my employee time worth versus the cost of getting these things deployed? >> Well, and I think that's going to be a differentiator for them. I wish we had more time because we could keep talking to you for a long time, but you got to add theCUBE to your list of TV: Bloomberg, CNBC, >> Bob: It's all there. Hey, I'm excited. >> Squawk Box, Now, theCUBE. Bob, it has been such a pleasure to have you on theCUBE. >> Thank you. >> We appreciate your time. >> Thanks so much. Appreciate being here, thank you. >> Our pleasure. For Keith Townsend, I am Lisa Martin. You're watching theCUBE, live from CITRIX Synergy 2019. Thanks for watching. (upbeat techno music)

>> Live, from Orlando, Florida. It's theCube covering Microsoft Ignite, brought to you by Cohesity, and theCube's ecosystem partners. >> Welcome back everyone, to theCube's live coverage of Microsoft Ignite. I'm your host, Rebecca Knight, along with my cohost, Stu Miniman. We have two guests for this segment, we have Ross Smith, the Principle Program Manager at Microsoft, and Greg Taylor, who is the Director of Product Marketing at Microsoft. Thank you so much for joining us! >> Thanks for having us. >> So, I want to start off by talking about messaging. You are both legends in the Microsoft messaging world, sorry to be obsequious here. >> That just means we're old. >> You've been around a while, it's not your first rodeo. >> No, no. >> So, talk a little bit about what's new, what the enhancements you're doing for Enterprise, it is the most used app. >> Yeah. >> So we're launching Exchange Server 2019 this year. It's another version of on-premises exchange, it's incredible. We had 2000 people registered for the session, we had 1000 in the room. There's still some love for on-prem exchange, no doubt, so that's been a big thing we're talking about at Ignite this year. For those customers, and I'll be honest it's very much a release aimed at large Enterprise customers who want to keep some exchange on-prem. We strongly believe that small-medium business should be in the cloud, so we've focused on the kind of features that really large Enterprises really want to get from Exchange. >> Yeah, and then from a app perspective, we've been heavily invested with ALUP, Fry, WES and Android to bring a unique and valuable experience for both consumers and commercial users using both Office 365 and Exchange on-premises. So we now have a hundred million users using Outlook Mobile today, and it's been a great experience and we continue to evolve the app on a weekly basis, now. >> Can you talk a little bit about the evolution of the app and what kinds of features and enhancements you're using for both the consumers and Enterprise? >> Right, yeah. So the app originally began as a consumer acquisition, which we've now targeted and rebranded it as Outlook, and we've been heavily focused on bringing Enterprise features that our users know and love. Office 365 Groups is a great example of an experience that we built into the app that no other native mail client or third-party mail client can deliver today. We've delivered other Enterprise security-specific features like Azure Active Directory conditional access so customers can lock down what mobile apps can access the service and prevent any other client from doing so. And then, of course, there's in-tune app protection policies which allow us to, and customers to, ensure only the corporate data is protected and exclude the personal data, so that we can ensure there's no data leakage scenarios going. >> I wonder if we can step back for a second. I think about messaging, it's very diverse. I remember back in the '90s, I was helping companies get access to this whole "internet thing" and LANs and setting up and oh, we're going to go from faxes and memos to emails, show how old I am in this business, too. But today, our mobile devices, a lot of what we're doing companies, whether they have their own data-centers or doing their cloud, there's usually lots of different ways we communicate. My joke is, the best way to communicate with someone is probably the one they prefer to and hopefully aren't buried in. >> Yes. Because we all have the Slacks and all those other things out there. How do you view the word's game, how does the Exchange and Outlook and those fit into the overall portfolio and interact with everything else. >> From the Exchange side, email is dead. I've heard email is dead for I don't know how many years and well, email is still one of the primary communication methods we all use and rely upon. And so Exchange was one of the applications that kind of coined the mission-critical application moniker, right? 22 years ago, 20 years ago, Exchange was one of the mission-critical apps. But we actually kind of think of Exchange now as almost a service, a commodity, like the power. And most people, it's kind of interesting, we have the front and the back end of things, right? I'm thinking about the messaging infrastructure of the back, and Ross is now working on the client side. Most people see the client features and think of them as Outlook and client features, but a lot of them are Exchange features which are servicing the client. It's been a real kind of evolution. We've got to a point where nobody really cares about the back end, unless it's not there, then that's a problem, but most of the things servicing the client. >> And so what we see is that the transition from typical on-premises infrastructure to the cloud service usually, generally begins with email into the Office 365 stack, and that starts lighting up additional features. And then from a mobility perspective, we're seeing that that begins the on-ramp into mobile. Because, like Greg mentioned, we've had email capability on mobile devices integrated into Exchange for 17 years now, so it's a very ubiquitous thing to have on a mobile device, so it's just a natural progression just to use email on a mobile device. And then that begins lighting up as customers begin to move to Office 365, they start lighting up additional features like teams integration or Skype for business or any of the other Office apps. And then they just light up naturally. And then through all of our protection mechanisms we're able to ensure that that entire experience is secure from a IT business, and protecting it. >> Just speaking of the evolution of messaging in and of itself, what do you see, people who've been in the industry a long time, what do you see as next, I mean, where do we go from here? Email, they say, is dead, we know it's not dead, but what are the next kinds of generation of features and enhancements that you see customers really needing, and that you're working on at Microsoft? >> Alright, I think that Exchange was really interesting from an Office 365 perspective, as Exchange isn't really just a messaging engine anymore, it's a data store that we are, through things like Graph and all the other applications, is giving businesses a whole new way of looking at the data, and so we're pulling data from all the different places. Exchange is becoming almost a plumbing kind of infrastructure piece, but it's a key data source and I think the data is still there, the communication is still there, but I think much of the future development is in the client-side apps and how people interact with the data, and the back-end just becomes the infrastructure, right? >> Actually you bring up a great point. A premise that my Head of Research at Wikibon had is talking about Microsoft's position in AI today, and Office 365 and the messaging that you have, there's so much data there if you wanted it. What are people worrying about? How can a company understand that? How can Microsoft help businesses in general? There's a touchpoint that even an infrastructure as a service-provider wouldn't have, but you really get to the end-point and the end users in productivity, and that's a huge opportunity for Microsoft in the future as long as you're not messing with our data, you're not as heavy into, you know some of the other messaging people out there, that you're like, wait, why am I getting ads for that stuff, or, I think I talked about that stuff. >> And that's a great point, Stu, because going back to Outlook Mobile as an example, right? We're heavily invested in AI-driven capabilities into that app, zero-touch search, as an instance. You can go right in the app, tap one button and you see your favorite contacts, you get your Discover information from the Office Graph your next itinerary and travel information, and we're lighting up that functionality across the board throughout the app. Location-rich data, using Cortana time-to-leave services, so that you can get to a meeting at the right time, as opposed to a typical oh, it reminded me at 15 minutes and I got to hop 45 minutes down the other end of, where are we, West? In the West building, right? So we're building all that functionality into clients like Outlook Mobile and the rest of the stack to help drive that type of capabilities. >> And all of that data's in the back end, right? You said email is this repository of incredible business information, and so the question is how you leverage that, how do you take what's in there and surface it in a way that makes sense to the users? It's a fascinating time at the moment, where the data's there, we just got to know how to use it in the right way. And I agree, using it in the right way and not using it to sell stuff, that's absolutely our approach to it, so, super important. >> And do you work closely with clients to come up with this new kind of functionality? One of the biggest challenges that so many technology companies face is staying on the cutting edge of these ideas and innovation, so how closely are you working with customers to dream up new functionality? >> Yeah, we're working with customers all the time. We do it through a variety of different channels. We have UserVoice, which allows customers and end users to directly interface and provide their ideas. We have private preview programs, where we target customers about specific new feature sets. TAP programs, like we're doing with Exchange 2019, as well as future releases within Office 365 that enable that type of experience. >> Exchange, I think, historically, has always been very customer focused, very community focused. We have a great bunch of MVPs, the TAP program, the Technology Adoption Program, is a bunch of customers that deploy our pre-production code in production for us, so we've got some real big customers who, they're running versions of Exchange that the world hasn't seen. >> One of the themes we heard in Satya's keynote yesterday is business productivity, and we know one of the biggest challenges out there is, you get this new stuff, and you're like, well, I'm going to pretty much just try to use it the way I always have been doing it, and some of us have been using emails for decades and decades and I look at my own usage and wow, I'm probably a bit out of date. If I could just wipe my brain and say 'okay, here's this cool new tool' that could do all this stuff, we wouldn't even call it email, we'd call it something different. I know you guys do things like the Channel 9 broadcast, I'm sure there's lots of things on the website, how do you help customers learn to use the new stuff and get rid of some of the things, the old habits that they had in using these technologies. And can you get everybody to stop 'reply to all' in the big group, that would be super helpful. >> Work on that please. >> That's interesting, we're building it into the apps, to be honest. We're doing a lot of work whenever we release new features to light up an experience within the app that guide the user on how to use that new functionality to help them understand what they can do with the app, as well as simplifying the overall app structure. You look at some of our apps, they become very bloated in terms of all the widgets you have available and knobs to control it and we're trying to simplify that stack. We're refreshing with Outlook 2019 and Office Pro Plus. We're refreshing the user interface on desktop, we're doing the same in Mac. We've done it in Outlook for iOS, we're redoing OA, as well, and Office 365, all to enhance and simplify the experience, and, as well, provide a consistent experience across all the endpoints, which will help. >> If the question is here, how do we wean people off email, how do we get them off email. >> Just their old habits and patterns. >> And you know, it's kind of funny, but it still works. I remember having a conversation with somebody once who, it was a presentation we did once, and it was a team who did more of a social kind of thing, and their view was, they put a picture of the Queen of England up on a slide and said 'Email is old, like the Queen of England.' And my response was, well so are fire and the wheel, but they seem to be hanging around pretty well, so far. So I think there are certain things for which email is still king, but it's evolving and changing. I think we're still waiting for the real killer app that replaces email. >> It's not Yammer. >> It's not what? (laughter) >> It's not Yammer. >> I'm not going on camera saying that. The way I prefer to think of it is, I don't really matter what the client is or how you all interact with it, if we can all use an app that suits our own style of working, right? My inbox is zero inbox. I'm a zero inbox kind of guy, right? If I can work like that and interact with people who want to work on a different client, I'm happy. >> Not to go on the Yammer piece, but you made me think a little bit about acquisitions. Big acquisitions, like LinkedIn and Github, messaging ties into both of those quite a bit. Any visibility you can give? I know there's some integrations there, but how does that look? >> So we're launching LinkedIn integration with Outlook for iOS and Android as we speak. That's something we'll be rolling out shortly, and it enables, within the people or contact card, you can quickly see information from their LinkedIn data set, as well as the ability for us to push data from Office 365 into LinkedIn, so that LinkedIn users can also see relevant information about who that person's interacting with from a calendar type of perspective. So we're definitely taking that availability and providing that through our mutual customers. >> Great. Well, Ross and Greg, thank you so much for coming on the show, it was >> Thanks for having us. really a pleasure having you. >> Yeah, it was great. >> I'm Rebecca Knight for Stu Miniman, we will have more of theCube's live coverage from the Orange County Civic Center Microsoft Ignite in just a little bit. (electronic music)

(music) >> Live from Orlado, Florida, it's theCUBE. Covering Microsoft Ignite. Brought to you by Cohesity. and theCube's ecosystem partners. >> Welcome back, everyone, to theCube's live coverage of Microsoft Ignite. Happy hour has started. The crowd is roaring. I'm your host Rebecca Knight, along with my cohost, Stu Miniman. We are joined by Thomas LaRock. >> He is the Head Geek at SolarWinds. Thanks so much for coming on the show. >> Thanks for having me. >> Great title: Head Geek >> Yes. >> So, tell our viewers a little bit about what - tell us about SolarWinds and also about what you do. >> SolarWinds is a company that offers about forty different products to help with your enterprise infrastructure monitoring. Really unify management of your systems. Been in the business for about twenty years and I've been with them for about eight now. Head Geek is really, uh, you can equate it to being a technical evangelist. >> Okay. So you're out there trying to win the hearts and minds, trying to tell everyone what you do. >> Yes, I need you all to love me. (laughing) and love my products. >> So, Thomas, and for those who don't already follow you on Twitter, you're a SQL rockstar. >> Yes, yes [Stu] - I need to say, "thank you," because you helped connect me with a lot of the community here, especially on the data side of the house. You and I have known each other for a bunch of years. You're a Microsoft MVP. So maybe give us a little bit of community aspect: what it means to be a Microsoft MVP for those who don't know. You're an evangelist in this space and you've been on this show many times. >> I usually don't talk about myself a lot, but sure. (Rebecca laughing) Let's go for it. I've been a Microsoft data platform MVP for about 10 year now. And it was intresting when you reached out, looking to get connected. I was kind of stunned by how many people I actually knew or knew how to get in touch with for you. I help you line up, I guess, a handful of people to be on the show because you were telling me you hadn't been here at Microsoft Ignite and I just thought, "well I know people," and they should know Stu, and we should get them connected so that you guys can have some good conversations. But, yeah, it's been a wild ride for me those ten years where Microsoft awards people MVP designation. It's kind of being an evangelist for Microsoft and some of the great stuff that they've been doing over the past ten years. >> It's a phenomenal program. Most people in the technology industry know the Microsoft MVP program. I was a Vmware expert for a number of years. Many of the things were patterned off of that. John Troyer is a friend of mine. He said that was one the things he looked at. Sytrics has programs like this. Many of the vendors here have evangelists or paragons showing that technology out here. Alight. So talk a little bit about community. Talk about database space. Data and databases have been going through such, you know, explosion of what's going on out there, right? SQL's still around. It's not all cosmos and, you know, microservices-based, cloud, native architecture. >> So the SQL Server box product is still around, but what I think is more amazing to me has been the evalution of...Let's take for example, one of the announcements today, the big data cluster. So, it's essentially a container that's going to run SQL servers, Spark and Hadoop, all in one. Basically, a pod that will get deployed by kubernetes. When you wrap all that together, what you start to realize is that the pattern that Microsoft has been doing for the past few years, which is, essentially, going to where the people are. What I mean is: you have in the open-source world, you have people and developers that have embraced things like DevOps much faster than what the Windows developers have been doing. So instead of taking your time trying to drag all these people where you want them to be, they've just start building all the cool stuff where all the cool kids already are, and everybody's just going to gravitate. Data has gravity, right? So, you're building these things, and people are going to follow it. Now, it's not that they're expecting to sell a billion dollars woth of licenses. No. They just need to be a part of the conversation. So if you're a company that's using those technologies, now all of a sudden, it's like, this is an option. Are you interested in it? Microsoft is the company that's best poised to bring enterprises to the cloud. Amazon has a huge share. We all know that, but Microsoft's already that platform of choice for these enterprises. Microsoft is going to be the one to help them get to the cloud. [Stu]- Thomas, Explain what you mean by that because the strength I look at Microsoft is look, they've got your application. Business productivity: that's where they are. Apologize for cutting you off there. Is that what you mean? The applications are changing and you trusted Microsoft and the application and therefore, that's a vendor of choice. >> Absolutely. If it's already your vendor of choice then, I don't want to say, "Lock in," but if it's already your preference and if they can help get to the cloud, or in the hybrid situation or just lift and shift and just get there, then that's the one you going to want to do it. Everything they're building and all the services they're providing... At the end of the day, they and Amazon, they're the new electric company. They want data. That's the electricity. They don't care how you get it, but between... even Vmware. Between Amazon, Vmware and Microsoft, they're going to be the ones to help... They're going to be your infrastructure companies. Microsoft-managed desktop now. We'll manage your laptop for you. >> Everything that they're doing essentially like, don't even need my own IT department. Microsoft's going to be the largest MSP in history, right? That's where they're headed. They're going to manage everything for you. The data part of it, of course for me, I just love talking about data. But the data part of it...Data is essential to everything we do. It's all about the data. They're doing their best to manage it and secure it. Security is a huge thing. There were some security announcements today as well, which were awesome. The advanced threat detection, the protection that they have. I'm always amazed when I walk through the offering they have for SQL injection protection. I try and ask people, "Who's right now monitoring for SQL injection?" And they're like, "We're not doing that." For fifteen dollars a month, you could do this for your servers. They're like, "that's amazing what they're offerening." Why wouldn't you want that as a service? Why wouldn't you sign-up tomorrow for this stuff? So, I get excited about it. I think all this stuff they're building is great. The announcements today were great. I think they have more coming out over the next couple days. Or at least in the sessions, we'll start seeing a lot of hands-on stuff. I'm excited for it. >> So when you were talking about Microsoft being the automatic vendor of choice. Why wouldn't you? You treated it as a no brainer. What does Microsoft need to do to make sure customers feel that way too? >> I think Microsoft is going to do that... How I would do that. A couple ways. One, at the end of the day, Microsoft wants what we all want, what I want, is they want happy customers. So they're going to do whatever it takes so their customers are happy. So one way you do that is you get a lot of valuable feedback from customers. So, one thing Microsoft has done in the past is they've increased the amount telemetry they're collecting from their products. So they know the usage. They know what the customers want. They know what the customers need. But they also collect simple voice to the customer. You're simply asking the customer, "What do you want?" And you're doing everything you can to keep them happy. And you're finding out where the struggles are. You're helping them solve those problems. How do you not earn trust as a result of all that, right? I think that's the avenue they've been doing for, at least, ten years. Well, let's say, eight years. That's the avenue and the approach they've been doing. I'd say it's been somewhat successful. >> Thomas, as our team was preparing for this show, we understand that Microsoft has a lot of strengths, but if I look at the AI space, Microsoft is not the clear leader today. Um, we think that some of the connections that Microsoft has, everything that you said, down to the desktop. Heck, even in the consumer space, they're down to the Xbox. There's a lot of reasons why Microsoft... You can say, "Here's a path of how Microsoft could become. You know number one, number two in the AI space over time. But, we're listening to things, like the Open Data Initiative that they announced today, which, obviously, Microsoft's working with a lot of partners out there, but it's a big ecosystem. Data plays everywhere. I mean, Google obviously has strong play in data. We've talked plenty about Amazon. What does Microsoft need to do to take the strength that they have in data move forward in AI and become even stronger player in the marketplace? >> So, AI, itself, is kind of that broad term. I mean, AI is a simple if-then statement. It doesn't really have to do anything, right? So let's talk about machine learning, predictive analytics, or even deep learning. That's really the are that we're talking about. What does Microsoft have to do? Well, they have to offer the services. But they don't have offer, say, new things. They just have to offer things that already exist. For example, the idea of, um, incorperating Jupiter notebooks into the Azure Data Studio. So if that could be achieved, you know, now you're bringing the workspaces people are using into the Microsoft platform a little bit, making it a little bit easier. So instead of these people in these enterprises... They already trust Microsoft. They already have the tools. But I got to go use these other things. Well, eventually, those other things come into the Microsoft tools, and now you don't have to use that other stuff either. I would talk about the ability to publish these models as a service. I've done the Academy program. I've earned a few certifications on some of this stuff. I was amazed at how easy it was with a few clicks, you know, published as a service as an API. It's sitting there. I sent in my data and I get back a result, a prediction. I was like, that was really easy. So I know they're not the leaders, but they're making it easy, especially for somebody like me who can start at zero and get to where I need to be. They made it incredibly easy and in some cases, it was intuative. I'm like, oh, I know what to do next with this widgit I'm building. I think it will take time for them to kind of get all that stuff in place. I don't know how long. But does Microsoft have to be the leader in AI? They have the Cognitive Toolkit. They have all that stuff with Cortana. They have the data. I think the customers are coming along. I think they get there just by attrition. I'm not sure there's something they're going to build where everybody just says, "There it is." Except there's the Quantum stuff. And last year's announcement of Quantum, I thought was one of the most stunning things. It just hit me. I had no idea working on it. So, who knows? A year from now there could be something similar to that type of announcement, where we're like, now I get it, now I got to go have this thing. I don't think we all need, you know, a hotdog not hotdog app, which seems to be the bulk of the examples out there. Some of the image classification stuff that you have out there is fabulous. There are a lot of use cases for it. Um, I'm not sure how they get there. But, I do think eventually over time, the platform that they offer, they do get just through attrition. >> One of the things you brought up earlier in this conversation was the Open Source Initiative and Stu, we had expressed a bit of skepticism that it's still going to take three to five years, for, really, customers to see the value of this. But once...The announcement was made today, so now we're going to go forward with this Initiative. What do you see as the future? >> Yeah, I was trying to, even, figure it out. So it sounds like the three companies are sharing data with each other. They pledged to be open. So if you buy one of their products, that data can seamlessly go into that other product is what it sounded like. And they were open, if I heard it right, they were open to partnering with other companies as well. >> Correct. >> Yes. Yes. >> Other vendors or customers, even that could tie in into these APIs, doing everything that they're doing. Open data models. >> Speaking as a data guy, that means if I trust one, I have to trust them all. (Stu Laughing) >> Right? So I don't know. I have trus&t issues. (Rebecca laughing) >> Clearly. >> I'm a DBA, by heart, so I have trust issues. I need to know a little more about it, but on the surface, just the words, "open data," sound great. I just don't know the practical, uh, practicality of it. It sounds like it's a way for people, or these companies, to partner with each other to get more of your data into their platform and their infrastructure. >> Yeah. I think next time we have Thomas on, we're going to spend some time talking about the dark side of data. >> Yes, indeed. >> We can talk dark data. Oh, sure. (Rebecca laughing) >> Well, Thomas, it was so much fun having you on this show and I should just plug your book. You are the author of "DBA Survivor." >> I am. Yes. It was a little book. So being a DBA, uh, I had some challenges in my role and I decided, as my friend Kevin Kline put it to me, he goes, "You should write the book you wish had written for you and handed to you on day zero of being a DBA." And I said, "Oh." It took m&e, I think, like, three weeks. It was just so easyto write all of that. >> It just flowed (laughing.) >> It was just stuff I had to say. But, yeah, thank you. >> Excellent. I'm Rebecca Knight for Stu Miniman. We will have more from theCUBE's live coverage of Microsoft Ignite coming up in just a little bit. (music playing)

(upbeat music) >> From San Francisco, it's The Cube, covering Girls in Tech Catalyst Conference. Brought to you by Girls in Tech. >> Hey welcome back everybody, Jeff Frick here, with The Cube. We're at Downtown San Francisco, Girls in Tech Catalyst. Great event. We've been coming for a couple of years. About 700 professionals, mainly women, a few men, and I think they brought in a busload of kids to get inspired, talking about their stories, and really, it's a series. It's a one-track conference, two days, about 20 minute talks and really good stuff. Really great content. Check it out online if you didn't register this year. Make sure you come next year, and we're excited to have our next guest, Cube alum, really from one of the hottest companies in tech right now, she's Wendy Pfeifer, the CIO of Nutanix. Wendy, great to see you again. >> Hey, nice to see you, Jeff. >> Absolutely, so we see you at Nutanix Next all the time, but we haven't seen you at Girls in Tech. >> Yeah. >> So how long have you been involved in Girls in Tech? >> So, I've been involved since the very first meet up, more than 10 years ago. Girls in Tech was very inspiring to me, and I was here at the Catalyst Conference last year, and I'm a member of the board of Girls in Tech as well, so I'm able to give back and provide some leadership at that level. >> So we just had Adriana on, and she was going through-- >> Yeah. >> Some of the numbers, I mean, the growth of this organization, second to Nutanix, is off the chart. >> Yeah. >> I mean, really amazing. >> It really is amazing, you know. In some ways our time has come. Adriana's had this big vision for a really long time. Really focused on educating women, helping them to understand the potential of careers in tech, and technology knowledge, and that's a global message, and a message that resonates at every age level, and in lots of different sectors of society, so it's juts a privilege to be able to partner with her and others on the board, to enable the vision, and Nutanix as well, you know, is donating, is present here at these conferences, and partnering at Catalyst and Amplify, and other parts of the organization. >> Right, because it's not only the right thing to do, it's also good business, which has been proven time and time again. >> Absolutely, and you know, it's kind of taken on this passion, mission, just excitement thing, but it is practical as well and you know, all the studies, I'm sure so many folks have talked with you about this. There's so many studies, there's so much research that says diversity brings better decision-making, better product development. >> Right. >> And better satisfaction in our work environments as well. >> Right. The other thing that struck me talking to Adriana, and I guess I just didn't know, kind of the breadth of types of activities that Girls in Tech's put on. So we've been to Catalyst before. We've been to-- the Pitch Night, Amplify-- >> Amplify, yeah. >> But I didn't know, she's running, you know, there's all kinds of different-- types of things. >> Absolutely. I think the underlying passion is for education. If you think about, particularly people in underserved communities, there is a real opportunity, you know coding, and learning to code, learning to interact with computers; that's a language that transcends geographic boundaries, ethnic boundaries, age, and religious boundaries, and it's something that, you know ever since my days at Yahoo, I really felt like technology could bring the world together, and today in particular, there is so much disparity between women and men and their access to technology education and technology careers. >> Right. >> That this is, you know, more than just creating a level playing field. I think we're making our own playing field. We're not going to their playing field, anymore. We're creating our own at locations like this. >> Right, and clearly a bunch of founders are here today, who've-- >> Yeah. >> Started their own companies. But the other thing I think is interesting, is culture keeps coming up time and time again in all these conversations, and Adriana's built a culture starting, always from the top down, with the board. It's a phenomenal board of professional women-- >> Yes. >> That she's pulled together of this organization. >> Yeah, there are a couple of males on the board, too. I want to make sure I point out. >> Yep. >> Because we're a diverse board as well, but she has. She has brought together people who are leaders in the technology space, but also folks who are passionate about building a healthy nonprofit organization; one that's global, one that can scale, and so we also look at the fundamentals, and the business fundamentals as well, so we are expanding from 60 to 100 countries, and from 100,000 members to 200,000 members, I mean, who would think, right? >> Right, right, right. >> It's extraordinary. Even then, though, those 200,000 women are a drop in the bucket, compared to the 50% of the global population-- >> Right. >> Who are female. >> Right. And then you work at Nutanix. Super hot-- >> Yeah. >> I don't want to say startup anymore. You guys have IPO'd. >> Right, right. >> But, you know, but you're livin' it in terms of trying to get enough, good, qualified talent-- >> Yes. >> Just to feed the one engine that I Nutanix, so it's a real-- >> Yeah. >> Demand in the market place. >> Definitely, that's the case, you know, we sort of struggle with the thought, you know, are there just not enough women candidates in these fields, but what we learn at conferences like this is, that there are enough women candidates, but we don't necessarily recognize those women, and we don't know where to find them, and they may not find the sort of work that we represent to be attractive. And so we're sort of trying to change how we speak and think. Culture is a good word, but it's a revolution. It's a cultural revolution in terms of identifying talent where it sits. We spoke a lot in the last day and a half around blended careers, the bringing together of art and technology, or communication and technology, and the fact is that technology just underscores everything we do-- >> Right. >> Nowadays. >> Right. >> And so, you know, having people who can blend those things, is a real advantage, and women have this ability to take a multi-faceted approach to the work that we do and the way that we live our lives. We multi-task as a sport. >> Right, right. It's interesting, too, as the machines get better and as A.I. gets better, machine learning, the softer skills applied with the context become so much more important than necessarily just the super hard-core coding skills. >> You know, I have a story around that. So, we've just deployed, my IT department has deployed a machine-learning tool at Nutanix, to replace a lot of the interactions that happen on our help desk, and we found we just couldn't scale as the company was scaling, so we've been training A.I. from a company called Moveworks, and you know, we've been training it uniquely with our voice, and I think a little bit with my voice, and I just had one of our employees write back to me and say, "Not only is this thing", we call it Xbot, "Not only is Xbot solving my problems, but", he said, "she is pretty sassy, too." And I'm like, yay, he knows it's a she! >> Right, right. >> Right, and she's sassy too, so yeah, that unique voice-- >> Right. >> Is infusing even the machine-learning training that we're doing-- >> Right. >> And I think that makes for a more delightful experience-- >> Right. >> For all of us. >> It's funny, the voice thing, 'cause you know, Google had their very famous, the restaurant reservation call-in demo-- >> Yes! >> They got capped on a little bit-- >> Right. >> For, you know, was it real or not, but what made it so, so dramatic was the human-like elements in the conversation of the machine-- with ums, and ahs-- >> Absolutely. >> And uhs, and pauses, which we laugh about, 'cause we can shoot Cube interviews, everybody wants to cut those parts out, and we're like no, that's what makes people, people. >> Right, exactly, I agree with you. And at the same time, you know, there are, you know, things that are uniquely female stereotypes. We're more wordy. We have more things to say. >> Right. >> You know, we're more multi-dimensional. We can hold two thoughts at the same time, and so that's part of the richness of communication and our interaction too, but to the extent to which we can embed that in our technologies and our interactions, those are the extent to which they'll be more delightful-- >> Right. >> It's no coincidence that Siri and Cortana and all of those A.I.s sort of have this female persona, and I don't know if you know this, the, you know, Cortana, who's the Microsoft, you know, A.I., you know, she's voiced by the same character that's Cortana in one of their video games-- >> Oh, really? >> And she's sort of this like, badass fighter gal, too, so check it out. >> Well, we know what happened to Bob, right? >> Right. >> I know, poor Bob. >> Which, ironically, was Melinda Gates's project. Which, I don't know if you knew-- that story. >> I did not know that. >> So yeah, Melinda Gates's introduction to Bill was as product manager for Bob, which, if you don't know that story, check it out. It's old history. >> Oh, that's-- fantastic! >> But it's very good. Alright, before I let you go, one last thing. >> Yes. >> So you spoke, and they've got these great posters all around the room with little highlights from people's-- >> Yes. >> Conversations and yours was, I described it off the wall, "It's okay to be bad." >> Yes. >> I'd love, for the people that missed it, what's the message there? It's an important message. >> Yeah. >> Especially for women. >> Yeah, I think as women, you know, we don't have a lot of role models and when I get up as a role model, I'm one of the few CIO's who's female and Silicon Valley. You know, we give these speeches, and they sort of make us like Mother Teresa, you know. First you hae your mission in mind, and you lean in, and you do all these awesome things. But the fact is, it is actually okay, to be yourself. It's okay to be bitchy. It's okay to be cranky. It's okay for anger to fuel you. It's okay to be aggressive, and even if your male counterparts tell you otherwise, or say, "Wow, that's "unseemly.", I think it's just okay. We don't have to be pure and perfect in order to be successful. I can be those things all at the same time. And I also say, it's also okay to be good, to be merciful, to be soft-spoken, to be wordy, to be studious; that combination of things. We're allowed to be our genuine selves, and we don't have to be perfect to be successful and I feel like I embody that-- in particular. >> Yes, you certainly do. You certainly do! >> What, I'm not perfect? >> Yes, I mean the Nutanix story is a phenomenal story. >> It is. We are fortunate, we've been there since the beginning-- >> Absolutely. >> Watching it grow, and so no-- >> Helping us to frame the story, so thanks to The Cube. I appreciate that. >> Well, and you're super successful, and the company's successful so the fact that are Wendy, you know, you are who you are. You're a big personality, and it comes through, and it's great, and it works, and you're successful, so, if they need someone to look up to, you're certainly a fantastic role model. >> Thank you so much. Well I appreciate that. It's funny, 'cause I have never tried to be a role model, and now, just by accident, I've survived long enough. Here I am. (both laughing) >> Well that's a whole different conversation-- >> Right, right. >> You just look around like, I am the oldest guy in the room. But that's a different thing. >> I know. You're actually the only guy, just sayin'. >> Alright, well Wendy thanks for takin' a few minutes, and I guess we'll see you next at Nutanix next, if not sooner. >> I look forward to it, thanks. >> Alright, thanks. She's Wendy, I'm Jeff, you're watching The Cube from women, or Girls in Tech Catalyst 2018. (upbeat music)

(upbeat music) >> From San Francisco, it's The Cube, covering Girls in Tech Catalyst Conference. Brought to you by Girls in Tech. >> Hey welcome back everybody, Jeff Frick here, with The Cube. We're at Downtown San Francisco, Girls in Tech Catalyst. Great event. We've been coming for a couple of years. About 700 professionals, mainly women, a few men, and I think they brought in a busload of kids to get inspired, talking about their stories, and really, it's a series. It's a one-track conference, two days, about 20 minute talks and really good stuff. Really great content. Check it out online if you didn't register this year. Make sure you come next year, and we're excited to have our next guest, Cube alum, really from one of the hottest companies in tech right now, she's Wendy Pfeifer, the CIO of Nutanix. Wendy, great to see you again. >> Hey, nice to see you, Jeff. >> Absolutely, so we see you at Nutanix Next all the time, but we haven't seen you at Girls in Tech. >> Yeah. >> So how long have you been involved in Girls in Tech? >> So, I've been involved since the very first meet up, more than 10 years ago. Girls in Tech was very inspiring to me, and I was here at the Catalyst Conference last year, and I'm a member of the board of Girls in Tech as well, so I'm able to give back and provide some leadership at that level. >> So we just had Adriana on, and she was going through-- >> Yeah. >> Some of the numbers, I mean, the growth of this organization, second to Nutanix, is off the chart. >> Yeah. >> I mean, really amazing. >> It really is amazing, you know. In some ways our time has come. Adriana's had this big vision for a really long time. Really focused on educating women, helping them to understand the potential of careers in tech, and technology knowledge, and that's a global message, and a message that resonates at every age level, and in lots of different sectors of society, so it's juts a privilege to be able to partner with her and others on the board, to enable the vision, and Nutanix as well, you know, is donating, is present here at these conferences, and partnering at Catalyst and Amplify, and other parts of the organization. >> Right, because it's not only the right thing to do, it's also good business, which has been proven time and time again. >> Absolutely, and you know, it's kind of taken on this passion, mission, just excitement thing, but it is practical as well and you know, all the studies, I'm sure so many folks have talked with you about this. There's so many studies, there's so much research that says diversity brings better decision-making, better product development. >> Right. >> And better satisfaction in our work environments as well. >> Right. The other thing that struck me talking to Adriana, and I guess I just didn't know, kind of the breadth of types of activities that Girls in Tech's put on. So we've been to Catalyst before. We've been to-- the Pitch Night, Amplify-- >> Amplify, yeah. >> But I didn't know, she's running, you know, there's all kinds of different-- types of things. >> Absolutely. I think the underlying passion is for education. If you think about, particularly people in underserved communities, there is a real opportunity, you know coding, and learning to code, learning to interact with computers; that's a language that transcends geographic boundaries, ethnic boundaries, age, and religious boundaries, and it's something that, you know ever since my days at Yahoo, I really felt like technology could bring the world together, and today in particular, there is so much disparity between women and men and their access to technology education and technology careers. >> Right. >> That this is, you know, more than just creating a level playing field. I think we're making our own playing field. We're not going to their playing field, anymore. We're creating our own at locations like this. >> Right, and clearly a bunch of founders are here today, who've-- >> Yeah. >> Started their own companies. But the other thing I think is interesting, is culture keeps coming up time and time again in all these conversations, and Adriana's built a culture starting, always from the top down, with the board. It's a phenomenal board of professional women-- >> Yes. >> That she's pulled together of this organization. >> Yeah, there are a couple of males on the board, too. I want to make sure I point out. >> Yep. >> Because we're a diverse board as well, but she has. She has brought together people who are leaders in the technology space, but also folks who are passionate about building a healthy nonprofit organization; one that's global, one that can scale, and so we also look at the fundamentals, and the business fundamentals as well, so we are expanding from 60 to 100 countries, and from 100,000 members to 200,000 members, I mean, who would think, right? >> Right, right, right. >> It's extraordinary. Even then, though, those 200,000 women are a drop in the bucket, compared to the 50% of the global population-- >> Right. >> Who are female. >> Right. And then you work at Nutanix. Super hot-- >> Yeah. >> I don't want to say startup anymore. You guys have IPO'd. >> Right, right. >> But, you know, but you're livin' it in terms of trying to get enough, good, qualified talent-- >> Yes. >> Just to feed the one engine that I Nutanix, so it's a real-- >> Yeah. >> Demand in the market place. >> Definitely, that's the case, you know, we sort of struggle with the thought, you know, are there just not enough women candidates in these fields, but what we learn at conferences like this is, that there are enough women candidates, but we don't necessarily recognize those women, and we don't know where to find them, and they may not find the sort of work that we represent to be attractive. And so we're sort of trying to change how we speak and think. Culture is a good word, but it's a revolution. It's a cultural revolution in terms of identifying talent where it sits. We spoke a lot in the last day and a half around blended careers, the bringing together of art and technology, or communication and technology, and the fact is that technology just underscores everything we do-- >> Right. >> Nowadays. >> Right. >> And so, you know, having people who can blend those things, is a real advantage, and women have this ability to take a multi-faceted approach to the work that we do and the way that we live our lives. We multi-task as a sport. >> Right, right. It's interesting, too, as the machines get better and as A.I. gets better, machine learning, the softer skills applied with the context become so much more important than necessarily just the super hard-core coding skills. >> You know, I have a story around that. So, we've just deployed, my IT department has deployed a machine-learning tool at Nutanix, to replace a lot of the interactions that happen on our help desk, and we found we just couldn't scale as the company was scaling, so we've been training A.I. from a company called Moveworks, and you know, we've been training it uniquely with our voice, and I think a little bit with my voice, and I just had one of our employees write back to me and say, "Not only is this thing", we call it Xbot, "Not only is Xbot solving my problems, but", he said, "she is pretty sassy, too." And I'm like, yay, he knows it's a she! >> Right, right. >> Right, and she's sassy too, so yeah, that unique voice-- >> Right. >> Is infusing even the machine-learning training that we're doing-- >> Right. >> And I think that makes for a more delightful experience-- >> Right. >> For all of us. >> It's funny, the voice thing, 'cause you know, Google had their very famous, the restaurant reservation call-in demo-- >> Yes! >> They got capped on a little bit-- >> Right. >> For, you know, was it real or not, but what made it so, so dramatic was the human-like elements in the conversation of the machine-- with ums, and ahs-- >> Absolutely. >> And uhs, and pauses, which we laugh about, 'cause we can shoot Cube interviews, everybody wants to cut those parts out, and we're like no, that's what makes people, people. >> Right, exactly, I agree with you. And at the same time, you know, there are, you know, things that are uniquely female stereotypes. We're more wordy. We have more things to say. >> Right. >> You know, we're more multi-dimensional. We can hold two thoughts at the same time, and so that's part of the richness of communication and our interaction too, but to the extent to which we can embed that in our technologies and our interactions, those are the extent to which they'll be more delightful-- >> Right. >> It's no coincidence that Siri and Cortana and all of those A.I.s sort of have this female persona, and I don't know if you know this, the, you know, Cortana, who's the Microsoft, you know, A.I., you know, she's voiced by the same character that's Cortana in one of their video games-- >> Oh, really? >> And she's sort of this like, badass fighter gal, too, so check it out. >> Well, we know what happened to Bob, right? >> Right. >> I know, poor Bob. >> Which, ironically, was Melinda Gates's project. Which, I don't know if you knew-- that story. >> I did not know that. >> So yeah, Melinda Gates's introduction to Bill was as product manager for Bob, which, if you don't know that story, check it out. It's old history. >> Oh, that's-- fantastic! >> But it's very good. Alright, before I let you go, one last thing. >> Yes. >> So you spoke, and they've got these great posters all around the room with little highlights from people's-- >> Yes. >> Conversations and yours was, I described it off the wall, "It's okay to be bad." >> Yes. >> I'd love, for the people that missed it, what's the message there? It's an important message. >> Yeah. >> Especially for women. >> Yeah, I think as women, you know, we don't have a lot of role models and when I get up as a role model, I'm one of the few CIO's who's female and Silicon Valley. You know, we give these speeches, and they sort of make us like Mother Teresa, you know. First you hae your mission in mind, and you lean in, and you do all these awesome things. But the fact is, it is actually okay, to be yourself. It's okay to be bitchy. It's okay to be cranky. It's okay for anger to fuel you. It's okay to be aggressive, and even if your male counterparts tell you otherwise, or say, "Wow, that's "unseemly.", I think it's just okay. We don't have to be pure and perfect in order to be successful. I can be those things all at the same time. And I also say, it's also okay to be good, to be merciful, to be soft-spoken, to be wordy, to be studious; that combination of things. We're allowed to be our genuine selves, and we don't have to be perfect to be successful and I feel like I embody that-- in particular. >> Yes, you certainly do. You certainly do! >> What, I'm not perfect? >> Yes, I mean the Nutanix story is a phenomenal story. >> It is. We are fortunate, we've been there since the beginning-- >> Absolutely. >> Watching it grow, and so no-- >> Helping us to frame the story, so thanks to The Cube. I appreciate that. >> Well, and you're super successful, and the company's successful so the fact that are Wendy, you know, you are who you are. You're a big personality, and it comes through, and it's great, and it works, and you're successful, so, if they need someone to look up to, you're certainly a fantastic role model. >> Thank you so much. Well I appreciate that. It's funny, 'cause I have never tried to be a role model, and now, just by accident, I've survived long enough. Here I am. (both laughing) >> Well that's a whole different conversation-- >> Right, right. >> You just look around like, I am the oldest guy in the room. But that's a different thing. >> I know. You're actually the only guy, just sayin'. >> Alright, well Wendy thanks for takin' a few minutes, and I guess we'll see you next at Nutanix next, if not sooner. >> I look forward to it, thanks. >> Alright, thanks. She's Wendy, I'm Jeff, you're watching The Cube from women, or Girls in Tech Catalyst 2018. (upbeat music)

>> Live from Orlando, Florida, it's theCUBE covering Cisco Live 2018. Brought to you by Cisco, NetApp, and theCUBE's Ecosystem partner. (techy music playing) >> Welcome back, I'm Stu Miniman and we're getting to the end of three days of live, wall-to-wall coverage here at Cisco Live 2018, and you're watching theCUBE. Happy to welcome to the program first time guest David Tucker, who's the SVP of business development, with SingleWire, thanks so much for joining us. >> I'm glad to be here, Stu. >> All right, so David, you've worked for Cisco, you're now a partner with them. Give us a little bit about your background and tell us, for those who don't know, what SingleWire's mission is. >> Okay, my background is almost 40 years in the voice space, and then I joined SingleWire about two... Two and a half years ago, after leaving Cisco for 18 years. So, Singlewire is a ISV that partnered with Cisco right after 9/11 when the Department of Interior came to Cisco and said, "We have to evacuate "all of our buildings in less than "10 minutes, give us a solution." Our product, InformaCast, was born after that event. So, what we do is we work with Cisco's UC collaboration portfolio, and when a customer needs to get critical communications out to employees, such as a weather alert, such as a safety announcement, in a hurry and they need to reach all their employees no matter where they may be, that's where we come in. >> Yeah, so David, it's an interesting dichotomy. On the one hand, you know, when I go to my kids and I say, you know, "You have this device"-- >> Right. >> It's for the internet, the apps, and you know, text and everything... They don't actually use voice on it all that much. >> Right. >> On the other hand, you know, I go to some of the cloud shows and things like that, you know, voice is the new interface. I've got an Alexa and I got a Google Home and I talk to Siri and Cortana and everything like that, so people are programming again for voice. Give us your perspective on, you know, just voice in general and then I definitely want to get into, you know, your company's mission and how some of that stuff works. >> Well, couple thoughts... First off, when you need to communicate to people and get their attention there's nothing better than audio with voice, live audio. You know, if there's an emergency in a building, for example, if you hear it in your ear through, you know, a speaker, through a phone, through your cell phone, it gets your attention. If it's a text or an image I may look at it later and it's too late. From a user interface perspective, when you walk into a building or you now need to communicate that there's an event going on, what better way other than to speak it? "I need help." "Man down." "There's an armed gunman in the building." "There's a chemical spill in the factory." Using voice is a great way to communicate and to trigger events is a natural way of doing it. So, voice is still very powerful in terms of, you know, that human to human interaction. >> Yeah, absolutely, so tell us a little bit about how do these mass notifications work? You know, I've been, I travel a bunch, you know, for these environments and I've been places where all of a sudden everybody's phones start making those weird sounds because you know, flood alerts are going on. You know, "Thunderstorm, stay in place." You know, sometimes when there are either manmade or nature made events, you know, how does this work? Is this tied to the phone network, is it, you know, how does this fit in? >> Well, think of us as kind of a Swiss Army knife piece of software where a customer may have all kinds of ways to trigger an event, and it could be as simple as a panic button under a desk or a panic button on a Cisco phone, it could be tied to the weather service, such as a tornado bearing down on your building, and then we have to then communicate out to reach all the employees through their mobile interface, through digital sign-ins, through overhead speakers, through their Cisco phone be able to reach everybody. So, it's kind of that any-to-any kind of model because you never know where people are going to be, and so that's really what SingleWire really does. Very common in schools, K through 12, obviously. A lot of universities, but there's now a workflow component of this as well. "I need to be able to tell the "employees that my network is down." "There's a chemical spill in the factory. "How do I tell the right people not "to drive through that chemical spill?" So, that's what we really do, we're that Swiss Army knife of really making sure people know, whatever event it may be, as quickly as possible, and seconds is what it really comes down to. >> All right, and David, I heard you say this can be like a featurous part of a Cisco phone, so I assume that the software that goes in... Can you speak a little bit about, you know, how much is just... You have pre-made packages for verticals and how much is it... You know, we're here in the DevNet zone or you know, people coding and you know, putting together their own packages or you know, building you as part of a custom application. >> Well, we're one of the very first Cisco Ecosystem partners going back into 2001. Our system is API forward, so we've been working with Cisco APIs into the phone and into Call Manager since that timeframe, because we need to be able to talk to the speaker, be able to put something on the display of the phone. We need to be able to talk to Call Manager to know where people are, who's on what phone, what building, what floor they're on, and then we also have APIs on our side. So, we're also like a Ecosystem partner of Cisco but talking to another ecosystem of speaker vendors and of digital sign vendors. We're working now with the intent-based networking solutions, so when they're having problems in the network and they need to be able to communicate to certain people that there's a network issue, you know, who do you tell? So, you know, plug into that ecosystem, as well. So, that's our livelihood is DevNet. >> That's fascinating, yeah, it's great. No longer the pagers going off, right? >> That's right. >> Now that they hear that little voice on the weekend when they're not even on call anymore. (laughing) >> That's right, that's right. We're going to find you, yeah. (laughing) >> It sounds like you've got a really interesting, diverse customer set. I wonder if you have any interesting customer examples or things that would help us, you know, really put a face on these solutions. >> Our common, our core applications deal around safety, safety in the workplace, safety in a government building, safety in a school, but our customers have taken our product and used it for all different kinds of things. We have a school system, for example, that connected us to their restrooms because they wanted to be able to save water, and after hours we'd turn off the water supply so the toilets aren't running all the time. >> Right. >> We have an ice cream company that connected us to their ammonia sensors because they use ammonia to clean the tanks to make sure there's no Wisteria in there. So, that basically is an application where now, you know, that sensor goes off, we tell the people on the forklifts not to drive through this particular area. So, we have another hospital in California, Laguna Hospital, it's a hospital that focuses on patients with dementia, and they put RFID tags on the patient, and when they get up and they wander the hallways they may get lost and they get confused. We can detect that that patient is now in this particular wing. We now play back over the closest speaker the voice of their loved one telling them to go back to their room, which they tend to respond to. So, those are some interesting use cases how we tied Cisco technology to ours. >> Yeah, that's fascinating, David, have you been to a few of these Cisco Lives in the past? >> In my career quite a few, yes. >> Yeah, it had been a couple of years since I'd been here. There's great energy here, especially being, you know, here in the DevNet zone. What do you see that's different today in networking in general and at Cisco Live specifically? >> It continues to be a evolution to more open connectivity. In the early days it was all about Cisco and it was very much, "Sell my box." Now it's selling solutions and the resellers and the partners here that are selling those solutions look to multi-vendor type environments, and Cisco's openness to that has really changed over the years, and I was involved in the very beginning days of the Ecosystem and the collab group, and it was really about starting that ball going. But you know, this is a totally different environment now and it's really amazing to feel the energy of people willing to work together and create something unique. So, that's the big change I see. >> Yeah, absolutely, I think back to... You know, the line you'd hear is like, "Well, Cisco is the standard," so that's kind of the way people do things, but that community and openness, it's making progress. Not saying that everything that Cisco does is 100% open, but it is... We were talking to Susie Wee earlier and some of the other people in DevNet is... Remember when Cisco had, like, one API-- >> Oh, yeah. >> For a product, now you know, there are a lot of solutions and they're building and they're collaborating with the community. >> Right, right. >> All right, Dave, I want to just give you a final word as to, you know, things you're seeing out there, what's exciting you the most and any final takeaways from the show? >> Well, I think networking continues to evolve. I think UC and collaboration is really still in the forefront of how it can affect how businesses operate, and you know, with the extension of video in meetings, you know, I see that's going to continue to be very exciting for both Cisco and for customers. You know, what we do is really on the forefront of people's minds now with safety and we're just on the tip of the iceberg of customer opportunities, so you know, if somebody's out there, he knows a Cisco customer, give us a call. >> All right, well David Tucker, thank you so much. SingleWire, absolutely, security of the network has been top of mind, security of people, absolutely, critically, and great to see some of those things also spreading into lots of other ecosystems and building interesting solutions. So, be back with lots more coverage here at Cisco Live 2018. I'm Stu Miniman and thanks so much for watching theCUBE. (techy music playing)

>> Narrator: Live from Las Vegas, it's the CUBE covering Service Now Knowledge 2018. Brought to you by Service Now. >> Welcome back to Service Now Knowledge 18 this is the CUBE's live coverage. We are the leader in live technology coverage. We extract the signal from the noise. I'm Rebecca Knight your host along with my cohost Dave Vellante. We've got a great panel right now. We have Andrew Wilson who is the CIO of Accenture and Ellen Shook who is the chief leadership in human resources officer at Accenture. Thanks so much for coming on the show. >> Thanks for having us. >> Hello great to be back. >> Good to see you again. >> Before the cameras were rolling we were talking about people driven change. But Accenture not but, and Accenture is a huge organization. 400,000 plus individuals working around the world. How do you drive change in such a large and dispersed organization? >> Well I think the most important thing is that change isn't human driven but humans need to be at the center of all change and I think that's why Andrew and I show up in a lot of places together. Because we do use technology to elevate the human experience at Accenture. And the more digital an organization becomes the more important human connection is and that's what we do is create truly compelling experiences for our people. >> Because we don't have separate agendas at Accenture. The relationship that Ellen and I have I think is one of the most important in our enterprise. Where we're driving digital transformation for our clients and within our own business and it's equal parts technology, talent, and change. And so you have to bring those things together and so what we're doing at Knowledge is talking a lot about the outcomes that we drive. Where we're in an experience rich culture our people, our employees, our citizens, our customers. They demand an experience which is very different to how the old IT posture had to deliver. So if we get the partnership right we create a culture and an environment that they'll have fun in and enjoy and not just have to turn up at work for. >> So Ellen what's the outcome that you're trying to achieve? Let's work backwards from there when you think about your human experience? >> Well really what we're trying to do is create an environment where our people can be successful both professionally and personally. Because you, we really require huge diversity at Accenture because in order to bring innovative solutions to our clients we truly need very broad diversity and in order to discover and inspire diverse base of talent. We need to create world class experiences that really unlock their full potential. >> We're all human beings after all. But human beings whether or not we're delivering services or whether we're consuming them. So under Ellen's leadership we talk about truly human and I think that's really important because we must reflect and understand the community we serve. So if we don't have the diversity, if we don't have the gender mix. If we're not looking like the humans who we need to look after then there's going to be a barrier and I think that's at the heart of a lot of modern transformation. >> Now hang on. I heard you say today you have a lot of nn human workers. >> I do, I do. >> So they're not all humans. Who are they, are they robots? >> Well the future of work and the future workforce is a combination of human and machine. Because you need both and you need both working in a way that compliments each other. So we're often asked does the machine replace the human. No it doesn't it changes the content of the work and frees the human to do more interesting work and we need both in a modern agenda. >> And quite simply we do have a very strong belief that technology elevates humans and does not eliminate humans. >> And I'm an optimist too but when I go to the airport I see kiosks, more kiosks than humans. When I drive down the highway out of Heathrow I see all the billboards and they're neon now or electronic so clearly machines have always replaced humans in jobs and clearly as humans we've always overcome. So I'm an optimist too but it seems different this time around because, it cognitive functions and it seems like a whole new set of skills. You guys are experts at this. What are your thoughts? >> I think we are building a set of skills is the new that's absolutely essential for the modern enterprise. So when you drive down the road from Heathrow you don't see the data scientists, you don't see the design thinkers. You don't see the humans that are listening to and talking with their customers and surfacing insights. We think about applying intelligence in the enterprise. Now the humans wouldn't have time to do that if they had to deal with all the old transactions. Free them up from that and then they can do all of this interesting work and that's the future of work. >> One of the things you were talking about on the main stage Andrew was about the changing role of the CIO and you said I actually think of myself as a chief experience officer. Can you refine that a little bit? >> Well I think Ellen and I both care about the experience of all of our employees, all of our humans, all of our citizens and all of our customers and clients as well. So the days of operating in a data center, of buildings systems are long gone. Accenture is now 90% in the cloud and I have to think about services which are really flexible, agile that deliver outcomes. So if my customers are not enjoying the experience and having fun and feeling at home. They're going to walk away so I care much more and that's why I think I lead with experience as the chief experience officer. >> So one just, to bring that down to an example. We hire about a 100,000 people a year and if you think of kind of the old paradigm when someone starts at your company. They have to get assigned a desk, a computer, a security badge you know get onto payroll and all of that historically has been done very siloed function by function. What Andrew and I are trying to create is an exciting experience when you show up for work on the first day where all of that is frictionless. All of that process goes to the backstage and how you feel about showing up as a new employee on your first day is just a glorious experience. >> So we always talk about people process and technology as a CIO you understand. Well the technology will continue to progress it's the people in process that are hard part. But can you actually achieve that vision without a technology platform that is flexible, that enables that type of work environment? >> The technology problem is really what is the enabler of the experiences we're trying to create. But the most important thing that the technology does for us is enables us to create truly world class human experiences. >> Before the cameras were rolling you were talking about how you have five generations of workers at Accenture. How do you cater to them? I mean as you said you want, coming to work everyday whether it's your first day or your, you know you've been there for 20 years to be a glorious experience. How do you make sure you are taking this empathetic people centered approach for each of these different kind of workers? >> I call it with my team sweating the small stuff and that's not worrying about bureaucracy and process. That's worrying about the individual. So we do have five generations working side by side both serving our clients and serving our business and the most important thing is truly understanding what's most important to the human? Not what generation they're coming from or were born during. >> Those five generations have a lot in common before they come to work they typically watch the news. They may have read the Wall Street Journal. They may have consumed content on YouTube. They may have looked at Twitter, they may have subscribed to Netflix. They may have asked Alexa or Cortana for advice and guidance. When they get to work what changes? It has to feel and be exactly like that and Ellen and I will be creating the services that do that so that it feels welcoming and sticky and so I want to stay. Which is really important in the modern enterprise when there's so much opportunity out there for the human. >> And to go back to the question you were asking and talking about driving out of Heathrow and not seeing humans. I think the thing that CEOs really need to understand is that employees are excited about the opportunity that technology is going to bring to their job. In fact we did a piece of research that we launched earlier this year that says over 80% of people are excited about how technology is going to improve their work. Because of the very reason they Google things at home. They use you know Amazon or whatever to go buy their things that they need for themselves. And so they see the opportunity and it's companies and organization's roles to tap into that excitement and really change the future of work. >> Here's a really good example of that. So there is nothing more boring than security training. >> I agree. >> So inside Accenture why don't you subscribe to a TV show that looks like 24. The TV show, the 24 that's episodic. We drop a season that has actors portraying the implications of if you don't get your security rights as a human and as an individual. It gets great ratings, great viewing figures. So it's ratings and viewing figures that tell us we're communicating with our employees. That's what being in the new is about. >> And that's really innovative. I was going to ask you about training and education because the example of Heathrow you don't see the data scientist the person who's putting paper and glue and doesn't have the skill sets of that data scientist. So I know Accenture big on training, education. You guys invest a lot there. My question is as you span five generations is the training regimen... Sort of how do you tailor it to those different needs? >> Well what we're finding frankly is that all of our people really want to stay relevant to their clients and to their people and so what we did was we worked together to democratize our learning platforms. So you no longer have to be tapped on the shoulder and invited to take training. We've enabled our training platform to be available real time and on demand and when you create a culture in which people are hungry to learn. You see some amazing things happen and we can see on our dashboard that Andrew's team has built all of the trending topics on any given day in any day of the week. That our people are doing through self learning. >> And that's shared and open? So there's a little bit of game theory going on here. >> Because transparency builds trust. Absolutely. >> What you want, where you want, when you want it, why you want it and at the rate you want it. Because everybody has different sets of needs. Well they'll stay relevant, they'll stay liquid and they'll be able to keep up with modern technology because we're a technology business in our case. That's wat training is about and they'll be more effective and they'll have fun and they'll have job security and none of that is threatened by other aspects of technology. >> But one point to add to that because I think Andrew's brilliance doesn't always fully come through is that everything that he's built for our people has a social component it. So for example on the learning platform I can recommend different learning experiences that I've gone through to my colleagues, to my peers and when you see the interaction among the people and how you can create real change. With just each other, without driving change top down. That social experience really changes the whole dynamic in an organization. >> I think one of the things that Ellen and I have had a chance to leave our mark on is that we have both democratized training and we socialize training as well and both are really important. >> You talked about, oh sorry. Go ahead please. >> You said you hire a 100,000 people a year and at a time where the skill set is really changing. Because so many of the repetitive automate the task are being automated and so really the skillsets that we need are more empathetic, more creative. How are you finding those people? Particularly at a time we really are in a war for talent? >> We talk about discovering new sources of talent rather than attracting talent to us. So we really try to go digital where the people are. So that's where people are, that's where we go look for them but the most important thing is that we are investing in new skilling our people. So we're not just hiring people in with new skills we're giving all of the 442,000 humans at Accenture the opportunity to continue to keep themselves relevant. >> So rather than coders and testers we now have data scientists and I do think we have new talent sources inside and outside the company. So I'm delighted to say that 54% of my team in China happen to be ladies and there's a really good solid data science gene in them which is helping us with our analytics and surfacing insights in a way that my organization didn't used to do. So we've tapped into new talent, many of them we already had it's just how you free them to do the job that they are very very capable of doing. >> Well Andrew, Ellen thank you so much for coming on the CUBE. It was great to have you here. >> Thanks for having us. >> Great to see you guys. >> I'm Rebecca Knight for Dave Vellante, we will have more from Service Now Knowledge 18 just after this.

>> Narrator: Live from Las Vegas, it's theCUBE, covering AWS re:Invent 2017. Presented by AWS, Intel and our ecosystem of partners. >> Welcome back, we are live here in Las Vegas, located at the Sands. Day three of our coverage here at re:Invent. AWS starting to wrap things up, but still, I think, making a very major statement about the progress they're making in their making in their market. 45,000 plus attendees here, thousands of exhibitors and exhibit space being used here in hundreds of thousands of square footage. Sort of a reflection of the vibrancy of that market. I'm with James Kobielus, who's the lead analyst at Wikibon and we're joined, once again, second appearance on theCUBE in one day, how 'bout that for Nayaki Nayyar, who is the President of Digital Services Management at BMC. Glad to have you back, we appreciate the time. >> Thank you, John, thank you, Jim. Great to be here and I'm becoming a pro at this, right? >> You are. >> My second time of the day. >> We'll punch your card and you win a prize by being on theCUBE more than once a day. >> Twice in four hours, I mean, that's a pretty good track record. >> We'll pick up your toy, you know. >> Tell me about, first off, just your thought about the show in general. I mean, you've been in this environment for some time now, but I'm kind of curious what you think about what you're seeing here and the sense of how this thing's really taking off. >> So, first of all, it's just the energy, the vibe, the fun that we're having here is just amazing. But, I do want to drop to the keynote that Andy did yesterday, it's just phenomenal the pace at which AWS is innovating. Just to be releasing over 1300 features in a year, that is phenomenal. >> James: I think he said innovations in a year. >> Features a year. >> Did he say features, okay. >> Yeah, I think so. But, independent of that, I'm just saying the pace at which, and their model of new stuff that they're bringing to the market is just phenomenal. For customers like us, vendors, it's just phenomenal. >> We hear a lot about, I mean, it's the buzzword, digital transformation and all that. So, what does it really mean to service? What transformation is happening in that, what is that pushing you on that side of the fence to have to be thinking about now? >> You said the word, digital, and sometimes it's very hyper-used. And what we have done at BMC, since our core is service management, we have defined what service management looks like for our customers in this digital age. And we have defined it, because we were primarily in I.T. service management for the last 10-15 years, the future of the service management in this digital world is what we call cognitive service management. Where service management is no longer just reactive, it is proactive and it is also a conversational through various agents like chatbots, or Alexa or virtual agents. So, it's a complete transformation that we are experiencing and we are driving most of that change for our customers right now. >> And, of course, the word cognitive signals the fact that there's some artificial intelligence going on behind the scenes, possibly to drive that conversational UI. With that in mind, I believe that, at BMC, you are one of AWS's partners for Alexa for businesses, is that true? And you're bringing it into an I.T. service management context. That's sounds like an innovation, can you tell us more about that? >> Absolutely, so we announced partnership with AWS on multiple fronts. One of them is with Alexa, Alexa for Business, where we do integrate with Alexa for providing that end user experience. So, Alexa was known for consumer world, my son used it all the time. >> Tell me the temperature? >> But now, we are looking at how we could bring it into the enterprise world, especially to provide service to all employees. So that, you don't actually have to send an email or pick up the phone to call a service agent, now you can actually interact with Alexa or a chatbot to get any service you need. So that's what we call omni-channel experience for providing that experience for end users, employees, customers, partners, anyone. >> So, do you have, right now, any reference customers, it's so new? Or, can you give us a sense for how this capability is working in the field in terms of your testing? Do business people understand, or are they comfortable, with using essentially a consumer appliance as an interface to some serious business infrastructure? Like, being able to report a fault in a server, or whatnot. There's a risk there of bringing in a technology, like a consumer technology, before it's really been accepted as a potential business tool. Tell us how that's working. >> That's a very interesting. We are actually seeing a very fast pace at which customers are adopting it. As we speak, I have three customers I'm working with right now, who not only wants to use a chatbot, or a virtual agent, for providing service, not just to employees but to the end customers, also want to use Alexa inside their company for providing service to their employees. So, it's starting the journey, we already have the integration that is working with Alexa. Customers have gotten very excited about it, they're doing POCs, they're starting their journey. I think in the next couple of years, we'll see a huge uptake with customers wanting to do that across the board. >> Well, give me an example, if I'm working and I need to go to Alexa Business, how deep can I go? What kind of problems can be solved? And then, at what point where does that shut off and then we trip over to the human element? >> James: Don't forget where the A.I. fits in to the picture. If you could just have a little bit of the plumbing, not too much. >> So, let me give you like two segments, one is the experience through Alexa, the second one is, where does deep learning get embedded into the process. So, usually every company has level one, level two service desk agents who are taking the calls, are responding to emails for resetting passwords or fixing foreign issues, laptop issues. So, that level one, level two service desk process is what is being replaced through a chatbot or an Alexa. So, now you can take the routine kind of a task away from having a human respond to it, you can have Alexa or a chatbot respond, do that work. The second piece, for high-complex scenarios, is where it switches. So, being able to automatically switch between an Alexa to a live agent, is where the beauty comes in and how we handle the transition. It has all the historical interaction through the whole journey for the customer. >> But then, Alexa forwards any information it has gained from the conversations- >> That interaction history we call it. >> To a human being who takes it to the next step. >> Nayaki: So when I- >> Can a human kick it back to Alexa at some point? >> No, no, we haven't seen that go back. It's usually, level one, level two is where Alexa takes care and then level three is where the human takes care and goes forward. Now, the second piece, the A.I.-ML piece. In a service management, there are a lot of processes that are very, I would say, routine and very manual. Like, every ticket that comes in, customers have millions of tickets that come in on a periodic basis. Every ticket that comes in, how you assign the ticket to the right individual, log the ticket and categorize the ticket is a very labor intensive and expensive process. So, we are embedding deep learning capabilities into that so we can automate, customers can automate all of those. >> James: Natural language processing, is that? >> With NLP embedded into it. Now, customers can choose to use an NLP engine of their choice, like Watson, or Amazon, or Cortana. And then, that gets fed back into the service management process. >> In fact, that's consistent with what AWS is saying about the whole deep learning space. They are agnostic as to the underlying deep learning framework you use to build this logic, whether it be TensorFlow or MXNet, or whatever. So, what you're saying is very consistent with that sort of open framework for plugging deep learning, or A.I., into the, in this case, the business application. Very good. So, developers within your customer base, what are you doing, BMC, to get developers up to speed on what they'll need to do to build the skills to be able to drive this whole service management workflow? >> So, all this work that we're doing with, what we call these cognitive services, they're all micro services that we are built into our platform. That, not only we are using in our own applications, like in Remedy, like in, what we call digital workplace, but also we have made it available for all the developers, partners, ecosystems, to consume it in their own applications. Just like what Amazon is doing with their micro services strategy, we have micro services for every one of these processes that developers can now consume and build their own special use cases, or use cases that are very unique to their business or to their customers. >> So who, I mean we were talking about this before we started the interview, about invent versus innovation, so, on the innovation side, what's driving that? I mean, are these interactions that you're having with customers and so you're trying to absorb whatever that input is, that feedback? Or, are you innovating almost in a vacuum, or in space a little bit, and are providing tools that you think could get traction? >> No, in fact, no, we are not just dreaming in our labs and saying, "This is what we should go do." (laughing) >> James: Dreaming in our labs. >> That's not where the driver is. What's really happening, independent of the industry, you pick any industry like telcos or financial industry, any industry is going through a major transformation where they are under competitive pressure to provide a service at the highest efficiency, highest speed, at the lowest cost. So if I'm a bank, or if I'm a telco, when a customer calls me and they have an issue, the pace at which I provide the service, the speed, and the cost at which I provide that service, and the accuracy at which I provide that service, is my competitive advantage. So, that is what is actually driving the innovations that we are bringing to market. And, all the three things that I talked about, end user experience through bots or through virtual agents, how we are automating the processes inside the service management, and how we are also providing it for the developers. All these three, create a package for our customers in every one of those industries, to address the speed, the efficiency and the cost for their service management. >> John: Go ahead James. >> At this show, AWS, among their many announcements that are building on their A.I., they have a new product called, and it's related to this, the accuracy, it's called Amazon Comprehend. Which is able to build on Polly, their NLP, their Natural Language Processing, to be able to identify in a natural language, entities like, "Hey, my PC doesn't work "and I think it's the hard drive," those are entities. But, also identify sentiment, whether the customer is very angry, mildly miffed, and so forth. Conceivably, you could use, or your customers could use that information in building out skills that are more fine-grained in terms of handing off to level two or level three support, "Okay, we've identified with a high degree of confidence "that the problem might reside in this particular component "of the system, the customer is really out of joint, "you need to put somebody on this right away." So forth and so on. Any thoughts about possibly using this new functionality within the context of Alexa for Business as you were deploying it at BMC? In the future? Your thoughts? >> Absolutely, in fact that was what I was very excited about that, when they announced that. You know, in an NLP, NLP has been around for many years now and there's been a lot of experiments around NLP. >> The first patent for NLP was like in the late '50s. >> But the maturity of NLP now, and the pace at which, like Amazon, they're innovating is just phenomenal. And the real beauty of it would be, when an NLP engine can really become intelligent when it can understand the sentiment of the customer, when the customer is saying something, it should detect that the customer is angry, happy, or on the edge. We are not there yet, I'm really excited to see the announcements from AWS on the Comprehend side. If they really can deliver on that understanding sentiment, I think it would be phenomenal. >> I don't want to get us off the tracks, but it's a fascinating point. Because, as you know words, in a static environment can be misinterpreted one of 50,000 ways. So, how do you get this A.I. to apply to emotional pitch, tone, agitation? How do you recognize that? >> That is where NLP, the maturity of an NLP, is what's gonna be game changing in the long term. For it to be able to know what the underlying sentiment. >> Anger, excitement, joy, despair, I mean, all those things. "I've had enough," can be said many different ways. >> And that's when we'll switch to a live agent, if it's not able to do it, we will quickly switch to a live agent. (laughing) >> The bot gives up, right? (laughing) >> Or is it emotion threshold where a human being might be the best immediate front-line support. >> Just curious, it's fascinating. Well, thank you for the time, we certainly appreciate that. And, we promise, this'll be it for the day. (laughing) All right, no more CUBE duty. But, we certainly wish you all the best down the road. And, like you, I think we've certainly seen, and have a deeper appreciation for what's happening in this marketplace with what we've seen here this week. It was extraordinary. >> Fascinating. >> Thank you, John, it was a pleasure. And really excited to have two CUBE interviews in a day. >> John: How 'bout that? >> But, I think it's a great forum for us to get our message out and get the world to know what we are doing as BMC and the innovations we're beginning. >> We're excited to talk to real innovators in the business world, so, all power to you. >> Thanks for the time. >> Thank you. >> Nice to meet you. Back with more, we are live here at re:Invent AWS in Las Vegas. Back with more live here on theCUBE right after this break. (upbeat music)

>> Narrator: Live from Las Vegas, it's the Cube, covering VMWorld 2017. Brought to you by VMWare and its ecosystem partners. (bright music) >> Hi, I'm Stu Miniman with the Cube, here with my guest host, Justin Warren. Happy to have a returning Cube alum, but in a different role then we had. It's been a few years. Tal Klein, who is the author of The Punch Escrow. >> Au-tor, please. No, I'm just kidding. (laughing) Tal, thanks so much for joining us. It's great for you to be able to find time to hang out with the tech geeks rather than all the Hollywood people that you've been with recently. (laughing) >> You guys are more interesting. (laughing) >> Well thank you for saying that. So last time we interviewed you, you were working for a sizable tech company. You were talking about things like, you know, virtualization, everything like that. Your Twitter handle's VirtualTal. So how does a guy like that become not only an author but an author that's been optioned for a movie, which those of us that, you know, are geeks and everything are looking at, as a matter of fact, Pac Elsiger this morning said, "we are seeing science fiction become science fact." >> That's right. >> Stu: So tell us a little of the journey. >> Yeah, cool, I hope you read the book. (laughing) I don't know, the journey is really about marketing, right? Cause a lot of times when we talk about virtual, like, in fact last time I was on the Cube, we were talking about the idea that desktops could be virtual. Cause back then it was still this, you know, almost hypothetical notion, like could desktops be virtual, and so today, you know, so much of our life is virtual. So much of the things that we do are not actually direct. I was watching this great video by Apple's new augmented reality product, where you sit in the restaurant and you look at it with your iPad, and it's your plate, and you can just shift the menu items, and you see the menu items on your plate in the context of the restaurant and your seat and the person you're sitting across from. So I think the future is now. >> Yeah, it reminds of, you know, the movie Wall-E, the animated one. We're all going to be sitting in chairs with our devices or Ready Player One, you know, very popular sci-fi book that's being done by Speilberg, I believe. >> Yes, yeah, very exciting. >> Tell us a little bit about your book, you know, we talked, when I was younger and used to read a lot of sci-fi, it was like, what stuff had they done 50 years ago that now's reality, and what stuff had they predicted, like, you know, we're going to go away from currency and go digital currency, and it's like we're almost there. But we still don't have flying cars. >> Yeah, we're, I mean, the main problem with flying cars is that we need pilots. And I think actually we're very close to flying cars, cause once we have self-driving vehicles and we no longer need to worry about it being a person behind the joystick, then we're in really good shape. That's really the issue, you know, the problem with flying cars is that we are so incompetent at driving and or flying. That's not our core competency, so let's just put things that do understand how to make those things happen and eliminate us from the equation. >> Everything is a people problem. >> Yeah, so when I wrote the book, Punch Escrow, Punch Escrow, (laughing) when I wrote the book, I really thought about all the things that I read growing up in science fiction, you know, things like teleportation, things like nanotechnology, things like digital currency, you know, how do we make those, how do we present those in a viable way that doesn't seem too science fictiony. Like one of the things I really get when people read the book is it feels really near-future, even though it's set like 100 plus years in the future, all the concepts in it feel very pragmatic or within reach, you know? >> Yeah, absolutely. It's interesting, we look at, you know, what things happen in a couple of years and what things take a long time. So artificial intelligence, machine learning, it's not like these are new concepts, you know? I read a great book by, you know, it was Isaacson, The Innovators. You go back to like Aida Lovelace, and the idea of what a machine or computer would be able to do. So 100 years from now, what's real, what's not real? We still all have jobs or something? >> We have jobs but different. Remember, I don't know if you're a historian, but back in the industrial age, there was a whole bunch of people screaming doom and gloom. In fact, if we go way back to the age of the Luddites, who just hated machines of any kind. I think that in general, we don't like, you know, we're scared of change. So I do think a lot of the jobs that exist today are going to be done by machines or code. That doesn't mean the jobs are going away. It means jobs are changing. A lot of the jobs that people have today didn't exist in the industrial age. So I think that we have to accept that we are going to be pragmatic enough to accept the fact that humans will continue to evolve as the infrastructure powering our world evolves, you know? We talk about living in the age of the quantified self, right? There's a whole bunch that we don't understand how to do yet. For example, I can think of a whole industry that tethers my FitBit to my nutrition. You know, like there's so much opportunity that for us to say, oh that's going to be the end of jobs, or the end of innovation or the end of capitalism, is insane. I think this just ushers in a whole new age of opportunity. And that's me, I'm just an optimist that way, you know. >> So the Luddites did famously try to destroy the machines. But the thing is, the Luddites weren't wrong. They did lose their jobs. So what about the people whose jobs are replaced, as you say net new, there's a net new number of jobs. But specific individuals, like people who manufacture cars for example, lose their jobs because a robot can do that job safer and better and faster than a human can do it. So what do we do with those humans? Because how do we get people to have new jobs and retrain themselves? >> I address some of these notions in the book. For example, one of the weird things that we're suffering from is the lack of welders in society today, cause welding has become this weird thing that we don't think we need people for, so people don't really get trained up in it because, you know, machines do a lot of welding but there's actually specialty welding that machines can't do. So I think the people who are really good at the things that they do will continue to have careers. I think their careers will become more niche. Therefore they'll be able to create, to demand a higher wage for it because almost like a carpenter, you know, a specialist carpenter will be able to earn a much higher wage today by having fewer customers who want really custom carpentry versus things that can be carved up by a machine. So I think what we end up seeing is that it's not that those jobs go away. It's they become more specialized. People still want Rolls Royces. People still want McLarens. Those are not done by machines. Those are hand-made, you know? >> That's an interesting point, so the value of something being hand-made becomes, instead of it being a worse product, it's actually- >> Tal: That's a big concept in the book. >> Oh okay, right. >> A big concept in the book is that we place a lot of value on the uniqueness of an object. And that parlays in multiple ways. So one of the examples that I use in the book is the value of a Big Mac actually coming from McDonald's. Like, you can make a Big Mac. We know the recipe for a Big Mac. But there is a weird sort of nacent value to getting a Big Mac from McDonald's. It's something in our brain that clicks that tethers it to an originality. Diamonds, another really good example. Or you know, we know there's synthetic diamonds. We still want the ones that get mined in the cave. Why? We don't know. Right, they're just special. >> Because De Beers still has really good marketing. (laughing) >> So I think there's- >> That's interesting, so the concept of uniqueness, which again comes to scarcity and so on. As an author, someone who is no doubt, signed a lot of his book, that means that that book is unique because it's signed by the author, unlike something which is mass produced and there is hopefully thousands and thousands of copies that you sell. >> Going into this, I actually thought about that a lot. And that's why I've created like multiple editions of the book. So like the first 500 people who pre-ordered it, they get like a special edition of the book that's like stamped and all this kind of stuff. I even used different pens. (laughs) I appreciate that because I'm also a collector. I collect music, I collect books. And you know, so I see those aspects in myself. So I know what I value about them, you know? >> And the crossover between music and books is interesting. So as someone who has a musical background, I know that there's a lot of musicians who'll come out with special editions, and you know, because this is an age where we can download it. You can download the book. Do you think there is something, is there something that is intrinsic to having a physical object in a virtual world? >> I think to our generation, yes. I'm not so sure about millennials, when they grow up. But there are, for example, I'm going to see U2 next week, I'm very lucky to see that. But part of the U2 buying experience, to get access to the presale, you need to be part of their fan club. To be a part of their fan club, you need to get, you get like a whole bunch of limited edition posters, limited edition vinyl, and all this kind of stuff. So there's an experience. It's no longer just about going to see U2 at a concert. There's like the entire package of you being a special U2 fan. And they surround it with uniqueness. It's not necessarily limited, but there's an enhanced experience that can't just be, it's not just about you having a ticket to a single concert. >> Justin: Yeah, okay. >> I'm curious, the genre, if you'd call it, is hard science fiction. >> Yes. >> The challenge with that is, you know, what is an extension of what we're doing, and what is fiction? And people probably poke at that. Have you had any interesting experience, things like that? I mean, I've listened to a lot of stuff like Andy Weir, like let the community give feedback before he created the final The Martian. (laughing) But so yeah, what's it like, cause we can, the geeks can be really harsh. >> Yes, I've learned from my Reddit experience that, so what's really funny about it is the first draft of this novel was hard as nails. It was crazy. And my publisher read it, and it would have made all the hard science fiction guys super happy. My publisher read it, he was like, you've written a really great hard science fiction book, and all five people who read it are going to love it. (laughing) You know, but like, I came here with my buddy Danny. He couldn't even get through the first three pages of it. He's like, he wanted to read it. So part of working through the editorial process is saying, look, I care a lot about the science because one of my deep goals is to write a STEM-oriented book that gets people excited about technology and present the future as not a dystopian place. And so I wanted the science to be there and have a sort of gravity to the narrative. But yeah, it's tough. I worked with a physicist, a biologist, a geneticist, an anthropologist, and a lawyer. (laughs) Just to try to figure out, how do we carve out, you know, what does the future look like, what does the evolution of each individual sciences, we talked about the mosquitoes, right? You know, we're already doing a lot of crazy stuff with mosquitoes. We're modifying them so that the males mate with females that carry the Zika virus, you know, give birth to offspring that never reach maturity. I mean, this is just crazy, it's science fiction. And now that they're working on modifying female mosquitoes into vaccine carriers instead of disease carriers. I mean, this is science fiction, right? Like who believes this stuff? It's crazy. >> Christopher is amazing. >> Yeah, I've loved, there's been a bunch of movies recently that have kind of helped to educate on STEM some, you know, Martian got a lot of people excited, you know, Hidden Figures, the one that I could being my kids that are teenagers now into it and they get excited, oh, science is great. So the movie, how much will you be involved? You know, what can you share about that experience, too, so far? >> It's been, it's very surreal. That's the word is use to describe it, the honest, god's honest truth, I mean. I've been very lucky in that my representation in Hollywood is this rock-solid guy called Howie Sanders. And he's this bigger-than-life Hollywood agent guy. He's hooked me up, we've made a lot of business decisions that we're focused less on the money and more on the team, which is nice to be, like when you're in your 40s and you're more financially settled, you're not in the kind of situation where you might be in your 20s and just going to sign the first deal that people give you. So we really focused on hooking up with like the director, James Bovin is, you know, he's the guy who co-created Flight of the Concords. He did the Muppets movie, you know, Alice Through the Looking Glass. Really professional guy but also really understands the tone of the book, which is like humorous, you know, kind of sarcastic. It's not just about the technology. It's also about the characters. Same thing with the production team. The two producers, Mandeville Productions, I was just talking to Todd Lieberman, and we're talking about just what is augmented reality, like how does it look like on the screen? So I'm not- >> It's not going to look like Blade Runner is what I'm hearing. >> (laughs) I don't know. It's going to look real. I imagine, I don't know, they're going to make whatever movie they're going to make, but their perspective, one of the things we talked about is keeping the movie very grounded. Like you know, one of the big questions they ask first going into it is before we even had any sort of movie discussions is like is this more of like a Looper, Gattica, or District Nine, or is it more like The Fifth Element, you know, I mean, is it like, do you want it to be this sort of grounded movie that feels authentic and real and near future or do you want this to be like completely alien and weird and out of it. And the story is more grounded. So I think a lot, hopefully what we display on the screen will not feel that far away from reality. >> Okay, yeah. >> You do marketing in your day job. >> I do. >> I'm curious as you look at this, kind of the balance of educating, reaching a broad audience, you have passion for STEM, what's your thoughts around that? Is it, I worry there's so much general, like television or things like that, when I see the science stuff, it like makes me groan. Because you know, it's like I don't understand that. >> I am the worst, because I got a security background too, so that's the one I get scrambled on. The war, I mean, like. >> Wait, thank goodness I updated my firewall settings because I saved the world from terrorists. >> Hang on, we're breaking through the first firewall. Now we're through the second firewall. (laughing) Now we're going through the third firewall, like 15 firewalls. And let me upload the virus, like all that stuff. It's difficult for me. I think that, you know, hopefully, there's also a group in Hollywood called the Hollywood Science and Entertainment Exchange. And they're a group of scientists who work with film makers on, you know, reigning things in. And film makers don't usually take all their advice, i.e. Interstellar, (laughing) but you know, I think (laughing) in many cases there's some really good ideas that come to play into it that hopefully bring up, like I think Jarvis for example, in Iron Man or the Avengers is a really cool implementation of what the future of AI systems might be like. And I know they used the Hollywood Science Exchange to figure out how is that going to work? And I think the marketing aspect is, you know, the reason I came up with the idea for this book is because my CEO of a company I used to work for, he had this whole conversation about teleportation, like teleportation was impossible. And he's like, it's not because the science, yes, the science is a problem right now, but we'll get over it. The main issue is that nobody would ever step foot into a device that vaporizes them and then printed them out somewhere else. And I said, well that's great, cause that's a marketing problem. (laughing) >> Yeah, you're dead every time you do it. But it's the same you, I can't tell the difference. >> Well, you say you're dead, I'm saying you're just moving. (laughing) >> Artificial intelligence, you know, kind of a big gap between the hype to where we need to go. What's your thoughts on that space in general? >> I think that we have, it's a great question because I feel like that's a term that gets thrown around a lot, and I think as a result it's becoming watered down. So you've this sort of artificial intelligence that comes with like, you know, Google building an app that can beat the world's best Go player, which is a really, really difficult puzzle. The problem is, that app can do one thing, and that's play Go. You put in it a chess game, and it's like I don't know what's going on. >> It's a very specialized kind of intelligence, yeah. >> Now with Open AI, you know, they just had some pretty interesting implementations where they actually played video games with a real live competition and won. Again, you know, but without the smack talk, which really I think would add a lot. Now you got to get an AI to smack talk. So I think the problem is we haven't figured out a really good way of creating a general purpose AI. And there's a lot of parallels to the evolution of computing in general because if you look at how computers were before we had general purpose operating systems like Unix, every computer was built to do a very, very specific function, and that's kind of what AI is right now. So we're still waiting to have a sort of general purpose AI that can do a lot of specialized activities. >> Even most robots are still very single-purpose today. >> That's the fundamental problem. But you're seeing the Cambridge guys are working on sort of the bipedal robot that can do lots of things. And Siri's getting better, Cortana's getting better, Watson's getting better, but we're not there. We still need to find a really good way of integrating deep knowledge with general purpose conversational AI. Cause that's really what you need to like, Stu, what do you need? Here, let me give it to you, you know? >> Do you draw a distinction between AI that's able to simply sort of react as a fairly complex machine or something that can create new things and add something? >> That's in the book as well. So the fundamental thing that I don't think we get around even in the future is giving computers the ability to actually come up with new ideas. There's actually a career, the main job of the protagonist in the book, his job is a salter. And his job is to salt AI algorithms to introduce entropy so they can come up with new ideas. >> Okay, interesting. >> So based off the sort of chaos theory. >> Like chaos monkey, right? >> Yeah. And that's really what you're trying to do is like, okay, react to things that are happening because you can't just come up with them on their own. There's a whole, I don't want to bore you, but there's a whole bunch of stuff in the book about how that works. >> It's like hand-carving ideas that are then mass produced by machines. >> Yeah, I don't know if you guys are going to have Simon Crosby on here, he's kind of like an expert on that. He was the Dean of Kings College, which is where Turing came from. So he really knows a lot about that. He's got a lot of strong ideas about it. But I learned a lot from him in that regard. There's a lot of like, the snarky spirit of Simon Crosby lives on in my book somewhere. But he's just funny cause he's, coming from that field, he immediately sees a lot of BS right off the bat, whenever anybody's presenting. He's got like the ability to just cut through it. Because he understands what it would actually take to make that happen, you know? So I tried to preserve some of that in the book. >> That is refreshing in the tech industry. >> So Tal, I need to let you, you know, wrap this up. Give us a plug for the book, tell us, when are we going to be able to see this on the big screen? >> I don't know about the big screen, but the Punch Escrow is now available. You can get it on Amazon, Barnes and Noble, anywhere books are sold. It's been optioned by Lionsgate. The director attached to it is James Bovin, production team is Mandeville Productions. I'm very excited about it. Go check it out. It's a pretty quick read, reads like a technothriller. It's not too hard. And it's fun for the whole family. I think one of the coolest things about it is that the feedback I've been getting has been that it really is appealing to everybody. I've got mother-in-laws reading it, you know, it's pretty cool. Initially I sold it, my initial audience is like us, but it's kind of cool, like, Stu will finish the book, he'll give it to, you know, wife, daughter, anything, and they're really digging it. So it's kind of fun. >> Justin: Thanks a lot. >> Tal Klein, really appreciate you coming. Congratulations on the book, we look forward to the movie. Maybe, you know, we'll get the Cube involved down the road. (laughing) >> And we're giving away 75 copies of it here at Lakeside booth, if you guys want to come. >> Tal Klein, author of The Punch Escrow, also CMO of Lakeside, who is here in the thing. But yeah, (laughing) a lot of stuff. Justin and I will be back with more coverage here from VMWorld 2017. You're watching the Cube. (bright music)

>> Announcer: Live from Las Vegas, it's the CUBE! Covering HPE Discover 2017. Brought to you by Hewlett Packard Enterprise. >> Hey, welcome back, everyone. We are live here in Las Vegas for SiliconANGLE Media's CUBE exclusive coverage of HPE Discover 2017. I'm John Furrier, my co-host, Dave Vellante. Our next guest is Kirk Bresniker, fellow and VP chief architect of Hewlett Packard Labs, and Natalia Vassilieva, senior research manager, Hewlett Packard Labs. Did I get that right? >> Yes! >> John: Okay, welcome to theCUBE, good to see you. >> Thank you. >> Thanks for coming on, really appreciate you guys coming on. One of the things I'm most excited about here at HPE Discover is, always like to geek out on the Hewlett Packard Labs booth, which is right behind us. If you go to the wide shot, you can see the awesome display. But there's some two things in there that I love. The Machine is in there, which I love the new branding, by the way, love that pyramid coming out of the, the phoenix rising out of the ashes. And also Memristor, really game-changing. This is underlying technology, but what's powering the business trends out there that you guys are kind of doing the R&D on is AI, and machine learning, and software's changing. What's your thoughts as you look at the labs, you look out on the landscape, and you do the R&D, what's the vision? >> One of the things what is so fascinating about the transitional period we're in. We look at the kind of technologies that we've had 'til date, and certainly spent a whole part of my career on, and yet all these technologies that we've had so far, they're all kind of getting about as good as they're going to get. You know, the Moore's Law semiconductor process steps, general-purpose operating systems, general-purpose microprocessors, they've had fantastic productivity growth, but they all have a natural life cycle, and they're all maturing. And part of The Machine research program has been, what do we think is coming next? And really, what's informing us as what we have to set as the goals are the kinds of applications that we expect. And those are data-intensive applications, not just petabytes, exabytes, but zettabytes. Tens of zettabytes, hundreds of zettabytes of data out there in all those sensors out there in the world. And when you want to analyze that data, you can't just push it back to the individual human, you need to employ machine learning algorithms to go through that data to call out and find those needles in those increasingly enormous haystacks, so that you can get that key correlation. And when you don't have to reduce and redact and summarize data, when you can operate on the data at that intelligent edge, you're going to find those correlations, and that machine learning algorithm is going to be that unbiased and unblinking eye that's going to find that key relationship that'll really have a transformational effect. >> I think that's interesting. I'd like to ask you just one follow-up question on that, because I think, you know, it reminds me back when I was in my youth, around packets, and you'd get the buffer, and the speeds, and feeds. At some point there was a wire speed capability. Hey, packets are moving, and you can do all this analysis at wire speed. What you're getting at is, data processing at the speed of, as fast as the data's coming in and out. Is that, if I get that right, is that kind of where you're going with this? Because if you have more data coming, potentially an infinite amount of data coming in, the data speed is going to be so high-velocity, how do you know what a needle looks like? >> I think that's a key, and that's why the research Natalia's been doing is so fundamental, is that we need to be able to process that incredible amount of information and be able to afford to do it. And the way that you will not be able to have it scale is if you have to take that data, compress it, reduce it, select it down because of some pre-determined decision you've made, transmit it to a centralized location, do the analysis there, then send back the action commands. Now, we need that cycle of intelligence measurement, analysis and action to be microseconds. And that means it needs to happen at the intelligent edge. I think that's where the understanding of how machine learning algorithms, that you don't program, you train, so that they can work off of this enormous amount of data, they voraciously consume the data, and produce insights. That's where machine learning will be the key. >> Natalia, tell us about your research on this area. Curious. Your thoughts. >> We started to look at existing machine learning algorithms, and whether their limiting factors today in the infrastructure which don't allow to progress the machine learning algorithms fast enough. So, one of the recent advances in AI is appearance, or revival, of those artificial neural networks. Deep learning. That's a very large hype around those types of algorithms. Every speech assistant which you get, Siri in your phone, Cortana, or whatever, Alexa by Amazon, all of them use deep learning to train speech recognition systems. If you go to Facebook and suddenly it starts you to propose to mark the faces of your friends, that the face detection, face recognition, also that was deep learning. So that's a revival of the old artificial neural networks. Today we are capable to train byte-light enough models for those types of tasks, but we want to move forward. We want to be able to process larger volumes of data, to find more complicated patterns, and to do that, we need more compute power. Again, today, the only way how you can add more compute power to that, you scale out. So there is no compute device on Earth today which is capable to do all the computation. You need to have many of them interconnect together, and they all crunch numbers for the same problem. But at some point, the communication between those nodes becomes a bottleneck. So you need to let know laboring node what you achieved, and you can't scale out anymore. Adding yet another node to the cluster won't lead up to the reduction of the training time. With The Machine, when we have added the memory during computing architecture, when all data seeds in the same shared pool of memory, and when all computing nodes have an ability to talk to that memory. We don't have that limitation anymore. So for us, we are looking forward to deploy those algorithms on that type of architecture. We envision significant speedups in the training. And it will allow us to retrain the model on the new data, which is coming. To do not do training offline anymore. >> So how does this all work? When HP split into two companies, Hewlett Packard Labs went to HPE and HP Labs went to HP Ink. So what went where, and then, first question. Then second question is, how do you decide what to work on? >> I think in terms of how we organize ourselves, obviously, things that were around printing and personal systems went to HP Ink. Things that were around analytics, enterprise, hardware and research, went to Hewlett Packard Labs. The one thing that we both found equally interesting was security, 'cause obviously, personal systems, enterprise systems, we all need systems that are increasingly secure because of the advanced, persistent threats that are constantly assaulting everything from our personal systems up through enterprise and public infrastructure. So that's how we've organized ourselves. Now in terms of what we get to work on, you know, we're in an interesting position. I came to Labs three years ago. I used to be the chief technologist for the server global business unit. I was in the world of big D, tiny R. Natalia and the research team at Labs, they were out there looking out five, 10, 15, or 20 years. Huge R, and then we would meet together occasionally. I think one of the things that's happened with our machine advanced development and research program is, I came to Labs not to become a researcher, but to facilitate that communication to bring in the engineering, the supply chain team, that technical and production prowess, our experience from our services teams, who know how things actually get deployed in the real world. And I get to set them at the bench with Natalia, with the researchers, and I get to make everyone unhappy. Hopefully in equal amounts. That the development teams realize we're going to make some progress. We will end up with fantastic progress and products, both conventional systems as well as new systems, but it will be a while. We need to get through, that's why we had to build our prototype. To say, "No, we need a construction proof of these ideas." The same time, with Natalia and the research teams, they were always looking for that next horizon, that next question. Maybe we pulled them a little bit closer, got a little answers out of them rather than the next question. So I think that's part of what we've been doing at the Labs is understanding, how do we organize ourselves? How do we work with the Hewlett Packard Enterprise Pathfinder program, to find those little startups who need that extra piece of something that we can offer as that partnering community? It's really a novel approach for us to understand how do we fill that gap, how do we still have great conventional products, how do we enable breakthrough new category products, and have it in a timeframe that matters? >> So, much tighter connection between the R and the D. And then, okay, so when Natalia wants to initiate a project, or somebody wants Natalia to initiate a project around AI, how does that work? Do you say, "Okay, submit an idea," and then it goes through some kind of peer review? And then, how does it get funded? Take us through that. >> I think I'll give my perspective, I would love to hear what you have from your side. For me, it's always been organic. The ideas that we had on The Machine, for me, my little thread, one of thousands that's been brought in to get us to this point, started about 2003, where we were getting ready for, we're midway through Blade Systems C-class. A category-defining product. A absolute home run in defining what a Blade system was going to be. And we're partway through that, and you realize you got a success on your hands. You think, "Wow, nothing gets better than this!" Then it starts to worry, what if nothing gets better than this? And you start thinking about that next set of things. Now, I had some insights of my own, but when you're a technologist and you have an insight, that's a great feeling for a little while, and then it's a little bit of a lonely feeling. No one else understands this but me, and is it always going to be that way? And then you have to find that business opportunity. So that's where talking with our field teams, talking with our customers, coming to events like Discover, where you see business opportunities, and you realize, my ingenuity and this business opportunity are a match. Now, the third piece of that is someone who can say, a business leader, who can say, "You know what?" "Your ingenuity and that opportunity can meet "in a finite time with finite resources." "Let's do it." And really, that's what Meg and leadership team did with us on The Machine. >> Kirk, I want to shift gears and talk about the Memristor, because I think that's a showcase that everyone's talking about. Actually, The Machine has been talked about for many years now, but Memristor changes the game. It kind of goes back to old-school analog, right? We're talking about, you know, login, end-login kind of performance, that we've never seen before. So it's a completely different take on memory, and this kind of brings up your vision and the team's vision of memory-driven computing. Which, some are saying can scale machine learning. 'Cause now you have data response times in microseconds, as you said, and provisioning containers in microseconds is actually really amazing. So, the question is, what is memory-driven computing? What does that mean? And what are the challenges in deep learning today? >> I'll do the machine learning-- >> I will do deep learning. >> You'll do the machine learning. So, when I think of memory-driven computing, it's the realization that we need a new set of technologies, and it's not just one thing. Can't we just do, dot-dot-dot, we would've done that one thing. This is more taking a holistic approach, looking at all the technologies that we need to pull together. Now, memories are fascinating, and our Memristor is one example of a new class of memory. But they also-- >> John: It's doing it differently, too, it's not like-- >> It's changing the physics. You want to change the economics of information technology? You change the physics you're using. So here, we're changing physics. And whether it's our work on the Memristor with Western Digital and the resistive RAM program, whether it's the phase-change memories, whether it's the spin-torque memories, they're all applying new physics. What they all share, though, is the characteristic that they can continue to scale. They can scale in the layers inside of a die. The die is inside of a package. The package is inside of a module, and then when we add photonics, a transformational information communications technology, now we're scaling from the package, to the enclosure, to the rack, cross the aisle, and then across the data center. All that memory accessible as memory. So that's the first piece. Large, persistent memories. The second piece is the fabric, the way we interconnect them so that we can have great computational, great memory, great communication devices available on industry open standards, that's the Gen-Z Consortium. The last piece is software. New software as well as adapting existing productive programming techniques, and enabling people to be very productive immediately. >> Before Natalia gets into her piece, I just want to ask a question, because this is interesting to me because, sorry to get geeky here, but, this is really cool because you're going analog with signaling. So, going back to the old concepts of signaling theory. You mentioned neural networks. It's almost a hand-in-glove situation with neural networks. Here, you have the next question, which is, connect the dots to machine learning and neural networks. This seems to be an interesting technology game-changer. Is that right? I mean, am I getting this right? What's this mean? >> I'll just add one piece, and then hear Natalia, who's the expert on the machine learning. For me, it's bringing that right ensemble of components together. Memory technologies, communication technologies, and, as you say, novel computational technologies. 'Cause transistors are not going to get smaller for very much longer. We have to think of something more clever to do than just stamp out another copy of a standard architecture. >> Yes, you asked about changes of deep learning. We look at the landscape of deep learning today, and the set of tasks which are solved today by those problems. We see that although there is a variety of tasks solved, most of them are from the same area. So we can analyze images very efficiently, we can analyze video, though it's all visual data, we can also do speech processing. There are few examples in other domains, with other data types, but they're much fewer. It's much less knowledge how to, which models to train for those applications. The thing that one of the challenges for deep learning is to expand the variety of applications which it can be used. And it's known that artificial neural networks are very well applicable to the data where there are many hidden patterns underneath. And there are multi-dimensional data, like data from sensors. But we still need to learn what's the right topology of neural networks to do that. What's the right algorithm to train that. So we need to broaden the scope of applications which can take advantage of deep learning. Another aspect is, which I mentioned before, the computational power of today's devices. If you think about the well-known analogy of artificial neural network in our brain, the size of the model which we train today, the artificial neural networks, they are much, much, much smaller than the analogous thing in our brain. Many orders of magnitude. It was shown that if you increase the size of the model, you can get better accuracy for some tasks. You can process a larger variety of data. But in order to train those large models, you need more data and you need more compute power. Today, we don't have enough compute power. Actually did some computation, though in order to train a model which is comparable in size with our human brain, you will need to train it in a reasonable time. You will need a compute device which is capable to perform 10 to the power of 26 floating-point operations per second. We are far, far-- >> John: Can you repeat that again? >> 10 to the power of 26. We are far, far below that point now. >> All right, so here's the question for you guys. There's all this deep learning source code out there. It's open bar for open source right now. All this goodness is pouring in. Google's donating code, you guys are donating code. It used to be like, you had to build your code from scratch. Borrow here and there, and share in open source. Now it's a tsunami of greatness, so I'm just going to build my own deep learning. How do customers do that? It's too hard. >> You are right on the point to the next challenge of deep learning, which I believe is out there. Because we have so many efforts to speed up the infrastructure, we have so many open source libraries. So now the question is, okay, I have my application at hand. What should I choose? What is the right compute node to the deep learning? Everybody use GPUs, but is it true for all models? How many GPUs do I need? What is the optimal number of nodes in the cluster? And we have a research effort towards to answer those questions as well. >> And a breathalyzer for all the drunk coders out there, open bar. I mean, a lot of young kids are coming in. This is a great opportunity for everyone. And in all seriousness, we need algorithms for the algorithms. >> And I think that's where it's so fascinating. We think of some classes of things, like recognizing written handwriting, recognizing voice, but when we want to apply machine learning and algorithms to the volume of sensor data, so that every manufactured item, and not only every item we manufacture, but every factory that can be fully instrumented with machine learning understanding how it can be optimized. And then, what of the business processes that are feeding that factory? And then, what are the overall economic factors that are feeding that business? And instrumenting and having this learning, this unblinking, unbiased eye examining to find those hidden correlations, those hidden connections, that could yield a very much more efficient system at every level of human enterprise. >> And the data's more diverse now than ever. I'm sorry to interrupt, but in Voice you mentioned you saw Siri, you see Alexa, you see Voice as one dataset. Data diversity's massive, so more needles, more types of needles than ever before. >> In that example that you gave, you need a domain expert. And there's plenty of those, but you also need a big brain to build the model, and train the model, and iterate. And there aren't that many of those. Is the state of machine learning and AI going to get to the point where that problem will solve itself, or do we just need to train more big brains? >> Actually, one of the advantages of deep learning that you don't need that much effort from the domain experts anymore, from the step which was called future engineering, like, what do you do with your data before you throw machine learning algorithm into that? So they're, pretty thing, cool thing about deep learning, artificial neural network, that you can throw almost raw data into that. And there are some examples out there, that the people without any knowledge in medicine won the competition of the drug recognition by applying deep neural networks to that, without knowing all the details about their connection between proteins, like that. Not domain experts, but they still were able to win that competition. Just because algorithm that good. >> Kirk, I want to ask you a final question before we break in the segment because, having spent nine years of my career at HP in the '80s and '90s, it's been well-known that there's been great research at HP. The R&D has been spectacular. Not too much R, I mean, too much D, not enough applied, you mention you're bringing that to market faster, so, the question is, what should customers know about Hewlett Packard Labs today? Your mission, obviously the memory-centric is the key thing. You got The Machine, you got the Memristor, you got a novel way of looking at things. What's the story that you'd like to share? Take a minute, close out the segment and share Hewlett Packard Labs' mission, and what expect to see from you guys in terms of your research, your development, your applications. What are you guys bringing out of the kitchen? What's cooking in the oven? >> I think for us, it is, we've been given an opportunity, an opportunity to take all of those ideas that we have been ruminating on for five, 10, maybe even 15 years. All those things that you thought, this is really something. And we've been given the opportunity to build a practical working example. We just turned on the prototype with more memory, more computation addressable simultaneously than anyone's ever assembled before. And so I think that's a real vote of confidence from our leadership team, that they said, "Now, the ideas you guys have, "this is going to change the way that the world works, "and we want to see you given every opportunity "to make that real, and to make it effective." And I think everything that Hewlett Packard Enterprise has done to focus the company on being that fantastic infrastructure, provider and partner is just enabling us to get this innovation, and making it meaningful. I've been designing printed circuit boards for 28 years, now, and I must admit, it's not as, you know, it is intellectually stimulating on one level, but then when you actually meet someone who's changing the face of Alzheimer's research, or changing the way that we produce energy as a society, and has an opportunity to really create a more sustainable world, then you say, "That's really worth it." That's why I get up, come to Labs every day, work with fantastic researchers like Natalia, work with great customers, great partners, and our whole supply chain, the whole team coming together. It's just spectacular. >> Well, congratulations, thanks for sharing the insight on theCUBE. Natalia, thank you very much for coming on. Great stuff going on, looking forward to keeping the progress and checking in with you guys. Always good to see what's going on in the Lab. That's the headroom, that's the future. That's the bridge to the future. Thanks for coming in theCUBE. Of course, more CUBE coverage here at HP Discover, with the keynotes coming up. Meg Whitman on stage with Antonio Neri. Back with more live coverage after this short break. Stay with us. (energetic techno music)

(energetic music) >> Announcer: Live from San Francisco, it's the CUBE, covering DevNetCreate 2017, brought to you by Cisco. >> Okay, welcome back everyone. We're live in San Francisco for the inaugural event for Cisco's DevNetCreate, part of their DevNet classic developer community now extending out into the community of open source and cloud native and dev ops world, where applications and infrastructure coming together. It's the CUBE's exclusive two-days coverage. I'm John Furrier with my co-host, Peter Burris, head of WikiBon.com research. Our next guess is Ben Brown, CEO of Botkit out of Austin. Welcome to the CUBE. >> Thank you. >> So we were just chatting before we came on about how open source and how essentially using machines and humans workin' together, that there's a nice evolving machine learning marketplace for having new kinds of re-imagined recommendation engines. Chat bots that actually work. Integrations, again, back to software. >> Ben: Yeah. >> Tell us what you guys do, and how you guys relate to the cloud native, and what your role in open source is. >> Sure. So, it's real interesting, you know. Over the last couple of decades, an enormous amount of progress has been made on AI and machine learning, and NLP tools at these big companies like Google and Microsoft, and they are now giving that away, right? Like, it is free to use Facebook's top of the line machine learning algorithm. But, it's sort of a mystery and unfamiliar territory for developers coming from web or mobile. It's a black box that nobody's ever used before. So, what we do at Botkit is provide tools for developers, mostly developers who are coming from the web or coming from mobile development, and give them semantic, easy-to-use, and customized tools for building conversational user interfaces. And that can mean chat bots, that can mean voice skills for the Amazon Echo or Cortana or things like that, and give them these open source tools that allow them to take advantage of this exciting NLP and voice to text, and text to voice, and all that to build real software today. So what Botkit is is an open source library. It's free to use, it's MIT-licensed, so very liberally licensed, and it gives the developers tools like hearing and saying, right? So it's not about API calls and NLP classification and utterances and all that. It's about how does a robot think and act, and the metaphors around that. >> So I think of Botkit, I think of Webkit, these are languages of developers. So are you guys actually providing bot kits to create bots, or is it more of a platform? How do you guys describe what you do in open source, and how do you guys stay in business and keep the lights on? (laughter) >> Good question. Yeah, so we're a venture-backed startup. We have an open source toolkit and these kits, right? So if you want to build a Slack bot or a Facebook bot, we will give you 90% of the code that you need to bring that bot up and start talking. And that piece is all free. And we do that for Slack, for Facebook, for Twilio, for Cisco, for Alexa, and Microsoft, and a bunch of other platforms. And what we're really hoping is that we can instill in people, or sort of give to people a skill set that is akin to a web master, right? There's a bunch of skills that are interrelated that you need to actually bring this software to life. >> It saves time. It's tooling to save them time and to get acclimated and get working. >> Absolutely, absolutely. And then, on top of that, we have a set of power tools that sort of complete the process. Botkit, the open source piece is a software development library, but you also need deployment management and operational tools and content management and integrations and things like that. So that's where our business is. >> The class freemium model. The first hit's free, as they say. I'm sorry, that's a drug dealer model. (laughter) You get 'em in there but, as they scale, they're already successful, so it's not like you're gouging someone for not getting value out of it. >> Absolutely. I mean, we think about our business model in the same way a lot of other developer APIs do these days. >> Well, let's talk about some of those other developer APIs, because used to be that you used a language, then you would use a data management system, and then we start talking about web services, and that's all good. But where does this end up going, where you have a specialized toolkit for bots that you can add? You made up specialized toolkits for-- Amazon's talkin' about specialized toolkits for voice recognition that you can add. So is it just going to be in the interface? Are there going to be other classes of kits that developers are going to buy, and combine them together? Where do you see this going? >> Yeah, absolutely. I mean, it's just like, you know, all software development that came before, right? Nobody built every line of code for their mobile app. Nobody had to define what a button was for iOS. That was done at a higher level. In the same way, people who are building these conversational apps, or composing their own code with third party services, with open source software and all that combine. So there's really interesting stuff going on. Like I said, there's NLP tools coming down from all of these big players, but also from small players. There are tools like human takeover, which is like a new thing that didn't exist before. You're talking to a bot, you're starting to get angry, IBM Watson can identify your sentiment and say, "Oh, this person is frustrated. Let's bring in "a real operator." So there's third-party services to actually manage that kind of thing. >> Male: I want that job, by the way. (laughter) >> Only angry customers. >> Parachute me in just for the angry customers, yeah. >> Does not sound like a great job, yeah. And then there are almost every kind of component that you might imagine existing in the web stack is being specialized, or the mobile stack, is being specialized for conversational stuff, 'cause it's just different enough, right? So analytics and CRM and push notifications. >> I mean, you don't got to be a rocket scientist to figure out that voice is the hottest app in the market. I mean, you got Alexa, you got Siri, Google. I mean, voice interface is here. That's conversational, to your point. >> Ben: Yeah, yeah, absolutely. >> So now software will evolve. So that's kind of where you guys are betting, right? >> Yeah, absolutely. I mean-- >> John: Not just voice, but conversational software. >> Right. I mean, as I was just saying in my session here, I don't think anybody really wanted to sit down at a typewriter attached to a television. That was just a technology that we had at the time. Charles Babbage or whatever was dreaming about the thinking machine. So we're just much, much closer to that now, and we think that, over the next five or ten years, almost all software will have some sort of conversational element, whether that's in the app, does it mean you're on an Alexa skill that's embedded in the car, who knows? >> It's just never fight fashion, but this is a relevant fashion piece, where we see machine learning get rendered in AI and some of the cool applications like cars and voice and AI. So I got to ask you. You mention that all this free stuff's comin' out. It's like Christmas, it's like a kid in the candy store if you're a developer. How, in your opinion, has that shaped the developer ecosystems because, outside of the young kids who are just green and have no idea that it wasn't like this before. Back in the old days we used to actually program everything. Lot of cool stuff coming in for free from Google, from Facebook, in some cases Amazon. But I mean, what's the impact? >> I mean, people are able to take advantage of much more sophisticated technology much earlier on in the process, right? For the last 10 years, we've been talking about "Ah, machine learning, isn't it great if you're Google, "and you have ten trillion data points?" But nobody else has it, so it's not even worth talking about. But now, it's possible. You can start on day one, and start training your machine learning and models and things like that. And you don't have to actually invest in that technology. And voice to text, things like-- >> It's given them more speed to get to newer high, the higher functioning stuff. >> Yeah, absolutely. And it's bringing that kind of technology that was-- Most of AI has been in academia, right, and in research. And now, all of a sudden, it's on my kitchen counter. My kid now uses NLP technology every day, and that is a big-- Without the independent developers and smaller apps-- >> Well, the IoT's going to be in your wheelhouse, too. As more things get connected, the interfaces will be more human. >> Well, I was going to ask a question about that. Does this technology-- Today, the technology's mainly thought of part of the interface between the machine and the human being. Does this technology end up in between machines? >> Yeah, absolutely, sort of between bot. Inter-bot communication is very, very interesting. And then also-- So yes, absolutely. But also, like being on the other side of the human, or like between people, right? So customer service representatives using AI to have solutions suggested to them that they can pick from and things like that, like translating systems that suggest the response, so that you can use it if you so desire. And it makes your job easier, but it's not actually doing the transaction for you. It's really, really interesting, and that's nothing that the end user would actually experience themselves. >> Final question for you. Cisco has always been the king of networks. I mean, the internet was their wave, they rode that hard. We all know what they've done. Amazing, connecting routes together, routers, MLPS routers, PLSM routers, paths. I mean, they own that. Now they're moving up the stack, so now you're seeing this a gesture of going into the community, bringing apps and infrastructure together, to bring true dev ops. Kind of like what you're doing with your interfaces to software. What's your thoughts on this strategy. So, what's your take and reaction to what Cisco's doing? >> Clearly, the software layer is becoming more and more powerful and prevalent for people, and a bigger part of people's lives. So I think it makes tons of sense. And what Cisco's going to gain by opening these things up is the innovation of the community, like they were never going to be able to do the things that people are going to do with Spark APIs. And the way that things are connected and interwoven to each other, because I have a smart home, I have all these IoT devices. They don't talk to one another. I am left to weave them together. >> Peter: You mediate. >> I mediate, right. And I'm sophisticated enough to be able to do that. But if they're going to make it as easy as plug and play, and drag and drop, it's going to open up all sorts of exciting capabilities. >> It's the quote as saying waterfall versus agile, which one's faster? Agile. >> Well, but that's exactly why I asked the question about bots reconciling, or bots you having mediating between different devices or different machines, is that it could be a way that a human being can understand a set of instructions for how these things engage other stuff, so that it still looks like it's a set of human interfaces while, at the same time, it's operating at machine speed with machine efficiency. >> This is one of the most interesting things, particularly in the IoT space, that I've seen. There's an app called Thing-tin that is like a chat room for devices, and the way it works is like those devices emit machine messages and human readable messages, but they can talk to each other in machine language, but you can read it as a dialogue. >> That's SkyNet. That's SkyNet. I'm tellin' you, it's coming. >> Yeah, if SkyNet only turns your lights on and off. >> Machines talking to each other. "Hey, go kill that human over there." (laughter) >> Somebody's going to have to program it to kill first. >> We need algorithms to watch the algorithms. Great stuff. I think Cisco clearly, this is a move that they have to make. I've been following Cisco for many generations. Past 10 years, they were one of the first in smart homes, one of the first in smart cities, first with IoT, they called it Internet of Everything, the human network, social network. They had the pulse on all the right trends, but could not execute it, Peter. And, to your point, they'll never get there without open source, in my opinion. I think this is a signal that Cisco can do that. Now here's the key: They have the keys to the kingdom. It's called the network, and I think that making that programmable and extensible is a great strategy. >> Well, that's what they have to be able to do. They have to be able to make it, they have to make it obviously available to developers so they can create value on it. And that's something that they're still struggling to do. >> Yeah, so when he does the Botkit and does all this new creative activity going on, the network has to be adaptive and not get in the way, and not for the creativity of the developer, 'cause networking is hard. >> And that's a great point. And so much of what we do at Botkit is try to drain the complexity out of this complex stuff and make it available so that this enormous amount of power is available to the developer of today. >> Power to the developer, developers are in charge, developers are driving the network policy in a dynamic way. Congratulations on your success, great to chat with you. I'm going to check out Botkit. I already have some ways, Peter and I are already lookin' at it for the clips, and then the crowd chat virtually, great stuff, congratulations. Ben Brown, CEO of Botkit. Check it out, Botkit-dot-AI. We are soon to be replaced by bots here in the CUBE (laughter) with talking machines, but that's down the way, when SkyNet takes over. This is the CUBE here at the inaugural event for Cisco DevNetCreate. I'm John Furrier with Peter Burris. We'll be back after this short break. (electronic music) >> Hi, I'm April Mitchell, and I'm the senior--

>> Narrator: Live from Austin, Texas, it's the Cube covering South by Southwest 2017. Brought to you by Intel. Now, here's John Furrier. >> Hey, welcome back everyone. We're live here in the Cube coverage of South by Southwest. We're at the Intel AI Lounge, hashtag Intel AI. And the theme is AI for social good. So if you really support that, go in Twitter and use the hashtag Intel AI and support our cause. I'm John Furrier with Silicon Angle, I'm here with Robert Scoble, @Scobalizer. Just announcing this week the new formation of his new company, the Transformation Group. I've known Robert for over 12 years now. Influencer, futurist. You've been out and about with the virtual reality, augmented reality, you're wearing the products. >> Yup. >> You've been all over the world, you were just at Mobile World Con, we've been following you. You are the canary in the coalmine poking at all the new technology. >> Well, the next five years, you're going to see some mind blowing things. In fact, just the next year, I predict that this thing is going to turn into a three ounce pair of glasses that's going to put virtual stuff on top of the world. So think about coming back to South by Southwest, you're wearing a couple pairs of glasses, and you are going to see blue lines on the floor taking you to your next meeting or TV screens up here so I can watch the Cube while I walk around the streets here. It's going to be a lot of crazy stuff. >> So, we've been on our opening segment, we talked about it, we just had a segment on social good around volunteering, but what the theme is coming out is this counter culture where there's now this humanization aspect they called the consumerization of IT in the past. But in the global world, the human involvement now has these emersion experiences with technology, and now is colliding with impacting lives. >> Well, absolutely true. >> This is a Microsoft HoloLens first of all. And HoloLens puts virtual stuff on top of the real world. But at home, I have an HTC Vibe, and I have an Oculus Rift for VR, and VR is that immersive media. This is augmented reality or what we call mixed reality, where the images are put on top of the world. So I can see something pop off of you. In fact, last year at South by, I met a guy who started a company called iFluence, he showed me a pair of glasses and you look at a bottle like this and a little menu pops off the side of a bottle, tells you how much it is, tells you what's in the bottle, and lets you buy new versions of this bottle, like a case of it and have it shipped to my house all with my eyes. That's coming out from Google next year. >> So the big thing on the immersion the AR, you look at what's going on at societal impact. What are the things that you see? Obviously, we've been seeing at Mobile World Congress before Peelers came out, autonomous vehicles is game changing, smart cities, median entertainment, the world that we know close to our world, and then smart home. >> Oh yeah. >> Smart home's been around for years, but autonomous vehicles truly is a societal change. >> Yes. >> The car is a data center now. It's got experiences. And there's three new startups you should pay attention to, in the new cars that are coming in the next 18 months. Quanergy is one. They make a new kind of light R, a new sensor. In fact, there's sensors here that are sensing the world as I walk around and seeing all the surfaces. The car works the same way. It has to see ahead to know that there's a kid in front of your car, the car needs to stop, right. And Quanergy is making a focusable semiconductor light R, that's going to be one to watch. And then there's a new kind of brain, a new kind AI coming, and DeepScale is the one that I'm watching. The DeepScale brain uses a new third company called Luminar Technologies, which is making a new kind of 3D map of the world. So think about going down the street. This new map is going to know every pot hole, every piece of paint, every bridge on the street, and it's going to, the brain, the AI, is going to compare the virtual map to the real map, to the real world and see if there's anything new, like a kid crossing across the street. Then the car needs to do something and make a new decision. So 3D startups are going to really change the car. But the reason I'm so focused on mixed reality, is mixed reality is the user interface for the self-driving car, for the smart city, for the internet of things, the fields in your farm or what not, and for your robot, and for your drone. You're going to have drones that are going to know this space, and you can fly it right, I've seen drones already in the R & D labs at Intel. You can fly them straight at the wall, it'll stop an inch from the wall because it knows where the wall is. >> 'Cause it's got the software, it's got the sensors, the internet of things. We are putting out a new research report at Wikibound called IOT and P, Internet Things and People. And this is the key point. I want to get your thoughts on this because you nailed a bunch of things, and I want you to define for the folks watching what you mean by mixed reality because this is not augmented reality. >> Well it is. >> John: You're talking about mixed reality. >> It is augmented reality, it's just-- >> John: But why mixed reality? >> We came up with the new term called mixed reality because on our, we have augmented reality on phones. But the augmented reality you have on phones like the Pokemon's we've been talking about. They're not locked to the world. So when I'm wearing this, there's actually a shark right here on this table, and it's locked on the table, and I can walk around that shark. And it seems like it's sitting here just like this bottle of water is sitting on the table. This is mind blowing. And now we can actually change the table itself and make it something else. Because every pixel in this space is going to be mapped by these new sensors on it. >> So, let's take that to the next level. You had mentioned earlier in your talk just now about user interface to cars. You didn't say in user interface to cars, you didn't say just smart, you kind of implied, I think you meant it's interface to all the environments. >> Robert: Yes. >> Can you expand on what your thoughts on that? >> You're going to be wearing glasses that look like yours in about a year, much smaller than this. This is too dorky and too big for an average consumer to wear around right, but if they're three ounces and they look something like what you're wearing right now. >> Some nice Ray Bans, yup. >> And they're coming. I've seen them in the R & D labs. They're coming from a variety of different companies. Google, Facebook, Loomis, Magic Leap, all sorts of different companies are coming with these lightweight small glasses. You're going to wear them around and it's going to lay interface elements on everything. So think about my watch. Why if I do this gesture, why do I have to look at a little tiny screen right here? Why isn't the whole screen of my calendar pop up right here? They could do that, that's a gesture. This computer in here can sense that I'm doing a gesture and can put a new user interface on top of that. Now, I've seen tractors that have sensors in them. Now, using a glass like this, it shows me what the pumps are doing in the tractor on the glasses. I can walk around a factory floor and see the sensors in the pipes on the factory floor and see the sensors in my electric motors on the factory. All with a one pair of glasses. >> So this is why the Intel AI thing interests me, this whole theme. Because what you just described requires data. So one, you need to have the data available. >> Robert: Yes. >> The data's got to be a frictionless, it can't be locked in some schema as they say in the database world. It's got to be free to be addressed by software. >> Yes. >> You need software that understands what that is. And then you need horsepower, compute power, chips to make it all happen. >> Yeah, think about a new kind of TV that's coming soon. I'm going to look at TV like this one, a physical TV. But it's too small and it's in the wrong angle. So I can just grab the image off the TV and virtually move it over here. And I'll see it, nobody else will see it. But I can put that TV screen right here, so I can watch my TV the way I want to watch it. >> Alright so this is all sci-fi great stuff, which actually-- >> It's not sci-fi, it's here already. You just don't have it. I have it (laughs). >> Well, you can see it's kind of dorky, but I'm not going to say you're a dork 'cause I know you. To mainstream America, mainstream world, it's a bit sci-fi but people are grokking this now. Certainly the younger generation that are digital native all are coming in post-9/11, they understand that this is a native world to them, and they take to it like a fish to water. >> Yes. >> Us old guys, but we are the software guys, we're the tech guys. So continue to the mainstream America, what has to happen in your mind to mainstream this stuff? Obviously self driving cars is coming. It's in fleets first, and then cars. >> We have to take people on a journey away from computing like this or computing like this to computing on glasses. So how do we do that? Well, you have to show deep utility. And these glasses show that. Wearing a HoloLens, I see aliens coming out of the walls. Blowing holes in this physical wall. >> John: Like right now? >> Yeah. >> What are you smoking (laughs)? >> Nothing yet. And then I can shoot them with my fingers because the virtual things are mixing with the real world. It's a mind blowing experience. >> So do you see this being programmed by users or being a library of stuff? >> Some are going to be programmed by users like Minecraft is today on a phone or on a tablet. Most of it is going to be built by developers. So there's a huge opportunity coming for developers. >> Talk about the developer angle, because that's huge. We're seeing massive changes in the developer ecosystems. Certainly, open source is going to be around for awhile. But which friends do you see in open source, I mean, I'm sorry, in the developer community, with this new overlay of 5G connectivity, all this amazing cloud technology? >> There's a new 3D mapping and it's a slam based map. So think about this space, this physical space. These sensors that are on the front of these new kinds of glasses that are coming out are going to sense the world in a new way and put it into a new kind of database, one that we can put programmatic information into. So think about me walking around a shopping mall. I walk in the front door of a shopping mall, I cross geo fence in that shopping mall. And the glasses then show me information about the shopping mall 'cause it knows it's in the shopping mall. And then I say, hey Intel, can you show me, or Siri, or Alexa, or Cortana, or whoever you're talking to. >> Mostly powered by Intel (laughs). >> Most of it is powered by Intel 'cause Intel's in all the data centers and all these glasses. In fact, Intel is the manufacturer of the new kind of controller that's inside this new HoloLens. And when I ask it, I can say, hey, where's the blue jeans in this shopping mall? And all of a sudden, three new pairs of blue jeans will appear in the air, virtual blue jeans, and it'll say this one's a Guess, this one's a Levi's, this one's a whatever. And I'll say, oh I want the Levi's 501, and I'll click on it, and a blue line will appear on the floor taking me right to the product. You know, the shopping mall companies already have the data. They already know where the jeans are in the shopping mall and these glasses are going to take you right to it. >> Robert, so AI is the theme, it's hot, but AI, I mean I love AI, don't get me wrong. AI is a mental model in my mind for people to kind of figure out that this futuristic world's here and it's moving fast. But machine learning is a big part of what AI is becoming. >> Yes. >> So machine learning is becoming automated. >> Well it's becoming a lot faster. >> Faster and available. >> Because it use to take 70,000 images of something like a bottle to train the system that this is a bottle versus a can, bottle versus can. And the scientists have figured out how to make it two images now. So all I need is two images of something new to train the system that we have a bottle versus a can. >> And also the fact that computes available. There's more and more faster processors that this stuff can get crunched, the data can be crunched. >> Absolutely, but it's the data that trains these things. So let's talk about the bleeding edge of AI. I've seen AIs coming out of Israel that are just mind blowing. They take a 3D image of this table, they separate everything into an object. So this is an object. It's separate from the table that it's on. And it then lets me do AI look-ups on the object. So this is a Roxanne bottle of water. The 3D sensor can see the logo in this bottle of water, can look to the cloud, find all sorts of information about the manufacturer here, what the product is, all sorts of stuff. It might even pull down a CAD drawing like the computer that you're on. Pull down a CAD drawing, overlay it on top of the real product, and now we can put videos on the back of your Macintosh or something like that. You can do mind blowing stuff coming soon. That's one angle. Let's talk about medical. In Israel, I went to the AI manufacturers. They're training the MRI machines to recognize cancers. So you're going to be lying in an MRI machine and it's going to tell the people around the machine whether you have cancer or not and which cancer. And it's already faster than the doctor, cheaper than the doctor, and obviously doesn't need a doctor. And that's going to lead into a whole discussion-- >> The Christopher thing. These are societal problems by the way. The policy is the issue, not the technology. How do you deal with the ethical issues around gene sequencing and gene editing? >> That's a whole other thing. I'm just recognizing whether you have cancer on this example. But now we need to talk about jobs. How do we make new jobs in massive quantities. Because we're going to decimate a lot of peoples' jobs with these new technologies, so we need to talk about that, probably on a future Cube. But I think mixed reality is going to create millions of jobs because think about this bottle. In the future, I'm going to be wearing a pair of glasses and Skrillex is going to jump out of the bottle, on to the table, and give a performance, and then jump back into the bottle. That's only four years away according to the guy who's running a new startup called 8i. He's making a new volumetric camera, it's a camera 40 or 50 cameras around-- >> If you don't like Skrillex, Martin Garrix can come on. >> Whatever you want. Remember, this media's going to be personalized to your liking. Spotify is already doing that. Do you listen to Spotify? >> John: Yeah, of course. >> Do you listen to the discovery weekly feature on that? >> No. >> You should. It's magical. It brings you the best music based on what you've already listened and it's personalized. So your discovery weekly on your phone is different than the discovery weekly on my phone. And that's run by AI. >> So these are new collaborative filters. This is all about software? >> Yeah. Software and a little bit of hardware. Because you still need to sense the world in a new way. You're going to get new watches this year that have many more sensors that are looking in your veins for whether you have high blood pressure, whether you're a in shape for running. By the way, you're going to have an artificial coach when you go running in the morning, running next to you, just like when you see Mark Zuckerberg. He can afford to pay a real coach, I can't. So he has a real coach running with him every morning and saying hey, we're going to do some interval training today, we're going to do some sprints to get your cardio up. Well, now the glasses are going to do that for you. It's going to say, let's do some intervals today and you're going to wear the watch that's going to sense your blood pressure and your heart rate and the artificial coach running next you. And that's only two years away. >> Of course, great stuff. Robert Scoble, we have to close the segment. Quickly, how has South by changed in ten years? >> Well, 20, I've been coming for 20 years. I've been coming since it was 500 people and now it's 50,000, 70,000 people, it's crazy. >> How has it changed this year? What's going on this year? >> This is the VR year. Every year we have a year right. There was the Twitter year, there was the Foursquare year. This is the VR year, so if you're over at Capital Factory, you're going to see dozens of VR experiences. In fact, my co-author's playing the Mummy right now. I had to come on your show, I got the short straw (laughs). Sit in the sun instead of playing some cool stuff. But there's VR all over the place. Next year is going to be the mixed reality year, and this is a predictor of the next year that's coming. >> Alright, Robert Scoble, futurist right here on the Cube. Also, congratulations on your new company. You're going out on your own, Transformation Group. >> Yeah, we're helping out brands figure out this mixed reality world. >> Congratulations of course. As always, it is a transformational time in the history of our world and certainly the computer industry is going to a whole other level that we haven't seen before. And this is going to be exciting. Thanks for spending the time with us. It's the Cube here live at South by Southwest special Cube coverage, sponsored by Intel. And the hashtag is Intel AI. If you like it, tweet us at Twitter. We'll be happy to talk to you online. I'm John Furrier. More after this short break. (electronic music)