(upbeat music) >> Morning guys and girls, welcome back to theCUBE's live coverage of Women in Data Science WIDS 2023 live at Stanford University. Lisa Martin here with my co-host for this segment, Tracy Zhang. We're really excited to be talking with a great female rockstar. You're going to learn a lot from her next, Jacqueline Kuo, solutions engineer at Dataiku. Welcome, Jacqueline. Great to have you. >> Thank you so much. >> Thank for being here. >> I'm so excited to be here. >> So one of the things I have to start out with, 'cause my mom Kathy Dahlia is watching, she's a New Yorker. You are a born and raised New Yorker and I learned from my mom and others. If you're born in New York no matter how long you've moved away, you are a New Yorker. There's you guys have like a secret club. (group laughs) >> I am definitely very proud of being born and raised in New York. My family immigrated to New York, New Jersey from Taiwan. So very proud Taiwanese American as well. But I absolutely love New York and I can't imagine living anywhere else. >> Yeah, yeah. >> I love it. >> So you studied, I was doing some research on you you studied mechanical engineering at MIT. >> Yes. >> That's huge. And you discovered your passion for all things data-related. You worked at IBM as an analytics consultant. Talk to us a little bit about your career path. Were you always interested in engineering STEM-related subjects from the time you were a child? >> I feel like my interests were ranging in many different things and I ended up landing in engineering, 'cause I felt like I wanted to gain a toolkit like a toolset to make some sort of change with or use my career to make some sort of change in this world. And I landed on engineering and mechanical engineering specifically, because I felt like I got to, in my undergrad do a lot of hands-on projects, learn every part of the engineering and design process to build products which is super-transferable and transferable skills sort of is like the trend in my career so far. Where after undergrad I wanted to move back to New York and mechanical engineering jobs are kind of few and fall far in between in the city. And I ended up landing at IBM doing analytics consulting, because I wanted to understand how to use data. I knew that data was really powerful and I knew that working with it could allow me to tell better stories to influence people across different industries. And that's also how I kind of landed at Dataiku to my current role, because it really does allow me to work across different industries and work on different problems that are just interesting. >> Yeah, I like the way that, how you mentioned building a toolkit when doing your studies at school. Do you think a lot of skills are still very relevant to your job at Dataiku right now? >> I think that at the core of it is just problem solving and asking questions and continuing to be curious or trying to challenge what is is currently given to you. And I think in an engineering degree you get a lot of that. >> Yeah, I'm sure. >> But I think that we've actually seen that a lot in the panels today already, that you get that through all different types of work and research and that kind of thoughtfulness comes across in all different industries too. >> Talk a little bit about some of the challenges, that data science is solving, because every company these days, whether it's an enterprise in manufacturing or a small business in retail, everybody has to be data-driven, because the end user, the end customer, whoever that is whether it's a person, an individual, a company, a B2B, expects to have a personalized custom experience and that comes from data. But you have to be able to understand that data treated properly, responsibly. Talk about some of the interesting projects that you're doing at Dataiku or maybe some that you've done in the past that are really kind of transformative across things climate change or police violence, some of the things that data science really is impacting these days. >> Yeah, absolutely. I think that what I love about coming to these conferences is that you hear about those really impactful social impact projects that I think everybody who's in data science wants to be working on. And I think at Dataiku what's great is that we do have this program called Ikig.AI where we work with nonprofits and we support them in their data and analytics projects. And so, a project I worked on was with the Clean Water, oh my goodness, the Ocean Cleanup project, Ocean Cleanup organization, which was amazing, because it was sort of outside of my day-to-day and it allowed me to work with them and help them understand better where plastic is being aggregated across the world and where it appears, whether that's on beaches or in lakes and rivers. So using data to help them better understand that. I feel like from a day-to-day though, we, in terms of our customers, they're really looking at very basic problems with data. And I say basic, not to diminish it, but really just to kind of say that it's high impact, but basic problems around how do they forecast sales better? That's a really kind of, sort of basic problem, but it's actually super-complex and really impactful for people, for companies when it comes to forecasting how much headcount they need to have in the next year or how much inventory to have if they're retail. And all of those are going to, especially for smaller companies, make a huge impact on whether they make profit or not. And so, what's great about working at Dataiku is you get to work on these high-impact projects and oftentimes I think from my perspective, I work as a solutions engineer on the commercial team. So it's just, we work generally with smaller customers and sometimes talking to them, me talking to them is like their first introduction to what data science is and what they can do with that data. And sort of using our platform to show them what the possibilities are and help them build a strategy around how they can implement data in their day-to-day. >> What's the difference? You were a data scientist by title and function, now you're a solutions engineer. Talk about the ascendancy into that and also some of the things that you and Tracy will talk about as those transferable, those transportable skills that probably maybe you learned in engineering, you brought data science now you're bringing to solutions engineering. >> Yeah, absolutely. So data science, I love working with data. I love getting in the weeds of things and I love, oftentimes that means debugging things or looking line by line at your code and trying to make it better. I found that on in the data science role, while those things I really loved, sometimes it also meant that I didn't, couldn't see or didn't have visibility into the broader picture of well like, well why are we doing this project? And who is it impacting? And because oftentimes your day-to-day is very much in the weeds. And so, I moved into sales or solutions engineering at Dataiku to get that perspective, because what a sales engineer does is support the sale from a technical perspective. And so, you really truly understand well, what is the customer looking for and what is going to influence them to make a purchase? And how do you tell the story of the impact of data? Because oftentimes they need to quantify well, if I purchase a software like Dataiku then I'm able to build this project and make this X impact on the business. And that is really powerful. That's where the storytelling comes in and that I feel like a lot of what we've been hearing today about connecting data with people who can actually do something with that data. That's really the bridge that we as sales engineers are trying to connect in that sales process. >> It's all about connectivity, isn't it? >> Yeah, definitely. We were talking about this earlier that it's about making impact and it's about people who we are analyzing data is like influencing. And I saw that one of the keywords or one of the biggest thing at Dataiku is everyday AI, so I wanted to just ask, could you please talk more about how does that weave into the problem solving and then day-to-day making an impact process? >> Yes, so I started working on Dataiku around three years ago and I fell in love with the product itself. The product that we have is we allow for people with different backgrounds. If you're coming from a data analyst background, data science, data engineering, maybe you are more of like a business subject matter expert, to all work in one unified central platform, one user interface. And why that's powerful is that when you're working with data, it's not just that data scientist working on their own and their own computer coding. We've heard today that it's all about connecting the data scientists with those business people, with maybe the data engineers and IT people who are actually going to put that model into production or other folks. And so, they all use different languages. Data scientists might use Python and R, your business people are using PowerPoint and Excel, everyone's using different tools. How do we bring them all in one place so that you can have conversations faster? So the business people can understand exactly what you're building with the data and can get their hands on that data and that model prediction faster. So that's what Dataiku does. That's the product that we have. And I completely forgot your question, 'cause I got so invested in talking about this. Oh, everyday AI. Yeah, so the goal of of Dataiku is really to allow for those maybe less technical people with less traditional data science backgrounds. Maybe they're data experts and they understand the data really well and they've been working in SQL for all their career. Maybe they're just subject matter experts and want to get more into working with data. We allow those people to do that through our no and low-code tools within our platform. Platform is very visual as well. And so, I've seen a lot of people learn data science, learn machine learning by working in the tool itself. And that's sort of, that's where everyday AI comes in, 'cause we truly believe that there are a lot of, there's a lot of unutilized expertise out there that we can bring in. And if we did give them access to data, imagine what we could do in the kind of work that they can do and become empowered basically with that. >> Yeah, we're just scratching the surface. I find data science so fascinating, especially when you talk about some of the real world applications, police violence, health inequities, climate change. Here we are in California and I don't know if you know, we're experiencing an atmospheric river again tomorrow. Californians and the rain- >> Storm is coming. >> We are not good... And I'm a native Californian, but we all know about climate change. People probably don't associate all of the data that is helping us understand it, make decisions based on what's coming what's happened in the past. I just find that so fascinating. But I really think we're truly at the beginning of really understanding the impact that being data-driven can actually mean whether you are investigating climate change or police violence or health inequities or your a grocery store that needs to become data-driven, because your consumer is expecting a personalized relevant experience. I want you to offer me up things that I know I was doing online grocery shopping, yesterday, I just got back from Europe and I was so thankful that my grocer is data-driven, because they made the process so easy for me. And but we have that expectation as consumers that it's going to be that easy, it's going to be that personalized. And what a lot of folks don't understand is the data the democratization of data, the AI that's helping make that a possibility that makes our lives easier. >> Yeah, I love that point around data is everywhere and the more we have, the actually the more access we actually are providing. 'cause now compute is cheaper, data is literally everywhere, you can get access to it very easily. And so, I feel like more people are just getting themselves involved and that's, I mean this whole conference around just bringing more women into this industry and more people with different backgrounds from minority groups so that we get their thoughts, their opinions into the work is so important and it's becoming a lot easier with all of the technology and tools just being open source being easier to access, being cheaper. And that I feel really hopeful about in this field. >> That's good. Hope is good, isn't it? >> Yes, that's all we need. But yeah, I'm glad to see that we're working towards that direction. I'm excited to see what lies in the future. >> We've been talking about numbers of women, percentages of women in technical roles for years and we've seen it hover around 25%. I was looking at some, I need to AnitaB.org stats from 2022 was just looking at this yesterday and the numbers are going up. I think the number was 26, 27.6% of women in technical roles. So we're seeing a growth there especially over pre-pandemic levels. Definitely the biggest challenge that still seems to be one of the biggest that remains is attrition. I would love to get your advice on what would you tell your younger self or the previous prior generation in terms of having the confidence and the courage to pursue engineering, pursue data science, pursue a technical role, and also stay in that role so you can be one of those females on stage that we saw today? >> Yeah, that's the goal right there one day. I think it's really about finding other people to lift and mentor and support you. And I talked to a bunch of people today who just found this conference through Googling it, and the fact that organizations like this exist really do help, because those are the people who are going to understand the struggles you're going through as a woman in this industry, which can get tough, but it gets easier when you have a community to share that with and to support you. And I do want to definitely give a plug to the WIDS@Dataiku team. >> Talk to us about that. >> Yeah, I was so fortunate to be a WIDS ambassador last year and again this year with Dataiku and I was here last year as well with Dataiku, but we have grown the WIDS effort so much over the last few years. So the first year we had two events in New York and also in London. Our Dataiku's global. So this year we additionally have one in the west coast out here in SF and another one in Singapore which is incredible to involve that team. But what I love is that everyone is really passionate about just getting more women involved in this industry. But then also what I find fortunate too at Dataiku is that we have a strong female, just a lot of women. >> Good. >> Yeah. >> A lot of women working as data scientists, solutions engineer and sales and all across the company who even if they aren't doing data work in a day-to-day, they are super-involved and excited to get more women in the technical field. And so. that's like our Empower group internally that hosts events and I feel like it's a really nice safe space for all of us to speak about challenges that we encounter and feel like we're not alone in that we have a support system to make it better. So I think from a nutrition standpoint every organization should have a female ERG to just support one another. >> Absolutely. There's so much value in a network in the community. I was talking to somebody who I'm blanking on this may have been in Barcelona last week, talking about a stat that showed that a really high percentage, 78% of people couldn't identify a female role model in technology. Of course, Sheryl Sandberg's been one of our role models and I thought a lot of people know Sheryl who's leaving or has left. And then a whole, YouTube influencers that have no idea that the CEO of YouTube for years has been a woman, who has- >> And she came last year to speak at WIDS. >> Did she? >> Yeah. >> Oh, I missed that. It must have been, we were probably filming. But we need more, we need to be, and it sounds like Dataiku was doing a great job of this. Tracy, we've talked about this earlier today. We need to see what we can be. And it sounds like Dataiku was pioneering that with that ERG program that you talked about. And I completely agree with you. That should be a standard program everywhere and women should feel empowered to raise their hand ask a question, or really embrace, "I'm interested in engineering, I'm interested in data science." Then maybe there's not a lot of women in classes. That's okay. Be the pioneer, be that next Sheryl Sandberg or the CTO of ChatGPT, Mira Murati, who's a female. We need more people that we can see and lean into that and embrace it. I think you're going to be one of them. >> I think so too. Just so that young girls like me like other who's so in school, can see, can look up to you and be like, "She's my role model and I want to be like her. And I know that there's someone to listen to me and to support me if I have any questions in this field." So yeah. >> Yeah, I mean that's how I feel about literally everyone that I'm surrounded by here. I find that you find role models and people to look up to in every conversation whenever I'm speaking with another woman in tech, because there's a journey that has had happen for you to get to that place. So it's incredible, this community. >> It is incredible. WIDS is a movement we're so proud of at theCUBE to have been a part of it since the very beginning, since 2015, I've been covering it since 2017. It's always one of my favorite events. It's so inspiring and it just goes to show the power that data can have, the influence, but also just that we're at the beginning of uncovering so much. Jacqueline's been such a pleasure having you on theCUBE. Thank you. >> Thank you. >> For sharing your story, sharing with us what Dataiku was doing and keep going. More power to you girl. We're going to see you up on that stage one of these years. >> Thank you so much. Thank you guys. >> Our pleasure. >> Our pleasure. >> For our guests and Tracy Zhang, this is Lisa Martin, you're watching theCUBE live at WIDS '23. #EmbraceEquity is this year's International Women's Day theme. Stick around, our next guest joins us in just a minute. (upbeat music)

>>Hey everyone. Welcome back to Miami. Lisa Martin here live with the Cube at IFS Unleashed 2022. We're so excited to be here. We just had a great conversation with Ifss, CEO of Darren Rouse. Now we've got another exciting conversation. F1 is here. You know how much I love f1. Christian Peterson joins us as well, the Chief Product Officer at ifs, and Sean Edwards IT business partner at Aston Martin. F1. Guys, it's great to have you on the program. Thank you for having >>Us. Thank you >>Very much. We were talking about F one. We probably could have an entire conversation just on that, but Christian, I wanna talk with you. It's been three years since the Cube has covered ifs obviously for obvious reasons during that time. So much momentum has happened. IFS cloud was launched about 18 months ago. Give our audience an o, a flavor of IFS, cloud and some of the milestones that you've hit in such a short time period. >>Yeah, I mean IFS cloud is really transformational in many ways. It's transformational for first and foremost for our customers in what enables them to do, but also transformational for us from a technology perspective, how we work and how we do everything. And at the end of the day, it has really surfaced, served around the the, the fact of what we need to do for our customers. And what we saw our customers often do back then, or any company, was they were out looking for EAP solutions or FSM Solutions or EAM Solutions or what have you. And then they were trying to stitch it all together and we, we said like, Hang on a second, these these traditional software s, those are some that I'm guilty. You know, there's some that we actually invented over the years together with analysts. So we invented EER P and we invented CRM and EAM and all these different things. >>But at the end of the day, customers really want a solution to what they are, they are what they're dealing with. And so in these conversations it became very clear that and very repeated conclusions from the conversations that customers wanted something that could manage and help them optimize the use of their assets. Regardless of what industry you're in, assets is such a key component. Either you are using your assets or you're producing assets. Second thing is really get the best use of of your people, your teams and your crew. How do you get the right people on the right job at the same time? How do you assemble the right crew with the right set of skills in the crew? Get them to the right people at the same time. So, and then the final thing is of course customers, you know all the things that you need to do to get customers to answer these ultimate questions, Will you buy from this company again? And they should say yes. That's the ultimate results of moments of service. So that's how we bring it all together and that's what we have been fast at work at. That's what IFS cloud is all about. >>And you, you talked about IFS cloud, being able to to help customers, orchestrate assets, people, customers, Aston Martin being one of those customers. Shawn, you came from ifs so you have kind of the backstory but just give the audience a little bit of, of flavor of your role at Aston Martin and then let's dig into the smart factory. >>Sure. So I previously worked at IFS as a manufacturing consultant. So my bread and butter is production planning in the ERP sector. So we, I Aston Martin didn't have an ERP system pre IFS or a legacy system that wasn't working for them and the team couldn't rely upon it. So what we did was bring IFS in. I was the consultant there and as IFS always preached customer first, well customer first did come and I jumped to support the team. So we've implemented a fully RP solution to manage the production control and the material traceability all the way through from design until delivery to track. And we've mo most recently implemented a warehouse solution at Trackside as well. So we are now tracking our parts going out with the garage. So that's a really exciting time for RFS. In terms of the smart factory, it's not built yet. >>We're we're supposed to move next year. So that's really exciting cause we're quadrupling our footprint. So going from quite a small factory spread out across the North Hampton Share countryside, we're going into one place quadruple in our footprint. And what we're gonna start looking at is using the technology we're implementing there. So enabling 5G to springboard our IFFs implementations going forward with the likes of Internet of things to connect our 15 brand new CMC machines, but also things like R F I D. So that comes with its own challenges on a Formula One car, but it's all about speed of data capture, single point of truth. And IFFs provides that >>And well, Formula One, the first word that comes to mind is speed. >>Absolutely. Second >>Word is crazy. >>We, we are very unique in terms of most customers Christian deals with, they're about speed but also about profit and efficiency. That doesn't matter to us. It is all about time. Time is our currency and if we go quicker in designing and manufacturing, which ifs supports ultimately the cargo quicker. So speed is everything. >>And and if we, if we think of of people, customers and assets at Asset Martin F one, I can't, I can't imagine the quantity of assets that you're building every race weekend and refactoring. >>Absolutely. So a Formula one car that drives out of the garage is made up of 13,000 car parts, most of which, 50% of which we've made in house. So we have to track that all the way through from the smallest metallic component all the way up to the most complex assembly. So orchestrating that and having a single point of truth for people to look at and track is what IFFs has provided us. >>Christian, elaborate on that a little bit in terms of, I mean, what you're facilitating, F1 is such a great example of of speed we talked about, but the fact that you're setting up the car every, every other weekend maybe sometimes back to back weeks, so many massive changes going on. You mentioned 50% of those 13,000 parts you manufacture. Absolutely. Talk about IFS as being a catalyst for that. >>I mean the, it's, it's fascinating with Formula One, but because as a technology geek like me, it's really just any other business on steroids. I mean we talk, we talk about this absolutely high tech, super high tech manufacturing, but even, even before that, the design that goes in with CFDs and how you optimize for different things and loose simulation software for these things goes into manufacturing, goes into wind tunnels and then goes on track. But guess what, when it's on track, it's an asset. It's an asset that streams from how many sensors are on the car, >>I think it's over 10,000 >>Sensors, over 10,000 sensors that streams maybe at 50 hertz or 50 readings. So every lap you just get this mountain of data, which is really iot. So I always say like F one if one did IOT before anybody invented the term. >>Absolutely. >>Yep. You know, F1 did machine learning and AI before anybody thought about it in terms of pattern recognition and things like that with the data. So that's why it's fascinating to work with an organization like that. It's the, it's the sophistication around the technologies and then the pace what they do. It's not that what they do is actually so different. >>It is, it absolutely isn't. We just have to do it really quickly. Really >>Quickly. Right. And the same thing when you talk about parts. I mean I was fascinated of a conversation with, with one of your designers that says that, you know, sometimes we are, we are designing a part and this, the car is now ready for production but the previous version of that part has not even been deployed on the car yet. So that's how quick the innovation comes through and it's, it's, it's fascinating and that's why we like the challenge that Esther Martin gives us because if we can, if we can address that, there's a lot of businesses we can make happy with that as far, >>So Sha I talk a little bit about this is, so we're coming up, there's what four races left in the 2022 season, but this is your busy time because that new car, the 23 car needs to be debuted in what February? So just a few months time? >>Absolutely. So it's a bit cancer intuitive. So our busiest time is now we're ramping up into it. So we co, we go into something called car build which is from December to December to February, which is our end point and there's no move in that point. The car has gotta go around that track in February. So we have got to make those 13,000 components. We've gotta design 'em, we've gotta make 'em and then we've gotta get 'em to the car in February for our moment of service. They said it on stage. Our moment of service as a manufacturing company is that car going around the track and we have to do it 24 times next year and we've gotta start. Well otherwise we're not gonna keep up. >>I'm just gonna ask you what a, what a moment, what's a moment of service in f1 and you're saying basically getting that >>Functional car >>On the track quickly, as quickly as possible and being able to have the technology underpinning that's really abstracting the complexity. >>Absolutely. So I would say our customer ultimately is the driver and the fans they, they need to have a fast car so they can sport it and they ultimately drive it around the track and go get first place and be competitive. So that is our moment of service to our drivers is to deliver that car 24 times next year. >>I imagine they might be a little demanding >>They are and I think it's gonna be exciting with Alonzo coming in, could the driver if we've gotta manage that change and he'll have new things that he wants to try out on a car. So adds another level of complexity to that. >>Well how influential are the drivers in terms some of the, the manufacturing? Like did they, are they give me kind of a a sense of how Alon Fernando Alanzo your team and ifs maybe collaborate, maybe not directly but >>So Alonzo will come in and suggest that he wants cars to work a certain way so he will feed back to the team in terms of we need this car, we need this car part to do this and this car part to do that. So then we're in a cycle when he first gets into the car in that February, we've then gotta turnaround car parts based off his suggestions. So we need to do that again really quickly and that's where IFS feeds in. So we have to have the release and then the manufacturer of the component completely integrated and that's what we achieve with IFFs and >>It needs to be really seamless. >>Absolutely. If, if we don't get it right, that car doesn't go out track so there's no moving deadline. >>Right. That's the probably one of the industries where deadlines do not move. Absolutely. We're so used to things happening in tech where things shift and change and reorgs, but this is one where the dates are set in their firm. >>Absolutely. And we have to do anything we can do to get that car on the track. So yeah, it's just a move. >>Christian, talk about the partnership a little bit from your standpoint in terms of how influential has Aston Martin F1 been in IFS cloud and its first 18 months. I was looking at some stats that you've already gotten 400,000 plus users in just a short time period. How influential are your customers in the direction and even the the next launch 22 R too? >>I mean our customers do everything plain and simple. That's that's what it is. And we have, we have a partnership, I think about every single customer as a partner of ours and we are partnering in taking technology to the next level in terms of, of the outputs and the benefits it can create for our customers. That's what it's all, all about. And I, I always think about these, these three elements I think I mentioned in our state as well. I think the partnership we have is a partnership around innovation. Innovation doesn't not only come from IFS or the technology partner, it comes from discussions, requirements, opportunities, what if like all these things. So innovation comes from everywhere. There's technology driven innovation, there's customer driven innovation, but that's part of the partnership. The second part of the partnership is inspiration. So with innovation you inspire. So when you innovate on something new that inspires new innovation and new thinking and that's again the second part of the partnership. And then the third part is really iterate and execute, right? Because it's great that we can now innovate and we can agree on what we need to do, but now we need to put it into products, put it in technology and put it into actual use. That's when the benefits comes and that's when we can start bringing the bell. >>And I think it's really intrinsically linked. I mean if you look at progress with Formula One teams and their innovation, it's all underpinned by our technology partners and that's why it's so important. The likes of Christian pushes the product and improves it and innovates it because then we can realize the benefits and ultimately save time and go faster. So it's really important that our, our partners and certainly inform one, push the boundaries and find that technology. >>And I think one of the things that we also find very, very important is that we actually understand our customers and can talk the language. So I think that was one of the key things in our engagement, Martin from the beginning is that we had a set of people that really understand Formula One felt it on their bodies and can have the conversation. So when the Formula One teams they say something, then we actually understand what we're talking about. So for instance, when we talk about, you know, track side inventory, well it's not that different from what a field service technician have in his van when he goes service. The only difference is when you see something happening on track, you'll see the parts manager go out to the pit lane with a tablet and say like, oh we need this, we need that, we need this and we need that. And then we'll go back and pick it and put it on the car and the car is service and maintain and off go. Absolutely. >>Yeah that speed always impresses me. >>It's unbelievable. >>Shannon, last question for you. From a smart factory perspective, you said you're moving in next year. What are some of the things that you are excited about that you think are really gonna be transformative but IFS is doing? >>So I think what I'm really excited about once we get in is using the technology they've already put in terms of 5G networks to sort of springboard that into a further IFS implementation. Maybe IFFs cloud in terms of we always struggle to keep the system up to date with, with what's physically happening so that the less data entry and the more automatic sort of data capture, the better it is for the formula on team cuz we improve our our single point of truth. So I'm really excited to look at the internet of things and sort of integrate our CNC machines to sort of feed that information back into ifs. But also the RFID technology I think is gonna be a game changer when we go into the new factory. So really >>Excited. Excellent. Well well done this year. We look forward to seeing Alonso join the team in 23. Fingers >>Crossed. >>Okay. Fingers crossed. Christian, Jeanette, it's been a pleasure to have you on the program. Thank you so much for sharing your insights and how ifs asked Martin are working together, how you really synergistically working together. We appreciate your time. >>Thank you very much for having us. Our >>Thanks for having us. And go Aston >>Woo go Aston, you already here first Lisa Martin, no relation to Aston Martin, but well, I wanna thank Christian Peterson and Shannon Edwards for joining me, talking about IFS and Aston Martin team and what they're doing at Speed and Scale. Stick around my next guest joins me in a minute. >>Thank you.

foreign [Music] Lisa Martin of the cube here hpe and AMD better together with Shi is the name of our segment and I'm here with four guests please welcome Charlie mulrooney Global pre-sales engineering manager at SHI John saw is also of shi joins us Global pre-sales Technical consultant and back with me are Terry Richardson North American Channel Chief and Dr John Fry Chief technologist of sustainable transformation at hpe welcome gang great to have you here all here Thank you Lisa thank you good to be here all right Charlie let's go ahead and start with you keeping the Earth sustainable and minimizing carbon emissions greenhouse gases is a huge priority for businesses right everywhere globally can you talk truly about what Shi is seeing in the marketplace with respect to sustainable I.T sure so starting about a year and a half two years ago we really noticed that our customers certainly our largest Enterprise customers were putting into their annual reports their Chairman's letters their SEC filings that they had sustainability initiatives ranging from achieving carbon neutral uh or carbon zero goals starting with 20 50 dates and then since then we've seen 20 40 and 2030 targets to achieve net neutrality and rfps rfis that we're Fielding certainly all now contain elements of that so this is certainly top of mind for our largest customers our Fortune 250 and Fortune 500 customers for sure where we're seeing an onslaught of requests for this we get into many conversations with the folks that are leading these efforts to understand you know here's what we have today what can we do better what can we do different to help make it an impact on those goals so making an impact top of Mind pretty much for everyone as you mentioned John Sal's let's bring you into the conversation now when you're in customer conversations what are some of the things that you talk about with respect to shi's approach to sustainability sustainable I.T are you seeing more folks that are implementing things tactically versus strategically what's going on in the customer space well so Charlie touched on something really important that you know the the wake-up moment for us was receiving you know proposal requests or customer meeting requests that were around sustainability and it was really around two years ago I suppose for the first time and those requests started coming from european-based companies because they had a bit of a head start uh over the U.S based global companies even um and what we found was that sustainability was already well down the road and that they were doing very interesting things to uh use renewable energy for data centers uh utilized they were already considering sustainability for new technologies as a high priority versus just performance costs and other factors that you typically had at the top so as we started working with them uh I guess that beginning was more tactical because we really had to find a way to respond uh we were starting to be asked about our own efforts and in regards to sustainability we have our headquarters in Somerset and our second Headquarters in Austin Texas um those are the gold certified we've been installing solar panels producing waste across the company recycling efforts and so forth charging stations for electric vehicles all that sort of thing to make our company more sustainable in in uh in our offices and in our headquarters um but it's a lot more than that and what we found was that we wanted to look to our vast number of supply of customers and partners we have over 30 000 partners that would work with globally and tens of thousands of customers and we wanted to find best practices and Technologies and services that we could uh talk about with these customers and apply and help integrate together as a as a really large Global uh reseller and integrator we can have a play there and bring these things together from multiple uh partners that we work with to help solve customer problems and so over time it's become more strategic and we've been uh as a company building the uh the the the forward efforts through organizing a true formal sustainability team and growing that um and then also reporting for CDP echovatus and so forth and it's really that all has been coming about in the last couple of years and we take it very seriously it sounds like it also sounds like from the customer's perspective they're shifting from that tactical maybe early initial approach to being more strategic to really enabling sustainable I.T across their organization and I imagine from a business driver's perspective John saws and Charlie are you hearing customers you talked about it being part of rfps but also where are customers in terms of we need to have a sustainable I.T strategy so that we can attract and retain the right investors we can attract and retain customers Charlie John what are your thoughts on that yeah that's top of mind with uh with all the folks that we're talking to uh I would say there's probably a three-way tie for the importance of uh attracting and retaining investors as you said plus customers customers are shopping their customers are shopping for who has aligned their ESG priorities in sustainable priorities uh with their own and who is going to help them with their own reporting of you know spoke to and ultimately scope three reporting from greenhouse gas emissions and then the attracting and retaining Talent uh it's another element now of when you're bringing on a new talent to your organization they have a choice and they're thinking with their decision to accept a role or not within your organization of what your strategies are and do they align so we're seeing those almost interchangeable in terms of priorities with with the customers we're talking to it was a little surprising because we thought initially this is really focused on investors attracting the investors but it really has become quite a bit more than that and it's been actually very interesting to see the development of that prioritization more comprehensive across the organization let's bring Dr John Fry into the conversation and Terry your neck so stay tuned Dr Frey can you talk about hpe and Shia partnering together what are some of the key aspects of the relationship that help one another support and enable each other's aggressive goals where sustainability is concerned yeah it's a great question and one of the things about the sustainability domain in solving these climate challenges that we all have is we've got to come together and partner to solve them no one company's going to solve them by themselves and for our Collective customers the same way from an hpe perspective we bring the expertise on our products we bring in a sustainable I.T point of view where we've written many white papers on the topic and even workbooks that help companies Implement a sustainable I.T program but our direct sales forces can't reach all of our customers and in many cases we don't have the local knowledge that our business partners like Shi bring to the table so they extend the reach they bring their own expertise their portfolio that they offer to the customer is wider than just Enterprise Products so by working together we can do a better job of helping the customer meet their own needs give them the right Technology Solutions and enhance that customer experience it's because they get more value from us collectively it really is better together which is a very appropriate name for our segment here Terry let's bring you into the conversation talk to us about AMD how is it helping customers to create that sustainable I.T strategy and what are some of the differentiators that what AMD is doing that that are able to be delivered through Partners like Shi well Lisa you use the word enabling um just a short while ago and fundamentally AMD enables hpe and partners like Shi to bring differentiated solutions to customers so in the data center space We Begin our journey in 2017 with some fundamental Design Elements for our processor technology that we're really keenly focused on improving performance but also efficiency so now the the most common measure that we see for the types of customers that Charlie and John were talking about was really that measure of performance per watt and you'll continue to see AMD enable um customers to to try to find ways to to do more in a sustainable way within the constraints that they may be facing whether it's availability of power data center space or just needing to meet overall sustainability goals so we have skills and expertise and tools that we make available to hpe and to Shi to help them have even stronger differentiated conversations with customers sounds like to me Terry that it's that AMD can be even more of an more than an enabler but really an accelerator of what customers are able to do from a strategic perspective on sustainability you're right about that and and we actually have tools greenhouse gas TCO tools that can be leveraged to really quantify the impact of some of the the new technology decisions that customers are making to allow them to achieve their goals so we're really proud of the work that we're doing in partnership with companies like hpe and Shi Better Together as we've said at the beginning and just a minute ago Charlie let's bring you back in talk to us a little bit about what Shi is doing to leverage sustainable I.T and enable your customers to meet their sustainability goals and their initiatives so for quite a while we've had uh some offerings to help customers especially in the end user compute side a lot of customers were interested in I've got assets for you know let's say a large sales force that had been carrying tablets or laptops and you know those need to be refreshed what do I do with those how do I responsibly retire or recycle those and we've been offering solutions for that for quite some time it's within the last year or two when we started offering for them guarantees and Assurance assurances of how they can if that equipment is reusable by somebody else how can we issue them you know credits for uh carving credits for reuse of that equipment somewhere else so it's not necessarily going to be E-Waste it's uh something that can be recycled and reused we have other programs with helping extend the life of of some systems where they look at boy I have an awful lot of data on these machines where historically they might want to just retire those because the the sensitivity of the data needed to be handled very specifically we can help them properly remove the sensitive data and still allow reuse of that equipment so we've been able to accomplish some Creative Solutions specifically around end user compute in the past but we are looking to new ways now to to really help extend that into Data Center infrastructure and Beyond to really help with what are the needs what are the the best ways to help our customers handle the things that are challenging them [Music] that's a great point that you bring up Charlie and the security kind of popped into my head here John saw his question for you when you're in customer conversations and you're talking about or maybe they're talking about help us with waste reduction with recycling where are you having those customer conversations I know sustainability is a board level it's a c-level discussion but where are you having those conversations within the customer organization well so it's a it's a combination of um organizations within the customer these are these Global organizations typically when we're talking about asset like cycle management asset recovery how do you do that in a sustainable Green Way and securely the customers we're dealing with I mean security is top sustainability is right up there too obviously but uh um Charlie touched on a lot of those things and these are Global rollouts tens of thousands of employees typically to to have mobile devices laptops and phones and so forth um and they often are looking for a true managed service around the world that takes into consideration things like the most efficient way to ship products to to the employees and how do you do that in a sustainable way you need to think about that does it all go to a central location um or to each individual's home during the pandemic that made a lot of sense to do it that way I think the reason I wanted to touch on those things is that well for for example one European pharmaceutical that the states and their reports that they are already in scope one in scope two they're fully uh Net Zero at this point and and they say but that only solves three percent of our overall sustainability goals uh 97 is scope three it's travel it's shipping it's it's uh it's all the all these things that are out of their direct control a lot of times but they're coming to us now as a as a supplier and ask and and we're filling out forms and rfps and so forth uh to show that we can be a sustainable supplier in their supply chain because that's their next big goal so sustainable supply chain absolutely Dr John Fry and Terry I want to kind of get your perspectives Charlie talked about from a customer requirements perspective customers coming through RFP saying hey we've got to work with vendors who have clear sustainability initiatives that are well underway hpe and AMD hearing the same thing Dr Fry will start with you and then Terry sure absolutely we receive about 2500 customer questionnaires just on sustainability every year and that's come up from a few hundred so yeah absolutely accelerating then the conversations turn deeper can you help us quantify our carbon emissions and power consumption then the conversation has recently gone even further to when can hpe offer Net Zero or carbon neutral Technology Solutions to the customer so that they don't have to account for those Solutions in their own carbon footprint so the questions are getting more sophisticated the need for the data and the accuracy of the data is climbing and as we see potential regulatory disclosure requirements around carbon emissions I think this trend is just going to continue up yeah and we see the same thing uh we get asked more and more from our customers and partners around our own corporate sustainability goals but the surveying that the survey work that we've done with customers has led us to you know understand that you know approximately 75 percent of customers are going to make sustainability goals a key component of their rfis in 2023 which is right around the corner and you know 60 of those same customers really expect to have business level kpis uh in the new year that are really related to sustainability so this is not just a a kind of a buzzword topic this is this is kind of business imperatives that you know the company the companies like hpe and AMD and the partners like Shi that really stand behind it and really are proactive in getting out in front of customers to help are really going to be ahead of the game that's a great point that you make Terry there that this isn't we're not talking about a buzzword here we're talking about a business imperative for businesses of probably all sizes across all Industries and Dr Farr you mentioned regulations and something that we just noticed is that the SEC recently said it's proposing some rules where companies must disclose greenhouse gas emissions um if they were if that were to to come into play I'm going to come back to Charlie and John saws how would Shi and frankly at hpe and AMD be able to help companies comply if that type of Regulation were to be implemented Charlie yeah so we are in the process right now of building out a service to help customers specifically with that with the reporting we know reporting is a challenge uh the scope 2 reporting is a challenge and scope three that I guess people thought was going to be a ways out now all of a sudden hey if you have made a public statement that you're going to make an impact on your scope three uh targets and you have to report on them so that that has become really important very quickly uh as word about this requirement is rumbling around uh there's concern so we are actually working right now on something it's a little too early to fully disclose but stay tuned because we have something coming that's interesting definitely peaked my ears are are parked here Charlie well stay tuned for that Dr Brian Terry can you talk about together with Shi hpe and AMD enabling customers to manage access to the data obviously which is critical and it's doing nothing but growing and proliferating key folks need access to it we talked a little bit about security but how are from a Better Together perspective Dr Fry will start with you how are you really helping organizations on that sustainability journey to ensure that data can be accessible to those who need it when they need it and these days what is real-time requirements yeah it's an increasing challenge in fact we have changed the HP Story the way we talk about hpe's value proposition to talk about data first modernization so how often do you collect data where do you store it how do you avoid moving it how do you make sure if you're going to collect data you get insights from that data that change your business or add business value and then how long do you retain that data afterward and all of that factors into sustainable I.T because when I talk to technology Executives what they tell me again and again is there's this presumption within their user community that storage is free and so when when they have needs for collecting data for example if if once an hour would do okay but the system would collect it once a minute the default the user asks for of course is once a minute and then are you getting insights from that data or are we moving it that becomes more important when you're moving data back and forth between the public cloud or the edge because there is quite a network penalty for moving that equipment across your network there's huge power and carbon implications of doing that so it's really making a better decision about what do we collect why do we collect it what we're going to do with it when we collect and how we store it and for years customers have really talked about you know modernization and the need to modernize their data center you know I fundamentally believe that sustainability is really that Catalyst to really Drive true modernization and as they think forward um you know when we work with with hpe you know they offer a variety of purpose-built servers that can play a role in you know specific customer workloads from the larger supercomputers down to kind of general purpose servers and when we work with Partners like Shi not only can they deliver the full Suite of um offerings for on-premise deployments they're also very well positioned to leverage the public Cloud infrastructure for those workloads that really belong there and that certainly can help customers kind of achieve an end-to-end sustainability goal that's a great point that that it needs to be strategic but it also needs to be an end-to-end goal we're just about out of time but I wanted to give John saws the last word here take us out John what are some of the things Charlie kind of teased some of the things that are coming out that piqued my interest but what are some of the things that you're excited about as hpe AMD and Shi really help customers achieve their sustainability initiatives sure um a couple of comments here um so Charlie yeah you touched on some upcoming capabilities uh that uh Shi will have around the area of monitoring and management see this is difficult for all customers to be able to report in this formal way this is a train coming at everybody very quickly and um they're not ready most customers aren't ready and if we can help um as as a reseller integrator assessments to be able to understand what they're currently running compared to different scenarios of where they could go to in a future state that seems valuable if we can help in that way that's those are things that we're looking into specifically uh you know greenhouse gas emissions relevant assessments and and um and what in the comments uh of Terry and John around the power per watt and um the vast um uh portfolio of technologies that they that they had to address various workloads is uh is fantastic we'd be able to help point to Technologies like that and move customers in that direction I think as a as an integrator and a technical advisor to customers I saw an article on BBC this morning that I I think if we think about how we're working with our customers and we can help them maybe think differently about how they're using their technology to solve problems um the BBC article mentioned this was ethereum a cryptocurrency and they have a big project called merge and today was a go live date and BBC US news outlets have been reporting on it they basically changed the model from a model called The Power of work which takes a a lot of compute and graphic GPU power and so forth around the world and it's now called a power of stake which means that the people that validate that their actions in this environment are correct they have to put up a stake of their own cryptocurrency and if they're wrong it's taken from them this new model reduces the emissions of their um uh environment by 99 plus percent the June emissions from ethereum were it was 120 uh terawatts per per year terawatt hours per year and they reduced it um actually that's the equivalent of what the Netherlands needed for energy so the comparable to a medium-sized country so if you can think differently about how to solve problems it may be on-prem it may be extremely it may be that may be the public cloud in some cases or other you know interesting Innovative Technologies that the AMD hpe other partners that we can bring in along along with them as well we can solve problems differently there is a lot going on the opportunities that you all talked about to really make such a huge societal impact and impact to our planet are exciting we thank you so much for talking together about how hpe AMD and sha are really working in partnership in Synergy to help your customers across every organization really become much more focused much more collaborative about sustainable I.T guys we so appreciate your time and thank you for your insights Thank you Lisa thank you my pleasure for my guests I'm Lisa Martin in a moment Dan Molina is going to join me he's the co-president and chief technology officer of nth generation you're watching the cube the leader in high tech Enterprise coverage [Music]

>>mhm Yes. >>Welcome back to the Cube coverage of Red Hat summit 21 2021. I'm john for host of the Cubans virtual this year as we start preparing to come out of Covid a lot of great conversations here happening around technology. This is the emerging technology with Red hat segment. We've got three great guests steve watt manager, distinguished engineer at Red Hat hurl saying senior software engineer Red Hat and luke Hines, who's the senior software engineer as well. We got the engineering team steve, you're the the team leader, emerging tech within red hat. Always something to talk about. You guys have great tech chops that's well known in the industry and I'll see now part of IBM you've got a deep bench um what's your, how do you view emerging tech um how do you apply it? How do you prioritize, give us a quick overview of the emerging tech scene at Redhead? >>Yeah, sure. It's quite a conflated term. The way we define emerging technologies is that it's a technology that's typically 18 months plus out from commercialization and this can sometimes go six months either way. Another thing about it is it's typically not something on any of our product roadmaps within the portfolio. So in some sense, it's often a bit of a surprise that we have to react to. >>So no real agenda. And I mean you have some business unit kind of probably uh but you have to have first principles within red hat, but for this you're looking at kind of the moon shot, so to speak, the big game changing shifts. Quantum, you know, you got now supply chain from everything from new economics, new technology because that kind of getting it right. >>Yeah, I think we we definitely use a couple of different techniques to prioritize and filter what we're doing. And the first is something will pop up and it will be like, is it in our addressable market? So our addressable market is that we're a platform software company that builds enterprise software and so, you know, it's got to be sort of fit into that is a great example if somebody came up came to us with an idea for like a drone command center, which is a military application, it is an emerging technology, but it's something that we would pass on. >>Yeah, I mean I didn't make sense, but he also, what's interesting is that you guys have an open source D N A. So it's you have also a huge commercial impact and again, open sources of one of the 4th, 5th generation of awesomeness. So, you know, the good news is open source is well proven. But as you start getting into this more disruption, you've got the confluence of, you know, core cloud, cloud Native, industrial and IOT edge and data. All this is interesting, right. This is where the action is. How do you guys bring that open source community participation? You got more stakeholders emerging there before the break down, how that you guys manage all that complexity? >>Yeah, sure. So I think that the way I would start is that, you know, we like to act on good ideas, but I don't think good ideas come from any one place. And so we typically organize our teams around sort of horizontal technology sectors. So you've got, you know, luke who's heading up security, but I have an edge team, cloud networking team, a cloud storage team. Cloud application platforms team. So we've got these sort of different areas that we sort of attack work and opportunities, but you know, the good ideas can come from a variety of different places. So we try and leverage co creation with our customers and our partners. So as a good example of something we had to react to a few years ago, it was K Native right? So the sort of a new way of doing service um and eventing on top of kubernetes that was originated from google. Whereas if you look at Quantum right, ibms, the actual driver on quantum science and uh that originated from IBM were parole. We'll talk about exactly how we chose to respond to that. Some things are originated organically within the team. So uh luke talking about six law is a great example of that, but we do have a we sort of use the addressable market as a way to sort of focus what we're doing and then we try and land it within our different emerging technologies teams to go tackle it. Now. You asked about open source communities, which are quite interesting. Um so typically when you look at an open source project, it's it's there to tackle a particular problem or opportunity. Sometimes what you actually need commercial vendors to do is when there's a problem or opportunity that's not tackled by anyone open source project, we have to put them together to create a solution to go tackle that thing. That's also what we do. And so we sort of create this bridge between red hat and our customers and multiple different open source projects. And this is something we have to do because sometimes just that one open source project doesn't really care that much about that particular problem. They're motivated elsewhere. And so we sort of create that bridge. >>We got two great uh cohorts here and colleagues parole on the on the Quantum side and you got luke on the security side. Pro I'll start with you. Quantum is also a huge mentioned IBM great leadership there. Um Quantum on open shift. I mean come on. Just that's not coming together for me in my mind, it's not the first thing I think of. But it really that sounds compelling. Take us through, you know, um how this changes the computing landscape because heterogeneous systems is what we want and that's the world we live in. But now with distributed systems and all kinds of new computing modules out there, how does this makes sense? Take us through this? >>Um yeah john's but before I think I want to explain something which is called Quantum supremacy because it plays very important role in the road map that's been working on. So uh content computers, they are evolving and they have been around. But right now you see that they are going to be the next thing. And we define quantum supremacy as let's say you have any program that you run or any problems that you solve on a classical computer. Quantum computer would be giving you the results faster. So that is uh, that is how we define content supremacy when the same workload are doing better on content computer than they do in a classical computer. So the whole the whole drive is all the applications are all the companies, they're trying to find avenues where Quantum supremacy are going to change how they solve problems or how they run their applications. And even though quantum computers they are there. But uh, it is not as easily accessible for everyone to consume because it's it's a very new area that's being formed. So what, what we were thinking, how we can provide a mechanism that you can you don't connect this deal was you have a classical world, you have a country world and that's where a lot of thought process been. And we said okay, so with open shift we have the best of the classical components. You can take open shift, you can develop, deploy around your application in a country raised platform. What about you provide a mechanism that the world clothes that are running on open shift. They are also consuming quantum resources or they are able to run the competition and content computers take the results and integrate them in their normal classical work clothes. So that is the whole uh that was the whole inception that we have and that's what brought us here. So we took an operator based approach and what we are trying to do is establish the best practices that you can have these heterogeneous applications that can have classical components. Talking to our interacting the results are exchanging data with the quantum components. >>So I gotta ask with the rise of containers now, kubernetes at the center of the cloud native value proposition, what work clothes do you see benefiting from the quantum systems the most? Is there uh you guys have any visibility on some of those workloads? >>Uh So again, it's it's a very new, it's very it's really very early in the time and uh we talk with our customers and every customers, they are trying to identify themselves first where uh these contacts supremacy will be playing the role. What we are trying to do is when they reach their we should have a solution that they that they could uh use the existing in front that they have on open shift and use it to consume the content computers that may or may not be uh, inside their own uh, cloud. >>Well I want to come back and ask you some of the impact on the landscape. I want to get the look real quick because you know, I think security quantum break security, potentially some people have been saying, but you guys are also looking at a bunch of projects around supply chain, which is a huge issue when it comes to the landscape, whether its components on a machine in space to actually handling, you know, data on a corporate database. You guys have sig store. What's this about? >>Sure. Yes. So sick store a good way to frame six store is to think of let's encrypt and what let's encrypt did for website encryption is what we plan to do for software signing and transparency. So six Door itself is an umbrella organization that contains various different open source projects that are developed by the Six door community. Now, six door will be brought forth as a public good nonprofit service. So again, we're very much basing this on the successful model of let's Encrypt Six door will will enable developers to sign software artifacts, building materials, containers, binaries, all of these different artifacts that are part of the software supply chain. These can be signed with six door and then these signing events are recorded into a technology that we call a transparency log, which means that anybody can monitor signing events and a transparency log has this nature of being read only and immutable. It's very similar to a Blockchain allows you to have cryptographic proof auditing of our software supply chain and we've made six stores so that it's easy to adopt because traditional cryptographic signing tools are a challenge for a lot of developers to implement in their open source projects. They have to think about how to store the private keys. Do they need specialist hardware? If they were to lose a key then cleaning up afterwards the blast radius. So the key compromise can be incredibly difficult. So six doors role and purpose essentially is to make signing easy easy to adopt my projects. And then they have the protections around there being a public transparency law that could be monitored. >>See this is all about open. Being more open. Makes it more secure. Is the >>thief? Very much yes. Yes. It's that security principle of the more eyes on the code the better. >>So let me just back up, is this an open, you said it's gonna be a nonprofit? >>That's correct. Yes. Yes. So >>all of the code is developed by the community. It's all open source. anybody can look at this code. And then we plan alongside the Linux Foundation to launch a public good service. So this will make it available for anybody to use if your nonprofit free to use service. >>So luke maybe steve if you can way into on this. I mean, this goes back. If you look back at some of the early cloud days, people were really trashing cloud as there's no security. And cloud turns out it's a more security now with cloud uh, given the complexity and scale of it, does that apply the same here? Because I feel this is a similar kind of concept where it's open, but yet the more open it is, the more secure it is. And then and then might have to be a better fit for saying I. T. Security solution because right now everyone is scrambling on the I. T. Side. Um whether it's zero Trust or Endpoint Protection, everyone's kind of trying everything in sight. This is kind of changing the paradigm a little bit on software security. Could you comment on how you see this playing out in traditional enterprises? Because if this plays out like the cloud, open winds, >>so luke, why don't you take that? And then I'll follow up with another lens on it which is the operate first piece. >>Sure. Yes. So I think in a lot of ways this has to be open this technology because this way we have we have transparency. The code can be audited openly. Okay. Our operational procedures can be audit openly and the community can help to develop not only are code but our operational mechanisms so we look to use technology such as cuba netease, open ship operators and so forth. Uh Six store itself runs completely in a cloud. It is it is cloud native. Okay, so it's very much in the paradigm of cloud and yeah, essentially security, always it operates better when it's open, you know, I found that from looking at all aspects of security over the years that I've worked in this realm. >>Okay, so just just to add to that some some other context around Six Law, that's interesting, which is, you know, software secure supply chain, Sixth floor is a solution to help build more secure software secure supply chains, more secure software supply chain. And um so um there's there's a growing community around that and there's an ecosystem of sort of cloud native kubernetes centric approaches for building more secure software. I think we all caught the solar winds attack. It's sort of enterprise software industry is responding sort of as a whole to go and close out as many of those gaps as possible, reduce the attack surface. So that's one aspect about why 6th was so interesting. Another thing is how we're going about it. So we talked about um you mentioned some of the things that people like about open source, which is one is transparency, so sunlight is the best disinfectant, right? Everybody can see the code, we can kind of make it more secure. Um and then the other is agency where basically if you're waiting on a vendor to go do something, um if it's proprietary software, you you really don't have much agency to get that vendor to go do that thing. Where is the open source? If you don't, if you're tired of waiting around, you can just submit the patch. So, um what we've seen with package software is with open source, we've had all this transparency and agency, but we've lost it with software as a service, right? Where vendors or cloud service providers are taking package software and then they're making it available as a service but that operationalize ng that software that is proprietary and it doesn't get contributed back. And so what Lukes building here as long along with our partners down, Lawrence from google, very active contributor in it. Um, the, is the operational piece to actually run sixth or as a public service is part of the open source project so people can then go and take sixth or maybe run it as a smaller internal service. Maybe they discover a bug, they can fix that bug contributed back to the operational izing piece as well as the traditional package software to basically make it a much more robust and open service. So you bring that transparency and the agency back to the SAS model as well. >>Look if you don't mind before, before uh and this segment proportion of it. The importance of immune ability is huge in the world of data. Can you share more on that? Because you're seeing that as a key part of the Blockchain for instance, having this ability to have immune ability. Because you know, people worry about, you know, how things progress in this distributed world. You know, whether from a hacking standpoint or tracking changes, Mutability becomes super important and how it's going to be preserved in this uh new six doorway. >>Oh yeah, so um mutability essentially means cannot be changed. So the structure of something is set. If it is anyway tampered or changed, then it breaks the cryptographic structure that we have of our public transparency service. So this way anybody can effectively recreate the cryptographic structure that we have of this public transparency service. So this mutability provides trust that there is non repudiation of the data that you're getting. This data is data that you can trust because it's built upon a cryptographic foundation. So it has very much similar parallels to Blockchain. You can trust Blockchain because of the immutable nature of it. And there is some consensus as well. Anybody can effectively download the Blockchain and run it themselves and compute that the integrity of that system can be trusted because of this immutable nature. So that's why we made this an inherent part of Six door is so that anybody can publicly audit these events and data sets to establish that there tamper free. >>That is a huge point. I think one of the things beyond just the security aspect of being hacked and protecting assets um trust is a huge part of our society now, not just on data but everything, anything that's reputable, whether it's videos like this being deep faked or you know, or news or any information, all this ties to security again, fundamentally and amazing concepts. Um I really want to keep an eye on this great work. Um Pearl, I gotta get back to you on Quantum because again, you can't, I mean people love Quantum. It's just it feels like so sci fi and it's like almost right here, right, so close and it's happening. Um And then people get always, what does that mean for security? We go back to look and ask them well quantum, you know, crypto But before we get started I wanted, I'm curious about how that's gonna play out from the project because is it going to be more part of like a C. N. C. F. How do you bring the open source vibe to Quantum? >>Uh so that's a very good question because that was a plan, the whole work that we are going to do related to operators to enable Quantum is managed by the open source community and that project lies in the casket. So casket has their own open source community and all the modification by the way, I should first tell you what excuse did so cute skin is the dedicate that you use to develop circuits that are run on IBM or Honeywell back in. So there are certain Quantum computers back and that support uh, circuits that are created using uh Houston S ticket, which is an open source as well. So there is already a community around this which is the casket. Open source community and we have pushed the code and all the maintenance is taken care of by that community. Do answer your question about if we are going to integrate it with C and C. F. That is not in the picture right now. We are, it has a place in its own community and it is also very niche to people who are working on the Quantum. So right now you have like uh the contributors who who are from IBM as well as other uh communities that are specific specifically working on content. So right now I don't think so, we have the map to integrated the C. N. C. F. But open source is the way to go and we are on that tragic Torri >>you know, we joke here the cube that a cubit is coming around the corner can can help but we've that in you know different with a C. But um look, I want to ask you one of the things that while you're here your security guru. I wanted to ask you about Quantum because a lot of people are scared that Quantum is gonna crack all the keys on on encryption with his power and more hacking. You're just comment on that. What's your what's your reaction to >>that? Yes that's an incredibly good question. This will occur. Okay. And I think it's really about preparation more than anything now. One of the things that we there's a principle that we have within the security world when it comes to coding and designing of software and this aspect of future Cryptography being broken. As we've seen with the likes of MD five and Sha one and so forth. So we call this algorithm agility. So this means that when you write your code and you design your systems you make them conducive to being able to easily swap and pivot the algorithms that use. So the encryption algorithms that you have within your code, you do not become too fixed to those. So that if as computing gets more powerful and the current sets of algorithms are shown to have inherent security weaknesses, you can easily migrate and pivot to a stronger algorithms. So that's imperative. Lee is that when you build code, you practice this principle of algorithm agility so that when shot 256 or shot 5 12 becomes the shar one. You can swap out your systems. You can change the code in a very least disruptive way to allow you to address that floor within your within your code in your software projects. >>You know, luke. This is mind bender right there. Because you start thinking about what this means is when you think about algorithmic agility, you start thinking okay software countermeasures automation. You start thinking about these kinds of new trends where you need to have that kind of signature capability. You mentioned with this this project you're mentioning. So the ability to actually who signs off on these, this comes back down to the paradigm that you guys are talking about here. >>Yes, very much so. There's another analogy from the security world, they call it turtles all the way down, which is effectively you always have to get to the point that a human or a computer establishes that first point of trust to sign something off. And so so it is it's a it's a world that is ever increasing in complexity. So the best that you can do is to be prepared to be as open as you can to make that pivot as and when you need to. >>Pretty impressive, great insight steve. We can talk for hours on this panel, emerging tech with red hat. Just give us a quick summary of what's going on. Obviously you've got a serious brain trust going on over there. Real world impact. You talk about the future of trust, future of software, future of computing, all kind of going on real time right now. This is not so much R and D as it is the front range of tech. Give us a quick overview of >>Yeah, sure, yeah, sure. The first thing I would tell everyone is go check out next that red hat dot com, that's got all of our different projects, who to contact if you're interested in learning more about different areas that we're working on. And it also lists out the different areas that we're working on, but just as an overview. So we're working on software defined storage, cloud storage. Sage. Well, the creator of Cf is the person that leads that group. We've got a team focused on edge computing. They're doing some really cool projects around um very lightweight operating systems that and kubernetes, you know, open shift based deployments that can run on, you know, devices that you screw into the sheet rock, you know, for that's that's really interesting. Um We have a cloud networking team that's looking at over yin and just intersection of E B P F and networking and kubernetes. Um and then uh you know, we've got an application platforms team that's looking at Quantum, but also sort of how to advance kubernetes itself. So that's that's the team where you got the persistent volume framework from in kubernetes and that added block storage and object storage to kubernetes. So there's a lot of really exciting things going on. Our charter is to inform red hats long term technology strategy. We work the way my personal philosophy about how we do that is that Red hat has product engineering focuses on their product roadmap, which is by nature, you know, the 6 to 9 months. And then the longer term strategy is set by both of us. And it's just that they're not focused on it. We're focused on it and we spend a lot of time doing disambiguate nation of the future and that's kind of what we do. We love doing it. I get to work with all these really super smart people. It's a fun job. >>Well, great insights is super exciting, emerging tack within red hat. I'll see the industry. You guys are agile, your open source and now more than ever open sources, uh, product Ization of open source is happening at such an accelerated rate steve. Thanks for coming on parole. Thanks for coming on luke. Great insight all around. Thanks for sharing. Uh, the content here. Thank you. >>Our pleasure. >>Thank you. >>Okay. We were more, more redhead coverage after this. This video. Obviously, emerging tech is huge. Watch some of the game changing action here at Redhead Summit. I'm john ferrier. Thanks for watching. Yeah.

>>live from Stanford University. It's the queue covering Stanford women in data science 2020. Brought to you by Silicon Angle Media. >>Yeah, yeah, and welcome to the Cube. I'm your host Sonia Category and we're live at Stanford University, covering the fifth annual Woods Women in Data Science Conference. Joining us today is new Sha Ajami, who's the director of urban water policy for Stanford. You should welcome to the Cube. Thank you for having me. Absolutely. So tell us a little bit about your role. So >>I directed around water policy program at Stanford. We focused on building solutions for resilient cities to try to use data science and also the mathematical models to better understand how water use is changing and how we can build a future cities and infrastructure to address the needs of the people in the US, in California and across the world. >>That's great. And you're gonna give a talk today about how to build water security using big data. So give us a preview of your talk. >>Sure. So the 20th century water infrastructure model was very much of a >>top down model, >>so we built solutions or infrastructure to bring water to people, but people were not part of the loop. They were not the way that they behaved their decision making process. What they used, how they use it wasn't necessarily part of the process and the assume. There's enough water out there to bring water to people, and they can do whatever they want with it. So what we're trying to do is you want to change this paradigm and try to make it more bottom up at to engage people's decision making process and the uncertainty associated with that as part of the infrastructure planning process. Until I'll be talking, I'll talk a little bit about that. >>And where is the most water usage coming from? So, >>interestingly enough, in developed world, especially in the in the western United States, 50% of our water is used outdoors for grass and outdoor spacing, which we don't necessarily are dependent on. Our lives depend on it. I'll talk about the statistics and my talk, but grass is the biggest club you're going in the US while you're not really needing it for food consumption and also uses four times more water >>than than >>corn, which is which is a lot of water. And in California alone, if you just think about some of the spaces that we have grass or green spaces, we have our doors in the in. The in the malls are institutional buildings or different outdoor spaces. We have some of that water. If we can save, it can provide water for about a 1,000,000 or two million people a year. So that's a lot of water that we can be able to we can save and use, or you are actually a repurpose for needs that you really half. >>So does that also boil down to like people of watering their own lawns? Or is the problem for a much bigger grass message? >>Actually, interestingly enough, that's only 10% of that water out the water use. The rest of it is actually the residential water use, which is what you and I, the grass you and I have in our backyard and watering it so that water is even more than that amount that I mentioned. So we use a lot of water outdoors and again. Some of these green spaces are important for community building for making sure everybody has access to green spaces and people. Kids can play soccer or play outdoors, but really our individual lawns and outdoor spaces. If there are not really a native you know landscaping, it's not something that views enough to justify the amount of water you use for that purpose. >>So taking longer showers and all the stuff is very minimal compared to no, not >>at all. Sure, those are also very, very important. That's another 50% of our water. They're using that urban areas. It is important to be mindful the baby wash dishes. Maybe take shower the baby brush rt. They're not wasting water while you're doing that. And a lot of other individual decisions that we make that can impact water use on a daily basis. >>Right, So So tell us a little bit more about right now in California, We just had a dry February was the 1st 150 years, and you know, this is a huge issue for cities, agriculture and for potential wildfires. So tell us about your opinion about that. So, >>um, the 20th century's infrastructure model I mentioned at the beginning One of the flaws in that system is that it assumes that we will have enough snow in the mountains that would melt during the spring and summer time and would provide us water. The problem is, climate change has really, really impacted that assumption, and now you're not getting as much snow, which is comes back to the fact that this February we have not received any snow. We're still in the winter and we have spring weather and we don't really have much snow on the mountain. Which means that's going to impact the amount of water we have for summer and spring time this year. We had a great last year. We got enough water in our reservoirs, which means that you can potentially make it through. But then you have consecutive years that are dry and they don't receive a lot of water precipitation in form of snow or rain. That will become a very problematic issue to meet future water demands in California. >>And do you think this issue is along with not having enough rainfall, but also about how we store water, or do you think there should be a change in that policy? >>Sure, I think that it definitely has something also in the way we store water and be definitely you're in the 21st century. We have different problems and challenges. It's good to think about alternative ways off a storing water, including using groundwater sources. Groundwater as a way off, storing excess water or moving water around faster and making sure we use every drop of water that falls on the ground and also protecting our water supplies from contamination or pollution. >>And you see it's ever going to desalination or to get clean water. So, interestingly >>enough, I think desalination definitely has worth in other parts of the world, and then they have. Then you have smaller population or you have already tapped out of all the other options that are available to you. Desalination is expensive. Solution costs a lot of money to build this infrastructure and also again depends on you know, this centralized approach that we will build something and provide resources to people from from that location. So it's very costly to build this kind of solutions. I think for for California we still have plenty of water that we can save and repurpose, I would say, and also we still can do recycling and reuse. We can capture our stone water and reuse it, so there's so many other, cheaper, more accessible options available before you go ahead and build a desalination plants >>and you're gonna be talking about sustainable water resource management. So tell us a little bit more about that, too. So the thing with >>water mismanagement and occasionally I use also the word like building resilient water. Future is all about diversifying our water supply and being mindful of how they use our water, every drop of water that use its degraded on. It needs to be cleaned up and put back in the environment, so it always starts from the bottom. The more you save, the less impact you have on the environment. The second thing is you want to make sure every trouble wanted have used. We can use it as many times possible and not make it not not. Take it, use it, lose its right away, but actually be able to use it multiple times for different purposes. Another point that's very important, as actually majority of the water they've used on a daily basis is it doesn't need to be extremely clean drinking water quality. For example, if you tell someone that you're flushing down our toilets. Drinkable water would surprise you that we would spend this much time and resources and money and energy to clean that water to flush it down the toilet video using it. So So basically rethinking the way we built this infrastructure model is very important, being able to tailor water to the needs that we have and also being mindful of Have you use that resource? >>So is your research focus mainly on California or the local community? We actually >>are solutions that we built on our California focus. Actually, we try to build solutions that can be easily applied to different places. Having said that, because you're working from the bottom up, wavy approach water from the bottom up, you need to have a local collaboration and local perspective to bring to their to this picture on. A lot of our collaborators have been so far in California, we have had data from them. We were able to sort of demonstrate some of the assumptions we had in California. But we work actually all over the world. We have collaborators in Europe in Asia and they're all trying to do the same thing that we dio on. You're trying to sort of collaborate with them on some of the projects in other parts of the world. >>That's awesome. So going forward, what do you hope to see with sustainable water management? So, to >>be honest with you, I would often we think about technology as a way that would solve all our problems and move us out of the challenges we have. I would say technology is great, but we need to really rethink the way we manager resource is on the institutions that we have on there. We manage our data and information that we have. And I really hope that became revolutionized that part of the water sector and disrupt that part because as we disrupt this institutional part >>on the >>system, provide more system level thinking to the water sector, I'm hoping that that would change the way we manage our water and then actually opens up space for some of these technologies to come into play as >>we go forward. That's awesome. So before we leave here, you're originally from Tehran. Um and and now you're in this data science industry. What would you say to a kid who's abroad, who wants to maybe move here and have a career in data science? >>I would say Study hard, Don't let anything to disk or do you know we're all equal? Our brains are all made the same way. Doesn't matter what's on the surface. So, um so I and encourage all the girls study hard and not get discouraged and fail as many times as you can, because failing is an opportunity to become more resilient and learn how to grow. And, um and I have, and I really hope to see more girls and women in this in these engineering and stem fields, to be more active on, become more prominent. >>Have you seen a large growth within the past few years? Definitely, >>the conversation is definitely there, and there are a lot more women, and I love how Margot and her team are sort of trying to highlight the number of people who are out there. And working on these issues because that demonstrates that the field wasn't necessarily empty was just not not highlighted as much. So for sure, it's very encouraging to see how much growth you have seen over the years for sure >>you shed. Thank you so much. It's really inspiring all the work you do. Thank you for having me. So no, Absolutely nice to meet you. I'm Senator Gary. Thanks for watching the Cube and stay tuned for more. Yeah, yeah, yeah.

>> Narrator: Live from Las Vegas, it's the CUBE (light electronic music) covering Interconnect 2017. Brought to you by IBM. >> So, my first question for you is, as we digitize our worlds with business, the value chains and all the processes are changing, there's a new value equation model around digital business. What's your view on the digital business value creation equation? >> Sure, John, thank you for having me here, today, and Dave, as well. Thank you for having me. So, I think that automation in combination with cognitive computing, AI, machine learning, is really going to revolutionize the way we work, the way we interact, and it's going to create new experiences for people, experiences that we don't even know that exist in the future. They're going to be real value, and that value is not just about cost take-up, that value's going to be around innovation, that value's going to be around the combination of block chain, machine learning, ubiquitous computing, and I think that this is going to create new industries, new business models, that we could take really advantage of in many different industries. >> One of the cool things that's happening that I like in the computer science, and how society in general now is seeing cloud computing, which has been around for awhile getting full-steam ahead, big data industry evolving very rapidly, and what's kind of pulling them together in this gravity is machine learning, data, cognitive, iterative things, and AI is kind of the over-arching, you know, sizzle, if you will. So, the sci-fi aspect of AI. Everyone can relate to some sort of mental image of AI. You know, robots taking over the world, to automated things just make us smarter, augmented reality, what-not. But iterative things, and data science, that's connecting the power of the cloud with data is changing the game. So, one little change in a value equation, in a company, could change their business model. >> Absolutely. >> How do you rationalize that with your customers (laughing)? Hey, you know, full steam ahead, or slow down, it depends. What's your perspective on that? >> So, it's interesting you mention about science fiction, right, because science fiction inspired robots and automation for centuries, now. But, the reality, today, is that we are already using automation. You know, it's been used ubiquitously across production lines, manufacturing, logistics. So, we've started this journey, already, for many, many years. I think, quite rightfully, like you described in the cloud world, what we're seeing now, in automation, you're combining Artificial Intelligence, you're combining cognitive computing, and what that will do is it will create new value for companies out there, right. That new value is going to be about creating new industries, creating new data, and in the IOT space, it's going to create a new level of intelligence for us that's really going to change the experience that we could deliver. >> So, I've said this before, the greatest chess player in the world is not a machine, it's not a supercomputer, it's a combination of humans and computers. And, so to the point, we were talking off camera, machines hae always replaced humans. It's now cognitive functions are being augmented. And so, it seems like the scarce resources, the creativity to combine innovations. For decades, we've marched to the cadences of Moore's Law. >> John: Yeah. >> Right. The innovation is not coming from Moore's Law anymore. You know, whether or not it's tapering. We can argue, let's assume it is for a moment. >> Reinventions. >> So, where's the innovation coming from? Clearly the innovation curve's not slowing down. >> Dave: So, what's IBM's point of view on that innovation and where it comes from? >> So, you started by talking about robots and machines and how it's kind of changing jobs and, let's say, taken over jobs. The reality is that only a small percentage of work, five to 10%, will be fully automated in the future, because we've seen this throughout history. Technology advances in the last 20 years has created new professions. You know, 25% of the work type and profession in the last 20 years are new type of work. And John, you were mentioning about the ATM machine just a couple of minutes ago. >> Yep. >> The ATM machine actually has created a new economy. >> John: It was supposed to kill the teller. >> Yeah. >> It kind of did, but it created more jobs because more branches were opening up. >> Exactly, more branches and new ways of interacting, and new, and so on. Now, you have mobile apps, but actually you have to develop applications which you never had to do in the past before, and exactly the same with automation. We're going to have, and robotics and Internet things, combined them together, we'll create a new economy, and the value of that economy is going to be in a couple of areas. One, I think one of the fundamental changes is that our work type, the type of work we do, is going to be automated, about 30% of our work type is going to be automated in certain industries, industries which are highly tasked orientated, highly manual orientated, highly data orientated. They'll all change, that's the reality of it. But, that's also going to create a new type of work, a new profession and people will be up-skilling to that. But, our prediction is that, you know, in the next few years we're going to see between one to one and a half percent GDP increase as a result of cognitive computing and AI. >> Incremental. >> Incremental, incremental, so yes, there'll be some changes of jobs, changes in profession, but incremental, they'll be increasing, and that, for the aging population issue that we know very well, is going to really help to boost a lot of economy out there. >> That scares people, too, this whole notion of job loss and, again, we were talking about before camera. It's not so much controversial, it's more education, both educating people on what the narrative is of the future scenario. >> Exactly. >> But also, education for people to get the new skill. I mean, the stat after the stat, but it's high percentage of jobs are even created yet. So, you know, cross-disciplinary education in higher eds changing, but the skills gap is a huge issue. So, how do you talk to that point because, certainly, that's an area we heard on stage today. Mark Benioff and Ginni Rometty talking about, you know, having a societal impact, and having a mission, education, is a big one. What's your thoughts? >> Absolutely. >> I mean, so I think it starts right from the way we teach, because you can't necessarily always teach the future, but what you can do is you could prepare for the future. So, we need to start teaching our children to our graduates who start in our companies with new skills around creativity, right. High emotional intelligence. I believe that a robot is never going to be able to manage emotional intelligence, right. So, how do use more emotional intelligence? How do we provide more discipline around education? How do we provide them vital skills? >> Critical thinking. >> Critical thinking, absolutely. You know, and science, but also, these Artificial Intelligence going to age human being, you know, it's going to help us discover new remedies for problems that we have today in our society, problems that we have in healthcare, problems that we have in political systems, you know, which we are seeing now and, hopefully, provide more confidence in our system because of the data and intelligence that we see. >> So, now, I've got to throw in the augmented reality because AI is obviously kind of a concept that people are getting. It's not clear, yet, what that is. What really is AI? Well, that chapter will be written, certainly as it evolves. But, augmented reality is happening. So, IoT, you can have googles on that look at meters and get new data, that's not even there. You can do automation around getting predictive analytics around machine, industrial IoT, these kinds of things. You're seeing consumer devices having augmented reality. >> Shamayum: Yep. >> That's here, right. That's here and now. So, how do you advise your clients and customers, the big IBM customers you service, to prepare for augmented reality? Because, is there a playbook? Are they nodding their heads, are they going, "Oh!," face palm. Or, I mean, what's happening? >> So, augmented reality is here and it's here to stay. The difference between augmented reality, now, or if you looked at it, let's say, five years ago when we had Google glasses. One was hype versus reality. One was a use case, now, where actually is transformational, and it's having real impact in ROI. Like the example you gave around manufacturing, or how you use it in logistics, when you are looking at airlines, and how you look at training people. Now you could train people using augmented reality and speed the level of adoption required or the time required to skill people. And then in the past, we never had that. Is there a playbook? I don't think there is a playbook, John, because I think the use cases are so diverse. But I think what we really need to do is go back to fundamental of consulting. What do we look for, you know, in business problem solving? We look for problems. We analyze that problem through design thinking, or whatever methodology we use. We look up what the impact. Is it speed, quality, and cost? And, if we can answer these questions, speed, quality, and cost, and the human impact unto it, those are the factors that's going to determine what are the use case of augmented reality that's really going to transform, and have impact, in industries. >> I find it interesting, too, you mentioned that the old way of doing things, is not going to be there, but the older way of doing software was general purpose, computing, and software. Buy a shrink wrap package, load it, does some function. Now, the composability of APIs and micro services allow for common building blocks. >> Yep. >> Son ow , essentially every solution is custom. >> Shamayum: Yes. >> So, you have a diverse use case. Remember, beauty is in the eye of the beholder. So, that's how it is in the enterprise. So, that's a reality. So, with that as kind of a backdrop, what are some of the cool things that you're working on now that you can point to and say, "These are examples of the kinds of journeys customers are going through." It could be a crazy idea that's implemented or a something, a great idea. Share a story about some of the highlights, some of this new way of building apps, new way of being agile, new way of discovering value creation. >> Sure, so you're absolutely right. You know, we're moving into a world of consumable services, if I could describe it that way, API services, micro-services, pulling data from different sources, augmenting your data source, having functions that you get from your competitors, even, to augment the capability that you want and to create new business processes. And I think we'll see more and more of this, and, you know, I was speaking to a bank, even last week, and in Abu Dhabi where they're saying, "What's the future of a bank? "Do I need a processing bank? "Do I need a back office anymore? "Do I need a branch? "Can it not just be a virtual bank? "Can I not just connect to fin-tech to provide my services, "and I have the customer and own the customer?" So, I think there's an advancement in terms of thinking, now, and that thinking is possible because the possibilities are endless and we have never seen more access to technology at relatively low cost, even, than ever before, and, also, open source is making it more possible, I think. Open source has given power to the people and companies to have world-class technology, you know, combined with IBM technology to provide, you know, real great value. So... >> Oh, go ahead, please carry on. >> Just, in terms of use case. Another example is that I recently sent a use case around, "Know your customer." You know, one example was, you know, opening up accounts for high-worth customers could take months and months to make sure the security checks, and so... You may have an account, but in terms of fully transactional, it takes months. Now, using machine learning, you go and search over a million databases and look for a million different patterns and make a recommendation to your work advisor to see what kind of customer you're going to be. You know, by analyzing movies, watching four movies that you love, we could predict, by 95%, what all the movies that you're going to love in the rest of your life. Those are the use cases I've seen. I just find it fascinating. >> Netflix is doing... They're getting all the data from me. >> Yes, yes. >> An arbitraging out the back door. >> Recommending books, I mean it's getting more and more. >> I want to own my own data. That's what Ginny was saying on stage, we should own our own data. >> Yeah, and there's certainly consumers out there who want to own their data and I think there's going to be this shift where you can have digital ident in the future where you own the data and could like trading your data. So, instead of just giving your data, you could start monetizing your own data, and saying what kind of information do you want, and what kind of experience do you want? You know, how do you want to trade? Who do you want to trade with? Do you want to share the data with your family? With your friends? With your business partner? And you become the owner of data, and that certainly an area that we're seeing a movement to, but, also, it's going to help with the identity. Your identity will be known only to you, not to service providers. >> I think you're on to something, and one of the things we were just talking with Don T was, the block chain, and The Block Chain Revolution, his new book, is when you get the transactional cost of business reduced, you mentioned that virtual bank, makes total sense. Why should I spend all this money to have a company? I can reduce my transactional cost of doing business and still provide great value. >> Well, I don't know. I mean, you talk about the future's hard to predict, sometimes, but the bank in Abu Dhabi, right. I mean, you see banks, we talk to them all the time, re-imagining the banking experience, but not necessarily eliminating the physical. >> Sha: Absolutely. >> And so, you know, to me it's fascinating. Like the list of things that machines can't do, that humans can changes, seemingly, every year, whether it's climbing stairs, or even autonomous vehicles, five years ago nobody thought was... I was and IBM conference, not that long ago, five years ago, they said it's 25 years before you'll see that. Then, wow, just overnight. >> Self-starting cars is another prediction. >> So, do your clients... How much do they try to, you know, skate to the puck, which seems to be a harder endeavor versus saying, you know, "Okay, we can apply this today, "and save money, or tap a new business opportunity." >> So, you make some great points here. The first point I'd just like to elaborate a little bit more which you mentioned about the physical and the digital. >> Yeah, right. >> Which you might, in your example was the branch. What's the role of the branch if you have a fully digital bank in the future? We still need a branch. And, why do we need a branch? Because in the branch, the branch is going to be different in the future. We all hate cueing up in the branch. We all hate going to a generic person that's says, "Can I help you?" >> John: What's your account number? >> "What's your account number?" >> Exactly. >> No, I'm John. >> Come on, you should know me. >> You should know as soon as I walk in, you should know, you know, what are the three things that I'm looking for. You should know how long I've been a customer, what my family is. >> How many Twitter followers you have. If you're an influencer. (laughter) >> Exactly, exactly. And more importantly, you should know that I love speaking to an expert. I don't want to speak to a generic person. So, the future bank is going to be when you walk into your bank, you're going to sit there in a room, in a very nice room, you're going to be in a screen, you're going to talk to someone who's an expert, who knows everything about you, through video conference. You can even order a coffee that someone comes in your room. You don't feel that it's just virtual. You have some emotional connections, as well. You'll have digital printers in there. You can connect. You have a different experience and by the time you go out, your app has already been updated with the loan that you wanted or the mortgages that you wanted. And then, coming back to the point that John and I were talking about, the consumer services, well, actually I might want my loan from one bank, my mortgage from another bank, and my car account from one bank, and I should be able to trade between that. >> Dave: Right. >> So, there's that connection, whether physical or digital, and then different service providers. I think there will be a mash-up if I think of it that way. >> It's that level& of intimacy that has been lacking for so many years in that example, financial services, which it seems like cognitive can help close that gap. >> Yeah, yeah, and cognitive absolutely can because cognitive is now, the technology's here. I think it's advanced, so much is here. The use cases are amazing and you heard about the use cases in healthcare and in customer services and aging assist, which is helping people with self-application repair. So, I think the advancement is here. I mean, the possibilities are huge. We just need to connect those dots together in order to create those new use case. >> And they did model that's come out of that conversation that is domain specific data, and you guys talk about that as verticals. But, you know, that's important because you need to specialism of the data. >> Sha: That's correct. >> But you also want the horizontally scalable cloud, as well. So that's the data challenge right there. >> Absolutely, absolutely. But one thing that's going to be critical, I think, even in the future, is that industry knowledge and how you use that industry knowledge to augment your data. How do you find that, you know... Computers always give you those patterns. How do you interpret that pattern, and how do you create that new experience? That's where the human value is. >> So, you know, we talked yesterday. You're in the consulting side of the business, but 60% of IBM's business remains services. But a key value that you bring to the marketplace is the ability, at least in concept, to codify those services into software. Talk about how you're doing that, and to the degree to which you're succeeding. >> So, we started a conversation in automation. So, if I go back to that. In automation, every client is thinking about automation. Every client is experimenting with automation now, to some level. And, what we have done with our services is that we create frameworks, maturity assessments, business component modeling. So now, what we can do when we go into a bank, we go into an example bank, we could say, "Hey, Mr. Customer, I've done it "with these 30 banks. "I know what does best-in-class bank look like. "You might not, necessarily, and trying to answer your initial question, You know, what's the roadmap look like. "You may want to go over here, "but your level of maturity's here." So, how do you get to that level of maturity, your kind of aspiration, and we could help with those tools and methods and our assessment capability and strategy engagement framework that we bring with the clients. Also, we don't just look at banks. Because, if you're a bank, banks are interesting, but you may want to look at retailers. You might want to look at pharmaceutical companies. You might want to look at Starbucks and all the people that around here, what are they doing, in terms of innovation, so you can bring all the innovation on to this and look at business functions. You know, what does the best-in-class logistic look like? What is the best-in-class back off function look like outside of my industry? And that's the kind of codifying that we have the knack of solving things we can bring to the market. >> Can I even jump industries because digital allows me to actually traverse horizontally, as John was saying. >> And the threat is there. You know, the threat is live today, to be Uber-ized or be a Uber. You know, you decide. So, you are going to jump through these industries because you have now a global platform which allows you to transform your industry, and jump from one to another, and monetize what you have very, very fast, and the barrier to entry is lower than ever before, not just because of technology, but because how industry works on the consumers' demand. Shamayum, than so much for coming on. Great insight. Thanks for sharing. Love that content. Really good insight. >> Pleasure. And the future's here. >> Thank you very much. The future's here, absolutely. Thank you very much. >> The future's here, now. This is the CUBE bringing you all the action, here, live in Las Vegas. Stay with us. We've got a lot more today to come, and all day tomorrow. We'll be right back. I'm John Furrier with Dave Vellante. (light electronic music)