>> As to the adoption challenges, I wasn't clear on where that should go. I mean, I'm happy to just throw it out there. >> You'll again punch it back to me, right? >> Okay. >> Question comes to me and I'm going to pass the ball to Greg to connect the thread on one backbone is needed. Emphasizing Cat 9K that we just talked about. >> And same thing for the last question. The routes to market? >> Yes. >> Okay. >> Yes. >> Great. So we'll use that program for everything. Perfect. >> Masum, could you... Yeah, right there. So mark your place and try not to move that seat. That's it. Now, come forward just a tad, just a tad. There we go. Yeah. Okay, that's fine. Okay Alex, we're good. >> Okay. So Leonard don't leave after this 'Cause I'm going to do my outro. I'm going to do that as a separate asset, okay? >> You bet. >> Okay, great. So guys just it'll be five, four, three, silent, two, one. And then just follow my lead, okay? All right, Alex, you're ready? Masum and Greg, you're ready? >> Ready. >> Ready. >> Okay, here we go on me. On Dave in five, four, three, (beep). Okay, we're back. Digging into the infrastructure to make hybrid work possible. High performance, cost effective, scalable, and secure. That's what it's all about. And so far, we've covered the rapid migration to Wi-Fi 6E technology, and the role that switching is going to play. And now we're going to get into Private 5G and to do that, let's welcome Masum Mir, who is Vice President, and General Manager of Mobile, Cable and IoT business at Cisco. And Greg Dorai who is the Vice President of Product Management for the networking experiences group at Cisco. He's responsible for Catalyst access, that whole portfolio, Enterprise 5G, Cisco DNA Spaces, Cisco ISE, a lot of stuff there Greg. And gentlemen, welcome. >> Dave thank you for having us. >> Yeah, our pleasure. Masum let's start with you on the topic of Private 5G. What do we need to know about that? And more specifically, what's unique about Cisco's Private 5G? >> So most importantly, delivering Private 5G in enterprise terms, that's super important to look at 5G. Many of our peer groups might have got it wrong. We're looking at Private 5G with the lens of enterprise, what enterprise really needs. Is 5G going to come and displace a lot of existing technology, or is it going to help augment the technology that enterprise. It has an excellent the digitization journey. I wanted to start Dave with the basic premise of hybrid work. And what hybrid work really means. Is it only for knowledge worker, or is it for all workers? So we strongly believe hybrid work needs to empower all workers. It's not only connecting remote workers but also bringing people, things and space together. And we strongly believe the combination of Wi-Fi 6 and 5G for private network is going to accelerate that journey bringing people, things and space together in a very, very cohesive way. Why our offer is so unique? We are going to create a continuum. Enterprises don't have to make a hard choice. They will be using Wi-Fi technology and 5G technology hand in hand without creating a disruption on their policy and identity systems. They don't have to rethink, "Do I have to go and build a new backbone?" Is a common backbone that will support both Wi-Fi as well as 5G. Most importantly, delivering this entire offer as a service with the ease of consumption, ease of operation, and a trusted environment that they can put their mission critical workload on. >> Now, I like it. So a couple takeaways there. I mean, it's inclusive of all workers not just knowledge workers, non disruptive, everybody loves to hear that. And of course, it has service model as key Masum, let me stay with you. I mean, we can't wait for 5G, right? It's lightning fast, it got super low latency, very high bandwidth. So that's what everybody's excited about. The question though is, 5G gets introduced, yeah it's going to power things like IoT networks. Is that going to replace Wi-Fi and legacy wired broadband? >> Absolutely not. So we see Private 5G as an augmentation to the enterprise on top of Wi-Fi. Wi-Fi as you heard in the previous conversation, Wi-Fi is bringing more capability with Wi-Fi 6 and Wi-Fi 6E. And 5G is going to be yet another augmentation. Wi-Fi and 5G will coexist within enterprise for many years to come. I would like my friend, Greg to talk a little bit about this continuum. Greg? >> Yeah, I think it's sort of like, I like to say it's an and not an or. Because there's enough use cases out there which require spectrum. And you know, spectrum is a constraint. So you have Private 5G, your Wi-Fi 6, and both offer opportunities. So for example, in an indoor carpeted setting where you're basically connecting your phone for basic browsing, or connecting your laptop, Wi-Fi is sufficient. But if it's a process automation factory where you need seven nines of reliability, Private 5G is the better technology. Similarly outdoor, large areas, it's probably Private 5G, right? 'Cause you can have easy handoff between public and private. So it's use case driven. And once it's use case driven, it's going to be an or because there's so many next-gen use cases. Whether it's AR VR, drones, you know, self-driving cars you name it, right? And so I think these two technologies, 5G and Wi-Fi 6E is going to work hand in hand to deliver awesome outcomes for our customers. >> Yeah. And just the data volumes are going to be incredible. We always talk about the data volumes. You ain't seen nothing yet is what I always say. But the thing is every new tech that's introduced into the enterprise, you can almost be certain that it's going to bring adoption challenges. And not only that, it also is going to bring changes in the way you do things. And that brings new complexities from an operational standpoint. So my question is, how are you addressing this with the introduction of 5G? >> Dave, this is a fantastic question. And this is why we have spent, me and Greg have spent tremendous amount of time to create continuum. I'll start with the foundation first, backbone. So we have been building this enterprise backbone supported with wired connection as well as Wi-Fi connection. We wanted to make sure that as Private 5G comes within enterprise, you don't have to rethink and reimagine your backbone. It's the common backbone that will support what Wi-Fi, Wi-Fi 6, Wi-Fi 6E, as well as Private 5G. You're rest assured that it is the same backbone that we have heard in the previous section on the Cat 9K that will also support a Private 5G access. The second aspect of Private 5G is as you build any new technology into enterprise often time we get into this trap. To get to an outcome, we move fast and we create a silo. And then that silo operation creates barriers to mainstream it. So upfront, we have to think about not creating another silo. And how we are doing it. Number one, is a device that can connect into Wi-Fi network or a Private 5G network. You don't have to reimagine or rethink how I'm going to manage the identity. We'll create continuum with a common identity across the Wi-Fi access or 5G access in the same environment. The second aspect of that is how are we going to retain all our staff? Our enterprise staff is well trained with Wi-Fi technology and wired technology. Now 5G comes with tremendous amount of value and benefit. But it also comes with inherent technology complexity, learning curve problem. This is where our simple to consume, simple to operate model of SaaS comes to play. That we're going to take all those complexity away. It is a cloud delivered service. So enterprise don't have to go through this massive learning curve adopting this technology. Last but not least, on how we are going to manage your capital. Any new technology and enterprise often time, you need huge amount of upfront investment to adopt the technology to get to the other side of getting the outcome. So again, our business model of SaaS will allow enterprise to adopt this new technology and pay as your grow model to meet with enterprise needs. Finally, I also wanted to pass to Greg to touch a little bit more on how we are thinking about this common identity across any access in the enterprise. Greg, to you. >> So we thought about it in two different ways. One is, a lot of enterprises today use our identity and secure management platform. We call it ISE, Cisco ISE platform. And so, years and years of policy and identities, and which access servers, radio servers they use et cetera, are plugged in already into our ISE, right? So, if you can share that with this Private 5G as a service infrastructure that Masum's been building, we think we'll be able to create that bridge. Because we are not forcing enterprises to create new identities or new policies. So that's sort of step one to make it easier. We also thought through so something where in the case of a public 5G network, for example. It's very convenient because you take your phone out of your pocket and it's connected to the network, right? Versus for wifi, you have to log into an SSID in your hotel, or in your home, and in home, it's automatic. But that's that login process that creates friction. And that's a problem because then you can't be seamless. So we initiated what we call as open roaming, right? Like that's a identity federation that we first created between identity owners. Could be carriers, could be anything, right? Anyone who owns an identity. And they will share with venues. And so if the sharing happens, then that onboarding can be automatic. And once onboarding is automatic, then it's easy to pass off between Wi-Fi and 5G. And so that's again, another way in which you can lower the adoption barriers 'cause you share across public Private 5G and Wi-Fi networks. So these are two concrete examples of how we thought about lowering the barriers of adoption as we enter into this heterogeneous world. >> Nice, I can't wait. Let's talk about how this thing, scales in the go to market. What are the most likely, or maybe preferred, or obvious routes to market for Private 5G from Cisco? >> So Dave stay tuned right when they announce more about it. But I can also assure you that access to this spectrum is a challenge for many enterprises when it comes to cellular technology. In some countries there are more spectrum accessible by enterprise. In many countries, that's not the case. So we have thought through very carefully that how do we bring this offer to the market partnering with many service providers and mobile operators. Where in countries where you don't have direct access to the spectrum, our partnership with mobile operators, that you will hear more about as we come to Mobile World Congress, is going to allow our enterprise to consume this technology. even if they don't have the spectrum. In the places where the enterprise might have spectrum access, we'll also in our manage service providers to hide the complexity of the new technology on top of our SaaS services, or cloud delivered services. This is the augmentation with the partnership with manage service providers and mobile operators that will ease this journey for enterprises. Our most important primitive in this journey is to keep it simple for enterprise, make it intuitive, and trust it from day one. >> Outstanding. Okay, Masum, Greg, thanks so much. It was great to have you guys on. I really appreciate your time. >> Thank you. >> Thank you. >> In a moment, I'll be back with some closing thoughts and an opportunity for you to actually see this technology in action and talk to the experts directly. Keep it right there.

momentum is gathering [Music] business is evolving more and more quickly moving through one transformation to the next because change never stops it only accelerates this is a world that demands a new kind of compute deployed from edge to core to cloud compute that can outpace the rapidly changing needs of businesses large and small unlocking new insights turning data into outcomes empowering new experiences compute that can scale up or scale down with minimum investment and effort guided by years of expertise protected by 360-degree security served up as a service to let it control own and manage massive workloads that weren't there yesterday and might not be there tomorrow this is the compute power that will drive progress giving your business what you need to be ready for what's next this is the compute power of hpe delivering your foundation for digital transformation welcome to accelerating next thank you so much for joining us today we have a great program we're going to talk tech with experts we'll be diving into the changing economics of our industry and how to think about the next phase of your digital transformation now very importantly we're also going to talk about how to optimize workloads from edge to exascale with full security and automation all coming to you as a service and with me to kick things off is neil mcdonald who's the gm of compute at hpe neil always a pleasure great to have you on it's great to see you dave now of course when we spoke a year ago you know we had hoped by this time we'd be face to face but you know here we are again you know this pandemic it's obviously affected businesses and people in in so many ways that we could never have imagined but in the reality is in reality tech companies have literally saved the day let's start off how is hpe contributing to helping your customers navigate through things that are so rapidly shifting in the marketplace well dave it's nice to be speaking to you again and i look forward to being able to do this in person some point the pandemic has really accelerated the need for transformation in businesses of all sizes more than three-quarters of cios report that the crisis has forced them to accelerate their strategic agendas organizations that were already transforming or having to transform faster and organizations that weren't on that journey yet are having to rapidly develop and execute a plan to adapt to this new reality our customers are on this journey and they need a partner for not just the compute technology but also the expertise and economics that they need for that digital transformation and for us this is all about unmatched optimization for workloads from the edge to the enterprise to exascale with 360 degree security and the intelligent automation all available in that as a service experience well you know as you well know it's a challenge to manage through any transformation let alone having to set up remote workers overnight securing them resetting budget priorities what are some of the barriers that you see customers are working hard to overcome simply per the organizations that we talk with are challenged in three areas they need the financial capacity to actually execute a transformation they need the access to the resource and the expertise needed to successfully deliver on a transformation and they have to find the way to match their investments with the revenues for the new services that they're putting in place to service their customers in this environment you know we have a data partner called etr enterprise technology research and the spending data that we see from them is it's quite dramatic i mean last year we saw a contraction of roughly five percent of in terms of i.t spending budgets etc and this year we're seeing a pretty significant rebound maybe a six to seven percent growth range is the prediction the challenge we see is organizations have to they've got to iterate on that i call it the forced march to digital transformation and yet they also have to balance their investments for example at the corporate headquarters which have kind of been neglected is there any help in sight for the customers that are trying to reduce their spend and also take advantage of their investment capacity i think you're right many businesses are understandably reluctant to loosen the purse strings right now given all of the uncertainty and often a digital transformation is viewed as a massive upfront investment that will pay off in the long term and that can be a real challenge in an environment like this but it doesn't need to be we work through hpe financial services to help our customers create the investment capacity to accelerate the transformation often by leveraging assets they already have and helping them monetize them in order to free up the capacity to accelerate what's next for their infrastructure and for their business so can we drill into that i wonder if we could add some specifics i mean how do you ensure a successful outcome what are you really paying attention to as those sort of markers for success well when you think about the journey that an organization is going through it's tough to be able to run the business and transform at the same time and one of the constraints is having the people with enough bandwidth and enough expertise to be able to do both so we're addressing that in two ways for our customers one is by helping them confidently deploy new solutions which we have engineered leveraging decades of expertise and experience in engineering to deliver those workload optimized portfolios that take the risk and the complexity out of assembling some of these solutions and give them a pre-packaged validated supported solution intact that simplifies that work for them but in other cases we can enhance our customers bandwidth by bringing them hpe point next experts with all of the capabilities we have to help them plan deliver and support these i.t projects and transformations organizations can get on a faster track of modernization getting greater insight and control as they do it we're a trusted partner to get the most for a business that's on this journey in making these critical compute investments to underpin the transformations and whether that's planning to optimizing to safe retirement at the end of life we can bring that expertise to bayer to help amplify what our customers already have in-house and help them accelerate and succeed in executing these transformations thank you for that neil so let's talk about some of the other changes that customers are seeing and the cloud has obviously forced customers and their suppliers to really rethink how technology is packaged how it's consumed how it's priced i mean there's no doubt in that to take green lake it's obviously a leading example of a pay as pay-as-you-scale infrastructure model and it could be applied on-prem or hybrid can you maybe give us a sense as to where you are today with green lake well it's really exciting you know from our first pay-as-you-go offering back in 2006 15 years ago to the introduction of green lake hpe has really been paving the way on consumption-based services through innovation and partnership to help meet the exact needs of our customers hpe green lake provides an experience that's the best of both worlds a simple pay-per-use technology model with the risk management of data that's under our customers direct control and it lets customers shift to everything as a service in order to free up capital and avoid that upfront expense that we talked about they can do this anywhere at any scale or any size and really hpe green lake is the cloud that comes to you like that so we've touched a little bit on how customers can maybe overcome some of the barriers to transformation what about the nature of transformations themselves i mean historically there was a lot of lip service paid to digital and and there's a lot of complacency frankly but you know that covered wrecking ball meme that so well describes that if you're not a digital business essentially you're going to be out of business so neil as things have evolved how is hpe addressed the new requirements well the new requirements are really about what customers are trying to achieve and four very common themes that we see are enabling the productivity of a remote workforce that was never really part of the plan for many organizations being able to develop and deliver new apps and services in order to service customers in a different way or drive new revenue streams being able to get insights from data so that in these tough times they can optimize their business more thoroughly and then finally think about the efficiency of an agile hybrid private cloud infrastructure especially one that now has to integrate the edge and we're really thrilled to be helping our customers accelerate all of these and more with hpe compute i want to double click on that remote workforce productivity i mean again the surveys that we see 46 percent of the cios say that productivity improved with the whole work from home remote work trend and on average those improvements were in the four percent range which is absolutely enormous i mean when you think about that how does hpe specifically you know help here what do you guys do well every organization in the world has had to adapt to a different style of working and with more remote workers than they had before and for many organizations that's going to become the new normal even post pandemic many it shops are not well equipped for the infrastructure to provide that experience because if all your workers are remote the resiliency of that infrastructure the latencies of that infrastructure the reliability of are all incredibly important so we provide comprehensive solutions expertise and as a service options that support that remote work through virtual desktop infrastructure or vdi so that our customers can support that new normal of virtual engagements online everything across industries wherever they are and that's just one example of many of the workload optimized solutions that we're providing for our customers is about taking out the guesswork and the uncertainty in delivering on these changes that they have to deploy as part of their transformation and we can deliver that range of workload optimized solutions across all of these different use cases because of our broad range of innovation in compute platforms that span from the ruggedized edge to the data center all the way up to exascale and hpc i mean that's key if you're trying to affect the digital transformation and you don't have to fine-tune you know be basically build your own optimized solutions if i can buy that rather than having to build it and rely on your r d you know that's key what else is hpe doing you know to deliver things new apps new services you know your microservices containers the whole developer trend what's going on there well that's really key because organizations are all seeking to evolve their mix of business and bring new services and new capabilities new ways to reach their customers new way to reach their employees new ways to interact in their ecosystem all digitally and that means app development and many organizations of course are embracing container technology to do that today so with the hpe container platform our customers can realize that agility and efficiency that comes with containerization and use it to provide insights to their data more and more that data of course is being machine generated or generated at the edge or the near edge and it can be a real challenge to manage that data holistically and not have silos and islands an hpe esmerald data fabric speeds the agility and access to data with a unified platform that can span across the data centers multiple clouds and even the edge and that enables data analytics that can create insights powering a data-driven production-oriented cloud-enabled analytics and ai available anytime anywhere in any scale and it's really exciting to see the kind of impact that that can have in helping businesses optimize their operations in these challenging times you got to go where the data is and the data is distributed it's decentralized so i i i like the esmerel of vision and execution there so that all sounds good but with digital transformation you get you're going to see more compute in in hybrid's deployments you mentioned edge so the surface area it's like the universe it's it's ever-expanding you mentioned you know remote work and work from home before so i'm curious where are you investing your resources from a cyber security perspective what can we count on from hpe there well you can count on continued leadership from hpe as the world's most secure industry standard server portfolio we provide an enhanced and holistic 360 degree view to security that begins in the manufacturing supply chain and concludes with a safeguarded end-of-life decommissioning and of course we've long set the bar for security with our work on silicon root of trust and we're extending that to the application tier but in addition to the security customers that are building this modern hybrid are private cloud including the integration of the edge need other elements too they need an intelligent software-defined control plane so that they can automate their compute fleets from all the way at the edge to the core and while scale and automation enable efficiency all private cloud infrastructures are competing with web scale economics and that's why we're democratizing web scale technologies like pinsando to bring web scale economics and web scale architecture to the private cloud our partners are so important in helping us serve our customers needs yeah i mean hp has really upped its ecosystem game since the the middle of last decade when when you guys reorganized it you became like even more partner friendly so maybe give us a preview of what's coming next in that regard from today's event well dave we're really excited to have hp's ceo antonio neri speaking with pat gelsinger from intel and later lisa sue from amd and later i'll have the chance to catch up with john chambers the founder and ceo of jc2 ventures to discuss the state of the market today yeah i'm jealous you guys had some good interviews coming up neil thanks so much for joining us today on the virtual cube you've really shared a lot of great insight how hpe is partnering with customers it's it's always great to catch up with you hopefully we can do so face to face you know sooner rather than later well i look forward to that and uh you know no doubt our world has changed and we're here to help our customers and partners with the technology the expertise and the economics they need for these digital transformations and we're going to bring them unmatched workload optimization from the edge to exascale with that 360 degree security with the intelligent automation and we're going to deliver it all as an as a service experience we're really excited to be helping our customers accelerate what's next for their businesses and it's been really great talking with you today about that dave thanks for having me you're very welcome it's been super neal and i actually you know i had the opportunity to speak with some of your customers about their digital transformation and the role of that hpe plays there so let's dive right in we're here on the cube covering hpe accelerating next and with me is rule siestermans who is the head of it at the netherlands cancer institute also known as nki welcome rule thank you very much great to be here hey what can you tell us about the netherlands cancer institute maybe you could talk about your core principles and and also if you could weave in your specific areas of expertise yeah maybe first introduction to the netherlands institute um we are one of the top 10 comprehensive cancers in the world and what we do is we combine a hospital for treating patients with cancer and a recent institute under one roof so discoveries we do we find within the research we can easily bring them back to the clinic and vis-a-versa so we have about 750 researchers and about 3 000 other employees doctors nurses and and my role is to uh to facilitate them at their best with it got it so i mean everybody talks about digital digital transformation to us it all comes down to data so i'm curious how you collect and take advantage of medical data specifically to support nki's goals maybe some of the challenges that your organization faces with the amount of data the speed of data coming in just you know the the complexities of data how do you handle that yeah it's uh it's it's it's challenge and uh yeah what we we have we have a really a large amount of data so we produce uh terabytes a day and we we have stored now more than one petabyte on data at this moment and yeah it's uh the challenge is to to reuse the data optimal for research and to share it with other institutions so that needs to have a flexible infrastructure for that so a fast really fast network uh big data storage environment but the real challenge is not not so much the i.t bus is more the quality of the data so we have a lot of medical systems all producing those data and how do we combine them and and yeah get the data fair so findable accessible interoperable and reusable uh for research uh purposes so i think that's the main challenge the quality of the data yeah very common themes that we hear from from other customers i wonder if you could paint a picture of your environment and maybe you can share where hpe solutions fit in what what value they bring to your organization's mission yeah i think it brings a lot of flexibility so what we did with hpe is that we we developed a software-defined data center and then a virtual workplace for our researchers and doctors and that's based on the hpe infrastructure and what we wanted to build is something that expect the needs of doctors and nurses but also the researchers and the two kind of different blood groups blood groups and with different needs so uh but we wanted to create one infrastructure because we wanted to make the connection between the hospital and the research that's that's more important so um hpe helped helped us not only with the the infrastructure itself but also designing the whole architecture of it and for example what we did is we we bought a lot of hardware and and and the hardware is really uh doing his his job between nine till five uh dennis everything is working within everyone is working within the institution but all the other time in evening and and nights hours and also the redundant environment we have for the for our healthcare uh that doesn't do nothing of much more or less uh in in those uh dark hours so what we created together with nvidia and hpe and vmware is that we we call it video by day compute by night so we reuse those those servers and those gpu capacity for computational research jobs within the research that's you mentioned flexibility for this genius and and so we're talking you said you know a lot of hard ways they're probably proliant i think synergy aruba networking is in there how are you using this environment actually the question really is when you think about nki's digital transformation i mean is this sort of the fundamental platform that you're using is it a maybe you could describe that yeah it's it's the fundamental platform to to to work on and and and what we see is that we have we have now everything in place for it but the real challenge is is the next steps we are in so we have a a software defined data center we are cloud ready so the next steps is to to make the connection to the cloud to to give more automation to our researchers so they don't have to wait a couple of weeks for it to do it but they can do it themselves with a couple of clicks so i think the basic is we are really flexible and we have a lot of opportunities for automation for example but the next step is uh to create that business value uh really for for our uh employees that's a great story and a very important mission really fascinating stuff thanks for sharing this with our audience today really appreciate your time thank you very much okay this is dave vellante with thecube stay right there for more great content you're watching accelerating next from hpe i'm really glad to have you with us today john i know you stepped out of vacation so thanks very much for joining us neil it's great to be joining you from hawaii and i love the partnership with hpe and the way you're reinventing an industry well you've always excelled john at catching market transitions and there are so many transitions and paradigm shifts happening in the market and tech specifically right now as you see companies rush to accelerate their transformation what do you see as the keys to success well i i think you're seeing actually an acceleration following the covet challenges that all of us faced and i wasn't sure that would happen it's probably at three times the paces before there was a discussion point about how quickly the companies need to go digital uh that's no longer a discussion point almost all companies are moving with tremendous feed on digital and it's the ability as the cloud moves to the edge with compute and security uh at the edge and how you deliver these services to where the majority of applications uh reside are going to determine i think the future of the next generation company leadership and it's the area that neil we're working together on in many many ways so i think it's about innovation it's about the cloud moving to the edge and an architectural play with silicon to speed up that innovation yes we certainly see our customers of all sizes trying to accelerate what's next and get that digital transformation moving even faster as a result of the environment that we're all living in and we're finding that workload focus is really key uh customers in all kinds of different scales are having to adapt and support the remote workforces with vdi and as you say john they're having to deal with the deployment of workloads at the edge with so much data getting generated at the edge and being acted upon at the edge the analytics and the infrastructure to manage that as these processes get digitized and automated is is so important for so many workflows we really believe that the choice of infrastructure partner that underpins those transformations really matters a partner that can help create the financial capacity that can help optimize your environments and enable our customers to focus on supporting their business are all super key to success and you mentioned that in the last year there's been a lot of rapid course correction for all of us a demand for velocity and the ability to deploy resources at scale is more and more needed maybe more than ever what are you hearing customers looking for as they're rolling out their digital transformation efforts well i think they're being realistic that they're going to have to move a lot faster than before and they're also realistic on core versus context they're they're their core capability is not the technology of themselves it's how to deploy it and they're we're looking for partners that can help bring them there together but that can also innovate and very often the leaders who might have been a leader in a prior generation may not be on this next move hence the opportunity for hpe and startups like vinsano to work together as the cloud moves the edge and perhaps really balance or even challenge some of the big big incumbents in this category as well as partners uniquely with our joint customers on how do we achieve their business goals tell me a little bit more about how you move from this being a technology positioning for hpe to literally helping your customers achieve their outcomes they want and and how are you changing hpe in that way well i think when you consider these transformations the infrastructure that you choose to underpin it is incredibly critical our customers need a software-defined management plan that enables them to automate so much of their infrastructure they need to be able to take faster action where the data is and to do all of this in a cloud-like experience where they can deliver their infrastructure as code anywhere from exascale through the enterprise data center to the edge and really critically they have to be able to do this securely which becomes an ever increasing challenge and doing it at the right economics relative to their alternatives and part of the right economics of course includes adopting the best practices from web scale architectures and bringing them to the heart of the enterprise and in our partnership with pensando we're working to enable these new ideas of web scale architecture and fleet management for the enterprise at scale you know what is fun is hpe has an unusual talent from the very beginning in silicon valley of working together with others and creating a win-win innovation approach if you watch what your team has been able to do and i want to say this for everybody listening you work with startups better than any other company i've seen in terms of how you do win win together and pinsando is just the example of that uh this startup which by the way is the ninth time i have done with this team a new generation of products and we're designing that together with hpe in terms of as the cloud moves to the edge how do we get the leverage out of that and produce the results for your customers on this to give the audience appeal for it you're talking with pensano alone in terms of the efficiency versus an amazon amazon web services of an order of magnitude i'm not talking 100 greater i'm talking 10x greater and things from throughput number of connections you do the jitter capability etc and it talks how two companies uniquely who believe in innovation and trust each other and have very similar cultures can work uniquely together on it how do you bring that to life with an hpe how do you get your company to really say let's harvest the advantages of your ecosystem in your advantages of startups well as you say more and more companies are faced with these challenges of hitting the right economics for the infrastructure and we see many enterprises of various sizes trying to come to terms with infrastructures that look a lot more like a service provider that require that software-defined management plane and the automation to deploy at scale and with the work we're doing with pinsando the benefits that we bring in terms of the observability and the telemetry and the encryption and the distributed network functions but also a security architecture that enables that efficiency on the individual nodes is just so key to building a competitive architecture moving forwards for an on-prem private cloud or internal service provider operation and we're really excited about the work we've done to bring that technology across our portfolio and bring that to our customers so that they can achieve those kind of economics and capabilities and go focus on their own transformations rather than building and running the infrastructure themselves artisanally and having to deal with integrating all of that great technology themselves makes tremendous sense you know neil you and i work on a board together et cetera i've watched your summarization skills and i always like to ask the question after you do a quick summary like this what are the three or four takeaways we would like for the audience to get out of our conversation well that's a great question thanks john we believe that customers need a trusted partner to work through these digital transformations that are facing them and confront the challenge of the time that the covet crisis has taken away as you said up front every organization is having to transform and transform more quickly and more digitally and working with a trusted partner with the expertise that only comes from decades of experience is a key enabler for that a partner with the ability to create the financial capacity to transform the workload expertise to get more from the infrastructure and optimize the environment so that you can focus on your own business a partner that can deliver the systems and the security and the automation that makes it easily deployable and manageable anywhere you need them at any scale whether the edge the enterprise data center or all the way up to exascale in high performance computing and can do that all as a service as we can at hpe through hpe green lake enabling our customers most critical workloads it's critical that all of that is underpinned by an ai powered digitally enabled service experience so that our customers can get on with their transformation and running their business instead of dealing with their infrastructure and really only hpe can provide this combination of capabilities and we're excited and committed to helping our customers accelerate what's next for their businesses neil it's fun i i love being your partner and your wingman our values and cultures are so similar thanks for letting me be a part of this discussion today thanks for being with us john it was great having you here oh it's friends for life okay now we're going to dig into the world of video which accounts for most of the data that we store and requires a lot of intense processing capabilities to stream here with me is jim brickmeyer who's the chief marketing and product officer at vlasics jim good to see you good to see you as well so tell us a little bit more about velocity what's your role in this tv streaming world and maybe maybe talk about your ideal customer sure sure so um we're leading provider of carrier great video solutions video streaming solutions and advertising uh technology to service providers around the globe so we primarily sell software-based solutions to uh cable telco wireless providers and broadcasters that are interested in launching their own um video streaming services to consumers yeah so this is this big time you know we're not talking about mom and pop you know a little video outfit but but maybe you can help us understand that and just the sheer scale of of the tv streaming that you're doing maybe relate it to you know the overall internet usage how much traffic are we talking about here yeah sure so uh yeah so our our customers tend to be some of the largest um network service providers around the globe uh and if you look at the uh the video traffic um with respect to the total amount of traffic that that goes through the internet video traffic accounts for about 90 of the total amount of data that uh that traverses the internet so video is uh is a pretty big component of um of how people when they look at internet technologies they look at video streaming technologies uh you know this is where we we focus our energy is in carrying that traffic as efficiently as possible and trying to make sure that from a consumer standpoint we're all consumers of video and uh make sure that the consumer experience is a high quality experience that you don't experience any glitches and that that ultimately if people are paying for that content that they're getting the value that they pay for their for their money uh in their entertainment experience i think people sometimes take it for granted it's like it's like we we all forget about dial up right those days are long gone but the early days of video was so jittery and restarting and and the thing too is that you know when you think about the pandemic and the boom in streaming that that hit you know we all sort of experienced that but the service levels were pretty good i mean how much how much did the pandemic affect traffic what kind of increases did you see and how did that that impact your business yeah sure so uh you know obviously while it was uh tragic to have a pandemic and have people locked down what we found was that when people returned to their homes what they did was they turned on their their television they watched on on their mobile devices and we saw a substantial increase in the amount of video streaming traffic um over service provider networks so what we saw was on the order of 30 to 50 percent increase in the amount of data that was traversing those networks so from a uh you know from an operator's standpoint a lot more traffic a lot more challenging to to go ahead and carry that traffic a lot of work also on our behalf and trying to help operators prepare because we could actually see geographically as the lockdowns happened [Music] certain areas locked down first and we saw that increase so we were able to help operators as as all the lockdowns happened around the world we could help them prepare for that increase in traffic i mean i was joking about dial-up performance again in the early days of the internet if your website got fifty percent more traffic you know suddenly you were you your site was coming down so so that says to me jim that architecturally you guys were prepared for that type of scale so maybe you could paint a picture tell us a little bit about the solutions you're using and how you differentiate yourself in your market to handle that type of scale sure yeah so we so we uh we really are focused on what we call carrier grade solutions which are designed for that massive amount of scale um so we really look at it you know at a very granular level when you look um at the software and and performance capabilities of the software what we're trying to do is get as many streams as possible out of each individual piece of hardware infrastructure so that we can um we can optimize first of all maximize the uh the efficiency of that device make sure that the costs are very low but one of the other challenges is as you get to millions and millions of streams and that's what we're delivering on a daily basis is millions and millions of video streams that you have to be able to scale those platforms out um in an effective in a cost effective way and to make sure that it's highly resilient as well so we don't we don't ever want a consumer to have a circumstance where a network glitch or a server issue or something along those lines causes some sort of uh glitch in their video and so there's a lot of work that we do in the software to make sure that it's a very very seamless uh stream and that we're always delivering at the very highest uh possible bit rate for consumers so that if you've got that giant 4k tv that we're able to present a very high resolution picture uh to those devices and what's the infrastructure look like underneath you you're using hpe solutions where do they fit in yeah that's right yeah so we uh we've had a long-standing partnership with hpe um and we work very closely with them to try to identify the specific types of hardware that are ideal for the the type of applications that we run so we run video streaming applications and video advertising applications targeted kinds of video advertising technologies and when you look at some of these applications they have different types of requirements in some cases it's uh throughput where we're taking a lot of data in and streaming a lot of data out in other cases it's storage where we have to have very high density high performance storage systems in other cases it's i gotta have really high capacity storage but the performance does not need to be quite as uh as high from an io perspective and so we work very closely with hpe on trying to find exactly the right box for the right application and then beyond that also talking with our customers to understand there are different maintenance considerations associated with different types of hardware so we tend to focus on as much as possible if we're going to place servers deep at the edge of the network we will make everything um maintenance free or as maintenance free as we can make it by putting very high performance solid state storage into those servers so that uh we we don't have to physically send people to those sites to uh to do any kind of maintenance so it's a it's a very cooperative relationship that we have with hpe to try to define those boxes great thank you for that so last question um maybe what the future looks like i love watching on my mobile device headphones in no distractions i'm getting better recommendations how do you see the future of tv streaming yeah so i i think the future of tv streaming is going to be a lot more personal right so uh this is what you're starting to see through all of the services that are out there is that most of the video service providers whether they're online providers or they're your traditional kinds of paid tv operators is that they're really focused on the consumer and trying to figure out what is of value to you personally in the past it used to be that services were one size fits all and um and so everybody watched the same program right at the same time and now that's uh that's we have this technology that allows us to deliver different types of content to people on different screens at different times and to advertise to those individuals and to cater to their individual preferences and so using that information that we have about how people watch and and what people's interests are we can create a much more engaging and compelling uh entertainment experience on all of those screens and um and ultimately provide more value to consumers awesome story jim thanks so much for keeping us helping us just keep entertained during the pandemic i really appreciate your time sure thanks all right keep it right there everybody you're watching hpes accelerating next first of all pat congratulations on your new role as intel ceo how are you approaching your new role and what are your top priorities over your first few months thanks antonio for having me it's great to be here with you all today to celebrate the launch of your gen 10 plus portfolio and the long history that our two companies share in deep collaboration to deliver amazing technology to our customers together you know what an exciting time it is to be in this industry technology has never been more important for humanity than it is today everything is becoming digital and driven by what i call the four key superpowers the cloud connectivity artificial intelligence and the intelligent edge they are super powers because each expands the impact of the others and together they are reshaping every aspect of our lives and work in this landscape of rapid digital disruption intel's technology and leadership products are more critical than ever and we are laser focused on bringing to bear the depth and breadth of software silicon and platforms packaging and process with at scale manufacturing to help you and our customers capitalize on these opportunities and fuel their next generation innovations i am incredibly excited about continuing the next chapter of a long partnership between our two companies the acceleration of the edge has been significant over the past year with this next wave of digital transformation we expect growth in the distributed edge and age build out what are you seeing on this front like you said antonio the growth of edge computing and build out is the next key transition in the market telecommunications service providers want to harness the potential of 5g to deliver new services across multiple locations in real time as we start building solutions that will be prevalent in a 5g digital environment we will need a scalable flexible and programmable network some use cases are the massive scale iot solutions more robust consumer devices and solutions ar vr remote health care autonomous robotics and manufacturing environments and ubiquitous smart city solutions intel and hp are partnering to meet this new wave head on for 5g build out and the rise of the distributed enterprise this build out will enable even more growth as businesses can explore how to deliver new experiences and unlock new insights from the new data creation beyond the four walls of traditional data centers and public cloud providers network operators need to significantly increase capacity and throughput without dramatically growing their capital footprint their ability to achieve this is built upon a virtualization foundation an area of intel expertise for example we've collaborated with verizon for many years and they are leading the industry and virtualizing their entire network from the core the edge a massive redesign effort this requires advancements in silicon and power management they expect intel to deliver the new capabilities in our roadmap so ecosystem partners can continue to provide innovative and efficient products with this optimization for hybrid we can jointly provide a strong foundation to take on the growth of data-centric workloads for data analytics and ai to build and deploy models faster to accelerate insights that will deliver additional transformation for organizations of all types the network transformation journey isn't easy we are continuing to unleash the capabilities of 5g and the power of the intelligent edge yeah the combination of the 5g built out and the massive new growth of data at the edge are the key drivers for the age of insight these new market drivers offer incredible new opportunities for our customers i am excited about recent launch of our new gen 10 plus portfolio with intel together we are laser focused on delivering joint innovation for customers that stretches from the edge to x scale how do you see new solutions that this helping our customers solve the toughest challenges today i talked earlier about the superpowers that are driving the rapid acceleration of digital transformation first the proliferation of the hybrid cloud is delivering new levels of efficiency and scale and the growth of the cloud is democratizing high-performance computing opening new frontiers of knowledge and discovery next we see ai and machine learning increasingly infused into every application from the edge to the network to the cloud to create dramatically better insights and the rapid adoption of 5g as i talked about already is fueling new use cases that demand lower latencies and higher bandwidth this in turn is pushing computing to the edge closer to where the data is created and consumed the confluence of these trends is leading to the biggest and fastest build out of computing in human history to keep pace with this rapid digital transformation we recognize that infrastructure has to be built with the flexibility to support a broad set of workloads and that's why over the last several years intel has built an unmatched portfolio to deliver every component of intelligent silicon our customers need to move store and process data from the cpus to fpgas from memory to ssds from ethernet to switch silicon to silicon photonics and software our 3rd gen intel xeon scalable processors and our data centric portfolio deliver new core performance and higher bandwidth providing our customers the capabilities they need to power these critical workloads and we love seeing all the unique ways customers like hpe leverage our technology and solution offerings to create opportunities and solve their most pressing challenges from cloud gaming to blood flow to brain scans to financial market security the opportunities are endless with flexible performance i am proud of the amazing innovation we are bringing to support our customers especially as they respond to new data-centric workloads like ai and analytics that are critical to digital transformation these new requirements create a need for compute that's warlord optimized for performance security ease of use and the economics of business now more than ever compute matters it is the foundation for this next wave of digital transformation by pairing our compute with our software and capabilities from hp green lake we can support our customers as they modernize their apps and data quickly they seamlessly and securely scale them anywhere at any size from edge to x scale but thank you for joining us for accelerating next today i know our audience appreciated hearing your perspective on the market and how we're partnering together to support their digital transformation journey i am incredibly excited about what lies ahead for hp and intel thank you thank you antonio great to be with you today we just compressed about a decade of online commerce progress into about 13 or 14 months so now we're going to look at how one retailer navigated through the pandemic and what the future of their business looks like and with me is alan jensen who's the chief information officer and senior vice president of the sawing group hello alan how are you fine thank you good to see you hey look you know when i look at the 100 year history plus of your company i mean it's marked by transformations and some of them are quite dramatic so you're denmark's largest retailer i wonder if you could share a little bit more about the company its history and and how it continues to improve the customer experience well at the same time keeping costs under control so vital in your business yeah yeah the company founded uh approximately 100 years ago with a department store in in oahu's in in denmark and i think in the 60s we founded the first supermarket in in denmark with the self-service and combined textile and food in in the same store and in beginning 70s we founded the first hyper market in in denmark and then the this calendar came from germany early in in 1980 and we started a discount chain and so we are actually building department store in hyber market info in in supermarket and in in the discount sector and today we are more than 1 500 stores in in three different countries in in denmark poland and germany and especially for the danish market we have a approximately 38 markets here and and is the the leader we have over the last 10 years developed further into online first in non-food and now uh in in food with home delivery with click and collect and we have done some magnetism acquisition in in the convenience with mailbox solutions to our customers and we have today also some restaurant burger chain and and we are running the starbuck in denmark so i can you can see a full plate of different opportunities for our customer in especially denmark it's an awesome story and of course the founder's name is still on the masthead what a great legacy now of course the pandemic is is it's forced many changes quite dramatic including the the behaviors of retail customers maybe you could talk a little bit about how your digital transformation at the sawing group prepared you for this shift in in consumption patterns and any other challenges that that you faced yeah i think uh luckily as for some of the you can say the core it solution in in 19 we just roll out using our computers via direct access so you can work from anywhere whether you are traveling from home and so on we introduced a new agile scrum delivery model and and we just finalized the rolling out teams in in in january february 20 and that was some very strong thing for suddenly moving all our employees from from office to to home and and more or less overnight we succeed uh continuing our work and and for it we have not missed any deadline or task for the business in in 2020 so i think that was pretty awesome to to see and for the business of course the pandemic changed a lot as the change in customer behavior more or less overnight with plus 50 80 on the online solution forced us to do some different priorities so we were looking at the food home delivery uh and and originally expected to start rolling out in in 2022 uh but took a fast decision in april last year to to launch immediately and and we have been developing that uh over the last eight months and has been live for the last three months now in the market so so you can say the pandemic really front loaded some of our strategic actions for for two to three years uh yeah that was very exciting what's that uh saying luck is the byproduct of great planning and preparation so let's talk about when you're in a company with some strong financial situation that you can move immediately with investment when you take such decision then then it's really thrilling yeah right awesome um two-part question talk about how you leverage data to support the solid groups mission and you know drive value for customers and maybe you could talk about some of the challenges you face with just the amount of data the speed of data et cetera yeah i said data is everything when you are in retail as a retailer's detail as you need to monitor your operation down to each store eats department and and if you can say we have challenge that that is that data is just growing rapidly as a year by year it's growing more and more because you are able to be more detailed you're able to capture more data and for a company like ours we need to be updated every morning as a our fully updated sales for all unit department single sku selling in in the stores is updated 3 o'clock in the night and send out to all top management and and our managers all over the company it's actually 8 000 reports going out before six o'clock every day in the morning we have introduced a loyalty program and and you are capturing a lot of data on on customer behavior what is their preferred offers what is their preferred time in the week for buying different things and all these data is now used to to personalize our offers to our cost of value customers so we can be exactly hitting the best time and and convert it to sales data is also now used for what we call intelligent price reductions as a so instead of just reducing prices with 50 if it's uh close to running out of date now the system automatically calculate whether a store has just enough to to finish with full price before end of day or actually have much too much and and need to maybe reduce by 80 before as being able to sell so so these automated [Music] solutions built on data is bringing efficiency into our operation wow you make it sound easy these are non-trivial items so congratulations on that i wonder if we could close hpe was kind enough to introduce us tell us a little bit about the infrastructure the solutions you're using how they differentiate you in the market and i'm interested in you know why hpe what distinguishes them why the choice there yeah as a when when you look out a lot is looking at moving data to the cloud but we we still believe that uh due to performance due to the availability uh more or less on demand we we still don't see the cloud uh strong enough for for for selling group uh capturing all our data we have been quite successfully having one data truth across the whole con company and and having one just one single bi solution and having that huge amount of data i think we have uh one of the 10 largest sub business warehouses in global and but on the other hand we also want to be agile and want to to scale when needed so getting close to a cloud solution we saw it be a green lake as a solution getting close to the cloud but still being on-prem and could deliver uh what we need to to have a fast performance on on data but still in a high quality and and still very secure for us to run great thank you for that and thank alan thanks so much for your for your time really appreciate your your insights and your congratulations on the progress and best of luck in the future thank you all right keep it right there we have tons more content coming you're watching accelerating next from hpe [Music] welcome lisa and thank you for being here with us today antonio it's wonderful to be here with you as always and congratulations on your launch very very exciting for you well thank you lisa and we love this partnership and especially our friendship which has been very special for me for the many many years that we have worked together but i wanted to have a conversation with you today and obviously digital transformation is a key topic so we know the next wave of digital transformation is here being driven by massive amounts of data an increasingly distributed world and a new set of data intensive workloads so how do you see world optimization playing a role in addressing these new requirements yeah no absolutely antonio and i think you know if you look at the depth of our partnership over the last you know four or five years it's really about bringing the best to our customers and you know the truth is we're in this compute mega cycle right now so it's amazing you know when i know when you talk to customers when we talk to customers they all need to do more and and frankly compute is becoming quite specialized so whether you're talking about large enterprises or you're talking about research institutions trying to get to the next phase of uh compute so that workload optimization that we're able to do with our processors your system design and then you know working closely with our software partners is really the next wave of this this compute cycle so thanks lisa you talk about mega cycle so i want to make sure we take a moment to celebrate the launch of our new generation 10 plus compute products with the latest announcement hp now has the broadest amd server portfolio in the industry spanning from the edge to exascale how important is this partnership and the portfolio for our customers well um antonio i'm so excited first of all congratulations on your 19 world records uh with uh milan and gen 10 plus it really is building on you know sort of our you know this is our third generation of partnership with epic and you know you are with me right at the very beginning actually uh if you recall you joined us in austin for our first launch of epic you know four years ago and i think what we've created now is just an incredible portfolio that really does go across um you know all of the uh you know the verticals that are required we've always talked about how do we customize and make things easier for our customers to use together and so i'm very excited about your portfolio very excited about our partnership and more importantly what we can do for our joint customers it's amazing to see 19 world records i think i'm really proud of the work our joint team do every generation raising the bar and that's where you know we we think we have a shared goal of ensuring that customers get the solution the services they need any way they want it and one way we are addressing that need is by offering what we call as a service delivered to hp green lake so let me ask a question what feedback are you hearing from your customers with respect to choice meaning consuming as a service these new solutions yeah now great point i think first of all you know hpe green lake is very very impressive so you know congratulations um to uh to really having that solution and i think we're hearing the same thing from customers and you know the truth is the compute infrastructure is getting more complex and everyone wants to be able to deploy sort of the right compute at the right price point um you know in in terms of also accelerating time to deployment with the right security with the right quality and i think these as a service offerings are going to become more and more important um as we go forward in the compute uh you know capabilities and you know green lake is a leadership product offering and we're very very you know pleased and and honored to be part of it yeah we feel uh lisa we are ahead of the competition and um you know you think about some of our competitors now coming with their own offerings but i think the ability to drive joint innovation is what really differentiate us and that's why we we value the partnership and what we have been doing together on giving the customers choice finally you know i know you and i are both incredibly excited about the joint work we're doing with the us department of energy the oak ridge national laboratory we think about large data sets and you know and the complexity of the analytics we're running but we both are going to deliver the world's first exascale system which is remarkable to me so what this milestone means to you and what type of impact do you think it will make yes antonio i think our work with oak ridge national labs and hpe is just really pushing the envelope on what can be done with computing and if you think about the science that we're going to be able to enable with the first exascale machine i would say there's a tremendous amount of innovation that has already gone in to the machine and we're so excited about delivering it together with hpe and you know we also think uh that the super computing technology that we're developing you know at this broad scale will end up being very very important for um you know enterprise compute as well and so it's really an opportunity to kind of take that bleeding edge and really deploy it over the next few years so super excited about it i think you know you and i have a lot to do over the uh the next few months here but it's an example of the great partnership and and how much we're able to do when we put our teams together um to really create that innovation i couldn't agree more i mean this is uh an incredible milestone for for us for our industry and honestly for the country in many ways and we have many many people working 24x7 to deliver against this mission and it's going to change the future of compute no question about it and then honestly put it to work where we need it the most to advance life science to find cures to improve the way people live and work but lisa thank you again for joining us today and thank you more most importantly for the incredible partnership and and the friendship i really enjoy working with you and your team and together i think we can change this industry once again so thanks for your time today thank you so much antonio and congratulations again to you and the entire hpe team for just a fantastic portfolio launch thank you okay well some pretty big hitters in those keynotes right actually i have to say those are some of my favorite cube alums and i'll add these are some of the execs that are stepping up to change not only our industry but also society and that's pretty cool and of course it's always good to hear from the practitioners the customer discussions have been great so far today now the accelerating next event continues as we move to a round table discussion with krista satrathwaite who's the vice president and gm of hpe core compute and krista is going to share more details on how hpe plans to help customers move ahead with adopting modern workloads as part of their digital transformations krista will be joined by hpe subject matter experts chris idler who's the vp and gm of the element and mark nickerson director of solutions product management as they share customer stories and advice on how to turn strategy into action and realize results within your business thank you for joining us for accelerate next event i hope you're enjoying it so far i know you've heard about the industry challenges the i.t trends hpe strategy from leaders in the industry and so today what we want to do is focus on going deep on workload solutions so in the most important workload solutions the ones we always get asked about and so today we want to share with you some best practices some examples of how we've helped other customers and how we can help you all right with that i'd like to start our panel now and introduce chris idler who's the vice president and general manager of the element chris has extensive uh solution expertise he's led hpe solution engineering programs in the past welcome chris and mark nickerson who is the director of product management and his team is responsible for solution offerings making sure we have the right solutions for our customers welcome guys thanks for joining me thanks for having us krista yeah so i'd like to start off with one of the big ones the ones that we get asked about all the time what we've been all been experienced in the last year remote work remote education and all the challenges that go along with that so let's talk a little bit about the challenges that customers have had in transitioning to this remote work and remote education environment uh so i i really think that there's a couple of things that have stood out for me when we're talking with customers about vdi first obviously there was a an unexpected and unprecedented level of interest in that area about a year ago and we all know the reasons why but what it really uncovered was how little planning had gone into this space around a couple of key dynamics one is scale it's one thing to say i'm going to enable vdi for a part of my workforce in a pre-pandemic environment where the office was still the the central hub of activity for work uh it's a completely different scale when you think about okay i'm going to have 50 60 80 maybe 100 of my workforce now distributed around the globe um whether that's in an educational environment where now you're trying to accommodate staff and students in virtual learning uh whether that's uh in the area of things like uh formula one racing where we had uh the desire to still have events going on but the need for a lot more social distancing not as many people able to be trackside but still needing to have that real-time experience this really manifested in a lot of ways and scale was something that i think a lot of customers hadn't put as much thought into initially the other area is around planning for experience a lot of times the vdi experience was planned out with very specific workloads or very specific applications in mind and when you take it to a more broad-based environment if we're going to support multiple functions multiple lines of business there hasn't been as much planning or investigation that's gone into the application side and so thinking about how graphically intense some applications are one customer that comes to mind would be tyler isd who did a fairly large roll out pre-pandemic and as part of their big modernization effort what they uncovered was even just changes in standard windows applications had become so much more graphically intense with windows 10 with the latest updates with programs like adobe that they were really needing to have an accelerated experience for a much larger percentage of their install base than than they had counted on so in addition to planning for scale you also need to have that visibility into what are the actual applications that are going to be used by these remote users how graphically intense those might be what's the login experience going to be as well as the operating experience and so really planning through that experience side as well as the scale and the number of users uh is is kind of really two of the biggest most important things that i've seen yeah mark i'll i'll just jump in real quick i think you you covered that pretty comprehensively there and and it was well done the couple of observations i've made one is just that um vdi suddenly become like mission critical for sales it's the front line you know for schools it's the classroom you know that this isn't a cost cutting measure or a optimization nit measure anymore this is about running the business in a way it's a digital transformation one aspect of about a thousand aspects of what does it mean to completely change how your business does and i think what that translates to is that there's no margin for error right you really need to deploy this in a way that that performs that understands what you're trying to use it for that gives that end user the experience that they expect on their screen or on their handheld device or wherever they might be whether it's a racetrack classroom or on the other end of a conference call or a boardroom right so what we do in in the engineering side of things when it comes to vdi or really understand what's a tech worker what's a knowledge worker what's a power worker what's a gp really going to look like what's time of day look like you know who's using it in the morning who's using it in the evening when do you power up when do you power down does the system behave does it just have the it works function and what our clients can can get from hpe is um you know a worldwide set of experiences that we can apply to making sure that the solution delivers on its promises so we're seeing the same thing you are krista you know we see it all the time on vdi and on the way businesses are changing the way they do business yeah and it's funny because when i talk to customers you know one of the things i heard that was a good tip is to roll it out to small groups first so you could really get a good sense of what the experience is before you roll it out to a lot of other people and then the expertise it's not like every other workload that people have done before so if you're new at it make sure you're getting the right advice expertise so that you're doing it the right way okay one of the other things we've been talking a lot about today is digital transformation and moving to the edge so now i'd like to shift gears and talk a little bit about how we've helped customers make that shift and this time i'll start with chris all right hey thanks okay so you know it's funny when it comes to edge because um the edge is different for for every customer in every client and every single client that i've ever spoken to of hp's has an edge somewhere you know whether just like we were talking about the classroom might be the edge but but i think the industry when we're talking about edge is talking about you know the internet of things if you remember that term from not to not too long ago you know and and the fact that everything's getting connected and how do we turn that into um into telemetry and and i think mark's going to be able to talk through a couple of examples of clients that we have in things like racing and automotive but what we're learning about edge is it's not just how do you make the edge work it's how do you integrate the edge into what you're already doing and nobody's just the edge right and and so if it's if it's um ai mldl there's that's one way you want to use the edge if it's a customer experience point of service it's another you know there's yet another way to use the edge so it turns out that having a broad set of expertise like hpe does to be able to understand the different workloads that you're trying to tie together including the ones that are running at the at the edge often it involves really making sure you understand the data pipeline you know what information is at the edge how does it flow to the data center how does it flow and then which data center uh which private cloud which public cloud are you using i think those are the areas where where we really sort of shine is that we we understand the interconnectedness of these things and so for example red bull and i know you're going to talk about that in a minute mark um uh the racing company you know for them the the edge is the racetrack and and you know milliseconds or partial seconds winning and losing races but then there's also an edge of um workers that are doing the design for for the cars and how do they get quick access so um we have a broad variety of infrastructure form factors and compute form factors to help with the edge and this is another real advantage we have is that we we know how to put the right piece of equipment with the right software we also have great containerized software with our esmeral container platform so we're really becoming um a perfect platform for hosting edge-centric workloads and applications and data processing yeah it's uh all the way down to things like our superdome flex in the background if you have some really really really big data that needs to be processed and of course our workhorse proliance that can be configured to support almost every um combination of workload you have so i know you started with edge krista but but and we're and we nail the edge with those different form factors but let's make sure you know if you're listening to this this show right now um make sure you you don't isolate the edge and make sure they integrate it with um with the rest of your operation mark you know what did i miss yeah to that point chris i mean and this kind of actually ties the two things together that we've been talking about here but the edge uh has become more critical as we have seen more work moving to the edge as where we do work changes and evolves and the edge has also become that much more closer because it has to be that much more connected um to your point uh talking about where that edge exists that edge can be a lot of different places but the one commonality really is that the edge is is an area where work still needs to get accomplished it can't just be a collection point and then everything gets shipped back to a data center or back to some some other area for the work it's where the work actually needs to get done whether that's edge work in a use case like vdi or whether that's edge work in the case of doing real-time analytics you mentioned red bull racing i'll i'll bring that up i mean you talk about uh an area where time is of the essence everything about that sport comes down to time you're talking about wins and losses that are measured as you said in milliseconds and that applies not just to how performance is happening on the track but how you're able to adapt and modify the needs of the car uh adapt to the evolving conditions on the track itself and so when you talk about putting together a solution for an edge like that you're right it can't just be here's a product that's going to allow us to collect data ship it back someplace else and and wait for it to be processed in a couple of days you have to have the ability to analyze that in real time when we pull together a solution involving our compute products our storage products our networking products when we're able to deliver that full package solution at the edge what you see are results like a 50 decrease in processing time to make real-time analytic decisions about configurations for the car and adapting to to real-time uh test and track conditions yeah really great point there um and i really love the example of edge and racing because i mean that is where it all every millisecond counts um and so important to process that at the edge now switching gears just a little bit let's talk a little bit about some examples of how we've helped customers when it comes to business agility and optimizing their workload for maximum outcome for business agility let's talk about some things that we've done to help customers with that mark yeah give it a shot so when we when we think about business agility what you're really talking about is the ability to to implement on the fly to be able to scale up to scale down the ability to adapt to real time changing situations and i think the last year has been has been an excellent example of exactly how so many businesses have been forced to do that i think one of the areas that that i think we've probably seen the most ability to help with customers in that agility area is around the space of private and hybrid clouds if you take a look at the need that customers have to to be able to migrate workloads and migrate data between public cloud environments app development environments that may be hosted on-site or maybe in the cloud the ability to move out of development and into production and having the agility to then scale those application rollouts up having the ability to have some of that some of that private cloud flexibility in addition to a public cloud environment is something that is becoming increasingly crucial for a lot of our customers all right well i we could keep going on and on but i'll stop it there uh thank you so much uh chris and mark this has been a great discussion thanks for sharing how we helped other customers and some tips and advice for approaching these workloads i thank you all for joining us and remind you to look at the on-demand sessions if you want to double click a little bit more into what we've been covering all day today you can learn a lot more in those sessions and i thank you for your time thanks for tuning in today many thanks to krista chris and mark we really appreciate you joining today to share how hpe is partnering to facilitate new workload adoption of course with your customers on their path to digital transformation now to round out our accelerating next event today we have a series of on-demand sessions available so you can explore more details around every step of that digital transformation from building a solid infrastructure strategy identifying the right compute and software to rounding out your solutions with management and financial support so please navigate to the agenda at the top of the page to take a look at what's available i just want to close by saying that despite the rush to digital during the pandemic most businesses they haven't completed their digital transformations far from it 2020 was more like a forced march than a planful strategy but now you have some time you've adjusted to this new abnormal and we hope the resources that you find at accelerating next will help you on your journey best of luck to you and be well [Music] [Applause] [Music] 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>>from around the globe. It's the Cube with digital coverage of Dell Technologies. World Digital Experience Brought to You by Dell Technologies Everyone welcome back to the cubes Coverage of Dell Technologies World Digital Experience I'm John for your host of the Cube Cube. Virtual. We're not in person this year were remote We're doing The interviews were not face to face. So thanks for watching two great guests to talk about the Dell Technology Storage and data protection for the VM Ware environments got Caitlin Gordon, vice President, product management, Dale Technologies and Leak as well. Vice president of Cloud Platform Business Unit, also known as CPB. You for VM where Lee and Cable in Great to see you both. Thanks for coming on. >>Thanks for having me >>s So what? What a crazy year. We're not in person. Usually the the events Awesome. VM world recently went on and then you guys have the same situation role online now and it's >>really kind >>of highlighted the customer environments of cloud needed. But I've been saying this on all my reports and all the Cube interviews that the executives who are in charge and now saying, Look at our modern APS have to be cloud native because the obvious benefits are there and container ization has become mainstream. But yet I d c still forecast about 15% of enterprises are still fully containing rise, with a huge amount of growth coming around the corner. So you're seeing this mature market where containers are validated, they're being put into production. People are now moving hard core with containers. And you have the kubernetes. I gotta ask you, Li, I'm Caitlin. What does this mean for the customers? Are they getting harder pressure points to do things faster? What does it all mean for the customer? >>Yeah, I'll start. Only you can add to it. I mean, I think what we see is the trends that were already happening of now. Accelerated and modern APs were kind of the top of the priority list, but now it has is really expedited. But at the same time, traditional applications haven't gone anywhere. So there's this dichotomy that a lot of I t is dealing with of head Oh, accelerate those modern APs while also streamlining and simplifying my environment for my traditional laps. And not only do I need to the right infrastructure to have that for production workloads, modern, traditional, but also form a data protection standpoint. How to ensure that those are all secure and do all of that in a way that simplifies life for whether it's the data protection admin, the BM admin or even the developer right, all of the different folks involved and needing to make all of their lives simpler has just really exacerbated a challenge and really given us a lot of opportunity to try to solve that for customers together. >>Lee, What's your take on the landscape out there? >>Yeah, I'd emphasized that speed really matters today, right? That we're really looking at. How do you go and deploy new applications faster, right? New ways to get engaged with customers. I mean, it's not happening physically anymore. So how is it happening while it's happening largely through applications? And so as you now basically develop new applications more quickly, containers are a way to speed the pace of applications, and the theme that you know we continue to drive home is that that means infrastructure has to respond more quickly, and it means that for the teams that are managing infrastructure, it really helps if you have a consistent model where you can get mawr done with the same teams and leverage all the experience you have, as well as the security and infrastructure resiliency model that we're bringing together to our customers. >>This brings up the real question, and if this comes up, kind of you see more of the executive level like we need to have a modern application direction. They'll go. Everyone goes, Yeah, of course. Thumbs up. Then they go Try to make that a reality because even though Dev ops and Infrastructures Code is still the viable path, it's hard. It's like Caitlin, we're talking about EJ to core Data center hybrid the multi cloud. There's a lot going on under the hood there. So you guys are doing a lot of stuff together. VM Ware and Dell Technologies. What's the solution for customers? They gotta move faster. As lead pointed out, Caitlin, how are you guys working together to make that infrastructure more modern, faster, programmable and reliable, >>and make it simpler for the customers right? I think it really comes down to one of the most powerful things about the partnership is that from the dull technology standpoint, we have really a plethora of different solutions to support your VM or environment. Whether it's a three tier architecture with Power Edge power store or leveraging the X rail. Or very commonly, it's gonna be both of those. You have the right infrastructure to support the production workloads and have a consistent operating model between them leveraging devils and primary storage side and all the integrations we have with the ex rail. And then we have with power, protect data manager Great integrations in some recent enhancements that make that even better and are now able to protect Tan Xue, protect the VCF management domain and not only have the storage, but also the protection for that environment. But do it in a way that supports what the V A madman needs and also gives that consistent protection, consistent storage, consistent operating model for the rest of I T. And at the same time you're enabling the developers to move faster. >>Lee, You guys have been doing a lot of joint development, and we've been covering a lot of the news VM world. Ah, lot of joint engineering, a lot of joint integrations. You guys have been collaborating with Dell Technologies for a long time. Also, the relationship. Where is that Today? Can you expand on that a little bit and take a minute to explain the joint >>collaboration? I'll start with the fact that you know, good marketing is really easy when you have great engineering. And so the work that we're doing together, like between our companies. Now we have a lot to talk about, right? E mean the work scaling mentioned right around Devil's integration, for example, on power Max right on da npower store, right? I mean, you start looking at the integration work that we're doing together. It means that customers are getting the benefits of the joint integration work and testing right that comes and so you're guaranteed out of the box toe work. Also, you know, don't forget that contain owners and all of the things we're doing around containers. It's basically designed thio accommodate the fact that containers air spun up more quickly or destroyed more quickly, their shared across the hybrid cloud more frequently and without an inherent security model and built in data protection. It's really hard to go and see how you can deploy these with the enterprise resilience that's demanded at enterprise scale. And so that's what we're doing together, right? And, you know, we build great software, Uh, but without great hardware partnerships, it's one hand clapping, right. It's about getting our teams together, right? That really makes it sing at the customer level. >>You know, I think that's a really example of the business. Performance results have come in Vienna, where you guys were doing a great job. Go way back to the years ago when Pat and Raghu we're talking with from Amazon and all. Since then, it's been joint development, join integrations, and that's a great business model for you. And so, Caitlyn, I wanna get back to you. Because at VMRO we covered Project Monterey, the new initiative for the anywhere but a year before they had Project Pacific that came toe life with product results. Tan Xue specifically, you guys have the power protect data manager that we talked about in the summer, but now for Tan Xue supported and Tan Xue environments that super relevant, can you share any updates on your end on the power protect Data Manager and Tan Xue? >>Yeah, I li I couldn't agree more that great engineering mix our jobs a lot more fun and a whole lot easier. So we've been really lucky. And the partnership we've had has really never been stronger. So yeah, but the most recent release of power protect Data Manager introduces the support for that tan xue protection. It also introduces really important things like storage, storage based policy management. So in in biosphere, when you set up a storage policy, you have data protection as part of that and you have the integration with power protect data Manager. So you're able to automatically protect new VM that are created by that storage policy of being applied. >>But >>at the same time, it's also being tracked in power. Protect Data Manager. So you have that consistency across enabling your vitamins and enabling your data protection your i t. Team. To keep track of that, we also have ah tech preview that we did at VM World about how we're working as from Dell technology standpoint to innovate around. How do you protect some of these VMS that are so large and so mission critical that you need to be able to protect them in a new and innovative way that doesn't disrupt the business. And we did a tech preview of that, and it's something you'll hear more about from us, too. But it's PM traditionally would be in this category of unprotected ble because of the impact it could have on the environment and how we're really looking to do that in a more efficient and intelligent way. So we can actually protect those be EMS. And there's there's really a whole lot more. When you talk about objects, scale and everything else that we've done, it's really exciting. And you don't think Lee and I have ever talked as much as we do now. Ah, and it's been a lot of a lot of fun. >>It's been great following both of you guys on the keep interviews over the years. The success in the vision We had early conversations about what the plans where it's kind of all playing out. So I want to congratulate both of you of VM Ware Adele Technology. So good job going forward. The collaboration. I want to get to that in a second, you'll into it. But Caitlin Lee, I want to get your thoughts because one of the big themes this year besides covert and all the issues that that's highlighting. But in the cloud world, automation has been the number one conversation we've been hearing, and with that you got machine learning all the tech around that as you abstract away. The complexity of the infrastructure to make the modern APS automation has been great. The business cross connect is everything is a service we're seeing. This is the big wave coming. Could you guys share your vision on how all this stuff you mentioned V balls and all objects scale all these things? There's a >>lot of >>plumbing underneath and a lot of tooling, a lot of part piece parts. If that gets programmable, >>automation >>kicks in, which then enables everything is the service because you guys both share your vision of what that means in terms of what's going to change and what would it impact the customer? >>Yeah, and it's very relevant for this week, right? Dell Technologies world. That's a big part of what we've announced this week in our commitment to really bringing our portfolio as a service, and it's really interesting, especially for folks like Lee and I, who have been doing kind of mawr product marking and talking about speeds and feeds and thinking about how you make the product life simpler. And how do you automate that? Have the intelligence built in things like Biaro have been such an important part of that, especially with power store coming to market. But if you think about where that leads us, actually changes everything, which is when you have everything as a service and we're really delivering outcomes to our customers and no longer products. That automation is actually just a important and maybe even more important. But it's not the end user that cares about it directly is actually us, because as Dell Technologies, we become the ones managing that infrastructure, owning that infrastructure and the more automation we can bring in, the more intelligence we can build them for ourselves. The more insights we can give to our customers, the better that service can become. And it's really a flip from how we've always been thinking about and really rolling out automation. It's not actually about enabling our end users to do anything. It's actually about enabling them to not worry about any of it, but enable our own organization to support their outcomes better. So it really changes everything. >>Lee, what's your thoughts on this? Everything you've got, V Sphere V Center. You've got all the storage you got all the back up. All this stuff has to be automated. Makes sense. But as a service, how does that impact your world? >>You know, it really does. When you think about the VMRO Cloud Foundation, right, which is the integration of all of our V sphere with Visa. And with these, you know, our NSX products that will be realized. Management suite. Tom Zoo now, right, All of this pulled together. One of things that's interesting is when you go to the public cloud, we have some experience now where we always deliver that full stack together. And what that does is it frees up customers. Thio, go on, focus on the applications, I think and stop looking down the infrastructure. Start looking up at the APS. And so we're offering and bringing that same level of experience to the on premises data centers. And now bridging that across the hybrid cloud that all of a sudden gives you this sense that Hey, I'm future ready. No, matter where I am today. If I'm thinking about the hybrid cloud, I could go on move there, right. And with our partnership with Dell Technologies, there's such a great opportunity to bridge that uniquely, by the way across all of my on premises infrastructure, including common policy based management, back into storage through RV Valls efforts, right and then back in through objects scale right into objects based, uh, applications and through our DP efforts to data protection efforts, then back into, like, date full data protection. And so what you get now is we're helping customers realize that I got this. I could take new Cooper navies orchestrated applications and I could make them work and do it with the same operational model that I have today. Start spending more time on the applications, less time, basically configuring and managing underlying infrastructure. >>Caitlin you mentioned that earlier at the top of the segment, ease of use, making it easier, simpler, great stuff on the on on the future. Lee, I gotta ask you about Project Monterey. We did a lot of coverage on VM World on silicon angle in the Cube. I love how this comes out. It's always, You know, the brain trust that VM Ware lays out the future, they fill it in throughout the year, expect to see some meat on the bone there. But what is that gonna do from for new capabilities and how with Dell Technologies? Because, um, it's end to end, right this Michael Dell and I talked, I think, two years ago, a Dell Tech world. And then last year, he hit the point home hard and to end with Dell Technologies. It kind of feels like it's gonna be a good fit. Could you share how that Monterey project fits in with Dell Technologies? >>Yeah. We're so pleased to be showing this together with Dell Technologies at the VM World to showcase this new idea that you could basically go on, start offloading CPUs and using smart knicks as a way to basically now provide, um or let's call it a, You know, a architecture that allows you to, uh, be responsive to new application needs. So let me talk a little bit about that. So when we opened up Tansu, right, we got this complete inflow pouring of new container base kubernetes orchestrated APS. So what? We found was, Hey, they're driving a lot of CPU needs their driving a lot of scale out security needs for things like distributed firewalls. And so we started looking at this, and what's clear is we need to basically use the CPU very judiciously, So it's basically reserved for the APS. And so what we're doing now is we're basically saying there's an opportunity for us to go in, offload the CPU for things that look more like infrastructure, including S X, I and other things. And at the same time, then we could go and work together with Dell Technologies to be the deployment vehicle. And so, just like Project Pacific, which was going broad, if you will, this project moderate, which is going deep like the canyon, John not far from here, um is, you know, a source of all new discovery right where we'll be working together and over time, just like the Project Pacific name faded to black and became product Tan Xue vcf with Tom juvie sphere. With Hangzhou, we'll see that Project Monterey will evolve into new products coming together with Dell Technologies. >>Caitlin, can you elaborate on Take a min, explain the product how this renders into products because I can also imagine just the benefits just from a security standpoint. Efficiency. If the platform, um, there's a range of things, could you take a minute to >>explain the >>impact on products? >>Yeah, I think you'll hear a lot more about it, but we're obviously excited to be partners on this is Well, and I think it's It's just another example of the more intelligent the infrastructure can become than the rest of the entire I T organization can run more efficiently and that that can come in the form of the A. I built into power, Max, that can come in the form of the evils that we have both in Power Max and Power Store that can come in the form of even just the fact that we have now built a fully containerized S three compatible objects or platform called objects scale which we have no in early access. Um, that can run on the V sand data persistence platform, and it just gives you the ability to leverage this all of the right technology. And we can continue to really partner on that. I think Project Monterey really opens up even more opportunities to do that, and you'll certainly hear more from us on that in the future. >>I >>mean, you got compression, you got encryption. A lot of benefits across the board. Great to have you guys both on and your graduation. The great event. Final question for both of you, talk about this has been a crazy year. We're not face to face, so everything will be online. What should customers and partners and people watching know about the relationship between VM Ware and Dell Technologies this year? What's the big message to take away? What should people walk away with and and think about? >>I think it's It's never been stronger than ever, uh, than it's been than it is right now. We have never had >>more >>breath and more depth of integration. I think that the partnership on the engineering level, on the product management level on the marketing level, we have really never been in a better place. And you know what? What? My team is really enjoyed with VM world season and you're coming up on Deltek. World season is we've really enjoyed the fact that we've had so much richness >>of >>that integration to talk >>about, and >>we also know there's even more coming. So I, you know, from from my standpoint, if we really feel it and probably the best and most rewarding time we hear about that, is when we bring new things into market, we hear that back. And when Power Store came into the market and over the past few right kind of first months in market, one of the most resounding feedback that has come out as one of the most differentiated parts is that it? It's so incredibly integrated with VM ware. But we've even gotten questions from analysts asking, you know, did you purposely make it feel like you are really working similarly to a B M or environment? And you know what? That just shows how closely we have been working as organizations is that it comes a very seamless experience for our customers. >>Lee Final Word. >>What >>should people walk away with this year on the relationship between Be and we're in Dell Technologies? >>Well, I think the best partnerships right are ones that are customer driven. And what you're finding here is customers. They're actually encouraging us, right? We're doing a lot of three way meetings now, right where customers like, Hey, tell me how you're going to go involved this. How do I How do I basically modernized right and preserve my existing investment, perhaps Or, you know, update here, Or how do I grow like customers have really complex individual situations. And what you confined right is that we're helping jointly not, you know, just simply with the engineering side, which is awesome, but also with the idea that we're helping customers go on deploy responsibly in a time where it's very difficult to plan. And so if you come to us, we can help you jointly plan for the future in uncertain times and make sure that you're gonna be successful. And that's just a great feeling when you're a customer looking at, How do you deploy going forward in this? You know, with the amount of pace of change that we've got, >>I want to congratulate. Both of you have been following you guys. Success has been proven out on the business results and also the products and the enablement that you guys are providing customers been great. Thanks for coming on. Great to see both of you have a great event. Thanks for. Come on. >>Thank you. It's a pleasure. >>Okay, I'm John for your here with the Cube. Covering Del Technology Worlds Digital experience 2020 The Cube Virtual. >>Thanks for watching.

>> Live from Las Vegas; it's the Cube. Covering the AWS Accenture Executive Summit. Brought to you by Accenture. >> Welcome back everyone to the Cube's live coverage of the AWS executive summit here at the Venetian in Las Vegas Nevada. I'm your host Rebecca Knight. We have two guests for this segment. We have Hitoshi Ienaka the CEO of ARISE Analytics and Takuya Kudo the Chief Sciences Officer at ARISE. Thank you both so much for coming on the program. >> Thank you. >> So I want to start by having you tell our viewers a little bit more about ARISE analytics. >> Well ARISE analytics is a joint venture between KDDI and Accenture. Well last, well last year we established a company yeah. That's family. >> Right and that's you know kind of we provide like tying the capabilities and the KDDI is kind of number two mobile network operator in Japan, has 50 million subscribers, massive data. So that's there a lot of room to cook but they don't have enough capability to support that. So that's why we kind of married together. >> And it helps companies leverage a wealth of knowledge resources and data between firms to bring about digital transformation. >> Right. >> That's what you're doing. So talk a little bit about what you've seen so far. >> Well so we have two assets, KDDI has, well big data and well Accenture has, well a lot of analytic skills. So using this well these assets, we built our integrated analytics platform hosted on a eda-brais. And what our first challenge was to deduce, channel out to the other operators and were which caused a challenge risk to well more than 40 million subscribers and by digging into that data and using machine learning origin and our data includes (mumbles) and life style service usage. And well, we optimize customer channels and contact timing and well to target customers efficiently. And well we well we tried art of well, other event well art of >> (mumbles) >> Yeah yeah. >> Yeah (mumbles) marketing. >> Okay. >> Yeah and we can get a good result and well it was not only due to our activities but only last year, only KDDI well could increase the market share among three network operators in Japan. That is our our achievements yeah. >> That's very impressive! So can you talk a little bit about the initial pilot in particular what you saw. Taku, do want to? >> Right so like as he mentioned like we have two work stream gigantic work stream. One is for consumer facing right. So customer chai and the you know out of on three marketing's or like recommendation engines based upon this stream data because we have massive like this is a consumption data too. Not just about like you know one handset data. In another work stream is a B2B, a business domain which is sounds like not related to mobile network operators but they have massive network to sell to B2B customer. So we utilize those gigantic data, combine those maybe I can mention but data but combine those data creating new service model. So that's quite a new IOT initiatives for B2B layers and consumer initiatives you know to support ongoing current business. >> And you're using this in a variety of sectors in particular I wanted you to ask you about one that you're doing with Toyota and a taxi service. >> Right so (mumbles) so yeah that that one is like five years like example because a, unless otherwise, I don't think that new business model to compete with Uber never happened right? So KDDI provide like Maura Handu said like location data over like you indigenous subscribers creating some, you know demand side riders for (mumbles) right? Over there, on top of that Toyota's transact log, which is technically like kinematics data provide like supply side which is cause, right? Focusing model and taxi also provide like meters, where customer riders get in and get off and combine those three completely different cable and data sets. >> But also with things like weather and those kinds of other >> Exactly yeah. >> outside. >> Open data too. And combine those data sets. We in, we provide, Accenture provides like talents and creating completely new forecasting model it's called AI taxi dispatch model. So now if you go to Tokyo, majority of taxi has our algorithm like Arizona takes in, you know KDDI and Accenture provide it. >> So that's very cool! Can you talk a little bit about what you've learned, about, in terms of when the weather is like this, taxis happen this >> Yeah, so it's of course weather has massive impact over, like if it's mornings specifically lane, it boosts like demands and also events. We have also events data. Maybe I don't know concerts, some famous singer, celebrities came and it's you know boost like riders demands. So that's actually significant impact of our demand focused model. Rather than using pushing like Uber, you strike you know app, mobile app. we actually treated as (mumbles) like taxi actually go because taxi driver and I can see where is a hot spot to pick up riders. And that's what we try to do. So based up on those, you know people don't even have like maybe like my father's age right, that don't have a smartphone they can get the benefit universality right. So that's the base concepts to provide Universal model to those you know without these >> So even people lacking technology >> Right exactly. >> Can still reap the benefits of this kind of approach. >> (mumbles) is universality so that's also our business strategy. Yeah. >> So you're also using this approach in a manufacturing environment. >> Yeah that's right. We are also working with some manufacturing factory. On the factory field were experienced workers can detect machine breakdown before they occur. But well how can that not be passed on to less experienced employees? So we created a live predictive maintenance which alerts companies ahead of time to pre potential breakdowns. Sensors (mumbles) about things like vibrations, temperature and electrical current. The collected data is analyzed by the AI system. So in this way the prediction of machine (mumbles) can be performed by almost anyone. Well it used to be others by only experienced employees before, yeah. >> So it not only helps the company know when a machine is going to fail, it also empowers the employee to fix it him or herself. >> Right it's a preventive way and so it's up and running over the ad-abreis. We use kinesis in late shift you know, learn the functions and over EC2. So that's completely free stock over ad-abreis capability too. >> So what you're describing sounds like it requires a lot of collaboration, a lot of deep relationship building between not only Accenture and KDDI but also the clients that you're working with. Can you describe how you all work together? >> Right. So maybe I'm going to provide that information. So like of course like KDDI's employee has specific domain knowledge and we provide like you know like data science capabilities and also like maybe through the interview right, found workers or like taxi, they have specific domain knowledge So combine those collaboration. It's called two in the box and we collaboratively paired each employees and you know supply the knowledge each other so that's it. Just one is not enough but as a team integrated over database and created a very strong team and that's a you know we try to cherish and that's culture. And the two boost the data science, data driven companies decision-making process. >> So i think our viewers are pretty amazed and impressed with what's going on. But in this era of 5G and IOT, what's next, what are you working at? It's a relatively new partnership. What are what are some of the most exciting things in the pipeline? >> So the (laughs) the very strategic so we strategizing right now in terms of 5G in IOT. But definitely one of the pieces could be like deep learning right? And also about your realities which nobody has done before. So that's where we try to collaborate with other sectors, industries, to create a new. And to do so we need a massive like computation power like GPU servers and we have to rely on the ad-abreis because otherwise we cannot achieve those goals and specifically 5G maybe changing in the game. Maybe like you know low latency and you know wireless connectivity, you know we don't need connections so maybe the factory lining assembly lines. You know completely change the way crispy like edge computing no more. Maybe like for computing, right, in between like Saba and edge because of the 5G. I don't know but we are strategizing now in a very exciting moment. We are doing right now. >> Indeed it is. >> Yeah. >> Well Hitoshi, Taku, thank you so much for coming on the Cube. This was a lot of fun. >> Thank you very much. I'm Rebecca Knight. Stay tuned for more of the Cube's live coverage of the AWS Executive Summit coming up just after this. (Uptempo music)

>> Narrator: Vancouver, Canada. It's theCUBE, covering OpenStack Summit North America, 2018. Brought to you by Red Hat, the OpenStack Foundation and its Ecosystem partners. (soft music) >> Hi, and you're watching SiliconANGLE Medias coverage of theCUBE, here at OpenStack Summit 2018 in beautiful Vancouver. I'm Stu Miniman with my co-host John Troyer. We've been here, this is now the third day of coverage, John. We've done a couple dozen interviews already. We've got one more day of coverage. We had some kind of perceptions coming in and I have some interesting differing viewpoints as to where we are for OpenStack the project, where this show itself is going. First of all John, give me your impressions overall. Vancouver, your first time here, city I fell in love with last time I came here, and let's get into the show itself, too. >> Sure, sure, I mean the show's a little bit smaller this year than it had been in past years. Some of that is because they pulled some of the technical stuff out last year, or a couple years ago. By being a little bit smaller, and being in a place like Vancouver, I get good energy off of the crowd. The folks we've talked to, the folks that have been going to sessions, have said they've been very good. The people here are practitioners. They are running OpenStack, or about to run OpenStack, or upgrading their OpenStack, or other adjacent technologies. They're real people doing real work. As we talk to folks and sponsors, the conversations have been productive. So, I'd say in general, this kind of a small venue and a beautiful city allows for a really productive community-oriented event, so that's been great. >> Alright, so John come on, on the analysis segment we're not allow to pull any punches. Attendance, absolutely is down. Three years ago when we were here it was around 5500. Mark Collier, on our opening segment, said there was about 2600. But two-year point, I've not talked to a single vendor or attendee here that was like, "Oh boy, nobody's here, "it's not goin' on." Yes, the Expo Hall is way smaller and people flowing through the Expo Hall isn't great all the time, but why is that? Because the people that are here, they're in sessions. They have 40 sessions about Edge Computing. Hot topic, we've talked a bunch about that. Interesting conversations. There is way more in Containers. Containers for more than three years, been a topic conversation. There's so many other sessions of people digging in. The line you've used a couple a time is the people here are people that have mortgages. In a good way, it means these are jobs, these are not them, "Oh, I heard about "this cool new thing, and I'm going to "go check out beautiful Vancouver." Now, yes, we've brought our spouses or significant others, and checking out the environment because yeah, this place is awesome, but there's good energy at the show. There's good technical conversation. Many of the people we've talked to, even if they're not the biggest OpenStack fans, they're like, "But our customers are using this in a lot of different ways." Let's talk about OpenStack. Where is it, where isn't it? What's your take from what you've heard from the customers and the vendors? >> Sure, I definitely think the conversation is warranted. As we came in, from outside the community there was a lot of conversation, even backchannel, like why are you going to OpenStack Summit? What's going on there, is it still alive? Which is kind of a perception of maybe it's an indication of where the marketing is on this project, or where it is on the hype cycle. In terms of where it is and where it isn't, it's built into everything. At this point OpenStack, the infrastructure management, open infrastructure management solution, seems to be mature. Seems to be inside every Telco, every cable company, every transportation company, every bank. People who need private resources and have the smarts and power to do that have leveraged OpenStack now. That seems stable. What was interesting here is, that that doesn't speak to the health overall, and the history of, or the future of the project itself, the foundation, the Summit, I think those are separate questions. You know, the infrastructure and projects seem good. Also here, like we've talked about, this show is not just about OpenStack now. It's about Containers, it's broadening the scope of these people informally known as infrastructure operators, to the application level as well. >> Yeah, if you want to hear a little bit more, some two great interviews we did yesterday. Sean Michael Kerner, who's a journalist. Been here for almost every single one of the OpenStack shows. He's at eWeek, had some really good discussion. He said private cloud, it doesn't exist. Now, he said what does he mean by that? There are companies that are building large scalable cloud with OpenStack but it's like if some of the big China Telecom, big China cloud companies. Oracle and IBM have lots of OpenStack, in what they do, and yes there are, as you mentioned, the telcos are a big used case. We had some Canonical customers talking about Edge as in a used case for a different type of scalability. Lots of nodes but not one massive infrastructure as a service piece. If I talk, kind of the typical enterprise, or definitely going the SNE piece of the market, this is not something that they go and use. They will use services that have OpenStack. It might be part of the ecosystem that they're playing, but people saying, "Oh, I had my VMware environment "and I want to go from virtualization "to private cloud" OpenStack is not usually the first choice, even though Red Hat has some customers that kind of fit into some of the larger sides of that, and we'll be talking to them more about that today. Randy Bias is the other one, take a look. Randy was one of the early, very central to a lot of stuff happening in the Foundation. He's in the networking space now, and he says even though he's not a cheerleader for OpenStack, he's like, "Why am I here? "That's where my customers are." >> Right, right. I mean, I do think it's interesting that public cloud is certainly mentioned. AWS, Google, et cetera, but it's not top of mind for a lot of these folks, and it's mentioned in very different ways depending on, kind of, the players. I think it's very different from last week at Red Hat Summit. Red Hat, with their story, and OpenShift on top of OpenStack, definitely talked public cloud for folks. Then they cross-cloud, hybrid-cloud. I think that was a much different conversation than I've been hearing this week. I think basically, kind of maybe, depends on the approach of the different players in the market, Stu. I know you've been talkin' to different folks about that. >> Yeah, absolutely. So like, Margaret Dawson at Red Hat helped us talk about how that hybrid-cloud works because here, I hate to say it's, some oh yeah, public cloud, that's too expensive. You're renting, it's always going to be more. It's like, well no, come on, let's understand. There's lot of applications that are there and customers, it's an and message for almost all of them. How does that fit together, I have some critiques as to how this goes together. You brought up another point though John, OpenStack Foundation is more than just OpenStack projects. So, Kata Containers, something that was announced last year, and we're talking about there's Edge, there's a new CI/CD tool, Zuul, which is now fully under the project. Yes, joke of the week, there is no OpenStack, there's only Zuul. There are actually, there's another open-source project named Zuul too, so boy, how many CI/CD tools are out there? We've got two different, unrelated, projects with the same name. John, you look at communities, you look at foundations, if this isn't the core knitting of OpenStack, what is their role vis-a-vis the cloud native and how do they compare to say, the big player in this space is Linux Foundation which includes CNCF. >> That's a good one. I mean, in some sense like all organic things, things are either growing or shrinking. Just growing or dying. On the other hand, in technology, nothing ever truly dies. I think the project seems mature and healthy and it's being used. The Foundation is global in scope and continues to run this. I do wonder about community identity and what it means to be an OpenStack member. It's very community-oriented, but what's at the nut of it here if we're really part of this cloud-native ecosystem. CNCF, you know, it's part of Linux Foundation, all these different foundations, but CNCF, on the other hand, is kind of a grab-bag of technology, so I'm not sure what it means to be a member of CNCF either. I think both of these foundations will continue to go forward with slightly different identities. I think for the community as a whole, the industry as a whole, they are talking and they better be talking, and it's good that they're talking now and working better together. >> Yeah, great discussion we had with Lisa-Marie Namphy who is an OpenStack Ambassador. She holds the meat up in Silicon Valley and when she positions it, it's about cloud-native and its about all these things. So like, Kubernetes is front and center whereas some of the OpenStack people are saying, "Oh no, no, we need to talk more about OpenStack." That's still the dynamic here was, "Oh, we go great together." Well, sometimes thou dost protest too much. Kubranetes doesn't need OpenStack, OpenStack absolutely must be able to play in this Container, cloud-native Kubranetes world. There's lots of other places we can learn about Kubranetes. It is an interesting dynamic that have been sorting out, but it is not a zero-sum game. There's absolutely lots, then we have, I actually was real impressed how many customers we got to speak with on the air this time. Nice with three days of programming, we had a little bit of flexibility, and not just people that were on the keynote stage. Not just people that have been coming for years, but a few of the interviews we had are relatively new. Not somebody that have been on since very early in the alphabet, now we're at queens. >> Right. >> Anything more from the customers or that Container, Kubranetes dynamic that you want to cover? >> Sure, well I mean just that, you know, Containers at least, Containers are everywhere here. So, I think that kind of question has been resolved in some sense. It was a little more contentious last year than this year. I'm actually more bullish on OpenStack as a utility project, after this week, than before. I think I can constantly look people in the eye and say that. The interesting thing for me though, coming from Silicon Valley, is you're so used to thinking about VCs and growth, and new startups, and where's the cutting edge that it's kind of hard to talk about this, maybe this open source business model where the customer basis is finite. It's not growing at 100% a year. Sometimes the press has a hard time covering that. Analysts have a hard time covering that. And if you wanted to give advice to somebody to get into OpenStack, I'm not sure who should if they're not in it already, there's definitely defined use cases, but I think maybe those people have already self-identified. >> Alright, so yeah, the last thing I wanted to mention is yeah. Big thank you to our sponsors to help get us here. The OpenStack Foundation, really supportive of us for years. Six years of us covering it. Our headline sponsor, Red Hat, had some great customers. Talked about this piece, and kind of we talk about it's practically Red Hat month on theCUBE for John with Red Hat Summit and OpenStack. Canonical, Contron, Nuage Networks, all helping us to be able to bring this content to you. Be sure to check out theCUBE.net for all the coverage in the past as well as where we'll be. Hit John Troyer, J. Troyer, on Twitter or myself, Stu, on Twitter if you ever have any questions, people we should be talking to, viewpoints, whether you agree or disagree with what we're talking about. Big thanks to all of our crew here. Thank you to the wonderful people of Vancouver for being so welcoming of this event and of all of us. Check out all the interviews. For John Troyer, I'm Stu Miniman. Thanks for watching theCUBE. (soft upbeat music)

>> Live, from Barcelona, Spain, it's the CUBE, covering CISCO Live 2018, brought to you by CISCO, Veeam, and the Cube's ecosystem partners. Welcome back, I'm Stu Miniman, and this is the CUBE's coverage of CISCO Live 2018 in Barcelona. You know, I'm a networking guy by background, but there's certain people in the industry that really I've gone to to learn, been really thrilled that I've had the opportunity to get to know, and every once in awhile I get to bring them to our audience, and really happy to bring back to the program Ivan Pepelnjak, from Slovenia, blogger, author, webinar, generally, you know, that network guy that those of us who watch the industry know. >> That grumpy networking guy. >> Ah, ya know, aren't most networking people at least online at least a little bit grumpy? And when you meet 'em in person, though, it's a slightly different experience, so thanks for joining us. >> Ah, thank you for inviting me. >> All right, so 2013 was the last time that we actually go to do one of these in person. >> Ivan: That's true. >> So networking, it's all the same, right? >> Ivan: It is. >> I mean we're probably still working on 10 gig rollout, ah, maybe 25 or 50 gig, speeds and feeds, and, ya know, oh, okay, ya know, IPV 6, I think we're kind of getting there, lots of other acronyms. We could talk awhile. But really, what's been some of the big things that you've been looking at? What are customers actually doing, and what are customers thinking of that you've been playing with? >> Well, it's amazing how little has changed. >> People are still talking about SDN like that's the big thing. No one has delivered on that apart from some point products like VMware, NSX, or CISCO ACI. Cloud is still the thing that will happen next year to most companies. We hear how 90% of all the companies that participate in some survey are using Cloud. And then the next question I'll ask is, "Well, is this Office 365, "or is this something more?" And they go like, "Well the survey "didn't differentiate on that." So thank you. >> Yeah, but, yeah look. The SDN, a friend of mine said SDN stands for Still Does Nothing. That being said, ACI, NSX, there's customers using it. >> Ivan: Oh, absolutely. >> It has not totally transformed the industry like they said. Cloud, I've yet to find a company that's not doing some SAS, and unless you have some regulation or things like that, you at least have some sandbox that you're doing some public Cloud. >> Ivan: Absolutely. >> But, absolutely people, they still have data centers, despite... >> Ivan: Well, it's a... >> It might not be their own building anymore. I was just talking to a service provider and the like, but yeah, I mean, the more things change the more things stay the same, right? >> Absolutely. Well yeah, we do see people moving to colos or, they would build their stuff somewhere else, or whatever, but it's amazing how much interest I am still getting in data center design courses, so there are still zillions of people who think that that is important, and yes, we all know we'll go to the Cloud, but everyone has his own hurdles, and so I think that eventually everyone will get to some sort of hybrid Cloud, where some stuff will be there, and some stuff legacy whatever will be here, and we'll have to live with that forever. >> Yeah, I mean, those of us we think back, I remember when this wave came, it was like, well, remember the XSPs in the 90s? There were two reasons why it failed. Number one, there wasn't enough network, and number two, ah, security. Well, you fast forward to, you know, two decades, and the network's gotten way better. I've got great speeds, and stuff like that, but you know physics is still a factor- >> Ivan: Well, yeah. >> And security is even more of an issue today than it was 20 years ago, I think. >> This started as a joke, but it is becoming more and more true. If you move to the Cloud, your security actually improves. >> Stu: Right. >> Because they have some security and you had none before. (both laugh) >> I at least get to rethink my security. >> Yeah. >> When I make some transformation. >> No, and they have the basics right. >> Right. >> Like physical access control, multi-tenant separation, encryption, trunk authentication. They get those things right, because otherwise they would be out of business. >> Okay, so we spent like more than a decade with how virtualization in networking. Have we gotten most of that at least reasonably well now? >> There are still people who don't get that ethernet was designed to be used on a single cable. So they still think that stretching a single ethernet across wide distances is a great idea, and everyone is still letting them get away with that. >> Yeah. >> Fortunately the Cloud vendors aren't buying. So if you want to move to Amazon, Google, whoever else, you have to redesign your applications and make them work correctly. So, eventually this thing will die, but it's like COBOL and mainframes, it will be there forever. >> Yeah, I mean, we've been saying for a few years on the Cube now that the challenge of our time is really distributed architectures, and of course they have a huge impact on networking, so how's the industry doing? How would you rate, you know, say we're here at CISCO Live, you know, how are they doing helping customers with these challenges? >> Most of them don't. >> I mean, if you look at a typical enterprise application, it still isn't developed for a distributed environment. Yeah, they use three tiers of servers, like always, but then they try to cope by solving all the problems in the ops phase, when they deploy stuff. And that's the biggest problem we are facing today. We are not changing the development processes and paradigms. >> Well, we're actually here in the Dev Net zone. I mean, I give CISCO kudos. Last time I came to CISCO Live was 2009. There weren't, we didn't talk about developers. >> Really? >> Everybody was, you know, doing plug fests, and getting their latest certification, but they're trying to embrace the developers more. There seem to be more of them here. >> Yeah. >> That boundary between network operator and developer, do you see? You know, is there communication, or are the network guys still stuck in a closet somewhere not talking to anybody? >> Well, there are two types of challenges. The first type of challenge is that the network guy in particular, but ops teams in general, are still not invited to the table when new stuff is discussed. So, the application developers dream up something based on their best knowledge. I mean, they're not evil or anything. They just don't know the operational impact of their decision. And because the networking security virtualization people are not at the table, then they have to cope with whatever these guys dream up in isolation. I'm never blaming them, because, you know, we should education them, and we are not doing that. >> Yeah. >> So anyone who manages to bring security, networking, and storage people in when the application architecture is being designed is my hero. But there are only few of them. And the other challenge is that the networking people don't realize that their world has changed. That they can't manually provision VLANs the way they've been doing for the last 20 years, and it's amazing once they get it, once they start simple automation stuff, how creative they become. What types of problems they solve. They don't have the shackles of CLI anymore. I shouldn't be saying that. (both laugh) I'm the old CLI junkie. But it's amazing how much can be done once you realize that you don't have to do everything manually. >> Yeah, CISCO's, you know, not shy about putting out strong visions. Marketing is definitely part of what they do. And the keynote this morning said it's a new era, and new infrastructure, powered by intent, informed by context. It sounded like a nice message, but this whole intent-based networking, what's your take on it? Is this, you know, are we going to come back five years from now and talk about intent based like we did SDN? Or, you know, what's your take? >> Well, let's keep in mind that this is all hype. What we're really talking about is an orchestration system with an abstraction layer. 'Cause first, it's really hard to define what intent based is, because there's no good definition. But there is a definition in programming which differentiates between declarative programming and imperative programming. And if we use declarative programming as something which could be intent based, that thing says, well, I don't tell the machine, or whatever, the system, how to do things. I just tell it what to do. And if you take a look at that from that perspective, then you figure out that every device configuration is an expression of your intent. >> Right. >> You never tell the device how to work. >> Yeah. >> You just tell the device what to do. >> Right. It's interesting, Ivan. I think back, you know, we used to manage individual boxes. Then we kind of created a little bit more pools, and the challenge they see right now is with the explosion of device, we're not going to have time to talk about all the IOT edge piece and everything, but there's no way an admin or a team of admins are going to be able to help there, so I need to infuse, I hate that, the ML, AI, choose your buzzword of choice, though, the machines need to be able to manage that a little bit more, you know, autonomous networks or something they (mumbles). I understand you're skeptical, so how do we get there, or, you know, otherwise, this whole label crap. >> There are two, there are three totally different things here. The first one, I totally agree with you that we should view networks as a single entity. Configuring boxes is stupid, and it's like, these admins don't do that. Well, some still do. They get the results they deserve. So, we should start thinking about network-wide data models which are then translated into device intent, which is really device configuration. And that makes absolute sense. But remember what I said. This is just a glorified orchestration system with an abstraction layer. The second problem is machine learning. Some of the things we are dealing with have physical limitations, like the speed of light, or the number of things you can put into a hardware forwarding table. Once you're faced with those physical limitations, it's like, you know, self-driving cars, yeah, they are self driving, but they cannot go 300 miles per hour because laws of physics. So, it's one thing to say, well, I have these infinite resources and I can learn how to play Go in eight hours. >> Right. >> And it's a completely different thing to say now I will figure out how to deal with my network, which has this physical limitations. And also, you know, whenever I hear about these autonomous distributed thingees, we have routing protocols. They have been autonomous and distributed and self healing for decades, and we didn't call them machine learning or artificial intelligence. And, finally, once you get to the bottom of it, and you're faced with all those physical limitations, and now, let's say you want to solve a simple problem, which is, how do I optimize the use of my network? You do some research. You figure out that this problem has been solved 20 years ago. There are companies with commercial products that have solved this problem. It's just that no one is using them because they are too expensive, because what you can save by using them doesn't offset the cost that these people had to invest into R and D to make this work. So, machine learning, yeah. Can you make it cheaper? I don't think so. >> All right, so, Ivan, I want to give you the last word. >> Mm-hmm. >> Grumpy networking, what do you look forward to the most at this show, and any final anecdotes you want to share, before we have to wrap? >> Well, the one thing I am looking forward is to see people to start automate their networks. To jump over that mental barrier, and when they break through it, it's amazing how many success stories you get. So I know a number of networking engineers who were on my automation course, and six months later, they write me saying, "Now I have this thing in production, "and we cut down the site deployment "from three days to five minutes." When I read emails like that, it's like, "You're my hero." >> Excellent, well I love it. For a grumpy person, you sure sound a little bit of an optimist about what some of the people come in and get this. Maybe a realist is more right. Ivan Pepelnjak, really appreciate you joining us. We'll be back with lots more coverage from CISCO Live 2018 from Barcelona. I'm Stu Miniman. You're watching the Cube. (the Cube jingle)

(upbeat music) >> Hi we're at the Palo Alto studio of SiliconANGLE Media and theCUBE. My name is George Gilbert, we have a special guest with us this week, Veeru Ramaswamy who is VP IBM Watson IoT platform and he's here to fill us in on the incredible amount of innovation and growth that's going on in that sector of the world and we're going to talk more broadly about IoT and digital twins as a broad new construct that we're seeing in how to build enterprise systems. So Veeru, good to have you. Why don't you introduce yourself and tell us a little bit about your background. >> Thanks George, thanks for having me. I've been in the technology space for a long time and if you look at what's happening in the IoT, in the digital space, it's pretty interesting the amount of growth, the amount of productivity and efficiency the companies are trying to achieve. It is just phenomenal and I think we're now turning off the hype cycle and getting into real actions in a lot of businesses. Prior to joining IBM, I was junior offiicer and senior VP of data science with Cable Vision where I led the data strategy for the entire company and prior to that I was the GE of one of the first two guys who actually built the Cyamon digital center. GE digital center, it's a center of excellence. Looking at different kinds of IoT related projects and products along with leading some of the UX and the analytics and the club ration or the social integration. So that's the background. >> So just to set context 'cause this is as we were talking before, there was another era when Steve Jobs was talking about the next work station and he talked about objectory imitation and then everything was sprinkled with fairy dust about objects. So help us distinguish between IoT and digital twins which GE was brilliant in marketing 'cause that concept everyone could grasp. Help us understand where they fit. >> The idea of digital twin is, how do you abstract the actual physical entity out there in the world, and create an object model out of it. So it's very similar in that sense, what happened in the 90s for Steve Jobs and if you look at that object abstraction, is what is now happening in the digital twin space from the IoT angle. The way we look at IoT is we look at every center which is out there which can actually produce a metric on every device which produces a metric we consider as a sense so it could be as simple as the pressure, temperature, humidity sensors or it could be as complicated as cardio sensors and your healthcare and so on and so forth. The concept of bringing these sensors into the to the digital world, the data from that physical world to the digital world is what is making it even more abstract from a programming perspective. >> Help us understand, so it sounds like we're going to have these fire hoses of data. How do we organize that into something that someone who's going to work on that data, someone is going to program to it. How do they make sense out of it the way a normal person looks at a physical object? >> That's a great question. We're looking at sensors as a device that we can measure out of and that we call it a device twin. Taking the data that's coming from the device, we call that as a device twin and then your physical asset, the physical thing itself, which could be elevators, jet engines anything, physical asset that we have what we call the asset twin and there's hierarchical model that we believe that will have to be existing for the digital twin to be actually constructed from an IoT perspective. The asset twins will basically encompass some of the device twins and then we actually take that and represent the digital twin on a physical world of that particular asset. >> So that would be sort of like as we were talking about earlier like an elevator might be the asset but the devices within it might be the bricks and the pulleys and the panels for operating it. >> Veeru: Exactly. >> And it's then the hierarchy of these or in manufacturing terms, the building materials that becomes a critical part of the twin. What are some other components of this digital twin? >> When we talk about digital twin, we don't just take the blueprint as schematics. We also think about the system, the process, the operation that goes along with that physical asset and when we capture that and be able to model that, in the digital world, then that gives you the ability to do a lot of things where you don't have to do it in the physical world. For instance, you don't have to train your people but on the physical world, if it is periodical systems and so on and so forth, you could actually train them in the digital world and then be able to allow them to operate on the physical world whenever it's needed. Or if you want to increase your productivity or efficiency doing predictive models and so forth, you can test all the models in your digital world and then you actually deploy it in your physical world. >> That's great for context setting. How would you think of, this digital twins is more than just a representation of the structure, but it's also got the behavior in there. So in a sense it's a sensor and an actuator in that you could program the real world. What would that look like? What things can you do with that sort of approach? >> So when you actually have the data coming this humongous amount of terabyte data that comes from the sensors, once you model it and you get the insights out of that, based on the insight, you can take an actionable outcome that could be turning off an actuator or turning on an actuator and simple thngs like in the elevator case, open the door, shut the door, move the elevator up, move the elevator down etc. etc All of these things can be done from a digital world. That's where it makes a humongous difference. >> Okay, so it's a structured way of interacting with the highly structured world around us. >> Veeru: That's right. >> Okay, so it's not the narrow definition that many of us have been used to like an airplane engine or the autonomous driving capability of a car. It's more general than that. >> Yeah, it is more general than that. >> Now let's talk about having sort of set context with the definition so everyone knows we're talking about a broader sense that's going on. What are some of the business impacts in terms of operational efficiency, maybe just the first-order impact. But what about the ability to change products into more customizable services that have SLAs or entirely new business models including engineered order instead of make to stock. Tell us something about that hierarchy of value. >> That's a great question. You're talking about things like operations optimization and predicament and all of that which you can actually do from the digital world it's all on digital twin. You also can look into various kinds of business models now instead of a product, you can actually have a service out of the product and then be able to have different business models like powered by the hour, pay per use and kinds of things. So these kinds of models, business models can be tried out. Think about what's happening in the world of Air BnB and Uber, nobody owns any asset but still be able to make revenue by pay per use or power by the hour. I think that's an interesting model. I don't think it's being tested out so much in the physical asset world but I think that could be interesting model that you could actually try. >> One thing that I picked up at the Genius of Things event in Munich in February was that we really have to rethink about software markets in the sense that IBM's customers become in the way your channel, sometimes because they sell to their customers. Almost like a supply chain master or something similar and also pricing changes from potentially we've already migrated or are migrating from perpetual licenses to service softwares or service but now we could do unit pricing or SLA-based pricing, in which case you as a vendor have to start getting very smart about, you owe your customers the risk in meeting an SLA so it's almost more like insurance, actuarial modeling. >> Correct so the way we want think about is, how can we make our customers more, what do you call, monetizable. Their products to be monetizable with their customers and then in that case, when we enter into a service level agreement with our customers, there's always that risk of what we deliver to make their products and services more successful? There's always a risk component which we will have to work with the customers to make sure that combined model of what our customers are going to deliver is going to be more beneficial, more contributing to both bottom line and top line. >> That implies that your modeling, someone's modeling and risk from you the supplier to your customer as vendor to their customer. >> Right. >> That sounds tricky. >> I'm pretty sure we have a lot of financial risk modeling entered into our SLAs when we actually go to our customers. >> So that's a new business model for IBM, for IBM's sort of supply chain master type customers if that's the right word. As this capability, this technology pervades more industries, customers become software vendors or if not software vendors, services vendors for software enhanced products or service enhanced products. >> Exactly, exactly. >> Another thing, I'd listened to a briefing by IBM Global Services where they thought, ultimately, this might end up where there's far more industries are engineered to order instead of make to stock. How would this enable that? >> I think the way we want think about it is that most of the IoT based services will actually start by co-designing and co-developing with your customers. And that's where you're going to start. That's how you're going to start. You're not going to say, here's my 100 data centers and you bring your billion devices and connect and it's going to happen. We are going to start that way and then our customers are going to say, hey by the way, I have these used cases that we want to start doing, so that's why platform becomes so imortant. Once you have the platform, now you can scale, into a scale, individual silos as a vertical use case for them. We provide the platform and the use cases start driving on top of the platform. So the scale becomes much easier for the customers. >> So this sounds like the traditional application. The traditional way an application vendor might turn into a platform vendor which is a difficult transition in itself but you take a few use cases and then generalize into a platform. >> We call that a zone application services. The zone application service is basically, is drawing on perfectly cold platform service which actually provides you the abilities. So for instance like an asset management. An asset management can be done in an oil and gas rig, you can look at asset management in power tub vine, you can can look at asset management in a jet engine. You can do asset management across any different vertical but that is a common horizontal application so most of the time you get 80% of your asset management API's if you will. Then you can be able to scale across multiple different vertical applications and solutions. >> Hold that thought 'cause we're going to come back to joint development and leveraging expertise from vendor and customer and sharing that. Let's talk just at a high level one of the things that I keep hearing is that in Europe industry 4.0 is sort of the hot topic and in the states, it's more digital twins. Help parse that out for us. >> So the way we believe how digital twin should be viewed is a component view. What we mean the component view is that we have your knowledge graph representation of the real assets in the digital world and then you bring in your IoT sensors and connections to the models then you have your functional, logical, physical models that you want to bring into your knowledge graph and then you also want to be able to give the ability of search visualize allies. Kind of an intelligent experience for the end consumer and then you want to bring your similation models when you do the actual similation models in digital to bring it in there and then your enterprise asset management, your ERP systems, all of that and then when you connect, when you're able to build a knowledge graph, that's when the digital twin really connects with your enterprise systems. Sort of bring the OT and the IT together. >> So this is sort of to try and summarize 'cause there are a lot of moving parts in there. You've got you've got the product hierarchy which, in product Kaiser call it building materials, sort of the explosion of parts in an assembly, sub-assembly and then that provides like a structure, a data model then the machine learning models in the different types of models that they could be represent behavior and then when you put a knowledge graph across that structure and behavior, is that what makes it simulation ready? >> Yes, so you're talking about entities and connecting these entities with the actual relationship between these entities. That's the graph that holds the relation between nodes and your links. >> And then integrating the enterprise systems that maybe the lower level operation systems. That's how you effect business processes. >> Correct. >> For efficiency or optimization, automation. >> Yes, take a look at what you can do with like a shop floor optimization. You have all the building materials, you need to know from your existing ERP systems and then you will actually have the actual real parts that's coming to your shop floors to manage them and now base supposing, depending on whether you want to repair, you want to replace, you want an overall, you want to modify whatever that is, you want to look at your existing building materials and see, okay do I first have it do we need more? Do we need to order more? So your auditing system naturally gets integrated into that and then you have to integrate the data that's coming from these models and the availability of the existing assets with you. You can integrate it and say how fast can you actually start moving these out of your shop, into the. >> Okay that's where you translate essentially what's more like intelligent about an object or a rich object into sort of operational implications. >> Veeru: Yes. >> Okay operational process. Let's talk about customer engagement so far. There's intense interest in this. I remember in the Munich event, they were like they had to shut off attendance because they couldn't find a big enough venue. >> Veeru: That's true. >> So what are the characteristics of some of the most successful engagements or the ones that are promising. Maybe it's a little early to say successful. >> So, I think the way you can definitely see success from customer engagement are two fold. One is show what's possible. Show what's possible with after all desire to connect, collection of data, all of that so that one part of it. The second part is understand the customer. The customer has certain requirements in their existing processes and operations. Understand that and then deliver based on what solutions they are expecting, what applications they want to build. How you bring them together is what is, so we're thinking about. That Munich center you talked about. We are actually bringing in chip manufacturers, sensor manufacturers, device manufacturers. We are binging in network providers. We are bringing in SIs, system integrators all of them into the fold and show what is possible and then your partners enable you to get to market faster. That's how we see the engagement with customer should happen in a much more foster manner and show them what's possible. >> It sounds like in the chip industry Moore's law for many years it wasn't deterministic that you we would do double things every 18 months or two years, it was actually an incredibly complex ecosystem web where everyone's sort of product release cycles were synchronized so as to enable that. And it sounds like you're synchronizing the ecosystem to keep up. >> Exactly The saxel of a particular organization IoT efforts is going to depend on how do you build this ecosystem and how do you establish that ecosystem to get to market faster. That's going to be extremely key for all your integration efforts with your customer. >> Let's start narrowly with you. IBM what are the key skills that you feel you need to own starting from sort of the base rocket scientists you know who not only work on machine learning models but they come up with new algorithms on top of say tons of flow work or something like that. And all the way up to the guys who are going to work in conjunction with the customer to apply that science to a particular industry. How does that hold together? >> So it all starts on the platform. On the platform side we have all the developers, the engineers who build these platform all the video connection and all of that to make the connections. So you need the highest software development engineers to build these on the platform and then you also need the solution builders so who is in front of the customer understanding what kind of solutions you want to build. Solutions could be anything. It could be predictive maintenance, it could be as simple as management, it could be remote monitoring and diagnostics. It could be any of these solutions that you want to build and then the solution builders and the platform builders work together to make sure that it's the holistic approach for the customer at the final deployment. >> And how much is the solution builder typically in the early stages IBM or is there some expertise that the customer has to contribute almost like agile development, but not two programmers but like 500 and 500 from different companies. >> 500 is a bit too much. (laughs) I would say this is the concept of co-designing and co-development. We definitely want the ultimate, the developer, the engineers form, the subject exports from our customers and we also need our analytics experts and software developers to come and sit together and understand what's the use case. How do we actually bring in those optimized solution for the customer. >> What level of expertise or what type of expertise are the developers who are contributing to this effort in terms of do they have to, if you're working with manufacturing let's say auto manufacturing. Do they have to have automotive software development expertise or are they more generically analytics and the automotive customer brings in the specific industry expertise. >> It depends. In some cases we have RGB for instance. We have dedicated servers, that particular vertical service provider. We understand some of this industry knowledge. In some cases we don't, in some cases it actually comes from the customer. But it has to be an aggregation of the subject matter experts with our platform developers and solution developers sitting together, finding what's the solution. Literally going through, think about how we actually bring in the UX. What does a typical day of a persona look like? We always by the way believe it's an augmented allegiance which means the human and the machine work together rather than a complete. It gives you the answer for everything you ask for. >> It's a debate that keeps coming up Doug Anglebad sort of had his own answer like 50 years ago which was he sort of set the path for modern computing by saying we're not going to replace people, we're going to augment them and this is just a continuation of that. >> It's a continuation of that. >> Like UX design sounds like someone on the IBM side might be talking to the domain expert and the customer to say how does this workflow work. >> Exactly. So have this design thinking, design sessions with our customers and then based on that we take that knowledge, take it back, we build our mark ups, we build our wire frames, visual designs and the analytics and software that goes behind it and then we provide on top of platform. So most of the platform work, the standard what do you call table state connections, collection of data. All of that as they are already existing then it's one level above as to what the particular solution a customer wants. That's when we actually. >> In terms of getting the customer organization aligned to make this project successful, what are some of the different configurations? Who needs to be a sponsor? Where does budget typically come from? How long are the pilots? That sort of stuff so to set expectations. >> We believe in all the agile thinking, agile development and we believe in all of that. It's almost given now. So depending on where the customer comes from so the customer could actually directly come and sign up to our platform on the existing cloud infrastructure and then they will say, okay we want to build applications then there are some customers really big customers, large enterprises who want to say, give me the platform, we have our solution folks. We will want to work on board with you but we also want somebody who understands building solutions. We integrate with our solution developers and then we build on top of that. They build on top of that actually. So you have that model as well and then you have a GBS which actually does this, has been doing this for years, decades. >> George: Almost like from the silicon. >> All the way up to the application level. >> When the customer is not outsourcing completely, The custom app that they need to build in other words when when they need to go to GBS Global Business Services, whereas if they want a semi-packaged app, can they go to the industry solutions group? >> Yes. >> I assume it's the IoT, Industry Solutions Group. >> Solutions group, yes. >> They then take a it's almost maybe a framework or an existing application that needs customization. >> Exactly so we have IoT-4. IoT for manufacturing, IoT for retail, IoT for insurance IoT for you name it. We have all these industry solutions so there would be some amount of template which is already existing in some fashion so when GBS gets a request to say here is customer X coming and asking for a particular solution. They would come back to IoT solutions group to say, they already have some template solutions from where we can start from rather than building it from scratch. You speed to market again is much faster and then based on that, if it's something that is to be customizable, both of them work together with the customer and then make that happen, and they leverage our platform underneath to do all the connection collection data analytics and so on and so forth that goes along with that. >> Tell me this from everything we hear. There's a huge talent shortage. Tell me in which roles is there the greatest shortage and then how do different members of the ecosystem platform vendors, solution vendors sort of a supply-chain master customers and their customers. How do they attract and retain and train? >> It's a fantastic question. One of the difficulties both in the valley and everywhere across is that three is a skill gap. You want advanced data scientists you want advances machinery experts, you want advanced AI specialists to actually come in. Luckily for us, we have about 1000 data scientists and AI specialists distributed across the globe. >> When you say 1000 data scientists and AI specialists, help us understand which layer are they-- >> It could be all the way from like a BI person all the way to people who can build advanced AI models. >> On top of an engine or a framework. >> We have our Watson APIs from which we build then we have our data signs experience which actually has some of the models then built on top of what's in the data platform so we take that as well. There are many different ways by which we can actually bring the AM model missionary models to build. >> Where do you find those people? Not just the sort of band strengths that's been with IBM for years but to grow that skill space and then where are they also attracted to? >> It's a great question. The valley definitely has a lot of talent, then we also go outside. We have multiple centers of excellence in Israel, in India, in China. So we have multiple centers of excellence we gather from them. It's difficult to get all the talent just from US or just from one country so it's naturally that talent has to be much more improvement and enhanced all the wat fom fresh graduates from colleges to more experienced folks in the in the actual profession. >> What about when you say enhancing the pool talent you have. Could it also include productivity improvements, qualitative productivity improvements in the tools that makes machine learning more accessible at any level? The old story of rising obstruction layers where deep learning might help design statistical models by doing future engineering and optimizing the search for the best model, that sort of stuff. >> Tools are very, very hopeful. There are so many. We have from our tools to python tools to psychic and all of that which can help the data scientist. The key part is the knowledge of the data scientist so data science, you need the algorithm, the statistical background, then you need your applications software development background and then you also need the domestics for engineering background. You have to bring all of them together. >> We don't have too many Michaelangelos who are these all around geniuses. There's the issue of, how do you to get them to work more effectively together and then assuming even each of those are in short supply, how do you make them more productive? >> So making them more productive is by giving them the right tools and resources to work with. I think that's the best way to do it, and in some cases in my organization, we just say, okay we know that a particular person is skilled is up skilled in certain technologies and certain skill sets and then give them all the tools and resources for them to go on build. There's a constant education training process that goes through that we in fact, we have our entire Watson ED platform that can be learned on Kosera today. >> George: Interesting. >> So people can go and learn how to build a platform from a Kosera. >> When we start talking with clients and with vendors, things we hear is that and we were kind of I think early that calling foul but in the open source infrastructure big data infrastructure this notion of mix-and-match and roll your own pipeline sounded so alluring, but in the end it was only the big Internet companies and maybe some big banks and telcos that had the people to operate that stuff and probably even fewer who could build stuff on it. Do we do we need to up level or simplify some of those roles because mainstream companies can't have enough or won't will have enough data scientists or other roles needed to make that whole team work >> I think it will be a combination of both one is we need to up school our existing students with the stem background, that's one thing and the other aspect is, how do you up scale your existing folks in your companies with the latest tools and how can you automate more things so that people who may not be schooled will still be able to use the tool to deliver other things but they don't have to go to a rigorous curriculum to actually be able to deal with it. >> So what does that look like? Give us an example. >> Think of tools like today. There are a lot of BI folks who can actually build. BI is usually your trends and graphs and charts that comes out of the data which are simple things. So they understand the distribution and so on and so forth but they may not know what is the random model. If you look at tools today, that actually gives you to build them, once you give the data to that model, it actually gives you the outputs so they don't really have to go dig deep I have to understand the decision tree model and so on and so forth. They have the data, they can give the data, tools like that. There are so many different tools which would actually give you the outputs and then they can actually start building app, the analytics application on top of that rather than being worried about how do I write 1000 line code or 2000 line code to actually build that model itself. >> The inbuilt machine learning models in and intend, integrated to like pentaho or what's another example. I'm trying to think, I lost my, I having a senior moment. These happen too often now. >> We do have it in our own data science tools. We already have those models supported. You can actually go and call those in your web portal and be able to call the data and then call the model and then you'll get all that. >> George: Splank has something like that. >> Splank does, yes. >> I don't know how functional it is but it seems to be oriented towards like someone who built a dashboard can sort of wire up a model, it gives you an example of what type of predictions or what type of data you need. >> True, in the Splank case, I think it is more of BI tool actually supporting a level of data science moral support on the back. I do not know, maybe I have to look at this but in our case we have a complete data science experience where you actually start from the minute the data gets ingested, you can actually start the storage, the transformation, the analytics and all of that can be done in less than 10 lines of coding. You can just actually do the whole thing. You just call those functions then it will the right there in front of you. So in twin you can do that. That I think is much more powerful and there are tools, there are many many tools today. >> So you're saying that data science experience is an enter in pipeline and therefore can integrate what were boundaries between separate products. >> The boundary is becoming narrower and narrower in some sense. You can go all the way from data ingestion to the analytics in just few clicks or few lines of course. That's what's happening today. Integrated experience if you will. >> That's different from the specialized skills where you might have a tri-factor, prexada or something similar as for the wrangling and then something else for sort of the the visualizations like Altracks or Tavlo and then into modeling. >> A year or so ago, most of data scientists try to spend a lot of time doing data wrangling because some of the models, they can actually call very directly but the wrangling is actually where they spend their time. How do you get the data crawl the data, cleanse the data, etc. That is all now part of our data platform. It is already integrated into the platform so you don't have to go through some of these things. >> Where are you finding the first success for that tool suite? >> Today it is almost integrated with, for instance, I had a case where we exchange the data we integrate that into what's in the Watson data platform and the Watson APIs is a layer above us in the platform where we actually use the analytics tools, more advanced AI tools but the simple machinery models and so on and so forth is already integrated into as part of the Watson data platform. It is going to become an integrated experience through and through. >> To connect data science experience into eWatson IoT platform and maybe a little higher at this quasi-solution layer. >> Correct, exactly. >> Okay, interesting. >> We are doing that today and given the fact that we have so much happening on the edge side of things which means mission critical systems today are expecting stream analysts to get to get insights right there and then be able to provide the outcomes at the edge rather than pushing all the data up to your cloud and then bringing it back down. >> Let's talk about edge versus cloud. Obviously, we can't for latency and band width reasons we can't forward all the data to the cloud, but there's different use cases. We were talking to Matasa Harry at Sparks Summit and one of the use cases he talked about was video. You can't send obviously all the video back and you typically on an edge device wouldn't have heavy-duty machine learning, but for video camera, you might want to learn what is anomalous or behavior call out for that camera. Help us understand some of the different use cases and how much data do you bring back and how frequently do retrain the models? >> In the case of video, it's so true that you want to do a lot of any object ignition and so on and so forth in the video itself. We have tools today, we have cameras outside where if a van goes it detect the particular object in the video live. Realtime streaming analytics so we can do that today. What I'm seeing today in the market is, in the transaction between the edge and the cloud. We believe edge is an extension of the cloud, closer to the asset or device and we believe that models are going to get pushed from the cloud, closer to the edge because the compute capacity and storage and the networking capacity are all improving. We are pushing more and more computing to their devices. >> When you talk about pushing more of the processing. you're talking more about predicts and inferencing then the training. >> Correct. >> Okay. >> I don't think I see so much of the training needs to be done at the edge. >> George: You don't see it. >> No, not yet at least. We see the training happening in the cloud and then once a train, the model has been trained, then you come to a steady, steady model and then that is the model you want to push. When you say model, it could be a bunch of coefficients. That could be pushed onto the edge and then when a new data comes in, you evaluate, make decisions on that, create insights and push it back as actions to the asset and then that data can be pushed back into the cloud once a day or once in a week, whatever that is. Whatever the capacity of the device you have and we believe that edge can go across multiple scales. We believe it could be as small with 128 MB it could be one or two which I see sitting in your local data center on the premise. >> I've had to hear examples of 32 megs in elevators. >> Exactly. >> There might be more like a sort of bandwidth and latency oriented platform at the edge and then throughput and an volume in the cloud for training. And then there's the issue of do you have a model at the edge that corresponds to that instance of a physical asset and then do you have an ensemble meaning, the model that maps to that instance, plus a master canonical model. Does that work for? >> In some cases, I think it'll be I think they have master canonical model and other subsidiary models based on what the asset, it could be a fleet so you in the fleet of assets which you have, you can have, does one asset in the fleet behave similar to another asset in the fleet then you could build similarity models in that. But then there will also be a model to look at now that I have to manage this fleet of assets which will be a different model compared to action similarity model, in terms of operations, in terms of optimization if I want to make certain operations of that asset work more efficiently, that model could be completely different with when compared to when you look at similarity of one model or one asset with another. >> That's interesting and then that model might fit into the information technology systems, the enterprise systems. Let's talk, I want to go get a little lower level now about the issue of intellectual property, joint development and sharing and ownership. IBM it's a nuanced subject. So we get different sort of answers, definitive answers from different execs, but at this high level, IBM says unlike Google and Facebook we will not take your customer data and make use of it but there's more to it than that. It's not as black-and-white. Help explain that for so us. >> The way you want to think is I would definitely paired back what our chairman always says customers' data is customers' data, customer insights is customer insights so they way we look at it is if you look at a black box engine, that could be your analytics engine, whatever it is. The data is your inputs and the insights are our outputs so the insights and outputs belong to them. we don't take their data and marry it with somebody else's data and so forth but we use the data to train the models and the model which is an abstract version of what that engine should be and then more we train the more better the model becomes. And then we can then use across many different customers and as we improve the models, we might go back to the same customers and hey we have an improved model you want to deploy this version rather than the previous version of the model we have. We can go to customer Y and say, here is a model which we believe it can take more of your data and fine tune that model again and then give it back to them. It is true that we don't actually take their data and share the data or the insights from one customer X to another customer Y but the models that make it better. How do you make that model more intelligent is what out job is and that's what we do. >> If we go with precise terminology, it sounds like when we talk about the black box having learned from the customer data and the insights also belonging to the customer. Let's say one of the examples we've heard was architecture engineering consulting for large capital projects has a model that's coming obviously across that vertical but also large capital projects like oil and gas exploration, something like that. There, the model sounds like it's going to get richer with each engagement. And let's pin down so what in the model is sort of not exposed to the next customer and what part of the model that has gotten richer does the next customer get the balance of? >> When we actually build a model, when we pass the data, in some cases, customer X data, the model is built out of customer X data may not sometimes work with the customer Y's data so in which case you actually build it from scratch again. Sometimes it doesn't. In some case it does help because of the similarity of the data in some instance because if the data from company X in oil gas is similar to company Y in oil gas, sometimes the data could be similar so in which case when you train that model, it becomes more efficient and the efficiency goes back to both customers. we will do that but there are places where it would really not work. What we are trying to do is. We are in fact trying to build some kind of knowledge bundles where we can actually what used to be a long process to train the model can ow shortened using that knowledge bundle of what we have actually gained. >> George: Tell me more about how it works. >> In retail for instance, when we actually provide analytics, from any kind of IoT sense, whatever sense of data this comes in we train the model, we get analytics used for ads, pushing coupons, whatever it is. That knowledge, what you have gained off that retail, it could be models of models, it could be metamodels, whatever you built. That can actually serve many different customers but the first customer who is trying to engage with us, you don't have any data to the model. It's almost starting from ground zero and so that would actually take a longer time when you are starting with a new industry and you don't have the data, it'll take you a longer time to understand what is that saturation point or optimization point where you think the model cannot go any further. In some cases, once you do that, you can take that saturated model or near saturated model and improve it based on more data that actually comes from different other segments. >> When you have a model that has gotten better with engagements and we've talked about the black box which produces the insights after taking in the customer data. Inside that black box there's like at the highest level we might call it the digital twin with the broad definition that we started with, then there's a data model which a data model which I guess could also be incorporated into the knowledge graft for the structure and then would it be fair to call the operational model the behavior? >> Yes, how does the system perform or behave with respect the data and the asset itself. >> And then underpinning that, the different models that correspond to the behaviors of different parts of this overall asset. So if we were to be really precise about this black box, what can move from one customer to the next and what what won't? >> The overall model, supposing I'm using a random data retrieval model, that remains but actual the coefficients are the feature rector, or whatever I use, that could be totally different for customers, depending on what kind of data they actually provide us. In data science or in analytics you have a whole platora of all the way from simple classification algorithms to very advanced predictive modeling algorithms. If you take the whole class when you start with a customer, you don't know which model is really going to work for a specific user case because the customer might come and can say, you might get some idea but you will not know exactly this is the model that will work. How you test it with one customer, that model could remain the same kind of use case for some of other customer, but that actual the coefficients the degree of the digital in some cases it might be two level decision trees, in others case it might be a six level decision tree. >> It is not like you take the model and the features and then just let different customers tweak the coefficients for the features. >> If you can do that, that will be great but I don't know whether you can really do it the data is going to change. The data is definitely going to change at some point of time but in certain cases it might be directly correlated where it can help, in certain cases it might not help. >> What I'm taking away is this is fundamentally different from traditional enterprise applications where you could standardize business processes and the transactional data that they were producing. Here it's going to be much more bespoke because I guess the processes, the analytic processes are not standardized. >> Correct, every business processes is unique for a business. >> The accentures of the world we're trying to tell people that when SAP shipped packaged processes, which were pretty much good enough, but that convince them to spend 10 times as much as the license fee on customization. But is there a qualitative difference between the processes here and the processes in the old ERP era? I think it's kind of different in the ERP era and the processes, we are more talking about just data management. Here we're talking about data science which means in the data management world, you're just moving data or transforming data and things like that, that's what you're doing. You're taking the data. transforming to some other form and then you're doing basic SQL queries to get some response, blah blah blah. That is a standard process that is not much of intelligence attached to it but now you are trying to see from the data what kind of intelligence can you derive by modeling the characteristics of the data. That becomes a much tougher problem so it now becomes one level higher of intelligence that you need to capture from the data itself that you want to serve a particular outcome from the insights you get from is model. >> This sounds like the differences are based on one different business objectives and perhaps data that's not as uniform that you would in enterprise applications, you would standardize the data here, if it's not standardized. >> I think because of the varied the disparity of the businesses and the kinds of verticals and things like that you're looking at, to get complete unified business model, is going to be extremely difficult. >> Last question, back-office systems the highest level they got to were maybe the CFO 'cause you had a sign off on a lot of the budget for the license and a much much bigger budget for the SI but he was getting something that was like close you quarter in three days or something instead of two weeks. It was a control function. Who do you sell to now for these different systems and what's the message, how much more strategic how do you sell the business impact differently? >> The platforms we directly interact with the CIO and CTOs or the head of engineering. And the actual solutions or the insights, we usually sell it to the COOs or the operational folks. So because the COO is responsible for showing you productivity, efficiency, how much of savings can you do on the bottom line top line. So the insights would actually go through the COOs or in some sense go through their CTOs to COOs but the actual platform itself will go to the enterprise IT folks in that order. >> This sounds like it's a platform and a solution sell which requires, is that different from the sales motions of other IBM technologies or is this a new approach? >> IBM is transforming on its way. The days where we believe that all the strategies and predictives that we are aligned towards, that actually needs to be the key goal because that's where the world is going. There are folks who, like Jeff Boaz talks about in the olden days you need 70 people to sell or 70% of the people to sell a 30% product. Today it's a 70% product and you need 30% to actually sell the product. The model is completely changing the way we interact with customers. So I think that's what's going to drive. We are transforming that in that area. We are becoming more conscious about all the strategy operations that we want to deliver to the market we want to be able to enable our customers with a much broader value proposition. >> With the industry solutions group and the Global Business Services teams work on these solutions. They've already been selling, line of business CXO type solutions. So is this more of the same, it's just better or is this really higher level than IBM's ever gotten in terms of strategic value? >> This is possibly in decades I would say a high level of value which come from a strategic perspective. >> Okay, on that note Veeru, we'll call it a day. This is great discussion and we look forward to writing it up and clipping all the videos and showering the internet with highlights. >> Thank you George. Appreciate it. >> Hopefully I will get you back soon. >> I was a pleasure, absolutely. >> With that, this George Gilbert. We're in our Palo Alto studio for wiki bond and theCUBE and we've been talking to Veeru Ramaswamy who's VP of Watson IoT platform and we look forward to coming back with Veeru sometime soon. (upbeat music)

San Francisco extracting the signal from the noise it's the cube covering vmworld 2015 brought to you by VM world and its ecosystem sponsors now your host Stu miniman and Brian Grace Lee welcome back this is the cube SiliconANGLE TVs live production of vmworld 2015 here in moscone north san francisco happy to have back on this segment we're actually gonna dig into some of the networking pieces Brian Grace Lee and myself here hosting it Sean Walsh repeat cube guest you know in a new role though so Sean welcome back here now the general manager of the ethernet business at qlogic thanks for joining us thank you thanks for having me alright so I mean Sean you know we're joking before we start here I mean you and I go back about 15 years I do you know those that know the adapter business I mean you know Jay and I've LJ core business on you've worked for qlogic before you did a stint in ml accent and you're now back to qlogic so why don't we start off with that you know what brought you back to qlogic what do you see is the opportunity there sure um I'll tell you more than anything else what brought me back was this 25 gig transition it's very rare and I call it the Holy trifecta of opportunity so you've got a market transition you actually have a chip ready for the market at the right time and the number one incumbent which is Intel doesn't have a product I mean not that they're late they just don't have a product and that's the type of stuff that great companies are built out of are those unique opportunities in the market and you know more than anything else that's when brought me back to qlogic alright so before we dig into some of the ethernet and hyperscale piece you know what what's the state of fibre channel Sean you know what we said is in those fiber channel the walking dead is it a cash cow that you know qlogic be a bit of milk and brocade and the others in the fibre channel business for a number years you know what's your real impression of fibre channel did that yeah so you know look fibre channel is mature there's no question about it is that the walking dead no not by any stretch and if it is the walking dead man it produces a lot of cash so I'll take that any day of the year right The Walking Dead's a real popular show so fibre channel you know it's still it's still gonna be used in a lot of environments but you know jokingly the way that I describe it to people is I look at fibre channel now is the Swiss bank of networks so a lot of web giant's by our fiber channel cards and people will look at me and go why do they do that because for all the hype of open compute and all the hype of the front end processors and all the things that are happening when you click on something where there's money involved that's on back end Oracle stuff and it's recorded on fibre channel and if there's money involved it's on fibre and as long as there's money in the enterprise or in the cloud I'm reasonably certain fibre channel will be around yeah it's a funny story I remember two years ago I think we were at Amazon's reinvent show and Andy Jesse's on stage and somebody asked you know well how much of Amazon is running amazoncom is running on AWS and its most of it and we all joke that somewhere in the back corner running the financials is you know a storage area network with the traditional array you know probably atandt touched by fibre channel absolutely i mean we just did a roll out with one of the web giants and there were six different locations each of the each of the pods for the service for about 5,000 servers and you know as you would expect about 3,000 on the front access servers there's about 500 for pop cash that was about 15 maybe twelve thirteen hundred for the for the big data and content distribution and all those other things the last 500 servers look just like the enterprise dual 10 gigs dual fibre channel cards and you know I don't see that changing anytime soon all right so let's talk a bit a little bit 25 gig Ethernet had an interview yesterday with mellanox actually who you know have some strong claims about their market leadership in the you know greater than 10 gig space so where are we with kind of the standards the adoption in queue logical position and 25 gig Ethernet sure so you know obviously like everyone in this business we all know each other yeah and when you look at the post 10 gig market okay 40 gigs been the dominant technology and I will tip my hat to mellanox they've done well in that space now we're both at the same spot so we have exactly the same opportunity in front of us we're early to market on the 25 we have race to get there and what we're seeing is the 10 gig market is going to 25 pretty straightforward because I like the single cable plant versus the quad cable plant the people that are at 40 aren't going to 50 they're going to transition straight to 100 we're seeing 50 more as a blade architecture midplane sort of solution and that's where at right now and I can tell you that we have multiple design win opportunities that we're in the midst of and we are slugging it out with these guys everything and it will be an absolute knife fight between us and mellanox to see who comes out number one in this market obviously we both think we're going to win but at the end of the day I've placed my bet and I expect to win all right so Sean can you lay out for us you know where are those battles so traditionally the network adapter it was an OEM type solution right I got it into the traditional server guys yeah and then it was getting the brand recognition for the enterprise customers and pushing that through how much is that traditional kind of OEM is it changing what's having service providers and those hyperscale web giants yes so there's there's three fundamental things when you look at 25 gig you gotta deal with so first off the enterprise is going to be much later because they need the I Triple E version that has backwards auto-negotiation so you know that's definitely a 17 18 pearly transition type thing the play right now is in the cloud and the service provider market where they're rolling out specific services and they're not as concerned about the backwards compatibility so that's where we're seeing the strength of this so they're all the names that you would expect and I have to say one of the interesting things about working with these guys is there n das or even nastier than our Liam India is they do not want you talking about them but it is very much that market where it's a non traditional enterprise type of solution for the next 12-18 months and then as we roll into that next gen around the pearly architecture where we all have full auto-negotiation that's where you're going to see the enterprise start to kick in yeah what what what are the types of applications that are driving this this next bump in speed what is it is it video is it sort of east and west types of application traffic is a big data what's what's driving this next bump so a couple of things you would expect which would be the you know certainly hadoop mapreduce you know those sorts of things are going there the beginning of migration to spark where they're doing real-time analytics versus post or processing batch type stuff so there they really care about it and this is where our DMA is also becoming very very popular in it the next area that most people probably don't think of is the telco in a vspace is the volume as these guys are doing their double move and there going from a TCA type platforms running mostly one in ten they're going to leave right to 25 and for them the big thing is the ability to partition the network and do that virtualization and be able to run deep edk in one set of partitions standard storage another set of partitions in classic IP on the third among the among the few folks that you know you would expect in that are the big content distribution guys so one of the companies that I can mention is Netflix so they've already been out at their at 40 right now and you know they're not waiting for 50 they're going to make another leap that goes forward and they've been pretty public about those types of statements if you look at some of the things that they talked about at NDF or IDF and they're wanting to have nvme and direct gas connection over i serve that's driving 100 gig stuff we did a demo at a flash memory summit with Samsung where we had a little over 3 million I ops coming off of it and again it's not the wrong number that matters but it's that ability to scale and deal with that many concurrent sessions that are driving it so those are the early applications and I don't think the applications will be a surprise because they're all the ones that have moved to 40 you know the 10 wasn't enough 40 might be too much they're going to 25 and for a lot of the others and its really the pop cash side that's driving the hunter gig stuff because you know when that Super Bowl ad goes you got to be able to take all that bandwidth it once yeah so Sean you brought up nvme maybe can you discuss a little bit you know what are the you know nvm me and some of these next-generation architectures and what's the importance to the user sure so nvme is basically a connection capability that used to run for hard drives then as intel moved into SSDs they added this so you had very very high performance low latency pci express like performance what a number of us in this business are starting to do is then say hey look instead of using SAS which is kind of running out of gas at 12 gig let's move to nvme and make it a fabric and encapsulate it so there's three dynamics that help that one is the advent of 25 50 100 the second is the use of RDMA to get the latency that you want and then the third is encapsulation I sir or the ice cozy with RDMA together and it's sort of that trifecta of things that are giving very very high performance scale out on the back end and again this is for the absolute fastest applications where they want the lowest latency there was an interesting survey that was done by a university of arizona on latency and it said that if two people are talking and if you pause for more than a quarter of a second that's when people change their body language they lean forward they tilt their head they do whatever and that's kind of the tolerance factor for latency on these things and again one of the one of the statements that that Facebook made publicly at their recent forum was that they will spend a hundred million dollars to save a millisecond because that's the type of investment that drives their revenue screen the faster they get clicks the faster they generate revenue so when you think of high frequency trading when you think of all those things that are time-sensitive the human factor and that are going to drive this all right so storage the interaction with networking is you know critically important especially to show like this at vmworld I mean John you and I talked for years is it wasn't necessarily you know fibre channel versus the ethernet now it's changing operational models if I go use Salesforce I don't think about my network anymore I felt sort of happen to used Ethernet it's I don't really care um hyper convergence um when somebody buys hyper convergence you know they just kind of the network comes with it when I buy a lot of these solutions my networking decision is made for me and I haven't thought about it so you know what's that trend that you're seeing so the for us the biggest trend is that it's a shifting customer base so people like new tonics and these guys are becoming the drivers of what we do and the OEMs are becoming much more distribution vehicles for these sorts of things than they are the creators of this content so when we look at how we write and how we build these things there's far more multi-threading in terms of them there's far more partitions in terms of the environment because we never know when we get plugged into it what that is going to be so incorporating our l2 and our RDMA into one set of engine so that you always have that hyper for it's on tap on demand and you know without getting down into the minutia of the implementation it is a fundamental shift in how we look at our driver architectures you know looking at arm based solutions and micro servers versus just x86 as you roll the film forward and it also means that as we look at our architectures they have to become much smaller and much lighter so some of the things that we traditionally would have done in an offload environment we may do more in firmware on the side and I think the other big trend that is going to drive that is this move towards FPGAs and some of the other things that are out there essentially acting as coprocessors from you you mentioned earlier Open Compute open compute platform those those foundations and what's going on what is what what's really going on there i think a lot of us see the headlines sometimes you think about it you go okay this is an opportunity for lots of engineering to contribute to things but what's the reality that you're dealing with the web scale folks sure if they seem like the first immediate types of companies that would buy into this or use it what's the reality of what's going on with that space well obviously inside the the i will say the web scale cloud giant space you know i think right now if you look at it you've got sort of the big 10 baidu Tencent obama at amazon web as your microsoft being those guys and then you know they are definitely building and designing their own stuff there's another tier below that where you have the ebays the Twitter's the the other sorts of folks that are in there and you know they're just now starting that migration if you look at the enterprise not a big surprise the financial guys are leading this we've seen public statements from JPM and other folks that have been at these events so you know I view it very much like the blade server migration I think it's going to be twenty twenty-five percent of the overall market whether we whether people like to admit it or not good old rack and stack is going to be around for a very long time and you know they're there are applications where it makes a lot of sense when you're deploying prop private cloud in the managed service provider market we're starting to see a move into that but you know if you say you know what's the ten year life cycle of an architect sure i would say that in the cloud were probably four or five years into it and the enterprise were maybe one or two years into it all right so what about the whole sdn discussion Sean you know how much does qlogic play into that what are you seeing in general and you know we're at vmworld so what about nsx you know is that part of the conversation and what do you hear in the marketplace today yeah it really is part of the conversation and the interesting part is that I think sdn is getting a lot of play because of the capabilities that people want and again you know when you look at the managed service providers wanting to have large scale lower costs that's going to definitely drive it but much like OpenStack and Linux and some of these other things it's not going to be you know the guys going to go download it off the web and put it in production at AT&T you know it's going to be a prepackaged solution it's going to be embedded as part of it if you look at what Red Hat is doing with their OpenStack release we look what mirantis is doing with their OpenStack release again from an enterprise perspective and from a production in the MSP and second tier cloud that's what you're going to see more of so for us Sdn is critical because it allows us to then start to do things that we want to do for high-performance storage it allows us to change the value proposition in terms of if you look at Hadoop one of these we want to be able to do is take the storage engine module and run that on our card with our embedded V switch and our next gen ship so that we can do zero stack copies between nodes to improve latency so it's not just having RDMA is having a smart stack that goes with it and having the SDN capability to go out tell the controller pay no attention this little traffic that's going on over here you know these are not the droids you're looking for and then everything goes along pretty well so it's it's very fundamental and strategic but it's it's a game it's a market in which we're going to participate but it's not one we're going to try and write or do a distribution for okay any other VMware related activities q logics doing announcements this week that you want to share this week I would have to say no you know I think the one other thing that we're strategically working on them on with that you would expect is RDMA capabilities across vMotion visa and those sorts of things we've been one of the leaders in terms of doing genevieve which is the follow-on to VX land for hybrid cloud and that sort of thing and we see that as a key fundamental partnership technology with VMware going forward all right so let's turn back to qlogic for a second so the CEO recently left he DNA that there's a search going on so give us the company update if you will well actually there isn't a search so Jean who is gonna is going to run the ship forward as CEO we've brought in chris king who was on our board as executive chair in person chris has a lot of experience in the chip market and she understands that intimate tie that we have to that intel tick-tock model and really how you run an efficient ship driven organization you know whether we play in the systems in between level you know we're not quite the system but we're not quite the chip and understanding that market is part of what she does and the board has given us the green light to continue to go forward develop what we need to do in terms of the other pieces jean has a strong financial background she was acting CEO for a year between HK and simon aires me after Simon left so she's got the depth she knows the business and for us you know you know it's kind of a non op where everything else is continuing on as you would expect yeah okay last question I have for you Sean I mean the dynamics change for years you know what there was kind of the duopoly Xin the market I mean it was in tellin broadcom oh yeah on the ethernet side it was Emulex and amp qlogic it's a different conversation today I mean you mentioned Intel we talked about mellanox don't you logic you know your old friend I don't lie back on a vago bought broadcom and now they're called broadcom I think so yeah so you know layout for us you know kind of you know where you see that the horses on the track and you know what excites you yeah so again you know if you look at the the 10 gig side of the business clearly intel has the leadership position now we're number two in the market if you look at the shared data that's come out you know the the the Emulex part of a vago has been struggling in losing chair then we have this 25 gig transition that came in the market and that was driven by broadcom and you know for those of us who have followed this business they I think everyone can appreciate the irony of avago of avago buying Emulex and then for all the years we tried to keep him separate bringing them back together was but we-we've chuckled over a few beers on that one but then you've got this 25 gig transition and you know the other thing is that if you look at so let me step back and say the other thing on the 10 gig market is was a very very clear dividing line the enterprise was owned by the broadcom / qlogic emulex side the cloud the channel the the the appliance business was owned by Intel mellanox okay now as we go into this next generation you've got us mellanox and the the original broadcom team coming in with 25 game we've all done something that gets us through this consortium approach we're all going to have a night Ripley approach from there and Intel isn't there you know we haven't seen any announcements or anything specific from Emulex that they've said publicly in that space so right now we kind of view it as a two-horse race we think from a software perspective that our friends at at broadcom com whatever we want to call them or bravado I think is how r CT / first tool that I don't think they have a software depth to run this playbook right now and then we have to do is take our enterprise strength and move those things like load balancing and failover and the SDN tools and end par and all the virtualization capabilities we have we got to move those rapidly into the into the cloud space and go after it for us it means we have to be more open source driven than we have been in the past it means that we have a different street fight for every one of these it represents a change in some of the sales model and how we go to market so you know not to say that we're you know we we've got all of everything wrapped up and perfect in this market but again right time right place and this will be the transition for another you know we think three to five years and there's there's still a lot of interesting things that are happening ironically one of the most interesting things I think it's got to happen in 25 is this use of the of the new little profile connectors I think that will do more to help the adoption of 25 gig in Hunter gig where you can use the RCX or r XC connector there's our cxr see I forgot the acronym but it kind of looks like the firewire HDMI connectors that you have on your laptop's now and now imagine that you can have a car that has that connector in a form factor that's you know maybe a half inch square and now you've got incredible port density and you can dynamically change between 25 50 and 100 on the fly well let Sean Sean you know we've always talked there's a lot of complexity that goes in under the covers and it's the interest who's got a good job of making that simple and consumable right and help tried those new textures go forward all right Sean thank you so much for joining us we'll be right back with lots more coverage including some more networking in-depth conversation thank you for watching thanks for having me