>> Announcer: Live from Las Vegas, it's The Cube, covering HPE Discover, 2017 brought to you by Hewlett Packard Enterprise. >> Okay, welcome back everyone. We're here live in Las Vegas for our exclusive three day coverage from The Cube Silicon Angle media's flagship program. We go out to events, talk to the smartest people we can find CEOs, entrepreneurs, R&D lab managers and of course we're here at HPE Discover 2017 our next two guests, Andrew Wheeler, the Fellow, VP, Deputy Director, Hewlett Packard Labs and Kirk Bresniker, Fellow and VP, Chief Architect of HP Labs, was on yesterday. Welcome back, welcome to The Cube. Hewlett Packard Labs well known you guys doing great research, Meg Whitman really staying with a focused message and one of the comments she mentioned at our press analyst meeting yesterday was focusing on the lab. So I want ask you where is that range in the labs? In terms of what you guys, when does something go outside the lines if you will? >> Andrew: Yeah good question. So, if you think about Hewlett Packard Labs and really our charter role within the company we're really kind of tasked for looking at things that will disrupt our current business or looking for kind of those new opportunities. So for us we have something we call an innovation horizon and you know it's like any other portfolio that you have where you've got maybe things that are more kind of near term, maybe you know one to three years out, things that are easily kind of transferred or the timing is right. And then we have kind of another bucket that says well maybe it's more of a three to five year kind of in that advanced development category where it needs a little more incubation but you know it needs a little more time. And then you know we reserve probably you know a smaller pocket that's for more kind of pure research. Things that are further out, higher risk. It's a bigger bet but you know we do want to have kind of a complete portfolio of those, and you know over time throughout our history you know we've got really success stories in all of those. So it's always finding kind of that right blend. But you know there's clearly a focus around the advanced development piece now that we've had a lot of things come from that research point and really one of the... >> John: You're looking for breakthroughs. I mean that's what you're... Some-- >> Andrew: Clearly. >> Internal improvement, simplify IT all that good stuff, you guys still have your eyes on some breakthroughs. >> That's right. Breakthroughs, how do we differentiate what we're doing so but yeah clearly, clearly looking for those breakthrough opportunities. >> John: And one of the things that's come up really big in this show is the security and chip thing was pretty hot, very hot, and actually wiki bonds public, true public cloud report that they put out sizing up on prem the cloud mark. >> Dave: True private cloud. >> True private cloud I'm sorry. And that's not including hybrids of $265 billion tam but the notable thing that I want to get your thoughts on is the point they pushed was over 10 years $150 billion is going to shift out of IT on premise into other differentiated services. >> Andrew: Out of labor. >> Out of labor. So this, and I asked them what that means, as he said that means it's going to shift to vendor R&D meaning the suppliers have to do more work. So that the customers don't have to do the R&D. Which we see a lot in cloud where there's a lot of R&D going on. That's your job. So you guys are HP Labs, what's happening in that R&D area that's going to off load that labor so they can move to some other high yield tasks. >> Sure. Take first. >> John: Go ahead take a stab at it. >> When we've been looking at some of the concepts we had in the memory driven computing research and advanced development programs the machine program, you know one of the things that was the kick off for me back in 2003 we looked at what we had in the unix market, we had advanced virtualization technologies, we had great management of resources technologies, we had memory fabric technologies. But they're all kind of proprietary. But Silicon is thinking and back then we were saying how does risk unix compete with industry standards service? This new methodology, new wave, exciting changing cost structures. And for us it was that it was a chance to explore those ideas and understand how they would affect our maintaining the kind of rich set of customer experiences, mission criticality, security, all of these elements. And it's kind of funny that we're sort of just coming back to the future again and we're saying okay we have this move we want to see these things happen on the cloud and we're seeing those same technologies, the composable infrastructure we have in synergy and looking forward to see the research we've done on the machine advanced development program and how will that intersect hardware composability, converged infrastructure so that you can actually have that shift, those technologies coming in taking on more of that burden to allow you freedom of choice, so you can make sure that you end up with that right mix. The right part on a full public cloud, the right mix on a full private cloud, the right mixing on that intelligent edge. But still having the ability to have all of those great software development methodologies that agile methodology, the only thing the kids know how to do out of school is open source and agile now. So you want to make sure that you can embrace that and make sure regardless of where the right spot is for a particular application in your entire enterprise portfolio that you have this common set of experiences and tools. And some of the research and development we're doing will enable us to drive that into that existing, conventional, enterprise market as well as this intelligent edge. Making a continuum, a continuum from the core to the intelligent edge. And something that modern computer science graduates will find completely comfortable. >> One attracting them is going to be the key, I think the edge is kind of intoxicating if you think about all the possibilities that are out there in terms of what you know just from a business model disruption and also technology. I mean wearables are edge, brain implants in the future will be edge, you know the singularities here as Ray Kersewile would say... >> Yeah. >> I mean but, this is the truth. This is what's happened. This is real right now. >> Oh absolutely. You know we think of all that data and right now we're just scratching the surface. I remember it was 1994 the first time I fired up a web server inside of my development team. So I could begin thinning out design information on prototype products inside of HP, and it was a novelty. People would say "What is that thing "you just sent me an email, W W whatever?" And suddenly we went from, like almost overnight, from a novelty to a business necessity, to then it transformed the way that we created the applications for the... >> John: A lot of people don't know this but since you brought it up this historical trivia, HP Labs, Hewlett Packard Labs had scientists who actually invented the web with Tim Berners-Lee, I think HTML founder was an HP Labs scientist. Pretty notable trivia. A lot of people don't know that so congratulations. >> And so I look at just what you're saying there and we see this new edge thing is it's going to be similarly transformative. Now today it's a little gimmicky perhaps it's sort of scratching the surface. It's taking security and it can be problematic at times but that will transform, because there is so much possibility for economic transformation. Right now almost all that data on the edge is thrown away. If you, the first person who understands okay I'm going to get 1% more of that data and turn it into real time intelligence, real time action... That will unmake industries and it will remake new industries. >> John: Andrew this the applied research vision, you got to apply R&D to the problem... >> Andrew: Correct. >> That's what he's getting at but you got to also think differently. You got to bring in talent. The young guns. How are you guys bringing in the young guns? What's the, what's the honeypot? >> Well I think you know for us it's, the sell for us, obviously is just the tradition of Hewlett Packard to begin with right? You know we have recognition on that level even it's not just Hewlett Packard Labs as well it's you know just R&D in general right? Kind of it you know the DNA being an engineering company so... But it's you know I think it is creating kind of these opportunities and whether it's internship programs you know just the various things that we're doing whether it's enterprise related, high performance computing... I think this edge opportunity is a really interesting one as a bridge because if you think about all the things that we hear about in enterprise in terms of "Oh you know I need this deep analytics "capability," or you know even a lot of the in memories things that we're talking about, real time response, driving information, right? All of that needs to happen at the edge as well for various opportunities so it's got a lot of the young graduates excited. We host you know hundreds of interns every year and it's real exciting to see kind of the ideas they come in with and you know they're all excited to work in this space. >> Dave: So Kirk you have your machine button, three, of course you got the logo. And then the machine... >> I got the labs logo, I got the machine logo. >> So when I first entered you talked about in the early 1980s. When I first got in the business I remembered Gene Emdall. "The best IO is no IO." (laughter) >> Yeah that's right. >> We're here again with this sort of memory semantics, centric computing. So in terms of the three that Andrew laid out the three types of sort of projects you guys pursue... Where does the machine fit? IS it sort of in all three? Or maybe you could talk about that a little bit. >> Kirk: I think it is, so we see those technologies that over the last three years we have brought so much new and it was, the critical thing about this is I think it's also sort of the prototyping of the overall approach our leaning in approach here... >> Andrew: That's right. >> It wasn't just researchers. Right? Those 500 people who made that 160 terabyte monster machine possible weren't just from labs. It was engineering teams from across Hewlett Packard Enterprise. It was our supply chain team. It was our services team telling us how these things fit together for real. Now we've had incredible technology experiences, incredible technologist experiences, and what we're seeing is that we have intercepts on conventional platforms where there's the photonics, the persistent memories. Those will make our existing DCIG and SDCG products better almost immediately. But then we also have now these whole cloth applications and as we take all of our learnings, drive them into open source software, drive them into the genesys consortium and we'll see you know probably 18, 24 months from now some of those first optimized silicon designs pop out of that ecosystem then we'll be right there to assemble those again, into conventional systems as well as more expansive, exo-scale computing, intelligent edge with large persistent memories and application specific processing as that next generation of gateways, I think we can see these intercept points at every category Andrew talked about. >> Andrew: And another good point there that kind of magnifies the model we were talking about, if we were sitting here five years ago, we would talking about things like photonics and non-volatile memory as being those big R projects. Those higher risk, longer term things, that right? As those mature, we make more progress innovation happens, right? It gets pulled into that shorter time frame that becomes advanced development. >> Dave: And Meg has talked about that... >> Yeah. >> Wanting to get more productivity out of the labs. And she's also pointed out you guys have spent more on R&D in the last several years. But even as we talked about the other day you want to see a little more D and keep the R going. So my question is, when you get to that point, of being able to support DCIG... Where do you, is it a hand off? Are you guys intimately involved? When you're making decisions about okay so member stir for example, okay this is great, that's still in the R phase then you bring it in. But now you got to commercialize this and you got 3D nan coming out and okay let's use that, that fits into our framework. So how much do you guys get involved in that handoff? You know the commercialization of this stuff? >> We get very involved. So it's at the point where when we think have something that hey we think you know maybe this could get into a product or let's see if there's good intercept here. We work jointly at that point. It's lab engineers, it's the product managers out of the group, engineers out of the business group, they essentially work collectively then on getting it to that next step. So it's kind of just one big R&D effort at that point. >> Dave: And so specifically as it relates to the machine, where do you see in the next in the near term, let's call near term next three years, or five years even, what do you see that looking like? Is it this combination of memory width capacitors or flash extensions? What does that look like in terms of commercial terms that we can expect? >> Kirk: So I really think the palette is pretty broad here. That I can see these going into existing rack and tower products to allow them to have memory that's composable down to the individual module level. To be able to take that facility to have just the right resources applied at just the right time with that API that we have in one view. Extend down to composing the hardware itself. I think we look at those edge line systems and want to have just the right kind of analytic capability, large persistent memories at that edge so we can handle those zeta bytes and zeta bytes of data in full fidelity analyzed at the edge sending back that intelligence to the core but also taking action at the edge in a timeframe that matters. I also see it coming out and being the basis of our exoscale high performance computing. You know when you want to have a exoscale system that has all of the combined capacity of the top 500 systems today but 1/20th of their power that is going to take rather novel technologies and everything we've been working on is exactly what's feeding that research and soon to be advanced development and then soon to be production in supply chain. >> Dave: Great. >> John: So the question I have is obviously we saw some really awesome Gen 10 stuff here at this show you guys are seeing that obviously you're on stage talking about a lot of the cool R&D, but really the reality is that's multiple years in the works some of this root of trust silicon technology that's pretty, getting the show buzzed up everyone's psyched about it. Dreamworks Animation's talking about how inorganic opportunities is helping their business and they got the security with the root of trust NIST certified and compliant. Pretty impressive. What's next? What else are you working on because this is where the R&D is on your shoulders for that next level of innovation. Where, what do you guys see that? Because security is a huge deal. That's that great example of how you guys innovated. Cause that'll stop the vector of a tax in the service area of IOT if you can get the servers to lock down and you have firmware that's secure, makes a lot of sense. That's probably the tip of the iceberg. What else is happening with security? >> Kirk: So when we think about security and our efforts on advanced development research around the machine what you're seeing here with the proliance is making the machines more secure. The inherent platform more secure. But the other thing I would point to you is the application we're running on the prototype. Large scale graph inference. And this is security because you have a platform like the machine. Able to digest hundreds and hundreds of tera bytes worth of log data to look for that fingerprint, that subtle clue that you have a system that has been compromised. And these are not blatant let's just blast everything out to some dot dot x x x sub domain, this is an advanced persistent thread by a very capable adversary who is very subtle in their reach out from a system that has been compromised to that command and control server. The signs are there if you can look at the data holistically. If you can look at that DNS log, graph of billions of entries everyday, constantly changing, if you can look at that as a graph in totality in a timeframe that matters then that's an empowering thing for a cyber defense team and I think that's one of the interesting things that we're adding to this discussion. Not only protect, detect and recover, but giving offensive weapons to our cyber defense team so they can hunt, they can hunt for those events for system threats. >> John: One of the things, Andrew I'll get your thoughts and reaction to this because Ill make an observation and you guys can comment and tell me I'm all wet, fell off the deep end or what not. Last year HP had great marketing around the machine. I love that Star Trek ad. It was beautiful and it was just... A machine is very, a great marketing technique. I mean use the machine... So a lot of people set expectations on the machine You saw articles being written maybe these people didn't understand it. Little bit pulled back, almost dampered down a little bit in terms of the marketing of the machine, other than the bin. Is that because you don't yet know what it's going to look like? Or there's so many broader possibilities where you're trying to set expectations? Cause the machine certainly has a lot of range and it's almost as if I could read your minds you don't want to post the position too early on what it could do. And that's my observation. Why the pullback? I mean certainly as a marketer I'd be all over that. >> Andrew: Yeah, I think part of it has been intentional just on how the ecosystem, we need the ecosystem developed kind of around this at the same time. Meaning, there are a lot of kind of moving parts to it whether it's around the open source community and kind of getting their head wrapped around what is this new architecture look like. We've got things like you know the Jin Zee Consortium where we're pouring a lot of our understanding and knowledge into that. And so we need a lot of partners, we know we're in a day and an age where look there's no single one company that's going to do every piece and part themselves. So part of it is kind of enough to get out there, to get the buzz, get the excitement to get other people then on board and now we have been heads down especially this last six months of... >> John: Jamming hard on it. >> Getting it all together. You know you think about what we showed first essentially first booted the thing in November and now you know we've got it running at this scale, that's really been the focus. But we needed a lot of that early engagement, interaction to get a lot of the other, members of the ecosystem kind of on board and starting to contribute. And really that's where we're at today. >> John: It's almost you want it let it take its own course organically because you mentioned just on the cyber surveillance opportunity around the crunching, you kind of don't know yet what the killer app is right? >> And that's the great thing of where we're at today now that we have kind of the prototype running at scale like this, it is allowing us to move beyond, look we've had the simulators to work with, we've had kind of emulation vehicles now you've got the real thing to run actual workloads on. You know we had the announcement around DZ and E as kind of an early early example, but it really now will allow us to do some refinement that allows us to get to those product concepts. >> Dave: I want to just ask the closing question. So I've had this screen here, it's like the theater, and I've been seeing these great things coming up and one was "Moore's Law is dead." >> Oh that was my session this morning. >> Another one was block chain. And unfortunately I couldn't hear it but I could see the tease. So when you guys come to work in the morning what's kind of the driving set of assumptions for you? Is it just the technology is limitless and we're going to go figure it out or are there things that sort of frame your raison d'etre? That drive your activities and thinking? And what are the fundamental assumptions that you guys use to drive your actions? >> Kirk: So what's been driving me for the last couple years is this exponential growth of information that we create as a species. That seems to have no upper bounding function that tamps it down. At the same time, the timeframe we want to get from information, from raw information to insight that we can take action on seems to be shrinking from days, weeks, minutes... Now it's down to micro seconds. If I want to have an intelligent power grid, intelligent 3G communication, I have to have micro seconds. So if you look at those two things and at the same time we just have to be the lucky few who are sitting in these seats right when Moore's Law is slowing down and will eventually flatten out. And so all the skills that we've had over the last 28 years of my career you look at those technologies and you say "Those aren't the ones that are going "to take us forward." This is an opportunity for us to really look and examine every piece of this, because if was something we could of just can't we just dot dot dot do one thing? We would do it, right? We can't just do one thing. We have to be more holistic if we're going to create the next 20, 30, 40 years of innovation. And that's really what I'm looking at. How do we get back exponential scaling on supply to meet this unending exponential demand? >> Dave: So technically I would imagine, that's a very hard thing to balance because the former says that we're going to have more data than we've ever seen. The latter says we've got to act on it fast which is a great trend for memory but the economics are going to be such a challenge to meet, to balance that. >> Kirk: We have to be able to afford the energy, and we have to be able to afford the material cost, and we have to be able to afford the business processes that do all these things. So yeah, you need breakthroughs. And that's really what we've been doing. And I think that's why we're so fortunate at Hewlett Packard Enterprise to have the labs team but also that world class engineering and that world class supply chain and a services team that can get us introduced to every interesting customer around the world who has those challenging problems and can give us that partnership and that insight to get those kind of breakthroughs. >> Dave: And I wonder if there will be a tipping point, if the tipping point will be, and I'm sure you've thought about this, a change in the application development model that drives so much value and so much productivity that it offsets some of the potential cost issues of changing the development paradigm. >> And I think you're seeing hints of that. Now we saw this when we went from systems of record, OLTP systems, to systems of engagement, mobile systems, and suddenly new ways to develop it. I think now the interesting thing is we move over to systems of action and we're moving from programmatic to training. And this is this interesting thing if you have those data bytes of data you can't have a pair of human eyeballs in front of that, you have to have a machine learning algorithm. That's the only thing that's voracious enough to consume this data in a timely enough fashion to get us answers, but you can't program it. We saw those old approaches in old school A.I., old school autonomous vehicle programs, they go about 10 feet, boom, and they'd flip over, right? Now you know they're on our streets and they are functioning. They're a little bit raw right now but that improvement cycle is fantastic because they're training, they're not programming. >> Great opportunity to your point about Moore's Law but also all this new functionality that has yet been defined, is right on the doorstep. Andrew, Kirk thank you so much for sharing. >> Andrew: Thank you >> Great insight, love Hewlett Packard Labs love the R&D conversation. Gets us a chance to go play in the wild and dream about the future you guys are out creating it congratulations and thanks for spending the time on The Cube, appreciate it. >> Thanks. >> The Cube coverage will continue here live at Las Vegas for HPE Discover 2017, Hewlett Packard Enterprises annual event. We'll be right back with more, stay with us. (bright music)

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

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome back to the Cube's continuing coverage of HPE. Discover 22 live from Las Vegas, the Venetian expo center at Lisa Martin and Dave Velante have a very special guest. Next one of our esteemed alumni here on the cube, Antonio Neri, the president and CEO of HPE, Antonio. Thank you so much for joining us this morning. >>Well, thanks for free with us today. >>Great to be back here after three years away. Yeah. Sit on stage yesterday in front of a massive sea of people. The energy here is electric. Yeah. Must have felt great yesterday, but you, you stood on stage three years ago and said buy 20, 22. And here it is. Yeah. We're gonna deliver our entire portfolio as a service. What was it like to be on stage and say we've done that. Here's where we are. We are a new company. >>Well, first of all, as always, I love the cube to cover HP discover, as you said, has been many, many years, and I hope you saw a different company yesterday. I'm really proud of what happened yesterday, because it was a pivotable moment in our journey. If I reflect back in my four years as a CEO, we said the enterprise of the future will be edge centric, cloud enable and data driven in 2018. And I pledged to invest 4 billion over four years. And you see the momentum we have at the edge with our business. And then in 19, to your point, Lisa, we said, by the end of 2022, we will offer everything as a service. When you look at the floor behind us, everything is a as a service experience from the moment you log through IHP GreenLake platform to all the cloud services we offer. So for me, it is a proud moment because our team worked really hard to deliver on that province on the face of a lot of challenges, >>Tremendous challenges, the last couple years that nobody could have predicted or even forecast, how can we tolerate this? Talk to me about your customer conversations and how they have changed and evolved as every company today has to be a data company. >>Well, even this morning, up to this interview, I already met four customers in, in less than an hour and a half. And I will say all of them, first of all, really appreciated bringing HP discover back. And what they really appreciated was the fact that they had the opportunity to meet and greet and talk to people. The energy that comes from that engagement is second to none. And I think says something right about the moment we are at this time, where the return to work and everything else. I think this is a wake up call in many ways, but customers are telling us is that they want to engage with a partner that has a vision that can take them to their journey, whatever that journey is. And we know digital transformation is core to everything, but ultimately they are now more focused on delivering outcomes for the organization they're running in it. And that's why HP GreenLake is incredible well positioned to do so, you >>Know, just picking up on that. I, I, I counted Antonio. I think I've been to 14 HP and HPE discovers when you include Europe. Yeah. I mean, Frankford, London, Barcelona Madrid, of course, you know the us, and I've never seen why I've tweeted this out. I've never seen this type of energy. Right. People are excited to get back. That's part of it. The other big part of it is course the focus. Yeah. So that focus on as a service was a burn, the boat moment for HPV. >>I don't think it was a burn the boat moment. It was a moment that we have to decide how we think about the future and how we become even more relevant for customers. And we are very important to all the customers they buy from us. Right. But I think about the next 3, 5, 10 years, how we position the company, enter the future to be relevant to whatever they need to do. >>Well, what I mean by that is you're not turning back. No, the bridge is gone. You go, you're going forward. And so my question is, did the pandemic accelerate that move or did it, did it hinder it? And, and, and how so >>Actually it was an, a moment for us to think about how we go further and faster to what we call this journey to one, one platform, one experience. And, and we felt as a team, as an organization, this was a unique moment in time to go further, faster. So to us, it was a catalyst to accelerate that transformation. >>Yeah. Now I, I want to ask you a question in your keynote. I love this, cuz you say I'm often asked by customers, what workload should we move to the public cloud and what should stay on prem? I'm like, yeah, I get that question all the time. And I was waiting for the answer. You said, that's the wrong question. And I was like, wait, but that's the question everybody's asking. So it was really interesting that you said that. And I wonder if you could, you could comment. And I think you said basically the world's hybrid is your challenge with, with the customers in this initiative to actually get people to stop asking that question. Right. And not think about that. >>No, I think the challenge we all collectively have is that how we think about data and how we drive what I call a data first modernization, you know, strategy for our customers in an age to cloud architecture, which basically says you are living a hybrid world is not a question which workloads are put in the public cloud, which workloads are put OnPrem. You know, the, all the issues around data gravity and whatnot is a question of how I bring the cloud experience to all your workloads of data, wherever they live. And that's where, you know, the opportunity really exists. And as customers understand more and more about the new environments, how they work, how they enable these new experiences is all driven by that data. And that data has enormous value. So it's not about which cloud use is about how you bring the cloud experience to your data in workloads. >>When you're talking to CIOs, especially transformational CIOs, what's the value pro to those CIOs that wanna transform and need to transform with the power of HPE. >>More and more of them are becoming conscious about the fact that they need to go faster in everything they do. We have done some interesting analysis with the brands that have done a better job or have become way more proficient on extracting insight from the data. They are actually the brands that winning the marketplace, not just with customers driving the preference, but also in the market capitalization because they become where more sophisticated in driving better efficiency, which is a necessity today. Second is the fact that also they need to improve their security aspect of it, but they are creating new experiences and new revenue streams. And those transformational CIOs are transforming their business in the way they run it into more an innovation engine. And so that's why, you know, we love working with them because they are advanced and the push has to think differently in the way we think about the innovation. How >>Do you help customers go from data, rich insight, port to data, rich insight, rich actions, new revenue, streams, new services. >>Well, first of all, you have to deploy the right architecture, which starts with a network, obviously because digital transformation requires an on-ramp and the connectivity is the first step. Second is to make sure you have a true end to end visibility of that data. And that's why we announced yesterday with the data fabric, right? A, a revolutionary way to think about that age to cloud architecture from a data driven perspective. And then the third piece of this is, is the aspect of how we bring that intelligence to that data. And that's where, you know, we are enabling all these amazing services with AI machine learning with, with, you know, HP GreenLake, which is ultimately the way we are gonna enable them. >>What's your favorite announcement from this week? >>I think HP GreenLake, you know, I think I >>Mentioned a lot of GreenLake, >>36 times HP GreenLake. And to me, you know, as I think about what comes next, right, is about how we innovate now on the platform at the pace that customers are demanding. And so for me, there is a lot of things there, but obviously the private cloud enterprise edition was a big moment for us because that's the way we bring the cloud operating experience on-prem and at the edge, but also all the hybrid capabilities that Brian showed during the demo is something that I think customers now say, wow, I didn't know. We can do that. >>And thinking about your business, you know, despite some macro headwinds and, and like you, you reaffirmed your guidance on the, on the last earnings call. Does GreenLake give you better visibility or is it harder to predict? >>No, I think the more we get engaged with customers in running their workloads and data, the more visibility we get, you know, I said, you know, customers voted with the workloads and data. And in, in that context, you know, we already have 65,000 customers more than 120,000 users. And the one interesting stat, which I hope it didn't go lost during that transition was the, the fact that we now have under the GreenLake management over an next bite of data. And so to me, right, that's a unique, a unique opportunity for us to learn and improve the whole cycle. >>So obviously a big pillar of your strategy is the data. And I wanted, if you could talk more about that because I, I would observe, you know, we, the cube started in sort of as big data, you know, started to take off and you saw that had ecosystem and, and that ecosystem has dispersed now. Yeah. So gone into the cloud, it's got snowflakes pulling and some in Mongo. Now you have the opportunity with this ecosystem yeah. To have a data ecosystem. How do you look at the ecosystem and the value that your partners can build on top of GreenLake and specifically monetize? Well, >>If you walk through the floor, one of the things we changed this time is that the partners are actually in the flow of all our solutions, not sitting on a corner of the show floor, right? And, and, and that's because what we have done in the last three years has been together with our partners, but we conceive HP GreenLake with the partners in mind, at the core of everything we do in the platform. And that's why on Monday we announced the new partner one ready vantage program that actually opens the platform through our APIs for allowing them to add their own value on the platform, whether in their own services to the marketplace or the other way around they to use our capabilities in their own solutions. Because some of these cloud operating capabilities are hard to develop, whether it is, you know, metering and billing and all the other services, sometimes you don't don't have to build yourself. So that's why, what we love about our strategies, the partners can decide where to participate in this broad ecosystem and then grow with us and we can grow through them as well. >>So GreenLake as a service, the focus is, is very clear. Hybrid is very clear. What's less clear to me is, is that I'll and I'll ask you to comment, is this, we go a term called super cloud and super cloud is different than multi-cloud multi-cloud oh, I run in AWS or, and, or I run in Azure. I run in, in, in GCP, Supercloud builds a layer above that hides the underlying complexity of the primitives and the APIs, and then builds new value on top of that, out to the edge as well. You guys talk about the edge all the time. You have Aruba a as an asset, you got space space born. You're doing some pretty edge. Like, well, >>We have it here. Yeah. Yeah. We are connected to the ISS. So if you were to that show floor, you can actually see what's being processed today. >>I mean, that's, you don't get more edge than that. So my question is, is, is that part of the vision to actually build that I call super cloud layer? Or is it more to be focused on hybrid and connecting on-prem to the cloud? >>No, I, I don't like to call it super cloud because that means, unless you are a superpower, you can't do what you need to do. I, I think I call it a super straight okay. Right. That we are enabling to our H to cloud architecture. So the customers can build their own experiences and consume the services that they need to compete and win in today's market. So our H to cloud approach is to create that substrate with connectivity, obviously the cloud and the data capability that you need to operate in today's >>Environment. Okay. So they're fair enough. I would say that your customers are gonna build then the super cloud on top of that software. >>Well, actually we want to give it to them. They don't have to build anything. They just need to run the business. Well, they don't have the time to really build stuff. They just need to innovate that's our, our value proposition. So they don't have to waste cycles in doing so if it comes ready to go, why you want to build it? >>Well, when I say build it, I'm talking about building their business on top of it things you're not gonna, I agree with that, bringing their tools, financial services companies with their data, their tools, their ecosystem, connecting OnPrem to the clouds. Yeah. That above that substrate that's their as a digital. >>Yeah. And that's why I said yesterday with our approach, we're actually enabling customers to power the next generation business models that they need. We enable the substrate, they can innovate on the platform, these next gen business models, >>Tap your engineering mind. And I'd like you to talk about how architectures are changing you along with many, many other CEOs signed a letter to, to the us government, you know, urging them to, to, to pass the chips act. As I posted on LinkedIn, there were, there were a few notables missing apple wasn't on there, meta wasn't on there, Tesla wasn't on there. I'd like to see them step up and sign that. Yeah. And so why did you, you know, sign that? Why did you post that? And, and, and why is that important? >>Well, first of all, it's important to customers because obviously they need to get access to technologies in a more ubiquitous way. And second it's important for the United States. We live in a, in a global economy that today is going to a refactoring of sorts where supply chain disruption has caused a lot of consternation and disruption across many industries. And I think, you know, as we think about the next generation supply chains, which are built for resiliency and obviously inclusion, we need to make sure that the United States address this problem. Because once you fall behind, it takes a long time to catch up. Even if we sign the chips act, it's gonna take many years for us, but we need to start now. Otherwise we never get what we need to >>Get. I, I agree. We're late. I think pat Gelsinger has done a very good job laying out the mission, you know, to bring, I mean, to me, it's modest, bring 20% of the manufacturing back to the us by the end of the decade. I mean that that's not gonna be easy, but even so that's, >>That's, we need stuff somewhere. Absolutely. You know, we are great partners with Intel. I really support the vision that path has laid out. And its not just about Intel again, it's about our customers in the United States, >>HP and HPE now cuz H HP labs is part of, of HPE. I believe that's correct state. Well, >>We refocus HP labs as a part of our high performance. Yeah. And AI business. Yes. >>But H HP and, and now HPE possess custom Silicon expertise. We may, we always >>Had. >>Yeah, exactly. And, and you know, with the fabulous world, do you see, I mean, you probably do in some custom Silicon today that I don't really, you know, have visibility on, but do you see getting more into that? Is there a need for >>That? Yeah. Well we already design more than 60 different silicons that are included in our solution. More and more of that. Silicon is actually in support of our other service experience. That's truly programmable for this new way to deploy a cloud or a data fabric or a network in fabric of sorts. When you look our, our age portfolio as a part of green lake through our Aruba set of offerings, we actually have a lot of the Silicon building. Our switching portfolio that's program. Normally give us the ability to drive intelligent routing in the network at the application layer. But also as you know, many years ago, we introduced our own ILO, the lights out technology, the BMC type of support that allows us to provide security to the root of our systems. But now more implement a cloud operating security environment if you will, but there is many more in the analog space for AI at scale. And even the latest introduction with frontier. When you look at frontier that wonderful high performance exit scale system, the, the magic of that is in the Silicon we developed, which is the interconnect fabric. Plus the smart mix at massive massive scale for parallel computing. And then ultimately it's the software environment that we put on top of it. So we can process billion, billion, square transactions per second. >>And when you think about a lot of the AI today is modeling, that's done in the cloud. When you think about the edge actual real time in, you're not gonna send all that back to the cloud. When you have to make a left turn or a right turn, >>Stop sign. I think, you know, people need to realize that 70% of the data today is outside the public cloud and 50% is at the edge. And when you think about the real time use cases, actually 30% of that data will need to be processed real time. So which means you need to establish inference the rate at the edge and at the same time run, you know, the analytics at the edge, whether it's machine learnings or some sort of simulation they need to do at the edge. And so that's why, you know, we can provide inference. We can provide machine learning at the edge on top of the connectivity and the edge compute or cloud computing at the edge. But also we can provide on the other side, AI at scale for massive amount of data analytics. And >>Will that be part of the GreenLake? >>We already offered that experience. We already offered that as a HPC, as a service is one of the key services we provide at scale. And then you also have machine learning operations as a service. So we have both and with the data fabric, now we're gonna take it to one step forward so we can connect the data. And I think one of the most exciting services, I actually, I'm a true believer. That is the capability we develop through HP labs. Since you asked for that early on, which is called the swarm learning technology. Of >>Course. Yeah. I've talked to Dr. GU about there you >>Go. >>So, so he >>Will do a better job than me explaining, >>Hey, I don't know. You're pretty, pretty good at it, but he's awesome. I mean, I have to admit on your keynote, you specifically took the time to mention your support for women's rights. Yes. Will HPE pay for women to leave the state to have a medical procedure? >>Yeah. So what happened last week was a sad moment in a history. I believe we, as a company felt compelled to stand up and take a position on the rights of women to choose. And as a part of that, we already offer as a part of our benefits, the ability to travel and pay all the medical expenses related to their choice. >>Yeah. Well thank you for doing that. I appreciate it. As a, as a father of two daughters who have less rights than, than my wife did when she was their age, I applaud you for your bravery and standing up and, and thank you for doing that. How excited are you for Janet Jackson? >>I think is gonna be a phenomenal rap of the HP discover, I think is gonna be a great moment for people to celebrate the coming together. One of the feedback I got from the meetings early on from customers is that put aside the vision, the strategy, the solutions that they actually can experience themselves is the fact that the, the, the one thing that really appreciated it is that they can be together. They can talk to people, they can learn with each other from each other. That energy is obviously very palpable when you go through it. And I think, you know, the celebration tonight and I want to thank the sponsor for allowing us to do so, is, is the fact that, you know, it's gonna be a moment of reuniting ourselves and look at the Fu at the future with optimism, but have some fun. >>Well, that's great, Antonio, as I said, I've been to a lot of HP and HPE discovers. You've brought a new focus clearly to the company, outstanding job of, of getting people aligned. I mean, it's not easy. It's 60,000, you know, professionals a around the globe and the energy is like I've never seen before. So congratulations. Thank you so much for coming back in the queue. >>Thank you, Dave. And as always, we appreciate you covering the, the event. You, you share the news with all the audiences around the globe here and, and that's, that means us means a lot to us. Thank you. Thank you. >>And thank you for watching. This is Dave Velante for Lisa Martin and John furrier. We'll be right back with our next guest. Live from HPE. Discover 2022 in Las Vegas.

>>from around the globe. It's the Cube covering HP. Discover Virtual experience Brought to you by HP. >>Welcome back to the Cube's coverage of HP Discover. 2020. The virtual experience. The Cube. The Cube has been virtualized. My name is Dave Vellante. I'm here with Stuart Minuteman and our good friend Tim Crawford is here. He's a strategic advisor to see Io's with boa. Tim, Great to see you. Stuart. Thanks for coming on. >>Great to see you as well, Dave. >>Yes. So let's unpack. What's going on in that Discover Antonio's, He notes, Maybe talk a little bit about the prospects for HP of coming forward in this decade. You know, last decade was not a great one for HP, HP. I mean, there was a lot of turmoil. There was a botched acquisitions. There was breaking up the company and spin merges and a lot of distractions. And so now that companies really and you hear this from Antonio kind of positioning for innovation for the next decade. So So I think this is probably a lot of excitement inside the company, but I want to touch on a couple of points and then you get your guys reaction, I guess, you know, to start off. Obviously, Antonio's talking about Cove in the role that they played in that whole, you know, pandemic and the transition toe the the isolation economy. But so let me start with you, Tim. I mean, what is the sort of posture amongst cios that you talk to? How strategic is HB H B two? The folks that you talk to in your community? >>Well, I think if you look at how CIOs are thinking, especially as we head into covert it into Corona virus and kind of mapping through that, that price, um, it really came down to Can they get their hands on technology? Can they get people back to work working from home? Can they do it in a secure fashion? Um, keeping people productive. I mean, there was a lot of block and tackling, and even to this day, there's still a fair amount of that was taking place. Um, we really haven't seen the fallout from the cybersecurity impact of expanding our foot print. Um, quite. But we'll see that, probably in the coming months. There are some initial inklings there when it comes to HP specifically I think it comes back to just making sure that they had the product on hand, that they understood that customers are going through dramatic change. And so all bets are off. You have to kind of step back and say, Okay, those plans that I had 60 9100 and 20 days ago those strategies that I may have already started down the path with those are up for grabs. I need to step back from those and figure out What do I do now? And I think each company, HP included, needs to think about how do they start to meld themselves, to be able to address those changing customer needs? And I think that's that's where this really kind of becomes the rubber hits the road is is HP capable of doing that? And are they making the right changes? And quite frankly, that starts with empathy. And I think we've heard pretty clearly from Antonio that he is sympathetic to the plight of their customers and the world >>on the whole. >>Yeah, and I think culturally 10 minutes do I mean I think you know HP is kind of getting back to some of its roots, and Tony has been there for a long time. I think people I think is very well liked. Andi, I think, ease of use, and I'm sure he's tough. But he's also a very fair individual, and he's got a vision and he's focused. And so, you know, I think again, as they said, looking forward to this decade, I think could be one that is, you know, one of innovation. Although, you know, look, you look at the stock price, you know, it's kind of piqued in November 19. It's obviously down like many stocks, so there's a lot of work to do there, and it's too. We're certainly hearing from HP. This notion of everything is a service that we've talked about green like a lot. What's your sense of their prospects going forward in this, you know, New Era? >>Yeah, I mean, Dave, one of the biggest attacks we've heard about H E in the last couple of years, you know the line Michael Dell would use is you're not going to grow by, say, abstraction. But as a platform company, HP is much more open. From what I've seen in the HP that I remember from, you know, 5 to 10 years ago. So you look at their partner ecosystem. It's robust. So, you know, years ago, it seemed to be if it didn't come out of HP Labs, it wasn't a product, you know. That was the services arm all wanted to sell HP here. Now, in this software defined world working in a cloud environment, they're much more open to finding that innovation and enabling it. So, you know, we talk about Green Lake Day. Three lakes got about 1000 customers right now, and a big piece of that is a partner. Port Police, whether it's VM Ware Amazon Annex, were H B's full stack themselves. They have optionality in there, and that's what we hear from from users is that they want flexibility they don't want. You know, you look at the cloud providers, it's not, you know, here's a solution. You look at Amazon. There's dozens of databases that you can use from Amazon or, if you use on top of Amazon, so H p e. You know, not a public cloud provider, but looking more like that cloud experience. They've done so many acquisitions over the years. Many of them were troubled. They got rid of some of the pieces that they might have over paid for. But you look at something like CTP them in this multi cloud world in the networking space, they've got a really cool, open source company, the company behind spiffy, inspire. And, you know, companies that are looking at containers and kubernetes, you know, really respond to say, Hey, these are projects that were interesting Oh, who's the company that that's driving that it's HP so more open, more of a partner ecosystem definitely feels that there's a lot there that I respect and like that hp >>well, I mean, the intent of splitting the company was so that HP could be more focused but focused on innovation was the intent was to be the growth company. It hasn't fully played out yet. But Tim, when you think about the conversations that CIOs are having with with HPI today versus what they were having with hpe HP, the the conglomerate of that the Comprising e ds and PCs, I guess I don't know, in a way, more more Dell like so Certainly Michael Dell's having strategic conversations, CIOs. But you got to believe that the the conversations are more focused today. Is that a good thing or a jury's still out? >>No, it absolutely is a good thing. And I think one of the things that you have to look at is we're getting back to brass tax. We're getting back to that focus around business objectives. So no longer is that hey, who has the coolest tech? And how can we implement that tax? Kind of looking from a tech business? Ah, spectrum, you're now focused squarely is a C i. O. You have to be squarely focused on what are the business objectives that you are teamed up for, and if you're not, you're on a very short leash and that doesn't end well. And I think the great thing about the split of HP HP e split and I think you almost have to kind of step back for a second. Let's talk about leadership because leadership plays a very significant role, especially for CIOs that are thinking about long term decisions and strategic partners. I don't think that HP necessarily had the right leadership in place to carry them into that strategic world. I think Antonio really makes a change there. I mean, they made some really poor decisions. Post split. Um, that really didn't bode well for HP. Um, and frankly, I talked a bit about that I know wasn't really popular within HP, but quite frankly, they needed to hear it. And I think that actually has been heard. And I think they are listening to their customers. And one of the big changes is they're getting back into the software business. And when you talk about strategic initiatives, you have to get beyond just the hardware and start moving up the proverbial stack, getting closer to those business initiatives. And that is software. >>Yeah, well, Antonio talked about sort of the insights. I mean, something I've said a lot about borrowed from the very Meeker conversations that that data is plentiful. Something I've always said. Insights aren't. And so you're right. You've seen a couple of acquisitions, you know, Matt bahr They picked up, I think pretty inexpensively. Kind of interesting cause, remember, HP hp had an investment in Horton works, which, of course, is now Cloudera and Blue Data. Ah Kumar Conte's company, you know, kind of focusing on maybe automating data, you know, they talked about Ed centric, cloud enabled, data driven. Nobody's gonna argue with those things. But you're right, Tim. I mean, you're talking more software than kind of jettisons the software business and now sort of have to rebuild it. And then, of course, do this cloud. What do you make of HP ease Cloud play? >>Yeah, well, I >>mean, >>Dave, you the pieces. You were just talking about math bar and blue data, where HP connects it together is, you know, ai ops. So you know, where are we going with infrastructure? There needs to be a lot more automation. We heard a great quote. I love from automation anywhere. Dave was, if you talk about digital transformation without automation, it's hallucination. So, you know, HP baking that into what they're doing. So, you know, I fully agree with Tim software software software, you know, is where the innovation is. So it can't just be the infrastructure. How do you have eyes and books into the applications? How are you helping customers build those new pieces? And what's the other software that you build around that? So, you know, absolutely. It's an interesting piece. And you know, HP has got a lot of interesting pieces. You know, you talk about the edge. Aruba is a great asset for that kind of environment and from a partnership, that is a damn point. Dave. They have. John Chambers was in the keynote. John, of course. Long time partners. He's with Cisco for many years Intel. Cisco started eating with HP on the server business, but now he's also the chairman of pensando. HP is an investor in pensando general availability this month of that solution, and that's going to really help build out that next generation edge. So, you know, a chip set that HP E can offer similar to what we see how Amazon builds outpost s. So that is a solution both for the enterprise and beyond. Is as a B >>yeah course. Do. Of course, it's kind of, but about three com toe. Add more fuel to that tension. Go ahead, Tim. >>Well, I was going to pick apart some of those pieces because you know, at edge is not an edge is not an edge. And I think it's important to highlight some of the advantages that HP is bringing to the table where Pensando comes in, where Aruba comes in and also we're really comes in. I think there are a number of these components that I want to make sure that we don't necessarily gloss over that are really key for HP in terms of the future. And that is when you step back and you look at how customers are gonna have to consume services, how they're going to have to engage with both the edge and the cloud and everything in between. HP has a great portfolio of hardware. What they haven't necessarily had was the glue, that connective tissue to bring all of that together. And I think that's where things like Green Lake and Green Lake Central really gonna play a role. And even their, um, newer cloud services are going to play a role. And unlike outposts and unlike some of the other private cloud services that are on the market today, they're looking to extend a cloud like experience all the way to the edge and that continuity creating that simplicity is going to be key for enterprises. And I think that's something that shouldn't be understated. It's gonna be really important because when I look at in the conversations I'm having when we're looking at edge to cloud and everything in between. Oh my gosh, that's really complicated. And you have to figure out how to simplify that. And the only way you're going to do that is if you take it up a layer and start thinking about management tools. You start thinking about autumn, and as companies start to take data from the edge, they start analyzing it at the edge and intermediate points on the way to cloud. It's going to be even more important to bring continuity across this entire spectrum. And so that's one of the things that I'm really excited about that I'm hearing from Antonio's keynote and others. Ah, here at HP Discover. >>Yeah, >>well, let's let's stay on that stupid. Let's stay on that for a second. >>Yeah, I wanted to see oh interested him because, you know, it's funny. You think back. You know, HP at one point in time was a leader in, you know, management solutions. You know, HP one view, you know, in the early days, it was really well respected. I think what I'm hearing from you, I think about outpost is Amazon hasn't really put management for the edge. All they're doing is extending the cloud piece and putting a piece out of the edge. It feels like we need a management solution that built from the ground up for this kind of solution. And do I hear you right? You believe that to be as some of those pieces today? >>Well, let's compare and contrast briefly on that. I think Amazon and the way Amazon is well, is Google and Microsoft, for that matter. The way that they are encompassing the edge into their portfolio is interesting, but it's an extension of their core business, their core public cloud services business. Most of the enterprise footprint is not in public cloud. It's at the other end of that spectrum, and so being able to take not just what's happening at the edge. But what about in your corporate data center in your corporate data center? You still have to manage that, and that doesn't fall under the purview of Cloud. And so that's why I'm looking at HP is a way to create that connective tissue between what companies are doing within the corporate data center today, what they're doing at the edge as well as what they're doing, maybe in private cloud and an extension public cloud. But let's also remember something else. Most of these enterprises, they're also in a multi cloud environment, so they're touching into different public cloud providers for different services. And so now you talk about how do I manage this across the spectrum of edge to cloud. But then, across different public cloud providers, things get really complicated really fast. And I think the hints of what I'm seeing in software and the new software branding give me a moment of pause to say, Wait a second. Is HP really gonna head down that path? And if so, that's great because it is of high demand in the enterprise. >>Well, let's talk about that some more because I think this really is the big opportunity and we're potentially innovation is. So my question is how much of Green Lake and Green Lake services are really designed for sort of on Prem to make that edge to on Prem? No, I want to ask about Cloud, how much of that is actually delivering Cloud Native Services on AWS on Google on Azure and Ali Cloud etcetera versus kind of creating a cloud like experience for on Prem in it and eventually the edge. I'm not clear on that. You guys have insight on how much effort is going into that cloud. Native components in the public cloud. >>Well, I would say that the first thing is you have to go back to the applications to truly get that cloud native experience. I think HP is putting the components together to a prize. This to be able to capitalize on that cloud like experience with cloud native APS. But the vast majority of enterprise app they're not cloud native. And so I think the way that I'm interpreting Green Lake and I think there are a lot of questions Greenland and how it's consumed by enterprises there. There was some initial questions around the branding when it first came out. Um, and so you know it's not perfect. I think HP definitely have some work to do to clarify what it is and what it isn't in a way that enterprises can understand. But from what I'm seeing, it looks to be creating and a cloud like experience for enterprises from edge to cloud, but also providing the components so that if you do have applications that are shovel ready for cloud or our cloud native, you can embrace Public Cloud as well as private cloud and pull them under the Green Lake >>Rela. Yeah, ostensibly stew kubernetes is part of the answer to that, although you know, as we've talked about, Kubernetes is necessary containers and necessary but not sufficient for that experience. And I guess the point I'm getting to is, you know we do. We've talked about this with Red Hat, certainly with VM Ware and others the opportunity to have that experience across clouds at the Edge on Prim. That's expensive from an R and D standpoint. And so I want to kind of bring that into the discussion. HP last year spent about 1.8 billion in R and D Sounds like a lot of money. It's about 6% of its of it's revenues, but it's it's spread thin now. It does are indeed through investments, for instance, like Pensando or other acquisitions. But in terms of organic R and D, you know, it's it's it's not at the top of the heap. I mean, obviously guys like Amazon and Google have surpassed them. I've written about this with regard to IBM because they, like HP, spend a lot on dividends on share buybacks, which they have to do to prop up the stock price and placate Wall Street. But it But it detracts from their ability to fund R and d student your take on that sort of innovation roadmap for the next decade. >>Yeah, I mean, one of the things we look at it in the last year or so there's been what we were talking about earlier, that management across these environments and kubernetes is a piece of it. So, you know, Google laid down and those you've got Microsoft with Azure, our VM ware with EMS. Ooh! And to Tim's point, you know, it feels like Green Lake fits kind of in that category, but there's there's pieces that fall outside of it. So, you know, when I first thought of Green Lake, it was Oh, well, I've got a private cloud stack like an azure stack is one of the solutions that they have there. How does that tie into that full solution? So extending that out, moving that brand I do here, you know good things from the field, the partners and customers. Green Lake is well respected, and it feels like that is, that is a big growth. So it's HB 50 from being more thought of, as you know, a box seller to more of that solution in subscription model. Green Lake is a vehicle for that. And as you pointed out, you know, rightfully so. Software so important. And I feel when that thing I'd say HPI ee feels toe have more embracing of software than, say, they're closest competitors. Which is Dell, which, you know, Dell Statement is always to be the leading infrastructure writer, and the arm of VM Ware is their software. So, you know, just Dell alone without VM ware, HP has to be that full solution of what Dell and VM ware together. >>Yeah, and VM Ware Is that the crown jewel? And of course, HP doesn't have a VM ware, but it does have over 8000 software engineers. Now I want to ask you about open source. I mean, I would hope that they're allocating a large portion of those software engineers. The open source development developing tooling at the edge, developing tooling from multi cloud certainly building hooks in from their hardware. But is HP Tim doing enough in open source? >>Well, I don't want to get on the open source bandwagon, and I don't necessarily want to jump off it. I think the important thing here is that there are places where open source makes sense in places where it doesn't, um, and you have to look at each particular scenario and really kind of ask yourself, does it make sense to address it here? I mean, it's a way to to engage your developers and engage your customers in a different mode. What I see from HP E is more of a focus around trying to determine where can we provide the greatest value for our customers, which, frankly, is where their focus should be, whether that shows up in open source for software, whether that shows up in commercial products. Um, we'll see how that plays out. But I think the one thing that I give HP e props on one of several things I would say is that they are kind of getting back to their roots and saying, Look, we're an infrastructure company, that is what we do really well We're not trying to be everything to everyone. And so let's try and figure out what are customers asking for? How do we step through that? I think this is actually one of the challenges that Antonio's predecessors had was that they tried to do jump into all the different areas, you know, cloud software. And they were really X over, extending themselves in ways that they probably should. But they were doing it in ways that really didn't speak to their four, and they weren't connecting those dots. They weren't connecting that that connective tissue they needed to dio. So I do think that, you know, whether it's open source or commercial software, we'll see how that plays out. Um, but I'm glad to see that they are stepping back and saying Okay, let's be mindful about how we ease into this >>well, so the reason I bring up open source is because I think it's the mainspring of innovation in the industry on that, but of course it's very tough to make money, but we've talked a lot about H B's strength since breath is, we haven't talked much about servers, but they're strong in servers. That's fine We don't need to spend time there. It's culture. It seems to be getting back to some of its roots. We've touched on some of its its weaknesses and maybe gaps. But I want to talk about the opportunities, and there's a huge opportunity to the edge. David Flores quantified. He says that Tam is four. Trillion is enormous, but here's my question is the edge Right now we're seeing from companies like HP and Dell. Is there largely taking Intel based servers, kind of making a new form factor and putting them out on the edge? Is that the right approach? Will there be an emergence of alternative processors? Whether it's our maybe, maybe there's some NVIDIA in there and just a whole new architecture for the edge to authority. Throw it out to you first, get Tim Scott thoughts. >>Yeah, So what? One thing, Dave, You know, HP does have a long history of partnering with a lot of those solutions. So you see NVIDIA up on stage when you think about Moonshot and the machine and some of the other platforms that they felt they've looked at alternative options. So, you know, I know from Wicky Bon standpoint, you know, David Foyer wrote the piece. That arm is a huge opportunity at the edge there. And you would think that HP would be one of the companies that would be fast to embrace that >>Well, that's why I might like like Moonshot. I think that was probably ahead of its time. But the whole notion of you know, a very slim form factor that can pop in and pop out. You know, different alternative processor architecture is very efficient, potentially at the edge. Maybe that's got got potential. But do you have any thoughts on this? I mean, I know it's kind of Yeah, any hardware is, but, >>well, it is a little hardware, but I think you have to come back to the applicability of it. I mean, if you're taking a slim down ruggedized server and trying Teoh essentially take out, take off all the fancy pieces and just get to the core of it and call that your edge. I think you've missed a huge opportunity beyond that. So what happens with the processing that might be in camera or in a robot or in an inch device? These are custom silicon custom processors custom demand that you can't pull back to a server for everything you have to be able to to extend it even further. And, you know, if I compare and contrast for a minute, I think some of the vendors that are looking at Hey, our definition of edge is a laptop or it is this smaller form factor server. I think they're incredibly limiting themselves. I think there is a great opportunity beyond that, and we'll see more of those kind of crop up, because the reality is the applicability of how Edge gets used is we do data collection and data analysis in the device at the device. So whether it's a camera, whether it's ah, robot, there's processing that happens within that device. Now some of that might come back to an intermediate area, and that intermediate area might be one of these smaller form factor devices, like a server for a demo. But it might not be. It might be a custom type of device that's needed in a remote location, and then from there you might get back to that smaller form factor. Do you have all of these stages and data and processing is getting done at each of these stages as more and more resources are made available. Because there are things around AI and ML that you could only do in cloud, you would not be able to do even in a smaller form factor at the edge. But there are some that you can do with the edge and you need to do at the edge, either for latency reasons or just response time. And so that's important to understand the applicability of this. It's not just a simple is saying, Hey, you know, we've got this edge to cloud portfolio and it's great and we've got the smaller servers. You have to kind of change the vernacular a little bit and look at the applicability of it and what people are actually doing >>with. I think those are great points. I think you're 100% right on. You are going to be doing AI influencing at the edge. The data of a lot of data is going to stay at the edge and I personally think and again David Floor is written about this, that it's going to require different architectures. It's not going to be the data center products thrown over to the edge or shrunk down. As you're saying, That's maybe not the right approach, but something that's very efficient, very low cost of when you think about autonomous vehicles. They could have, you know, quote unquote servers in there. They certainly have compute in there. That could be, you know, 2344 $5000 worth of value. And I think that's an opportunity. I'd love to see HP Dell, others really invest in R and D, and this is a new architecture and build that out really infuse ai at the edge. Last last question, guys, we're running out of time. One of the things I'll start with you. Still what things you're gonna watch for HP as indicators of success of innovation in the coming decade. As we said last decade, kind of painful for HP and HP. You know, this decade holds a lot of promise. One of the things you're gonna be watching in terms of success indicators. >>So it's something we talked about earlier is how are they helping customers build new things, So a ws always focuses on builders. Microsoft talks a lot. I've heard somethin double last year's talk about building those new applications. So you know infrastructure is only there for the data, and the applications live on top of it. And if you mention Dave, there's a number of these acquisitions. HP has moved up the stack. Some eso those proof points on new ways of doing business. New ways of building new applications are what I'm looking for from HP, and it's robust ecosystem. >>Tim. Yeah, yeah, and I would just pick you back right on. What's do was saying is that this is a, you know, going back to the Moonshot goals. I mean, it's about as far away as HP ease, and HP is routes used to be and that that hardware space. But it's really changing business outcomes, changing business experiences and experiences for the customers of their customers. And so is far cord that that eight p e can get. I wouldn't expect them to get all the way there, although in conversations I am having with HP and with others that it seems like they are thinking about that. But they have to start moving in that direction. And that's actually something that when you start with the builder conversation like Microsoft has had, an Amazon has had Google's had and even Dell, to some degree has had. I think you missed the bigger picture, so I'm not saying exclude the builder conversation. But you have to put it in the right context because otherwise you get into this siloed mentality of right. We have solved one problem, one unique problem, and built this one unique solution. And we've got bigger issues to be able to address as enterprises, and that's going to involve a lot of different moving parts. And you need to know if you're a builder, you've it or even ah ah, hardware manufacturer. You've got to figure out, How does your piece fit into that bigger picture and you've got to connect those dots very, very quickly. And that's one of the things I'll be looking for. HP as well is how they take this new software initiative and really carry it forward. I'm really encouraged by what I'm seeing. But of course the future could hold something completely different. We thought 2020 would look very different six months ago or a year ago than it does today. >>Well, I wanna I want to pick up on that, I think I would add, and I agree with you. I'm really gonna be looking for innovation. Can h P e e get back to kind of its roots? Remember, H B's router invents it was in the logo. I can't translate its R and D into innovation. To me, it's all about innovation. And I think you know cios like Antonio Neri, Michael Dell, Arvind Krishna. They got a They have a tough, tough position because they're on the one hand, they're throwing off cash, and they can continue Teoh to bump along and, you know, placate Wall Street, give back dividends and share buybacks. And and that's fine. And everybody would be kind of happy. But I'll point out that Amazon in 2007 spent spend less than a $1,000,000,000 in R and D. Google spent about the back, then about the same amount of each B E spends today. So the point is, if the edge is really such a huge opportunity, this $4 trillion tam is David Foyer points out, there's a There's a way in which some of these infrastructure companies could actually pull a kind of mini Microsoft and reinvent themselves in a way that could lead to massive shareholder returns. But it was really will take bold vision and a brave leader to actually make that happen. So that's one of things I'm gonna be watching very closely hp invent turn r and D into dollars. And so you guys really appreciate you coming on the Cube and breaking down the segment for ah, the future of HP be well, and, uh and thanks very much. Alright. And thank you for watching everybody. This is Dave Volante for Tim Crawford and Stupid men. Our coverage of HP ease 2020 Virtual experience. We'll be right back right after this short break. >>Yeah, yeah, yeah, yeah.

thanks Peter we're here with Patrick Osbourne who's the vice president and general manager of big data and secondary storage with HPE Patrick help us put into context what we've been talking about Emel ops AI and HP strategy in this area yeah thanks to I you know as you as you all have reported in the past and we've worked with with with you your HP is very strong in infrastructure solutions we've had you know quite a bit of success in AI and now deep learning cookbook which we released last year and so you know we're definitely helping customers along the maturity curve for AI and ml you see that we've got a number of advisory services I think one of the big things that we could get called out from customers is that there's a skills gap in operationalizing and and putting AI and ml workloads into production as well as you know we are a thought leader and have quite a bit of research with HP Labs on memory driven computing Gen Z and being able to squit you know scale those workloads within the enterprise so those are things that we're building off of in addition to some pretty high-profile and very valuable software acquisitions first and last year first around blue data which we talked about today in the context of ml ops and then most recently map R which is a very powerful scaleable persistent data layer for analytics so for us it's AI is a is a very is a top priority for us at HPE it's part of our corporate narrative and helping customers along that maturity curve is definitely where we're focused on great so how are HP and its partners helping customers along their journey that they're going on with AI yes so I think at the end of the day HP is very focused on our customers especially from a go-to markets perspective so we are we're in the phase now where we're helping customers not just explore but to operationalize AI and ml so whether it's cookbooks and our a specific products like machine learning operations which helps you scale from you know a data scientist or a danger engineer developing an algorithm on you know laptop to be able to running that at scale in the data center so for us that journey is is very important especially around the the outcome from the technology perspective technology partner perspective we have a number of really high profile and new relationships that were building for this new ecosystem around AI and ml and DL and so folks like data iku h2o on the hardware side Intel and NVIDIA we are bringing that to our customers to provide you know a complete solution so being able to take those ISVs and run them and containerized stateful you know deployment and then be able to you know partner with all of our hardware vendors and software vendors and then for the channel we feel that this is a huge you know this is like this is a great opportunity for them to certainly move up stack in how they talk to customers about their business outcomes so I think it's part of a three prong strategy and we're really kind of focused on those key areas yeah no doubt an area that's getting attention from all sectors of the marketplace so those that are watching HPE what should we be expecting to look to see from them in the form near future yeah so I think you know from our perspective we've got a number of releases that are coming up over the next year and pretty excited about that in addition to machine learning operations I think that the world you know will continue to be moving towards containers for more than just stateless applications we're starting now with AI and ml and I think there's a big you know future for other applications whether they're cloud native or you know those applications are refactored certainly living within a world of kubernetes right is becoming more of a reality from a deployment perspective so you know for us we're very you know focused on the customer outcome I think the other area too is that that HP has been very famous for lately is around consumption based services right so we're able to bring that vetted ecosystem the containerized deployment model and platform this the your accelerators compute networking and storage and even a persistent data layer and even you know even the the cloud experience to the customer as a biz outcome in a consumption experience their Green Lake is something that you know we think is very valuable for our customers all right well thank you patrick for helping us to put all of that into context Peter I'm going to send it back to you for the wrap

>> Announcer: Live, from downtown San Francisco, it's theCUBE covering IBM Chief Data Officer Strategy Summit 2018, brought to you by IBM. >> We're back at the IBM CDO Strategy Summit in San Francisco, we're at the Parc 55, you're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante, and I'm here with Krishna Venkatraman, who is with IBM, he's the Vice President of Data Science and Data Governance. Krishna, thanks for coming on. >> Thank you, thank you for this opportunity. >> Oh, you're very welcome. So, let's start with your role. Your passion is really creating value from data, that's something you told me off-camera. That's a good passion to have these days. So what's your role at IBM? >> So I work for Inderpal, who's GCDO. He's the CDO for the company, and I joined IBM about a year ago, and what I was intrigued by when I talked to him early on was, you know, IBM has so many assets, it's got a huge history and legacy of technology, enormous, copious amounts of data, but most importantly, it also has a lot of experience helping customers solve problems at enterprise scale. And in my career, I started at HP Labs many, many years ago, I've been in a few startups, most recently before I joined IBM, I was at On Deck. What I've always found is that it's very hard to extract information and insights from data unless you have the end-to-end pieces in place, and when I was at On Deck, we built all of it from scratch, and I thought this would be a great opportunity to come to IBM, leverage all that great history and legacy and skill to build something that would allow data to almost be taken for granted. So, in a sense, a company doesn't have to think about the pain of getting value extracted from data, they could just say, you know, I trust data just as I trust the other things in life, like when I go buy a book, I know all the backend stuff is done for me, I can trust the product I get. And I was interested in that, and that's the role that Inderpal offered to me. >> So the opposite of On Deck, really. On Deck was kind of a blank sheet of paper, right? And so now you have a complex organization, as Inderpal was describing this morning, so big challenge. Ginni Rometty at IBM Think talked about incumbent disruptors, so that's essentially what IBM is, right? >> Exactly, exactly. The fact is IBM has a history and a culture of making their customers successful, so they understand business problems really well. They have a huge legacy in innovation around technology, and I think now is the right time to put all of those pieces together, right? To string together a lifecycle for how data can work for you, so when you embark on a data project, it doesn't have to take six months, it could be done in two or three days, because you've cobbled together how to manage data at the backend, you've got the data science and the data science lifecycle worked out, and you know how to deploy it into a business process, because you understand the business process really well. And I think, you know, those are the mismatches that I've seen happen over and over again, data isn't ready for the application of machine learning, the machine learning model really isn't well-suited to the eventual environment in which it's deployed, but I think IBM has all of that expertise, and I feel like it's an opportunity for us to tie that together. >> And everybody's trying to get, I often say, get digital right, you know, your customers, your clients, everyone talks about digital transformation, but it's really all about the data, isn't it? Getting the data right. >> Getting the data right, that's where it starts. Tomorrow, I'm doing a panel on trust, you know, we can talk about the CDO and all the great things that are happening and extracting value, but unless you have trust at the beginning and you're doing good data governance, and you're able to understand your data, all of the rest will never happen. >> But you have to have both, alright? Because if you have trust without the data value, then okay. And you do see a lot of organizations just focusing, maybe over-rotating on that privacy and trust and security, for good reason, how do you balance that information as an asset versus liability equation? Because you're trying to get value out of it, and at the same time, you're trying to protect your organization. >> Yeah. I think it's a virtuous cycle, I think they build on each other. If customers trust you with their data, they're going to give you more of it, because they know you're going to use it responsibly, and I think that's a very positive thing, so I actually look at privacy and trust as enablers to create value, rather than somehow they're in competition. >> Not a zero-sum game. >> Not at all. >> Let's talk some more about that, I mean, when you think about it, because I've heard this before, GDPR comes up. Hey, we can turn GDPR into an opportunity, it's not just this onerous, even though it is, regulatory imposition, so maybe some examples or maybe talk through how organizations can take the privacy and trust part of the equation and turn it into value. >> So very simply, what does GDPR promise, right? It's restoring the fundamental rights of data subjects, in terms of their ownership of their data and the processing of their data and the ability to know how that data is used at any point in time. Now imagine if you're a data scientist and you could, for a problem that you're trying to solve, have the same kind of guarantees. You know all about the data, you know where it resides, you know exactly what it contains. They're very similar, you know? They both are asking for the same type of information. So, in a sense, if you solve the GDPR problem well, you have to really understand your data assets very well, and you have to have it governed really well, which is exactly the same need for data scientists. So, in a way, I seem them as, you know, they're twins, separated at some point, but... >> What's interesting, too, is you think about, we were sort of talking about this off-camera, but now, you're one step away from going to a user or customer and saying here, here's your data, do what you like with it. Now okay, in the one case, GDPR, you control it, sort of. But the other is if you want to monetize your own data, why pay the search company for clicking on an ad? Why not monetize your own data based on your reputation or do you see a day where consumers will actually be able to own, truly own their own data? >> I think, as a consumer, as well as a data professional, I think that the technologies are falling into place for that model to possibly become real. So if you have something that's very valuable that other people want, there should be a way for you to get some remuneration for that, right? And maybe it's something like a blockchain. You contribute your data and then when that data is used, you get some little piece of it as your reward for that. I don't know, I think it's possible, I haven't really... >> Nirvana. I wonder if we can talk about disruption, nobody talks about that, we haven't had a ton of conversations here about disruption, it seems to be more applying disciplines to create data value, but coming from the financial services industry, there's an industry that really hasn't been highly disrupted, you know, On Deck, in a way, was trying to disrupt. Healthcare is another one that hasn't been disrupted. Aerospace really hasn't been disrupted. Other industries like publishing, music, taxis, hotels have been disrupted. The premise is, it's the data that enables that disruption. Thoughts on disruption from the standpoint of your clients and how you're helping them become incumbent disruptors? >> I think sometimes disruption happens and then you look back and you say, that was disrupted after all, and you don't notice it when it happens, so even if I look at financial services and I look at small business lending, the expectations of businesses have changed on how they would access capital in that case. Even though the early providers of that service may not be the ones who win in the end, that's a different matter, so I think the idea that, you know, and I feel like this confluence of technologies, where's there's blockchain or quantum computing or even regulation that's coming in, that's sort of forcing certain types of activities around cleaning up data, they're all happening simultaneously. I think we will see certain industries and certain processes transform dramatically. >> Orange Bank was an example that came up this morning, an all-digital bank, you can't call them, right? You can't walk into their branch. You think banks will lose control of the payment systems? They've always done a pretty good job of hanging onto them, but... >> I don't know. I think, ultimately, customers are going to go to institutions they trust, so it's all going to end up with, do you trust the entity you've given your precious commodities to, right? Your data, your information, I think companies that really take that seriously and not take it as a burden are the ones who are going to find that customers are going to reach out to them. So it's more about not necessarily whether banks are going to lose control or whether... Which banks are going to win, is the way I would look at it. >> Maybe the existing banks might get trouble, but there's so many different interesting disruption scenarios, I mean, you think about Watson in healthcare, maybe we're at the point already where machines can make better diagnoses than doctors. You think about retail, and certain retail won't go away, obviously grocery and maybe high-end luxury malls won't go away, but you wonder about the future of retail as a result of this data disruption. Your thoughts? >> On retail? I do feel like, because the data is getting more, people are going to have more access to their own information, it will lead to a change in business models in certain cases. And the friction or the forces that used to keep customers with certain businesses may dissolve, so if you don't have friction, then it's going to end up with value and loyalty and service, and those are the ones I think that will thrive. >> Client comes to you, says, Krishna, I'm really struggling with my overall data strategy, my data platform, governance, skills, all the things that Inderpal talked about this morning, where do I start? >> I would start with making sure that the client has really thought about the questions they need answered. What is it that you really want to answer with data, or it doesn't even have to be with data, for the business, with its strategy, with its tactics, there have to be a set of questions framed up that are truly important to that business. And then starting from there, you can say, you know, let's slow it down and see what technologies, what types of data will help support answering those questions. So there has to be an overarching value proposition that you're trying to solve for. And I see, you know, that's why when, the way we work in our organization is, we look at use cases as a way to drive the technology adoption. What are the big business processes you are trying to transform, what's the value you expect to create, so we have a very robust discovery process where we ask people to answer those types of questions, we help them with it. We ask them to think through what they would do if they had the perfect answer, how they will implement it, how they will measure it. And then we start working on the technology. I often think technology is an easier question to answer once you know what you want to ask. >> Totally. Is that how you spend your time, mostly working with the lines of business, trying to help them sort of answer those questions? >> That is one part of my charter. So my charter involves basically four areas, the first is data governance, just making sure that we are creating all the tools and processes so that we can guarantee that when data is used, it is trusted, it is certified, and that it's always going to be reliable. The second piece is building up a real data competency and data science competency in the organization, so we know how to use data for different types of business value, and then the third is actually taking these client engagements internally and making sure that they are successful. So our model is what we call co-creation. We ask business teams to contribute their own resources. Data engineers, data scientists, business experts. We contribute specialized skills as well. And so we're jointly in the game together, right? So that's the third piece. And the last piece is, we're building out this platform that Inderpal showed this morning, that platform needs product management, so we are also working on, what are the fundamental pieces of functionality we want in the platform, and how do we make sure they're on the roadmap and they're prioritized in the right way. >> Excellent. Well, Krishna, thanks very much for coming to theCUBE, it was a pleasure meeting you. >> Thanks. >> Alright, keep it right there everybody, we'll be back with our next guest. You're watching theCUBE live from IBM CDO Summit in San Francisco. We'll be right back. (funky electronic music) (phone dialing)

>> Narrator: Live from Madrid, Spain, it's theCUBE, covering HPE Discover Madrid 2017, brought to you by Hewlett Packard Enterprise. >> Welcome back to Madrid, Spain, everybody. This is theCUBE, the leader in live tech coverage, and this is day two of our exclusive coverage of HPE Discover 2017. I'm Dave Vellante with my co-host Peter Burris. Last night was a great night of customer meetings. We stumbled into the CIO meeting, we were at the-- >> And were quickly ushered out. (both laugh) >> We were at the analyst event, and of course we met our good friend Dr. Tom Bradicich at the analyst meeting. This is the man who brought a lot of the IOT Initiative into HPE. He's the general manager of the IOT and Systems division. Great to see you again, Dr. Tom. Thanks so much for coming on. >> Thank you Dave and Peter, it's great to be here at theCUBE, great to be here at HPE Discover Madrid. Lots of great things happening, I can't wait to tell you about 'em. >> So we're very excited to have you on. John Furg and I interviewed you in the very early days after you came over from your previous company, and you had this sort of vision of, you know, bringing the HPE into the intelligent edge. >> Yes. >> And we're like okay, this sounds really complicated. You got ecosystem, you got all kinds of technologies that you gotta develop. Hardware, software. And you're making it happen. It's become a meaningful portion of HPE's business, so I know you got a long way to go, but congratulations on the progress so far. >> Thank you. Give us the update on the-- >> Well, first of all, thank you for that, I appreciate it. I must give credit to my team, I tell them all the time that if you don't execute and do the work, I'm just a science fiction writer. (interviewers laugh) And the vision has come about, and we have real customer deployments of course that the, you know, the proof of it. >> Right. >> At first we had no products and no customers, now we have these products that we'll talk about, and we have the customer deployments, and we're changing things for businesses at the edge, and again the edge is just not the data center. And the manufacturing floor, we'll talk about refineries, oil rigs, those type of edges. We're doing a lot of work there. And it's been exciting to see the ideas that we have get adopted by not only customers, but the industry, so we're seeing other analysts pick up on two dimensions: computing at the edge, and a little more complicated one, a little more difficult to grasp, is converged OT and IT at the edge, the two worlds of operational technology converging with IT. We were on theCUBE talking with an OT partner, National Instruments, a long while ago, and now we literally have those products in the market in the hands of customers. National Instruments is reselling the Edgeline 1000, the Edgeline 4000 products, as well as of course us selling it, and it's pretty exciting to see this happening. >> Well what I love about that conversation is, you know, when we first started to talk to you, we said okay, let's play the skeptic, analysts are skeptic. >> Sure. >> And we said one of the big problems you're gonna face is bringing the organizations together, OT and IT. They're just different worlds, oil and water, you know, you got hardcore engineers and you got IT guys, and then subsequent to that conversation, you bring on National Instrument, right? >> Yes. >> And we have that conversation. Okay, so we sit down, I check that box, at least they're having conversations. Can you talk about how that convergence is actually occurring, and what's in it for the customer? >> Well great. To talk about this convergence, the best thing to do is say it can happen at several levels. It can happen at a solutions level, it can happen at a software level and a hardware, physical level. Let's talk about a physical level, it's a little more tangible to understand. Let me use the smartphone, which everybody has. Like Peter, you have one there. If you hold that up, you will notice inside the manufacturer of that phone converged, or integrated, those are synonyms, many consumer devices. Such as what? A music player, of course, the phone, of course. But also many other things. A GPS system. >> Camera. >> A camera. The list goes on, right? We can go on. Oh, the flashlight, and by the way, your wallet. Maybe not your wallet, but a millennial and younger's wallet-- >> Yeah, sure. >> Is in that phone. >> My wallet's in it. >> My wallet's in it. >> In it, and-- >> Venmo, baby. >> That's right. (all laugh) >> I have my kids' wallets in there too. >> Oh that's great, you've done that switch. So what is happening there obviously is the notion of we're, you know, software defining and we're converging. Now the benefits of that are irrefutable. One thing you buy, it's less energy. One thing to manage, the convenience of carrying it around. Let's take that metaphor and impute it at, let me say a manufacturing floor edge. There's lots of edges out there. We go to a manufacturing floor edge, we see several devices, just like the early pioneers of the smartphone saw a consumer with a camera around his neck, a GPS on his belt, text, right, a flashlight, a wallet, and all this. We see all these devices out there, and what are they? Some of 'em are OT, as you mentioned. Operational technology devices such as control systems, such as data acquisition systems. >> Real-time systems. >> Real-time systems, industrial networks. CAN, PROFIBUS, SCADA solutions and networks. And the second thing we see is some IT. Most of it's closed, so this is important. It's good IT, meaning computing and storage, but a lot of it is closed systems. It's not the open EXEDY 6 architecture that we so enjoy in the data center. So those things are out there. We looked at 'em and we put them all in one box, just like the smartphone is one device. What are the benefits? Lower space, there's not a lot of space at the edge. Lower energy, there's not a lot of energy, right, at the edge. But the more profound benefits that we're seeing, and we have a large auto manufacturer who has deployed this on their manufacturing line, is it keeps uptime higher. In other words, it reduces downtime. So if the manufacturing line stops, there's nothing worse than a manufacturing line stopped, except perhaps an empty one. But the point is, when a manufacturing line stops, you can't put out product. You can't put out product, you can't recognize revenue get it in the consumer's hands. It's very obvious. It's an air-tight business case, actually. So we're able to reduce any downtime, why? Because first of all, everything's together, and secondly, we're able to manage it just like we're managing the data center because it's an open EXEDY 6 architecture. >> So you're converging tasks as well as hardware. >> As well as hardware, and then the next step is software, you know, as well. We just launched a new class of software called the Edgeline Services Platform, and this is OT software. So we're talking OT functions like aggregators and things that do OT technologies and some IT, but because we have so much compute power and it's open, it's EXEDY 6, it can run software like VMware, Microsoft Products, even database products as well. But because we have that, we're able to software define. When you software define, and I'll use the wallet again. You don't have a billfold with your license anymore. Plastic and leather has been software defined, and therefore it's less to deal with. It's much more efficient. So that announcement of our software strategy along now with our hardware strategy is very exciting for us, and customers are very much interested in it. >> So do you have some examples, you know, some real world examples? Customers that you can talk about where you're bringing together OT and IT disciplines? >> Yeah, you bet. Yeah, you bet. Let me talk about a large global beverage and snack company, and they make snacks, and in this case, potato chips. So a potato chip is a product, and the idea of having them come out of the line in the bag and be a higher quality is important. So we took an Edgeline System, the EL 1000, and we put it at the edge, and we were able to software define several of their IT and OT components and get it to a consolidation and integration in one box. Now what that did is it allowed the, and will do, is allowed the foods to move faster. So if they move across the conveyor belt faster, you can bag them faster, get 'em out to the consumer. The second thing is because it's so powerful, this is interesting. Now they can use video cameras to inspect the quality. Now think about that. That's not necessarily a new idea, but what is new is the notion that you can take video, which I think you'd agree is the largest data, is that right? A video is big, big data. >> We know that well. >> Especially if it's high, Yeah, especially if it's higher resolution, and your hosting costs are telling you that as well, right? Of all these videos. But if it's high resolution, and because you're looking for, you know, defects, indeed, one has to process that not only in high resolution, massive data, number one. Number two, quickly, because the thing is moving, and you wanna know to knock it off or stop or whatever the case may be. So what has happened there is my team and I did not think of that. Our customers thought that, well because you gave us this platform, we can now enhance it with a new type of sensor called a camera, with a new type of data, called video, to enhance our quality and keep our process moving faster. >> So keeping this converged notion going, you're converging the hardware, which is, you know, important. You're converging a lot of the administrative tasks. >> Yes. >> Which reduces the likelihood of any single human failure bringing the whole system down, but now you're talking about, in the whole sense, infer, and act loop that typifies what happens at the edge, you're converging new technologies into that loop by being able to add new data type, bring modeling, machine learning, analytics, in the infer, and then being able to act right there, which allows you to think about new invention, new innovation very, very rapidly because you have the processing power to converge all that new function as it becomes better understood. Have I got that right? >> You got it right. I serve as an adjunct professor at university, so let me position it in an easy way to learn. You said sense, infer, and act. Let's just call 'em the three A's. Acquire, analyze, and act. >> Okay. >> It's just easier to remember. And let me talk to that too, but this is actually just synonyms. So the acquisition of the data is through sensors in D to A conversion, or let me say A to D, analog to digital. Because most of these phenomenon, video for example, it has to be, is a light phenomenon. Moisture, pressure. At Duke Energy, for example, the second largest energy provider I worked on that industrial internet of things solution, and vibration was the thing that needed to be acquired and then analog to digital. Now the analysis has to take place. There are seven reasons to analyze at the edge. There are seven reasons not to send the data to the cloud. In the past, we have talked about it. One of them's latency, one of them's cost, one of them's bandwidth, another one is security, another one is reliability, another one is geofencing and policy, another one is duplication and security, you know, hostile or just, you know, reliability drop packets. There's a lot of issues to do that analysis there. But because we have a non-compromised full EXEDY 6, in fact, 64 in one box. 64 Xeon, Intel Xeon product in one box. We don't have to compromise the stack. We can take it directly out of the data center and run things like artificial intelligence, machine learning algorithms. We can virtualize, we can containerize, we can run Citrix applications at the edge to have better access to the data and of course the application. But you're absolutely right, and then the second thing in this point is we move from the middle A, analysis right, to the action. The reason, I've learned this doing many IOT deployments. The reason people do an IOT deployment is to act. Yes, it's exciting to collect data. It's also exciting to analyze it. But have you ever been in a business meeting where you sit and you analyze data and you give tremendous insights, and one conclusion is pit against another conclusion and it cancels out all conclusiveness, and then you talk and you analyze, and you walk out and nothing happens, there's no action. Many of us have been in that. That's the idea here. You can't stop at the analysis, even though artificial intelligence, deep algorithms, moving averages, signatures that we can compare are very powerful. Well, what do you do when you do that? Because we have control and actuation systems built into Edgeline, we literally in a physically space, as well as in a logical process, as you pointed out, close that loop. >> Right. >> Acquire, analyze, act, acquire, analyze, act. Yes, connect to the cloud or the data center if we need to, but the issue is you don't have to. Now here's what's profound about that. This system at the edge can be managed and run the same stacks as any cloud or data center. I'm gonna use those as synonyms because a cloud is just a data center that nobody's supposed to know where it is. So a data center far away on the corporate campus or in a public or private cloud somewhere, is managed the same way. When that happens, we are revolutionizing workload management. Now, I spent a lot of years in my former time in IT and building data centers and building some of the first clouds, workload management's a big deal. How do you shift the workload to the free server? >> Peter: Right. >> Or to the free resources, right? To optimize, obviously. And it's a packing problem many times in the data center. Well now we've introduced another place to workload manage. >> Right. >> It's called the edge, it's far away. So we workload managed in the data center, then the cloud was invented, that's the first off premises. The next off premises is now the edge. So the other off premise is the edge. So now we have a workload management capability. Do you wanna do 100% processing at the edge where the action is, and where the acquisition is? Do you wanna do 100% in the cloud? That's still possible. Do you wanna do 50-50? Would you like to do 10-90? Would you like to do 30-70? You get my point. >> Totally. >> I can shift this, and depending on the season, depending on issues like disaster recovery, depending on your workloads, you can now do that, and again, you can do this with the Edgeline 1000, the Edgeline 4000, because of the processing power and the converged OT inside it. >> Well our observation is that it's not about bringing your business to the cloud, it's about bringing the cloud to your business. >> Yes. >> So bringing that sense of workload management. You know, you might say the cloud is just a virtualized data center when you come right down to it. So bringing all those capabilities and bringing them to wherever the data requires it. And there's gonna be a lot of instances where the data is gonna be at the edge, stay at the edge, but that doesn't mean you don't want all the benefits of how you run computing data at the edge where that data is. >> Yeah, and we're not obviating, we're offering choice. >> Right. >> But again, there are seven reason I went over why you do it here, but I've had a customer say none of those seven matter. So okay, we send everything to the cloud, and we have great cloud hybrid IT products that do that. >> Yeah. >> And we've envisioned a three-tier data model, you know, real time at the edge. >> Yes. >> Maybe you don't persist everything, but like you said, there are a lot of reasons not to move all the data back. But there is maybe a spot where you aggregate some of that data from discrete devices, and sure, if you wanna do some deep modeling in the cloud, go for it. And that cloud might be the public cloud, it might be your own private cloud. Does that seem reasonable to you? >> Very reasonable, and another reason for a cloud is it's an aggregation point for other, in this case, manufacturing lines where other smart cities to come together, because you're not gonna connect every city, every plant, any to any. You'll have a hub and spoke model where the cloud serves as that hub. So there are always reasons, and that's why, you know, if you look at our company, the pillars of our company, Pointnext services, the second pillar is hybrid IT, primarily focused on cloud and data centers, and the third is the intelligent edge. And those all play very, very closely together, in fact we have edge to core strategies, we have edge to core offerings with partners like NVIDEA, with partners like SAP, with partners like SAS, we have edge to core. For example, Schneider as well, Schneider Electric. All of them are looking at this idea, GE, Microsoft Azure, let's go to the edge. And two years ago, that was not the case, right? Let's go there, when you go to the edge, what are you gonna run it on? Well, let's not force our software partners to re-architect like they used to have to to run at the edge, which is like I'd call that drive-by analytics. You just have to cut out everything because it only ran on a wimpy core somewhere or a little device. No, let's move the entire data center capability out to the edge, when I was presenting this to one of our partners, the CEO of the company, I was presenting this vision, and he was texting during my talk 'cause I was boring. (interviewers laugh) And then I said this, this is a very powerful company, I won't mention names. Then I said, we're gonna move data center class technology out to the edge. It's not gonna be in compromised cores or limited memory or a little bit of storage. It's the very things in the data center we'll harden called Edgeline. We'll add controls systems and data acquisition, we'll put it out at the edge. He stopped texting. Then he looked up at me and said, "Wow, you're really moving a data center out to the edge." and you just said that, right? It's the cloud is coming. It's almost a reverse idea of what was happening before. >> Well you wrote a blog recently. >> Yes. >> About the space edge. So I wanted to ask you about that. What's going on in the space, and that's the ultimate edge, I guess. >> The infinite edge. >> The infinite edge. Explain what you guys are doing there and why it's important. >> Well, this is exciting. Space travel for exploration and eventually colonization, if you would believe that, is happening. We have the first supercomputer technology in a NASA spaceship now. It has orbited the Earth well over 1,000 times and it is doing thousands of benchmarks and is doing very well, isn't failing. Now, why is that profound? Because again, that edge is so far away and the ability to push that back to Earth now, which we could call the data centers on Earth, is limited. It takes minutes, sometimes even longer. There's issues with reliability as well. So we were able to do that, and then we've created a new thing called Project Extreme Edge, where we're going to build Edgeline systems that will fit better with lower energy, smaller size in spaceships, and eventually in colonization, but we're just going into space travel and exploration right now. And I'd like to mention that HP Labs is a great participant in this because they're working on a technology, and the name of it is called the Dot-Product Engine. And dot-product is a mathematical operation needed in high-performance computing and artificial intelligence. But we're able to use that technology because it's small, it's fast, faster than we believe anything else on the market, and also it has a low energy profile. And those are all any edge, obviously, but it's also great for the space edge, and I like to quote Frank Sinatra when he said if I can make it there, I can make it anywhere, New York, New York. (laughs) Well, if we can make it in the space edge, these Earth edges will benefit as well. Some of the same challenges. >> All right, we're out of time, but I gotta ask you. Meg stopped by yesterday, and was giving great support for the intelligence. >> She has, yes. >> The company's now reporting the intelligent edge is gonna be one of the main areas. What about the new guy? Antonio. >> Antonio Neri. >> You know, what's your relationship with him, experience? Has he been focused on this area? >> Support? >> He's been great, he supports in three ways, let me just sum up in three ways. Number one, he supports in customer visits. He and I have been on customer visits together, it's always wonderful to have the president and now the new CEO with you affirming what we're doing. That's number one of three, number two of three, he supports the work we're doing with our new global IoT innovation labs, in fact our first grand opening, the first one in Houston, we will have one in Singapore opening in February, and then we'll have one in Europe and perhaps one in India, we're opening these labs for innovation, but my point is, the one in Houston, our first grand opening, Antonio Neri came personally and did the ribbon cutting and sponsored that as well. And then third, he is of course funding my business unit, and he's been very, very supportive and I'm really happy that he's staying with us and he'll be CEO. >> Excellent, Dr. Tom, thanks so much for coming on theCUBE. Congratulations, as you say, I know there's a long way to go, but looks like you're off to a great start and have some real traction. >> Tom: Thank you very much. >> So we appreciate your time and your insights. Okay, keep it right there buddy, we'll be back with our next guest. This is theCUBE, we're live from Madrid. Be right back. (upbeat electronic music)

>> Announcer: Live from Las Vegas it's The Cube covering HPE Discover 2017 brought to you by Hewlett Packard Enterprise. (electronic music) >> Welcome back everyone, we're live here in Las Vegas for HPE, Hewlett Packard Enterprise, Discover 2017 SiliconAngle Media's program The Cube where we go out to the events and extract the signal from the noise. I'm John Furrier, my co-host Dave Vellante, my Co-CEO and Co-Founder SiliconAngle Media which is part of siliconangle.com, The Cube, SiliconAngle.tv, thecube.net, and wikibon.com. Go to wikibon.com and seek out all the great research, and a lot of the stuff they're talking about here at HPE Discover has a lot to do with what's happening at Wikibon and around big data and IoT. Dave, summary of day one wrap-up, kind of our take if you will on HPE's messaging, what they're showing and the debate. We were at Dell EMC World. We heard Michael Dell and his team say bigger is better. HP is saying agile, nimble, but they've got a confederation, federation, all these little kind of HP companies. It's still a conglomerate. It's not small, as you said in our opening. Meg's keynote today was all about the future of computing in a new way, if you will, data, IoT center of it. Your thoughts and analysis of day one keynote, our guests, your thoughts. >> John, I opened up this morning's segment saying that five years ago we talked on The Cube about, and I made the statement, HP's got to shrink to grow. The other thing I said about HP, now HPE, was it's got to get back to its roots of invent, and it has not gotten back to those roots, and now it is reinventing itself, and it's opportunity to get back to its roots of invention is through a partner ecosystem. That's very clear, kind of point number one. The second point I want to make is that these transformations that HPE and companies have gone through, I mean I've never seen anything this large, splitting a company up of 100 billion dollar company, changing all the IT systems, doing all these spin merges, these are not trivial exercises. So when Meg says we're sort of at the end of that transformation, that five year process, in many respects they've now got to create a new transformation. They finally got this, they have this smaller company that's more focused, and they've really got to still sharpen the edges on that sword in my opinion. The software business is still part of HPE, so that's got to happen. The cash coming in from the CSC spin-merge still has to come in, so the balance sheet is still being restructured. But essentially the message that you're hearing from HP is we're going to help you keep the lights on. We're going to make hybrid IT simple which is a good sort of tagline, but it's a very, again, nontrivial thing to do. We've got this new partner ethos, and we've got this fourth piece which is a moonshot on IoT, and that's our big growth opportunity, and we're going to put all our muscle behind that. I like the strategy. I mean if you're going to go smaller and more focused, you've got to have some kind of moonshot like that. You've got to have a partner ecosystem as they've described, but as I say, there's still some more work to be done. They're still shaking off the embers of the exit of the cloud business, trying to reshape that whole thing, so there's, as I say, more work to be done. >> You know it's interesting, good points, I agree 100%. I would add that my observation and what I came into HPE looking at was what will leadership, and specifically Meg Whitman and Antonio Neri, mainly Meg Whitman, and the team articulate to the customers, because they've been getting pounded in the press on financial performance, the journey. I mean if I'm Meg Whitman, I got to be saying hey, enough with the backbiting on, the five-year journey and trying to peg me to a milestone, because the market's changing. You go back five years and say oh, it's going to be a five year journey, let's say Meg Whitman says that. What that really means is that's just kind of an estimate, based on her opinion execute but what I think, well, she mighta seen but what happened was: the cloud just came in and completely decimated the landscape relative to disruption opportunity so a five-year journey, pegged at that time, becomes essentially maybe longer. And so they're executing a turbulent marketplace that's good for them but it could be wind at their back too. So I think they had to come out and talk to their customers. The customers need to hear from HP, and saying, "Look, we got your back. "We're going to be delivering. "We understand the transformation. "We understand what's going on." They've been in the IT consumption business, serving customers in IT. They're a big company. They got to calm the customers down and give them confidence. So to me, I saw confidence in the simplicity message, hybrid IT message, and the IoT with the headroom. I didn't see any game-changing, futuristic, vapor. I didn't see a lot of AI washing, I didn't see a lot of machine learning, which is, I think we're seeing the trend. But they didn't lead with that. They led with the meat and potatoes of HP: Storage, talking about the acquisitions: Simplicity.. >> Dave: Services.. >> Nimble, the messaging with partners, I thought that's very much a meat-and-potatoes, it wasn't like a lights-out keynote by Meg Whitman in the sense of standing ovation on, yeah rah-rah. But it was meat-and-potatoes, aggressive, assertive, "we're here for the long haul" and I thought that was positive. >> I think the partner-friendly ethos is really, really important, and you see it around the show, I mean look at, Veeam is a Platinum Sponsor, right? That never would've happened two years ago because of HP Protector, HP's backup software. Never would've happened before. You see Fortunet out in the show, basically a competitor with HP, HP's security business. And then this whole new partnership around the large SI's, right, I mean that's a big deal. You were saying "India, SI's." The CEO of Wipro, standing up today, I thought he was one of the more impressive parts of the keynote. So, a much more aggressive posture with partnerships, a much cleaner story for partners. Yesterday, the partner conference got pretty high marks. People, I think, are fairly excited about that, because HP has got enough muscle to put resources in, and John you know. What's your take on the whole channel and partnership thing? I mean, you lived that for a decade. >> Well, I mean, I think the channel thing is a great opportunity for them. It's about making money together and I think that's going to be a key thing. My thoughts, just from trying to read the tea leaves, and I'm going to put this out there, it's, I would say, not half-baked but my observation from today, and in the interviews, things came together for me around something that I was thinking about but I could see it now with a little bit of a clarity, and that is I think we're going to see a hardware renaissance. And what I mean by that is, I think the message of computing is changing. We've been predicting, with Open Compute, that we've been covering, which is an open source project, where Facebook and now others are donating reference and imitations after which, Antonio Neri was supporting that project. It's not a lot of funding, there's a lot of open source projects going on. There's a lot of disruption happening. It's almost just like, small little, not real well-reported marketplace. Not a lot of money's being made yet, cuz there's some new things happening. I think, what's clear to me today is that a new business model of hardware is coming. And I think HP, if smart, could change their business model. Instead of being a hardware box supplier, which they know is a declining market, to a TAM, a Total Addressable Market, true private cloud, of $260 billion, and be a supplier of hardware business model, rather than hardware product, where they bring their systems expertise in, use open source, bring the stuff out of HP Labs, and not try to be hardcore about productising it in a hardcore way, meaning another SKU. I think they got to have some core products, but the growth, I think's going to come from a hardware renaissance, where a new developer's going to come out of hardware, you're going to start to see hardware being in the game. Just last week at the Recode Conference, you had Steve Ballmer with Kara Swisher, saying "We should have got in the hardware business a long time ago. Everyone's making their own phones," in reference to the consumer market. So, I think the enterprise market, you're going to see real opportunity around service providers and enterprises, essentially getting the best of what Amazon and Google does, which is build their own boxes, in a new hardware development way. That, to me, is absolutely clear and I think that's going to open up, essentially, that long tail of compute. Cloud-like, true private cloud, and hybrid. And I think if HP's smart, they should jump on that and double down on that trend. >> So, the things I'm looking for between, say now and the next Discover in Madrid in December. The post-spin-merge balance sheet. Let's take a look at that, 'cause I think it's going to look a lot better. And that's going to cause people to go "Whoa, look at that, now HP's got even more leverage "to go out and do deals." The second is, when does IoT actually become a meaningful and measurable component of HPE's business? Talking a lot about it, building up the ecosystem, talking about some use cases, a lot of blue-sky types of things, but not a lot of hardcore, concrete examples at the customer level. So when does that become a meaningful revenue generator? And then, I think from credibility's standpoint, margins. Meg said, "This is it, margins have bottomed. "They're going to bounce off the bottom "and grow from here." We've got to see that, and I think the keys are services, really executing on the services side, leveraging their acquisitions, let's see what they can do with, I mean Aruba looks good, Nimble, SimpliVity. Can they turn those into billion dollar businesses like they did with 3Par? And then the partnerships, I don't expect any head-fakes, you remember HP used to always head-fake the channel and head-fake the partnerships. I don't expect that now. >> They've never had fake partners. Partners would call them out on the carpet on that. I think they have been groping with the partners, and hoping to have a flagship. >> Dave: I dunno, I mean.. >> I don't think they've, now you're trying to be critical of HP, but they've never had fake partners. >> When they, say head-fake. They would buy a company like EDS, and their partners Ecosystem would go "Whoa, wait a minute, I'm not sure "I want to partner with these guys." >> I'd debate that with you, but I think HP's always had great partnerships. I think where they've misfired, if you want to be critical, is that they mismatched where the growth was, with throwing an outsource for instance, that's a complete mismatch to where the growth is. Now, to your point about IoT, I think that's their big opportunity because IoT is a beachhead setup. I think it's a great opportunity as a flagship message to take the portfolio of HP into a partner-friendly world that's going beyond swim lanes, this is like the Grand Canyon, the Panama Canal. And none of them more than swim lanes. So I think having the portfolio with more M&A activity, with Aruba and some of the hardware they have, they can go in and get the beachhead in IoT and use that as a driver, a flagship with their partnerships to start engaging customers and holding the ground. And then, moving the services in, that could hold them for a good couple years. And then, as the margins shift from the declining hardware business, I think that's an opportunity, and we're going to look at that. >> And the other big opportunity, beyond IoT, is this intercloud management. Will HP participate in earnest in building up some software capabilities to manage cross-cloud? On-prem, off-prem, everything in between, Sass, et cetera. You don't hear anything about that now. So is that part of the HPE strategy? Will it use its new balance sheet to go after some of those emerging software companies, and rebuild its software business? >> Well, we always will analyze. We've got all day tomorrow. We've got some great guests. But Dave, Information Technology, known as IT, is not going away. It's changing, certainly, for sure. Information and technology's really going to be a great opportunity for HP. If they stick in their old ways, they'll be dead. If they can transform over themselves, I think it's a winner. Of course we've got live coverage, three days, tomorrow and Thursday This is theCUBE. Go to SiliconAngle.com, check out all the latest reporting and journalism. Go to Wikibon.com for all the great research. The best research is behind a subscription. You got to pay for that, I would definitely do that. The true private cloud report you guys did, I thought was killer, really that's groundbreaking, and IoT stuff's fantastic. Of course, go to SiliconAngle.tv to check out all the great stuff. And of course, go to CrowdChat.net, and we have a new CUBE 365 product coming out of the oven from SiliconAngle labs, lot of great stuff. Stay with us for more coverage tomorrow and check out YouTube.com/SiliconAngle for all the videos in replay. We'll be back tomorrow, stay with us. Have a great day. (electronic music)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering HPE Discover 2017. Brought to you by Hewlett-Packard Enterprise. >> Okay, welcome back everyone. We're here live in Las Vegas for HPE, Hewlett-Packard Enterprise, Discover 2017. I'm John Furrier, co-host of theCUBE with Dave Vellante, and our next guest is Bill Philbin, who's the general manager of storage and big data for Hewlett-Packard Enterprise. Bill, welcome to theCUBE. Again, good to see you. I think you've been on since 2012, '13, '15. >> Is that right? What, are we carbon dating ourselves now or something? >> We've been tracking our CUBE alumni, but you're heading up the storage business-- >> Do I get a pen? >> We're working on that, Jerry Chen-- >> Seven of them >> Jerry Chen at Greylock wants to have, now, badge values. So, welcome back. >> Thank you, thank you for having me. >> You were just on theCUBE at VeeamON, which is an event Dave was hosting, I missed it in New Orleans. But a lot of stuff going on around stores, certainly. Virtualization has been around for a while, but now with Cloud; whole new ballgame. Programmable infrastructure, hybrid IT, Wikibond's true private Cloud report came out showing that private Cloud on Prim is $250 billion market. So nothing's really changing radically in the enterprise, per se, certainly maybe servers and storage, but people got to store their data. >> Bill: That's right What's the update from your perspective, what's the story here at HPE Discover? >> So I think there's really three things we're talking about amongst a number of announcements. One is sort of the extension of our All Flash environment for customers, who, as I was saying at Veeam, have the always-on. New world order is we expect everything to be available at a moment's notice, so I was in the middle of the Indian Ocean, using Google Voice over satellite IP on the boat, talking to San Jose, and it worked. That's always-on environment, and the best way to get that is, you know, with an All Flash [unknown], so that's number one. Number two, going back to the story about programmable infrastructures, storage also needs to be programmable, and so, if you've had Rick Lewis or Rick Lewis is coming he'll talk about composable infrastructures with Synergy, but the flip side of that is our belief that storage really needs to be invisible. And the acquisition of Nimble gets us a lot closer to sort of doing that in the same way that you have a safe self-driving car is all the rage. All that rich telemetry comes back, it's analyzed, fingerprinted, and sent out to customers to a point where it's, I call it the Rule of 85. 85% of the customers, the cases are raised by InfoSight and closed by InfoSight, and they have an 85 net promoter score. We're getting to a point where storage can be invisible, cause that's the experience you get on Amazon or as you swipe your credit card, say I want ten terabytes of storage, and that's the last time you have to think about it. We need to have the economics of the web, we need to have the programmability of the web, that's number two, and number three of what we talked about, and this is a big issue, a big thing we talked about with VeeamON, was data protection. The rules of data protection are also changing. Conventional backup does not protect data. I was with a customer a couple weeks ago in London. 120 petabytes; this is a financial services customer now. 120 petabytes of storage: not unusual. 40 of it was Hadoop, and they were surprised because it's unprotected, it's on servers, it's sort of the age of the client-server, and the age of Excel spreadsheets all over again. We realized that most businesses were running on Excel, so All Flash, a different way of supporting our customer support experience, and number three, it's all around how do you protect your data differently. >> What's the big trend from your standpoint, because a lot of that self-driving storage concept, or self-driving car analogy, it speaks to simplicity and automation. >> That's right >> The other thing that's going on is data is becoming more irrelevant, certainly in the Cloud. Whether that's a data protection impact or having data availability for Cloud-native apps, or in memory, or all kinds of cool stuff going on. So you got to lot of stuff happening, so to be invisible, and be programmable, customer's architectures are changing. What's the big trend that you're seeing from a customer standpoint? Are there new ways to lay out storage so that they can be invisible? Certainly a lot of people were looking at their simplification in IT operationally, and then have to prepare for the Cloud, whether that's Multicloud or hybrid or true private Cloud. What architects are you seeing changing, what are people doubling down on, what's the big trends in storage, kind of laying out storage as a strategy? >> So I think the thing about storage in the large, one of the trends obviously that we're seeing is sort of storage co-located with the server. When I started at HP now seven years ago, gen six to gen ten, which we've announced here at this show, the amount of locally attached storage in the box itself is massive. And then the applications are now becoming more and more responsible for data placement, and data replication. And so, even while capacities are growing, I think six or seven percent is what I saw from the latest IDC survey, the actual storage landscape, from a shared storage company, they're actually going down. And the reason is, application provisioning, application-aware storage is really the trend, that's sort of number one. Number two, you see customers looking at deploying the right storage for the right applications. hyperconverge with SimpliVity's a really good example of that, which is they're trying to find the right sort of storage to sort of serve up the right application. And that's where, if you're a single-PoINT provider company now in storage, and you don't have a software-only, a hyperconverge, an All Flash in a couple different flavors, including XP at the top, you're going to find it very, very difficult to sort of continue to compete in this market, and frankly, we're driving a lot of that consolidation, we put some bookends around what we're prepared to pay for. But if you're a PoINT providing storage company now? Life is a lot harder for you than it was a couple years ago. When we started with All Flash, I think it was like 94 All Flash companies. There are not 94 All Flash companies today. And so, I think that's sort of what we see. >> Well, to your point about PoINT companies are going to have a hard time remaining independent, and that's why a lot of 'em are in business to basically sell to a company like yours, cause they fill a need. So my question relates to R&D strategy. As the GM, relatively new GM, you know well that a large company like HPE has to participate in multiple markets, and in order to expand your team, you have to have the right product at the right time. One size does not fit all. So the Nimble acquisition brings in a capability at the lower end of the market, lower price spans, but it also has some unique attributes with regard to the way it uses data and analytics. You've got 3PAR Legendary at the high end. What's the strategy in terms of, and is there one, to bring the best of both of those worlds together, or is it sort of let 20 flowers bloom? >> So, I don't know if it's going to be 'let 20 flowers bloom', but I would probably answer a couple different ways. One is that InfoSight, you're right, is unique value proposition, is part of Nimble. I would bet if I come see you in Madrid, if you have me back for the, whatever, 13th time, [Laughing] that we'll be talking about how InfoSight and 3PAR can come together. So that's sort of the answer to number one. The answer to number two is, even though within the Nimble acquisition, one party acquired the other party, what we're really looking at is the best breed of both organizations. Whether that's a process, a person, a technology, we don't feel wedded to, "Just because we do it a certain way at HP, that means the Nimble team must conform." It's really, "Bring us the best and brightest." That's what we got. At the end of the day, we got a company, we got revenue, but we got the people, and in this storage business, these are serial entrepreneurs who have actually developed a product, we want to keep those people, and the way you do that is you bring 'em in and you use the best and greatest of all the technologies. There's probably other optimizations we'll look at, but looking at InfoSight across the entire portfolio, and one day maybe across the server portfolio, is the right thing to do. >> And just to follow up on that, Tom, if I may, so that's a hard core of sort of embedded technology, and then you've got a capability, we talk about the API economy all the time. How are you, and are you able to leverage other HPE activities to create infrastructure as code, specifically within the storage group? >> So if you look at us, at our converged systems appliances like our SAP HANA appliance, databases greater than six terabytes, we have 85% market share at Hewlett-Packard. And the way we do that, and that's all on 3PAR by the way, and the way we do that is we've got a fixed system that is designed solely to deliver HANA. On the flip of that, you have Synergy, which is a composable programmable infrastructure from the start, where it's all template-based and based on application provisioning. You provision storage, you provision the fabric, you provision compute. That programmable infrastructure also is supported by HP storage. And so, you have-- You can roll it the way you want to, and to some degree I think it's all about choice. If you want to go along, and build your own programmable infrastructure and OpenStack or VCloud Director, whatever it is, we have one of those. If you think simplicity is key, and app and server integration is important part of how you want to roll it out, we have one of those, that's called SimpliVity. If you want a traditional shared storage environment, we have one of those in 3PAR and Nimble, and if you want composable we have that. Now, choice means more than one, I don't know what it means in Latin or Italian, but I'm pretty sure choice means more than one. What we don't want to do is introduce, however, the complexity of what owning more than one is. And that's where things like Synergy make sense, or federation between SerVirtual and 3PAR, and soon we'll have federation between Nimble and 3PAR. So to help customers with that operational complexity problem, but we actually believe that choice is the most important thing we can provide our customers. >> I've always been a big fan of that compose thing, going back a couple years when you guys came and brought it out to the market. We're first, by the way, props to HP, also first on converged infrastructure way back in the day. I got to ask you, one of the things I love doing with theCUBE interviews is that we get to kind of get inspiration around some of the things that you're working on in your business unit. Back in 2010, Dave and I really kind of saw storage move from being boring storage, provisioning storage, to really the center of the action, and really since 2010 you've seen storage really at the center of all these converging trends. Virtualization, and hyperconverges, all this great stuff, now Cloud, so storage is kind of like the center point of all the action, so I got to ask you the question on virtualization, certainly changed the game with storage. Containerization is also changing the game, so I was telling some HP Labs guys last night that I've been looking at provisioning containers in microseconds. Where virtualization is extending and continuing to have a nice run, on the heels of that we got containerization, where apps are going to start working with storage. What's your vision and how do you guys look at that trend? How are you riding that next wave? >> It all comes down to an application-driven approach. As we were saying a little earlier, our view is that storage will be silent. You're going to provision an application. That's really the-- see, look at the difference between us and, let's say, Nutanix with SimpliVity. It's all about the application being provisioned into the hyperconverged environment. And if you look at the virtualization business alone, VMware's going to have a tough go because Hyper-V has actually gotten good enough, and it's cheaper, but people are really giving Hyper-V a much better look at than we've seen over the course of the last couple years. But guess what? That tool will commoditize, and the next commoditization point is going to be containers. Our vantage point, and if you look at 3PAR, you look at Nimble, we're already got it, we've already supported containers within the product, we've actually invested companies that are container-rich. I think it's all about, "What's the next--" >> And we at Dacron last year said, "We know you're parting with all the guys." But this is a big wave. You see containers as-- >> I see containers as sort of the place that virtualization sort of didn't ever get to. If you look at-- >> John: Well, the apps. >> On the apps absolutely, positively. And also it's a much simpler way to deploy an application over a conventional VM. I think containers will be important. Is it going to be important as the technology inflection point around All Flash? >> John: Flash is certainly very-- >> That I don't know, but I think as far as limiting costs in your datacenter, making it easier to deploy your applications, et cetera, I think containers is the one. >> What's the big news here, at HPE Discover 2017, for you guys? What's the story that you're telling, what's going on in the booth? Share some insight into what's happening here on the ground in Las Vegas from your standpoint. >> So I would say a couple of things. I think if you look out on the show floor, it seems more intimate and smaller this year. And there's a lot of concern, I think, that HP is chopping itself off into various pieces and parts, but I think the story that maybe we're not telling well enough, or that it gets missed, is out of that is actually a brand new company called Hewlett-Packard Enterprise, which is uniquely focused on serving enterprise infrastructure customers. And so I think, if I was going to encourage a news story, it's about the phoenix of that, and not the fact that we've taken the yes guys, and the software guys, and the PC guys. It's that company, maybe in Madrid we'll do this, and that company, that's really, really, really exciting. And as you said, storage; sort of in a Ptolemy versus Galileo approach. We believe everything, first of all, revolves around storage. We don't believe in Galileo. So if you look in here at the booth, we've announced the next generation of MSA platforms of 2052, we've got the 9450 3PAR -- three times as fast, more connectivity for All Flash solutions. We've talked about the secondary Flash array for Nimble, most effective place to protect your data is on an array, is on a type where the data came from, and that is the secondary Flash market. We're big into Cloud, we've talked about CloudBank here, which is the ability to keep a copy of your store-once data in any S3-compliant interface, including Scality. I don't know if I'm forgetting, I'm sure I'm forgetting something. >> John: There's a lot there. >> There's a lot there. >> I mean, you guys, I love your angle on the phoenix. We've been seeing that, we've been covering seven years now, and it is a phoenix. And the point that I think the news media is not getting on HP, there's a lot of fud out there, is that this is not a divested strategy. There's some things that went away that were the outsourcing business, but that was just natural. But this is HP-owned, it's not like it's like we're getting out of that, it's just how you're organizing it. >> And with a balance sheet that now is really a competitive weapon, if you will, you're going to see HP both grow organically and inorganically, and I think as the market continues to consolidate, the thing to remember also is there's fewer places to consolidate to. And so if you're a start-up, there's a handful of companies that you can go to now, and probably the best-equipped, right-sized, great balance sheet, great company, is Hewlett-Packard Enterprise. >> Well we had hoped to get Chris Hsu on, but I've always said the day we talk about the debates on management style, but I've always been a big believer as a computer science undergraduate, decouple highly cohesive strategy is a really viable one, I think that's a great one. >> Yeah, and there's still a good partnership with DXC, there'll be a great partnership with Micro Focus, and there's both financially as well as from a business perspective. But it's really an opportunity to focus, and if I was at another company, I would wonder whether or not if their strategy continues to be appropriate. >> Bill Philbin, senior Vice President and general manager of storage and big data at Hewlett-Packard Enterprises, theCUBE more live coverage after the short break. From Las Vegas, HPE Discover 2017, I'm John Furrier with Dave Vellante with theCUBE, we'll be right back after this short break.

>> Narrator: Live from Las Vegas, it's The Cube covering HPE Discover 2017 brought to you by Hewlett-Packard Enterprise. >> Welcome back everyone, live here in Las Vegas, this is the Cube special presentation of Hewlett-Packard Enterprise, HPE Discover 2017. I'm John Furrier with The Cube, my co-host Dave Vellante for the next three days with wall-to-wall coverage here in Las Vegas. Our next guess is Tom Lattin, Vice President and General Manager of HPE Server Options which is all the good stuff that wrap around the servers. And certainly the big news here at HP is the Gen10, the continuation of the, the generation of servers which is all the rage these days. People are talkin' about servers, are we buying more or buying less? Still a lot of private cloud going on. Nothing really changing in the premise world. Welcome to The Cube. >> Thank you, good to be here. >> Alright, so what's the big news? I mean, to me the, the thing that I've always been watching is the Gen8 stuff, Gen10 now is the new announcement platform for servers. >> Certainly. >> A lot of stuff happening around, a lot of innovations. Give us a quick update on the key things happening around Gen10 and the options. >> Well certainly with Gen10, we've got a whole new level of security that is a big part of the Gen10 story. And with the server options in the memory SEP system and the storage SEP system and the networking SEP system, all of those technologies contribute to building up those layers of security in Gen10. So that's a key part of what we're doing this week at discover. The second thing in the options space, the server options space, is persistent memory. So we introduced persistent memory on Gen9 servers last year with the MB DIMM, an eight gigabyte MB DIMM. We're extending that portfolio this year with the Gen10 servers and increasing the MB DIMM capacity to 16 gigabytes. But the really big news in the persistent memory offering is scalable persistent memory. >> I just saw a great article on the CRN, Computer Reseller News or CRN, really giving you guys some props on this. "Persistent memory combines the performance of D RAM with the persistent of traditional SSDs or spinning disk. So, essentially a huge performance gain, and, which is always good, HP has that, always has some good mojo when it comes to, you know, high quality products and performance. But talk about the impact because one of things that's going on right now is storage has to be invisible but applications now have, going beyond virtual machines. You've got containers, you've got all kinds of cloud things happening with the apps. So the data, the state of the data, the performance of the data is really critical to customers. What's the impact of this to that trend? >> This is, persistent memory unleashes an incredible amount of performance for the server, for the application running on the server. At it's most fundamental level, persistent memory and MB DIMM or a scalable persistent memory implementation can replace a layer of flash storage. And we're seein' performance benefits on the order of doubling the performance of the application just by swapping out an SSD for persistent memory or an MB DIMM. When the applications, when the architects actually modify the applications to take advantage of the fact that there's a persistent memory layer in there, we see performance benefits as small as four times improvement, but in many cases we're seeing 20, 25, 27x performance improvements because the architects of the applications now can dive right into the memory sub-system without going through layers and layers of code and moving data around to get to storage. >> Love, love the options comps that you guys are running because I think one of the things that we here is, you know, flexibility is key and it's kind like goin' to the store and, like, getting some accessories for your suit. Not one size fits all, you need to have a lot of options given the environment. So I got to ask you the competitive question. How do you guys compare vis-a-vis the competition with the persistent memory stuff, for instance? You mentioned the performance, how does that compare with some of your competitors? >> I think persistent memory is a good example of where we're way out ahead of where our competition is right now. It's, you can't just drop in a piece of hardware in the server and get all of the benefit out of it. You've got to be able to integrate that piece of hardware with the system software, the bios in the system, and then work with software application partners especially to go modify, or to optimize their applications to work best with that component that you put in there. >> And you guys do that? >> We do that extensively. >> Not the customer, the customer just, what? Just installs it? >> The customer gets it. It just works. >> So, what's the typical sort of anatomy of a life cycle of a server these days? And, and, I mean, it used to be, in the old days it was called peripherals and peripherals made up probably 60 to 70% of the market so it was very huge, you know, quite a huge opportunity. So how does it work from a customer standpoint? Does, do they, what's their starting point? How do they plan this out? Or is it more reactive? I wonder if you could sort of bring us up to date on that dynamic, Tom. >> I think that's, part of what we bring to the market is a set of server platforms that have an incredible breadth of capability and that breadth comes from the configuration choices that customer can make through the server options portfolios. So, generally, they're, a customer will standardize on a few different platform types and then deploy those servers for a variety of different workloads. And so it's through those configuration choices, storage capacity, memory capacity, the performance of different layers in the memory and storage hierarchy that allow them to be able to fine-tune a small set of servers, really, for a much broader set of workloads. >> So we've commented for a number of years now on The Cube that the pendulum is swinging. Storage is, and servers are coming, and computer coming closer together. >> Absolutely. >> You certainly saw that with Flash and PCIe. Sort of, those trends brought storage and compute together and now you're accelerating that even further with, with persistent memory. >> Tom: Yes. >> So, as that happens, one of the big challenges is data sharing, right? Now you hear things like, you know, NVMe over Fabric and other technologies to, to link these capabilities, these nodes if you will. What's, I mean it sounds like The Machine, so. >> Tom: Exactly. >> What's happening there and help us sort of squint through those two big trends. >> Yeah, I think that as we evolve architectures to focus on the data and recognize that the data really is where the value resides, we're moving from a world where, first of all, sharing the data on storage makes a lot of sense to enable that. If you look at some of the demonstrations that we've done recently with the machine and with memory driven computing, it's about taking that shared presence of the data or shared instance of the data to an entirely new level where the processors, processing capability can get directly at it and operate it and work on that really as a shared body of information, shared body of knowledge. So yes, started in the storage sub-system but absolutely where we're headed is a memory-driven computing world where it's in the memory sub-systems. >> And that is The Machine, but, and which is a, you know, big R&D project that's kind of comin' out of HP Labs, and, you know, Martin Fink showing it off a couple years ago and giving us the roadmap, but now we're seein' it sort of evolve. But as well, I would think your ecosystem can kind of build it's own pseudo-machine, you know? With compute power and all this persistent memory and you know, architecting, I mean, do you see those as two separate vectors that, you know, let's see what happens in the channel? Or, or do you see those two worlds coming together? >> Fundamentally, we are a partnering business, right? We work extensively with the ecosystem of software providers, partners in the industry. So what we're demonstrating with The Machine, necessarily we've done a lot of those parts ourselves to show the capability. But absolutely this memory-centric computing vision and that we're beginning to realize with some of the products that we're releasing today, persistent memory is a great example of that, is all about enabling the industry, the ecosystem in the industry to bring that value for, ultimately for all of our customers. >> And has heading up the sort of options business, if you will, how do you, one of the things we've talked about a lot is this notion of true private cloud which is substantially mimicking public cloud on PRIM because the world is hybrid as we all sort of point out. How do you create that experience for customers? That, that cloud-like experience? >> I think it, well with the simplicity and the agility of what we're doing with the HPE compute experience now is very focused on creating that cloud-like experience in a hybrid cloud world, right? On premises for example. And so that's, a lot of that is about being able to scale up and down the computing capability, to incorporate new financial models so that you can buy compute, rent compute at your, kind of, depending on what your strategic corporate objectives are. So the options themselves then give you that ability to, for example, scalable persistent memory uses the base system in the server and one day you may say, "Hey, I need to use a "portion of that as persistent "because of the workload that I'm running." And then later that night, that same system could translate over to run a completely different workload and change the profile of the persistent memory that's being used because it's a configuration setting of the base system memory. So making the system itself very flexible to adapt to the changing needs of workloads, either overtime or very realtime like that in the course of a day. >> Tom I want to get your thoughts on the trends that we're covering, and certainly the industry's covering. So you have an industry scope and you have, obviously, partners which are going to be critical in getting things certified and or working so the customer just plugs, plugs stuff in, like the memory. >> Tom: Yes. >> Obviously the market place says, well, "Oh server ships are down," but the cloud's happening, servers are actually growing no matter how you look at. But there's more realtime stuff goin' on. There's more processing happening. How do you guys look at the marketplace trends because there is more need, at The Edge for instance, we had Bill Philbin on just earlier before you came on talkin' about how storage and compute are comin' together. This is kind of the, the options world you're in. You're in the middle of all this action so people actually cobbling together and composing solutions, whether it's on PRIM or working with similar architectures in the cloud, same code bases moving back and forth. So this whole world is really not declining. Maybe shifting how it was before, that transformation you're in the middle of, how do you guys look at that and how you do talk to the customers who are like, "I was buying servers and options before, "I still got to do that but I got to "transform and be prepared for realtime analytics, "using multiple clouds, all these kinds of, "these, these important items for the future"? >> Yeah, it's a bit of an architectural revolution if you will, right? As we move to a memory-centric computing world, as we move to a world where everything is cloud-based, cloud architecture-based, whether it's out in a public cloud somewhere or on an on-prep as kind of hybrid IT model, it really is a completely different architectural model. And so to capitalize on that, what we work with customers on is things like the composable capability of synergy. Things like persistent memory and making that scalable to move to a memory-driven computing model. Things like our all-Flash array business and our product offerings to be able to accelerate that storage sub-system well beyond what's been done before. >> It's performance driven too, you got to eek out performance more and more. >> Yes. That's kind of the mandate. Another interesting thing I wanted to get your thoughts on, and, you know, I'm old in the industry these days relative to the average age of most people in the big the big companies, like hyper-scalers are like 28 to 30-something. The trend is systems. I mean, you're seeing, if you look at what the cloud ' doing in the revolution at the architectural level, it's almost a complete crossover to a systems mindset. Systems meaning operating systems or, you know, core systems. So a lot of the people that are really doing well in the industry, who are radically transforming it, are older guys. James Gosling was at, just joined Amazon Web Services. You got guys who are in their 50s who are leading major architectural shifts. This kind of puts HP in an interesting position because you guys have so much experience with systems, servers, you know, just on an isolated basis. But now, as that looks out over the landscape, it's even more important to look at it from a holistic perspective. Your thoughts on this trend? >> Well absolutely, it's a huge trend and by taking the expertise that we've got at a systems level and coupling that with our strategic imperative to partner with other industry leaders in the industry revolution, I think those two together position not just HPE well, but the ecosystem of HPE and our software industry partners to really help advance that, that architectural-- >> I was talking to James Governor last who's the, with Red Monk and one of the research firms we like and I said to him, "It's open bar and open source," was my kind of headline story I was tryin', we were collaborating on and what I mean by that is that, you know, as open source evolves, we saw some of the stuff goin' on with The Machine in mem-store, a lot of that stuffs going to be open source at the core at the system level. So open source is growing, but when I say open bar, it's like there is more goodness being contributed to open source than ever before. You're seeing great machine learning libraries being, you know, given in to collaboration. You're seeing open source being a great recruiting environment. So if you're a young gun in the marketplace right now, you're getting all this contribution so with that kind of as a context, what's the open source strategy that you see? 'Cause you're in kind of a glue layer with options. You're kind of creating some flexibility for customers. At the same time, you've got a glue kind of concept goin' on with software. What do you guys do with open source? Is there a trend there that you'd like to share? I mean, I'm interested to know what your position is vis-a-vis contribution programs and whatnot. >> Yeah, I think, certainly at the hardware layers, right, of what we're doing with server options, it's about enabling new capabilities. And so we work with quite a few open source partners to enable those. So say, for example, Red Hat, they're taking our persistent memory offerings and optimizing those so that they get, certainly the immediate benefit of a layer of high-performance storage but the more radical performance improvements that they can get when they address directly a layer of persistent memory. So it's not so much that we're creating a whole new, at least in the option space, kind of a whole new open source plane. >> But you're intersecting. >> Absolutely. >> I mean, one other thing is networking is hot right now. Certainly, SDM we see that. A lot of the open source projects, and even in Linux foundation you're seeing the network stack just kind of being, kind of decomposed. So a very interesting opportunity. >> Yes. >> Well, and the same thing with storage, right? And you mentioned Flash a couple of times right? You're seeing the whole storage stack just completely morphing and changing. >> Tom: Yeah. >> So you guys are in the center of that, how does a customer engage? Does it happen typically through the channel, do they go to hpe.com, how does that happen? >> For server option kind of products, yeah, certainly. Through our direct sales force, through our partners' sales forces, 'cause, as we said, it's an ecosystem that brings us value forward. So in many cases, it's not us in, even in explaining something like persistent memory. It's Microsoft or it's Red Hat or it's SUSE, or partners there, VMware. We've got a, actually a lot of presence with VMware and some interesting things they're going to be talking about in one of our sessions here later today at Discover. So that's one path. Or two paths. Our sales force, their sales force and then, absolutely, the channel. We've got a very rich channel program and a lot of engagement with them to bring them up on networking technologies, storage technologies, memory, persistent memory technologies so that they can-- >> John: So it's ecosystem is really the key. >> They can effectively engage customers, yeah. >> Alright, Tom Lattin is the Vice President and General Manager at HP Server Options. My final question for you to end the segment here is what should customers know about Gen10 and server options if you had a chance to look right into the camera and say, "Hey, new game in town," or, "Think differently around architecture," what would be, what would be your words? In your words, what should customers know about the world you're building? >> Certainly with Gen10, the server options portfolio unleashes or helps support the overall security capabilities of Gen10, number one. But if I can have a second one. >> John: Of course. >> I've got to play persistent memory high because we've got a terabyte-scale persistent memory capability in the Gen10 platforms which is, opens up a whole new world of opportunity for applications, as I said, early on to develop or increase performance, in many cases, 20, 25, 27 times the capabilities today. >> That's awesome, I mean I think the memories awesome. Dave and I have been talkin' for years that memory used to be the resource that was constrained and unlimited storage, now it's the other way around, people want memory, application developers and programmers. This is The Cube bringing you great content you can put to memory, Flash memory. HPE Discover, I'm John Fullier with Dave Vellante, we'll be back with more live coverage after this short break.

live from Las Vegas Nevada it's the cube at HP discover 2014 brought to you by HP the keynotes this afternoon meg whitman was just on a panel with thomas friedman and intel and satya nadella microsoft and pretty interesting i was it was interesting i'm here with Jeff Rick to note how passionate meg is about politics and government wow I'm she comforted by boat for Bobby Patrick is here we've been drilling down into cloud all day Bobby is the CMO of the HP Cloud Division a lot of new announcements coming on a lot of action and HP Cloud Bobby welcome to the cube yeah thank it's great to be here yeah good to see you so yeah good keynotes good good that was a good refresher you know a lot of these keynotes just products pushing and pushing we had some of that earlier but I thought it was a good eye opening refreshing right kind of discussion so it was very worthwhile but anyway you're relatively new to to HP to run to actually soon how's it going it's great it's exciting i joined it like a great time for the company we were gearing up for the big launch of our new brand HP Helion that that was launched on May seventh so just a little over a month ago and we hit the mark market hard globally it's a complete pull together of all of our products and services around cloud under a single brand customers love it and and it's really reiterated our commitment to OpenStack and you know it's great HP announced the billion dollar commitment to HP Helion over the next two years so it's backed by some some big funding that's a great time to come in so I saw that what is that would help us unpack that billion dollars it was big number right it's popular number right even we aren't buffin right her site Warren Buffett hehe underwrote the whole thing the March Madness right giving away a billion dollars for the perfect bracket right no longer a million does out of the abelian so what is that billion what does it go to what does it comprised yeah I mean it goes 2 r.d where where the most where the most active corporate sponsor behind OpenStack which is the fastest-growing open source project on the planet we are we have more contributors we have more team leads for the different projects and so we're working with the community we're hiring OpenStack experts always looking for the best in the world all around the world and we're then hardening and curating it in making a commercial now with our support and we believe it's the underpinning of the future of what we call hybrid cloud the ability to put some of your information some of your applications with an enterprise some of the public cloud some in different countries that matter for compliance reasons and to be able to move around between those different clouds in a very easy fashion so this money is going to that rd2 skills and to you know truly a global global launch so when you think about the sort of messaging for our HP Cloud what do you want customers to think about in the Helion brand and the HP Cloud yeah the number one thing is commitment to open standards so we are if you heard Martin Fink today talk about HP Labs and they're coming to open source we're all in on open source we believe it's the way to deliver innovation faster we can bring the market tech new technologies faster to customers so we're all into open source we are committed to the projects that matter to the next 20 years of IT and so that could emma has a real though we have to be to prove it with to say you know you can run our software on other hardware we think it'll be we'll have some optimal integrated solutions for you using our entire stack but this is about this is about eliminating vendor lock-in which is one of the biggest challenges at IT departments have faced in the last 20 years and so I think the commitment behind it open is at the core of our messaging so we should mention so Martin fake gave i really liked his presentation i have been safer I don't know for years that HP's got to get back to its roots right which are in fence right and I have not heard until today something that excited me about invention and we saw it today right now invention is not easy all we've talked about a lot that the previous administration cut cut cut by the bone right it takes a long time to turn that's Nisha but but we saw today think was put into that job for very particular reason I said about two things one it's a guy who's going to commercialize inventions answer the marketplace and two there's going to be a heavy systems focus so he basically showed a little leg on the machine which eventually is probably gonna be powering your clouds right he also announced HP is going to put forth a new open source operating system optimized for non-volatile memory not only a blank sheet of paper that they're going to work on with universities but also a Linux derivative stripped-down Linux driven and one for Android that was excited yeah I think what's great also is the cloud business actually falls under market so our our entire business worldwide in our cloud effort our rd on product development is all under martin who runs our CTO of our of our HP labs and when you look at the problems he's addressing with the machine and he's going after it's going after the massive scale challenges of the internet right and the massive scale challenge to the cloud and the day-to-day lose that we're all that we're all facing within the Internet of Things and so you know what's great is by being a part of the labs and being part of Martin's organization you know we're we're injecting that thinking into our cloud we're injecting it into our innovation and and you can see a road map here right you can see this this whole new architecture you talk about architecture that's been in existence since 1950 it was called the von Neumann architecture all the way to now and you know the world with copper at the core you know the world's in need of a new architecture and so it's great to be part of that there's that was a cool talk you talking about electrons photons and ions electrons compute compute autonomy photon photons communicate anions door right and that in essence is the future direction of where HP is going with the machine run a civ massive memory blowing away the volatility hierarchy blowing way ultimately slow spinning disks using memory store right as the platform for future systems I love it yeah he mentioned also but one thing that's close to my heart is the distributed mesh you saw that distributed mesh where we're different different hardware software combinations sit at different points of the you know the net work and they work together you know compute and data and that's really hybrid cloud you know hybrid cloud is putting compute workloads in certain areas and having data stored and distributed for maximum availability and doing that you know with self-service and doing that in a way that you know I see over nations can scale effectively yeah I think that you know as a marketing person you realize that customers want to know that your relevant for their future right and you know as much as I love things like store once it's not the future of computing Ryan comes out HP Labs this potentially is so that's got to have customers really excite this really the first time you've unveiled it right massively in the public scale right maybe you're talking you know that's why that's why i joined the HP i saw that coming out a few months ago and the the new style of IT thinking we're we're saying you know we're radically going to be at the core of helping IT transition from the old style very inward to a customer centric style 21 you know where you're delivering the customer you know consumer experience in the business world and i saw that with HP and it got me excited and i joined on board not upside yeah the other part that Martin mentioned I no idea of the power of HP Labs but the leveraging open source as well which are I probably not a tool in the arsenal not that long ago to really bring the power of a large communities engaged you can attack right specific problems and make that a core piece of the of the process yeah we think about it we've got thousands of the world's best developers right the Millennial developers these guys working all around the clock working on you know our core cloud future called OpenStack contributing to that right including our experts and then we're taking that and then bringing it to market you know into providing that twenty four seven support testing and hardening it you know doing the things need to do to help it enterprise feel comfortable with that decision you could never do that we could never do that and deliver that kind of innovation on our own just couldn't afford it we wouldn't be able to deliver on it you know these are the best minds of the world who are contributing this and we're we're all in nope in fact so you talked about we talked about what the brand is stand for you said open no lock-in can open source innovation occur at a pace with somebody who's got full control of a stack it's much faster actually I mean this is the you watch the innovation of OpenStack it's only what four years old we just at a four-year birthday of OpenStack already that's an entire cloud computing platform you've got databases service projects like trove you've got object storage projects like Swift and block storage like Senator you know all of these things are being worked on by people around the world you could never deliver and so what's happening is the pace of innovation with an open source project like OpenStack is like it's a hockey stick and and so I think yeah I think if we did this ourselves we or anyone else you would never be able to deliver the kind of innovation it's coming to market now we talked about some of the announcements you guys know why don't we actually go back a month right but Helion and then work through today we've got some HPC announcements you got the network you know for Helion right start with Helia so what's great about healing on is is it really brought together a lot of great products and services of the cloud that already existed and it took OpenStack and it was our first foray into the market with an OpenStack distribution and what's important actually is we have technology one called HP cloud system that is actually the most popular cloud platform right now private cloud platform on the planet about almost two thousand users right or two thousand companies third of the Fortune 100 right now using that technology so it is a proven capable platform used by big banks and others we're injecting OpenStack into that so that you can you can over time scale that out with new applications and so the launch really was about pulling all the pieces together pulling our support and services together and saying to a customer you know with confidence here's here's our cloud portfolio and here's how we can take you on a journey it's your pace and accelerate that journey take advantage of that cloud portfolio and that was really the launch month ago today and it discover I mean only a month later we've already done a number of great things but one is we brought out OpenStack the commercial version so we've launched community one you can download it thousands of downloads already the commercial versions coming up now and we announced pricing and what we are all about here this is what it really really important we are about accelerating the adoption of OpenStack throughout the enterprise we're about breaking down the barriers that have that have inhibited the proliferation of this great technology so one of those things today was the price point we announced 1000 for three dollars per year per server all in price point for HP Helion OpenStack and that's critical because this is a scale out a scale-out product you're going to have dozens hundreds maybe even thousands of these all around the world and so the price point is it's disruptive it's the lowest of the planet and and you know we said it's gonna be simple and easy we're not going to do all of this good better best packaging it's it's super easy and that's a big part of today the other part of today as we said you know what we're going to work with partners we're going to deploy this all around the world and that was the helium Network announcement along with ATT and the British Telecom and Intel and that's that's just huge for today now now helium comprises both on-premise in an HP public cloud correct that's right so talk about how that pricing works I mean I like what you're saying simple because cloud pricing is really complicated yeah so we use we wear that we're probably the largest user of OpenStack in production in production today without public cloud so we use it and people can consume services from that buy them on a on a you know on an as you go basis but with OpenStack which you what's really happening is people are able to deploy their own private clouds right they're able to a service provider could deploy and build their own public cloud so when I talk about the price point talking about a customer building their own cloud building their own cloud and a third party data center or in one of HP's 82 data centers and that that price point is is is you know it's easy easy to use you can predict it in your business model and feel comfortable about what it's going to cost you know two three four years out and so help me understand let's unpack that a little bit what am I getting for that fourteen hundred dollars per so you get the entire so this is what's amazing you get the entire cloud operating system called OpenStack right you get all of the projects now that are part of the OpenStack bill you're getting a top you're getting an object story it's it's a you know a la amazon s3 but in a box called Swift right with a swift API and you can build that and do that yourself now you can do that in a way that controls that gives you full control and full flexibility you get databases the service product you get a cute engine with cinder grizzly everything that's right no lad for the computer and so you get all of this in that box all of this and you can go deploy this and you can benefit now from the thousands of developers who are every six weeks putting out new code and innovative so okay so all the new innovations will fall under that umbrella and that's right at any price they choose to use you might say I'm just building a cloud storage environment you might choose to be heavy on Swift that's what you're doing but it is all inclusive and you can use the entire cloud platform or you can build a storage platform or databases a service platform that's a different model clearly what a customer is telling you about that yeah so they well they want they want the control and the flexibility of having their own platform for you know security reasons their own for compliance they want to put their data you know in their own centers but they're also saying I want to use public cloud some too and I like the idea that if OpenStack is here and OpenStack is here right same code bases I can fairly easily take a workload take an application to go from here to here and back and forth that kind of flexibility call interoperability and that's what's coming down the road with OpenStack underneath is something that does not exist today is everybody wants make sure I understand so I'm paid 1400 hours per server for that OpenStack instance on-premise and then when I want to access public cloud services I'm what you would pay an answer you might want to burst you might want to just go do you might have some peak demand he's burst out there you pay for and I would vote for money to make your partner of ours yep excellent now you also had some hpc announcements that's right so there's a number what's great is HP now is people are taking Helion OpenStack and they're putting it in their products are hpc group a high-performance computing group said hey we want to have a self-service mechanism we want to be able to scale out sap architecture people want in that in hpc so they put OpenStack inside their solution and launched it today and so it's you know OpenStack and better than hpc open hybrid simple to consume is what I'm that's right that's right it's ductable and predictable all right good Dave Lisa Marie wrote the book on this so this is great if you don't believe Bobby Lisa came I gave me this right gave me the books it's the OpenStack technology breaking the enterprise barrier you've got it you got it it's one of the best best reads on the planet right now yeah excellent all right so what does it go to the next level what is it I'm just buying computer part of just I'm just getting capacity if you just want capacity you might say you might just build a storage cloud yourself or you might use the our public cloud storage or with our Helia network our partners around the world be deploying OpenStack and you can buy it from them awesome all right we got to leave it there Bobby thanks so much for coming to the cube is a pleasure meantime take it all right keep it right to everybody John furrier is in the house he's back from San Francisco or San Jose good to have him back John keep right there but back with job fair in just a moment