>> 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)

>> Presenter: Live from Las Vegas it's theCUBE covering HPE Discover 2017, brought to you by Hewlett Packard Enterprise. (light techno music) >> Okay welcome back everyone we are here live in Las Vegas for HP Discover 2017. This is SiliconANGLE's, theCUBE is our flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier, the co-founder and co-CEO of SiliconANGLE with my co-founder and co-CEO Dave Vellante with Wikibon, and our next guest is Alain Andreoli, who's the Senior Vice and President General Manager of the DCIG, the Data Center Infrastructure Group at HPE. Great to see you, welcome back to theCUBE. >> Thank you, it's a pleasure to be here again. >> Great show, you guys have a lot of great innovations. Notable was the analyst press conference that we were at. You were feeling all the questions, the buzz around Gen10 and all the action you guys are putting inside the new service from security to all the innovation that's happening, pretty great opportunity and the true private cloud numbers coming out of Wikibon are showing fastest growth is cloud on-prem. This points to significant opportunities, your thoughts? >> Yeah, well, the need for compute is clearly growing and you continue to grow forever. What we see is that the compute points are also expanding so it can be on-prem, it can be off-prem, it can be in the edge, and on-prem there is a bit of a revolution which is coming from the experience of the public cloud, and so, private clouds are becoming very, very fancy. So you see on-prem compute basically turning into two families, very specialized for high-performance computing, for mission-critical, for AI, and others. The things that are really, very critical to the business. And then for all the other workloads, they need flexibility like a public cloud but on-prem because they can keep control, they want to mimic the agility and they want to have the same economic level. So we are playing on both fronts, we are doing very well on the specialized front with HPC Acquisitions of HDI and so on, and we are making a breakthrough on the private cloud with Synergy and soon with the new stack. >> So the whole notion of DevOps and cloud have opened up the doors and certainly you guys have been very clear with the simplicity message. Big data is big part of the application process, cloud providers, multiple clouds, so this right mix conversation-- >> Alain: The right mix, the right mix >> Is what Meg is putting out their is a nice message, and what you're saying is "hey the on-prem is not going "anywhere and we have the data to prove it." But you look at the big clients, they want the control. What is the conversation that you're having when you say, "Hey I need more capabilities," obviously high-performance computing, powering AI, and machine-learning, we're seeing, obviously those things. But from the business model side, what are the customers asking from you for solutions? What are the key things they want from HPE right now? What is that-- >> In terms of economic control? >> Solutions that are top priorities. When they sit down and say, "Well, you know, I need more compute." Okay, what does than mean? What specifically are you building for customers to help them with the digital transformation, to simplify the business model of on-prem with cloud and to deal with the multi-cloud world. >> So, they believe that the management of the mix between the different alternatives that they have right now with, certainly, a complexity and they rely on us to take this complexity away. So we are very bullish about the project New Stack because we think that this will allow data to be managed across the different horizons in the data center, across multiclouds and with more and more data being created and eventually computed at the edge. So these three horizons together make intelligent distributed computing, which will be more self-tuning, which will be extreme data analytics, and ultimately, this will allow customers to manage data seamlessly across everything. We think that this is kind of strategically where our customers want to be. Then the way they get there depends. Some customers have a view, which is just modernization of what they have right now. Some of the customers want to be more dramatic and run everything they have as if it was a seamless cloud, and then they have to decide the mix between on-prem and on-prem. Most of the customers, I was looking at what is actually making the public cloud. More than 50% are born from the cloud, they are people who never had the data center and may never have one until they grow up because then when they grow up, they need one. >> John: (chuckles) For control? >> What we have learned, for control-- >> John: And expense-- >> Dave: The Cloud Cliff. >> Expense, That's The Cloud Cliff. So, more than half of the public cloud customers never had a data center. About 15%, 15, 16% of the customers of the public cloud are consumers. And then, you have a small third which are enterprises. That's the first thing to realize, right? That the move of the enterprise is still pretty small. I was discussing with the largest systems integrator in Germany yesterday, and their view is the German perspective, because here in the US we have a tendency to believe that everything is public cloud or will be. The German view is totally different, for instance. So, I think, you know, we have gone through a cycle which has been public-cloud-heavy in terms of marcom where the market believed that public cloud was going to be everything, and we are now landing in a reality zone where this mix is an opportunity for the customers. They have some trivial workloads that can go on the public cloud, but we see that on-prem remains, basically, what people are doing. >> That last point's really important because even though you said, "Well, less than maybe a third is enterprises "in the public cloud," if you look and feel the workloads that are going to the public cloud, it's not the core of enterprise IT workloads. >> So what I believe is that we are thinking it the wrong way when we think in public cloud and which workload goes there. The workloads are not going to the public cloud. It's that a lot of the workloads that used to be run on-prem are now coming from the cloud, SaaS-- >> John: Right. >> That's different, that is very different. So, customers are not deciding what is on-prem, off-prem, they are now looking at software packages that come from the cloud, like Salesforce, or others. And this means that while they're running their data center as vital applications that don't come from the cloud, so it's more and more specialized, and then they have a variety of applications that don't come from the cloud, that they will run on their public cloud. This is why I see these two topologies, if you want, of specialized-- >> John: Yeah. >> Super compute and data-centric, and then, very fluid, and this where Synergy plays so well, because Synergy allows this fluidity-- >> John: Yeah. >> Of pools of resources, and you can basically adjust to the various applications that you have. >> Oh, this is classic early adopter kind of behavior, you mentioned the SaaS coming in and being influenced because they're easy to get into right? You can get some subscription and get some value, but then I think the true private cloud is interesting to me because what it really shows, to extend your point, is that the business models are changing for the agility piece, that's the DevOps. So, as you see IT consumption changing to cloud-like, or true private cloud-- >> Dave: Yep, yep, yep, yep. >> Essentially, that is an OPEX business model. So, the business transformation is now where the rubber hits the road for what digital is. So to me, we see this dynamic so with that being said, what aspects of HP taking advantage of? You mention Synergy, what else do you guys have cookin' up? What's out there that customers are using to turn the knob and go faster on the acceleration on that? >> With customers, I wouldn't like us to look at customers only as being enterprises, because as more and more business is being generated from the cloud, people who do business from the cloud, whether they are enterprise service providers, or software providers, or business born from the cloud, these people also acquire technology, and they have need for services, and they require infrastructure. So, this is a segment of the market where we're going to to double down in the future. So, we are looking, we call them, like, Tier 2, Tier 3's, because the very large ones have a tendency to try to build their own things-- >> John: Yeah, service providers-- >> But, a lot of other service providers and there are-- >> John: Cloud service providers. >> You know, a small third of the market also demand technology and support from us. So, we are going to expand our cloud line strategy. We are going to offer open systems, and be very aggressive there, both for compute, storage and for networking. So there are kind of two prevalent markets. If you want more, there is a market of completely open systems, we call them whiteboxes, you know, we call them for the cloud, Cloudline, which is now a multi-billion dollar business for us. And then you have the people who want products that offer a lot of value that are differentiated, like Synergy, like Proliant, like Blade Systems, like 3PAR, like Nimble, and so on, and obviously we are doubling down on these as well with our Acquisitions and own development like Gen10. >> So the narrative from Hewlett Packard Enterprise and all of your competitors is, you know, hybrid is the reality, fair enough-- >> Alain: That's for sure. >> And we agree, but there is an aspect of zero-sum game here in that the markets at the macro level are not growing like they used to. So, market share becomes very, very important. You've put up a slide in your keynote, 81 straight quarters of leadership. Now, we all know that you can play games with the numbers, but the most important metric we would argue is revenue share. If you're number one in revenue, that's the true market leadership. So you've had 81 straight quarters of leadership, as we've just defined leadership. That's 20 years. >> In this quarter, we had leadership, and next quarter I think we'll have leadership as well-- >> Dave: How have you been able to do that? >> We are not looking at market share for the sake of market share. We want to bring value to our customers and to our shareholders. So if there is, moving forward, a part of the market that does not yield value for either party, we may not want to measure our market share against that because we may not define this as being our own market. But so far, we are leading the overall market in compute. We are now a strong number two in storage, with the acquisition of Nimble, and we're happy to be there. But our strategy is not being number one for the sake of being number one. >> Now on Dave's point, I'm very critical on this, I've been readin' about it, and again I may be overstepping my boundaries here, but I believe that if we're going to a new era of modern computing, dull metrics don't apply because everybody seems to be number one at something. I go to so many shows where I go to Dave where I'm number one in this, I'm-- So, the question is if the old is shifting to a new model, and it's horizontally scalable, vertically specialized kind of a marketplace, which you guys are addressing with some of your tech, what are the metrics? So that we're asking ourselves the question, what should be the benchmark standard? >> So I have a strong point of view and I was discussing with an analyst last night, we had dinner, and I've had the same point of view for the last couple of years. The history of the market is to measure by product category: rack, towers, old flash arrays, disk arrays, mixed arrays, and so on. I think this is a rear mirror view, it doesn't matter. The decisions that customers are making are: what is my specialized computing? Which includes computing, storage, networking. What is my specialized data center, basically. What is my private cloud? Then what is my consumption of IT coming from service providers and therefore, you have the service provider market, which itself can be separated into different segments. That's the way to measure the business. So, I want to be leader in specialized compute. I want to be leader in private cloud because this is what enterprise will be consuming. And basically, we're already leaders there, but I want to be continue to be leader in providing gear to service providers, who have decided to rely on partners to build their data centers and not build them themselves. This makes sense, because then you look at the market differently, you're not looking at micro-territory-- >> John: I agree, I 100% agree with you. >> Density, optimized whatever, you're saying, okay, what is a service provider going to need in the future? What is going to be specialized computing in the future? What is going to be a private cloud in the future? Once you have covered that-- >> John: Yeah. >> What is going to be compute at the edge in the future? And what do you need to orchestrate all the data? These are the clusters of the market that matters. They are the ones we are pressuring and they are the ones-- >> And you could be building technology-- 100% agree with you, I would also add, by the way, I agree with you 100%, and I would even amplify it by saying you could be building something new, like a server, chips, silicon security, that has no category. So how does that relate into things-- (laughing) >> Well, Synergy is the category. >> Dave: Right. >> You know, it's-- >> 'Cause it's horizontally scalable, so again, you could be number one, two, or three by the old categories, but be wholistically number one in the market. >> So, I think it's more, you know, it's more categories of business outcomes. >> John: Yeah. >> Like, specialized high performance, you know, flexibility, agility of a private cloud. I think that's, you know, so, if you make a parallel with the car industry, you can say is the market, like, diesel engine, or gas engine, or electric engine, or is it like sport cars, SUVs, or whatever. I want us to look at SUVs and sport cars, how do we do the best SUV? How do we do the best sports car? Versus, you know-- >> John: The components, and do how you have-- >> This technical view of it's a rack or it's a tower. >> Yeah. >> And how do you add the most value for customers-- >> Yeah. >> That is profitable for shareholders? >> At the end of the day, when we have our argument in our office about this on the research side, we say, "Look, at the end of the day, "let's identify some of these new catego-- and try 'em, not measurement points, but customers and revenue can't lie. If you have customers, here it is, number of customers. >> And so, the problem then is to measure it. Once you have defined what is right metrics, can you measure it? >> John: Right. >> And so, unfortunately, the analyst today cannot measure the market where it has evolved. So we are still looking at rack and towers, and so on, and I think this is wrong, the wrong view. >> Okay, so, talk about the hot thing that we like is the Root of Trust product, the silicon thing that's called the Root of Trust, you know, with the firmware thing. This seems to be getting a lot of buzz to show. It's innovation, we had some independent testers on with your guys, and the Gen10, this is pretty impressive. Thoughts on, is this the kind of direction you continue to go with, what's your thoughts on this security-- >> Well, we think security's super important and, you know, you open the newspaper or the TV today, and you see what's happening, it's quite amazing, including today, what's happening today, here in the US. So, it's incidental the we come in just today with our new generation of compute, but it's taken two years of interviews with customers to really understand what's most important to them. And the risk of cyber threat has turned enormous, and I think that you have been interviewing experts from the FBI, and so on-- >> John: Yeah, right. >> During this session, who came here and help us to build this solution. And I think we're coming at the right time with the right solution that will take a few years to our competitors to try to match that, and then we'll go in this direction because that's the only way technically you can do it. >> John: Yeah. >> It's at the silicon level, so you basically have unique encoding on your server in silicon, and the firmware always, you know, compares itself throughout the whole life cycle of the server, even before the server is finally built through this Root of Trust. I think we've done this extremely well, I'm very, very proud of our ingenious. >> And it's been validated against the The NIST, NIST Securities Team, and so, congratulations on that. >> Alain: And these are the most stringent startups in the industry, right? >> It's pretty impressive, I mean, this has been a trend that we've been seeing, the silicon, the silicon angle, no pun intended. But it's interesting, and always, security's come up in the past, people want that. And with IoT, the support, the attack vectors can be sealed up pretty well-- >> And so are our Edgeline products, they have IDOL 5, and so, they will also have access to this technology. >> Great innovation, thanks for coming on theCUBE, really appreciate you share the insight. I'll give you a final word here. Share with the audience something you think they should know about HPE right now that they may not know about, I know the messaging's pretty simple, you got the nice messaging, but going beyond the messaging, what would you like to share with the audience about your group and HPE's innovation coming out of Discover 2017? >> You feel the buzz here, you can see, I think we have never been in such a focused and clear position, we exactly know the businesses we are pressuring, the Hybrid IT make it simpler, and the edge, and the service to make it happen. We are just crystal clear. But when you put the three together, you get to this dimension of intelligent distributed computing, and this is a market that we will lead in the future. Also, we are such a strong and stable company. We will have over $12 billion of cash net in our balance sheet by the end of next month. And this puts us in a position to continue to double down on these bets we have made for the future of the market. So we are very, very confident that we are in a great spot, and frankly, it's great now because it feels like we are starting to be a destination. The last 18 months, we separated from some of our legacy friends, and now, not only are we on our own, but we have a clear strategy moving forward. We are proving that we are implementing it with the six acquisitions that we have made over the last few months, and more in the pipeline, continuing to deliver the capability to integrate these acquisitions, and the capability to continue to motivate our customers to be with us. >> And the spotlight is on you guys, we'll be tracking it, thanks for coming on theCUBE, really appreciate it, Senior Vice President, General Manager of the Data Center Infrastructure Group, sharing his opinion here on what's happening and where's it going in the future for HPE. We'll be back with more live coverage with theCUBE, here in Las Vegas after the short break. I'm John Furrier with Dave Vellante, we'll be right back, stay with us. (light techno music)