>> from New York City. It's Theo Cube covering new relic Future Stack 2019. Brought to you by new relic. >> Welcome back on stupid a minute. This is the cubes coverage here of future stack 2019 new relics. 70 year they're doing the show is the U. S. Show. They actually bring these few locations around the globe, right next door to Grand Central Station and about 600 in attendance. And been really excited to kick off with the number of the users here at the show and happened. Welcome program. First time guests. Another cut. Who is the technical fellow in chief? Architect with Genesis. You been at the event a number of times. You're speaking at the event today, but let's start with Genesis. Customer experience is something that I think a lot of people been hearing about on. That is the product. The Genesis has tell us a little bit about the company itself. Sure. >> Yeah. So, Genesis, uh, brain that Maybe not. Everybody knows, but they certainly transitive Lee know us. We're a customer experience platform. We like to say that we're a technology company, but we power. The experience is about 25 billion customer experiences every year for 11,000 plus customers. About 1000 different countries around the world s So we are all about having a connection between brands and their customers, and we enable that >> s o not only some of the cloud shows. I was an enterprise connect earlier this year and definitely was, you know, something I heard a lot about see Exit really important Not only how customers interact with the brand, but internally how you know we treat the employees and that interaction is something that that is raised up. People are kind of important inside, but we're going to talk too much about the people here. We're gonna talk about the technology as the chief architect of this gives a little bit about what you have your arms around in a responsible for >> sure s o for for me, of the project. Your cloud was the name for for a long time, Genesis Cloud as of yesterday. So we are a public cloud offering as a CX platform and I say platform because we made the transition from just being a product to a platform. In my opinion last year, more than half of our FBI work is actually code we didn't right? So I think people using you as a programmable thing is when you become a platform. So I'm responsible for things like cloud architecture for understanding. Let's say industry trends. What technologies? We're gonna use a lot of eight of us service designed technical vetting, general cat hurting that sort of thing, >> Right? So you said your public cloud, but you said it sits on top of AWS. But it's a platform that your customers can then build on top. >> That's right. That's right. So we like to think of ourselves as C X. As a service. We've had some that use us still like a product all shrink wrapped, ready to go, others that want to extend us either writing their own. You guys writing their own back ends their own integration points. We make all of that possible. >> All right, so I'm expecting you have a bit of an opinion when it comes to that platform, As Lou said with a capital P A, and it's gotta be programmable, it's gonna be open. Tell us what your thoughts about new relic kind of entering, you know, new relic one being they said today the first, and only if their claim of observe ability platform s o give us your thoughts around. >> Absolutely. Yeah. S O. I like to think that we have been using the relic as a platform for awhile, whether they knew it or wanted it or not way have a fairly rigorous continuous delivery pipeline. And we are very big believers in infrastructure is code and develops principles. So for us, the engineering teams don't just own the code that they write, but they own the infrastructure definitions. They even own alert definitions, dashboard configurations. And we push that information directly into the relic as our deployments happen. Live hundreds of times a week around the globe. >> All right, so how do these modern architecture's enable you to run a team? >> I can't imagine trying to manage 350 plus Micro service is in production, which is roughly what we have today over 1000 Lambda Functions way can't improve what we don't measure. Everyone likes to say that, but it's true. I have a little bit of an a p m background from from places past. So I was a firm believer that you need to invest early and observe ability and metrics. So we've been a day one kind of new relic subscriber in the cloud space. Everything from understanding how the infrastructure parts work now to serve earless. It's all been about moving up the value stack like commodity metrics of servers is great and still needed. But transactional information and now trace information is absolutely essential. >> Okay, in the Kino this morning, they walk through their metrics events, logs and traces. Where are you with, you know, these various sources of data and harnessing the value of that. >> So I would say, with fairly early towards the tracing part before new relic headed as a managed thing they had cross at tracing. I'm sure you're familiar with that sort of the prior incarnation of distributed tracing on. We leverage that pretty pretty heavily, but it obviously doesn't have quite the same utility a cz what the new open tracing standards provide s so we do things like having correlation i d. S. That let us tag and follow things around. Now we just get to off load that from our team's being as responsible for it. And now the platform gives it to us. >> Yeah. Glen is open source important to your organization? >> Absolutely. We try Thio, give back some ourselves. In fact, one of the one of the nerd lets the nerd packs that Lou mentioned on stage was one that our team wrote s Oh, yeah, way believe not only that, we need a p i's and programmatic access to do our jobs, but we like toe enable and help other people with the same >> Eric Spence got a shout out on the Maquis note was that the thing that you were talking about it is >> I expect to see us probably released two or three more nerd packs before the end of the year Way, way are eager to do that rather than just investing in all of our own. You I that we had glass over the top of the relic. Now we actually just get to put those components deeper inside of new relic proper. >> Okay, eyes there. Anything else from the announcements this morning that you're looking forward to leveraging? >> So I think there's there's definite changes in the A p M space. You'll hear a little bit more, probably in the deep dives one of the talks I'm having later with not even she will be talking about. Some of those things were definitely interested in that. Open telemetry has some value. Greater Genesis definitely has investments around things like Prometheus and other sorts of monitoring. So if I'm not talking about just the public cloud side of it and other aspects there definitely things we can leverage. >> All right, Glenn gives us share a little bit, if you can. About what? What you're talking about here at the show. So one of >> the big mitts is entity centric. Observe, ability. The idea again that we're not just looking at servers and static infrastructure. We're looking at things that are very ephemeral. We have a lot of dynamics scale on our platform on. We need ways to actually frame what we're looking at at the level of Micro Service's but often level like business applications. So even when we're creating some of these extension points like the one you just mentioned way framed that within the context of a service that does a particular vertical slice on dhe, that's that's kind of where we like to invest. So we like to live. >> Okay, um, you know what's what's on your road map of? You know where you're going with your journey and is there anything that you're looking for? Beyond what was announced today from new relic ER from the ecosystem at large, >> I think there's lots of refinements of what was announced today that will help us theeighty I ops side, I think not just for noise reduction, but also for like, early early signal detection. It's a pretty fascinating space. Will likely invest some of our own dollars in times trying to help that along. Definitely Ah, lot of distributed tracing and Maur investment. There is a big piece for us. I think the A PM space. There are areas that I'd like to see a peon vendors invest in that goes beyond what now, I guess, is becoming more, more traditional, like transaction information. We have a lot of a i machine learning ourselves, and I think monitoring those types of workloads is going to be very different. As big of a paradigm shift as it was to go from classic monitoring Transactional. I think we're about to see that happen again in the >> industry. Yeah. What can you share some of the kind of the A I journey that you're going through a genesis where you are, You know what the maturity level is of solutions that you're using and >> sure way have a fairly robust aye aye team on products range from in the W m space back to the people that you mentioned at the first part of the talk way have workforce optimization, workforce management, and we brought a I algorithms to that a lot of time. Siri's forecasting that used certain machine learning techniques. We've invested a fair amount in until you and Opie any are so everything from sentiment detection to live transcription that we built in house to our own body engines that d'oh the new dialogue management. So we have a fairly robust bit there and some on the management side on the operational back in that we used to try to improve our quality of service on reduced any sort of incidents on the platform. >> All right, it's your third year. Third time coming to this show was what brings you back? What you excited about? I kind of dig in and take away from the event this year. >> I think the relics always been a partner in my stance, not just a vendor we believe so deeply in the observe ability message that one I want to be part of shaping that narrative. Eso coming to future sack actually talking to a lot of other executives, seeing where they're going and kind of sharing that use case, but also trying to be a little bit of a lighthouse. Thio, the new relic team as well, is what brings me back every year. >> Observe ability is something that it hurt. A number of startups talking about in the last couple of years were, in your opinion, does new Rolex it compared to the marketplace overall, obviously, they just kind of announced the observe ability, you know, full suite with new relic one. But you know what your viewpoint is? Toe have their wealth, their position? >> Where did I think their position? I think they are best of breed for what we're currently seeing. Owners of ability. There are other things, I think, where we could cobble together bits from multiple vendors but frankly, having application performance monitoring along with infrastructure, along with data being cold from the cloud platforms that we're all in, like, eight of us. They've got a unique place. I think the power of their agent technology has proven itself over time as well. My guidance to most other other companies that I speak with about this subject is don't just trust that it's all magic invest on. And I think they make themselves easy to invest in on. I think this platform play is a good one for them. >> All right. Well, another cut. Thank you so much for joining us. Sharing your journey, What we're doing in the best of luck on your presentation today. Thank you, sir. All right. Be back with lots more coverage here from a new relic. Future stack 2019. I'm still Minutemen. And thank you for watching the Cube.

(cheerful music) >> Live from San Francisco. It's theCUBE. Covering IBM Think 2019. Brought to you by IBM. >> Welcome to theCUBE, I'm Lisa Martin. We are at day one of IBM Think 2019, I'm with Dave Vellante. Hey Dave! Hey Lisa, good to see you. The new improved Moscone. >> Exactly, and Stu Miniman, yeah. >> Shiny. >> Yeah, this is the new, it is shiny, The carpets smells new. This is the second annual IBM Think, gentleman where there's this conglomeration of five to six previous events. Doesn't really kick off yet today. I think Partner World starts today but here we are in San Francisco. Moscone North, I think south, and west they have here expecting about 25,000 people. No news yet today, Dave, so let's kind of talk about where IBM is right now with the early part of Q1 of 2019. Red Hat acquisition just approved by shareholders last month. What are your thoughts on the status of Big Blue? >> Well, I think you're right, Lisa, that the Red Hat news is the big news for IBM. We're now entering the next chapter but if you look back for the last five years IBM had to go out and pay two billion dollars for a soft layer to get into the cloud business. That was precipitated by the big, high profile loss of the CIA deal against Amazon. So that was a wake up call for IBM. So they got into the public cloud game. So that's the good news. The bad news is the public cloud's not easy when you're going up against the likes of Google and Microsoft and of course, Amazon. But the linchpin of IBM's cloud strategy is it's SAS portfolio. Over the last 20 years Steve Mills and his organization built a very large software business which they now have migrated into their cloud and so they've got that advantage much like Oracle. They're not a big, dominant cloud infrastructure as a service player but they have a platform where they can put things like Cognitive Solutions and Watson and offer those SAS services to clients. So you'll check on that but when you'll peel through the numbers IBM beat it's numbers last quarter. Stock was up. You know, when it announced the Red Hat acquisition the stock actually got crushed because when you spend 34 billion dollars on a company, you know the shareholders don't necessarily love that but we'll talk about the merits of that move. But they beat in the fourth quarter. They beat on the strength of services. So IBM remains largely a services company, about 60% plus of it's revenues comes from services. It's a somewhat lower margin business, even though IBM margins have been ticking up. As I say, you go back the last five, six years IBM Genesys did Mike's it's microelectronics business, which was a, you know, lost business. It got rid of it's x86 business which is a x86 server business, which is a low margin business. So again, like Oracle, it's focusing on high margin software and services and now we enter the era, Stu, of hybrid cloud with the Red Hat acquisition. A lot of money to pay, but it gets IBM into the next generation of multi cloud. >> Yeah, Dave, the knock I've had against IBM is in many ways they always try to be all things to all people and of course we know you can be good at some things but, you know, it's really tough to be great at everything. And, you know, you talked about cloud, Dave, you know, the SoftLayer acquisition to kind of get into public cloud but, you know, IBM is not one of the big players in public cloud. It's easy. It's Amazon and then followed by you know, Azure, Google, and let's talk Alibaba if we're talking globally. In a multi cloud world IBM has a strong play. As you said, they've got a lot of application assets, they have public cloud, they partner with a lot of the different cloud players out there and with Red Hat they get a key asset to be able to play across all of these multi cloud environments whether we're talking public cloud, private cloud, across all these environments. IBM's been pushing hard into the Kubernetes space, doing a lot with Istio. You know, where they play there, in Red Hat is a key piece of this puzzle. Red Hat running at about three billion dollars of revenue and paying 34 billion dollars but, you know, this is a linchpin as to say how does IBM stay relevant in this cloud world going forward? It's really a you know, a key moment for IBM as to what this means. A lot of discussion as to you know, it's not just the revenue piece but what will Red Hat do to the culture of IBM? IBM has a strong history in open source but you know, you got to, you have a large bench of Red Hat's strong executive team. We're going to see some of them here at the show. We're even going to have one Red Hat executive on our program here and so what will happen once this deal finally closes, which is expected later this year, probably October if you read, you know everything right. But what will it look like as to how will, you know, relatively small Red Hat impact the larger IBM going forward? >> Well, I think it's a big lever, right? I mean we were, Lisa, we were at Cisco Live in Barcelona last week kind of laying out the horses on the track for this multi cloud. Cisco doesn't own it's own public cloud. VMware and Dell don't own it's own public cloud. They both tried to get into the public cloud in the early days and IBM does own it's own public cloud as does Oracle but they're also going hard after this notion of multi cloud as is Cisco, as is VMware. So it sort of sets up the sort of Cisco, IBM Red Hat, VMware, Dell, sort of competing to get after that multi cloud revenue and then HPE fits in there somewhere. We can talk about that. >> So I saw a stat the other day that said in 2018, 80% of companies moved data or apps from public cloud. Reasons being security, control, cost, performance. So to some of the things I've read, Dave, that you've covered recently, if IBM isn't able to really go head to head against the Azures and the AWS, what is their differentiator in this new, hybrid multi cloud world? Is it being able to bring AI, Watson, Cognitive Solutions, better than their competitors in that space that you just mentioned? >> Yeah, IBM does complicate it. You know and cloud and hybrid cloud is complicated and so that's IBM's wheelhouse. And so it tends not to do commodity. So if it's complicated and sophisticated and requires a lot of services and a lot of business processing happening and things like that, IBM tends to excel. So, you know, if you do the SWOT analysis it's big opportunity is to be that multi-cloud provider for it's largest customers. And the larger customers are running, you know, transaction systems on mainframe. They're running cognitive systems on things like power. They've got a giant portfolio, at IBM that is, and they can cobble things together with their services and solve problems and that's kind of how IBM approaches the marketplace. Much different than say, Stu, Cisco or VMware. >> Yeah, Dave, you're absolutely right. You know one of the things I look at is you know, in this multi-cloud space we've see the SI's that are very important there. Companies like Accenture and KPMG and the like. IBM partners with them but IBM also has a large services business. So, you know who's going to be able to help customers get in there and figure out this rather complicated environment. So we are definitely one of the things I want to dig into this week is understand where IBM is at the Cisco Show, Dave. We've talked about their messaging was the bridge to you know what's possible. You know meet the customers where they are, show them how to reach into the future and from Cisco's standpoint, it's strong partnerships with AWS and Google at the forefront. So IBM has just one of the broadest portfolios in the industry. They absolutely play in every single piece but you know customers need good consulting as to Okay, what's going to be the fit for my business. How do I modernize, how do I go forward? And IBM's been down this trip for a number of years. >> Well the in the legacy of Ginni Rometty, in my opinion is going to be determined by the pace at which it can integrate Red Hat and use Red Hat as a lever. Ginni Rometty, when she was doing the roadshow with Jim Whitehurst kept saying it's not a backend loaded deal, and the reason it's not a backend loaded deal is because IBM is a 20 plus billion dollar outsourcing business and they're going to plug Red Hat right into that business to modernize applications. So there's a captive revenue source for IBM. In my view they have to really move fast, faster than typically IBM moves. We've been hearing about strategic initiatives and cloud, and Watson and it's been moving too slow in my opinion. The Red Hat acquisition has to move very very quickly. It's got to move at the speed of cloud and that's going to determine in my opinion-- >> So, actually, so a couple of weeks after the acquisition Red Hat had brought in an analyst to hear what was going on, and while the discussion is Red Hat will stay a distinct brand, there's going to be no lay offs were >> Yeah absolutely. >> Going to keep them separate, what they will get is IBM can really help them scale so >> Yep. Red Hat is getting into some new environments, you know that whole services organization, Red Hat doesn't have that. So IBM absolutely can plug in there and we think really accelerate, the old goal for Red Hat was okay how do we get from that three billion dollars to five billion dollars in the next couple of years. IBM thinks that they can accelerate that even faster. >> And Lisa I think the good news is IBM has always had an affinity toward open source. IBM was really the first, really to make a big investment you know they poured a billion dollars into Linux as a means of competing with Microsoft back in the day, and so they've got open source chops. So for those large IBM customers that might not want to go it alone on open source and you know Red Hat's kind of the cool kid on the block. But at the same time, you know there's some risks there. Now IBM can take that big blue blanket wrap it around it's largest customers and say okay, we've got you covered in open source, we've got the Red Hat asset, and we've got the services organization to help you modernize your application portfolio. >> One of the things too that Stu, you brought up a couple minutes ago is culture. And so looking at what, Red Hat estimates that it's got about eight million developers world wide using their technologies and this is an area that IBM had historically not been really focused on. What are some of the things that you're expecting to hear this week or see this week with respect to the developer community embracing IMB? >> Yeah and Lisa it's not like IBM hasn't been trying to get into the developer community. I remember back at some of the previous shows Edge and Pulse and the like, they would have you know Dev at and try to do a nice little piece of it but it really didn't gain as much traction as you might like. Compare and contrast that with cisco, we've been watching over the last five years the DevNet community. They've got over half a million developers on that platform. So you know, developer engagement usually requires that ground level activity where I've seen good work from IBM has been getting into that cloud native space. So absolutely seen them at the Kubernetes shows working in the container space very heavily and of course that's an area that Red Hat exceeds. So the Linux developers are absolutely there. Now you mentioned how many developers Red Hat has and in that multi cloud, cloud native space, you know Red Hat one of the leaders if not kind of the leader in that space and therefore it should help super charge what IBM is doing, give them some credibility. I'd love to see how many developers we see at this show, you know, you've been to this show Dave and you've been to this show before, it looked more enterprisey to me from the outside-- >> Well, I'm glad you brought up developers because that is the lynch pin of the Red Hat acquisition. If you look at the companies that actually have in the cloud that have a strong developer affinity obviously Microsoft does and always had AWS clearly does Google has you know it's developer community. Stu you mentioned Sisco. Sisco came at it from a networking standpoint and opened up it's network for infrastructure's code. One of the few legacy hardware companies that's done a good job there. VMware, you know not so much. Right? Not really a big developer world and IBM has tried as you pointed out. When they announced Bluemix but that really didn't take off in the developer world. Now with Red Hat IBM, it's your point eight million developers. That is a huge asset for IBM and one that as I said before it absolutely has to leverage and leverage fast. >> And what are you expectations in terms of any sort of industry deeper penetration? There's been some big cloud deals, cloud wins that IBM has made is recent history. One of them being really big in the energy sector. Are you guys kind of expecting to see any sort of industry deeper penetration as a result of what the Red Hat Acquisition will bring? >> Well thats IBM's strength. Stu you pointed out before, it's Accenture, you know Ernie Young, to a lesser extend maybe KPNG but those big SI's and IBM. When IBM bought PWC Gerstner transformed the company and it became a global leader with deep deep industry expertise. That is IBM's you know, savior frankly over these past many many years. So it can compete with virtually anybody on that front and so yes absolutely every industry is being transformed because of digital transformation. IBM understands this as well as anybody. It's a boon for services, it's a good margin business and so that's their competitive advantage. >> Yeah I mean it ties back into their services. I think back when I lived on the vendor side I learned a lot of the industry off of watching IBM. I see how many companies are talking about smarter cities. IBM had you know a long history of working In those environment's. Energy, industrial, IBM is very good at digging into the needed requirements of specific industries and driving that forward. >> So we're going to be here for four days as we mentioned, today is day one. We're going to be talking a lot about this hybrid multi-cloud world. But some of the double clicks we're going to do is talking about data protection, modern data protection, you know a lot of the statistics say that there's eighty percent of the worlds data isn't searchable yet. We all hear every event we do guys, data is the new oil. If companies can actually harness that, extract insights faster than their competition. Create new business models, new services, new products. What are your expectations about how, I hear a lot get your data AI ready. As a marketer I go, what does that mean? What are your thoughts Stu on, and we're sitting in a lot of signage here. How is IBM going to help companies get AI, Data rather AI ready and what does that actually mean? >> So IBM really educated a lot of the world and the broader world as to what some of this AI is. I mean I know we all watched many years ago when Watson was on Jeopardy and we kind of hit through the past the peak and have been trying to sort out okay well how can IBM monetize this? They're taking Watson and getting it into healthcare, they're getting it into all these other environments. So IBM is well known in the AI space. Really well known in the data space but there's a lot of competition and we're still relatively early in the sorting how this new machine learning and AI are going to fit in there. You know we spent a lot of time looking at things like RPA was kind of the gateway drug of AI if you will robotic process automation. And I'm not sure where IBM fit's into that environment. So once again IBM has always had a broad portfolio they do a lot of acquisitions in the space. So you know how can they take all those pieces, pull them together, get after the multicloud world, enable developers to be able to really leverage data even more that's possible and as you said you know more than eighty percent of data today isn't used, you know from an infrastructure stand point I'm looking at how do things like edge computing all get pulled into this environment and lot of questions still. >> IBM is going after hard problems like I said before. You don't expect IBM to be doing things like ad serving with Alexa. You know that's not IBM's game, they're not going to appropriate to sell ad's they're going to take really hard complex problems and charge a lot of money for big services engagements to transform companies. That's their game and that's a data game for sure. >> It's a data game and one of the pieces too that I'm excited to learn about this week is what they're doing about security. We all know you can throw a ton of technology at security and infrastructure but there's the people piece. So we're going to be having a lot of conversations about that as well. Alright guys looking forward to a full week with you and with John joining us at IBM Think I'm Lisa Martin for Dave Vellante and Stu Miniman. You're watching theCUBE live day one IBM Think 2019. Stick around we'll be right back with our next guest. (energetic electronic music)

>> 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)