>> From the SiliconANGLE Media office in Boston, Massachusetts, it's theCUBE! (upbeat electronic music) Now, here's your host, Dave Vellante. >> Hi, everybody, this is Dave Vellante, and I want to share with you some recent survey data that talks to the IBM acquisition of Red Hat, which closed today. It's always really valuable to go out, talk to practitioners, see what they're doing, and it's a hard thing to do. It's very expensive to get this type of survey data. A lot of times, it's very much out of date. You might remember. Some of you might remember a company called the InfoPro. Its founder and CEO was Ken Male, and he raised some money from Gideon Gartner, and he had this awesome survey panel. Well, somehow it failed. Well, friends of mine at ETR, Enterprise Technology Research, have basically created a modern version of the InfoPro. It's the InfoPro on steroids with a modern interface and data science behind it. They've now been at this for 10 years. They built a panel of 4,500 users, practitioners that they can go to, a lot of C level folks, a lot of VP level and then some doers down at the engineering level, and they go out and periodically survey these folks, and one of the surveys they did back in October was what do you think of the IBM-Red Hat acquisition? And then they've periodically gone out and talked to customers of both Red Hat and IBM or both to get a sense of the sentiment. So given that the acquisition closed today, we wanted to share some of that data with you, and our friends at ETR shared with us some of their drill down data with us, and we're going to share it with you. So first of all, I want to summarize something that they said. Back in October, they said, "We view this acquisition as less of an attempt "by IBM to climb into the cloud game, cloud relevance, "but rather a strategic opportunity "to reboot IBM's early 1990s IT services business strategy." I couldn't agree with that more. I've said all along this is a services play connecting OpenShift from Red Hat into the what Ginni Rometty talks about as the 80% of the install base that is still on prem with the workloads at the backend of mission critical systems that need to be modernized. That's IBM's opportunity. That's why this is a front end loaded cashflow deal 'cause IBM can immediately start doing business through it services organization and generate cash. They went on to say, ETR said, "Here, IBM could position itself "as the de facto IT services partner "for Fortune 100 to Global 2000 organizations "and their digital transformations. "Therefore, in theory, this could reinvigorate "the global services business for IBM "and their overlapping customer bases "could alow IBM to recapture and accelerate a great deal "of service revenues that they have lost "over the past few years." Again, I couldn't agree more. It's less about a cloud play. It is definitely about a multi-cloud play, which is how IBM's positioning this, but services de-risks this entire acquisition in my opinion even though it's very large, 34 billion. Okay, I'm show you some data. So pull up this slide. So what ETR does is they'll go out. So this is a survey of right after the acquisition of about 132 Global 2000 practitioners across a bunch of different industries, energy, utilities, financial services, government, healthcare, IT, telco, retail consumers, so a nice cross section of industries and largely in North America but a healthy cross section of AMIA and APAC. And again, these are large enterprises. So what this slide shows is conditioned responses, which I love conditioned responses. It sort of forces people to answer which of the following best describes. But this says, "Given IBM's intent to acquire Red Hat, "do you believe your organization will be more likely "to use this new combination "or less likely in your digital transformation?" You can see here on the left hand side, the green, 23% positive, on the right hand side, 13% negative. So, the data doesn't necessarily support ETR's original conclusions and my belief that this all about services momentum because most IT people are going to wait and see. So you can see the fat middle there is 64%. Basically you're saying, "Yeah, we're going to wait and see. "This really doesn't change anything." But nonetheless, you see a meaningfully more positive sentiment than negative sentiment. The bottom half of this slide shows, the question is, "Do you believe that this acquisition "makes or will make IBM a legitimate competitor "in the cloud wars between AWS and Microsoft Azure?" You can see on the left hand side, it says 45% positive. Very few say, all the way on the left hand side, a very legitimate player in the cloud on par with AWS and Azure. I don't believe that's the case. But a majority said, "IBM is surely better off "with Red Hat than without Red Hat in the context of cloud." Again, I would agree with that. While I think this is largely a services play, it's also, as Stu Miniman pointed out in an earlier video with me, a cloud play. And you can see it's still 38% is negative on the right hand side. 15% absolutely not, IBM is far behind AWS and Azure in cloud. I would tend to agree with that, but IBM is different. They're trying to bring together its entire software portfolio so it has a competitive approach. It's not trying to take Azure and AWS head on. So you see 38% negative, 45% positive. Now, what the survey didn't do is really didn't talk to multi-cloud. This, to me, puts IBM at the forefront of multi-cloud, right in there with VMware. You got IBM-Red Hat, Google with Anthos, Cisco coming at it from a network perspective and, of course, Microsoft leveraging its large estate of software. So, maybe next time we can poke at the multi-cloud. Now, that survey was done of about over 150, about 157 in the Global 2000. Sorry, I apologize. That was was 137. The next chart that I'm going to show you is a sentiment chart that took a pulse periodically, which was 157 IT practitioners, C level executives, VPs and IT practitioners. And what this chart shows essentially is the spending intentions for Red Hat over time. Now, the green bars are really about the adoption rates, and you can see they fluctuate, and it's kind of the percentage on left hand side and time is on the horizontal axis. The red is the replacement. We're going to replace. We're not going to buy. We're going to replace. In the middle is that fat middle, we're going to stay flat. So the yellow line is essentially what ETR calls market share. It's really an indication of mind share in my opinion. And then the blue line is spending intentions net score. So what does that mean? What that means is they basically take the gray, which is staying the same, they subtract out the red, which is we're doing less, and they add in the we're going to do more. So what does this data show? Let's focus on the blue line. So you can see, you know, slightly declining, and then pretty significantly declining last summer, maybe that's 'cause people spend less in the summer, and then really dropping coming into the announcement of the acquisition in October of 2018, IBM announced the $34 billion acquisition of Red Hat. Look at the spike post announcement. The sentiment went way up. You have a meaningful jump. Now, you see a little dip in the April survey, and again, that might've been just an attenuation of the enthusiasm. Now, July is going on right now, so that's why it's phased out, but we'll come back and check that data later. So, and then you can see this sort of similar trend with what they call market share, which, to me, is, again, really mind share and kind of sentiment. You can see the significant uptick in momentum coming out of the announcement. So people are generally pretty enthusiastic. Again, remember, these are customers of IBM, customers of Red Hat and customer of both. Now, let's see what the practitioners said. Let's go to some of the open endeds. What I love about ETR is they actually don't just do the hardcore data, they actually ask people open ended questions. So let's put this slide up and share with you some of the drill down statements that I thought were quite relevant. The first one is right on. "Assuming IBM does not try to increase subscription costs "for RHEL," Red Hat Enterprise Linux, "then its organizational issues over sales "and support should go away. "This should fix an issue where enterprises "were moving away from RHEL to lower cost alternatives "with significant movement to other vendors. "This plus IBM's purchase of SoftLayer and deployment "of CloudFoundry will make it harder "for Fortune 1000 companies to move away from IBM." So a lot implied things in there. The first thing I want to mention is IBM has a nasty habit when it buys companies, particularly software companies, to raise prices. You certainly saw this with SPSS. You saw this with other smaller acquisitions like Ustream. Cognos customers complained about that. IBM buys software companies with large install bases. It's got a lock in spec. It'll raise prices. It works because financially it's clearly worked for IBM, but it sometimes ticks off customers. So IBM has said it's going to keep Red Hat separate. Let's see what it does from a pricing standpoint. The next comment here is kind of interesting. "IBM has been trying hard to "transition to cloud-service model. "However, its transition has not been successful "even in the private-cloud domain." So basically these guys are saying something that I've just said is that IBM's cloud strategy essentially failed to meet its expectations. That's why it has to go out and spend $34 billion with Red Hat. While it's certainly transformed IBM in some respects, IBM's still largely a services company, not as competitive as cloud as it would've liked. So this guys says, "let alone in this fiercely competitive "public cloud domain." They're not number one. "One of the reasons, probably the most important one, "is IBM itself does not have a cloudOS product. "So, acquiring Red Hat will give IBM "some competitive advantage going forward." Interesting comments. Let's take a look at some of the other ones here. I think this is right on, too. "I don't think IBM's goal is to challenge AWS "or Azure directly." 100% agree. That's why they got rid of the low end intel business because it's not trying to be in the commodity businesses. They cannot compete with AWS and Azure in terms of the cost structure of cloud infrastructure. No way. "It's more to go after hybrid multi-cloud." Ginni Rometty said today at the announcement, "We're the only hybrid multi-cloud, opensource vendor out there. Now, the third piece of that opensource I think is less important than competing in hybrid and multi-cloud. Clearly Red hat gives IMB a better position to do this with CoreOS, CentOS. And so is it worth 34 billion? This individual thinks it is. So it's a vice president of a financial insurance organization, again, IBM's strong house. So you can here some of the other comments here. "For customers doing significant business "with IBM Global Services teams." Again, outsourcing, it's a 10-plus billion dollar opportunity for IBM to monetize over the next five years, in my opinion. "This acquisition could help IBM "drive some of those customers "toward a multi-cloud strategy "that also includes IBM's cloud." Yes, it's a very much of a play that will integrate services, Red Hat, Linux, OpenShift, and of course, IBM's cloud, sprinkle in a little Watson, throw in some hardware that IBM has a captive channel so the storage guys and the server guys can sell their hardware in there if the customer doesn't care. So it's a big integrated services play. "Positioning Red Hat, and empowering them "across legacy IBM silos, will determine if this works." Again, couldn't agree more. These are very insightful comments. This is a largely a services and an integration play. Hybrid cloud, multi-cloud is complex. IBM loves complexity. IBM's services organization is number one in the industry. Red Hat gives it an ingredient that it didn't have before other than as a partner. IBM now owns that intellectual property and can really go hard and lean in to that services opportunity. Okay, so thanks to our friends at Enterprise Technology Research for sharing that data, and thank you for watching theCUBE. This is Dave Vellante signing off for now. Talk to you soon. (upbeat electronic music)

>> Live from Las Vegas, it's theCUBE! Covering Dell Technologies World 2019. Brought to you by Dell Technologies and its ecosystem partners. >> Hello everyone, welcome to theCUBE's live coverage here in Las Vegas for Dell Technologies World 2019. I'm John Furrier, Stu Miniman, Dave Vellante. Day two of three days of wall-to-wall coverage. We got two sets called theCube Cannon. We've got the Cannon of Content, interviews all day long, out at night at the analyst briefings, meet-ups, receptions, talking to all the executives at Dell Technologies VMware and across the industry. Stu, Dave, today is product announcements on the keynotes. Yesterday was the grand vision with Michael Dell and the big reveal on the Microsoft partnership with Satya Nadella's surprise visit onstage, unveiling new Azure-VMware integrations with Dell Technologies. Dell announced the Dell Cloud, which is a little bit of Virtustream, but they're trying to position this cloud, I guess it's a cloud if you want to call it a single cloud of glass. Dave, single pane in the glass with a variety of other things, unified workspace and some other things. This is Dell trying to be a supplier end-to-end. This is the pitch from Dell Technologies. We'll be talking to Michael Dell, also Pat Gelsinger, the CO of VMware. Dave, were you impressed, were you shocked, were you surprised with yesterday's big news and as the products start coming online here, what's your analysis? >> Well yesterday, John, was all about the big strategic vision, Michael Dell laying out check for good and then the linchpin of Dell strategy which of course is VMware for cloud, multicloud, hybrid cloud, kind of VMware everywhere. I was surprised that Satya Nadella flew down from Seattle and was here on stage in person. Didn't come in from the big screen. So I thought that was pretty impressive. You had the three power players up on stage. Today of course was all about the products. Both Dell and EMC have always been very practical in terms of their engineering. Stu, you used to work there. Their R&D is a lot of D. It's sort of incremental product improvements to keep the customers happy, to keep ahead of the competition, to keep the lifecycle going. They had like 10 announcements today. I can go through 'em real quick if you want, but they range from new laptops to talking about new branding on servers, new storage devices. You had PowerProtect which is their new rebranded backup and data protection and data manage portfolio, an area where Dell EMC has been behind. So lots of announcements. Another kind of mega launch tradition and again, a lot of incremental but important tactical improvements to the product line. >> Last year, what we heard from Jeff Clarke is they're looking to simplify that portfolio. Back in the EMC days, it was oh my gosh, look at the breadth of this. Every category, they had two or three offerings and you know, the stated goal is to simplify that and that means most categories are going to get one product. It's interesting. You talk about networking just got rebranded with that Power branding. I kind of said there there's marketing behind it. If you know what that product is because it's the Power brand and they put it out there. So you know, PowerMax, has been their tiered storage. They had a good update for Unity. It's Unity XT. Doesn't have a power name yet so maybe there's still some dry powder left in the product portfolio there, but they're making progress going through this 'cause these things don't happen overnight. It's great to spin up the clouds, but in the storage world, customers, they trust, they have the code, they test it out. So going to new generations, making that change, does take time but you've seen that progress. The tail end of that integration between Dell and EMC on the product side. >> Stu, what's your analysis of the products so far 'cause again like Dave said, it's a slew of announcements. What's resonating, what's popping out, what's boiling up to the surface? >> Yeah so look, the area that I spent so much time on, John, that hyper-converged infrastructure. If you look at a lot of the pieces underneath it all, it's VxRail. One of the things we've had a little bit of a challenge squinting through is oh wait, there's this managed service stack, it's VxRail underneath. Oh wait I've taken the appliance and I put VCF. Oh that's VxRail and then I've got this other, it's like I see three or four solutions and I'm like is it all just VxRail with like a VMware stack on top of it? But it's how do I package it, what applications live on it, how is it consumed, manage service, op ex, cap ex. So they've got that a little bit of complexity when VxRail itself is you know, dirt simple and really there so they're making progress on the cloud piece. Dell is the leader in hyper-converged. I'll point out, you don't hear anybody talking about Nutanix here, but Dell still has a partnership on the XC Core. They're going to sell a lot of Dell servers into Nutanix environment so I expect you'll still have the Nutanix show. John you're going to be at that next week. They're still going to talk about Dell. I'm sure you'll talk to Dheeraj. Yes they made a partnership with HP, but that does not kill the relationship with Nutanix just like Microsoft, heck. I'm going to see Satya Nadella on stage at Red Hat Summit next week and you're like oh well VMware and Red Hat. Red Hat's here. Red Hat's a Dell-ready partner. If you want to put open shift on top of their stack, they can do that so hardware and software, everybody's got their pieces, everybody's got their pieces, everybody competes a lot, but they partner across the board. IBM Global Services is here. There's so many companies here. Dell's a broad company, deep partnerships. The question I have is Pat Gelsinger was just on stage saying that this SDDC will be the building block for the future. I said kudos to them. They've got it on AWS, they've got it announced with Azure, we announced it with Google, but that is not necessarily the end state. VMware is a piece of the puzzle. I don't know if VMware will be the leader in multicloud management. vCenter was the leader in virtualization management so how much of that will there or do I get an Amazon and then start moving some stuff over? Do I get to Azure and start modernizing my environment so that I don't need to pay VMware and I don't need virtualization. VMware and Dell are going to containerize everything so in the future, are they containerware, you know? That's the competition kind of post-it note. They are VMware at their core. VMware is centra of the strategy and there's still some work to go, but they're making some good progress. >> I want to get your thoughts, guys, on the role VMware is playing here at the show. Normally they're here, usually they're here, but this year it seems to be much more smoother integration of talking points, messaging, product integrations. The show's got a good beat to it. Pretty packed, but the role of VMware, Dave, Stu, what's your reaction and thoughts? We've seen them dance all the time. Obviously VMware, Dave as you pointed out yesterday, a big part of the valuation of Dell Technologies, but what's your observation on the presence of VMware here at Dell Technologies World? >> I mean I've said many times that this company and I said this about EMC, it's kind of a boring company without VMware. You put VMware in the mix and all of a sudden, it becomes very strategic and very interesting from a lot of standpoints. Certainly from a financial standpoint. Remember, the Class V transaction that took Dell public was the result of an $11 billion dividend because of VMware. They took VMware's cash and they said okay, we're going to give nine billion to the shareholders. Without VMware, that wouldn't have happened. As well, the multicloud strategy, the underpinning of that multicloud strategy is VMWare. What strikes me, John and Stu, is that the cultural change. You had Dell, you had EMC. They said ah yeah the companies are compatible, but they're different companies. They maybe had shared kind of goals and values, but they had different cultures and really in a short timeframe, Michael Dell and his team have put these two companies together and they have aligned in a big way. I mean they are basically saying VMware and Dell, boom. That's how we're going to market and you know, Pat's coming on later today and I'm sure he'll say hey we love NetApp, we love HBE, we love IBM, but it's clear what the preferred partnership is. >> Dave, when the acquisition happened, there was talks of synergies and we were like oh where are they going to cut everything? If I look around here, they've got the seven logos of the primary companies. It's Dell, Dell EMC, Pivotal, RSA, Secureworks, Virtustream and VMware. They're one company. Michael Dell will go on calls for any of them. Friends of mine at Pivotal says you talk to Michael quite a bit. You know, he's out there. We talked about it yesterday. Dell and VMware are closer and tighter aligned than EMC and VMware ever were. Now on the one hand, EMC kept them separate because the growth of virtualization required that. Today in this cloud environment, it's a different world and it's matured so VMware, sure, there's still work on HP and IBM and all this other stuff, but Dell leads that move as you said, Dave. >> John, you're big on culture. This is a founder culture. What's your take on what Michael Dell has accomplished and how does it stand to compare with sort of other great cultural transformations that you've seen? >> Well I think HBE is a great example of a culture that split, was uncharged there. We know what happened there and I think they're hurting, they're losing talent and they're not winning in categories across the board like Dell is. I think Michael Dell, the founder-led approach that he's having 'cause he told us years ago, if you guys remember, here on the record, also privately that I'm going to take this off the table with EMC and I'm going to do all these things. We're going to execute. So he brought his execution mojo and ecos of Dell and become Dell Technologies, as Stu pointed out, a portfolio of multiple companies under one umbrella and he brought the execution discipline and this is a theme, Dave. Last night at the analysts reception, as I was talking to other analysts and talking to some of the execs, both from VMware and Dell Technologies, that the execution performance across the board both on product integration, which was a weak spot as you know, is getting better, the business performance discipline. We're going to have the CFO on here to talk more about it, they're executing. Howard Elias is going to be on this afternoon. He called this three years ago when he was talking about the integration that they saw synergies, they saw opportunities and they were going to unpack those. They stayed relentless on that. So I think this is a great example of keeping the founders around for all the VC-backed companies. You're thinking about getting rid of founders. Never let a founder leave a company. They bring the vision, they bring also some guts and grit and they bring a perspective and you can put great talent and team around that, that attract and retain great executives like Michael's done and he's poaching HPE, other companies and pulling talent in 'cause they're executing. They pay well, it's a great place to work according to the statistics. So again, this is all because of the founder and if the founder's not around, you have all the fiefdoms and the policists who kick in and then it becomes kind of sideways. So that's kind of what I see other companies that don't have founders around and HP lost their founders obviously and then the culture kind of went a little bit sideways. So they're trying to get back in the game, seeing them go back to their roots. We'll see how they do. We don't do that show anymore and again we don't have a lot of visibility into what HP's doing but we do know, Dave, that they do not have a lot of the pieces on the board that Dell does. So if you want to have an end-to-end operating model, and you're missing key value activities of an end-to-end value chain, that's going to be hard to automate, it's hard to be a performant, it's going to be hard to be successful. So I think Dell is showing the playbook of how to be horizontally scalable operationally and offer perspectives and data-driven specialism in any industry in any vertical. >> Yeah Dave, if I can just on the cultural piece 'cause it's really interesting. You talked about EMC, East Coast hard driving versus VMware, software, Silicon Valley company. While they're working together, a lot of it, you know, I talk to VMware people and they're like well it's great the Dell force is just selling our stuff. It's not like I'm having storage shoved down my throat or we have to have our arms twisted. It's the product portfolio that they're selling, the vSAN, NSX, the management software suite and those pieces, things like SD-WAN, there's some good synergies there. So the product portfolio is a nice fit that just jointly go out to market that they just really line up well together and Dell's a very different cultural beast than EMC was. >> Well again, staying on culture for a moment, when I discussed with some of the folks that I know out of Hopkinton the narrative early on was oh Dell's ruining EMC, tearing it apart and so forth. When you talk to people today, they say, you know what, it was painful. Dell came in and said okay, you're going to be accountable, really had an accountability culture, but now they've come out the other side, the narrative is it was the right thing to do. Jeff Clarke came in and sort of forced this alignment. There's like no question about it. People, this is a guy who you know, his calendar's set for the year. People know where he's going to be, what meeting he's going to have, what's expected and they're prepared and it seems to be taking hold. I mean if a $90 billion company that's growing at 14% in revenues, in profitable revenues, that's quite astounding when you think about it and I think it's a big result of the speed at which Dell has brought in its operating model to the broader EMC and transformed itself. It's quite amazing. >> Awesome show, guys. We've got clips out there on the #DellTechWorld on Twitter. We've got a lot of videos. We've got two sets here, three days of wall-to-wall coverage. Final word on this intro for day two, guys. Thoughts on the show? It's not a boring show. It's a lot of activities, a lot of things. They've got an Alienware eSports gaming studio which I think is totally badass. A lot of kind of cool things here. It's not the glitz and glam that we've seen in other EMC Worlds before or Dell Worlds, but it's meat and potatoes and it's got a spring to its step here. I feel it's not, it feels good. That's my takeaway. >> Well the big theme is hybrid cloud and multicloud. Jon Rowe as we were leaving the room today that we were early with that multicloud. Thanks for everybody else in the industry for hopping on board. The reality is the first time I heard the sort of hybrid cloud was called private cloud. Chuck Hollis wrote a blog back in the mid to late 2000s. Now I will make an observation in the customers that I talk to. Multicloud is not thus far, has not thus far has been a deliberate strategy. In my opinion, it's been the outcropping of multivendor, shadow IT, lines of business and I think the corner office is saying hold on, we need to reign this in, we need to have a better understanding of what our cloud strategy is, build a platform that is hybrid and sure, multicloud, to build our digital transformation. We need IT to basically help us build this out to make sure we comply with the corporate edicts and that's what's happening. It is early days. There's a long way to go. >> Yeah, as Dave, as you know, I sat right down the hallway from Chuck Hollis when he wrote that piece and I went and I called up Chuck and I was like hey Chuck, this sure sounds like my next generation virtual data center stuff that I joined the CTO office to work on and he's like yeah, yeah, new marketing branding and I wrote a piece, exactly what you said, Dave, on Wikibon.com, hybrid and multicloud were a bunch of pieces, you know. It's not a cohesive strategy. The management's not there. We're starting to see maturation. Some of the point products, you know, developed really fast. When we talk about VMware on AWS, that happened really fast. I heard if you stop by the VMware booth here at the show, they're showing outposts and I said is a diagram? No, no, I've got customers in production running this. I'm like hold on, I need to hear about this. Outpost in production? But that strategy as you said, hybrid and multicloud, we're starting to get there, starting to pull it together. David Foyer wrote a phenomenal piece about hybridcloud taxonomy. We've spent a lot of time on the research side. Really what does the industry need to do, how should customers think about all of the layers? You know, data and networking and all of these components to help make not just a bunch of pieces but actually drive innovation and help be better than the sum of its parts. >> Well ironic followup on that post, the Chuck Hollis post was around they called it the private cloud and it was all about homogeneity and now multicloud is everything but homogeneous. Outpost, however, is. Same hardware, same software, same control plane, same data plane so interesting juxtaposition. >> We'll see Amazon Outpost. Guys, go to SiliconAngle.com, Wikibon.com. Great hybridcloud, multicloud analysis coverage and news. And some of the headlines hitting the net here. Dell Technologies makes VMware linchpin of hybrid cloud, data center as a service, end user strategies from Zdnet. eWEEK, Dell makes major hybrid cloud push. Obviously great analysis, guys, right on the number. Day two, CUBE coverage here in Las Vegas. I'm John Furrier, Dave Vellante, Stu Miniman. We've got two sets. Rebecca Knight, Lisa Martin and more. Stay tuned for more coverage of day two after the short break. (upbeat music)

>> live from Las Vegas. It's the queue covering Dell Technologies. World twenty nineteen. Brought to you by Dell Technologies and its ecosystem partners. >> The one Welcome to the Special Cube Live coverage here in Las Vegas with Dell Technologies World 2019. I'm John Furrier with Dave Vellante breaking down day one of three days of wall the wall Coverage - 2 Cube sets. Uh, big news today and dropping here. Dell Technology World's series of announcements Cloud ability, unified work spaces and then multi cloud with, uh, watershed announced with Microsoft support for VMware with Azure are guests here theCUBE alumni that Seo, senior leader of'Em Where Sanjay *** and such a great to see you, >> John and Dave always a pleasure to be on your show. >> So before we get into the hard core news around Microsoft because you and Satya have a relationship, you also know Andy Jassy very well. You've been following the Clouds game in a big way, but also as a senior leader in the industry and leading BM where, um, the evolution of the end user computing kind of genre,  that whole area is just completely transformed with mobility and cloud kind of coming together with data and all this new kinds of applications. The modern applications are different. It's changing the game on how end users, employees, normal people use computing because some announcement here on their What's your take on the ever changing role of cloud and user software? >> Yeah, John, I think that our vision , as  you know, it was the first job I came to do at VMware almost six years ago, to run and use a computing. And the vision we had at that time was that you should be able to work at the speed of life, right? You and I happen to be on a plane at the same time  yesterday coming here, we should be able to pick our amps up on our devices. You often have Internet now even up at thirty thousand feet. In the consumer world, you don't lug around your CDs, your music, your movies come to you. So the vision of any app on any device was what we articulated with the digital workspace We. had Apple and Google very well figured out. IOS later on Mac,  Android,  later on chrome . The Microsoft relationship in end use the computing was contentious because we overlapped. They had a product, PMS and in tune. But we always dreamed of a day. I tweeted out this morning that for five and a half years I competed with these guys. It was always my dream to partner with the With Microsoft. Um, you know, a wonderful person, whom I respect there, Brad Anderson. He's a friend, but we were like LeBron and Steph Curry. We were competing against each other. Today everything changed. We are now partners. Uh, Brad and I we're friends, we'll still be friends were actually partners  now why? Because we want to bring the best of the digital workspace solution VMware brings workspace one to the best of what Microsoft brings in Microsoft 365 , active directory, E3 capabilities around E. M. S and into it and combined those together to help customers get the best for any device. Apple, Google and Microsoft that's a game changer. >> Tell about the impact of the real issue of Microsoft on this one point, because is there overlap is their gaps, as Joe Tucci used to say, You can't have any. There's no there's no overlap if you have overlapped. That's not a >> better to have overlapped and seems right. A gaps. >> So where's the gaps? Where this words the overlapping cloud. Next, in the end user world, >> there is a little bit of overlap. But the much bigger picture is the complementarity. We are, for example, not trying to be a directory in the Cloud That's azure active directory, which is the sequel to Active Directory. So if we have an identity access solution that connect to active directory, we're gonna compliment that we've done that already. With Octo. Why not do that? Also inactive Directory Boom that's clear. Ignored. You overlap. Look at the much bigger picture. There's a little bit of overlap between in tune and air Watch capabilities, but that's not the big picture. The big picture is combining workspace one with E. M s. to allow Office 365 customers to get conditional access. That's a game, so I think in any partnership you have to look past, I call it sort of these Berlin Wall moments. If the U. S and Soviet Union will fighting over like East Germany, vs West Germany, you wouldn't have had that Berlin wall moment. You have to look past the overlaps. Look at the much bigger picture and I find the way by which the customer wins. When the customer wins, both sides are happy. >> Tearing down the access wall, letting you get seamless. Access the data. All right, Cloud computing housely Multi cloud announcement was azure something to tell on stage, which was a surprise no one knew was coming. No one was briefed on this. It was kind of the hush hush, the big news Michael Delll, Pat Girl singer and it's nothing to tell up there. Um, Safia did a great job and really shows the commitment of Microsoft with the M wear and Dell Technologies. What is this announcement? First, give us your take an analysis of what they announced. And what does it mean? Impact the customers? >> Yeah, listen, you know, for us, it's a further That's what, like the chess pieces lining up of'Em wars vision that we laid up many years for a hybrid cloud world where it's not all public cloud, it isn't all on premise. It's a mixture. We coined that Tom hybrid loud, and we're beginning to see that realize So we had four thousand cloud providers starting to build a stack on VM, where we announced IBM Cloud and eight of us. And they're very special relationships. But customers, some customers of azure, some of the retailers, for example, like Wal Mart was quoted in the press, released Kroger's and some others so they would ask us, Listen, we're gonna have a way by which we can host BMO Workloads in there. So, through a partnership now with Virtue Stream that's owned by Dell on DH er, we will be able to allow we, um, where were close to run in Virtue Stream. Microsoft will sell that solution as what's called Azure V M, where solutions and customers now get the benefit of GMO workloads being able to migrate there if they want to. Or my great back on the on premise. We want to be the best cloud infrastructure for that multi cloud world. >> So you've got IBM eight of us Google last month, you know, knock down now Azure Ali Baba and trying you. Last November, you announced Ali Baba, but not a solution. Right >> now, it's a very similar solutions of easy solution. There's similar what's announced with IBM and Nash >> So is it like your kids where you loved them all equally or what? You just mentioned it that Microsoft will sell the VM wear on Azure. You actually sell the eight of us, >> so there is a distinction. So let me make that clear because everything on the surface might look similar. We have built a solution that is first and preferred for us. Called were MacLeod on a W s. It's a V m er manage solution where the Cloud Foundation stack compute storage networking runs on a ws bare metal, and V. Ember manages that our reps sell that often lead with that. And that's a solution that's, you know, we announced you were three years ago. It's a very special relationship. We have now customer attraction. We announce some big deals in queue, for that's going great, and we want it even grow faster and listen. Eight of us is number one in the market, but there are the customers who have azure and for customers, one azure very similar. You should think of this A similar to the IBM ah cloud relationship where the V C P. V Partners host VM where, and they sell a solution and we get a subscription revenue result out of that, that's exactly what Microsoft is doing. Our reps will get compensated when they sell at a particular customer, but it's not a solution that's managed by BM. Where >> am I correct? You've announced that I think a twenty million dollars deal last quarter via MacLeod and A W. And that's that's an entire deal. Or is that the video >> was Oh, that was an entirely with a customer who was making a big shift to the cloud. When I talked to that customer about the types of workloads, they said that they're going to move hundreds off their APs okay on premise onto via MacLeod. And it appears, so that's, you know, that's the type of cloud transformation were doing. And now with this announcement, there will be other customers. We gave an example of few that Well, then you're seeing certain verticals that are picking as yours. We want those two also be happy. Our goal is to be the undisputed cloud infrastructure for any cloud, any cloud, any AP any device. >> I want to get your thoughts. I was just in the analysts presentation with Dell technology CFO and looking at the numbers, the performance numbers on the revenue side Don Gabin gap our earnings as well as market share. Dell. That scales because Michael Delll, when we interviewed many years ago when it was all going down, hinted that look at this benefits that scale and not everyone's seeing the obvious that we now know what the Amazon scale winds so scale is a huge advantage. Um, bm Where has scale Amazon's got scale as your Microsoft have scales scales Now the new table stakes just as an industry executive and leader as you look at the mark landscape, it's a having have not world you'd have scale. You don't If you don't have scale, you're either ecosystem partner. You're in a white space. How do companies compete in this market? Sanjay, what's your thoughts on I thinkit's >> Jonah's? You said there is a benefit to scale Dell, now at about ninety billion in revenue, has gone public on their stock prices. Done where Dellvin, since the ideal thing, the leader >> and sir, is that point >> leader in storage leader inclined computing peces with Vienna and many other assets like pivotal leaders and others. So that scale VM, Where about a ten billion dollar company, fifth largest software company doing verywell leader in the softer to find infrastructure leader, then use a computing leader and softer, defined networking. I think you need the combination of scale and speed, uh, just scale on its own. You could become a dinosaur, right? And what's the fear that every big company should have that you become ossified? And I think what we've been able to show the world is that V M wear and L can move with scale and speed. It's like having the combination of an elephant and a cheetah and won and that to me special. And for companies like us that do have scaled, we've to constantly ask ourselves, How do we disrupt ourselves? How do we move faster? How do we partner together? How do we look past these blind spots? How do we pardon with big companies, small companies and the winner is the customer. That's the way we think. And we could keep doing that, you'll say so. For example, five, six years ago, nobody thought of VMware--this is going before Dell or EMC--in the world of networking, quietly with ten thousand customers, a two million dollar run rate, NSX has become the undisputed leader and software-defined networking. So now we've got a combination of server, storage and a networking story and Dell VMware, where that's very strong And that's because we moved with speed and with scale. >> So of course, that came to an acquisition with Nice Sarah. Give us updates on the recent acquisitions. Hep C e o of Vela Cloud. What's happening there? >> Yeah, we've done three. That, I think very exciting to kind of walk through them in chronological order about eighteen months ago was Velo Cloud. We're really excited about that. It's sort of like the name, velocity and cloud fast. Simple Cloud based. It is the best solution. Ston. How do we come to deciding that we went to talk to our partners like t other service providers? They were telling us this is the best solution in town. It connects to the data center story to the cloud story and allows our virtual cloud network to be the best softer. To find out what you can, you have your existing Mpls you might have your land infrastructure but there's nobody who does softer to find when, like Philip, they're excited about that cloud health. We're very excited about that because that brings a multi cloud management like, sort of think of it like an e r P system on top of a w eso azure to allow you to manage your costs and resource What ASAP do it allows you to manage? Resource is for materials world manufacturing world. In this world, you've got resources that are sitting on a ws or azure. Uh, cloud held does it better than anybody else. Hefty. Oh, now takes a Cuban eighty story that we'd already begun with pivotal and with Google is you remember at at PM world two years ago. And that's that because the founders of Cuban eighties left Google and started FTO. So we're bringing that DNA we've become now one of the top two three contributors to communities, and we want to continue to become the de facto platform for containers. If you go to some of the airports in San Francisco, New York, I think Keilani and Heathrow to you'LL see these ads that are called container where okay, where do you think the Ware comes from Vienna, where, OK, and our goal is to make containers as container where you know, come to you from the company that made vmc possible of'Em where So if we popularized PM's, why not also popularised the best enterprise contain a platform? That's what helped you will help us do >> talk about Coburn at ease for a minute because you have an interesting bridge between end user computing and their cloud. The service is micro. Services that are coming on are going to be powering all these APS with either data and or these dynamic services. Cooper, Nettie sees me the heart of that. We've been covering it like a blanket. Um, I'm gonna get your take on how important that is. Because back Nelson, you're setting the keynote at the Emerald last year. Who burn it eases the dial tone. Is Cooper Netease at odds with having a virtual machine or they complimentary? How does that evolving? Is it a hedge? What's the thoughts there? >> Yeah, First off, Listen, I think the world has begun to realize it is a world of containers and V ems. If you looked at the company that's done the most with containers. Google. They run their containers in V EMS in their cloud platform, so it's not one or the other. It's vote. There may be a world where some parts of containers run a bare metal, but the bulk of containers today run and Beyonce And then I would say, Secondly, you know, five. Six years ago, people all thought that Doctor was going to obliterate VM where, But what happened was doctors become a very good container format, but the orchestration layer from that has not become daugher. In fact, Cuban Eddie's is kind of taking a little of the head and steam off Dr Swarm and Dr Enterprise, and it is Cooper Navy took the steam completely away. So Senses Way waited for the right time to embrace containers because the obvious choice initially would have been some part of the doctor stack. We waited as Borg became communities. You know, the story of how that came on Google. We've embraced that big time, and we've stated a very important ball hefty on All these moves are all part of our goal to become the undisputed enterprise container platform, and we think in a multi cloud world that's ours to lose. Who else can do multi cloud better than VM? Where may be the only company that could have done that was Red Hat. Not so much now, inside IBM, I think we have the best chance of doing that relative. Anybody else >> Sanjay was talking about on our intro this morning? Keynote analysis. Talking about the stock price of Dell Technologies, comparing the stock price of'Em where clearly the analysis shows that the end was a big part of the Dell technologies value. How would you summarize what v m where is today? Because on the Kino there was a Bank of America customers. She said she was the CTO ran, she says, Never mind. How we got here is how we go floors the end wars in a similar situation where you've got so much success, you always fighting for that edge. But as you go forward as a company, there's all these new opportunities you outlined some of them. What should people know about the VM? We're going forward. What is the vision in your words? What if what is VM where >> I think packed myself and all of the key people among the twenty five thousand employees of'Em are trying to create the best infrastructure company of all time for twenty one years. Young. OK, and I think we have an opportunity to create an incredible brand. We just have to his use point on the begins show create platforms. The V's fear was a platform. Innocent is a platform workspace. One is a platform V san, and the hyper convert stack of weeks right becomes a platform that we keep doing. That Carbonetti stuff will become a platform. Then you get platforms upon platforms. One platforms you create that foundation. Stone now is released. ADelle. I think it's a better together message. You take VX rail. We should be together. The best option relative to smaller companies like Nutanix If you take, you know Veum Where together with workspace one and laptops now put Microsoft in the next. There's nobody else. They're small companies like Citrix Mobile. I'm trying to do it. We should be better than them in a multi cloud world. They maybe got the companies like Red Hat. We should have bet on them. That said, the end. Where needs toe also have a focus when customers don't have Dale infrastructure. Some people may have HP servers and emcee storage or Dell Silvers and netapp storage or neither. Dellery emcee in that case, usually via where, And that's the way we roll. We want to be relevant to a multi cloud, multi server, multi storage, any hardware, any cloud. Any AP any device >> I got. I gotta go back to the red hat. Calm in a couple of go. I could see you like this side of IBM, right? So So it looks like a two horse race here. I mean, you guys going hard after multi cloud coming at it from infrastructure, IBM coming at it with red hat from a pass layer. I mean, if I were IBM, I had learned from VM where leave it alone, Let it blossom. I mean, we have >> a very good partisan baby. Let me first say that IBM Global Services GTS is one about top sai partners. We do a ton of really good work with them. Uh, I'm software re partner number different areas. Yeah, we do compete with red hat with the part of their portfolios. Relate to contain us. Not with Lennox. Eighty percent plus of their businesses. Lennox, They've got parts of J Boss and Open Stack that I kind of, you know, not doing so well. But we do compete with open ship. That's okay, but we don't know when we can walk and chew gum so we can compete with Red Hat. And yet partner with IBM. That's okay. Way just need to be the best at doing containing platform is better than open shifter. Anybody, anything that red hat has were still partner with IBM. We have to be able to look at a world that's not black and white. And this partnership with Microsoft is a good example. >> It's not a zero sum game, and it's a huge market in its early days. Talk >> about what's up for you now. What's next? What's your main focus? What's your priorities? >> Listen, we're getting ready for VM World now. You know in August we want to continue to build momentum on make many of these solutions platforms. So I tell our sales reps, take the number of customers you have and add a zero behind that. OK, so if you've got ten thousand customers of NSX, how do we get one hundred thousand customers of insects. You have nineteen thousand customers of Visa, which, by the way, significantly head of Nutanix. How do we have make one hundred ninety thousand customers? And we have that base? Because we have V sphere and we have the Delll base. We have other partners. We have, I think, eighty thousand customers off and use of computing tens of millions of devices. How do we make sure that we are workspace? One is on billion. Device is very much possible. That's the vision. >> I think that I think what's resonating for me when I hear you guys, when you hear you talk when we have conversations also in Pat on stage talks about it, the simplification message is a good one and the consistency of operating across multiple environments because it sounds great that if you can achieve that, that's a good thing. How you guys get into how you making it simple to run I T. And consistent operating environment. It's all about keeping the customer in the middle of this. And when we listen to customs, all of these announcements the partnership's when there was eight of us, Microsoft, anything that we've done, it's about keeping the customer first, and the customer is basically guiding up out there. And often when I sit down with customers, I had the privilege of talking hundreds of thousands of them. Many of these CEOs the S and P five hundred I've known for years from S athe of'Em were they'LL Call me or text me. They want us to be a trusted advisor to help them understand where and how they should move in their digital transformation and compared their journey to somebody else's. So when we can bring the best off, for example, of developer and operations infrastructure together, what's called DEV Ops customers are wrestling threw that in there cloud journey when we can bring a multi device world with additional workspace. Customers are wrestling that without journey there, trying to figure out how much they keep on premise how much they move in the cloud. They're thinking about vertical specific applications. All of these places where if there's one lesson I've learned in my last ten twenty years of it has become a trusted advisor to your customers. Lean on them and they will lean on you on when you do that. I mean the beautiful world of technology is there's always stuff to innovate. >> Well, they have to lean on you because they can't mess around with all this infrastructure. They'LL never get their digital transformation game and act together, right? Actually, >>= it's great to see you. We'Ll see you at PM, >> Rollo. Well, well, come on, we gotta talk hoops. All right, All right, All right, big. You're a big warriors fan, right? We're Celtics fan. Would be our dream, for both of you are also Manny's themselves have a privileged to go up against the great Warriors. But what's your prediction this year? I mean, I don't know, and I >> really listen. I love the warriors. It's ah, so in some senses, a little bit of a tougher one. Now the DeMarcus cousins is out for, I don't know, maybe all the playoffs, but I love stuff. I love Katie. I love Clay, you know, and many of those guys is gonna be a couple of guys going free agents, so I want to do >> it again. Joy. Well, last because I don't see anybody stopping a Celtics may be a good final. That would be fun if they don't make it through the rafters, though. That's right. Well, I Leonard, it's tough to make it all right. That sounds great. >> Come on. Sanjay Putin, CEO of BM Wear Inside the Cube, Breaking down his commentary of you on the landscape of the industry and the big news with Microsoft there. Other partner's bringing you all the action here Day one of three days of coverage here in the Cubicle two sets a canon of cube coverage out there. We're back with more after this short break.

>> Live, from Las Vegas, it's theCube! Covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, And their ecosystem partners. >> Hey, welcome back everyone, live here, in Las Vegas, Amazon Web Services AWS re:Invent 2018. 52,000 people here. Two days. Second day of three days of wall to wall coverage here at theCUBE. I'm John, with Dave Vellante. Dave, six years, we've been doing theCUBE. We've been to all re:Invents except for the first year. We've been a customer, we've been following these guys. >> Plus the summits! >> Plus the summits. Great ecosystem. And VMware and VMworld, similar dynamic. I want to talk about that now, obviously the new announcement, on-premise, is huge. Want to dig in to it with our guest, Sanjay Poonen, who's the Chief Operating Officer of VMware. Sanjay, great to see you. Cube alumni, many times, thanks for coming back again. >> John and Dave, pleasure to be on your show. >> Thanks for coming on, great to see you. >> Congratulations on all this success, you've got a wonderful booth and presence here, and I think this is becoming like the Mecca of all IT events. >> You know, we have our new video cloud service on AWS, we're ingesting over 110 videos, we'll have 500 short video clips behind it. Tons of blog posts, tons of coverage. There's an insatiable appetite for Amazon Web Services content as Andy pointed out in my interview with him. And it's just the beginning. You guys at VMware really, I mean, talk about a seminal moment in the history of the computer industry, and VMware was, when you guys recognized the sea change of operators on IT and cloud developers coming together, you guys were very proactive two years ago. Raghu, yourself, and the team, Pat. We're going to, hey you know what? Let's just align. Culture's a fit with Amazon. Let's co-develop. Let's ride the wave together, and let's see where the chips fall. Which is basically, I'm oversimplifying, but that's kind of what's happened. So much has happened. I saw Raghu last night at the Greylock partner event. This is a historic moment. Good outcome so far, deep partnership, meaningful partnership. A lot of resonance in the marketplace, you guys are iterating and raising the bar. That's Amazon talk for success. How do you feel? >> Yeah, no, I think it's, absolutely, John. We, if you think about how this has evolved, you know five years ago when I joined VMware, I felt like cloud and containers, the two C's, were our big headwinds. We've turned those headwinds now into tailwinds, but it took some catharsis from us. We had vCloud Air, our own public cloud. We had to divest that. And I think the Amazon VMware coming together, when we announced it two and a half years ago, was like a Berlin Wall moment, where you had the US and the Soviet Union getting together. That was good for world peace. People were surprised, because these are two purported enemies now, and it really built trust. And step by step, launching VMware on AWS, announcing RDS on VMware, the beginning of on-premise, and then today, announcing Outposts, it's just an example of not just the validity of VMware as a hybrid cloud leader, but the strength of this partnership. We have a very special relationship with Andy, Pat, myself, Raghu, spent a lot of time together. Often, you can't tell, when our engineering teams meet, when an Amazon engineer and a VMware apart from each other. They're like finishing each other's sentences. That, we don't do, like, Mickey Mouse, Barney, you know press releases. It's real stuff. >> And the culture of, the engineering culture of VMware, which has been a core, cultural thing, the DNA of VMware is technical. Very community oriented. Amazon, technical, very operationally efficient, good community. This is good fit there. I got to get your perspective, though, on how that is going to evolve, specifically around on-premise. Because certainly Andy Jassy validates on-premises with the announcement that VMworld, which you guys covered, Pat Gelsinger uses words like dial tone, Kubernetes, you mentioned containers. Andy, when I asked him, "Andy, you know you told me "in theCUBE, five years ago, "that everything's going to the public cloud. "Change of tune? "You mind if I pin you down?" "No, John, you can pin me down all you want." He says good leaders are self-aware. He said "Our customers wanted this." And he's cool to it. And the partnership with VMware highlights that this is not going to happen overnight, he recognizes the duration, the role of on-premise. And then he also says that the data center's like a big Edge. So, if everything's cloud, what you guys basically announced with Outpost is, cloud, public cloud everywhere. So, just, there's no public, private, it's just cloud. This is a game changer, because-- >> Absolutely. >> Just, why wouldn't I want to buy this product? >> I mean, first off, congratulations on scoring that interview. Not many people have access to Andy that way, and you guys have built a very good relationship. I thought that interview you did with him was phenomenal. There was a special point in that, John, where you tried to get him to talk about Outposts, this was before he announced it, which is will Amazon go on-premise. So a couple of months ago, when Andy called us, and Matt Garman, to talk about this project under NDA, it was a continuation of those RDS type discussions where we basically said, if you want to do anything on-premise, you should do it with VMware, because you're going to have to go through this door called VMware. We are the de facto king of the on-premise private cloud world. Many of these customers are used to our tooling, vSphere, vMotion. They want anything to run on VMware. So from that became a sequence of discussions that really really evolved very quickly, and well, so we can announce this together. I mean, you know, Andy had three guests on stage, and only one partner, and that was VMware. And that's an indication of the strength of this partnership. Vice versa, of the 50,000 people here, probably all of them have VMware on-premise. So if Amazon's going to do more on premise, why not do it with the leader in that area, VMware. And we want to be in the software industry. The de facto standard for software-defined infrastructure. Right? And that's a special space that we can fill. >> Well, the amazing thing to me, is, here's VMware, no public cloud, Amazon wouldn't even say the word hybrid, or private cloud, doesn't use private cloud, but it wouldn't say hybrid before. You've now emerged as the tandem, de facto leader in hybrid cloud. Overnight. With an ecosystem that all wants to connect and partner with VMware and all wants to partner with AWS. Overnight. I mean, it feels that way anyway, 24 months. >> I think that's absolutely right. I mean, we were the first to start using the term hybrid, three or four years ago. As we did, then it took a while, because I think a lot of customers, and some of the public cloud vendors, felt it was going to be binary, all public cloud and no private cloud, but they began to realize you need both. But your point on the ecosystem, also surrounding, I just came back from meeting one of the top SIs in the world. They're betting big with us because they see this as the place for both of them, and they're also betting big with AWS. The System Integrators are all over this. The security vendors, all over this. Palo Alto Networks, Splunk, want to see. Often, many of these companies come to us and say, "You have cracked something special "in your relationship with Amazon. "How did you do that and how can we follow that model?" We're happy to share our playbook of how we think about ecosystems. So, we want to create a platform, just like Amazon's a platform, where everybody, SIs, tech vendors, software vendors, can all plug in to. >> And the other observation I make is, you know, previously the distance between infrastructure players and the guys who really are driving application value, the application developers, was quite a distance. And now it's closing, with infrastructure as code. And it's just so transformative for organizations. >> I think, and one of the things that's making that is microservices and containers. And as you know, since we last talked, we acquired Heptio. If you think about Heptio, they are the founders of Kubernetes, okay? They left Google, started their own company, Craig and Joe, and we're excited about that. That platform will augment PKS, which was our big bet in containers, and become something that could run on-premise, or in a public cloud environment like this. We acquired CloudHealth. CloudHealth is a multi-cloud management tool for costing resource management. That becomes something that could send, a lot of Amazon reps actually refer CloudHealth as the preferred way to get your insights. So we're beginning to see this now a lot more clearly than we did two years ago, thanks to this partnership. >> So, Sanjay, I know that Outposts, super exciting, it's been covered on Silicon Angle, there's a zillion stories on our site on this whole event. But, it's not going to be shipping for about a year. But you guys already have some working products now. What's the current track to that shipping because when that comes out, that'll be a game changer. Why would anyone want to buy hardware again? Michael Dell wins either way because he's got VMware. But others who sell hardware, this is a real, it could be a killer blow. But, I don't want to (laughs), you can comment on that if you want, but what's in-between that one year, you've got a product now, how do customers move along? >> Yeah, I think there's some very tangible things that, first off, VMware Cloud on AWS is, as you've described Dave, the best hybrid cloud option. You get the best of the on-premise world and the public cloud. You know, we announced hundreds of customers, we have a goal to get to thousands of customers, and then tens of thousands of customers. We're going to continue down that march. I want to have a significant number, over 500,000 customers. If Amazon has 40, 50 percent market share, based on some of the numbers that Andy shared today, a significant number of our customers have Amazon, we should get them onto VMC. VMware Cloud and AWS. Secondly, we do have, we announced Project Dimension, some Edge computing capabilities running on existing hardware players, so we are beginning this journey ourselves, in terms of cloud managed on-premise environment. Right? Project Dimension was announced before this, and that will run on Dell and Lenovo hardware, and that's well and good to go. They will have Edge IOT use cases. And then when Amazon comes and gets us ready, we would have learned a lot about this market. Which is really kind of this Edge computing market, cloud-managed. So we're not going to be, we're going to plan and do the other pieces. Much of the software components that VMware is building is not completely from scratch code. We're taking NSX. One of the most important components that VMware is adding to Outposts is NSX. We're not rewriting NSX, we're taking the NSX and applying this now, to a use case that's very much like that because we've adapted NSX now to be container-friendly, cloud-friendly. We've added NSX into the branch, VeloCloud. So those are the things that we're, you know, there's no rest for the weary anymore. >> And that gives you a consistent networking model, which is not trivial, as we've talked about. >> One of the things that I'm excited by, intrigued by, is, I know it's nuanced, but I see it as a key point, containers sometimes don't meet the security boundary issue. So, you guys can run a VM around a container, and run it under the covers. With Lambda. At super lightning speeds. It's not like a ten second instance to stand up. So that means there's more opportunities to create more abstractions around Kubernetes. And maintain security. There's so many benefits from this integrated kind of concept of consistency of operations for the software developer. >> John, you're absolutely right. Part of what we're trying to do is that word you talked about. Consistent infrastructure and operations. Consistent infrastructure and operations. And the container, if you've been seeing some of the ads in the San Francisco airport, we have some in London, and a few of the airports in New York, you'll see an ad that says "Containerware." It's playing on the word "ware", VMware. We want to be everyWARE, W-A-R-E. And if you think about the container being as pervasive as the vm in the future, I'm not going to say we're going to change the name of the company to be Containerware, but we want to be as pervasive as vm has been in VMware. So we have tens of millions of vms, in the twenty years we've had, maybe there'll be ten times as many containers. We want to become that de facto platform and containerware starts to take over. Right? What is that? Kubernetes-based. And we'll partner with the best. We've partnered with Google, we've partnered with Pivotal. Some of it would land on AWS, some of it will land on Azure. And you get a lot of the flexibility you have with that microservices platform. >> So, since you guys are on more of the software side, obviously Amazon's got software, but you guys actually are going to be much more broader, multiple clouds, as Amazon moves up the stack, I would imagine that as customers, I'm not going to buy in to only one cloud, there's other clouds out there, you guys should become a real strategic, traversal between clouds. So, we were debating, will customers have certain instances in, say, different clouds for specific, unique things, but yet run still horizontally, scalable on-premises, with VMware across multiple clouds. >> I think, you know John, it's going to be a lot like the hardware market was 20 years ago. It started to evolve into two or three major players. What's today Dell, HPE, Lenovo, at the time it was IBM, they divested to Lenovo, Cisco. In the storage place, two or three. I think the public cloud is not going to be three, five, ten. It's going to be two or three. Maybe four. And then maybe, in like China, Alibaba. So already, we have certain tools. Like CloudHealth's proposition is to manage costs and resources across multiple clouds. So we began to be already thinking about what is a multi-cloud world do? That said, in areas like this, which is a data center offer, we felt it was good for us to focus and get VMware Cloud and AWS to be the best hybrid cloud option. Give that a couple years, rather than trying to do everything and do it poorly, when you peanut butter your approach and try to do a lot of things with various different, so this is why we put a lot of special attention on VMware Cloud and AWS. We have an offering with IBM. We announced something with Alibaba. In due course VMware will need to have multiple cloud offerings. But I feel like this partnership and the specialness of this has really benefited both sides. >> Well, it's going to be very interesting, because IBM just made a 34 billion dollar validation of multi-cloud, so, and we talk about competition all the time. And it's evolving. >> We have a very good relationship with IBM. And listen, you have to be reasonably nuanced in your partnerships. So we're going to partner very heavily with IBM Global Services. We're going to partner very well with IBM Cloud. We're going to compete really hard with Red Hat! That's okay! Well, we'll compliment Linux. The bulk of their revenue's Linux. >> Of course, yeah. >> But make no mistake, we're going to compete hard with OpenShift. That's okay! That doesn't mean our IBM relationship is competitive. There's one piece of that, a very small part of the Red Hat revenue, OpenShift, that we overlap. The rest of it is complementary. We can be nuanced. It's sort of like walking and chewing gum. We can do both. And that's how we play. >> Before you wrap, now you know what we think of you, we think very highly of you, you're a superstar in our minds. However, you got to interview Sushmita, in India-- >> You know who Sushmita is? >> a true Bollywood superstar. Yes, an amazing actress, beautiful, talented. That must have been quite an experience. >> Well I got to tell ya, I was very intimidated. I opened-- >> I'll bet. >> Cause somehow I get assigned all these interviews to do. Malala, I'm usually on the opposite end. Your end. Malala, and Condoleezza Rice, and I told her I was really intimidated by her, and she said "Why?" I said, it's the first time that, I'm usually not tongue tied, but I did not know how to explain to my wife that I was going to be interviewing Ms. Universe. Okay, and she's like "What do you guys do at VMware? What the heck does Sushmita Sen have to do" But it was a good interview, I mean listen, for the India audience, we were celebrating our 20 year anniversary. She is an amazing woman who has achieved something that very few Indians have. And we wanted our Indian audience there to see that women can be successful. She's a big supporter of more women in business, fairness, equality, no prejudice, equal pay, all those things that we stand for. Which is part of our values. And if it weren't for the India audience she probably, I don't know if she would have worked at a Vmworld. We had Malala there, we had Condoleezza Rice at our last sales kickoff. We do these because we want to both teach our employees something, but also inspire them. And sometimes these speakers help with that cause. >> Sanjay, great to see you, thanks for coming on. I know you got to catch a flight. Big day today for you guys at VMware, congratulations. >> Thank you very much for having me. >> Thanks for all your support, great to see you. Great commentary, great insight. Sanjay Poonen, COO at VMware breaking down the announcement of Outposts, its relevance and impact on the market, and more importantly, the VMware AWS relationship. This is theCUBE bringing you all the action, day two of three days of wall-to-wall coverage. Two sets, hundreds of video assets coming, tons of posts on siliconangle.com, where all the coverage is. We'll be right back with more after this short break. (techno music)

(intense orchestral music) >> Welcome back everybody, Jeff Frick here with theCUBE, we're in our Palo Alto studio havin' a CUBEConversation, we're getting ready for the madness of the fall conference season to hit us full force, so we're excited to have things a little bit quiet this week and have a special guest, he's Jed Ayres, he is the North American CEO, and the Global CMO for IGEL, great to see you. >> Well, great to be here, thanks for inviting me, I know a lot of luminaries in the tech industry have sat in this chair so, >> That's right. >> It's an honor to have a chance to chat with you today. >> Well thank you, I appreciate that. So give a, for the people that aren't familiar with IGEL, give us kind of the IGEL 101. >> Yeah, so I wasn't actually that familiar with IGEL two years ago, and I've spent, you know over a decade in the end user compute space, so they were a little bit of a mystery I think to most people in the US; however, the companies been around for over 20 years, they're actually the number one Thin Client player in Germany since 2006. So what they really specialize in is a Linux, read-only operating system, that's fused to a management console that just really works for these cloud delivered desktops and applications, right? And so, a little bit shrouded in sort of this world of Thin Client hardware, but the company is really a software company. And so, the opportunity for me was to really help them build their US operation, but probably more importantly, put the right sort of US marketing prowess and kind of English first, we got out and kind of re-wrote their marketing playbook, and we really have exposed the IP of this beautiful, light, Linux OS, and the management tool which you know couldn't have been at a better time in terms of what's happening in the industry. >> So just to call those three things out specifically, so it's a light OS, that's Linux based, for x86 devices, >> Exactly. >> And so you're workin' with Citrix and VMware, and a lot of those platforms. >> I mean there's 17 different protocols that it works with out of the box, so, really when you think about you know Microsoft RDP, Parallels, Ericom, some of the, some things that you know, back in the history of end user compute, we still, out of the box, are synced up with those technologies. But the primary ones today are Citrix, and VMware, and Microsoft, and yeah we'll soon be doing some things with Amazon as well workin' with them to be their first Linux client for workspaces, so. >> So, we talked a little bit before we turned the cameras on, you know the bring your own device thing, we saw it first in mobile phones in a big, big way, you know people are bringing their laptops and all kinds of interesting stuff. At the same time you've got kind of this cloud move with the centralized control, and you don't have all this kind of rogue stuff, and you know some of the clouds like I don't have the right excel spreadsheet on this laptop, it's on my home desktop. So you guys are kind of riding that wave, but enabling a really interesting play on it, you enable a BYOD, but you actually have an opportunity to basically supplant that, overlay, I don't know what's the right verb, to enable a secure, lightweight, centralized control. >> Yeah, so there's really three ways to get this operating system, right? You can get it on the traditional hardware form factors that you find for most Thin Clients, right, we've got kind of a entry level, mid, high-level all in one. And then we have the ability to convert a device, so we would actually wipe the entire operating system off the device, and just, you'll have a last boot to the IGEL OS. But then, really what, two years ago we came out with this, and this is what we call the UD Pocket, it's about the size of your thumbnail, it's a hardened USB read-only stick, it has the same OS that the hardware has and the converter software has, it's just a bootable, right? So I could plug this into that laptop you have there, and you would boot to a secure Linux operating system, and we'd point it to whatever cloud delivery service that you're, you know, theCUBE was using, so if it was Citrix or VMware, so. Yeah, this has opened up a lot of new use cases, it's sort of changed how people think about Thin Clients too right, you sort of think Thin Client, kiosk task worker, not necessarily the CEO of a company or a knowledge worker, or a physician running an emergency room might want to have their own device, same device they use at home. So yeah, this has opened up a lot of interesting use cases: contractors, interns, we even see it being used for people in environments, in hospitals, where they keep a stash of these, for high availability, I guess ransomware. Right, you've seen these hospitals basically being attacked, what they would do is go and put these in, boot to a secondary epic or server environment, and you know this is kind of their way of not knowing which device is infected, they can just easily bypass that device, boot to this read-only operating system. >> It's a real game changer in terms of opening up >> It really is. >> Not only, not only, removing all the vulnerabilities that come with with kind of a classic laptop situation, but even giving the things new life, right, enabling them to kind of be reborn, really as a Thin, or excuse me as a light client. >> Yeah, we see three reasons why people are are buying IGEL today. And it's fun for me 'cause I get go out you know talk to a lot of customers and partners, you know we're 100% partner oriented organization, which is fun for me since I spent 20 years as a partner. But what's been really fun is that it's a C-level conversation, you wouldn't think Thin Client, I can go talk to a CEO or a CFO or a CIO, but this is a game changer. And it's really three things, right, we can save people money, which people like that, right, when you can save a company from having to go purchase 5000 new endpoints; we just had a hospital in Texas, they were about to buy 5000 new endpoints, that's about five million dollars, right? We walked in and sold them 5000 convertor licenses, for about a half a million dollars, so they saved four and a half million dollars in not having to buy new hardware. And then, you know the second piece is the operational headcount savings. When you think about managing Windows today, it's you know maybe great organizations one person can do 500 devices maybe; if you're lucky and you really have all the right tools. With IGEL we have numbers like one person managing 30000 devices, in retail, you know places where you don't have a lot of smart hands. And then the third reason why, you know we can talk to a lot of CSOs now too, right, as people are gravitating towards Linux, because of the challenges with Windows, and managing Windows, and securing windows. And Linux, when I first started people said kind of don't talk about Linux, you know, it's maybe kind of a bad word and people get you know scared. Today we walk in and we lead with this is a very mature Linux operating system, and we have a fantastic security roadmap... >> And 20 years of history, right? So you've got institutional, a foundation that you can build off of. It's funny on the Linux thing right, 'cause I'm sure they said the same thing when they wanted to roll Linux into the data centers back in the day. >> Exactly. (Jeff laughs) Yeah, this is the year where we believe, and IDC is tracking this pretty closely, that this is the year where on the endpoints of this Thin Client, you're going to see Windows is going to be surpassed by Linux; and that tracker that IDC does doesn't even track the ones that are being repurposed, right, where Linux is going in because it's going in on old hardware. So just on the new hardware it's going to be about 40% Linux and 40% Windows, and then there's you know some other you know operating systems out there, but. Yeah, this is, this is an exciting time to be in this space, right? We look at the challenges of managing Windows 10, we look at the security issues of GDPR, you know and people are just really gravitating towards towards this idea of a Linux OS. >> Right. It's funny, it's not, not directly related, but corollary, you know as Google really pushes Chromebooks as part of their enterprise play as a much more secure platform with central control, and in fact I think Diane mentioned at the Google Cloud show that we use like 37 different basically online applications to get work done these days, whether you're in your Salesforce application, or Marketo, or Gmail Suite, or you know. So we're all basically browser based application delivery, so it really does open up this opportunity for the incline 'cause you don't really need that much function, >> Exactly. >> But you know it's serving up that central HTTP. >> I talk to people all the time who have fancy, thousands of dollar laptops, and their like, all they do is hit a browser, right? And the reality is, is that's where we're going right, it's a pane of glass accessing data somewhere else, an application somewhere else right? But the underlying operating system still needs to be secured. If you look at sort of the priorities of CIOs today, endpoint--securities number one right, and inside of that it's typically endpoint security, as you know the most important piece of it right? And so that's really where IGEL is having a wonderful time taking tremendous market share, you know we've moved, in just the time that I've been in the US, from seven to three, just in the sort of hardware part of it. And we're just having a lot of fun growing an organization that's, you know and you're growin' in triple digits, it's kind of a Cinderella moment for your career, right, so. >> Plus different kind of challenges. (laughs) >> Exactly. Exactly. >> So is there a particular vertical, is there a particular kind of business group within the companies that you guys use as a point of entry? Or, I mean how do you, what's kind of your go-to-market, >> Yeah, so there's some very specific-- >> 'cause it's a huge opportunity right. >> Yeah, very specific verticals where we're having great success in: hospitals are number one, we've sold to 143 hospitals in the US, if you can believe that, and we're in pretty, and that was just last year. >> 140? Just in a typical, typical, average, whatever metric you want to use, is how many OS's going into a hospital? >> I mean, last quarter we sold about 10000 into one hospital, you know it's usually anywhere from 2500 to 5000, 10000. And then you know these hospitals are all merging with each other, that's another value of IGEL is that they're all kind of combing, and as they combine, IGEL can take all this heterogeneous hardware, heterogeneous operating systems, homogenize it, make it easy to manage and secure. >> Putting it all back in the same spot. >> So yeah, it's definitely healthcare, healthcare's number one, but we're also doing very well in retail, very well in finance, kind of banks, really well in higher education; and like I said, we're getting to talk to at the C-level, right, they really love the savings, right? Not only are the saving on the hardware, but they can get rid of antivirus, disk encryption, they can redeploy people to do things other than patching devices. We have some brilliant things in terms of the technology; you mentioned we have the IP of 20 years, the three guys who wrote the code at the very beginning of the 20 years ago actually they were with an IGEL version before the current iteration. So literally in the end of the '90s they were, idea was let's build an operating system for the internet, which you know they may have been a bit ahead of their time in 1999, but those three guys are actually still in the building. There's a hundred engineers in Germany that are sort of iterating on this and solving for this problem, and I think they've, you know now with the US operation and the new marketing, we're kind of, it's just a perfect storm I would say. >> And then with 5G and again the increasing importance of cloud-based applications, whether it be Salesforce, or whether it be, whatever that's delivered through Amazon, I mean you guys are in a very good spot. >> Yeah, and it's, I would tell you it's not just about, you know it's this operating system fused to a management console, but then it's sort of the curation of that, right? Like okay, every 12 weeks I'm going to push you a new OS, and I have an elegant way to get that to 10's of thousands of devices. So we're also starting to see managed service providers, right, the guys that are under contract to manage millions of devices. You know the DxEs and Wipros and IBM Global Services, those guys are starting to really look at IGEL also, right, 'cause, for the same reasons the enterprises who are managing large environments; so that's been an exciting part of our growth as well. >> Yeah, and that's another huge validation point, 'cause those guys don't make small bets, they only make big bets. >> Exactly and market's sort of hardened into their architecture, which is great. >> Alright, Jed, well it sounds like a great story, and we look forward to watching it unfold over the next couple years. >> Yeah! Well hopefully, for those of the people who are out watchin' we'd love to have them come by; we're doing an event in Las Vegas inside the Mandalay Bay, at VMworld, we actually have our own event, rightfully called disrupt. And we're going to be there from the 26th to the 29th, and-- >> What venue? >> In the Border Grill, so we actually taken over this restaurant, that's kind of like right you know in the footpath of-- >> In the hallway, right? >> In the hallway yeah. >> That's the inside, I know exactly where that is. >> So yeah, we're actually takin' a page out of your book, we're going to have a little EUC TV, so we'll be interviewing people about you know what they're doing to solve for their end user compute challenges, and talkin' to the ecosystem; we have an innovation theater in the Border Grill, we're going to throw a pool party at the end, out at one of those beautiful pools that no one ever gets to go to in Vegas. (both laugh) >> We look at it though as we walk just past the Border Grill, you can find a long beautiful look at that pool. >> So we're going to try to take advantage of it, although it'll be a bit hot out there, yeah it's a hundred plus degrees in Vegas this time of year, but we're going to have some fun. You know, you got to do that a little bit, work hard, play hard. >> Alright, we'll see ya in Vegas in a couple weeks! >> Yep! Look forward to it. >> Thanks for stopping by. >> Thanks very much. >> Alright he's Jed, I'm Jeff, you're watchin' the CUBEConversation from our Palo Alto studios, thanks for watchin', I'll see ya next time. (intense orchestral music)

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

>> Narrator: Live from Boston, Massachusetts, this is the Cube, covering Spark Summit East 2017, brought to you by Databricks. Now, here are your hosts, Dave Vellante and George Gilbert. >> Welcome back to Boston, everybody, where the town is still euphoric. Mike Gualtieri is here, he's the principal analyst at Forrester Research, attended the parade yesterday. How great was that, Mike? >> Yes. Yes. It was awesome. >> Nothing like we've ever seen before. All right, the first question is what was the bigger shocking surprise, upset, greatest win, was it the Red Sox over the Yankees or was it the Superbowl this weekend? >> That's the question, I think it's the Superbowl. >> Yeah, who knows, right? Who knows. It was a lot of fun. So how was the parade yesterday? >> It was magnificent. I mean, it was freezing. No one cared. I mean--but it was, yeah, it was great. Great to see that team in person. >> That's good, wish we could talk, We can, but we'll get into it. So, we're here at Spark Summit, and, you know, the show's getting bigger, you're seeing more sponsors, still heavily a technical audience, but what's your take these days? We were talking off-camera about the whole big data thing. It used to be the hottest thing in the world, and now nobody wants to have big data in their title. What's Forrester's take on that? >> I mean, I think big data-- I think it's just become mainstream, so we're just back to data. You know, because all data is potentially big. So, I don't think it's-- it's not the thing anymore. I mean, what do you do with big data? You analyze it, right? And part of what this whole Spark Summit is about-- look at all the sessions. Data science, machine learning, streaming analytics, so it's all about sort of using that data now, so big data is still important, but the value of big data comes from all this advanced analytics. >> Yeah, and we talked earlier, I mean, a lot of the value of, you know, Hadoop was cutting costs. You know, you've mentioned commodity components and reduction in denominator, and breaking the need for some kind of big storage container. OK, so that-- we got there. Now, shifting to new sources of value, what are you spending your time on these days in terms of research? >> Artificial intelligence, machine learning, so those are really forms of advanced analytics, so that's been-- that's been very hot. We did a survey last year, an AI survey, and we asked a large group of people, we said, oh, you know, what are you doing with AI? 58% said they're researching it. 19% said they're training a model. Right, so that's interesting. 58% are researching it, and far fewer are actually, you know, actually doing something with it. Now, the reality is, if you phrase that a little bit differently, and you said, oh, what are you doing with machine learning? Many more would say yes, we're doing machine learning. So it begs the question, what do enterprises think of AI? And what do they think it is? So, a lot of my inquiries are spent helping enterprises understand what AI is, what they should focus on, and the other part of it is what are the technologies used for AI, and deep learning is the hottest. >> So, you wrote a piece late last year, what's possible today in AI. What's possible today in AI? >> Well, you know, before understanding was possible, it's important to understand what's not possible, right? And so we sort of characterize it as there's pure AI, and there's pragmatic AI. So it's real simple. Pure AI is the sci-fi stuff, we've all seen it, Ex Machina, Star Wars, whatever, right? That's not what we're talking about. That's not what enterprises can do today. We're talking about pragmatic AI, and pragmatic AI is about building predictive models. It's about conversational APIs, to interact in a natural way with humans, it's about image analysis, which is something very hot because of deep learning. So, AI is really about the building blocks that companies have been using, but then using them in combination to create even more intelligent solutions. And they have more options on the market, both from open source, both from cloud services that-- from Google, Microsoft, IBM, and now Amazon, at their re-- Were you guys at their reinvent conference? >> I wasn't, personally, but we were certainly there. >> Yeah, they announced the Amazon AI, which is a set of three services that developers can use without knowing anything about AI or being a data scientist. But, I mean, I think the way to think about AI is that it is data science. It requires the expertise of a data scientist to do AI. >> Following up on that comment, which was really interesting, is we try and-- whereas vendors try and democratize access to machine learning and AI, and I say that with two terms because usually the machine learning is the stuff that's sort of widely accessible and AI is a little further out, but there's a spectrum when you can just access an API, which is like a pre-trained model-- >> Pre-trained model, yep. >> It's developer-accessible, you don't need to be a data scientist, and then at the other end, you know, you need to pick your algorithms, you need to pick your features, you need to find the right data, so how do you see that horizon moving over time? >> Yeah, no, I-- So, these machine learning services, as you say, they're pre-trained models, totally accessible by anyone, anyone who can call an API or a restful service can access these. But their scope is limited, right? So, if, for example, you take the image API, you know, the imaging API that you can get from Google or now Amazon, you can drop an image in there and it will say, oh, there's a wine bottle on a picnic table on the beach. Right? It can identify that. So that's pretty cool, there might be a lot of use cases for that, but think of an enterprise use case. No. You can't do it, and let me give you this example. Say you're an insurance company, and you have a picture of a steel roof that's caved in. If you give that to one of these APIs, it might say steel roof, it may say damage, but what it's not going to do is it's not going to be able to estimate the damage, it's not going to be able to create a bill of materials on how to repair it, because Google hasn't trained it at that level. OK, so, enterprises are going to have to do this themselves, or an ISV is going to have to do it, because think about it, you've got 10 years worth of all these pictures taken of damage. And with all of those pictures, you've got tons of write-ups from an adjuster. Whoa, if you could shove that into a deep learning algorithm, you could potentially have consumers take pictures, or someone untrained, and have this thing say here's what the estimate damage is, this is the situation. >> And I've read about like insurance use cases like that, where the customer could, after they sort of have a crack up, take pictures all around the car, and then the insurance company could provide an estimate, tell them where the nearest repair shops are-- >> Yeah, but right now it's like the early days of e-commerce, where you could send an order in and then it would fax it and they'd type it in. So, I think, yes, insurance coverage is taking those pictures, and the question is can we automate it, and-- >> Well, let me actually iterate on that question, which is so who can build a more end-to-end solution, assuming, you know, there's a lot of heavy lifting that's got to go on for each enterprise trying to build a use case like that. Is it internal development and only at big companies that have a few of these data science gurus? Would it be like an IBM Global Services or an EXIN SURE, or would it be like a vertical ISV where it's semi-custom, semi-patent? >> I think it's both, but I also think it's two or three people walking around this conference, right, understanding Spark, maybe understanding how to use TensorFlow in conjunction with Spark that will start to come up with these ideas as well. So I think-- I think we'll see all of those solutions. Certainly, like IBM with their cognitive computing-- oh, and by the way, so we think that cognitive computing equals pragmatic AI, right, because it has similar characteristics. So, we're already seeing the big ISVs and the big application developers, SAP, Oracle, creating AI-infused applications or modules, but yeah, we're going to see small ISVs do it. There's one in Austin, Texas, called InteractiveTel. It's like 10 people. What they do is they use the Google-- so they sell to large car dealerships, like Ernie Boch. And they record every conversation, phone conversation with customers. They use the Google pre-trained model to convert the speech to text, and then they use their own machine learning to analyze that text to find out if there's a customer service problem or if there's a selling opportunity, and then they alert managers or other people in the organization. So, small company, very narrowly focused on something like car buying. >> So, I wonder if we could come back to something you said about pragmatic AI. We love to have someone like you on the Cube, because we like to talk about the horses on the track. So, if Watson is pragmatic AI, and we all-- well, I think you saw the 60 Minutes show, I don't know, whenever it was, three or four months ago, and IBM Watson got all the love. They barely mentioned Amazon and Google and Facebook, and Microsoft didn't get any mention. So, and there seems to be sentiment that, OK, all the real action is in Silicon Valley. But you've got IBM doing pragmatic AI. Do those two worlds come together in your view? How does that whole market shake up? >> I don't think they come together in the way I think you're suggesting. I think what Google, Microsoft, Facebook, what they're doing is they're churning out fundamental technology, like one of the most popular deep learning frameworks, TensorFlow, is a Google thing that they open sourced. And as I pointed out, those image APIs, that Amazon has, that's not going to work for insurance, that's not going to work for radiology. So, I don't think they're in-- >> George Gilbert: Facebook's going to apply it differently-- >> Yeah, I think what they're trying to do is they're trying to apply it to the millions of consumers that use their platforms, and then I think they throw off some of the technology for the rest of the world to use, fundamentally. >> And then the rest of the world has to apply those. >> Yeah, but I don't think they're in the business of building insurance solutions or building logistical solutions. >> Right. >> But you said something that was really, really potentially intriguing, which was you could take the horizontal Google speech to text API, and then-- >> Mike Gualtieri: And recombine it. >> --put your own model on top of that. And that's, techies call that like ensemble modeling, but essentially you're taking, almost like an OS level service, and you're putting in a more vertical application on top of it, to relate it to our old ways of looking at software, and that's interesting. >> Yeah, because what we're talking about right now, but this conversation is now about applications. Right, we're talking about applications, which need lots of different services recombined, whereas mostly the data science conversation has been narrowly about building one customer lifetime value model or one churn model. Now the conversation, when we talk about AI, is becoming about combining many different services and many different models. >> Dave Vellante: And the platform for building applications is really-- >> Yeah, yeah. >> And that platform, the richest platform, or the platform that is, that is most attractive has the most building blocks to work with, or the broadest ones? >> The best ones, I would say, right now. The reason why I say it that way is because this technology is still moving very rapidly. So for an image analysis, deep learning, very good for image, nothing's better than deep learning for image analysis. But if you're doing business process models or like churn models, well, deep learning hasn't played out there yet. So, right now I think there's some fragmentation. There's so much innovation. Ultimately it may come together. What we're seeing is, many of these companies are saying, OK, look, we're going to bring in the open source. It's pretty difficult to create a deep learning library. And so, you know, a lot of the vendors in the machine learning space, instead of creating their own, they're just bringing in MXNet or TensorFlow. >> I might be thinking of something from a different angle, which is not what underlying implementation they're using, whether it's deep learning or whether it's just random forest, or whatever the terminology is, you know, the traditional statistical stuff. The idea, though, is you want a platform-- like way, way back, Windows, with the Win32 API had essentially more widgets for helping you build graphical applications than any other platform >> Mike Gualtieri: Yeah, I see where you're going. >> And I guess I'm thinking it doesn't matter what the underlying implementation is, but how many widgets can you string together? >> I'm totally with you there, yeah. And so I think what you're saying is look, a platform that has the most capabilities, but abstracts, the implementations, and can, you know, can be somewhat pluggable-- right, good, to keep up with the innovation, yeah. And there's a lot of new companies out there, too, that are tackling this. One of them's called Bonsai AI, you know, small startup, they're trying to abstract deep learning, because deep learning right now, like TensorFlow and MXNet, that's a little bit of a challenge to learn, so they're abstracting it. But so are a lot of the-- so is SAS, IBM, et cetera. >> So, Mike, we're out of time, but I want to talk about your talk tomorrow. So, AI meets Spark, give us a little preview. >> AI meets Spark. Basically, the prerequisite to AI is a very sophisticated and fast data pipeline, because just because we're talking about AI doesn't mean we don't need data to build these models. So, I think Spark gives you the best of both worlds, right? It's designed for these sort of complex data pipelines that you need to prep data, but now, with MLlib for more traditional machine learning, and now with their announcement of TensorFrames, which is going to be an interface for TensorFlow, now you've got deep learning, too. And you've got it in a cluster architecture, so it can scale. So, pretty cool. >> All right, Mike, thanks very much for coming on the Cube. You know, way to go Pats, awesome. Really a pleasure having you back. >> Thanks. >> All right, keep right there, buddy. We'll be back with our next guest right after this short break. This is the Cube. (peppy music)