>>from the Cube Studios in Palo Alto and Boston connecting with thought leaders all around the world. This is a cube conversation. Alright, welcome back to help us dig into this discussion and happy to welcome to the program. Chris Prasad. He is the senior vice president and general manager of the V Sphere business And just Simon, chief technologist for the high performance computing group. Both of them with VM ware. Gentlemen, thanks so much for joining. >>Thank you for having us. >>All right, Krish. When VM Ware made the bit fusion acquisition, everybody was looking the You know what this will do for this space GP use? We're talking about things like AI and ML. So bring us up to speed. As to, you know, the news today is the what being worth doing with fusion. >>Yeah. Today we have a big announcement. I'm excited to announce that, you know, we're taking the next big step in the AI ml and more than application strategy. With the launch off bit fusion, we just now being fully integrated with the V Sphere seven black home and we'll be releasing this very shortly to the market. As you said when we acquired institution a year ago, we had a showcase that's capable base as part of the normal event. And at that time we laid out a strategy that part of our institution as the cornerstone off our capabilities in the platform in the Iot space. Since then, we have had many customers. Take a look at the technology and we have had feedback from them as well as from partners and analysts. And the feedback has been tremendous. >>Excellent. Well, Chris, what does this then mean for customers, you know, what's the value proposition? That diffusion brings the visa versa? >>Yeah, if you look at our customers, they are in the midst of a big ah journey in digital transformation. And basically, what that means is customers are building a ton of applications, and most of those applications have some kind of data analytics or machine learning embedded in it. And what this is doing is that in the harbor and infrastructure industry, this is driving a lot of innovation. So you see the admin off a lot off specialized accelerators, custom a six FPs. And of course, the views being used to accelerate the special algorithms that these ai ml type applications need And, um, unfortunately, customer environment. Most of these specialized accelerators in a bare metal kind of set up. So they're not taking advantage off optimization and everything that it brings to that. Also, with fusion launched today, we are essentially doing the accelerator space. What we need to compute several years ago. And that is, um, essentially bringing organization to the accent leaders. But we take it one step further, which is, you know, we use the customers the ability to pull these accelerators and essentially going to be a couple of from the server so you can have a pool of these accelerators sitting in the network, and customers are able to then target their workloads and share the accelerators, get better utilization, drive a lot of cost improvements and, in essence, have a smaller pool that they can use for a whole bunch of different applications across the enterprise. That is a huge enabler for our customers. And that's the tremendous positive feedback that we get getting both from customers as well. >>Excellent. Well, I'm glad we've got Josh here to dig into some of the pieces, but before we get to you they got Chris. Uh, part of this announcement is the partnership of VM Ware in Dell. So tell us about what the partnership is in the solutions for for this long. >>Yeah. We have been working with the Dell in the in the AI and ML space for a long time. We have, ah, good partnership there. This just takes the partnership to the next level, and we will have, ah, execution solution support in some of the key. I am. It'll targeted the words like the sea for 1 40 the r 7 40 Those are the centers that would be partnering with them on and providing solutions. >>Okay, Tough. Take us in a little bit further as how you know the mechanisms of diffusion work. >>Yeah, that's a great question. So think of it this way. There there is a client component that we're using in a server component. The server component is running on a machine that actually has the physical GP use installed in it. The client machine, which is running the bit fusion client software, is where the user, the data scientist, is actually running their machine machine learning application. But there's no GPU actually in that host. And what is happening with fusion technology is that it is essentially intercepting the Cuda calls that are being made by that machine learning application and promoting those protocols over to the bit fusion server and then injecting them into the local GPU on the server. So it's actually, you know, we call it into a position in the ability that remote these protocols, but it's actually much more sophisticated than that. There are a lot of underlying capabilities that are being deployed in terms of optimization who takes maximum advantage of the, uh, the networking link that's it between the client machine and the server machine. But given all of that, once we've done it with diffusion, it's now possible for the data scientist either consume multiple GP use for single GPU use or even fractional GP use across that interconnected using the using technology. >>Okay, maybe it would help illustrate some of these technologies. If you got a couple of customers. >>Yeah, sure. So one example would be a retail customer. I'm thinking of who is. Actually it's ah grocery chain that is deploying ah, large number of video cameras into their into their stores in order to do things like, um, watch for pilfering, uh, identify when storage store shelves could be restocked and even looking for cases where, for example, maybe a customer has fallen down in denial on someone needs to go and help those multiple video streams and then multiple applications that are being run that part are consuming the data from those video screens and doing analytics and ml on them would be perfectly suited for this type of environment where you would like to be ableto have these multiple independent applications running. But having them be able to efficiently share the hardware resources of the GP is another example would be retailers who are deploying ML our check out registers who helped reduce fraud customers who are buying, buying things with, uh, fake barcodes, for example. So in that case, you would not necessarily want to deploy ah single dedicated GPU for every single check out line. Instead, what you would prefer to do is have a full set of resource. Is that each inference operation that's occurring within each one of those check out lines but then consume collectively. That would be two examples of the use of this wonderful in technology. >>Okay, great. So, Josh, last question for you is this technology is this only for use and anything else? You can give us a little bit of a look forward as to what we should be expecting from the big fusion technology. >>Yeah. So currently, the target is specifically NVIDIA gpu use with Buddha. Ah, the team, actually, even prior to acquisition had done some work on enablement of PJs. And also, I have done some work on open CL, which is more open standard for device access. So what you will see over time is an expansion of the diffusion capabilities to embrace devices like F PJs of the domain. Specific. A six that was referring to earlier will roll out over time, but we are starting with the NVIDIA GPU, which totally makes sense, since that is the primary hardware acceleration. And for deep learning currently >>excellent. Well, John and Chris, thank you so much for the updates to the audience. If you're watching this live leads growing, the crowd chat out Im to ask your questions. This page, if you're watching this on demand, you can also go to crowdchat dot net slash make ai really to be able to see the conversation that we had. Thanks so much for joy. Yeah, yeah, yeah, >>yeah.

>> Female Voice: From San Francisco, it's theCUBE, covering VMware RADIO 2019, brought to you by VMware. >> Welcome to theCUBE's exclusive coverage of VMware RADIO 2019, Lisa Martin with John Furrier in San Francisco, talking all sorts of innovation in this innovation long history culture at VMware, welcoming back to theCUBE, Mornay Van Der Walt, VP of R&D in the Explorer Group. Mornay, thank you for joining John and me on theCUBE today. >> Thank you for having me. >> So, I got to start with Explorer Group. Super cool name. >> Yeah. >> What is that within R&D? >> So the origins of the Explorer Group. I've had many roles at VMware, and I've been fortunate enough to do a little bit of everything. Technical marketing; product development; business development; one of the big things I did before the Explorer group was created was actually EVO:RAIL. I was the founder of that, pitched that idea. Raghu and Ray and Pat were very supportive. We took that to market, took it to (inaudible), handed that off to Dell EMC, the rest is history, right? And then was, "what's next?" So Ray and me look at some special projects, go and look at IoT, go and look at Telemetry, and did some orders for them, and then said "Alright, why don't you look at all our innovation programs." Because beyond RADIO, we actually have four other programs. And everyone, was -- RADIO gets a lot of airtime and press, but it's really the collective. It's the power of those other four programs that support RADIO that allow us to take an idea from inception to an impactful outcome. So hence the name, the Explorer Group. We're going out there, we're exploring for new ideas, new technologies, what's happening in the market. >> Talk about the R&D management style. You've actually got all these-- RADIO's one-- kind of a celebration, it's kind of the best of the best come together, with papers and submissions. Kind of a symposium meets kind of a, you know, successive end for all the top engineers. There's more, as you've mentioned. How does all of it work? Because, in this modern era of distributed teams, decentralization, decisions around business, decisions on allocating to the portfolio, what gets invested, money, spend, how do you organize? Give a quick minute to explain how R&D is structured. >> So, obviously, we have the BUs structured-- well there's PCS, Raghu and Rajeev head that up. And then we've got the OCTO organization, which Ray O'Farrell heads up. And the business, you know, it's innovating every day to get products out the door, right, and that's something that we've got to be mindful of because, I mean, that's ultimately what's allowing us to get products into the hands of our customers, solving tough problems. But then in addition to that, we want to give our engineers an avenue to go and explore, and, you know, tinker on something that's maybe related to their day job, or completely off, unrelated to their day job. The other thing that's important is, we also want to give, because we're such a global R&D, you know, our setup globally, we want to give teams the opportunity to work together, collaborate together, get that diversity of thought going, and so a lot of times, if we do a Hackathon, which we call a Borathon, we actually give bonus points if teams pull from outside of their business units. So you've got an idea, well, let's make it a diverse idea in terms of thought and perspective. If you're from the storage business unit, bring in folks from the network business unit. Bring in folks from the cloud business unit. Maybe you've partnered with some folks that are in IT. It's very, you know, sometimes engineers will go, "Ah, it's just R&D that's innovating." But in reality, there's great innovation coming out of our IT department. There's great innovation coming out of our global support organization. Our SEs that are on the front lines, sometimes are seeing the customers' pain points firsthand, and then they bring that back, and some of that makes it into the product. >> How much of R&D is applied R&D, which is kind of business unit aligned, or somewhat aligned, versus the wacky, crazy ideas: "Go solve a big, hairy problem", that's out there, that's not, kind of, related to the current product sets? >> Ah, that's tough to put an actual number on it, >> John: Well ballpark, I mean. >> But if I just say, like, if I had to just think about budgets and that, it's probably ten to fifteen percent is the wacky stuff, that's, you know, not tied to a roadmap, that's why we call it "off-road innovation", and the five programs that my Explorer Group ultimately leads is all about driving that off-road innovation. And eventually you want to find an on-ramp, >> Yeah. >> to a roadmap, you know, that's aligned to a business unit, or a new emerging, you know, technology. >> How does someone come up with an idea and say, "Hey, you know, I want to do this"? Do they submit, like, a form? Is there a proposal? Who approves it? I mean, do you get involved? How does that process work? >> So that's a good question. It really depends on the engineer, right? You take someone who's just a new college grad, straight out of, you know, college. That's why we have these five programs. Because some of these folks, they've got a good idea, but they don't really know how to frame it, pitch it. And so if you've got a good idea, and let's say, this is your first rodeo, so to speak, We have a program called TechTalks where it allows you to actually go and pitch your idea; get some feedback. And that's sometimes where you get the best feedback, because you go and, you know, present your idea, and somebody will come back and say, "Well, you know, have you met, you know, Johnny and Sue over there, in this group? They're actually working on something similar. You should go and talk to them, maybe you guys can bring your ideas together." Folks that are, you know, more seasoned, you know, longer tenure, sometimes they just come up, and-- "I'm going to pitch an idea to xLabs," and for xLabs, for example --that's an internal incubator-- there is, like, a submissions process. We want to obviously make sure, that, you know, your idea's timing in the market's correct, we've got limited funding there so we're going to make sure we're really investing on the right, you know, type of ideas. But if you don't want to go and pitch your idea and get feedback, go and do a Borathon. Turn an idea into a little prototype. And we see a lot of that happening, and some of the greatest ideas are coming from our Borathons, you know? And it's also about tracking the journey. So, we have RADIO here today, we have mentioned xLabs, TechTalks, we have another program called Flings. Some of our engineers are shipping product, and they've got an idea to augment the product. They put it out as a Fling, and our customers and the ecosystem download these, and it augments the product. And then we get great feedback. And then that makes it back into the product roadmap. So there's a lot of different ways to do it, and RADIO, the process for RADIO, there's a lot of rigor in it. It's, like, it's run as a research program. >> Lisa: It's a call for papers, right? >> Call for papers, you know, there's a strict format, it's got to be, you know, this many pages; if you go over about one line, you're sort of, disqualified, so to speak. And then once you've got those papers, like this year we had 560 papers be submitted, out of those 560, 31 made it onto mainstage, and another 61 made it as posters, as you can see in the room we're sitting in. >> I have an idea. Machine learning should get all those papers. (laughs) I mean, that's-- >> Funny you say that. We actually have, one of our engineers, Josh Simons, is actually using machine learning to go back in time and look at all the submissions. So idea harvesting is something we're paying a lot of attention to, because you submit an idea, >> Interesting. >> the market may not be right for it, or reality is, I just don't have a budget to fund it if it's an xLab. >> John: So it's like a Google search for your, kind of, the indexing all those workers. >> Internally, yeah, and sometimes it's-- there's a great idea here, you merge that with another idea from another group or another geo, and then you can actually go and fund something. >> Well, that's important because timing is critical, in these early-- most stuff can be early in just incubation, gestation period for that tech or concept, could be in play because the computer-- all the new things, right? >> Correct. And, do you actually have the time? You're an engineer working on a release, the priority is getting that release out the door, right? >> (laughs) >> So, put the idea on the back burner, come off the release, and then, you know, get a couple of colleagues together and maybe there's a Borathon being held and you go and move that idea forward that way. Or, it's time for RADIO submissions, get a couple of colleagues together and submit a RADIO paper. So we want to have different platforms for our engineers to submit ideas outside of their day job. >> And it sounds like, the different programs that you're talking about: Flings, xLab, Borathon, RADIO, what it sounds like is, there isn't necessarily a hierarchy that ideas have to go through. It really depends on the teams that have the ideas, that are collaborating, and they can put them forward to any of these programs, >> Correct, yeah. >> and one might get, say, rejected for RADIO, but might be great for a Borathon or a Fling? >> Correct. >> So they've got options there, and there's multiple committees, I imagine? Is that spearheaded out of Ray's OCTO group, >> Yep. >> that's helping to make the selections? Tell us a little bit about that process. >> Sure, so. That's a great point, right? To get an idea out the door, you don't always have to take the same pathway. And so one thing we started tracking was these innovation journeys that all take different pathways. We just published an impact report on innovation for FY19, and we've got the vSAN story in there, right? It was an idea. A group of engineers had an idea, like, in 2009, and they worked on their idea a little bit-- it first made it to RADIO in 2011. And then they came back in 2013, and, sort of, the rest is history, you know. vSAN launched in 2014. We had a press release this week for Carbon Avoidance Meter. It was an idea that actually started as a calculator many years ago. Was used, and then sort of died on the vine, so to speak? One of our SEs said, "You know, this is a good idea. I want to evolve this a little bit further." Came and pitched an xLabs idea, and we said, "Alright, we're going to fund this as an xLabs Lite. Three to six months project, limited funding, work on one objective --you're still doing your day job-- move the project forward a little bit." Then Nicola Acutt, our Sustainability VP, got involved, wanted to move the idea a little bit further along, came back for another round of funding through an xLabs Lite, and then GSS, with their Skyline platform, picked it up, and that's going to be integrated in the coming months into Skyline, and we're going to be able to give our customers a carbon, sort of, readout of their data center. And then they'll be able to, you know, map that, and get a bigger picture, because obviously, it's not just the servers that are virtualized, there's cooling in the data center plants, and all these other factors that you've got to, you know, take into account when you want to look at your carbon footprint for your facility. So, we have lots of examples of how these innovation pathways take different turns, and sometimes it's Team A starting with an idea, Team B joins in, and then there's this convergence at a particular point, and then it goes nowhere for a couple of months, and then, a business unit picks it up. >> One of the things that's come out-- Pat Gelsinger mentioned that a theme outside of the normal product stuff is how people do work. There's been some actual R&D around it, because you guys have a lot of distributed, decentralized operations in R&D because of the global nature. >> Yeah. >> How should companies and R&D be run when the reality is that developers could be anywhere? They could be at a coffee shop, they could be overseas, they could be in any geography, how do you create an environment where you have that kind of innovation? Can you just share some of the best practices that you guys have found? >> I'm not sure if there's 'best practices', per se, but to make sure that the programs are open and inclusive to everybody on the planet. So, I'll give you some stats. For example, when RADIO started in the early days, we were founded in Palo Alto. It was a very Palo Alto-centric company. And for the first few years, if you looked at the percentage of attendees, it was probably over 75% were coming from Palo Alto. We've now over the years shifted that, to where Palo Alto probably represents about 44%, 16% is the rest of North America, and then the balance is from across the globe. And so that shift has been deliberate, obviously that impacts the budget a little bit, but in our programs, like a Borathon, you can hack from anywhere. We've got a lot of folks that are remote office workers, using, you know, collaborative tools, they can be part of a team. If the Borathon's happening in China, it doesn't stop somebody in Palo Alto or in Israel or in Bulgaria, participating. And, you know, that's the beautiful nature of being global, right? If you think about how products get out of the door, sometimes you've got teams and you are literally following the sun, and you're doing handoff, you know, from Team A to B to C, but at the end of the day you're delivering one product. And so that's just part of our culture, I mean, everybody's open to that, we don't say, "Oh, we can't work with those guys because they're in that geo-location." It's pretty open. >> This is also, really, an essential driver, and I think I saw last year's RADIO, there were participants from 25+ countries. But this is an essential-- not only is VMware a global company, but many of your customers are as well, and they have very similar operating models. So that thought diversity, to be able to build that into the R&D process is critical. >> Absolutely. And also, think about, you know, when you're going to Europe. Smaller borders, countries, you deploy technology differently. And so, you want to have that diversity in thought as well, because you don't just want to be thinking, "Alright, we're going to deploy a disaster recovery product in North America where they can fail over from, you know, East Coast to West Coast. You go to Europe, and typically you're failing over from, you know, site A to site B, and they're literally three or four miles apart. And so, just having that perspective as well, is very important. And we see that, you know, when we release certain products, you'll get, you know, better uptick in a certain geo, and then, "Why is it stalling over here?" well it's, sometimes it's cultural, right? How do you deploy that technology? Just because it works in the US, doesn't mean it's going to work in Europe or in APJ. >> How was your team involved in the commercialization? You mentioned vSAN and the history of that, but I'm just wondering, looking at it from an investment standpoint of deciding which projects to invest in, and then there's also the-- if they're ready to go to market, the balance of "How much do we need to invest in sales and marketing to be able to get this great idea-- because if we can't market it and sell it, you know, then there's obviously no point." So what's that balance like, within your organization, about, "how do we commercialize this effectively, at scale"? >> So that is ultimately not the responsibility of my group. We'll incubate ideas, like, for example, through an xLabs project. And, you know, sometimes we'll get to a point and we'll work, collaborate with a business unit, and we'll say, "Alright, we feel this project's probably a 24 months project", if it's an xLabs Full. So these folks are truly giving up their day job. But at the end of the day, you want to have an exit and when we say exit, what does that exit mean? Is that an exit into a business unit? Are you exiting the xLabs project because we're now out of funding? You know, think about a VC, I'm going to fund you to, you know, to a particular point; if there is no market traction, >> Right. >> we may, you know, sunset the project. And, you know, so our goal is to get these ideas, select which ones we want to invest in, and then find a sort of off-ramp into a business unit. And sometimes there'll be an off-ramp into a business unit, and the project goes on for a couple of months, and then we make a decision, right? And it's not a personal decision, it's like, "Well we funded that as an xLabs; we're now going to shut it down because, you know, we're going to go and make an acquisition in this space. And with the talent that's going to come onboard, the talent that was working on this xLab project, we can push the agenda forward." >> John: You have a lot of action going on so you move people around. >> Exactly. >> Kind of like the cloud, elastic resource, yeah? (laughs) >> So, then, some of these things, because xLabs is only a two-year-old, you know, we haven't had things exit yet that are, you know, running within a business unit that we're seeing this material impact. You know, from a revenue point of view. So that's why tracking the journeys is very important. And, you know, stay tuned, maybe in about three or four years we'll have this, similar, you know, interview, and I'll be able to say, "Yeah, you know, that started as an xLab, and now it's three years into the market, and look at the run rate. >> So there's 31-- last question for you-- there's 31 projects that were presented on mainstage. Are there any that you could kind of see, early on, "ooh", you know, those top five? Anything that really kind of sticks out-- you don't have to explain it in detail, but I'm just curious, can you see some of that opportunity in advance? >> Absolutely. There's been some great papers up on mainstage. And covering, you know, things on the networking side, there's a lot of innovation going in on the storage side. If you think about data, right, the explosion of data because of edge computing, how are you going to manage that data? How are you going to take, you know, make informed decisions on that data? How can you manipulate that data? What are you going to have to do from a dedupe point of view, or a replication point of view, because you want to get that to many locations, quickly? So, I saw some really good papers on data orchestration, manipulation, get it out to many places, it can take an informed decision. I saw great-- there was a great paper on, you know, you want to go and put something in AWS. There's a bull that you get at the end of the month, right? Sometimes those bulls can be a little bit frightening, right? You know, what can you do to make sure that you manage those bulls correctly? And sometimes, the innovation has got nothing to do with the product per se, but it has to do with how we're going to develop. So we have some innovation on the floor here where an engineer has looked at a different way of, basically, creating an application. And so, there's a ton of these ideas, so after RADIO, it doesn't stop there. Now the idea harvesting starts, right? So yes, there were 31 papers that made it onto mainstage, 61 that are posters here. During that review process, and you asked that question earlier and I apologize, I didn't answer it-- you know, when we look at the papers, there's a team of over 100 folks from across the globe that are reviewing these papers. During that review process, they'll flag things like "This is not going to make it onto mainstage, but the idea here is very novel; we should send this off to our IP team," you know. So this year at RADIO, there were 250 papers that were flagged for further followup with our IP team, so, do we go and then file an IDF, Invention Disclosure Form, do those then become patents, you know? So if we look at the data last year, it was 210. Out of those 210, 74 patents were filed. So there's a lot of work that now will happen post-RADIO. Some of these papers come in, they don't make it onto mainstage; they might become a poster. But at the same time they're getting flagged for a business unit. So from last year, there were 39 ideas that were submitted that are now being mapped to roadmap across the BUs. Some of these papers are great for academic research programs, so David Tennenhouse's research group will take these papers and then, you know, evolve them a little bit more, and then go and present them at academic conferences around the world. So there's a lot of, like, the "what's next?" aspect of RADIO has become a really big deal for us. >> The potential is massive. Well, Mornay, thank you so much for joining John and me, >> Thank you. >> and I've got to follow xLabs, there's just a lot of >> (laughs) >> really, really, innovative things that are so collaborative, coming forward. We thank you for your time. >> Thank you. >> For John Furrier, I'm Lisa Martin; you're watching theCUBE, exclusive coverage of VMware RADIO 2019, from San Francisco. Thanks for watching.