>> Announcer: Live from Nice, France, it's The Cube covering Dot Next Conference 2017, Europe. Brought to you by Nutanix. (techno music) >> Welcome back, I'm Stu Miniman happy to welcome back to our program, from the IBM Cognitive Systems Group, we have Bob Picciano and Stefanie Chiras. Bob, fresh off the keynote, uh speech. Went a little bit long but glad we could get you in. Um, I think when the, when the IBM Power announcement with Nutanix got out there, a lot of people were trying to put the pieces together and understand. You know, we with The Cube we've, we've been tracking, you know, Power for quite a while, Open Power, all the things but, but I have to admit that even myself, it was like, okay, I understand cognitive systems. We got all this AI things and everything but on the stage this morning, you kind of talked a little bit about the chipset and the bandwidth. You know, things like GPUs and utilization, you know, explain to us, you know, what is resonating with customers and, you know, where, you know, what's different about this because a lot of the other ones it's like, oh well, you know, software runs a lot of places and it doesn't matter that much. What's important about cognitive systems for Nutanix? >> Yeah, so, first off, thanks Stu. And, as always, thanks for, you know, you for following us and understanding what we're doing. You mentioned not just Power but you mentioned Open Power, and I think that's important. It shows, actually, the deeper understanding. You know, we've come a long way in a very short amount of time with what we've done with Open Power. Open Power was very much at it's core about really making Power a natural choice for industry standard Linux, right? The Linuxes that used to run on Power a couple of generations ago were more proprietary Linuxes. They were Big Endian Linux but Open Power was about making all that industry standard software run on top of Power where we knew our value proposition would shine based on how much optimization we put into our cores and how much optimization we put into IO bandwidth and memory bandwidth. And boy, you know, have we been right. In fact, when we take an industry standard workload like a no sequel database or Enterprise DB, or a Mongoloid DB, Hadoop, and put it on top of Linux, an industry standard Linux, on top of Power, we typically see that run about 2X to 3X better price performance on Linux on Power than it would on Linux on Intel. This is a repeating pattern. And so, what we're trying to do here is uh, really enable that same efficiency and economics to the Nutanix Hyper Converged Space. And remember, all these things about insight based applications, artificial intelligence, are all about data intensive workloads. Data intensive workloads and that's what we do best. So we're bringing the best of what we do and the optionality now for these AI workloads and cognitive systems right into the heart of what Nutanix is pivoting to as well. Which is really at the, at the core of the enterprise for data intensive workloads. Not just, you know, edge related VDI based workloads. Stefanie will you, you want to comment on that a little bit as well. >> Yeah, we are so focused on being prioritized and what space we go after in the Linux market around these data centric and AI workloads. And at the end of the day, you know, Nutanix has Nutanix states. It's about invisible infrastructure, but the infrastructure underneath matters. And now with the simplicity of what Nutanix brings you can choose the best infrastructure for the workloads that you decide to run, all with single pane of glass management. So it allows us to bring our capabilities at the infrastructure levels for those workloads, into a very simplest, simple deployment model under a Nutanix private cloud. >> Yeah, I, I think back when, you know, we had things like, when Hadoop came out, you know, we got all these new modern databases, >> Right. >> You know, I wanted to change the infrastructure but simplicity sure wasn't there. >> Yep. >> Uh-huh. >> It was a couple of servers sitting under the desk, okay, but when you needed to scale, when you needed to manage the environment, um, it was challenging. We, we saw, when, you know, Wikibon for years was doing, you know, research on big data and it was like, ah, you know, half the deployments are failing because, you know, it wasn't what they expected. >> Right. >> The performance wasn't there, the cost was challenging. So it feels like we're kind of, you know, turn the corner on, you know, making, putting the pieces together to make these solutions workable. >> I think we are. I think Dheeraj and his team, Sunil, they've done a wonderful job on making the one click simplicity, ease of deployment, ease of manageability. We saw today, creation of availability zones. High availability infrastructure. Very very simplistic. So, you know, as, you know, I've had other segments with Dave and John in the past, we've always talked about, it's not about big data, it's about really creating the ability to get fast actionable insights. So it's a confluence of that date environment, the processed based workflow environment, and then making that all simple. And this feels like a very natural way to accomplish that. >> I want to understand, if I caught right, it's not Power or x86 but it's really putting the right workloads in the, in the right place. >> That's right. >> Did I get that right? >> That's right. >> What, what are the customer deployments, you know? >> Heterogeneity is key. >> How do I then manage those environments because, you know, I, I want kind of homogeneity of, of management, even if I have heterogeneity, you know, in, in my environment, you know. What, what are you hearing from your customers? >> I think how we've looked at Linux evolved. The set of workloads that are being run on Linux have evolved so dramatically from where they started to running companies and being much more aggressive on compute intensive. So it's about when you bring total cost of ownership which requires the ability to simply manage your operations in a data center. Now the best of Prism capabilities along with the Acropolis stack allows simplicity of single pane of glass management for you to run your Power node, set of nodes, side by side with your x86 set of nodes. So what you want to run on x86 or Windows can now be run seamlessly and compatible with your data centric workloads and data driven workloads, or AI workloads on your Power nodes. It really is about bringing total cost of ownership down. And that really requires accessibility and it requires simplicity of management. And that's what this partnership really brings. It's a new age for hyper converged. >> Yeah. >> What should we be looking for, for the partnership, kind of over the next 12 years, 12, 12 months. (laughs) >> 12 years? (laughs) (laughter) >> 12 years might be a little tough to predict, but over the next year, what, what should we be looking for the partnership? You know, I think back you talked about, Open Powered Google is, you know, a big partner there. Is there a connection? Am I drawing lines between, you know, Nutanix and Google and what you're doing? >> I won't comment on that yet but, you know, but, as you know we have a big rollout coming up as we're getting ready to launch Power Nine. So there'll be more news on some of those fronts as we go through the coming weeks. And I hope to see you down in Dallas at our Cloud or Cognitive event. Or at one of the other events we'll be jointly at where we do some of these announcements. But if you think about where this naturally takes us, Sunil talked about mode one and mode two applications. So what we want to see is increasing that catalog for mode one applications. So things that I'd like to see is an expanded set of relationships around what we both do in the SAP space. I'd like to see that catalog of support enriched for what's out there on top of the Linux on Power space, where we know our value proposition will continue to be demonstrated both in total cost of acquisition as well as total cost of ownership. >> Yeah. >> I mean, we're really, you know, seeing some great results on our Linux base. As you know, it's now about 20 percent of the power revenue base is from Linux. >> Uh-huh. >> And that's grown from a very small amount just a few years ago. So, I look to see that and then I would look at more heterogeneity in terms of the support of what we do, both in Linux and maybe, in the future, also what we do to support the AIX workloads, uh, with Nutanix as well. Because I do think our clients are asking about that optionality. They have big investments, mission critical workloads around AIX and the want to start to bring those worlds together. >> Alright and Stefanie, want to give you the final word, you know, anything kind of learnings that you've had, of the relationships as you've been getting out and getting into those customer environments. >> I have to say the excitement coming in from the sales team, from our clients, and from the business partners have been incredible. It really is about the coming together of, not only two spaces of simple, and absolutely the best infrastructure and being able to optimize from bottom to top, but it's about taking hyper converge to a new set of workloads. A new space. Um, so the excitement is just incredible. I am thrilled to be here at Dot Next and be able to talk to our clients and partners about it. >> Alright well Stefanie and Bob thank you so much for joining us. >> Thanks Stu. >> Thank you Stu. >> Sorry we had to do a short segment but we'll be catching ya up at many more. Alright so we'll be back with lots more coverage here from Nutanix Dot Next in Nice, France. I'm Stu Miniman, you're watching The Cube. (techno music)

>> Narrator: Live, from Las Vegas, it's theCUBE. Covering IBM Think, 2018. Brought to you by IBM >> Hello everyone, welcome back to theCUBE, we are here on the floor at IBM Think 2018 in theCUBE studios, live coverage from IBM Think. I'm John Furrier, the host of theCUBE, and we're here with Stefanie Chiras, who is the Vice President of Offering Management IBM Cognitive Systems, that's Power Systems, a variety of other great stuff, real technology performance happening with Power, it's been a good strategic bet for IBM. Stefanie, great to see you again, thanks for coming back on theCUBE. >> Absolutely, I love to be on, John, thank you for inviting me. >> When we we had a brief (mumbles) Bob Picciano, who's heading up Power and that group, one of the things we learned is there's a lot of stuff going on that's really going to be impacting the performance of things. Just take a minute to explain what you guys are offering in this area. Where does it fit into the IBM portfolio? What's the customer use cases? Where does that offering fit in? >> Yeah, absolutely. So I think here at Think it's been a great chance for us to see how we have really transformed. You know, we have been known in the market for AIX and IBMI. We continue to drive value in that space. We just GA'd on, yesterday, our new systems, based Power9 Processor chip for AIX and IBMI in Linux. So that remains a strong strategic push. Enterprise Linux. We transformed in 2014 to embrace Linux wholeheartedly, so we really are going after now the Linux base. SAP HANA has been an incredible workload where over a thousand customers run in SAP HANA. And boy we are going after this cognitive and AI space with our performance and our acceleration capabilities, particularly around GPUs, so things like unique differentiation in our NVLink is driving our capabilities with some great announcements here that we've had in the last couple of days. >> Jamie Thomas was on earlier, and she and I were talking about some of the things around really the software stack and the hardware kind of coming together. Can you just break that out? Because I know Power, we've been covering it, Doug Balog's been on many times. A lot of great growth right out of the gate. Ecosystem formed right around it. What else has happened? And separate out where the hardware innovation is and technology and what's software and how the ecosystem and people are adopting it. Can you just take us through that? >> Yeah, absolutely. And actually I think it's an interesting question because the ecosystem actually has happened on both sides of the fence, with both the hardware side and the software side, so OpenPOWER has grown dramatically on the hardware side. We just released our Power9 processor chip, so here is our new baby. This is the Power9. >> Hold it up. >> So this is our Power9 here, 8 billion transistors, 14 miles of wiring and 17 layers of metal, I mean it's a technology wonder. >> The props are getting so small we can't even show on the camera. (laughing) >> This is the Moore's Law piece that Jenny was talking about in her keynote. >> That's exactly it. But what we have really done strategically is changed what gets delivered from the CPU to more what gets delivered at a system level, and so our IO capabilities. First chip to market, delivering the first systems to market with PCIe Gen 4. So able to connect to other things much faster. We have NVLink 2.0, which provides nearly 10x the bandwidth to transport data between this chip and a GPU. So Jensen was onstage yesterday from NVIDIA. He held up his chip proudly as well. The capabilities that are coming out from being able to transport data between the power CPU and the GPU is unbelievable. >> Talk about the relationship with NVIDIA for a second, 'cause that's also, NVIDIA stocks up a lot of (mumbles) the bitcoin mining graphics card, but this is, again, one use case, NVIDIA's been doing very well, they're doing really well in IOT, self-driving cars, where data performance is critical. How do you guys play in that? What's the relationship with NVIDIA? >> Yeah, so it has been a great partnership with NVIDIA. When we launched in 2013, right at the end of 2013 we launched OpenPOWER, NVIDIA was one of the five founding members with us, Google, Mellanox, and Tyan. So they clearly wanted to change the game at the systems value level. We launched into that with we went and jointly bid with NVIDIA and Mellanox, we jointly bid for the Department of Energy when we co-named it Coral. But that came to culmination at the end of last year when we delivered the Summit and Sierra supercomputers to Oak Ridge and Lawrence Livermore. We did that with innovation from both us and NVIDIA, and that's what's driving things like this capability. And now we bring in software that exploits it. So that NVLink connection between the CPU and the GPU, we deliver software called PowerAI, we've optimized the frameworks to take advantage of that data transport between that CPU and GPU so it makes it consumable. With all of these things it's not just about the technology, it's about is it easy to consume at the software level? So great announcement yesterday with the capabilities to do logistic regression. Unbelievable, taking the ability to do advertising analytics, taking it from 70 minutes to 1 and 1/2. >> I mean we're going to geek out here. But let's go under the hood for a second. This is a really kind of a high end systems product, at the kind of performance levels. Where does that connect to the go to market? Who's the buyer of it? Is it OEMs? Is it integrators? Is it new hardware devices? How do I get involved and who's the target customer? And what kind of developers are you reaching? Can you just take us through that who's buying this product? >> So this is no longer relegated to the elite set. What we did, and I think this is amazing, when we delivered the Summit and Sierra, right? Huge cluster of these nodes. We took that same node, we pulled it into our product line as the AC922, and we delivered a 4 GPU air-cooled version to market. On December 22nd we GA'd, of last year. And we sold to over 40 independent clients by the end of 2017, so that's a short runway. And most of it, honestly, is all driven around AI. The AI adoption, and it's a cross enterprise. Our goal is really to make sure that the enterprises who are looking at AI now with their developer are ready to take it into production. We offer support for the frameworks on the system so they know that when they do development on this infrastructure, they can take it to production later. So it's very much driven toward taking AI to the enterprise, and it's all over. It's insurance, it's financial services sector. It's those kinds of enterprise that are using AI. >> So IO sensitive, right? So IOT not a target or maybe? >> So you know when we talk out to edge it's a little bit different, right? So the IOT today for us is driving a lot of data, that's coming in, and then you know at different levels-- >> There's not a lot of (mumbles) power needed at the edge. >> There is not, there is not. And it kind of scales in. We are seeing, I would say, kind of progression of that compute moving out closer. Whether or not it's on, it doesn't all come home necessarily anymore. >> Compute is being pushed to where the data is. >> Stefanie: Absolutely right. >> That's head room for you guys. Not a priority now because there's not an intense (mumbles) compute can solve that. >> Stefanie: That's right. >> All right, so where does the Cloud fit into it? You guys powering IBMs Cloud? >> So IBM Cloud has been a great announcement this year as well. So you've seen the focus here around AI and Cloud. So we announced that HANA will come on Power into the Cloud, specializing in large memory sets, so 24 terabyte memory sets. For clients that's huge to be able to exploit that-- >> Is IBM Cloud using Power or not? >> That will be in IBM Cloud. So go to IBM Cloud, be able to deploy an SAP certified HANA on Power deployment for large memory installs, which is great. We also announced PowerAI access, on Power9 technology in IBM Cloud. So we definitely are partnering both with IMB Cloud as well as with the analytics pieces. Data Science Experience available on Power. And I think it's very important, what you said earlier, John, about you want to bring the capabilities to where the data is. So things like a lot of clients are doing AI on prem where we can offer a solution. You can augment that with capabilities like Watson, right? Off prem. You can also do dev ops now with AI in the IBM Cloud. So it really becomes both a deployment model, but the client needs to be able to choose how they want to do it. >> And the data can come from multiple sources. There's always going to be latencies. So what about blockchain? I want to get to blockchain. Are you guys doing anything in the blockchain ecosystem? Obviously one complaint we've been hearing, obviously, is some of these cryptocurrency chains like Ethereum, has performance issues, they got projects coming out. A lot of open source in there. Is Power even puttin' their toe in the water with blockchain? >> We have put our toe in the water. Blockchain runs on Power. From an IBM portfolio perspective-- >> IBM blockchain runs on Power or blockchain, or other blockchains? >> Like Hyperledger. Like Hyperledger will run. So open source, blockchain will run on Power, but if you look at the IBM portfolio, the security capabilities in Z14 that that brings and pulling that into IBM Cloud, our focus is really to be able to deliver that level of security. So we lead with system Z in that space, and Z has been incredible with blockchain. >> Z is pretty expensive to purchase, though. >> But now you can purchase it in the Cloud through IBM Cloud, which is great. >> Awesome, this is the benefit of the Cloud. Sounds like soft layer is moving towards more of a Z mainframe, Power, backend? >> I think the IBM Cloud is broadening the capabilities that it has, because the workloads demand different things. Blockchain demands security. Now you can get that in the Cloud through Z. AI demands incredible compute strength with GPU acceleration, Power is great for that. And now a client doesn't have to choose. They can use the Cloud and get the best infrastructure for the workload they want, and IBM Cloud runs it. >> You guys have been busy. >> We've been busy. (laughing) >> Bob Picciano's been bunkered in. You guys have been crankin' out... love to do a deeper dive on this, Stefanie, and so we'd love to follow up with you guys, and we told Bob we would dig into that, too. Question I have for you now is, how do you talk about this group that you're building together? You know, the names are all internal IBM names, Power... Is it like a group? Do you guys call yourself like the modern infrastructure group? Is it like, what is it called, if you had to explain it to outside IBM, AIs easy, I know what AI team does. You're kind of doing AI. You're enabling AI. Are you a modern infrastructure? What is the pillar are you under? >> Yeah, so we sit under IBM systems, and we are definitely systems proud, right? Everything runs on infrastructure somewhere. And then within that three spaces you certainly have Z storage, and we empower, since we've set our sites on AI and cognitive workloads, internally we're called IBM Cognitive Systems. And I think that's really two things, both a focus on the workloads and differentiation we want to bring to clients, but also the fact that it's not just about the hardware, we're now doing software with things like PowerAI software, optimized for our hardware. There's magic that happens when the software and the hardware are co-optimized. >> Well if you look, I mean systems proud, I love that conversation because you look at the systems revolution that I grew up in, the computer science generation of the 80s, that was the open movement, BSD, pre-Linux, and then now everything about the Cloud and what's going on with AI and what I call the innovation sandwich with data in the middle and blockchain and AI as bread. >> Stefanie: Yep. >> You have all the perfect elements of automation, you know, Cloud. That's all going to be powered by a system. >> Absolutely. >> Especially operating systems skills are super imprtant. >> Super important. Super important. >> This is the foundational elements. >> Absolutely, and I think your point on open, that has really come in and changed how quickly this innovation is happening, but completely agree, right? And we'll see more fit for purpose types of things, as you mentioned. More fit for purpose. Where the infrastructure and the OS are driving huge value at a workload level, and that's what the client needs. >> You know, what dev ops proved with the Cloud movement was you can have programmable infrastructure. And what we're seeing with blockchain and decentralized web and AI, is that the real value, intellectual property, is going to be the business logic. That is going to be dealing with now a whole 'nother layer of programmability. It used to be the other way around. The technology determined >> That's right. >> the core decision, so the risk was technology purchase. Now that this risk is business model decision, how do you code your business? >> And it's very challenging for any business because the efficiency happens when those decisions get made jointly together. That's when real business efficiency. If you make one decision on one side of the line or the other side of the line only, you're losing efficiency that can be driven. >> And open is big because you have consensus algorithms, you got regulatory issues, the more data you're exposed to, and more horsepower that you have, this is the future, perfect storm. >> Perfect storm. >> Stefanie, thanks for coming on theCUBE, >> It's exciting. >> Great to see you. >> Oh my pleasure John, great to see you. >> You're awesome. Systems proud here in theCUBE, we're sharing all the systems data here at IBM Think. I'm John Furrier, more live coverage after this short break. All right.

[Voiceover] - Live from Washington D.C. It's theCUBE covering dot next conference. Brought to you by Nutanix. >> Welcome back to the district everybody. This is Nutanix NEXTconf, hashtag NEXTconf. And this is theCUBE, the leader in live tech coverage. Stephanie Chiras is here. She's the Vice President of IBM Power Systems Offering Management, and she's joined by Raja Mukhopadhyay who is the VP of Product Management at Nutanix. Great to see you guys again. Thanks for coming on. >> Yeah thank you. Thanks for having us. >> So Stephanie, you're welcome, so Stephanie I'm excited about you guys getting into this whole hyper converged space. But I'm also excited about the cognitive systems group. It's kind of a new play on power. Give us the update on what's going on with you guys. >> Yeah so we've been through some interesting changes here. IBM Power Systems, while we still maintain that branding around our architecture, from a division standpoint we're now IBM Cognitive Systems. We've been through a change in leadership. We have now Senior Vice President Bob Picciano leading IBM Cognitive Systems, which is foundationally built upon the technology that's comes from Power Systems. So our portfolio remains IBM Power Systems, but really what it means is we've set our sights on how to take our technology into really those cognitive workloads. It's a focus on clients going to the cognitive era and driving their business into the cognitive era. It's changed everything we do from how we deliver and pull together our offerings. We have offerings like Power AI, which is an offering built upon a differentiated accelerated product with Power technology inside. It has NVIDIA GPU's, it has NVLink capability, and we have all the optimized frameworks. So you have Caffe, Torch, TensorFlow, Chainer, Theano. All of those are optimized for the server, downloadable right in a binary. So it's really about how do we bring ease of use for cognitive workloads and allow clients to work in machine learning and deep learning. >> So Raja, again, part of the reason I'm so excited is IBM has a $15 billion analytics business. You guys talk, you guys talked to the analysts this morning about one of the next waves of workloads is this sort of data oriented, AI, machine learning workloads. IBM obviously has a lot of experience in that space. How did this relationship come together, and let's talk about what it brings to customers. >> It was all like customer driven, right? So all our customers they told us that, look Nutanix we have used your software to bring really unprecedented levels of like agility and simplicity to our data center infrastructure. But, you know, they run at certain sets of workloads on, sort of, non IBM platforms. But a lot of mission critical applications, a lot of the, you know, the cognitive applications. They want to leverage IBM for that, and they said, look can we get the same Nutanix one click simplicity all across my data center. And that is a promise that we see, can we bring all of the AHV goodness that abstracts the underlying platform no matter whether you're running on x86, or your cognitive applications, or your mission critical applications on IBM power. You know, it's a fantastic thing for a joint customer. >> So Stephanie come on, couldn't you reach somewhere into the IBM portfolio and pull out a hyper converged, you know, solution? Why Nutanix? >> Clients love it. Look what the hyper converged market is doing. It's growing at incredible rates, and clients love Nutanix, right? We see incredible repurchases around Nutanix. Clients buy three, next they buy 10. Those repurchase is a real sign that clients like the experience. Now you can take that experience, and under the same simplicity and elegance right of the Prism platform for clients. You can pull in and choose the infrastructure that's best for your workload. So I look at a single Prism experience, if I'm running a database, I can pull that onto a Power based offering. If I'm running a BDI I can pull that onto an alternative. But I can now with the simplicity of action under Prism, right for clients who love that look and feel, pick the best infrastructure for the workloads you're running, simply. That's the beauty of it. >> Raja, you know, Nutanix is spread beyond the initial platform that you had. You have Supermicro inside, you've got a few OEMs. This one was a little different. Can you bring us inside a little bit? You know, what kind of engineering work had to happen here? And then I want to understand from a workload perspective, it used to be, okay what kind of general purpose? What do you want on Power, and what should you say isn't for power? >> Yeah, yeah, it's actually I think a power to, you know it speaks to the, you know, the power of our engineering teams that the level of abstraction that they were able to sort of imbue into our software. The transition from supporting x86 platforms to making the leap onto Power, it has not been a significant lift from an engineering standpoint. So because the right abstractions were put in from the get go. You know, literally within a matter of mere months, something like six to eight months, we were able to have our software put it onto the IBM power platform. And that is kind of the promise that our customers saw that look, for the first time as they are going through a re-platforming of their data center. They see the power in Nutanix as software to abstract all these different platforms. Now in terms of the applications that, you know, they are hoping to run. I think, you know, we're at the cusp of a big transition. If you look at enterprise applications, you could have framed them as systems of record, and systems of engagement. If you look forward the next 10 years, we'll see this big shift, and this new class of applications around systems of intelligence. And that is what a lot-- >> David: Say that again, systems of-- >> Systems of intelligence, right? And that is where a lot of like IBM Power platform, and the things that the Power architecture provides. You know, things around better GPU capabilities. It's going to drive those applications. So our customers are thinking of running both the classical mission critical applications that IBM is known for, but as well as the more sort of forward leaning cognitive and data analytics driven applications. >> So Stephanie, on one hand I look at this just as an extension of what IBM's done for years with Linux. But why is it more, what's it going to accelerate from your customers and what applications that they want to deploy? >> So first, one of the additional reasons Nutanix was key to us is they support the Acropolis platform, which is KVM based. Very much supports our focus on being open around our playing in the Linux space, playing in the KVM space, supporting open. So now as you've seen, throughout since we launched POWER8 back in early 2014 we went Little Endian. We've been very focused on getting a strategic set of ISV's ported to the platform. Right, Hortonworks, MongoDB, EnterpriseDB. Now it's about being able to take the value propositions that we have and, you know, we're pretty bullish on our value propositions. We have a two x price performance guarantee on MongoDB that runs better on Power than it runs on the alternative competition. So we're pretty bullish. Now for clients who have taken a stance that their data center will be a hyper converged data center because they like the simplicity of it. Now they can pull in that value in a seamless way. To me it's really all about compatibility. Pick the best architecture, and all compatible within your data center. >> So you talked about, six to eight months you were able to do the integration. Was that Open Power that allowed you to do that, was it Little Endian, you know, advancements? >> I think it was a combination of both, right? We have done a lot from our Linux side to be compatible within the broad Linux ecosystem particularly around KVM. That was critical for this integration into Acropolis. So we've done a lot from the bottoms up to be, you know, Linux is Linux is Linux. And just as Raja said, right, they've done a lot in their platform to be able to abstract from the underlying and provide a seamless experience that, you know, I think you guys used the term invisible infrastructure, right? The experience to the client is simple, right? And in a simple way, pick the best, right for the workload I run. >> You talked about systems of intelligence. Bob Picciano a lot of times would talk about the insight economy. And so we're, you're right we have the systems of records, systems of engagement. Systems of intelligence, let's talk about those workloads a little bit. I infer from that, that you're essentially basically affecting outcomes, while the transaction is occurring. Maybe it's bringing transactions in analytics together. And doing so in a fashion that maybe humans aren't as involved. Maybe they're not involved at all. What do you mean by systems of intelligence, and how do your joint solutions address those? >> Yeah so, you know, one way to look at it is, I mean, so far if you look at how, sort of decisions are made and insights are gathered. It's we look at data, and between a combination of mostly, you know we try to get structured data, and then we try to draw inferences from it. And mostly it's human beings drawing the inferences. If you look at the promise of technologies like machine learning and deep learning. It is precisely that you can throw unstructured data where no patterns are obvious, and software will find patterns there in. And what we mean by systems of intelligence is imagine you're going through your business, and literally hundreds of terabytes of your transactional data is flowing through a system. The software will be able to come up with insights that would be very hard for human beings to otherwise kind of, you know infer, right? So that's one dimension, and it speaks to kind of the fact that there needs to be a more real time aspect to that sort of system. >> Is part of your strategy to drive specific solutions, I mean integrating certain IBM software on Power, or are you sort of stepping back and say, okay customers do whatever you want. Maybe you can talk about that. >> No we're very keen to take this up to a solution value level, right? We have architected our ISV strategy. We have architected our software strategy for this space, right? It is all around the cognitive workloads that we're focused on. But it's about not just being a platform and an infrastructure platform, it's about being able to bring that solution level above and target it. So when a client runs that workload they know this is the infrastructure they should put it on. >> What's the impact on the go to market then for that offering? >> So from a solutions level or when the-- >> Just how you know it's more complicated than the traditional, okay here is your platform for infrastructure. You know, what channel, maybe it's a question for Raja, but yeah. >> Yeah sure, so clearly, you know, the product will be sold by, you know, the community of Nutanix's channel partners as well as IBM's channels partners, right? So, and, you know, we'll both make the appropriate investments to make sure that the, you know, the daughter channel community is enabled around how they essentially talk about the value proposition of the solution in front of our joint customers. >> Alright we have to leave there, Stephanie, Raja, thanks so much for coming back in theCUBE. It's great to see you guys. >> Raja: Thank you. >> Stephanie: Great to see you both, thank you. >> Alright keep it right there everybody we'll be back with our next guest we're live from D.C. Nutanix dot next, be right back. (electronic music)