>>The cube presents HPE discover 2022 brought to you by HPE. >>Hello, everybody. Welcome to day three of the Cube's coverage of HPE discover 2022 we're live from Las Vegas and the Venetian convention center. This is I, I counted him up. I think this is the 14th HP HP slash HPE. Discover that we've done really excited to welcome in Alexia Clements. She's the vice president of go to market for HPE GreenLake cloud services. That's all the rage everybody's talking about. Green, all the wood behind the arrow, as the saying goes, welcome to the queue. Good to see >>You. Thank you so much for having me thrilled to be here. >>You walk up Janet Jackson last night, >>Epic. Wow. She killed it. She was awesome. >>I thought the band was super tight, but the other thing was the place was >>Packed. It was >>Nice. You know, what happens is a lot of time they put the band in the getaway day, you know, and nobody stays, but wow, the, the hall was jammed. >>It was great. It was, you could feel the momentum and the excitement. And it was just a great way to, to kind of end the, the HP discover. So it was great. >>Yeah. I mean, I, I mentioned that we've been to a lot of HP slash HPE discovers and, and this one was different in the sense that I think first of all, 8,000 people, yep. People are excited to get back together, but I think, you know, HPE has a spring in its step and the customers are kind of interested. It's much more focused than some of the past HPE discoverers, which was kind of hard to get my hands around. Sometimes the business was sort of an Antonio's pulled that together. So what's changed since the last time we were face to face. >>We're transforming and hope you all saw that on the, on the floor here. So, um, we're absolutely trans going through a transformation and, you know, I, I think we're, you know, we're shifting to an edge to cloud platform company. And with that, it's, it's how we approach our customers differently and our partners and, you know, we're hoping that, uh, we showed this week and that, that we're different and we're transforming. >>So how do you spend your time Mo mostly in front of customers having conversations about what, what their needs are and aligning is that right? >>Yeah. So, um, I, I lead the, the go to market for GreenLake. So that's everything around how we're driving our as a service go to market strategy, how we're driving programs, enablement, how we're really in the end, how we're executing on that as a service strategy from a sales perspective. >>So what do you hear? Of course, a lot of that involves partners. Yep. Right. I mean, that's kind of the route to market. Absolutely. The HPE prefers for obvious reasons, although others don't necessarily share that, but, but, so what are you hearing from the partner ecosystem and the customers that their biggest challenges are now that we're entering the let's call it the post isolation economy? <laugh> >>Yeah. I mean, the reality is, is digital transformations are hard and I think some customers, um, who haven't necessarily moved forward on it or, you know, maybe they move forward and they're realizing, Hey, I'm stuck and I'm not, I'm not getting to where I wanna be and really, you know, driving that end state. So, I mean, I, I would just say overall, I think things are like, customers are, are struggling if they didn't, you know, they're falling behind a little bit. And I think through the conversations that we're having and through HP green, like it gives customers choice. And so really, um, I mean, what, you know, I spend my time with, and, and when we're talking to customers and partners, it's about helping customers on that digital transformation journey and understanding what are they trying to drive? What business outcomes are they trying to drive and how we can help them get there. So >>I, I often call it the force March to digital yep. With the pandemic. Um, and, and I, I was looking at a survey recently, I think it was put on by couch base. And it was probably on a thousand respondents and it was a CIO survey and they asked who's, who's responsible for the digital transformation at the organization and overwhelmingly it was the it organization. And I said, uhoh, that's the problem now. But it made sense to me because when the economy shut down, everybody went to it and said help, right. Make this work somehow. Right. But, but what, that doesn't seem to me to be the right prescription for a successful digital transformation. Do you agree with that? And what do you see as a successful template for DX? >>Well, I think what, what we see is that really the lines of business are desperate to move fast and they're really looking for their it partners to help them in that journey and, and, and drive, you know, whether it be, you know, drive them, you know, drive orders, drive, you know, they need it to help them in that journey. And so really it's gotta be a partnership between the two organizations. And what we're trying to do with HP GreenLake is kind of abstract that almost. So, Hey, we're gonna give it to you in an, as a service and you're gonna get all of these components. And all you have to think about is where do I need to grow and what are the outcomes that I'm looking for? So that's what it's gotta be. There's gotta be tight alignment, I think between the lines of business and it, and sometimes those two don't know how to talk to each other. >>Mm-hmm <affirmative> so that's another way of, of really trying to speak to the business leaders and say, what are you trying to do? Where do you need to go? And what do you need to get? And, and a lot of times they don't even know what they need to get there. So that's where we need to have those different conversations with our customers to, and that's where we look for our partners to help us in that. So really having those different conversations to progress, um, what, you know, what customers are really looking to, to drive, >>How, how does GreenLake specifically accelerate that transformation? Where does it fit? Maybe you can kind of take us through, you know, a, a generic example of how that works. >>Yeah. I mean, a great example is, you know, especially with the pandemic is desktop, Hey, you now need to, you know, everybody's working from different locations. So, you know, desktop as a service VDI as a service, and, you know, you're putting it in a, you know, per whatever, you know, per you can, whatever variable pricing you want, but think about it, you have that one pay as you go. And so the it organization, all they have to think about is that's my, you know, per, per unit price there. So that's a great example of how we saw, like, especially during the pandemic, that was something that was, you know, a huge area of focus organizations. What's >>The spectrum that you see in terms of, you know, the maturity model, if you will, a digital transformation. I mean, if you weren't in a digital business during the pandemic, you were pretty much out of business. Yeah. And with very few exceptions. Um, and so, okay. So on the one end, you have folks that sort of were forced into it. You, my forced March scenario, others were actually moving quite a bit along before the pandemic, others were kind of given at lip service and maybe doing a few projects. What do you see as that spectrum? >>I think if you're not transforming, you're falling behind. And so everybody needs to be, you know, looking to the future and understanding, you know, really trying to get aggressive on that. And that's what we're seeing. We're seeing companies who, you know, aren't moving fast on that or falling behind. >>Do you see a bifurcation? I'm sure you do those that say, yeah, I want as a service and others that say, look, I I'm really well capitalized. I'm gonna gimme the, gimme the CapEx. I'm gonna put it in and run it myself. And is there a relationship between that approach and their digital transformation maturity, or is it kind of just really their preference? >>I, I mean, for us, we're meeting customers where they're at on their journey and their multi-cloud journey. So some, and, and what I'm seeing is that every customer today has multiple clouds, whether that be their, you know, their kind of, MultiGen it, the, the legacy stuff that they've gotta deal with. They've got stuff in public clouds, and they're trying to really transform and figure out how do I work all of that in like, how do I move forward with that new operating model? And so what I'm seeing is, you know, we're gonna meet customers where they're at on their journey. So some are gonna continue to go down that path in a, how they've always purchased their it. And others are really, you know, more often than not, we're seeing, they want that as a service cloudlike to have all the benefits of cloud, but yet still have it on their prem or in a colo or, you know, at the edge. So I do see some of those customers who are thinking differently, right. That, and they're the ones that are more apt to be a little bit more aggressive on their digital transformation. They're, they're open to the possibility if that makes sense. No, >>It does. It makes total sense. I, I, I think, you know, on the one hand they're a lot of customers are trying to build their own cloud. Yep. Um, so you mention multicloud, I'm not gonna go to Amazon to help me with my multicloud strategy. That's not, that's not gonna be my preferr. Yeah. I might talk to Microsoft about it a little bit. Google's got Antos and that's kind of interesting, but you know, Google's not enterprise, they got good data, but so, but there are other choices out there. Why HPE for my cloud hybrid multi-cloud strategy, give us the >>Sticker. It's, it's the best of both worlds for customers. So it enables them to have the security. It enables them to grow, to, to be in their data centers or in colos at the edge. It allows them to not over provision. It allows them to pay as they go and pay as they grow there's. Um, and then it also really is that ease factor. So it it's that thinking about it as I have, I already, I know what my pricing is. I know what that predictability is from a pricing perspective and what my costs are gonna be. So all of those things really re that all those messages resonate with customers, >>Right? L thanks so much for coming on. We got the trains are backing up super tight schedule today. This is wall to wall coverage of HPE. Discover. Thank you. Thank >>You so much for having me appreciate it. >>You're SU very welcome. All right. Keep it right there. Dave ante is here. John furrier, HPE discover 2022 from Las Vegas. We're live. We'll be right back.

>> Announcer: theCube presents HPE Discover 2022, brought to you by HPE. >> Hey, everyone. Welcome back to Las Vegas. This is Lisa Martin with Dave Vellante live at HPE Discover '22. Dave, it's great to be here. This is the first Discover in three years and we're here with about 7,000 of our closest friends. >> Yeah. You know, I tweeted out this, I think I've been to 14 Discovers between the U.S. and Europe, and I've never seen a Discover with so much energy. People are not only psyched to get back together, that's for sure, but I think HPE's got a little spring in its step and it's feeling more confident than maybe some of the past Discovers that I've been to. >> I think so, too. I think there's definitely a spring in the step and we're going to be unpacking some of that spring next with one of our alumni who joins us, Keith White's here, the executive vice president and general manager of GreenLake Cloud Services. Welcome back. >> Great. You all thanks for having me. It's fantastic that you're here and you're right, the energy is crazy at this show. It's been a lot of pent up demand, but I think what you heard from Antonio today is our strategy's changing dramatically and it's really embracing our customers and our partners. So it's great. >> Embracing the customers and the partners, the ecosystem expansion is so critical, especially the last couple of years with the acceleration of digital transformation. So much challenge in every industry, but lots of momentum on the GreenLake side, I was looking at the Q2 numbers, triple digit growth in orders, 65,000 customers over 70 services, eight new services announced just this morning. Talk to us about the momentum of GreenLake. >> The momentum's been fantastic. I mean, I'll tell you, the fact that customers are really now reaccelerating their digital transformation, you probably heard a lot, but there was a delay as we went through the pandemic. So now it's reaccelerating, but everyone's going to a hybrid, multi-cloud environment. Data is the new currency. And obviously, everyone's trying to push out to the Edge and GreenLake is that edge to cloud platform. So we're just seeing tons of momentum, not just from the customers, but partners, we've enabled the platform so partners can plug into it and offer their solutions to our customers as well. So it's exciting and it's been fun to see the momentum from an order standpoint, but one of the big numbers that you may not be aware of is we have over a 96% retention rate. So once a customer's on GreenLake, they stay on it because they're seeing the value, which has been fantastic. >> The value is absolutely critically important. We saw three great big name customers. The Home Depot was on stage this morning, Oak Ridge National Laboratory was as well, Evil Geniuses. So the momentum in the enterprise is clearly present. >> Yeah. It is. And we're hearing it from a lot of customers. And I think you guys talk a lot about, hey, there's the cloud, data and Edge, these big mega trends that are happening out there. And you look at a company like Barclays, they're actually reinventing their entire private cloud infrastructure, running over a hundred thousand workloads on HPE GreenLake. Or you look at a company like Zenseact, who's basically they do autonomous driving software. So they're doing massive parallel computing capabilities. They're pulling in hundreds of petabytes of data to then make driving safer and so you're seeing it on the data front. And then on the Edge, you look at anyone like a Patrick Terminal, for example. They run a whole terminal shipyard. They're getting data in from exporters, importers, regulators, the works and they have to real-time, analyze that data and say, where should this thing go? Especially with today's supply chain challenges, they have to be so efficient, that it's just fantastic. >> It was interesting to hear Fidelma, Keith, this morning on stage. It was the first time I'd really seen real clarity on the platform itself and that it's obviously her job is, okay, here's the platform, now, you guys got to go build on top of it. Both inside of HPE, but also externally, so your ecosystem partners. So, you mentioned the financial services companies like Barclays. We see those companies moving into the digital world by offering some of their services in building their own clouds. >> Keith: That's right. >> What's your vision for GreenLake in terms of being that platform, to assist them in doing that and the data component there? >> I think that was one of the most exciting things about not just showcasing the platform, but also the announcement of our private cloud enterprise, Cloud Service. Because in essence, what you're doing is you're creating that framework for what most companies are doing, which is they're becoming cloud service providers for their internal business units. And they're having to do showback type scenarios, chargeback type scenarios, deliver cloud services and solutions inside the organization so that open platform, you're spot on. For our ecosystem, it's fantastic, but for our customers, they get to leverage it as well for their own internal IT work that's happening. >> So you talk about hybrid cloud, you talk about private cloud, what's your vision? You know, we use this term Supercloud. This in a layer that goes across clouds. What's your thought about that? Because you have an advantage at the Edge with Aruba. Everybody talks about the Edge, but they talk about it more in the context of near Edge. >> That's right. >> We talked to Verizon and they're going far Edge, you guys are participating in that, as well as some of your partners in Red Hat and others. What's your vision for that? What I call Supercloud, is that part of the strategy? Is that more longer term or you think that's pipe dream by Dave? >> No, I think it's really thoughtful, Dave, 'cause it has to be part of the strategy. What I hear, so for example, Ford's a great example. They run Azure, AWS, and then they made a big deal with Google cloud for their internal cars and they run HPE GreenLake. So they're saying, hey, we got four clouds. How do we sort of disaggregate the usage of that? And Chris Lund, who is the VP of information technology at Liberty Mutual Insurance, he talked about it today, where he said, hey, I can deliver these services to my business unit. And they don't know, am I running on the public cloud? Am I running on our HPE GreenLake cloud? Like it doesn't matter to the end user, we've simplified that so much. So I think your Supercloud idea is super thoughtful, not to use the super term too much, that I'm super excited about because it's really clear of what our customers are trying to accomplish, which it's not about the cloud, it's about the solution and the business outcome that gets to work. >> Well, and I think it is different. I mean, it's not like the last 10 years where it was like, hey, I got my stuff to work on the different clouds and I'm replicating as much as I can, the cloud experience on-prem. I think you guys are there now and then to us, the next layer is that ecosystem enablement. So how do you see the ecosystem evolving and what role does Green Lake play there? >> Yeah. This has been really exciting. We had Tarkan Maner who runs Nutanix and Karl Strohmeyer from Equinix on stage with us as well. And what's happening with the ecosystem is, I used to say, one plus one has to equal three for our customers. So when you bring these together, it has to be that scenario, but we are joking that one plus one plus one equals five now because everything has a partner component to it. It's not about the platform, it's not about the specific cloud service, it's actually about the solution that gets delivered. And that's done with an ISV, it's done with a Colo, it's done even with the Hyperscalers. We have Azure Stack HCI as a fully integrated solution. It happens with managed service providers, delivering managed services out to their folks as well. So that platform being fully partner enabled and that ecosystem being able to take advantage of that, and so we have to jointly go to market to our customers for their business needs, their business outcomes. >> Some of the expansion of the ecosystem. we just had Red Hat on in the last hour talking about- >> We're so excited to partner with them. >> Right, what's going on there with OpenShift and Ansible and Rel, but talk about the customer influence in terms of the expansion of the ecosystem. We know we've got to meet customers where they are, they're driving it, but we know that HPE has a big presence in the enterprise and some pretty big customer names. How are they from a demand perspective? >> Well, this is where I think the uniqueness of GreenLake has really changed HPE's approach with our customers. Like in all fairness, we used to be a vendor that provided hardware components for, and we talked a lot about hardware costs and blah, blah, blah. Now, we're actually a partner with those customers. What's the business outcome you're requiring? What's the SLA that we offer you for what you're trying to accomplish? And to do that, we have to have it done with partners. And so even on the storage front, Qumulo or Cohesity. On the backup and recovery disaster recovery, yes, we have our own products, but we also partner with great companies like Veeam because it's customer choice, it's an open platform. And the Red Hat announcement is just fantastic. Because, hey, from a container platform standpoint, OpenShift provides 5,000 plus customers, 90% of the fortune 500 that they engage with, with that opportunity to take GreenLake with OpenShift and implement that container capabilities on-prem. So it's fantastic. >> We were talking after the keynote, Keith Townsend came on, myself and Lisa. And he was like, okay, what about startups? 'Cause that's kind of a hallmark of cloud. And we felt like, okay, startups are not the ideal customer profile necessarily for HPE. Although we saw Evil Geniuses up on stage, but I threw out and I'd love to get your thoughts on this that within companies, incumbents, you have entrepreneurs, they're trying to build their own clouds or Superclouds as I use the term, is that really the target for the developer audience? We've talked a lot about OpenShift with their other platforms, who says as a partner- >> We just announced another extension with Rancher and- >> Yeah. I saw that. And you have to have optionality for developers. Is that the way we should think about the target audience from a developer standpoint? >> I think it will be as we go forward. And so what Fidelma presented on stage was the new developer platform, because we have come to realize, we have to engage with the developers. They're the ones building the apps. They're the ones that are delivering the solutions for the most part. So yeah, I think at the enterprise space, we have a really strong capability. I think when you get into the sort of mid-market SMB standpoint, what we're doing is we're going directly to the managed service and cloud service providers and directly to our Disty and VARS to have them build solutions on top of GreenLake, powered by GreenLake, to then deliver to their customers because that's what the customer wants. I think on the developer side of the house, we have to speak their language, we have to provide their capabilities because they're going to start articulating apps that are going to use both the public cloud and our on-prem capabilities with GreenLake. And so that's got to work very well. And so you've heard us talk about API based and all of that sort of scenario. So it's an exciting time for us, again, moving HPE strategy into something very different than where we were before. >> Well, Keith, that speaks to ecosystem. So I don't know if you were at Microsoft, when the sweaty Steve Ballmer was working with the developers, developers. That's about ecosystem, ecosystem, ecosystem. I don't expect we're going to see Antonio replicating that. But that really is the sort of what you just described is the ecosystem developing on top of GreenLake. That's critical. >> Yeah. And this is one of the things I learned. So, being at Microsoft for as long as I was and leading the Azure business from a commercial standpoint, it was all about the partner and I mean, in all fairness, almost every solution that gets delivered has some sort of partner component to it. Might be an ISV app, might be a managed service, might be in a Colo, might be with our hybrid cloud, with our Hyperscalers, but everything has a partner component to it. And so one of the things I learned with Azure is, you have to sell through and with your ecosystem and go to that customer with a joint solution. And that's where it becomes so impactful and so powerful for what our customers are trying to accomplish. >> When we think about the data gravity and the value of data that put massive potential that it has, even Antonio talked about it this morning, being data rich but insights poor for a long time. >> Yeah. >> Every company in today's day and age has to be a data company to be competitive, there's no more option for that. How does GreenLake empower companies? GreenLake and its ecosystem empower companies to really live being data companies so that they can meet their customers where they are. >> I think it's a really great point because like we said, data's the new currency. Data's the new gold that's out there and people have to get their arms around their data estate. So then they can make these business decisions, these business insights and garner that. And Dave, you mentioned earlier, the Edge is bringing a ton of new data in, and my Zenseact example is a good one. But with GreenLake, you now have a platform that can do data and data management and really sort of establish and secure the data for you. There's no data latency, there's no data egress charges. And which is what we typically run into with the public cloud. But we also support a wide range of databases, open source, as well as the commercial ones, the sequels and those types of scenarios. But what really comes to life is when you have to do analytics on that and you're doing AI and machine learning. And this is one of the benefits I think that people don't realize with HPE is, the investments we've made with Cray, for example, we have and you saw on stage today, the largest supercomputer in the world. That depth that we have as a company, that then comes down into AI and analytics for what we can do with high performance compute, data simulations, data modeling, analytics, like that is something that we, as a company, have really deep, deep capabilities on. So it's exciting to see what we can bring to customers all for that spectrum of data. >> I was excited to see Frontier, they actually achieve, we hosted an event, co-produced event with HPE during the pandemic, Exascale day. >> Yeah. >> But we weren't quite at Exascale, we were like right on the cusp. So to see it actually break through was awesome. So HPC is clearly a differentiator for Hewlett Packard Enterprise. And you talk about the egress. What are some of the other differentiators? Why should people choose GreenLake? >> Well, I think the biggest thing is, that it's truly is a edge to cloud platform. And so you talk about Aruba and our capabilities with a network attached and network as a service capabilities, like that's fairly unique. You don't see that with the other companies. You mentioned earlier to me that compute capabilities that we've had as a company and the storage capabilities. But what's interesting now is that we're sort of taking all of that expertise and we're actually starting to deliver these cloud services that you saw on stage, private cloud, AI and machine learning, high performance computing, VDI, SAP. And now we're actually getting into these industry solutions. So we talked last year about electronic medical records, this year, we've talked about 5g. Now, we're talking about customer loyalty applications. So we're really trying to move from these sort of baseline capabilities and yes, containers and VMs and bare metal, all that stuff is important, but what's really important is the services that you run on top of that, 'cause that's the outcomes that our customers are looking at. >> Should we expect you to be accelerating? I mean, look at what you did with Azure. You look at what AWS does in terms of the feature acceleration. Should we expect HPE to replicate? Maybe not to that scale, but in a similar cadence, we're starting to see that. Should we expect that actually to go faster? >> I think you couched it really well because it's not as much about the quantity, but the quality and the uses. And so what we've been trying to do is say, hey, what is our swim lane? What is our sweet spot? Where do we have a superpower? And where are the areas that we have that superpower and how can we bring those solutions to our customers? 'Cause I think, sometimes, you get over your skis a bit, trying to do too much, or people get caught up in the big numbers, versus the, hey, what's the real meat behind it. What's the tangible outcome that we can deliver to customers? And we see just a massive TAM. I want to say my last analysis was around $42 billion in the next three years, TAM and the Azure service on-prem space. And so we think that there's nothing but upside with the core set of workloads, the core set of solutions and the cloud services that we bring. So yeah, we'll continue to innovate, absolutely, amen, but we're not in a, hey we got to get to 250 this and 300 that, we want to keep it as focused as we can. >> Well, the vast majority of the revenue in the public cloud is still compute. I mean, not withstanding, Microsoft obviously does a lot in SaaS, but I'm talking about the infrastructure and service. Still, well, I would say over 50%. And so there's a lot of the services that don't make any revenue and there's that long tail, if I hear your strategy, you're not necessarily going after that. You're focusing on the quality of those high value services and let the ecosystem sort of bring in the rest. >> This is where I think the, I mean, I love that you guys are asking me about the ecosystem because this is where their sweet spot is. They're the experts on hyper-converged or databases, a service or VDI, or even with SAP, like they're the experts on that piece of it. So we're enabling that together to our customers. And so I don't want to give you the impression that we're not going to innovate. Amen. We absolutely are, but we want to keep it within that, that again, our swim lane, where we can really add true value based on our expertise and our capabilities so that we can confidently go to customers and say, hey, this is a solution that's going to deliver this business value or this capability for you. >> The partners might be more comfortable with that than, we only have one eye sleep with one eye open in the public cloud, like, okay, what are they going to, which value of mine are they grab next? >> You're spot on. And again, this is where I think, the power of what an Edge to cloud platform like HPE GreenLake can do for our customers, because it is that sort of, I mentioned it, one plus one equals three kind of scenario for our customers so. >> So we can leave your customers, last question, Keith. I know we're only on day one of the main summit, the partner growth summit was yesterday. What's the feedback been from the customers and the ecosystem in terms of validating the direction that HPE is going? >> Well, I think the fantastic thing has been to hear from our customers. So I mentioned in my keynote recently, we had Liberty Mutual and we had Texas Children's Hospital, and they're implementing HPE GreenLake in a variety of different ways, from a private cloud standpoint to a data center consolidation. They're seeing sustainability goals happen on top of that. They're seeing us take on management for them so they can take their limited resources and go focus them on innovation and value added scenarios. So the flexibility and cost that we're providing, and it's just fantastic to hear this come to life in a real customer scenario because what Texas Children is trying to do is improve patient care for women and children like who can argue with that. >> Nobody. >> So, yeah. It's great. >> Awesome. Keith, thank you so much for joining Dave and me on the program, talking about all of the momentum with HPE Greenlake. >> Always. >> You can't walk in here without feeling the momentum. We appreciate your insights and your time. >> Always. Thank you you for the time. Yeah. Great to see you as well. >> Likewise. >> Thanks. >> For Keith White and Dave Vellante, I'm Lisa Martin. You're watching theCube live, day one coverage from the show floor at HPE Discover '22. We'll be right back with our next guest. (gentle music)

(upbeat music) >> Welcome to AnsibleFest, 2021, the virtual version. This is The Cube and my name is Dave Volante. We're going to dig into automation and its continuing evolution. Tom Anderson is here. He's the vice president of Red Hat Ansible, the automation platform. And Richard Henshall is also here, Senior Manager of Ansible Product Management, of course, at Red Hat. Guys, welcome to the cube. Good to see you. >> Thanks for having us. >> Thank you for having us Dave. You're welcome, so Rich with this latest release of the Ansible Automation Platform, AAP, we'll get the acronyms out of the way. The focus seems to be an expanding the reach of automation and its potential use cases. I mean, I'll say automation everywhere, not to be confused with the RPA vendor, but the point is, you're trying to make it easier to automate things like provisioning, configuration management, application deployment, throw in orchestration and all these other IT processes. Now, you've talked about this theme in previous releases of AAP. So what's new in this release? What can customers do now that they couldn't do before? >> Yeah, it's a good question thank you. So, we look at this in two dimensions. So, the first dimension we have is like where automation can happen, right? So, you know, we always have traditional data center, clouds being been very prevalent for us for the last, you know, sort of five, 10 years in most people's view. But now we have the Edge, right? So now we have Edge computing, which is sometimes a lot more of the same, but also it comes with a different dynamic of how it has to be sort of used and utilized by different use cases, different industry segments. But then, while you expand the use cases to make sure that people can do automation where they need to do it and make sure if we don't close to the Edge or close to the data center, based on where the technology needs to be run, you also have to think about who's now using automation. So, the second dimension is making sure that different users can take access. You mentioned like application deployment, or infrastructure, or network configuration. We expand the number of different users we have that are starting to take advantage of Ansible. So how do we get more developers? How do we get into the developer workflow, into the development workflow, for how Ansible is created, as well as how we help with the operational, the posts deployment stage that people do operating automation, as well as then the running of Ansible Automation Platform itself. >> Excellent, okay. So, in thinking about some of those various roles or personas, I mean, I think about product leads. I would see developers, obviously you're going to be in there. Managers I would think want that view. You know the thrust seems to be, you're trying to continue to enhance the experience, for these personas and others, I suppose, with new tooling. Maybe you could add some color to that and what's happening in the market Tom if you take this and Rich chime in, what's happening in the market that makes this so important? Who are the key roles and personas that you're targeting? >> Yeah. So, there's a couple of things happening here. I mean, traditionally the people that had been using Ansible to automate their subsystems were the domain expert for that subsystem, right? I'm the storage operations team. I'm the network operations team. I'm using this tool to automate the tasks that I do day to day to operate my piece of the sub system. Now, what they're being asked to do is to expose that subsystem to other constituencies in the organization, right? So they had not, they're not waiting for a call to come in to say, can I have a network segment? Can I have this storage allocated to me? Can I deploy these servers so I can start testing or building or deploying my application. Those subsystems need to be exposed to those different audiences. And so the type of automation that is required is different. Now, we need to expose those subsystems in a way that makes those domain owners comfortable. So they're okay with another audience having access to their subsystem. But at the same time, they're able to ensure the governance and compliance around that, and then give that third-party that developer, that QE person, that man, that business, that line of business manager, whoever it might be, that's accessing that resource, a interface that is friendly and easy enough for them to do. It's kind of the democratization. I know it's a cliche, but the democratization of automated automation within organizations, giving them roles, specific experiences, of how they can access these different subsystems and speed their access to these systems and deploy applications. >> So if we could stay on that for a second, cause that's a complicated situation. You're now opening this up. You Richard mentioned the Edge. So you got to make sure that the person that's getting access has access, but then you also have to make sure that that individual can't screw it up, do things that you don't want that individual to do. And it's probably a whole other set of compliance issues and policy things that you have to bake in. Is that, am I getting that right? >> Yeah. And then that's the aspect of it. When you start to think, you know, Tom listed off there, you know, 10, you can just keep adding different sort of personas that individuals that work in roles, identify with as themselves. I'm a network person, I'm a storage person. To us they're all just Ansible users, right? There may be using a slightly different way, maybe using it slightly different places, but they're just an Ansible user, right? And so as you have, like those people that just like become organically, you've now got thousands potentially of Ansible users inside a large enterprise organization, or if you know, a couple of hundred if your smaller. But you're then go, well, what do I do with Ansible, right? And so at that point, you then start to say, now we try to look at it as what's their use of Ansible itself, because it's not just a command line tool. It's got a management interface, it's got analytics, we've got content management, we've got operational runtime, we've got responsiveness to, you know, disaster recovery scenarios for when, you know, when you need to be able to do certain actions, you may use it in different ways at different places. So we start, try and break out, what is the person doing with Ansible Automation Platform at this part of their workflow? Are they creating content, right? Are they consuming content, or are they operating that automation content for those other constituent users that Tom referred to. >> Yeah, that's really helpful because there's context, there are different roles, different personas need different contexts, you know, trying to do different things. Sometimes somebody just wants to see the analytics to make sure it's, you know, hey, everything's green, Oh, we got a yellow, versus, hey actually want to make some changes and I'm authorized to do so. Let's shift gears a little bit and talk about containers. I want to understand how containers are driving change for customers. Maybe what new tools you're providing to support this space? What about the Edge? Yeah, how real is that in terms of tangible pockets or patterns that you can identify that require new types of capabilities that you're delivering? Maybe you can help us unpack that a little bit. >> Okay so, I think there's two ways to look at containers, right? So the first is how are we utilizing the container technology itself, right? So containers are a package, right? So the amount of work we've been doing as Ansible's become more successful in the last couple of years, separating content out with Ansible collections. The ability to bring back manage, control a containerized runtime of Ansible so that you can lifecycle it, you can deploy it, it becomes portable. Edge is important there. How do I make sure I have the same automation running in the data center as the same automation running out on the Edge, if I'm looking at something that needs to be identical. The portability that the packaging of the container gives us, is a fantastic advantage, given you need to bring together just that automation you want. Smaller footprint, more refined footprint, lifecycle manage footprint. But at the same time, containers are also a very useful way of scaling the operation, right? And so as red hat puts things like Open Shift out in all these different locations, how can we leverage those platforms, to push the runtime of Ansible, the execution component, the execution plane of Ansible. How into anywhere that's hospitable for it to run? And as you move out towards Edge, as you move further away from the data center, you need a more ubiquitous sort of like run-time plane that you can put these things on. So they can just spin up when as, and when you need to. Potentially even at the end, actually being on the device, because at the same time with Edge, you also have different limits around how Edge works. It's not just about, hey I'm wifi points in an NFL stadium, actually, you're talking about I'm at the end of a 2000 mile, you know, piece of cable on an oil pipeline or potentially I'm a refinery out in the Gulf of Mexico. You know, you've got a very different dynamic to how you interact with that end point, than you do when it's a nice big controlled network, you know, powered location, which is well-governed and well-orchestrated. >> That's good. Thank you Rich. So Tom, think about automation, you know, back in the day, seems like a long time ago, but it really wasn't, automation used to scare some IT folks, because you know, sometimes it created unintended consequences or maybe it was a cultural thing and that you didn't want to automate themselves out of a job, but regardless. The cloud has changed that mindset, you know, showing us what's possible. You guys obviously had a big role in that, and the pandemic and digital initiatives, they really have made I call it the automation mandate. It was like the fourth March to digital, at least that's how I see it. I wonder if you could talk about, how you see your users approaching automation in as it relates to their business goals. Do you think automation is still being treated sometimes with trepidation or as a side project for some organizations or is it really continuing to evolve as a mainstream business imperative? >> Yes, so Dave we see it continuing to evolve as a strategic imperative for our customers. I mean, you'll, hear some of the keynote folks that are speaking here today. I've done an interview or doing an interview with Joe Mills from Discover, talking about extreme automation throughout Discovers organization. You'll hear representatives from JPMC talk about 22,000 JPMC employees contributing automation content in their environment, across 20 or 22 countries. I mean, just think about that scale, and the number of people that are involved in automation now and their tasks. So I think it's, I think we are, we have moved beyond or are moving beyond that idea that automation is just there to replace people's jobs. And it's much more about automation replacing the mundane, increasing consistency, increasing security, increasing agility, and giving people an opportunity to do more and more interesting stuff. So that's what we hear from our customers, this idea of them building. And it's not just the technology piece, but it's the cultural piece inside organizations where they're building these guilds or communities of practice, bringing people together to share best practices and experience with automation, so that they can feel comfortable learning from others and sharing with others and driving the organization forward. So we see a lot of that, and you'll hear a lot of that, at some of the Ansible Fest sessions this week. >> Well, I mean though I think that's a really important point. The last point you made about the skills, because I think you're right. I think we have moved beyond it's just job replacement. I don't know anybody who loves provisioning LUNs and say, oh, I'm the best in the world at that. It's just kind of something that was maybe important 10, 15, 20 years ago, but today, he should let the machines do that. So that's the whole skills transformation, is obviously a big part of digital transformation. Isn't it? >> It absolutely is. And frankly, we still hear, it's an impediment, that skills shortages are still an impediment to our customer success. They are still skilling up. I mean, honestly, that's one of the differentiators, for Ansible, as a language, a human readable language, that is easy to learn, easy to use, easy to share across an organization. So that's why you see job boards, and whatnot with so many opportunities that require or, or ask for Ansible skills out there. It's just a, it's become sort of a ubiquitous automation language in organizations, because it can be shared across lots of different roles. You don't have to be a Ruby software developer or a Python software developer to create automation with Ansible. You can be Tom Anderson or Rich Henshall. You don't have to, you don't have to be the, you know, the, the sharpest software developer in the world to take advantage of it. So anyway, that's one of the things that kind of overcoming some of the skills apprehension and bringing people into this, into the kind of new environment, of thinking about automation as code, not software code, but thinking of it like code. >> Got it. Guys we've got to leave it there, but Rich, how about you bring us home. We'll give you the last word. >> I mean, I think, you know what Tom just said there I think, about the skills side of things, is I think that the part that made it resonates the most. I mean I was a customer before I joined Red Hat, and trying to get large numbers of people, onto a same path, to try and achieve that outbound objective, that an organization has. The objective of an organization is not to automate, it's to achieve what is needed by what the automation facilitates. So how do we get those different groups to go from, Hey, this is about me, to this is actually about what we're trying to achieve as a business what we're trying to facilitate as a business, and how do we get those people easier access, a reduced barrier of entry to the skills they need to help make that successful, that compliments what they do, in their primary role, with a really strong secondary skill set that helps them do all the bits and pieces they need to do to make that job work. >> That's great, I mean you guys have done a great job, I mean it wasn't clear, you know, decade ago, or maybe half a decade ago, who was going to win this battle. Ansible clearly has market momentum and has become the leader. So guys congratulations on that and good job. Keep it going. I really appreciate your time. >> Thank you. >> Thank you. Thanks. >> Okay. This is the cubes, continuous coverage of Ansible Fest, 2021. Keep it right there for more content that educates and inspires. Thanks for watching. (upbeat music)

>> Narrator: From around the globe it's theCUBE, covering HPE Discover Virtual Experience brought to you by HPE. >> Hi everybody. Welcome back. This is Dave Vellante for theCUBE, and this is our coverage of discover 2020, the virtual experience of HPE discover. We've done many, many discoveries, as usually we're on the show floor, theCUBE has been virtualized and we talk a lot at HPE discovers, a lot of storage and server and infrastructure and networking which is great. But the conversation we're going to have now is really, we're going to be talking about helping the world solve some big problems. And I'm very excited to welcome back to theCUBE Dr. Eng Lim Goh. He's a senior vice president of and CTO for AI, at HPE. Hello, Dr. Goh. Great to see you again. >> Hello. Thank you for having us, Dave. >> You're welcome. And then our next guest is Professor Joachim Schultze, who is the Professor for Genomics, and Immunoregulation at the university of Bonn amongst other things Professor, welcome. >> Thank you all. Welcome. >> And then Prasad Shastry, is the Chief Technologist for the India Advanced Development Center at HPE. Welcome, Prasad. Great to see you. >> Thank you. Thanks for having me. >> So guys, we have a CUBE first. I don't believe we've ever had of three guests in three separate times zones. I'm in a fourth time zone. (guests chuckling) So I'm in Boston. Dr. Goh, you're in Singapore, Professor Schultze, you're in Germany and Prasad, you're in India. So, we've got four different time zones. Plus our studio in Palo Alto. Who's running this program. So we've got actually got five times zones, a CUBE first. >> Amazing. >> Very good. (Prasad chuckles) >> Such as the world we live in. So we're going to talk about some of the big problems. I mean, here's the thing we're obviously in the middle of this pandemic, we're thinking about the post isolation economy, et cetera. People compare obviously no surprise to the Spanish flu early part of last century. They talk about the great depression, but the big difference this time is technology. Technology has completely changed the way in which we've approached this pandemic. And we're going to talk about that. Dr. Goh, I want to start with you. You've done a lot of work on this topic of swarm learning. If we could, (mumbles) my limited knowledge of this is we're kind of borrowing from nature. You think about, bees looking for a hive as sort of independent agents, but somehow they come together and communicate, but tell us what do we need to know about swarm learning and how it relates to artificial intelligence and we'll get into it. >> Oh, Dave, that's a great analogy using swarm of bees. That's exactly what we do at HPE. So let's use the of here. When deploying artificial intelligence, a hospital does machine learning of the outpatient data that could be biased, due to demographics and the types of cases they see more also. Sharing patient data across different hospitals to remove this bias is limited, given privacy or even sovereignty the restrictions, right? Like for example, across countries in the EU. HPE, so I'm learning fixers this by allowing each hospital, let's still continue learning locally, but at each cycle we collect the lumped weights of the neural networks, average them and sending it back down to older hospitals. And after a few cycles of doing this, all the hospitals would have learned from each other, removing biases without having to share any private patient data. That's the key. So, the ability to allow you to learn from everybody without having to share your private patients. That's swarm learning, >> And part of the key to that privacy is blockchain, correct? I mean, you you've been too involved in blockchain and invented some things in blockchain and that's part of the privacy angle, is it not? >> Yes, yes, absolutely. There are different ways of doing this kind of distributed learning, which swarm learning is over many of the other distributed learning methods. Require you to have some central control. Right? So, Prasad, and the team and us came up together. We have a method where you would, instead of central control, use blockchain to do this coordination. So, there is no more a central control or coordinator, especially important if you want to have a truly distributed swamp type learning system. >> Yeah, no need for so-called trusted third party or adjudicator. Okay. Professor Schultze, let's go to you. You're essentially the use case of this swarm learning application. Tell us a little bit more about what you do and how you're applying this concept. >> I'm actually by training a physician, although I haven't seen patients for a very long time. I'm interested in bringing new technologies to what we call precision medicine. So, new technologies both from the laboratories, but also from computational sciences, married them. And then I basically allow precision medicine, which is a medicine that is built on new measurements, many measurements of molecular phenotypes, how we call them. So, basically that process on different levels, for example, the genome or genes that are transcribed from the genome. We have thousands of such data and we have to make sense out of this. This can only be done by computation. And as we discussed already one of the hope for the future is that the new wave of developments in artificial intelligence and machine learning. We can make more sense out of this huge data that we generate right now in medicine. And that's what we're interesting in to find out how can we leverage these new technologies to build a new diagnostics, new therapy outcome predictors. So, to know the patient benefits from a disease, from a diagnostics or a therapy or not, and that's what we are doing for the last 10 years. The most exciting thing I have been  through in the last three, four, five years is really when HPE introduced us to swarm learning. >> Okay and Prasad, you've been helping Professor Schultze, actually implements swarm learning for specific use cases that we're going to talk about COVID, but maybe describe a little bit about what you've been or your participation in this whole equation. >> Yep, thank. As Dr Eng Lim Goh, mentioned. So, we have used blockchain as a backbone to implement the decentralized network. And through that we're enabling a privacy preserved these centralized network without having any control points, as Professor explained in terms of depression medicines. So, one of the use case we are looking at he's looking at the blood transcriptomes, think of it, different hospitals having a different set of transcriptome data, which they cannot share due to the privacy regulations. And now each of those hospitals, will clean the model depending upon their local data, which is available in that hospital. And shared the learnings coming out of that training with the other hospitals. And we played to over several cycles to merge all these learnings and then finally get into a global model. So, through that we are able to kind of get into a model which provides the performance is equal of collecting all the data into a central repository and trying to do it. And we could really think of when we are doing it, them, could be multiple kinds of challenges. So, it's good to do decentralized learning. But what about if you have a non ID type of data, what about if there is a dropout in the network connections? What about if there are some of the compute nodes we just practice or probably they're not seeing sufficient amount of data. So, that's something we tried to build into the swarm learning framework. You'll handle the scenarios of having non ID data. All in a simple word we could call it as seeing having the biases. An example, one of the hospital might see EPR trying to, look at, in terms of let's say the tumors, how many number of cases and whereas the other hospital might have very less number of cases. So, if you have kind of implemented some techniques in terms of doing the merging or providing the way that different kind of weights or the tuneable parameters to overcome these set of challenges in the swarm learning. >> And Professor Schultze, you you've applied this to really try to better understand and attack the COVID pandemic, can you describe in more detail your goals there and what you've actually done and accomplished? >> Yeah. So, we have actually really done it for COVID. The reason why we really were trying to do this already now is that we have to generate it to these transcriptomes from COVID-19 patients ourselves. And we realized that the scene of the disease is so strong and so unique compared to other infectious diseases, which we looked at in some detail that we felt that the blood transcriptome would be good starting point actually to identify patients. But maybe even more important to identify those with severe diseases. So, if you can identify them early enough that'd be basically could care for those more and find particular for those treatments and therapies. And the reason why we could do that is because we also had some other test cases done before. So, we used the time wisely with large data sets that we had collected beforehand. So, use cases learned how to apply swarm learning, and we are now basically ready to test directly with COVID-19. So, this is really a step wise process, although it was extremely fast, it was still a step wise probably we're guided by data where we had much more knowledge of which was with the black leukemia. So, we had worked on that for years. We had collected many data. So, we could really simulate a Swarm learning very nicely. And based on all the experience we get and gain together with Prasad, and his team, we could quickly then also apply that knowledge to the data that are coming now from COVID-19 patients. >> So, Dr. Goh, it really comes back to how we apply machine intelligence to the data, and this is such an interesting use case. I mean, the United States, we have 50 different States with 50 different policies, different counties. We certainly have differences around the world in terms of how people are approaching this pandemic. And so the data is very rich and varied. Let's talk about that dynamic. >> Yeah. If you, for the listeners who are or viewers who are new to this, right? The workflow could be a patient comes in, you take the blood, and you send it through an analysis? DNA is made up of genes and our genes express, right? They express in two steps the first they transcribe, then they translate. But what we are analyzing is the middle step, the transcription stage. And tens of thousands of these Transcripts that are produced after the analysis of the blood. The thing is, can we find in the tens of thousands of items, right? Or biomarkers a signature that tells us, this is COVID-19 and how serious it is for this patient, right? Now, the data is enormous, right? For every patient. And then you have a collection of patients in each hospitals that have a certain demographic. And then you have also a number of hospitals around. The point is how'd you get to share all that data in order to have good training of your machine? The ACO is of course a know privacy of data, right? And as such, how do you then share that information if privacy restricts you from sharing the data? So in this case, swarm learning only shares the learnings, not the private patient data. So we hope this approach would allow all the different hospitals to come together and unite sharing the learnings removing biases so that we have high accuracy in our prediction as well at the same time, maintaining privacy. >> It's really well explained. And I would like to add at least for the European union, that this is extremely important because the lawmakers have clearly stated, and the governments that even non of these crisis conditions, they will not minimize the rules of privacy laws, their compliance to privacy laws has to stay as high as outside of the pandemic. And I think there's good reasons for that, because if you lower the bond, now, why shouldn't you lower the bar in other times as well? And I think that was a wise decision, yes. If you would see in the medical field, how difficult it is to discuss, how do we share the data fast enough? I think swarm learning is really an amazing solution to that. Yeah, because this discussion is gone basically. Now we can discuss about how we do learning together. I'd rather than discussing what would be a lengthy procedure to go towards sharing. Which is very difficult under the current privacy laws. So, I think that's why I was so excited when I learned about it, the first place with faster, we can do things that otherwise are either not possible or would take forever. And for a crisis that's key. That's absolutely key. >> And is the byproduct. It's also the fact that all the data stay where they are at the different hospitals with no movement. >> Yeah. Yeah. >> Learn locally but only shared the learnings. >> Right. Very important in the EU of course, even in the United States, People are debating. What about contact tracing and using technology and cell phones, and smartphones to do that. Beside, I don't know what the situation is like in India, but nonetheless, that Dr. Goh's point about just sharing the learnings, bubbling it up, trickling just kind of metadata. If you will, back down, protects us. But at the same time, it allows us to iterate and improve the models. And so, that's a key part of this, the starting point and the conclusions that we draw from the models they're going to, and we've seen this with the pandemic, it changes daily, certainly weekly, but even daily. We continuously improve the conclusions and the models don't we. >> Absolutely, as Dr. Goh explained well. So, we could look at like they have the clinics or the testing centers, which are done in the remote places or wherever. So, we could collect those data at the time. And then if we could run it to the transcripting kind of a sequencing. And then as in, when we learn to these new samples and the new pieces all of them put kind of, how is that in the local data participate in the kind of use swarm learning, not just within the state or in a country could participate into an swarm learning globally to share all this data, which is coming up in a new way, and then also implement some kind of continuous learning to pick up the new signals or the new insight. It comes a bit new set of data and also help to immediately deploy it back into the inference or into the practice of identification. To do these, I think one of the key things which we have realized is to making it very simple. It's making it simple, to convert the machine learning models into the swarm learning, because we know that our subject matter experts who are going to develop these models on their choice of platforms and also making it simple to integrate into that complete machine learning workflow from the time of collecting a data pre processing and then doing the model training and then putting it onto inferencing and looking performance. So, we have kept that in the mind from the beginning while developing it. So, we kind of developed it as a plug able microservices kind of packed data with containers. So the whole library could be given it as a container with a kind of a decentralized management command controls, which would help to manage the whole swarm network and to start and initiate and children enrollment of new hospitals or the new nodes into the swarm network. At the same time, we also looked into the task of the data scientists and then try to make it very, very easy for them to take their existing models and convert that into the swarm learning frameworks so that they can convert or enabled they're models to participate in a decentralized learning. So, we have made it to a set callable rest APIs. And I could say that the example, which we are working with the Professor either in the case of leukemia or in the COVID kind of things. The noodle network model. So we're kind of using the 10 layer neural network things. We could convert that into the swarm model with less than 10 lines of code changes. So, that's kind of a simply three we are looking at so that it helps to make it quicker, faster and loaded the benefits. >> So, that's an exciting thing here Dr. Goh is, this is not an R and D project. This is something that you're actually, implementing in a real world, even though it's a narrow example, but there are so many other examples that I'd love to talk about, but please, you had a comment. >> Yes. The key thing here is that in addition to allowing privacy to be kept at each hospital, you also have the issue of different hospitals having day to day skewed differently. Right? For example, a demographics could be that this hospital is seeing a lot more younger patients, and other hospitals seeing a lot more older patients. Right? And then if you are doing machine learning in isolation then your machine might be better at recognizing the condition in the younger population, but not older and vice versa by using this approach of swarm learning, we then have the biases removed so that both hospitals can detect for younger and older population. All right. So, this is an important point, right? The ability to remove biases here. And you can see biases in the different hospitals because of the type of cases they see and the demographics. Now, the other point that's very important to reemphasize is what precise Professor Schultze mentioned, right? It's how we made it very easy to implement this.Right? This started out being so, for example, each hospital has their own neural network and they training their own. All you do is we come in, as Pasad mentioned, change a few lines of code in the original, machine learning model. And now you're part of the collective swarm. This is how we want to easy to implement so that we can get again, as I like to call, hospitals of the world to uniting. >> Yeah. >> Without sharing private patient data. So, let's double click on that Professor. So, tell us about sort of your team, how you're taking advantage of this Dr. Goh, just describe, sort of the simplicity, but what are the skills that you need to take advantage of this? What's your team look like? >> Yeah. So, we actually have a team that's comes from physicians to biologists, from medical experts up to computational scientists. So, we have early on invested in having these interdisciplinary research teams so that we can actually spend the whole spectrum. So, people know about the medicine they know about them the biological basics, but they also know how to implement such new technology. So, they are probably a little bit spearheading that, but this is the way to go in the future. And I see that with many institutions going this way many other groups are going into this direction because finally medicine understands that without computational sciences, without artificial intelligence and machine learning, we will not answer those questions with this large data that we're using. So, I'm here fine. But I also realize that when we entered this project, we had basically our model, we had our machine learning model from the leukemia's, and it really took almost no efforts to get this into the swarm. So, we were really ready to go in very short time, but I also would like to say, and then it goes towards the bias that is existing in medicine between different places. Dr. Goh said this very nicely. It's one aspect is the patient and so on, but also the techniques, how we do clinical essays, we're using different robots a bit. Using different automates to do the analysis. And we actually try to find out what the Swan learning is doing if we actually provide such a bias by prep itself. So, I did the following thing. We know that there's different ways of measuring these transcriptomes. And we actually simulated that two hospitals had an older technology and a third hospital had a much newer technology, which is good for understanding the biology and the diseases. But it is the new technology is prone for not being able anymore to generate data that can be used to learn and then predicting the old technology. So, there was basically, it's deteriorating, if you do take the new one and you'll make a classifier model and you try old data, it doesn't work anymore. So, that's a very hard challenge. We knew it didn't work anymore in the old way. So, we've pushed it into swarm learning and to swarm recognize that, and it didn't take care of it. It didn't care anymore because the results were even better by bringing everything together. I was astonished. I mean, it's absolutely amazing. That's although we knew about this limitations on that one hospital data, this form basically could deal with it. I think there's more to learn about these advantages. Yeah. And I'm very excited. It's not only a transcriptome that people do. I hope we can very soon do it with imaging or the DCNE has 10 sites in Germany connected to 10 university hospitals. There's a lot of imaging data, CT scans and MRIs, Rachel Grimes. And this is the next next domain in medicine that we would like to apply as well as running. Absolutely. >> Well, it's very exciting being able to bring this to the clinical world And make it in sort of an ongoing learnings. I mean, you think about, again, coming back to the pandemic, initially, we thought putting people on ventilators was the right thing to do. We learned, okay. Maybe, maybe not so much the efficacy of vaccines and other therapeutics. It's going to be really interesting to see how those play out. My understanding is that the vaccines coming out of China, or built to for speed, get to market fast, be interested in U.S. Maybe, try to build vaccines that are maybe more longterm effective. Let's see if that actually occurs some of those other biases and tests that we can do. That is a very exciting, continuous use case. Isn't it? >> Yeah, I think so. Go ahead. >> Yes. I, in fact, we have another project ongoing to use a transcriptome data and other data like metabolic and cytokines that data, all these biomarkers from the blood, right? Volunteers during a clinical trial. But the whole idea of looking at all those biomarkers, we talking tens of thousands of them, the same thing again, and then see if we can streamline it clinical trials by looking at it data and training with that data. So again, here you go. Right? We have very good that we have many vaccines on. In candidates out there right now, the next long pole in the tenth is the clinical trial. And we are working on that also by applying the same concept. Yeah. But for clinical trials. >> Right. And then Prasad, it seems to me that this is a good, an example of sort of an edge use case. Right? You've got a lot of distributed data. And I know you've spoken in the past about the edge generally, where data lives bringing moving data back to sort of the centralized model. But of course you don't want to move data if you don't have to real time AI inferencing at the edge. So, what are you thinking in terms of other other edge use cases that were there swarm learning can be applied. >> Yeah, that's a great point. We could kind of look at this both in the medical and also in the other fields, as we talked about Professor just mentioned about this radiographs and then probably, Using this with a medical image data, think of it as a scenario in the future. So, if we could have an edge note sitting next to these medical imaging systems, very close to that. And then as in when this the systems producers, the medical immediate speed could be an X-ray or a CT scan or MRI scan types of thing. The system next to that, sitting on the attached to that. From the modernity is already built with the swarm lending. It can do the inferencing. And also with the new setup data, if it looks some kind of an outlier sees the new or images are probably a new signals. It could use that new data to initiate another round up as form learning with all the involved or the other medical images across the globe. So, all this can happen without really sharing any of the raw data outside of the systems but just getting the inferencing and then trying to make all of these systems to come together and try to build a better model. >> So, the last question. Yeah. >> If I may, we got to wrap, but I mean, I first, I think we've heard about swarm learning, maybe read about it probably 30 years ago and then just ignored it and forgot about it. And now here we are today, blockchain of course, first heard about with Bitcoin and you're seeing all kinds of really interesting examples, but Dr. Goh, start with you. This is really an exciting area, and we're just getting started. Where do you see swarm learning, by let's say the end of the decade, what are the possibilities? >> Yeah. You could see this being applied in many other industries, right? So, we've spoken about life sciences, to the healthcare industry or you can't imagine the scenario of manufacturing where a decade from now you have intelligent robots that can learn from looking at across men building a product and then to replicate it, right? By just looking, listening, learning and imagine now you have multiple of these robots, all sharing their learnings across boundaries, right? Across state boundaries, across country boundaries provided you allow that without having to share what they are seeing. Right? They can share, what they have lunch learnt You see, that's the difference without having to need to share what they see and hear, they can share what they have learned across all the different robots around the world. Right? All in the community that you allow, you mentioned that time, right? That will even in manufacturing, you get intelligent robots learning from each other. >> Professor, I wonder if as a practitioner, if you could sort of lay out your vision for where you see something like this going in the future, >> I'll stay with the medical field at the moment being, although I agree, it will be in many other areas, medicine has two traditions for sure. One is learning from each other. So, that's an old tradition in medicine for thousands of years, but what's interesting and that's even more in the modern times, we have no traditional sharing data. It's just not really inherent to medicine. So, that's the mindset. So yes, learning from each other is fine, but sharing data is not so fine, but swarm learning deals with that, we can still learn from each other. We can, help each other by learning and this time by machine learning. We don't have to actually dealing with the data sharing anymore because that's that's us. So for me, it's a really perfect situation. Medicine could benefit dramatically from that because it goes along the traditions and that's very often very important to get adopted. And on top of that, what also is not seen very well in medicine is that there's a hierarchy in the sense of serious certain institutions rule others and swarm learning is exactly helping us there because it democratizes, onboarding everybody. And even if you're not sort of a small entity or a small institutional or small hospital, you could become remembering the swarm and you will become as a member important. And there is no no central institution that actually rules everything. But this democratization, I really laugh, I have to say, >> Pasad, we'll give you the final word. I mean, your job is very helping to apply these technologies to solve problems. what's your vision or for this. >> Yeah. I think Professor mentioned about one of the very key points to use saying that democratization of BI I'd like to just expand a little bit. So, it has a very profound application. So, Dr. Goh, mentioned about, the manufacturing. So, if you look at any field, it could be health science, manufacturing, autonomous vehicles and those to the democratization, and also using that a blockchain, we are kind of building a framework also to incentivize the people who own certain set of data and then bring the insight from the data into the table for doing and swarm learning. So, we could build some kind of alternative monetization framework or an incentivization framework on top of the existing fund learning stuff, which we are working on to enable the participants to bring their data or insight and then get rewarded accordingly kind of a thing. So, if you look at eventually, we could completely make dais a democratized AI, with having the complete monitorization incentivization system which is built into that. You may call the parties to seamlessly work together. >> So, I think this is just a fabulous example of we hear a lot in the media about, the tech backlash breaking up big tech but how tech has disrupted our lives. But this is a great example of tech for good and responsible tech for good. And if you think about this pandemic, if there's one thing that it's taught us is that disruptions outside of technology, pandemics or natural disasters or climate change, et cetera, are probably going to be the bigger disruptions then technology yet technology is going to help us solve those problems and address those disruptions. Gentlemen, I really appreciate you coming on theCUBE and sharing this great example and wish you best of luck in your endeavors. >> Thank you. >> Thank you. >> Thank you for having me. >> And thank you everybody for watching. This is theCUBE's coverage of HPE discover 2020, the virtual experience. We'll be right back right after this short break. (upbeat music)

>> (Narrator) Live from Madrid, Spain it's theCUBE. Covering HP Discover Madrid 2017. Brought to you by Hewlett Packard Enterprise. >> We're back in Espana. theCUBE, the leader in live tech coverage is here covering HPE Discover Madrid, day one. I'm Dave Villante with my cohost, Peter Burris. Well, it's all coming into focus, Peter. >> It is, it actually is. >> It is, I mean, it better be after five or six years. It's taking longer than I had hoped. But, the story is consistent now. The last four Discovers, despite some of the distractions of spin merges and so forth the story of hybrid IT, the Intelligent Edge, bringing automation is somewhat new to the data center. Services lead starts to actually make sense. >> Peter: Through private cloud. >> Yep, and you know, we talked about at the top of the show today, the spectrum. We're running AWS re:Invent, we got a big presence there. Obviously its affected the entire industry, and then you've got HPE, the likes of HPE, Dell EMC, to a certain extent IMB basically not given up, say wait a minute, these are our customers, they want Cloud on prem, we're gonna deliver to them. They want Cloud in the Cloud, we'll help them get there. >> Peter: Oracle. >> Oracle as well. Oracle, different strategy. We should talk about that a little bit. But, summarize, you know synthesize your take on the day, and where we're at with HPE. >> So I would say that the... What we talked about this morning was, when Meg first took over the reins, she stopped a whole bunch of stuff, and HP stopped spending and behaving like a company that believed that it had to get scale as fast as possible because that was the only way to win. And she ended up going back to, look, lets focus on the customers and what the customers are trying to do, and not how we're trying to leverage our assets. And it kind of took a pause, and for a while you could kind of see them start putting things back together, and you kind of had a sense of where it was all gonna go. But this has been kind of the coming out party for what the last five years have been about. As you said, I think we've seen the three core messages that certainly line up, you know, with a little bit of cavat here. Their story is very much aligned with what we think the industry needs to see right now. At least, our research suggests. Gonna need true private Cloud, the ability to put the Cloud service where your data requires, and not force your business to move it's data to some Clouds location. You're gonna need increased automation within your IT organization, because you're not going to be able to support these more complex workloads if you don't find ways to increase the productivity of your people, and even more importantly, dramatically reduce even the possibility of a failure, and that's what AI inside IT's all about. And very importantly, the idea that you gotta put more intelligence at the Edge, that that interface between the real world and the digital world is really what's gonna drive the dynamic in the computing industry over the next few years. And HP has shown up and they're not just talking about it, they're showing it. And it's nice to be there. >> Well it's interesting, Meg Whitman came by and was talking to us, and we were talking about the Aruba acquisition. She said, look, we bought this because it was a nice business, it could show some growth. And it was, you know, a way to compete with Cisco and differentiate, because, hey were trying to compete head to head with Cisco and it was going okay, but not great. Aruba gave them a clear differentiator. And then all of the sudden, the Edge became this tailwind. And it kinda got them there early. >> Well, lets remember what Mark Hurd talked about. He said, well, why are you going after the network world. I like their 67% gross margins. Okay, so... >> Dave: Talking about 3Com. >> He's talking about 3Com, he's talking about all the things that HP did as it tried to get into the networking business. >> Dave: Cisco, right, yeah. >> It was purely driven by gross margin. They didn't quite have the customer story down. Aruba has always been a great customer story. They've always say, look, this is your business challenge. You know, are you sick and tired of dropping your connection as you go from one conference room to another. This is your security issues. On, and on, and on. They had three or four concrete value propositions that just worked for customers. That acquisition at that time it happened, it happened about the same time that HP was starting to rededicate itself back to thinking about it's customer base. So, it's not surprising to me that that integration, or that merger has been one of the more successful that HP's undertaken. >> So again, the spectrum. You know, you got Andy Jassy on one end who started this whole thing, and you got the likes of HPE on the other end. And you're right, it does align with a lot of things that we've been saying around true private cloud and so forth. Jassy doesn't buy it. He flat out says, this is old guard thinking trying to hang on to the past. But, our analysis suggests it's not just old guard thinking. It's customer thinking because they can't just move their business into the Cloud. Thoughts. >> Totally agree. So I'd say there are a couple of things about it. It's customer thinking based on the realities of the data assets that they're trying to leverage as they transform into a digital business. Data is real, and it has, it's gonna weigh in on how your infrastructure looks. And the Edge is gonna have characteristics that mean you're gonna have to do automation right there, right where the action is. You're not gonna be able to send it up to the Cloud all the time. There's gonna be a lot of business events that take place in that core, in that second tier. So, it's not that it's... It's not that it's old versus new guard. And here's why I say that, Dave. It's because in many respects, we're giving some props to HP right now, which is great. But, in many respects, the story that HP is telling today is a story that is still being largely, has largely been told, largely fashioned by what AWS has done over the last 10 years. And that is, here's what the Cloud experience is. And now HP's adding, "And you want that Cloud experience whatever your data demands." The difference, therefore, between the old guard and and the new guard, or the old way and the new way, on premise, is that it used to be, it was pretty clear to me, and I think it was pretty clear to us, that the old, that the talk about private Cloud was simply a way of thinking about how to put new marketing spin on the enhancement, upgrade, replacement cycle for servers and storage. And that did not work. It just flat out didn't work. >> Well it worked in the sense that it froze the market a little bit. >> Eh, it froze the market a little bit. But, overall, for the past five or six years our growth has been slowing down pretty dramatically. So, I would say, that the data is pretty unassailable. You're not gonna move everything to a central location. But, you're gonna want that Cloud experience. And so, the question is, are we gonna see great Cloud experience where the physics, the legality, and inertia property governance demands that you put your data. >> Well, I thought Jesse St Laurent was gonna talk about the next wave. He mentioned Multi-Cloud. >> Peter: He's CTO of... >> Of SimpliVity, now HPE Hyperconverged. >> Peter: Right. >> I thought he was talking about, he said the next wave is Hyper-V. Okay, check. I mean, like, that's like to me a feature of the product. And then he sort of talked about Multi-Cloud. And that really where I thought he was gonna go, because when you look at what AWS is doing, and I've always contended, they're years ahead, we can debate how many. Five, seven, three. Probably closer to five than three. But where they're headed is serverless, you know, functional programming. Stateless, new programming models. It's all about the developer to those guys. And that's the parlance that they speak in. The Hyperconverge guys all talk in VM terms. And that's not how Amazon talks or thinks. So, you know, the question is, is that a next wave, and can the Enterprise guys >> Peter: Talk developer? >> Yeah, can they catch that wave? >> So, I think... Look, lets be honest. AWS is a great company. There's no question about it. They've done things that a lot of old style infrastructure jocks thought couldn't be done. And they did it. And they continue to, they continue to demonstrate that they are really engaging their customers and turning that insight and knowledge into great services. So, this is not, this is not a knock on AWS. But what ultimately has to, and I think AWS is recognizing this as well, because they're starting to talk a lot about IoT and their approach to IoT, recognizing that not all the data is gonna be sourced up in the Cloud. The data is gonna be generated in a lot of other places and they have to participate there as well. So, from our perspective ultimately, we would say that Multi-Cloud, the ability to, the ability to naturally place your data where the data needs to be placed, which is increasingly is gonna be closer to the event that needs to be automated, that needs to have that high quality experience, is gonna be the way, is gonna be the dominant factor in determining the characteristics of the application infrastructure that you put in place. And, we'll see what happens. Serverless, yeah, serverless is great. You can do a lot with it. But, you can also still build junky applications with serverless. Microservices are great, yeah. But you can still build junky applications with Microservices. >> A lot of those services aren't so micro as Neil Raden would say. >> That's exactly right. So you can still do bad stuff in the Cloud. So, at the end of the day, the whole point is to get a new compact between business who have the vision of the digital services and digital capabilities they want, IT professionals and developers who are gonna generate, create that value, and then infrastructure people who are not who are allowing the data and the workload to fall where is naturally should fall, and then making it possible for the industry to work together, because that's what users want. >> Okay, so let me ask the question differently. You agree that the Cloud guys generally, Amazon specifically, is ahead of the Enterprise guys when it comes to infrastructures and servers. >> Peter: Yeah, there's no question there. >> Okay, is the lead extending, or is it dwindling. Amazon's lead in your view. >> Well, so look, you have Amazon's lead, first of you have to think about Amazon's lead relative to Microsoft, Oracle, and others. And, they're not as far ahead as, they're not that far ahead of Microsoft. >> Dave: Right. >> So there's a real battle raging there. Google has at least as good a relationship with a lot of developers as Amazon does. When you think about what a lot of developers are building in the Cloud experience, they're using Kubernetes, they're using TensorFlow, they're increasingly going to use Istio. I mean, so, it's not, There's gonna be increased energy being put forward to try to talk about how that Cloud innovation's gonna happen. >> So those are the three Hypercloud guys. >> Those are three Hypercloud guys. And, as we talked about, they are increasingly defining what the Cloud experience is. I think what we're seeing now, is the Enterprise guys stepping back and saying, you know what, we have to define our roll in the Cloud experience, and not presume that we're gonna tell everybody what the Cloud experience is. Which is what they were doing for many years, and they failed at it. >> And you could make an argument that HPE as a smaller company with less assets to encumber them, can actually deliver that through partnerships, maybe not as profitably, most definitely not as profitably, but actually can deliver that outcome for customers as a more agile customer. >> We'll see, we'll see, because... >> Dave: You could make that argument is all I'm saying. >> Well, you could make that argument, but remember, we're moving from, and even HP announced some stuff today with Greenlake, moving from a product orientation increasingly to a service orientation. And there's demonstration that you can do things with your business model that may allow you to do things in different levels of profitability at somewhere, you know, when you take more of a services approach to things. So, I think the most important message that we can leave from today is that, our observation on that notion of a spectrum, from, you know, public put it on public, to a true private orientation which is hybrid where an on premise play is gonna be essential. That spectrum seems to be real, number one. Number two, however, it doesn't mean that AWS in particular is not going to be successful at driving the definition of the Cloud experience, and number three, we're now seeing at least one company, but we're also starting to see indications of others, acknowledge that their roll in all of this will be to take whatever the leaders in Cloud are talking about and make it possible, that experience possible where the data requires and that will include on premise. >> So, and I agree with you, AWS is defining that Cloud experience. So, as Ana Pinczuk was speaking, I just wrote down, I jotted down, AWS Cloud experience, which they've defined, and HPE Cloud experience. So I've got pay as you go, you know this kind of flex capacity, kind of. I mean it's as close as you can probably get. >> Peter: Greenlake. >> Yeah, Greenlake Kind of. >> Something we all need to learn more about. But, it's getting there, it's getting there. >> But it will never get there entirely, right? Because, they're gonna require to be, you know, buy a years worth of capacity, thresholds, you're gonna have thresholds above and threshold below. >> Except, we also heard, again I think there's more, I don't wanna, I think you're right. >> It's nuanced, it's not 100% of the way there. >> You start throwing the balance sheet and finances in there and how you're gonna do it. >> We'll come back to that. So, elastic? Again, kind of. You know, to a point. Integrated services? Like tons of them, like thousands a year? Some of those, but as I was saying before, HP's ecosystem play, allows them to pick and choose. >> Yeah, but remember Dave, okay keep going, keep going. >> Security, sort of, let's call it the Amazon way. Here's our security, it's good. But take it or leave it. And then, the HP approach is your way. HPE, you have security your way. If that's the edict of the organization, we can map to that. One Cloud versus Multi-Cloud. Obviously, HPE has a Multi-Cloud strategy, Amazon doesn't. They don't care about managing Multi-Clouds. They care about managing their Cloud. And then services as a service. HPE can deliver that and, Amazon I got a question mark, it's their ecosystem that's delivering those services. So I guess the point is, that I'm making is, maybe it's not the exact replica of the Amazon experience, but there are attributes of it, which appeal to Enterprise IT. >> Peter: That's right. >> Which Amazon is really not interested in delivering. >> Peter: Right. >> Ergo, the assumption is, my assumption is that, that business, that on prem business will be here for a long, long time. >> Peter: Absolutely. >> Indefinitely. >> And we would agree with that. In fact we think, ultimately, that there's gonna be enough uniqueness about how businesses use their data and treat their data that we expect to see this notion of true private Cloud actually be a bigger overall piece of the marketplace than the one size fits all, with a degree of customization possible, that Amazon's providing. But, again, this is, we have to be careful here. Because as analysts, we're sort of naturally falling into this trap of setting up AWS and HPE or any of these folks in opposition. There are companies that have very, very different opposed visions of how this is gonna play out. Specifically, we can talk about Amazon saying it's all gonna be IaaS, we're gonna out paths in there. And then, increasingly obviously, Microsoft and Oracle saying, oh no, we're gonna have application Clouds. You're gonna buy and application Cloud, and you're gonna do a whole bunch of stuff in that. What we see today is not in opposition, >> Dave: Right. >> to the AWS vision, it's not. It is a, okay, great. But for this type of work, this type of data, this type of workload, this type of reality, chances are, you're gonna need to put this type of stuff here, and have it fit into the overall motion of Cloud experience, and it doesn't have to be a complete substitute. It just has to work for that class of workload. >> Well, but, bringing it back to HP, and we gotta wrap, is HPE does not have an application Cloud, right? >> Peter: They don't. >> And as a result, it's going to be in a knife fight. With Amazon, with Dell EMC, and with China. >> It's gonna be in a knife fight with companies that are like it. China, you know, Huawei, Dell EMC, Cisco. >> You're right, you're right. Amazon's setting the pricing tone and the business model tone. >> Look, right now it's Amazon and Microsoft, are helping to set the stage of what this is all gonna look like. >> So, again, bottom line is, it's not a 60% gross margin company, Mark Hurds vision of going to compete with Cisco. It's a 25 to 32% gross margin business. >> Peter: That's really focused on customer problems. >> Focus on customer problems throws off a couple billion dollars of cash, it can eke out a little bit of growth. You know, that's what it is. >> Not a bad business. >> No, it's a great business, actually. Alright, Pete, thanks the wrap on day one. We'll be back tomorrow 8:30 am local time, right? >> Man: Sure. >> Roughly. >> Man: 8:45. >> 8:45 local time. Check out theCUBE.net, where you'll see this show, you'll see the other shows that we're doing including re:Invent John Furrier and the crew are over there today. That's a wrap for day one, this is theCUBE. We'll see you tomorrow. (upbeat music)