>>The Cube presents UI Path Forward five, brought to you by UI Path. >>Hi everybody. Welcome to Las Vegas. We're here in the Venetian, formerly the Sans Convention Center covering UI Path Forward five. This is the fourth time the Cube has covered forward, not counting the years during Covid, but UiPath was one of the first companies last year to bring back physical events. We did it at the Bellagio last year, Lisa Martin and myself. Today, my co-host is David Nicholson, coming off of last week's awesome CrowdStrike show back here in Vegas. David talking about UI path. UI path is a company that had a very strange path, as I wrote one time to IPO this company that was founded in 2005 and was basically a development shop. And then they realized they got lightning in a bottle with this RPA thing. Yeah. And Daniel Deez, the founder of the company, just really drove it hard and they really didn't do any big kind of VC raise for several years. >>And then all of a sudden, boom, the rocket ship took off, kind of really got out over their skis a little bit, but then got to IPO and, and has had a very successful sort of penetration into the market. The IPO obviously has not gone as well. We can talk about that, but, but they've hit a billion dollars in arr. There aren't a lot of companies that, you know, have hit a billion dollars in ARR that quickly. These guys had massive valuations that were cut back, obviously with the, with the downturn, but also some execution misuses. But the one thing about UiPath, Dave, is they've been very successful at penetrating customers. And that's the thing you always get at forward customer stories. And the other thing I'll, I'll, I'll add is that it started out with the narrative was, oh, automation software, robots, they're gonna take away jobs. The opposite has happened, the zero unemployment. Now basically we're heading into a recession, we're actually probably in a recession. And so how do you combat a recession? You put automation to work and gain if, if, if, if inflation is five to 7% and you can get 20% from automation. Well, it's a good roi. But you sat in the keynotes, it was really your first exposure to the company. What were your thoughts? >>Yeah, I think the whole subject is interesting. I think if you've been involved in tech for a while, the first thing you think of is, well, hold on a second. Isn't this just high tech scripting? Aren't you essentially just automating stuff? How, how cool can that possibly be? >>Well, it kinda was in the >>Beginning. Yeah, yeah. But, but, but when you dig into it, to your, to your point about the concern about displacing human beings, the first things that can automate it are the mundane and the repetitive tasks, which then frees individuals up frontline individuals who are doing those tasks to do more strategic things for the business. So when you, when we, you know, one of the things that was talked about in the keynote was this idea of an army of citizen developers within an organization. Not, you know, not just folks who are innovating and automating at the core of enterprise applications, but also folks out on the front line automating the tasks that are interfering with their productivity. So it seems like it's a win-win for, for everybody throughout the enterprise. >>Yeah. So let's take a, let's take folks through the, the keynote to, basically we learned there are 3,500 people here, roughly, you know, we're in the Venetian and we do a lot of shows at, at the Venetian, formerly the San Convention Center. The one thing about UiPath, they, they are a cool company. Yeah, they are orange colors, kinda like pure storage, but they got the robots moving around. The setup is very nice, it's very welcoming and very cool, but 300 3500 attendees, including partners and UiPath employees, 250 sessions. They've got a CIO, automation council and a pickleball court inside this hall, which pickleball is, you know, all the rage. So Bobby, Patrick and Mary Telo kicked it off. Bobby's the cmo, Mary's the head of branding, and Bobby raised four themes. It it, this is a tool that it's, this is RPA is going from a tool to a way of operating and innovating. >>The second thing is, the big news here is the UI path business platform, something like that. They're calling, but they're talking about about platform and they're really super gluing that to digital transformation. The third is really outcomes shifting from tactical. I have a robot, a software robot on my desk doing, you know, mimicking what I do with the script to something that's transformative. We're seeing this operationalized very deeply. We'll go into some examples. And then the fourth theme is automation is being featured as a strategic line item in annual reports. Bobby Patrick, as he left the stage, I think he was commenting on my piece where I said that RPA automation is more discretionary than some other things. He said, this is not discretionary, it's strategic. You know, unfortunately when you're heading into a recession, you can, you can put off some of the more strategic items. However, the flip side of that, Dave, is as they were saying before, if you're gonna, if if you're, if you're looking at five to 7% inflation may be a way to attack that is with automation. Yeah. >>There's no question, there's no question that automation is a way to attack that. There's no question that automation is critical moving forward. There's no question that we have moved. We're in the, you know, we're, we're still in the age of cloud, but automation is gonna be absolutely critical. The question is, what will UI path's role be in that market? And, and, and when you hear, when you hear UI path talk about platform versus tool sets and things like that, that's a critical differentiator because if they are just a tool, then why wouldn't someone exploit a tool that is within an application environment instead of exploiting a platform? So what I'm gonna be looking for in terms of the, the folks we talked to over the next few days is this question of, you know, make the case that this is actually a platform that extends across all kinds of application environments. If they can't seize that high ground moving forward, it's it's gonna be, it's gonna be tough for them. >>Well, they're betting the company on >>That, that's Rob Ensslin coming in. That's why he's part of the, the equation. But >>That platform play is they are betting the company. And, and the reason is, so the, the, the history here is in the early days of this sort of RPA craze, Automation Anywhere and UI path went out, they both raised a ton of money. UI Path rocketed out to the lead. They had a much e easier to install, you know, Automation Anywhere, Blue Prism, some of the other legacy business process folks, you know, kind of had on-prem, Big Stacks, UiPath came in a really simple self-serve platform and took off and really got a foothold in the market. And then started building or or making some of these acquisitions like Process Gold, like cloud elements, which is API automation. More recently Reiner, We, which is natural language processing. We heard them up on the stage today and they've been putting that together to do not just rpa but process mining, task mining, you know, document automation, et cetera. >>And so Rob Ins insulin was brought in from Google, formerly Google and SAP, to really provide that sort of financial and go to market expertise as well as Shim Gupta who's, who's the cfo. So they, they, and they were kinda late with that. They sort of did all this post ipo. I wish they had done it, you know, somewhat beforehand, but they're sort of bringing in that adult supervision supervision that's necessary. Rob Sland, I thought was very cogent. He was assertive on stage, he was really clear, he was energetic. He talked about the phases, e r p, Internet cloud and the now automation is a new S-curve. He quoted a Forester analyst talking about that. He also had a great quote. He said, you know, the old adage better, faster, cheaper, pick two. He said, You don't have to do that anymore with automation. He cited reports from analysts, 50% efficiency improvement, 40% productivity improvement, 40% improvement in customer satisfaction. >>And then what I always, again, love about UiPath is they're no shortage of customers. They do as good a job as anybody, and I think I would say the best of, of, of getting customers to talk about their experiences. You'll see that on the cube all this week, talked about Changi airport from Singapore. They're adding 50 able to service 50 million new customers, new travelers with no new headcount company called Vital or retail. And how you say that a hundred thousand employees having access to it. Uber, 150% ROI in one year. New York state getting 1.2 million relief checks out in two weeks and identifying potentially 12 billion in fraud. They also talk about 25% of the, of the UI path finance team is digital. And they've, they've only incremented headcount, you know, very slightly one and a half times their revenue's grown. What a 10 x? And really he talked about how to, for how to turn automation into a force multiplier for growth. And to your point, I think that's their challenge. What were your thoughts on Rob ens insulin's keynote? >>First of all, in addition to his background, Rob brings a brand with him. Rob Ensslin is a brand, and that brand is enterprise overarching platform. Someone you go to for that platform play, not for a tool set. And again, I'll, I'll say it again. It's critically important that they, that they demonstrate this to the marketplace, that they are a platform worth embracing as opposed to simply a tool set. Because the large enterprise software providers are going to provide their own tool sets within their platforms. And if you can't convince someone that it's worth doing two things instead of one thing, you're, you're, you're never gonna make it. So I've had experiences with Rob when he was at Google. He's, he's, he's the right person for the job and I, and I I I buy into his strategy and narrative about where we are and the critical nature of automation question remains, will you I path to be able to benefit from that trend. >>So a couple things on that. So your point about sap, you know, is right on EY was up on stage. They, EY is a huge SAP customer and they chose UI path to automate their SAP installation, right? And they're going all in with UI path as a partner. Of course. I I often like to say that the global system integrators, they like to eat at the trough, right? When you see GSIs like EY and others coming into the ecosystem, that means there's business being done. We saw Orange up on stage, which was really interesting. >>Javier from Spain. Yeah. Yep. >>Talking about he had this really cool dashboard and then Ted Coomer was talking about the business automation platform and all the different chapters and the evolution. They've gotta get to a platform play because the thing I failed to mention is Microsoft a couple years ago made a tuck in acquisition and got it to this market really providing individual automations and making it, you know, it's Microsoft, they're gonna make it really easy to add it really >>Cheaply. SAP would tell you that they have the same thing and, >>And then, and then just grow from that. So UiPath has to pivot to a platform play. They started this back in 2019, but as you know, it takes a long time to integrate stuff. Okay. So they're, they're, they're working through that. But this is, you know, Rob ends and put up on the, the slide go big, I, I tweeted, took a page outta Michael Dell. Go big or go home. Final thoughts before we break? >>I think go big or go home is pretty much sums it up. I mean this is, this is an existential mission that UiPath is on right now, starting to stay forward. They need to seize that high ground of platform versus tool set. Otherwise they will never get beyond where they are now. I I I, I do wanna mention too, to folks in the audience, there's a huge difference between a billion dollar valuation and a billion dollars in revenue every year. So, so, you know, these, these guys have reached a milestone, there's no question about that. But to get to that next level platform, platform, platform, and I know we'll be, we'll be probing our guests on that question over the next couple years. >>Yeah. And the key is obviously gonna be keep servicing the customers, you know, all the financial machinations and you know, they reduced yesterday their guidance from the high end being 25% ARR growth down to roughly 20% when you, when you factor out currency conversions. UiPath has a lot of business overseas. They're taking that overseas revenue and converting it back to dollars though dollars are appreciated. So they're less of them. I know this is kind of the inside baseball, but, but we're gonna get into that over the next two days. Dave Ante and Dave, you're watching the Cubes coverage of UI path forward, five from Las Vegas. We'll be right back, right after this short break.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome back to the Cube's coverage of HPE. Discover 22 live from the Sans expo center in Las Vegas. Lisa Martin, here with Dave Velante. We've an alumni back joining us to talk about high performance computing and AI, Justin ARD, EVP, and general manager of HPC and AI at HPE. That's a mouthful. Welcome back. >>It is no, it's great to be back and wow, it's great to be back in person as well. >>It's it's life changing to be back in person. The keynote this morning was great. The Dave was saying the energy that he's seen is probably the most out of, of any discover that you've been at and we've been feeling that and it's only day one. >>Yeah, I, I, I agree. And I think it's a Testament to the places in the market that we're leading the innovation we're driving. I mean, obviously the leadership in HPE GreenLake and, and enabling as a service for, for every customer, not just those in the public cloud, providing that, that capability. And then obviously what we're doing at HPC and AI breaking, uh, you know, breaking records and, uh, advancing the industry. So >>I just saw the Q2 numbers, nice revenue growth there for HPC and AI. Talk to us about the lay of the land what's going on, what are customers excited about? >>Yeah. You know, it's, it's a, it's a really fascinating time in this, in this business because we're, you know, we just, we just delivered the first, the world's first exo scale system. Right. And that's, uh, you know, that's a huge milestone for our industry, a breakthrough, you know, 13 years ago, we did the first Petta scale system. Now we're doing the first exo scale system, huge advance forward. But what's exciting too, is these systems are enabling new applications, new workloads, breakthroughs in AI, the beginning of being able to do proper quantum simulations, which will lead us to a much, you know, brighter future with quantum and then actually better and more granular models, which have the ability to really change the world. >>I was telling Lisa that during the pandemic we did, uh, exo scale day, it was like this co yep. You know, produce event. And we weren't quite at exo scale yet, but we could see it coming. And so it was great to see in frontier and, and the keynote you guys broke through that, is that a natural evolution of HPC or is this we entering a new era? >>Yeah, I, I think it's a new era and I think it's a new era for a few reasons because that, that breakthrough really, it starts to enable a different class of use cases. And it's combined with the fact that I think, you know, you look at where the rest of the enterprises data set has gone, right? We've got a lot more data, a lot more visibility to data. Um, but we don't know how to use it. And now with this computing power, we can start to create new insights and new applications. And so I think this is gonna be a path to making HPC more broadly available. And of course it introduces AI models at scale. And that's, that's really critical cause AI is a buzzword. I mean, lots of people say they're doing AI, but when you know, to, to build true intelligence, not, not effectively, you know, a machine that learns data and then can only handle that data, but to build true intelligence where you've got something that can continue to learn and understand and grow and evolve, you need this class of system. And so I think we're at, we're at the forefront of a lot of exciting innovation. H how, >>In terms of innovation, how important is it that you're able to combine as a service and HPC? Uh, what does that mean for, for customers for experimentation and innovation? >>You know, a couple things I've been, I've actually been talking to customers about that over the last day and a half. And, you know, one is, um, you think about these, these systems are, they're very large and, and they're, they're pretty, you know, pretty big bets if you're a customer. So getting early access to them right, is, is really key, making sure that they're, they can migrate their software, their applications, again, in our space, most of our applications are custom built, whether you're a, you know, a government or a private sector company, that's using these systems, you're, you're doing these are pretty specialized. So getting that early access is important. And then actually what we're seeing is, uh, with the growth and explosion of insight that we can enable. And some of the diversity of, you know, new, um, accelerator partners and new processors that are on the market is actually the attraction of diversity. And so making things available where customers can use multimodal systems. And we've seen that in this era, like our customer Lumi and Finland number, the number three fastest system in the world actually has two sides to their system. So there's a compute side, dense compute side and a dense accelerator side. >>So Oak Ridge national labs was on stage with Antonio this morning, the, the talking about frontier, the frontier system, I thought what a great name, very apropo, but it was also just named the number one to the super computing, top 500. That's a pretty big accomplishment. Talk about the impact of what that really means. >>Yeah. I, I think a couple things, first of all, uh, anytime you have this breakthrough of number one, you see a massive acceleration of applications. And if you really, if you look at the applications that were built, because when the us department of energy funded these Exoscale products or platforms, they also funded app a set of applications. And so it's the ability to get more accurate earth models for long term climate science. It's the ability to model the electrical grid and understand better how to build resiliency into that grid. His ability is, um, Dr. Te Rossi talked about a progressing, you know, cancer research and cancer breakthroughs. I mean, there's so many benefits to the world that we can bring with these systems. That's one element. The other big part of this breakthrough is actually a list, a lesser known list from the top 500 called the green 500. >>And that's where we measure performance over power consumption. And what's a huge breakthrough in this system. Is that not only to frontier debut at number one on the top 500, it's actually got the top two spots, uh, because it's got a small test system that also is up there, but it's got the top two spots on the green 500 and that's actually a real huge breakthrough because now we're doing a ton more computation at far lesser power. And that's really important cuz you think about these systems, ultimately you can, you can't, you know, continue to consume power linearly with scaling up performance. There's I mean, there's a huge issue on our impact on our environment, but it's the impact to the power grid. It's the impact to heat dissipation. There's a lot of complexities. So this breakthrough with frontier also enables us no pun intended to really accelerate, you know, the, the capacity and scale of these systems and what we can deliver. >>It feels like we're entering a new Renaissance of HPC. I mean, I'm old enough to remember. I, it was, it wasn't until recently my wife, not recently, maybe five, six years ago, my wife threw out my, my green thinking machines. T-shirt that Danny Hillis gave you guys probably both too young to remember, but you had thinking machines, Ken to square research convex tried to mini build a mini computer HPC. Okay. And there was a lot of innovation going on around that time and then it just became too expensive and, and, and other things X 86 happened. And, and, but it feels like now we're entering a, a new era of, of HPC. Is that valid or is it true? What's that mean for HPC as an industry and for industry? >>Yeah, I think, I think it's a BR I think it's a breadth. Um, it's a market that's opening and getting much more broader the number of applications you can run, you know, and we've traditionally had, you know, scientific applications, obviously there's a ton in energy and, and you know, physics and some of the traditional areas that obviously the department of energy sponsor, but, you know, we saw this with, with even the COVID pandemic, right? Our, our supercomputers were used to identify the spike protein to, to help and validate and test these vaccines and bring them to market and record time. We saw some of the benefits of these breakthroughs. And I think it's this combination of that, that we actually have the data, you know, it's, it's digital, it's captured, um, we're capturing it at, you know, at the edge, we're capturing it and, and storing it obviously more broadly. So we have the access to the data and now we have the compute power to run it. And the other big thing is the techniques around artificial intelligence. I mean, what we're able to do with neural networks, computer vision, large language models, natural language processing. These are breakthroughs that, um, one require these large systems, but two, as you give them a large systems, you can actually really enable acceleration of how sophisticated these, these applications can get. >>Let's talk about the impact of the convergence of HPC and AI. What are some of the things that you're seeing now and what are some of the things that we're gonna see? >>Yeah. So, so I, one thing I like to talk about is it's, it's really, it's not a convergence. I think it's it. Sometimes it gets a little bit oversimplified. It's actually, it's traditional modeling and simulation leveraging machine learning to, to refine the simulation. And this is a, is one of the things we talk about a lot in AI, right? It's using machine learning to actually create code in real time, rather than humans doing it, that ability to refine the model as you're running. So we have an example. We did a, uh, we, we actually launched an open source solution called smart SIM. And the first application of that was climate science. And it's what it's doing is it's actually learning the data from the model as the simulation is running to provide more accurate climate prediction. But you think about that, that could be run for, you know, anything that has a complex model. >>You could run that for financial modeling, you can use AI. And so we're seeing things like that. And I think we'll continue to see that the other side of that is using modeling and simulation to actually represent what you see in AI. So we were talking about the grid. This is one of the Exoscale compute projects you could actually use once you actually get, get the data and you can start modeling the behavior of every electrical endpoint in a city. You know, the, the meter in your house, the substation, the, the transformers, you can start measuring the FX of that. You can then build equations. Well, once you build those equations, you can then take a model, cuz you've learned what actually happens in the real world, build the equation. And then you can provide that to someone who doesn't need a extra scale supercomputer to run it, but that, you know, your local energy company can better understand what's happening and they'll know, oh, there's a problem here. We need to shift the grid or respond more, more dynamically. And hopefully that avoids brownouts or, you know, some of the catastrophic outages we've >>Seen so they can deploy that model, which, which inherently has that intelligence on sort of more cost effective systems and then apply it to a much broader range. Do any of those, um, smart simulations on, on climate suggest that it's, it's all a hoax. You don't have to answer that question. <laugh> um, what, uh, >>The temperature outside Dave might, might give you a little bit of an argument to that. >>Tell us about quantum, what's your point of view there? Is it becoming more stable? What's H HPE doing there? >>Yeah. So, so look, I think there's, there's two things to understand with quantum there's quantum hardware, right? Fundamentally, um, how, um, how that runs very differently than, than how we run traditional computers. And then there's the applications. And ultimately a quantum application on quantum hardware will be far more efficient in the future than, than anything else. We, we see the opportunity for, uh, much like we see with, you know, with HPC and AI, we just talked about for quantum to be complimentary. It runs really well with certain applications that fabricate themselves as quantum problems and some great examples are, you know, the, the life sciences, obviously quantum chemistry, uh, you see some, actually some opportunities in, in, uh, in AI and in other areas where, uh, quantum has a very, very, it, it just lends itself more naturally to the behavior of the problem. And what we believe is that in the short term, we can actually model quantum effectively on these, on these super computers, because there's not a perfect quantum hardware replacement over time. You know, we would anticipate that will evolve and we'll see quantum accelerators much. Like we see, you know, AI accelerators today in this space. So we think it's gonna be a natural evolution in progression, but there's certain applications that are just gonna be solved better by quantum. And that's the, that's the future we'll we'll run into. And >>You're suggesting if I understood it correctly, you can start building those applications and, and at least modeling what those applications look like today with today's technology. That's interesting because I mean, I, I think it's something rudimentary compared to quantum as flash storage, right? When you got rid of the spinning disc, it changed the way in which people thought about writing applications. So if I understand it, new applications that can take advantage of quantum are gonna change the way in which developers write, not one or a zero it's one and virtually infinite <laugh> combinations. >>Yeah. And I actually, I think that's, what's compelling about the opportunity is that you can, if you think about a lot of traditional the traditional computing industry, you always had to kind of wait for the hardware to be there, to really write, write, and test the application. And we, you know, we even see that with our customers and HPC and, and AI, right? They, they build a model and then they, they actually have to optimize it across the hardware once they deploy it at scale. And with quantum what's interesting is you can actually, uh, you can actually model and, and, and make progress on the software. And then, and then as the hardware becomes available, optimize it. And that's, you know, that's why we see this. We talk about this concept of quantum accelerators as, as really interesting, >>What are the customer conversations these days as there's been so much evolution in HPC and AI and the technology so much change in the world in the last couple of years, is it elevating up the CS stack in terms of your conversations with customers wanting to become familiar with Exoscale computing? For example? >>Yeah. I, I think two things, uh, one, one is we see a real rise in digital sovereignty and Exoscale and HPC as a core fund, you know, fundamental foundation. So you see what, um, you know, what Europe is doing with the, the, the Euro HPC initiative, as one example, you know, we see the same kind of leadership coming out of the UK with the system. We deployed with them in Archer two, you know, we've got many customers across the globe deploying next generation weather forecasting systems, but everybody feels, they, they understand the foundation of having a strong supercomputing and HPC capability and competence and not just the hardware, the software development, the scientific research, the, the computational scientists to enable them to remain competitive economically. It's important for defense purposes. It's important for, you know, for helping their citizens, right. And providing, you know, providing services and, and betterment. >>So that's one, I'd say that's one big theme. The other one is something Dave touched on before around, you know, as a service and why we think HP GreenLake will be, uh, a beautiful marriage with our, with our HPC and AI systems over time, which is customers also, um, are going to scale up and build really complex models. And then they'll simplify them and deploy them in other places. And so there's a number of examples. We see them, you know, we see them in places like oil and gas. We see them in manufacturing where I've gotta build a really complex model, figure out what it looks like. Then I can reduce it to a, you know, to a, uh, certain equation or application that I can then deploy. So I understand what's happening and running because you, of course, as much as I would love it, you're not gonna have, uh, every enterprise around the world or every endpoint have an exit scale system. Right. So, so that ability to, to, to really provide an as a service element with HP GreenLake, we think is really compelling. >>HP's move into HPC, the acquisitions you've made it really have become a differentiator for the company. Hasn't it? >>Yeah. And I, and I think what's unique about us today. If you look at the landscape is we're, we're really the only system provider globally. Yeah. You know, there are, there are local players that we compete with. Um, but we are the one true global system provider. And we're also the only, I would say the only holistic innovator at the system level to, to, you know, to credit my team on the work they're doing. But, you know, we're, we're also very committed to open standards. We're investing in, um, you know, in a number of places where we contribute the dev the software assets to open source, we're doing work with standards bodies to progress and accelerate the industry and enable the ecosystem. And, uh, and I think that, you know, ultimately the, the, the last thing I'd say is we, we are so connected in, um, with, through our, through the legacy or the, the legend of H Hewlett Packard labs, which now also reports into me that we have these really tight ties into advanced research and that some of that advanced research, which isn't just, um, around kind of core processing Silicon is really critical to enabling better applications, better use cases and accelerating the outcomes we see in these systems going forward. >>Can >>You double click on that? I, I, I wasn't aware that kind of reported into your group. Yeah. So, you know, the roots of HP are invent, right? Yeah. HP labs are, are renowned. It kinda lost that formula for a while. And now it's sounds like it's coming back. What, what, what are some of the cool things that you guys are working on? Well, >>You know, let me, let me start with a little bit of recent history. So we just talked about the exo scale program. I mean, that was a, that's a great example of where we had a public private partnership with the department of energy and it, and it wasn't just that we, um, you know, we built a system and delivered it, but if you go back a decade ago, or five years ago, there were, there were innovations that were built, you know, to accelerate that system. One is our Slingshot fabric as an example, which is a core enable of, of acceler, you know, of, of this accelerated computing environment, but others in software applications and services that allowed us to, you know, to really deliver a, a complete solution into the market. Um, today we're looking at things around trustworthy and ethical AI, so trustworthy AI in the sense that, you know, the models are accurate, you know, and that's, that's a challenge on two dimensions, cuz one is the, model's only as good as the data it's studying. >>So you need to validate that the data's accurate and then you need to really study how, you know, how do I make sure that even if the data is accurate, I've got a model that then, you know, is gonna predict the right things and not call a, a dog, a cat, or a, you know, a, a cat, a mouse or whatever that is. But so that's important. And, uh, so that's one area. The other is future system architectures because, um, as we've talked about before, Dave, you have this constant tension between the fabric, uh, you know, the interconnect, the compute and the, and the storage and, you know, constant, constantly balancing it. And so we're really looking at that, how do we do more, you know, shared memory access? How do we, you know, how do we do more direct rights? Like, you know, looking at some future system architectures and thinking about that. And we, you know, we think that's really, really critical in this part of the business because these heterogeneous systems, and not saying I'm gonna have one monolithic application, but I'm gonna have applications that need to take advantage of different code, different technologies at different times. And being able to move that seamlessly across the architecture, uh, we think is gonna be the, you know, a part of the, the hallmark of the Exoscale era, including >>Edge, which is a completely different animal. I think that's where some disruption is gonna gonna bubble up here in the next decade. >>So, yeah know, and, and that's, you know, that's the last thing I'd say is, is we look at AI at scale, which is another core part of the business that can run on these large clusters. That means getting all the way down to the edge and doing inference at scale, right. And, and inference at scale is, you know, I, I was, um, about a month ago, I was at the world economic forum. We were talking about the space economy and it's a great, you know, to me, it's the perfect example of inference, because if you get a set of data that you know, is, is out at Mars, it doesn't matter whether, you know, whether you wanna push all that data back to, uh, to earth for processing or not. You don't really have a choice, cuz it's just gonna take too long. >>Don't have that time. Justin, thank you so much for spending some of your time with Dave and me talking about what's going on with HBC and AI. The frontier just seems endless and very exciting. We appreciate your time on your insights. >>Great. Thanks so much. Thanks. >>Yes. And don't call a dog, a cat that I thought I learned from you. A dog at no, Nope. <laugh> Nope. <laugh> for Justin and Dave ante. I'm Lisa Martin. You're watching the Cube's coverage of day one from HPE. Discover 22. The cube is, guess what? The leader, the leader in live tech coverage will be right back with our next guest.

(upbeat music) >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at the RSA Conference in downtown San Francisco. We're live, it's 40,000 people all talking about security, and we're excited for a first-time attendee of RSA. We're joined by John Smith, a solutions architect from ExtraHop Networks. Welcome, John. >> Hey, thanks for having me. >> Absolutely. So you said it's your first time to the RSA Conference? I'm just curious, kind of first impressions of the show? >> Wow. Well, there's certainly a lot of people here. It's the biggest show I've ever been to. We've been to Synergy, HIMSS, a couple of them. I think HIMSS might have more people, but it certainly seems more crowded. People are more involved in the booths here, asking a lot of really good questions. A lot of ones and zeros people at the booth, so you really got to be on your toes (laughs) when you're talking to folks. (Jeff laughs) >> All right, for the people that aren't familiar with ExtraHop, give us kind of the overview, what you guys are all about. >> So we're a real-time IT analytics product that uses wire data to provide, at least in the security space, the biggest play we have is more around surveillance and invisibility. One of the first two controls that SANS recognizes as being, that you need to secure your environment, is asset inventory and the ability to see what applications are running on those assets. A lot of the tools in the security industry try to engineer down to that, to try to give you that. That's one of the, a lot of security people will kind of name that as one of the more difficult things to get. We start there. So we are a wire data analytics, that's kind of the core of what we do, so we don't require any IP addresses, we don't, or, I'm sorry, we don't require any agents, we don't require any SNMP, any ping sweeps or anything like that. If it has an IP address, it can't hide from us. So that means whether it's an IOT device or a medical device that's been compromised, if it's someone who wants to work in the dark and they've got a NACL that's blocking people, the minute they communicate with someone else, they're made and they can't hide from us. So what we've seen in our, with our customer base, is kind of a burgeoning security practice where people are actually using the appliance more in a security use case, and that's probably our fastest-growing use case right now. >> So what was the core of the business before? You said ExtraHop's been around for 10 years, but you're new here. What was kind of the core business before your security practice really grew? >> So the core of the business, and, you know, there's three kind of major areas. There's, we generally use the wire as a data source. So we position the customer to interact directly with the wire and the data that's coming across it. So that can be break, fix, and performance of your different web applications from layer two up to layer seven. A lot of that is business intelligence. We had an online retailer that wanted to know, you know, the average of income of people who filled out their credit app by ZIP code so that they could adjust pricing. That used to be a complicated OLAP job on the back end. We were able to give that to them in real time so that they could see, "Hey, people in this ZIP code make $300 a month more "than people in this ZIP code, we can raise prices here." So business intelligence and break, fix, and performance are big ones, and then of course in the security place, or the security space, where we're able to provide full accountability for every single IP address on the network, has been very powerful. >> Interesting. So you said you had some announcements that you guys are making here at the show? >> Yeah, so we have, are announcing our SaaS offering, which is another, it's basically a machine-learning, a cloud-based machine-learning platform that allows us to do some anomaly detection without the need to, you know, a lot of your cloud-based anomaly detection tools require you to forward terabytes of data so that then they can look at it, analyze it, and then maybe an hour later you get some information that you've been breached or that there's a problem-- >> That, or a day. >> Yeah, or, maybe, yeah. >> Months and months and months. >> Exactly. We're kind of unique in that we're able to, you know, what our Atlas program is able to essentially interrogate systems that are deployed around the world, currently around the U.S., it's a U.S. offering today, but basically we can interrogate those systems for any types of anomalies that happen. Actually, in the run up to the offering, we had a customer that was able to reroute some traffic because they were able to see the mirai botnet was starting to meddle with some of the performance of different parts of their infrastructure. So having the ability to be able to provide customers visibility into what's going on on their networks without the burden of making them FTP data up to you so that then you can evaluate it, one, you don't have the infrastructure burden of sending the data to you and the delay with that, but in addition to that, you're able to provide some real-time visibility. One of the things we've noticed is that the people who have the ability to interpret the data and to kind of parse and tell you when there is an anomaly, they're very overworked and they're spread really thin in a lot of their organizations. We augment that capability by doing some of that heavy lifting for them so that we can say, "Hey, did you know you have 1,000% increase in, you know, "DNS traffic from this particular host?" >> Right. >> That type of visibility that you can do in real time, so that if you have multiple branches around the country, we can provide that visibility from one centralized location. >> Yeah, it's all about the real time, right? Real time is in time, hopefully. >> Real time, and really, the money is in the mash-up, right? We've had a lot of really, one of the things I've noticed over the years is thread intelligence has really matured, and I think that's great, but if you can't marry that with some of your own intelligence that's going on on your own networks, you know, the value is really a lot tougher to realize. If you can ad hoc or if you can engage in some ad hoc thread intelligence by leveraging a platform like ExtraHop that can do the evaluation and thread things like anomalous behavior, that makes your agility to deal with today's threats really, really, a lot more effective. Most threats, as you're probably aware, happen, I think 93% of them happen within a minute. Dealing with that with humans, dealing with that with logs, is, it's really, really tough to do. I love logs and I love humans, but if you can position yourself to engage in programmatically dealing with that, we see orchestration is becoming, you know, kind of an emerging technology, and we're uniquely positioned to be able to interact with any sort of orchestration engines, something like a phantom, you know, things like that, where we can observe some actionable data, and then we have an open platform that can then integrate with the orchestration they're after. >> All right. Well, John, that was a great summary. We're going to leave it there, thanks for stopping by. The money's in the mash-up, did I get it right? >> John And Jeff: The money's in the mash-up. >> Baby. >> All right. >> All right. >> He's John Smith, I'm Jeff Frick. You're watching theCUBE from RSA. >> Thank you. >> Thanks for watching. (upbeat music)