>>We're here live in Las Vegas with a cubes coverage of Amazon re Mars. It's a reinvent re Mars reinforced. The big three shows called the res. This is Mars machine learning, automation, robotic and space. It's a program about the future it and the future innovation around industrial cloud scale climate change the moon, a lot of great topics, really connecting all the dots together here in Las Vegas with Amazon re Mars I'm John ER, host of the cube. Our first guest is Howard Hughes program manager, necess Ryan program. Howard is involved with all the action and space and the moon project, which we'll get into Howard. Thanks for coming on the cube. >>Well, Hey, thanks for having me here this morning. Appreciate you guys inviting me here. >>So this show is not obvious to the normal tech observer, the insiders in, in the industry. It's the confluence of a lot of things coming together. It's gonna be obvious very soon because the stuff they're showing here is pretty impressive. It's motivating, it's positive and it's a force for change in good. All of it coming together, space, machine learning, robotics, industrial, you have one of the coolest areas, the space what's going on with your Orion program. You guys got the big moon project statement to >>Explain. Well, let me tell you, I'll start with Orion. Orion is our next human space craft. That's gonna take humans beyond low earth orbit and we're part of the broader Artis campaign. So Artis is our plan, our NASA plan to return the first person of color, first woman, back to the moon. And we're very excited to do that. We have several missions that I could talk to you about starting with in a very few months, Artis one. So Artis one is going to fly on the space launch system, which is gonna be the biggest rocket we call the mega rocket has been built since the Saturn five on top of the SLS is the Ryan spacecraft and that Ryan spacecraft houses four crew members for up to 21 days in deep space. And we'll have an unru test in a few months launch on the S SLS. And Orion's gonna go around the moon for up to 40 days on Aus two, we will have the first test of the humans on board Orion. So four people will fly on Aus two. We will also circle the moon for about 10 to 12 days. And then our third mission will be our landing. >>So the moon is back in play, obviously it's close to the earth. So it's a short flight, relatively speaking the Mars a little bit further out. I'll see everyone as know what's going on in Mars. A lot of people are interested in Mars. Moon's closer. Yes, but there's also new things going on around discovery. Can you share the big story around why the moon what's? Why is the moon so important and why is everyone so excited about it? >>Yeah. You, you know, you know, coming to this conference and talking about sustainability, you know, I mean it is exploration is I think ingrained in our DNA, but it's more than just exploration is about, you know, projecting human presence beyond our earth. And these are the stepping stones. You know, we talk about Amazon talked about day one, and I think about, we are on those very early days where we're building the infrastructure Ryans of transportation infrastructure, and we're gonna build infrastructure on the moon to learn how to live on a surface and how to utilize the assets. And then that's very important because you know, it's very expensive to carry fuel, to carry water and all the necessities that you need to survive as a human being and outer space. If you can generate that on the surface or on the planet you go to, and this is a perfect way to do it because it's very in your backyard, as I told you earlier. So for future mission, when you want to go to Mars, you're nine months out, you really wanna make sure you have the technologies and you're able to utilize those technologies robustly and in a sustainable way. >>Yeah, we were talking before you came on, came camera camping in your backyard is a good practice round. Before you go out into the, to the wilderness, this is kind of what's going on here, but there's also the discovery angle. I mean, I just see so much science going on there. So if you can get to the moon, get a base camp there, get set up, then things could come out of that. What are some of the things that you guys are talking about that you see as possible exploration upside? >>Yeah. Well, several things. One is power generation recently. We just released some contracts that from vision power, so long, sustainable power capability is very, very important. You know, the other technologies that you need utilize is regenerative, you know, air, water, things that are, you need for that, but then there's a science aspect of it, which is, you know, we're going to the south pole where we think there's a lot of water potentially, or, or available water that we can extract and utilize that to generate fuel. So liquid hydrogen liquid oxygen is one of the areas that are very interesting. And of course, lunar minerals are very exciting, very interesting to bring and, and, and be able to mine potentially in the future, depending on what is there. >>Well, a lot of cool stuff happening. What's your take on this show here, obviously NASA's reputation as innovators and deep technologists, you know, big moonshot missions, pun intended here. You got a lot of other explorations. What's this show bring together, share your perspective because I think the story here to me is you got walkout retail, like the Amazon technology, you got Watson dynamics, the dog, everyone loves that's walking on. Then you got supply chain, robotics, machine learning, and space. It all points to one thing, innovation around industrial. I think what, what, what's your, what's your, what's your take? >>You know, I think one of the things is, is, you know, normally we are innovating in a, in our aerospace industry. You know, I think there's so much to learn from innovation across all these areas you described and trying to pull some of that into the spacecraft. You know, when, when you're a human being sitting in spacecraft is more than just flying the spacecraft. You know, you have interaction with displays, you have a lot of technologies that you normally would want to interact with on the ground that you could apply in space to help you and make your tasks easier. And I think those are things that are really important as we look across, you know, the whole entire innovative infrastructure that I see here in this show, how can we extract some that and apply it in the space program? I think there is a very significant leveraging that you could do off of that. >>What are some of the look at what's going on in donors? What are some of the cool people who aren't following the day to day? Anything? >>Well, well, certainly, you know, the Artman's mission Artis campaign is one of the, the, the coolest things I could think of. That's why I came into, you know, I think wrapping around that where we are not only just going to a destination, but we're exploring, and we're trying to establish a very clear, long term presence that will allow us to engage. What I think is the next step, which is science, you know, and science and the, and the things that can, can come out of that in terms of scientific discoveries. And I think the cool, coolest thing would be, Hey, could we take the things that we are in the labs and the innovation relative to power generation, relative to energy development of energy technologies, robotics, to utilize, to help explore the surface. And of course the science that comes out of just naturally, when you go somewhere, you don't know what to expect. And I think that's what the exciting thing. And for NASA, we're putting a program, an infrastructure around that. I think that's really exciting. Of course, the other parts of NASA is science. Yeah. And so the partnering those two pieces together to accomplish a very important mission for everybody on planet earth is, is really important. >>And also it's a curiosity. People are being curious about what's going on now in space, cuz the costs are down and you got universities here and you got the, of robotics and industrial. This is gonna provide a, a new ground for education, younger, younger generation coming up. What would you share to teachers and potential students, people who wanna learn what's different about now than the old generation and what's the same, what what's the same and what's new. What's how does someone get their arms around this, their mind around it? Where can they jump in? This is gonna open up the aperture for, for, for talent. I mean with all the technology, it's not one dimensional. >>Yeah. I think what is still true is core sciences, math, you know, engineering, the hard science, chemistry, biology. I mean, I think those are really also very important, but what we're we're getting today is the amount of collaboration we're able to do against organically. And I think the innovation that's driven by a lot of this collaboration where you have these tools and your ability to engage and then you're able to, to get, I would say the best out of people in lots of different areas. And that's what I think one of the things we're learning at NASA is, you know, we have a broad spectrum of people that come to work for us and we're pulling that. And now we're coming to these kinds of things where we're kind getting even more innovation ideas and partnerships so that we are not just off on our own thinking about the problem we're branching out and allowing a lot of other people to help us solve the problems that >>We need. You know, I've noticed with space force too. I had the same kind of conversations around those with those guys as well. Collaboration and public private partnerships are huge. You've seen a lot more kind of cross pollination of funding, col technology software. I mean, how do you do break, fix and space at software, right? So you gotta have, I mean, it's gotta work. So you got security challenges. Yeah. This is a new frontier. It is the cybersecurity, the usability, the operationalizing for humans, not just, you know, put atypical, you know, scientists and, and, and astronauts who are, you know, in peak shape, we're talking about humans. Yeah. What's the big problem to solve? Is it security? Is it, what, what would you say the big challenges >>Are? Yeah. You know, I think information and access to information and how we interact with information is probably our biggest challenge because we have very limited space in terms of not only mass, but just volume. Yeah. You know, you want to reserve the space for the people and they, they need to, you know, you want maximize your space that you're having in spacecraft. And so I think having access to information, being able to, to utilize information and quickly access systems so you can solve problems cuz you don't know when you're in deep space, you're several months out to Mars, what problems you might encounter and what kind of systems and access to information you need to help you solve the problems. You know, both, both, both from a just unplanned kind of contingencies or even planned contingencies where you wanna make sure you have that information to do it. So information is gonna be very vital as we go out into deep >>Space and the infrastructure's changed. How has the infrastructure changed in terms of support services? I mean see, in the United States, just the growth of a aerospace you mentioned earlier is, is just phenomenal. You've got smaller, faster, cheaper equipment density, it solved the technology. Where's there gonna be the, the big game changing move movement. Where do you see it go? Is it AIST three? It kind of kicks in AIST ones, obviously the first one unmanned one. But where do in your mind, do you see key milestones that are gonna be super important to >>Watch? I think, I think, I think, you know, we've already, you know, pushed the boundaries of what we, we are, you know, in terms of applying our aerospace technologies for AIST one and certainly two, we've got those in, in work already. And so we've got that those vehicles already in work and built yeah. One already at the, at the Kennedy space center ready for launch, but starting with three because you have a lot more interaction, you gotta take the crew down with a Lander, a human landing system. You gotta build rovers. You've gotta build a, a capability which they could explore. So starting with three and then four we're building the gateway gateways orbiting platform around the moon. So for all future missions after Rist three, we're gonna take Aion to the gateway. The crew gets into the orbiting platform. They get on a human landing system and they go down. >>So all that interaction, all that infrastructure and all the support equipment you need, not only in the orbit of the moon, but also down the ground is gonna drive a lot of innovation. You're gonna have to realize, oh, Hey, I needed this. Now I need to figure out how to get something there. You know? And, and how much of the robotics and how much AI you need will be very interesting because you'll need these assistance to help you do your daily routine or lessen your daily routine. So you can focus on the science and you can focus on doing the advancing those technologies that you're gonna >>Need. And you gotta have the infrastructure. It's like a road. Yeah. You know, you wanna go pop down to the moon, you just pop down, it's already built. It's ready for you. Yep. Come back up. So just ease of use from a deployment standpoint is, >>And, and the infrastructure, the things that you're gonna need, you know, what is a have gonna look like? What are you gonna need in a habitat? You know, are, are you gonna be able to have the power that you're gonna have? How many station power stations are you gonna need? Right. So all these things are gonna be really, things are gonna be driven by what you need to do the mission. And that drives, I think a lot of innovation, you know, it's very much like the end goal. What are you trying to solve? And then you go, okay, here's what I need to solve to build things, to solve that >>Problem. There's so many things involved in the mission. I can imagine. Safety's huge. Number one, gotta be up safe. Yep. Space is dangerous game. Yes. Yeah. It's not pleasant there. Not for the faint of heart. As you say, >>It's not for the faint >>Heart. That's correct. What's the big safety concerns obviously besides blowing up and oxygen and water and the basic needs. >>I think, I think, you know, I think you, you said it very well, you know, it is not for the faint of heart. We try to minimize risk. You know, asset is one of the big, you're sitting under 8.8 million pounds of thrust on the launch vehicle. So it is going very fast and you're flying and you, and, and it's it's light cuz we got solid rocket motors too as well. Once they're lit. They're lit. Yeah. So we have a escape system on Orion that allows a crew to be safe. And of course we build in redundancy. That's the other thing I think that will drive innovation. You know, you build redundancy in the system, but you also think about the kind of issues that you would run into potentially from a safety perspective, you know, how you gonna get outta situation if you get hit by a meteor, right? Right. You, you, you are going through the band, Ellen belt, you have radiation. So you know, some of these things that are harsh on your vehicle and on, on the human side of this shop too. And so when you have to do these things, you have to think about what are you gonna protect for and how do you go protect for that? And we have to find innovations for >>That. Yeah. And it's also gonna be a really exciting air for engineering work. And you mentioned the data, data's huge simulations, running scenarios. This is where the AI comes in. And that seems to me where the dots connect from me when you start thinking about how to have, how to run those simulations, to identify what's possible. >>I think that's a great point, you know, because we have all this computing capability and because we can run simulations and because we can collect data, we have terabytes of data, but it's very challenging for humans to analyze at that level. So AI is one of the things we're looking at, which is trying to systematically have a process by which data is called through so that the engineering mind is only looking at the things and focus on things that are problematic. So we repeat tests, every flight, you don't have to look at all the terabytes of data of each test. You have a computer AI do that. And you allow yourself to look at just the pieces that don't look right, have anomalies in the data. Then you're going to do that digging, right. That's where the power of those kinds of technologies can really help us because we have that capability to do a lot of computing. >>And I think that's why this show to me is important because it, it, it shows for the first time, at least from my coverage of the industry where technology's not the bottleneck anymore, it's human mind. And we wanna live in a peaceful world with climate. We wanna have the earth around for a while. So climate change was a huge topic yesterday and how the force for good, what could come outta the moon shots is to, is to help for earth. >>Yeah. >>Yeah. Better understanding there all good. What's your take on the show. If you had to summarize this show, re Mars from the NASA perspective. So you, the essence space, what's the what's going on here? What's the big, big story. >>Yeah. For, for me, I think it's eyeopening in terms of how much innovation is happening across a spectrum of areas. And I look at various things like bossy, scientific robots that the dog that's walking around. I mean to think, you know, people are applying it in different ways and then those applications in a lot of ways are very similar to what we need for exploration going forward. And how do you apply some of these technologies to the space program and how do we leverage that? How do we leverage that innovation and how we take the innovations already happening organically for other reasons and how would those help us solve those problems that we're gonna encounter going forward as we try to live on another planet? >>Well, congratulations on a great assignment. You got a great job. I do super fun. I love being an observer and I love space. Love how at the innovations there. And plus space space is cool. I mean, how many millions of live views do you see? Everyone's stopping work to watch SpaceX land and NASA do their work. It's just, it's bringing back the tech vibe. You know what I'm saying? It's just, it's just, things are going you a good tailwind. Yeah. >>Congratulations. Thank you very much. >>Appreciate it on the, okay. This cube coverage. I'm John fur. You're here for the cube here. Live in Las Vegas back at reinvent reinforce re Mars, the reser coverage here at re Mars. We'll be back with more coverage after this short break.

>> Live from Las Vegas it's The Cube covering NAB 2017. Brought to you by HGST. >> Welcome back to The Cube. We are live at NAB 2017. I'm Lisa Martin. Very, very excited, kind of geeking out right now to be joined by our next two guests. Sam Blackman, the co-founder and CEO of AWS Elemental, welcome to The Cube. >> Sam: Thank you so much. >> And we have NASA astronaut, Tracy Caldwell Dyson. Both of you, welcome to The Cube. >> Thank you. >> Today has been a very historic day for technology and space. This was the first ever live 4k video stream that happened between you on Earth, Sam, and Doctor Peggy Whitson, aboard the International Space Station. >> Sam: Yes. >> Wow. Tell us about that. >> It was truly amazing to be part of history and the amount of technology that came into play to make this possible. You know, sitting in the conference room in NAB in the middle of Las Vegas, seeing astronauts 250 miles ahead, going around the Earth, 17,000 miles an hour and a seamless, beautiful 4k picture. It was mind blowing. Hard to believe it's happened still. >> I can't even imagine. I'm getting goosebumps for you. Tell us some of the things that Dr. Whitson shared about her experiences. What was the interaction like? >> Well, Commander Whitson and Colonel Fisher was also in the interview and that guy is hilarious, by the way. >> Yeah, he is. >> He is hilarious. They talked about how advanced imaging technology really helps NASA perform experiments and bring experiments that are happening on the space station down to Earth for researchers to use that data and discover how the world works inside the universe. Some of the really interesting examples revolved around some experiments they showed. With thin film technology they had a very small, metallic structure that they could pull water out of and then corral that water, convert it into a spherical shape and in the 4k resolution, you could just see every element of that thin film in a way that looked like it was right next to us. I mean, it was transformative. >> Tracy: Yeah. >> I bet it was. Well, speaking of transformative, this was, I mentioned, a really historic event for a number of reasons. Obviously, for those of us on the ground, for AWS Elemental. But, Tracy, from your perspective, you've been in space for 188... I had it here somewhere, hours. >> Yeah, days. >> You've been on STS118, you've been on the Soyuz to the station on expeditions 23 and 24. What does this capability now mean in the life of an astronaut? >> I think what it does is it helps us bring the experience to everybody here on Earth. It is so hard to capture what we are not just seeing, but experiencing. The richness, the detail, the vividness of the colors and how they're changing are all a part of looking at our beautiful planet. And just from that alone, being able to bring that to the American people, the world, really, is, I think to me a great relief. Because it grieves me to think about how in the world I would describe this beautiful, magnificent view to everybody back home. >> I can imagine. You've done extra-vehicular space walks. >> Tracy: Yes. >> And I can imagine it's indescribable. >> It is. And from the fact you're looking at our planet from 250 miles above, you see the curvature of the Earth, you see it moving at a super high speed, you don't feel the wind in your face, but there's no doubt you're traveling very fast. Just the fact that you are out in the vacuum of space. If you could bring parts of that experience to people back home ... I'm excited to think about how that would transform just the way people think, not to mention the way that they act towards our planet. >> I also think inspiration ... We were talking before we went on that you were about 14 when the Challenger incident happened, we all kind of remember exactly where we were, and that really, a teacher being in space was so inspirational to you. Can you imagine shifting the conversation and what this technology is able to do inspiring the next generation of people that want to be the next Tracy Caldwell Dyson? >> Well, I think what the technology does today, especially in imaging capabilities, is it provides so much more detail than I could even describe. That a young person today watching that, and our generation today is so visual, that they're going to pick up on things that I wouldn't even think to describe to them. And it's going to capture their imagination in ways that are astounding. Compared to I, who, just the sheer knowledge of knowing there was a teacher that was going into space, propelled me to work really hard. I can only imagine what this generation's going to be capable of because of the images that we're bringing to them. >> It's so exciting. Sam, this is really kind of the tip of the iceberg. From AWS Elemental's perspective, first of all, you just had a rebrand. But what does this mean for the future of the video ecosystem? >> Well, I think it really shows you how the technology components came come together to create unbelievable pictures no matter where you are on the planet or in space. We had a live 4k encoder on the space station itself sending down signals to Johnson Space Center, then Johnson Space Center sending redundant links to Las Vegas, here, and the convention center. And then processing the video, the interview with Tracy, here in the space center-- or, here in NAB and then using the cloud to distribute that all over the world. So these 4k images, which take a significant amount of bandwidth, can be created in space, delivered here, produced and delivered anywhere in the world using the power of the cloud and advanced networking technology. And that's pretty amazing, when you think about it. >> Lisa: It really is. I don't think the three of us are smiling big enough. >> I know. It hurts! >> There's so much relief in this face. >> Lisa: I can imagine >> I bet. >> I absolutely can imagine, I think. One of the cool things about-- This is our first time at NAB with The Cube, but we're here: Media, entertainment, Hollywood. What this shows is this transcendence of technology to space. And there's so much interest in space. In fact, Tracy, you were an advisor to Jessica Chastain on "The Martian," which is probably pretty exciting. >> Oh, absolutely. It is. >> But just the transcendence of that and how this technology can be used to power things that everybody can understand, movies and things. But also the future of space exploration, which I can imagine, right now in the era of the space shuttle being retired now, depending on Soyuz rockets to get to the space station as the next vehicle is delivered, this must be quite inspirational for you as an astronaut, as not only is the next vehicle in development, but also, the exploration of Mars. In fact, you were just last month with President Trump. >> Tracy: Yes. >> As they signed a bill. What are your thoughts about that and how do you see imaging technology being an instrumental part of Mars exploration? >> In so many ways, but at the top is the momentum. Like you said, with Hollywood has captured space in some real endearing ways. And the images from NASA, from the human space flight program to Hubble to deep space, it is propelling ... it's momentum. And I think we need that momentum, especially with our young folks because they're going to be the ones, let's face it, who are going to be in the best condition to be on the planet of Mars. So, if we can continue to feed them the images as lifelike as we can, so that they feel they're there, I think we are heading in the right direction to actually being there. >> Wow, fantastic! Congratulations to both of you. Thank you both so much for joining us on The Cube. We can't wait to see what's next. >> Sam: Thank you so much. >> Tracy: Thank you. Thank you. >> Well, for Tracy and Sam, I'm Lisa Martin. You've been watching The Cube live from NAB 2017. Stick around, we'll be right back. (funky music)

>>Fly from Houston, Texas. It's the cube covering Grace Hopper celebration of women in computing. >>Welcome back to the cubes coverage of the Grace Hopper conference here in Houston, Texas. I am your host, Rebecca Knight. We have a great panel today. Uh, three distinguished guests, Jeanette Epps, an aerospace astronaut. Uh, an engineer at NASA, Mimi Valdez, a executive producer on the film, hidden figures and Christina DOJ who is a, I want to call her a rocket scientist. She will not let me, she's an electrical engineer at, at, at NASA. Thank you so much for joining me. Hey Jeanette. I want to start with you. Um, recently president Obama has said we're gonna put men on Mars, men and women, men and women on Mars. How realistic is that? I mean, it's exciting for the, for the rest of us, non astronauts to hear this is, is it realistic? >>It is realistic. And one of the things I love that he, he did that was that it gives a national initiative to go back to Mars. And so that means that people will get more involved in STEM careers, especially girls will get more involved. And it's kinda like, you know what JFK did back in the 60s to give us that push a goal, an end goal to do something. Great. >>And do you think that, you know, he said by 2030, it's not very long from now. I mean, is it going to happen? I mean, what's, >>well right now a witness is working on is we have the NASA Orion program and it's a, uh, a power light capsule that will be launched off of one of the largest rockets bigger than the Saturn five or as big. And so that the mission of NASA, Orion is to take us beyond low earth orbit and go deeper into space. So we're looking at NASA, Orion, potentially maybe being the ship that will go to Mars and you know, maybe we have more work to do, but all of getting the nation onboard with going to Mars will inspire a new generation to do great things that will help us to get to Mars. Even >>Obama has said he loves science as a kid. That was his favorite subject in school. And do you think that it will have this galvanizing effect of, as you said, making sure more little boys and girls are studying STEM? >>Well, I've seen it already with some of the tweets and different things, questions that kids ask me nowadays. I think every kid has in their heart this goal to go to Mars now. And um, I can't go to a conference or anywhere without, uh, some young child asking about Mars and what, what are, how are we going to get there? When are we going to get there? And you know, I think one of my jobs is to inspire them to get involved in STEM and help us to get to Mars. There's a lot of technology that we need to develop and produce so that we can get astronauts to live longer away from the earth surface. We have the propulsion system that can get them there faster and bring them back home long. Will it take, well, it depends on the propulsion system that we developed. So there's a number of things that we're working on to make sure that what president Obama has said will get us to Mars in the 2030s if it's pushed out to a little later, that's fine. We're working on it and we're, we're going forward with them. >>Mimi, I want to talk to you now about the film hidden figures. Uh, we'll be out in some theaters and Christmas wide release in January. It is the story of black women mathematicians working in the 1960s at NASA. How did you find out about this story? Well, I give credits at Donna gelato, one of the producers on the film who optioned the book when it was a book proposal. So before the book was even written, she optioned this the story, and it's just this amazing story that the world doesn't even know about. We all know about John Glenn's mission. He came back a national hero. It was a moment in history that galvanized the world. You know, America winning the space race. But we don't know the story of all these brilliant mathematicians, all these women who actually will really responsible Katherine Johnson specifically who hand calculated those numbers for his cause. >>Everybody, I mean, I think this is such an amazing thing to do. And, and again, we just don't know her story. And as well as Dorothy Vaughn and Mary Jackson, I mean, so many women that worked at NASA that were just, um, they were hidden. You just don't know their stories. So, so the film tells their story, it tells their, um, it tells what they did, how they helped John Glenn. Did John Glenn appreciate that John Glenn actually would not go into space unless Katherine double checked the numbers. Like he wanted her to actually, you know, he, he, he trusted her because this is when the IBM computers were first coming into NASA. So they had started asserted use that and he was like, Hmm, I, I need Catherine to check the numbers before I go into say they were friends, professional colleagues. I mean he just knew who, you know, obviously she, she was really responsible and sort of that whole mission. >>And, and you know, for him it was just sort of like, eh, these computers thing, this was like a new thing at NASA. He's like, I need a human to make sure that these numbers are right. Right. Yeah. So we're excited about the film. Who's in it? Taraji P Henson plays captain Johnson. Octavia Spencer, please. I'm Dorothy Vaughan and Janell Monae. Um, she's a, uh, a musician. This is sort of her first really big role and she plays Mary Jackson. Kevin Costner is the head of the space station. Um, we have really great actors, but I think what was really important to everyone who participated in the film was everyone understood the importance of the story and wanting to make sure that we got it right. And also, you know, movies are supposed to be entertaining, but when they can be also inspirational and educate in some way, the fact that some young girls somewhere may see this movie and decide to pursue a career in math or science or any of the STEM careers is really gratifying to us because that's what we would love to accomplish. >>You know, Christina, you have been at NASA for nine years. Uh, tell me about your style, how you got, how you got to NASA in the first place. So I've always loved space since I was like a young child. I was in fifth grade when I told my parents that I wanted to work for NASA. So really since that point, like that was, you know, my dream. And so I, you know, pursued the math and science. Those were some of my favorite subjects. Um, luckily I had some supportive parents who really like saw that desire in me and kind of nurtured and encouraged me to, Hey, if that's what you want to do, then you go for it. We'll do whatever we can. Um, and then I came across some NASA opportunities in high school. Um, and one of the programs was the high school aerospace scholars program. >>And in that program I kinda got a glimpse into what it was like to be an engineer, to work at NASA. I got to speak with, you know, fight directors and um, flight controllers. And there's so many people who contribute to the space program. And that experience really solidified my desire to pursue STEM, STEM. Um, so I started to electrical engineering and then from there, um, you know, did the internship at NASA and I've enjoyed my career so far. It's been a, it's been a great experience. And so you work on the jet propulsion system of spaceships. Um, I work Lena. Um, I work on the power systems power systems. So you are, what do you do? So, um, as an electrical engineer on power systems, I work on the design of the power system testing. Um, basically everything on the spacecraft is going to need power. >>So I'm responsible for how I need to provide power, how much, um, when we talk about going to Mars, that's a, that's a long duration mission and power is something that, um, you have to budget for. So we need to advance that technology to support these missions that, um, our administration has said we want to go there. How are y'all going to accomplish this? So there's a lot of um, design hands on work and it's, you know, it's a challenge. But I mean, together as a team, we can, I believe that will, you know, meet that goal and be able to deliver a power system that will take us to Mars. So this is a question for rip for really all of you. You're an astronaut, you were working at NASA, you just made a movie to encourage young women to, to, to, to get into the STEM field. Why is it NASA recruiting here at, at, at Grace Hopper and, and should it be, do not, do you want to take this? >>Well, that's a good question. It's not that I'm mass and I don't, it's not that I don't think NASA has a desire to recruit here. I think there's recruiting times where people come out and do that. But I think I'm, one of the things that we do in the astronaut Corps, we try to go out and attend conferences like that and try to inspire students to be interested in NASA to understand what NASA is doing, to understand, you know, the shuttle retired. But we're still flying. In fact, when I fly to space and hopefully in 2018 I'll fly with the Russians. But in the meantime, NASA's building two shadows that would take astronauts to the international space station and NASA, Orion, that'll take us deeper into space. So we want to try to inspire with our stories and get people interested in science, technology, engineering, mathematics, and now even the arts, the arts play a big part of this. The arts play a big part of the well, yeah, I think I'm as a scientist and looking at patterns and things like that, there's a lot of um, people who, um, begin to work in the arts, even if it's building things with their hands and making, sculpting things, painting things. And so there's a lot of artwork that comes into play in science that is >>really refreshing, exciting, count, counterintuitive. I mean, what would you say are the ways we've talked about getting them, getting them interested through, through film. Um, talking about, uh, Obama making this, this grand announcement and Treme, what are some other ways that we can get the next generation into this field? Well, representation is obviously important. I think when people get to see images in the media of these different fields and all the possibilities, I mean every kid on this planet is obsessed with their phone, maybe not realizing like the importance of these STEM careers that are making these phones even possible or even exist. And I think the more that we can expose these careers and all these possibilities, I think it will just be just more beneficial just for humanity in general. I mean, as we know, nothing in this world can exist without math. >>Nothing. So the more that we can sort of encourage young people to see what an incredible career this is in all the possibilities that go into it, I just think we'll be better off as a nation and as a, you know, just globally as a world. Jeanette, I mean, do you have any thoughts about how, what you would advise someone? I mean you started at NASA nine years ago. So I mean, as an engineer I feel like, I mean I am making some contribution, but really the way I feel like I have more impact is through mentoring and you know, participating in those outreach type of activities for, uh, younger students like K through 12. And then also, um, you know, undergraduate like where they're really like trying to figure out what are the career options and STEM. And so that's how I feel I can have an impact there. >>And these movies help because there's a surge of like, like it's inspirational for young students to see this and be like, Oh, I never knew that that was an option. And so we get outreached to NASA, um, our request to, you know, interact with, uh, local schools and communities and kind of, um, you know, do all my lessons or just teaching with them, just talking about kind of like what the career is like. So, um, I mean I hoping that I can contribute in that way for younger, younger people. Janette are, you are an impressive astronaut, but you are also known as a black woman astronaut. Yeah. D do you do, do you bristle at that or do you embrace it? What, what do you, how, what's the responsibility? >>Oh, I totally embrace it. You know, I'm young ladies always ask me, did you have a problem being a black woman and engineering? And I always tell them that, um, I don't have a problem with being a black woman. And if other people do, then that's their problem. I totally embrace it because I'm, one of the things that I didn't realize was that, um, there's still a need to have positive role models and images of yourself. You know, growing up, my mom never taught my twin sister and I that you couldn't do something because you are a female or Brown. But there are a lot of young ladies that actually do experience that. And so having a positive roam out of it, show them that, Hey look, if I can do this, you can do this too. There's no reason you shouldn't be doing this right now yourself. >>So you are a role model. And how do you then also make sure that it's active role modeling and not just sort of standing on a pedestal of. >>One of the things I like to do is like Catherine Johnson and these great ladies that, you know, without them I, you know, I wouldn't be here is you have to do well and you have to perform well. You have to do the same work that your colleagues are doing and don't do less and don't accept less either. And when it comes to the hard work, put in the time, do the work, complete the tasks and make sure you're, you're representing yourself and your group well and you don't want to be accounted as well. You know, she's the one that we've got to help and we've got to do this, but you want to be a contributing member to every group that you're a part of and completing the tasks, doing the same work if not better. I like to say do better work, but you know, you want to be a part of the. >>Yeah. But that puts so much pressure too because it is, it's, it's be a contributor, but also don't mess up because you are under a microscope to some degree because those are, >>you know, messing up isn't, isn't. Um, failure is never, um, should never be. If it's unintentional, that's okay because you always learn from your mistakes and you have to forgive yourself and keep moving forward. If you stop right there because of a failure, um, you wouldn't go anywhere. We all fell. And it's how you respond to it. That matters. >>Yeah. Every failure is an opportunity to learn. And I think, um, you know, yeah. You can't be scared. I mean, the first and foremost is just doing a good job that, cause once, if you're just dedicated and focused on that, then I think great things can happen. And then failure is really a, a buzzword in Silicon Valley too. Right now. It's a fail fast. Um, and this idea, as you were talking about that it's your response to failure that makes a difference. Yeah. And NASA, I became familiar with this famous phrase of failing forward, meaning that yes, you're going to encounter problems, but if you are learning from the, if you're making improvements, you can design something better. So we call it failing forward. And that concept has, I've embraced that comset and it's, you know, I've encountered many failures. I mean, designing new hardware. It's not gonna, you know, work right off the box. And I'm kind of embracing that idea that it's a learning experience. As long as you don't give up as if you're applying what you learned, then that is not a failure. Christina, this is great. Christina DOJ, Mimi Valdez, Jeanette Epps. Thank you so much for joining us today. This has been such a having to be here. I'm not worthy. Thank you. This has been Rebecca Knight live coverage of the Grace Hopper conference here in Houston, Texas. We'll be back after this break.

(upbeat music) >> We are back, approaching the finish line here at Supercomputing 22, our last interview of the day, our last interview of the show. And I have to say Dave Nicholson, my co-host, My name is Paul Gillin. I've been attending trade shows for 40 years Dave, I've never been to one like this. The type of people who are here, the type of problems they're solving, what they talk about, the trade shows are typically, they're so speeds and feeds. They're so financial, they're so ROI, they all sound the same after a while. This is truly a different event. Do you get that sense? >> A hundred percent. Now, I've been attending trade shows for 10 years since I was 19, in other words, so I don't have necessarily your depth. No, but seriously, Paul, totally, completely, completely different than any other conference. First of all, there's the absolute allure of looking at the latest and greatest, coolest stuff. I mean, when you have NASA lecturing on things when you have Lawrence Livermore Labs that we're going to be talking to here in a second it's a completely different story. You have all of the academics you have students who are in competition and also interviewing with organizations. It's phenomenal. I've had chills a lot this week. >> And I guess our last two guests sort of represent that cross section. Armando Acosta, director of HPC Solutions, High Performance Solutions at Dell. And Matt Leininger, who is the HPC Strategist at Lawrence Livermore National Laboratory. Now, there is perhaps, I don't know you can correct me on this, but perhaps no institution in the world that uses more computing cycles than Lawrence Livermore National Laboratory and is always on the leading edge of what's going on in Supercomputing. And so we want to talk to both of you about that. Thank you. Thank you for joining us today. >> Sure, glad to be here. >> For having us. >> Let's start with you, Armando. Well, let's talk about the juxtaposition of the two of you. I would not have thought of LLNL as being a Dell reference account in the past. Tell us about the background of your relationship and what you're providing to the laboratory. >> Yeah, so we're really excited to be working with Lawrence Livermore, working with Matt. But actually this process started about two years ago. So we started looking at essentially what was coming down the pipeline. You know, what were the customer requirements. What did we need in order to make Matt successful. And so the beauty of this project is that we've been talking about this for two years, and now it's finally coming to fruition. And now we're actually delivering systems and delivering racks of systems. But what I really appreciate is Matt coming to us, us working together for two years and really trying to understand what are the requirements, what's the schedule, what do we need to hit in order to make them successful >> At Lawrence Livermore, what drives your computing requirements I guess? You're working on some very, very big problems but a lot of very complex problems. How do you decide what you need to procure to address them? >> Well, that's a difficult challenge. I mean, our mission is a national security mission dealing with making sure that we do our part to provide the high performance computing capabilities to the US Department of Energy's National Nuclear Security Administration. We do that through the Advanced Simulation computing program. Its goal is to provide that computing power to make sure that the US nuclear rep of the stockpile is safe, secure, and effective. So how we go about doing that? There's a lot of work involved. We have multiple platform lines that we accomplish that goal with. One of them is the advanced technology systems. Those are the ones you've heard about a lot, they're pushing towards exit scale, the GPU technologies incorporated into those. We also have a second line, a platform line, called the Commodity Technology Systems. That's where right now we're partnering with Dell on the latest generation of those. Those systems are a little more conservative, they're right now CPU only driven but they're also intended to be the everyday work horses. So those are the first systems our users get on. It's very easy for them to get their applications up and running. They're the first things they use usually on a day to day basis. They run a lot of small to medium size jobs that you need to do to figure out how to most effectively use what workloads you need to move to the even larger systems to accomplish our mission goals. >> The workhorses. >> Yeah. >> What have you seen here these last few days of the show, what excites you? What are the most interesting things you've seen? >> There's all kinds of things that are interesting. Probably most interesting ones I can't talk about in public, unfortunately, 'cause of NDA agreements, of course. But it's always exciting to be here at Supercomputing. It's always exciting to see the products that we've been working with industry and co-designing with them on for, you know, several years before the public actually sees them. That's always an exciting part of the conference as well specifically with CTS-2, it's exciting. As was mentioned before, I've been working with Dell for nearly two years on this, but the systems first started being delivered this past August. And so we're just taking the initial deliveries of those. We've deployed, you know, roughly about 1600 nodes now but that'll ramp up to over 6,000 nodes over the next three or four months. >> So how does this work intersect with Sandia and Los Alamos? Explain to us the relationship there. >> Right, so those three laboratories are the laboratories under the National Nuclear Security Administration. We partner together on CTS. So the architectures, as you were asking, how do we define these things, it's the labs coming together. Those three laboratories we define what we need for that architecture. We have a joint procurement that is run out of Livermore but then the systems are deployed at all three laboratories. And then they serve the programs that I mentioned for each laboratory as well. >> I've worked in this space for a very long time you know I've worked with agencies where the closest I got to anything they were actually doing was the sort of guest suite outside the secure area. And sometimes there are challenges when you're communicating, it's like you have a partner like Dell who has all of these things to offer, all of these ideas. You have requirements, but maybe you can't share 100% of what you need to do. How do you navigate that? Who makes the decision about what can be revealed in these conversations? You talk about NDA in terms of what's been shared with you, you may be limited in terms of what you can share with vendors. Does that cause inefficiency? >> To some degree. I mean, we do a good job within the NSA of understanding what our applications need and then mapping that to technical requirements that we can talk about with vendors. We also have kind of in between that we've done this for many years. A recent example is of course with the exit scale computing program and some things it's doing creating proxy apps or mini apps that are smaller versions of some of the things that we are important to us. Some application areas are important to us, hydrodynamics, material science, things like that. And so we can collaborate with vendors on those proxy apps to co-design systems and tweak the architectures. In fact, we've done a little bit that with CTS-2, not as much in CTS as maybe in the ATS platforms but that kind of general idea of how we collaborate through these proxy applications is something we've used across platforms. >> Now is Dell one of your co-design partners? >> In CTS-2 absolutely, yep. >> And how, what aspects of CTS-2 are you working on with Dell? >> Well, the architecture itself was the first, you know thing we worked with them on, we had a procurement come out, you know they bid an architecture on that. We had worked with them, you know but previously on our requirements, understanding what our requirements are. But that architecture today is based on the fourth generation Intel Xeon that you've heard a lot about at the conference. We are one of the first customers to get those systems in. All the systems are interconnected together with the Cornell Network's Omni-Path Network that we've used before and are very excited about as well. And we build up from there. The systems get integrated in by the operations teams at the laboratory. They get integrated into our production computing environment. Dell is really responsible, you know for designing these systems and delivering to the laboratories. The laboratories then work with Dell. We have a software stack that we provide on top of that called TOSS, for Tri-Lab Operating System. It's based on Redhead Enterprise Linux. But the goal there is that it allows us, a common user environment, a common simulation environment across not only CTS-2, but maybe older systems we have and even the larger systems that we'll be deploying as well. So from a user perspective they see a common user interface, a common environment across all the different platforms that they use at Livermore and the other laboratories. >> And Armando, what does Dell get out of the co-design arrangement with the lab? >> Well, we get to make sure that they're successful. But the other big thing that we want to do, is typically when you think about Dell and HPC, a lot of people don't make that connection together. And so what we're trying to do is make sure that, you know they know that, hey, whether you're a work group customer at the smallest end or a super computer customer at the highest end, Dell wants to make sure that we have the right setup portfolio to match any needs across this. But what we were really excited about this, this is kind of our, you know big CTS-2 first thing we've done together. And so, you know, hopefully this has been successful. We've made Matt happy and we look forward to the future what we can do with bigger and bigger things. >> So will the labs be okay with Dell coming up with a marketing campaign that said something like, "We can't confirm that alien technology is being reverse engineered." >> Yeah, that would fly. >> I mean that would be right, right? And I have to ask you the question directly and the way you can answer it is by smiling like you're thinking, what a stupid question. Are you reverse engineering alien technology at the labs? >> Yeah, you'd have to suck the PR office. >> Okay, okay. (all laughing) >> Good answer. >> No, but it is fascinating because to a degree it's like you could say, yeah, we're working together but if you really want to dig into it, it's like, "Well I kind of can't tell you exactly how some of this stuff is." Do you consider anything that you do from a technology perspective, not what you're doing with it, but the actual stack, do you try to design proprietary things into the stack or do you say, "No, no, no, we're going to go with standards and then what we do with it is proprietary and secret."? >> Yeah, it's more the latter. >> Is the latter? Yeah, yeah, yeah. So you're not going to try to reverse engineer the industry? >> No, no. We want the solutions that we develop to enhance the industry to be able to apply to a broader market so that we can, you know, gain from the volume of that market, the lower cost that they would enable, right? If we go off and develop more and more customized solutions that can be extraordinarily expensive. And so we we're really looking to leverage the wider market, but do what we can to influence that, to develop key technologies that we and others need that can enable us in the high forms computing space. >> We were talking with Satish Iyer from Dell earlier about validated designs, Dell's reference designs for for pharma and for manufacturing, in HPC are you seeing that HPC, Armando, and is coming together traditionally and more of an academic research discipline beginning to come together with commercial applications? And are these two markets beginning to blend? >> Yeah, I mean so here's what's happening, is you have this convergence of HPC, AI and data analytics. And so when you have that combination of those three workloads they're applicable across many vertical markets, right? Whether it's financial services, whether it's life science, government and research. But what's interesting, and Matt won't brag about, but a lot of stuff that happens in the DoE labs trickles down to the enterprise space, trickles down to the commercial space because these guys know how to do it at scale, they know how to do it efficiently and they know how to hit the mark. And so a lot of customers say, "Hey we want what CTS-2 does," right? And so it's very interesting. The way I love it is their process the way they do the RFP process. Matt talked about the benchmarks and helping us understand, hey here's kind of the mark you have to hit. And then at the same time, you know if we make them successful then obviously it's better for all of us, right? You know, I want to secure nuclear stock pile so I hope everybody else does as well. >> The software stack you mentioned, I think Tia? >> TOSS. >> TOSS. >> Yeah. >> How did that come about? Why did you feel the need to develop your own software stack? >> It originated back, you know, even 20 years ago when we first started building Linux clusters when that was a crazy idea. Livermore and other laboratories were really the first to start doing that and then push them to larger and larger scales. And it was key to have Linux running on that at the time. And so we had the. >> So 20 years ago you knew you wanted to run on Linux? >> Was 20 years ago, yeah, yeah. And we started doing that but we needed a way to have a version of Linux that we could partner with someone on that would do, you know, the support, you know, just like you get from an EoS vendor, right? Security support and other things. But then layer on top of that, all the HPC stuff you need either to run the system, to set up the system, to support our user base. And that evolved into to TOSS which is the Tri-Lab Operating System. Now it's based on the latest version of Redhead Enterprise Linux, as I mentioned before, with all the other HPC magic, so to speak and all that HPC magic is open source things. It's not stuff, it may be things that we develop but it's nothing closed source. So all that's there we run it across all these different environments as I mentioned before. And it really originated back in the early days of, you know, Beowulf clusters, Linux clusters, as just needing something that we can use to run on multiple systems and start creating that common environment at Livermore and then eventually the other laboratories. >> How is a company like Dell, able to benefit from the open source work that's coming out of the labs? >> Well, when you look at the open source, I mean open source is good for everybody, right? Because if you make a open source tool available then people start essentially using that tool. And so if we can make that open source tool more robust and get more people using it, it gets more enterprise ready. And so with that, you know, we're all about open source we're all about standards and really about raising all boats 'cause that's what open source is all about. >> And with that, we are out of time. This is our 28th interview of SC22 and you're taking us out on a high note. Armando Acosta, director of HPC Solutions at Dell. Matt Leininger, HPC Strategist, Lawrence Livermore National Laboratories. Great discussion. Hopefully it was a good show for you. Fascinating show for us and thanks for being with us today. >> Thank you very much. >> Thank you for having us >> Dave it's been a pleasure. >> Absolutely. >> Hope we'll be back next year. >> Can't believe, went by fast. Absolutely at SC23. >> We hope you'll be back next year. This is Paul Gillin. That's a wrap, with Dave Nicholson for theCUBE. See here in next time. (soft upbear music)

>>We're back at Super Computing, 22 in Dallas, winding down the final day here. A big show floor behind me. Lots of excitement out there, wouldn't you say, Dave? Just >>Oh, it's crazy. I mean, any, any time you have NASA presentations going on and, and steampunk iterations of cooling systems that the, you know, it's, it's >>The greatest. I've been to hundreds of trade shows. I don't think I've ever seen NASA exhibiting at one like they are here. Dave Nicholson, my co-host. I'm Paul Gell, in which with us is Satish Ier. He is the vice president of emerging services at Dell Technologies and Satit, thanks for joining us on the cube. >>Thank you. Paul, >>What are emerging services? >>Emerging services are actually the growth areas for Dell. So it's telecom, it's cloud, it's edge. So we, we especially focus on all the growth vectors for, for the companies. >>And, and one of the key areas that comes under your jurisdiction is called apex. Now I'm sure there are people who don't know what Apex is. Can you just give us a quick definition? >>Absolutely. So Apex is actually Dells for a into cloud, and I manage the Apex services business. So this is our way of actually bringing cloud experience to our customers, OnPrem and in color. >>But, but it's not a cloud. I mean, you don't, you don't have a Dell cloud, right? It's, it's of infrastructure as >>A service. It's infrastructure and platform and solutions as a service. Yes, we don't have our own e of a public cloud, but we want to, you know, this is a multi-cloud world, so technically customers want to consume where they want to consume. So this is Dell's way of actually, you know, supporting a multi-cloud strategy for our customers. >>You, you mentioned something just ahead of us going on air. A great way to describe Apex, to contrast Apex with CapEx. There's no c there's no cash up front necessary. Yeah, I thought that was great. Explain that, explain that a little more. Well, >>I mean, you know, one, one of the main things about cloud is the consumption model, right? So customers would like to pay for what they consume, they would like to pay in a subscription. They would like to not prepay CapEx ahead of time. They want that economic option, right? So I think that's one of the key tenets for anything in cloud. So I think it's important for us to recognize that and think Apex is basically a way by which customers pay for what they consume, right? So that's a absolutely a key tenant for how, how we want to design Apex. So it's absolutely right. >>And, and among those services are high performance computing services. Now I was not familiar with that as an offering in the Apex line. What constitutes a high performance computing Apex service? >>Yeah, I mean, you know, I mean, this conference is great, like you said, you know, I, there's so many HPC and high performance computing folks here, but one of the things is, you know, fundamentally, if you look at high performance computing ecosystem, it is quite complex, right? And when you call it as an Apex HPC or Apex offering offer, it brings a lot of the cloud economics and cloud, you know, experience to the HPC offer. So fundamentally, it's about our ability for customers to pay for what they consume. It's where Dell takes a lot of the day to day management of the infrastructure on our own so that customers don't need to do the grunge work of managing it, and they can really focus on the actual workload, which actually they run on the CHPC ecosystem. So it, it is, it is high performance computing offer, but instead of them buying the infrastructure, running all of that by themself, we make it super easy for customers to consume and manage it across, you know, proven designs, which Dell always implements across these verticals. >>So what, what makes the high performance computing offering as opposed to, to a rack of powered servers? What do you add in to make it >>Hpc? Ah, that's a great question. So, I mean, you know, so this is a platform, right? So we are not just selling infrastructure by the drink. So we actually are fundamentally, it's based on, you know, we, we, we launch two validated designs, one for life science sales, one for manufacturing. So we actually know how these PPO work together, how they actually are validated design tested solution. And we also, it's a platform. So we actually integrate the softwares on the top. So it's just not the infrastructure. So we actually integrate a cluster manager, we integrate a job scheduler, we integrate a contained orchestration layer. So a lot of these things, customers have to do it by themself, right? If they're buy the infrastructure. So by basically we are actually giving a platform or an ecosystem for our customers to run their workloads. So make it easy for them to actually consume those. >>That's Now is this, is this available on premises for customer? >>Yeah, so we, we, we make it available customers both ways. So we make it available OnPrem for customers who want to, you know, kind of, they want to take that, take that economics. We also make it available in a colo environment if the customers want to actually, you know, extend colo as that OnPrem environment. So we do both. >>What are, what are the requirements for a customer before you roll that equipment in? How do they sort of have to set the groundwork for, >>For Well, I think, you know, fundamentally it starts off with what the actual use case is, right? So, so if you really look at, you know, the two validated designs we talked about, you know, one for, you know, healthcare life sciences, and one other one for manufacturing, they do have fundamentally different requirements in terms of what you need from those infrastructure systems. So, you know, the customers initially figure out, okay, how do they actually require something which is going to require a lot of memory intensive loads, or do they actually require something which has got a lot of compute power. So, you know, it all depends on what they would require in terms of the workloads to be, and then we do havet sizing. So we do have small, medium, large, we have, you know, multiple infrastructure options, CPU core options. Sometimes the customer would also wanna say, you know what, as long as the regular CPUs, I also want some GPU power on top of that. So those are determinations typically a customer makes as part of the ecosystem, right? And so those are things which would, they would talk to us about to say, okay, what is my best option in terms of, you know, kind of workloads I wanna run? And then they can make a determination in terms of how, how they would actually going. >>So this, this is probably a particularly interesting time to be looking at something like HPC via Apex with, with this season of Rolling Thunder from various partners that you have, you know? Yep. We're, we're all expecting that Intel is gonna be rolling out new CPU sets from a powered perspective. You have your 16th generation of PowerEdge servers coming out, P C I E, gen five, and all of the components from partners like Invidia and Broadcom, et cetera, plugging into them. Yep. What, what does that, what does that look like from your, from your perch in terms of talking to customers who maybe, maybe they're doing things traditionally and they're likely to be not, not fif not 15 G, not generation 15 servers. Yeah. But probably more like 14. Yeah, you're offering a pretty huge uplift. Yep. What, what do those conversations look >>Like? I mean, customers, so talking about partners, right? I mean, of course Dell, you know, we, we, we don't bring any solutions to the market without really working with all of our partners, whether that's at the infrastructure level, like you talked about, you know, Intel, amd, Broadcom, right? All the chip vendors, all the way to software layer, right? So we have cluster managers, we have communities orchestrators. So we usually what we do is we bring the best in class, whether it's a software player or a hardware player, right? And we bring it together as a solution. So we do give the customers a choice, and the customers always want to pick what you they know actually is awesome, right? So they that, that we actually do that. And, you know, and one of the main aspects of, especially when you talk about these things, bringing it as a service, right? >>We take a lot of guesswork away from our customer, right? You know, one of the good example of HPC is capacity, right? So customers, these are very, you know, I would say very intensive systems. Very complex systems, right? So customers would like to buy certain amount of capacity, they would like to grow and, you know, come back, right? So give, giving them the flexibility to actually consume more if they want, giving them the buffer and coming down. All of those things are very important as we actually design these things, right? And that takes some, you know, customers are given a choice, but it actually, they don't need to worry about, oh, you know, what happens if I actually have a spike, right? There's already buffer capacity built in. So those are awesome things. When we talk about things as a service, >>When customers are doing their ROI analysis, buying CapEx on-prem versus, versus using Apex, is there a point, is there a crossover point typically at which it's probably a better deal for them to, to go OnPrem? >>Yeah, I mean, it it like specifically talking about hpc, right? I mean, why, you know, we do have a ma no, a lot of customers consume high performance compute and public cloud, right? That's not gonna go away, right? But there are certain reasons why they would look at OnPrem or they would look at, for example, Ola environment, right? One of the main reasons they would like to do that is purely have to do with cost, right? These are pretty expensive systems, right? There is a lot of ingress, egress, there is a lot of data going back and forth, right? Public cloud, you know, it costs money to put data in or actually pull data back, right? And the second one is data residency and security requirements, right? A lot of these things are probably proprietary set of information. We talked about life sciences, there's a lot of research, right? >>Manufacturing, a lot of these things are just, just in time decision making, right? You are on a factory floor, you gotta be able to do that. Now there is a latency requirement. So I mean, I think a lot of things play, you know, plays into this outside of just cost, but data residency requirements, ingress, egress are big things. And when you're talking about mass moments of data you wanna put and pull it back in, they would like to kind of keep it close, keep it local, and you know, get a, get a, get a price >>Point. Nevertheless, I mean, we were just talking to Ian Coley from aws and he was talking about how customers have the need to sort of move workloads back and forth between the cloud and on-prem. That's something that they're addressing without posts. You are very much in the, in the on-prem world. Do you have, or will you have facilities for customers to move workloads back and forth? Yeah, >>I wouldn't, I wouldn't necessarily say, you know, Dell's cloud strategy is multi-cloud, right? So we basically, so it kind of falls into three, I mean we, some customers, some workloads are suited always for public cloud. It's easier to consume, right? There are, you know, customers also consume on-prem, the customers also consuming Kohler. And we also have like Dell's amazing piece of software like storage software. You know, we make some of these things available for customers to consume a software IP on their public cloud, right? So, you know, so this is our multi-cloud strategy. So we announced a project in Alpine, in Delta fold. So you know, if you look at those, basically customers are saying, I love your Dell IP on this, on this product, on the storage, can you make it available through, in this public environment, whether, you know, it's any of the hyper skill players. So if we do all of that, right? So I think it's, it shows that, you know, it's not always tied to an infrastructure, right? Customers want to consume the best thumb and if we need to be consumed in hyperscale, we can make it available. >>Do you support containers? >>Yeah, we do support containers on hpc. We have, we have two container orchestrators we have to support. We, we, we have aner similarity, we also have a container options to customers. Both options. >>What kind of customers are you signing up for the, for the HPC offerings? Are they university research centers or is it tend to be smaller >>Companies? It, it's, it's, you know, the last three days, this conference has been great. We probably had like, you know, many, many customers talking to us. But HC somewhere in the range of 40, 50 customers, I would probably say lot of interest from educational institutions, universities research, to your point, a lot of interest from manufacturing, factory floor automation. A lot of customers want to do dynamic simulations on factory floor. That is also quite a bit of interest from life sciences pharmacies because you know, like I said, we have two designs, one on life sciences, one on manufacturing, both with different dynamics on the infrastructure. So yeah, quite a, quite a few interest definitely from academics, from life sciences, manufacturing. We also have a lot of financials, big banks, you know, who wants to simulate a lot of the, you know, brokerage, a lot of, lot of financial data because we have some, you know, really optimized hardware we announced in Dell for, especially for financial services. So there's quite a bit of interest from financial services as well. >>That's why that was great. We often think of Dell as, as the organization that democratizes all things in it eventually. And, and, and, and in that context, you know, this is super computing 22 HPC is like the little sibling trailing around, trailing behind the super computing trend. But we definitely have seen this move out of just purely academia into the business world. Dell is clearly a leader in that space. How has Apex overall been doing since you rolled out that strategy, what, two couple? It's been, it's been a couple years now, hasn't it? >>Yeah, it's been less than two years. >>How are, how are, how are mainstream Dell customers embracing Apex versus the traditional, you know, maybe 18 months to three year upgrade cycle CapEx? Yeah, >>I mean I look, I, I think that is absolutely strong momentum for Apex and like we, Paul pointed out earlier, we started with, you know, making the infrastructure and the platforms available to customers to consume as a service, right? We have options for customers, you know, to where Dell can fully manage everything end to end, take a lot of the pain points away, like we talked about because you know, managing a cloud scale, you know, basically environment for the customers, we also have options where customers would say, you know what, I actually have a pretty sophisticated IT organization. I want Dell to manage the infrastructure, but up to this level in the layer up to the guest operating system, I'll take care of the rest, right? So we are seeing customers who are coming to us with various requirements in terms of saying, I can do up to here, but you take all of this pain point away from me or you do everything for me. >>It all depends on the customer. So we do have wide interest. So our, I would say our products and the portfolio set in Apex is expanding and we are also learning, right? We are getting a lot of feedback from customers in terms of what they would like to see on some of these offers. Like the example we just talked about in terms of making some of the software IP available on a public cloud where they'll look at Dell as a software player, right? That's also is absolutely critical. So I think we are giving customers a lot of choices. Our, I would say the choice factor and you know, we are democratizing, like you said, expanding in terms of the customer choices. And I >>Think it's, we're almost outta our time, but I do wanna be sure we get to Dell validated designs, which you've mentioned a couple of times. How specific are the, well, what's the purpose of these designs? How specific are they? >>They, they are, I mean I, you know, so the most of these valid, I mean, again, we look at these industries, right? And we look at understanding exactly how would, I mean we have huge embedded base of customers utilizing HPC across our ecosystem in Dell, right? So a lot of them are CapEx customers. We actually do have an active customer profile. So these validated designs takes into account a lot of customer feedback, lot of partner feedback in terms of how they utilize this. And when you build these solutions, which are kind of end to end and integrated, you need to start anchoring on something, right? And a lot of these things have different characteristics. So these validated design basically prove to us that, you know, it gives a very good jump off point for customers. That's the way I look at it, right? So a lot of them will come to the table with, they don't come to the blank sheet of paper when they say, oh, you know what I'm, this, this is my characteristics of what I want. I think this is a great point for me to start from, right? So I think that that gives that, and plus it's the power of validation, really, right? We test, validate, integrate, so they know it works, right? So all of those are hypercritical. When you talk to, >>And you mentioned healthcare, you, you mentioned manufacturing, other design >>Factoring. We just announced validated design for financial services as well, I think a couple of days ago in the event. So yep, we are expanding all those DVDs so that we, we can, we can give our customers a choice. >>We're out of time. Sat ier. Thank you so much for joining us. Thank you. At the center of the move to subscription to everything as a service, everything is on a subscription basis. You really are on the leading edge of where, where your industry is going. Thanks for joining us. >>Thank you, Paul. Thank you Dave. >>Paul Gillum with Dave Nicholson here from Supercomputing 22 in Dallas, wrapping up the show this afternoon and stay with us for, they'll be half more soon.

>>Welcome back to The Cube's coverage of Supercomputing Conference 2022, otherwise known as SC 22 here in Dallas, Texas. This is day three of our coverage, the final day of coverage here on the exhibition floor. I'm Dave Nicholson, and I'm here with my co-host, tech journalist extraordinaire, Paul Gillum. How's it going, >>Paul? Hi, Dave. It's going good. >>And we have a wonderful guest with us this morning, Dr. Panda from the Ohio State University. Welcome Dr. Panda to the Cube. >>Thanks a lot. Thanks a lot to >>Paul. I know you're, you're chopping at >>The bit, you have incredible credentials, over 500 papers published. The, the impact that you've had on HPC is truly remarkable. But I wanted to talk to you specifically about a product project you've been working on for over 20 years now called mva, high Performance Computing platform that's used by more than 32 organ, 3,200 organizations across 90 countries. You've shepherded this from, its, its infancy. What is the vision for what MVA will be and and how is it a proof of concept that others can learn from? >>Yeah, Paul, that's a great question to start with. I mean, I, I started with this conference in 2001. That was the first time I came. It's very coincidental. If you remember the Finman Networking Technology, it was introduced in October of 2000. Okay. So in my group, we were working on NPI for Marinette Quadrics. Those are the old technology, if you can recollect when Finman was there, we were the very first one in the world to really jump in. Nobody knew how to use Infin van in an HPC system. So that's how the Happy Project was born. And in fact, in super computing 2002 on this exhibition floor in Baltimore, we had the first demonstration, the open source happy, actually is running on an eight node infinite van clusters, eight no zeros. And that was a big challenge. But now over the years, I means we have continuously worked with all infinite van vendors, MPI Forum. >>We are a member of the MPI Forum and also all other network interconnect. So we have steadily evolved this project over the last 21 years. I'm very proud of my team members working nonstop, continuously bringing not only performance, but scalability. If you see now INFIN event are being deployed in 8,000, 10,000 node clusters, and many of these clusters actually use our software, stack them rapid. So, so we have done a lot of, like our focuses, like we first do research because we are in academia. We come up with good designs, we publish, and in six to nine months, we actually bring it to the open source version and people can just download and then use it. And that's how currently it's been used by more than 3000 orange in 90 countries. And, but the interesting thing is happening, your second part of the question. Now, as you know, the field is moving into not just hvc, but ai, big data, and we have those support. This is where like we look at the vision for the next 20 years, we want to design this MPI library so that not only HPC but also all other workloads can take advantage of it. >>Oh, we have seen libraries that become a critical develop platform supporting ai, TensorFlow, and, and the pie torch and, and the emergence of, of, of some sort of default languages that are, that are driving the community. How, how important are these frameworks to the, the development of the progress making progress in the HPC world? >>Yeah, no, those are great. I mean, spite our stencil flow, I mean, those are the, the now the bread and butter of deep learning machine learning. Am I right? But the challenge is that people use these frameworks, but continuously models are becoming larger. You need very first turnaround time. So how do you train faster? How do you do influencing faster? So this is where HPC comes in and what exactly what we have done is actually we have linked floor fighters to our happy page because now you see the MPI library is running on a million core system. Now your fighters and tenor four clan also be scaled to to, to those number of, large number of course and gps. So we have actually done that kind of a tight coupling and that helps the research to really take advantage of hpc. >>So if, if a high school student is thinking in terms of interesting computer science, looking for a place, looking for a university, Ohio State University, bruns, world renowned, widely known, but talk about what that looks like from a day on a day to day basis in terms of the opportunity for undergrad and graduate students to participate in, in the kind of work that you do. What is, what does that look like? And is, and is that, and is that a good pitch to for, for people to consider the university? >>Yes. I mean, we continuously, from a university perspective, by the way, the Ohio State University is one of the largest single campus in, in us, one of the top three, top four. We have 65,000 students. Wow. It's one of the very largest campus. And especially within computer science where I am located, high performance computing is a very big focus. And we are one of the, again, the top schools all over the world for high performance computing. And we also have very strength in ai. So we always encourage, like the new students who like to really work on top of the art solutions, get exposed to the concepts, principles, and also practice. Okay. So, so we encourage those people that wish you can really bring you those kind of experience. And many of my past students, staff, they're all in top companies now, have become all big managers. >>How, how long, how long did you say you've been >>At 31 >>Years? 31 years. 31 years. So, so you, you've had people who weren't alive when you were already doing this stuff? That's correct. They then were born. Yes. They then grew up, yes. Went to university graduate school, and now they're on, >>Now they're in many top companies, national labs, all over the universities, all over the world. So they have been trained very well. Well, >>You've, you've touched a lot of lives, sir. >>Yes, thank you. Thank >>You. We've seen really a, a burgeoning of AI specific hardware emerge over the last five years or so. And, and architectures going beyond just CPUs and GPUs, but to Asics and f PGAs and, and accelerators, does this excite you? I mean, are there innovations that you're seeing in this area that you think have, have great promise? >>Yeah, there is a lot of promise. I think every time you see now supercomputing technology, you see there is sometime a big barrier comes barrier jump. Rather I'll say, new technology comes some disruptive technology, then you move to the next level. So that's what we are seeing now. A lot of these AI chips and AI systems are coming up, which takes you to the next level. But the bigger challenge is whether it is cost effective or not, can that be sustained longer? And this is where commodity technology comes in, which commodity technology tries to take you far longer. So we might see like all these likes, Gaudi, a lot of new chips are coming up, can they really bring down the cost? If that cost can be reduced, you will see a much more bigger push for AI solutions, which are cost effective. >>What, what about on the interconnect side of things, obvi, you, you, your, your start sort of coincided with the initial standards for Infin band, you know, Intel was very, very, was really big in that, in that architecture originally. Do you see interconnects like RDMA over converged ethernet playing a part in that sort of democratization or commoditization of things? Yes. Yes. What, what are your thoughts >>There for internet? No, this is a great thing. So, so we saw the infinite man coming. Of course, infinite Man is, commod is available. But then over the years people have been trying to see how those RDMA mechanisms can be used for ethernet. And then Rocky has been born. So Rocky has been also being deployed. But besides these, I mean now you talk about Slingshot, the gray slingshot, it is also an ethernet based systems. And a lot of those RMA principles are actually being used under the hood. Okay. So any modern networks you see, whether it is a Infin and Rocky Links art network, rock board network, you name any of these networks, they are using all the very latest principles. And of course everybody wants to make it commodity. And this is what you see on the, on the slow floor. Everybody's trying to compete against each other to give you the best performance with the lowest cost, and we'll see whoever wins over the years. >>Sort of a macroeconomic question, Japan, the US and China have been leapfrogging each other for a number of years in terms of the fastest supercomputer performance. How important do you think it is for the US to maintain leadership in this area? >>Big, big thing, significantly, right? We are saying that I think for the last five to seven years, I think we lost that lead. But now with the frontier being the number one, starting from the June ranking, I think we are getting that leadership back. And I think it is very critical not only for fundamental research, but for national security trying to really move the US to the leading edge. So I hope us will continue to lead the trend for the next few years until another new system comes out. >>And one of the gating factors, there is a shortage of people with data science skills. Obviously you're doing what you can at the university level. What do you think can change at the secondary school level to prepare students better to, for data science careers? >>Yeah, I mean that is also very important. I mean, we, we always call like a pipeline, you know, that means when PhD levels we are expecting like this even we want to students to get exposed to, to, to many of these concerts from the high school level. And, and things are actually changing. I mean, these days I see a lot of high school students, they, they know Python, how to program in Python, how to program in sea object oriented things. Even they're being exposed to AI at that level. So I think that is a very healthy sign. And in fact we, even from Ohio State side, we are always engaged with all this K to 12 in many different programs and then gradually trying to take them to the next level. And I think we need to accelerate also that in a very significant manner because we need those kind of a workforce. It is not just like a building a system number one, but how do we really utilize it? How do we utilize that science? How do we propagate that to the community? Then we need all these trained personal. So in fact in my group, we are also involved in a lot of cyber training activities for HPC professionals. So in fact, today there is a bar at 1 1 15 I, yeah, I think 1215 to one 15. We'll be talking more about that. >>About education. >>Yeah. Cyber training, how do we do for professionals? So we had a funding together with my co-pi, Dr. Karen Tom Cook from Ohio Super Center. We have a grant from NASA Science Foundation to really educate HPT professionals about cyber infrastructure and ai. Even though they work on some of these things, they don't have the complete knowledge. They don't get the time to, to learn. And the field is moving so fast. So this is how it has been. We got the initial funding, and in fact, the first time we advertised in 24 hours, we got 120 application, 24 hours. We couldn't even take all of them. So, so we are trying to offer that in multiple phases. So, so there is a big need for those kind of training sessions to take place. I also offer a lot of tutorials at all. Different conference. We had a high performance networking tutorial. Here we have a high performance deep learning tutorial, high performance, big data tutorial. So I've been offering tutorials at, even at this conference since 2001. Good. So, >>So in the last 31 years, the Ohio State University, as my friends remind me, it is properly >>Called, >>You've seen the world get a lot smaller. Yes. Because 31 years ago, Ohio, in this, you know, of roughly in the, in the middle of North America and the United States was not as connected as it was to everywhere else in the globe. So that's, that's pro that's, I i it kind of boggles the mind when you think of that progression over 31 years, but globally, and we talk about the world getting smaller, we're sort of in the thick of, of the celebratory seasons where, where many, many groups of people exchange gifts for varieties of reasons. If I were to offer you a holiday gift, that is the result of what AI can deliver the world. Yes. What would that be? What would, what would, what would the first thing be? This is, this is, this is like, it's, it's like the genie, but you only get one wish. >>I know, I know. >>So what would the first one be? >>Yeah, it's very hard to answer one way, but let me bring a little bit different context and I can answer this. I, I talked about the happy project and all, but recently last year actually we got awarded an S f I institute award. It's a 20 million award. I am the overall pi, but there are 14 universities involved. >>And who is that in that institute? >>What does that Oh, the I ici. C e. Okay. I cycle. You can just do I cycle.ai. Okay. And that lies with what exactly what you are trying to do, how to bring lot of AI for masses, democratizing ai. That's what is the overall goal of this, this institute, think of like a, we have three verticals we are working think of like one is digital agriculture. So I'll be, that will be my like the first ways. How do you take HPC and AI to agriculture the world as though we just crossed 8 billion people. Yeah, that's right. We need continuous food and food security. How do we grow food with the lowest cost and with the highest yield? >>Water >>Consumption. Water consumption. Can we minimize or minimize the water consumption or the fertilization? Don't do blindly. Technologies are out there. Like, let's say there is a weak field, A traditional farmer see that, yeah, there is some disease, they will just go and spray pesticides. It is not good for the environment. Now I can fly it drone, get images of the field in the real time, check it against the models, and then it'll tell that, okay, this part of the field has disease. One, this part of the field has disease. Two, I indicate to the, to the tractor or the sprayer saying, okay, spray only pesticide one, you have pesticide two here. That has a big impact. So this is what we are developing in that NSF A I institute I cycle ai. We also have, we have chosen two additional verticals. One is animal ecology, because that is very much related to wildlife conservation, climate change, how do you understand how the animals move? Can we learn from them? And then see how human beings need to act in future. And the third one is the food insecurity and logistics. Smart food distribution. So these are our three broad goals in that institute. How do we develop cyber infrastructure from below? Combining HP c AI security? We have, we have a large team, like as I said, there are 40 PIs there, 60 students. We are a hundred members team. We are working together. So, so that will be my wish. How do we really democratize ai? >>Fantastic. I think that's a great place to wrap the conversation here On day three at Supercomputing conference 2022 on the cube, it was an honor, Dr. Panda working tirelessly at the Ohio State University with his team for 31 years toiling in the field of computer science and the end result, improving the lives of everyone on Earth. That's not a stretch. If you're in high school thinking about a career in computer science, keep that in mind. It isn't just about the bits and the bobs and the speeds and the feeds. It's about serving humanity. Maybe, maybe a little, little, little too profound a statement, I would argue not even close. I'm Dave Nicholson with the Queue, with my cohost Paul Gillin. Thank you again, Dr. Panda. Stay tuned for more coverage from the Cube at Super Compute 2022 coming up shortly. >>Thanks a lot.

(upbeat music) >> Hello, beautiful humans and welcome back to Supercomputing. We're here in Dallas, Texas giving you live coverage with theCUBE. I'm joined by David Nicholson. Thank you for being my left arm today. >> Thank you Savannah. >> It's a nice little moral. Very excited about this segment. We've talked a lot about how the fusion between academia and the private sector is a big theme at this show. You can see multiple universities all over the show floor as well as many of the biggest companies on earth. We were very curious to learn a little bit more about this from people actually in the trenches. And we are lucky to be joined today by two Purdue students. We have Lucas and Karl. Thank you both so much for being here. >> One Purdue, one IU, I think. >> Savannah: Oh. >> Yeah, yeah, yeah. >> I'm sorry. Well then wait, let's give Indiana University their fair do. That's where Lucas is. And Karl is at Purdue. Sorry folks. I apparently need to go back to school to learn how to read. (chuckles) In the meantime, I know you're in the middle of a competition. Thank you so much for taking the time out. Karl, why don't you tell us what's going on? What is this competition? What brought you all here? And then let's dive into some deeper stuff. >> Yeah, this competition. So we're a joint team between Purdue and IU. We've overcome our rivalries, age old rivalries to computer at the competition. It's a multi-part competition where we're going head to head against other teams from all across the world, benchmarking our super computing cluster that we designed. >> Was there a moment of rift at all when you came together? Or was everyone peaceful? >> We came together actually pretty nicely. Our two advisors they were very encouraging and so we overcame that, no hostility basically. >> I love that. So what are you working on and how long have you guys been collaborating on it? You can go ahead and start Lucas. >> So we've been prepping for this since the summer and some of us even before that. >> Savannah: Wow. >> And so currently we're working on the application phase of the competition. So everybody has different specialties and basically the competition gives you a set of rules and you have to accomplish what they tell you to do in the allotted timeframe and run things very quickly. >> And so we saw, when we came and first met you, we saw that there are lights and sirens and a monitor looking at the power consumption involved. So part of this is how much power is being consumed. >> Karl: That's right. >> Explain exactly what are the what are the rules that you have to live within? >> So, yeah, so the main constraint is the time as we mentioned and the power consumption. So for the benchmarking phase, which was one, two days ago there was a hard camp of 3000 watts to be consumed. You can't go over that otherwise you would be penalized for that. You have to rerun, start from scratch basically. Now there's a dynamic one for the application section where it's it modulates at random times. So we don't know when it's going to go down when it's going to go back up. So we have to adapt to that in real time. >> David: Oh, interesting. >> Dealing with a little bit of real world complexity I guess probably is simulation is here. I think that's pretty fascinating. I want to know, because I am going to just confess when I was your age last week, I did not understand the power of supercomputing and high performance computing. Lucas, let's start with you. How did you know this was the path you wanted to go down in your academic career? >> David: Yeah, what's your background? >> Yeah, give us some. >> So my background is intelligence systems engineering which is kind of a fusion. It's between, I'm doing bioengineering and then also more classical computer engineering. So my background is biology actually. But I decided to go down this path kind of on a whim. My professor suggested it and I've kind of fallen in love with it. I did my summer internship doing HPC and I haven't looked back. >> When did you think you wanted to go into this field? I mean, in high school, did you have a special teacher that sparked it? What was it? >> Lucas: That's funny that you say that. >> What was in your background? >> Yes, I mean, in high school towards the end I just knew that, I saw this program at IU and it's pretty new and I just thought this would be a great opportunity for me and I'm loving it so far. >> Do you have family in tech or is this a different path for you? >> Yeah, this is a different path for me, but my family is so encouraging and they're very happy for me. They text me all the time. So I couldn't be happier. >> Savannah: Just felt that in my heart. >> I know. I was going to say for the parents out there get the tissue out. >> Yeah, yeah, yeah. (chuckles) >> These guys they don't understand. But, so Karl, what's your story? What's your background? >> My background, I'm a major in unmanned Aerial systems. So this is a drones commercial applications not immediately connected as you might imagine although there's actually more overlap than one might think. So a lot of unmanned systems today a lot of it's remote sensing, which means that there's a lot of image processing that takes place. Mapping of a field, what have you, or some sort of object, like a silo. So a lot of it actually leverages high performance computing in order to map, to visualize much replacing, either manual mapping that used to be done by humans in the field or helicopters. So a lot of cost reduction there and efficiency increases. >> And when did you get this spark that said I want to go to Purdue? You mentioned off camera that you're from Belgium. >> Karl: That's right. >> Did you, did you come from Belgium to Purdue or you were already in the States? >> No, so I have family that lives in the States but I grew up in Belgium. >> David: Okay. >> I knew I wanted to study in the States. >> But at what age did you think that science and technology was something you'd be interested in? >> Well, I've always loved computers from a young age. I've been breaking computers since before I can remember. (chuckles) Much to my parents dismay. But yeah, so I've always had a knack for technology and that's sort of has always been a hobby of mine. >> And then I want to ask you this question and then Lucas and then Savannah will get some time. >> Savannah: It cool, will just sit here and look pretty. >> Dream job. >> Karl: Dream job. >> Okay. So your undergrad both you. >> Savannah: Offering one of my questions. Kind of, It's adjacent though. >> Okay. You're undergrad now? Is there grad school in your future do you feel that's necessary? Is that something you want to pursue? >> I think so. Entrepreneurship is something that's been in the back of my head for a while as well. So may be or something. >> So when I say dream job, understand could be for yourself. >> Savannah: So just piggyback. >> Dream thing after academia or stay in academia. What's do you think at this point? >> That's a tough question. You're asking. >> You'll be able to review this video in 10 years. >> Oh boy. >> This is give us your five year plan and then we'll have you back on theCUBE and see 2027. >> What's the dream? There's people out here watching this. I'm like, go, hey, interesting. >> So as I mentioned entrepreneurship I'm thinking I'll start a company at some point. >> David: Okay. >> Yeah. In what? I don't know yet. We'll see. >> David: Lucas, any thoughts? >> So after graduation, I am planning to go to grad school. IU has a great accelerated master's degree program so I'll stay an extra year and get my master's. Dream job is, boy, that's impossible to answer but I remember telling my dad earlier this year that I was so interested in what NASA was doing. They're sending a probe to one of the moons of Jupiter. >> That's awesome. From a parent's perspective the dream often is let's get the kids off the payroll. So I'm sure that your families are happy to hear that you have. >> I think these two will be right in that department. >> I think they're going to be okay. >> Yeah, I love that. I was curious, I want to piggyback on that because I think when NASA's doing amazing we have them on the show. Who doesn't love space. >> Yeah. >> I'm also an entrepreneur though so I very much empathize with that. I was going to ask to your dream job, but also what companies here do you find the most impressive? I'll rephrase. Because I was going to say, who would you want to work with? >> David: Anything you think is interesting? >> But yeah. Have you even had a chance to walk the floor? I know you've been busy competing >> Karl: Very little. >> Yeah, I was going to say very little. Unfortunately I haven't been able to roam around very much. But I look around and I see names that I'm like I can't even, it's crazy to see them. Like, these are people who are so impressive in the space. These are people who are extremely smart. I'm surrounded by geniuses everywhere I look, I feel like, so. >> Savannah: That that includes us. >> Yeah. >> He wasn't talking about us. Yeah. (laughs) >> I mean it's hard to say any of these companies I would feel very very lucky to be a part of, I think. >> Well there's a reason why both of you were invited to the party, so keep that in mind. Yeah. But so not a lot of time because of. >> Yeah. Tomorrow's our day. >> Here to get work. >> Oh yes. Tomorrow gets play and go talk to everybody. >> Yes. >> And let them recruit you because I'm sure that's what a lot of these companies are going to be doing. >> Yeah. Hopefully it's plan. >> Have you had a second at all to look around Karl. >> A Little bit more I've been going to the bathroom once in a while. (laughs) >> That's allowed I mean, I can imagine that's a vital part of the journey. >> I've ruin my gaze a little bit to what's around all kinds of stuff. Higher education seems to be very important in terms of their presence here. I find that very, very impressive. Purdue has a big stand IU as well, but also others all from Europe as well and Asia. I think higher education has a lot of potential in this field. >> David: Absolutely. >> And it really is that union between academia and the private sector. We've seen a lot of it. But also one of the things that's cool about HPC is it's really not ageist. It hasn't been around for that long. So, I mean, well, at this scale it's obviously this show's been going on since 1988 before you guys were even probably a thought. But I think it's interesting. It's so fun to get to meet you both. Thank you for sharing about what you're doing and what your dreams are. Lucas and Karl. >> David: Thanks for taking the time. >> I hope you win and we're going to get you off the show here as quickly as possible so you can get back to your teams and back to competing. David, great questions as always, thanks for being here. And thank you all for tuning in to theCUBE Live from Dallas, Texas, where we are at Supercomputing. My name's Savannah Peterson and I hope you're having a beautiful day. (gentle upbeat music)

>> Hello everyone and welcome back to theCUBE, where we're live from Dallas, Texas here at Super computing 2022. I am joined by my cohost David Nicholson. Thank you so much for being here with me and putting up with my trashy jokes all day. >> David: Thanks for having me. >> Yeah. Yes, we are going to be talking about AI this morning and I'm very excited that our guest has has set the stage for us here quite well. Please welcome Andrea Booker. Andrea, thank you so much for being here with us. >> Absolutely. Really excited to be here. >> Savannah: How's your show going so far? >> It's been really cool. I think being able to actually see people in person but also be able to see the latest technologies and and have the live dialogue that connects us in a different way than we have been able to virtually. >> Savannah: Oh yeah. No, it's all, it's all about that human connection and that it is driving towards our first question. So as we were just chit chatting. You said you are excited about making AI real and humanizing that. >> Andrea: Absolutely. >> What does that mean to you? >> So I think when it comes down to artificial intelligence it means so many different things to different people. >> Savannah: Absolutely. >> I was talking to my father the other day for context, he's in his late seventies, right. And I'm like, oh, artificial intelligence, this or that, and he is like, machines taking over the world. Right. >> Savannah: Very much the dark side. >> A little bit Terminator. And I'm like, well, not so much. So that was a fun discussion. And then you flip it to the other side and I'm talking to my 11 year old daughter and she's like, Alexa make sure you know my song preferences. Right. And that's the other very real way in which it's kind of impacting our lives. >> Savannah: Yeah. >> Right. There's so many different use cases that I don't think everyone understands how that resonates. Right. It's the simple things from, you know, recommend Jason Engines when you're on Amazon and it suggests just a little bit more. >> Oh yeah. >> I'm a little bit to you that one, right. To stuff that's more impactful in regards to getting faster diagnoses from your doctors. Right. Such peace of mind being able to actually hear that answer faster know how to go tackle something. >> Savannah: Great point, yeah. >> You know, and, and you know, what's even more interesting is from a business perspective, you know the projections are over the next five years about 90% of customers are going to use AI applications in in some fashion, right. >> Savannah: Wow. >> And the reason why that's interesting is because if you look at it today, only about 15% of of them are doing so. Right. So we're early. So when we're talking growth and the opportunity, it's, it's amazing. >> Yeah. I can, I can imagine. So when you're talking to customers, what are are they excited? Are they nervous? Are you educating them on how to apply Dell technology to advance their AI? Where are they off at because we're so early? >> Yeah well, I think they're figuring it out what it means to them, right? >> Yeah. Because there's so many different customer applications of it, right? You have those in which, you know, are on on the highest end in which that our new XE products are targeting that when they think of it. You know, I I, I like to break it down in this fashion in which artificial intelligence can actually save human lives, right? And this is those extreme workloads that I'm talking about. We actually can develop a Covid vaccine faster, right. Pandemic tracking, you know with global warming that's going on. And we have these extreme weather events with hurricanes and tsunamis and all these things to be able to get advanced notice to people to evacuate, to move. I mean, that's a pretty profound thing. And it is, you know so it could be used in that way to save lives, right? >> Absolutely. >> Which is it's the natural outgrowth of the speeds and feeds discussions that we might have internally. It's, it's like, oh, oh, speed doubled. Okay. Didn't it double last year? Yeah. Doubled last year too. So it's four x now. What does that mean to your point? >> Andrea: Yeah, yeah. >> Savannah: Yeah. >> Being able to deliver faster insight insights that are meaningful within a timeframe when otherwise they wouldn't be meaningful. >> Andrea: Yeah. >> If I tell you, within a two month window whether it's going to rain this weekend, that doesn't help you. In hindsight, we did the calculation and we figured out it's going to be 40 degrees at night last Thursday >> Knowing it was going to completely freeze here in Dallas to our definition in Texas but we prepare better to back to bring clothes. >> We were talking to NASA about that yesterday too. I mean, I think it's, it's must be fascinating for you to see your technology deployed in so many of these different use cases as well. >> Andrea: Absolutely, absolutely. >> It's got to be a part of one of the more >> Andrea: Not all of them are extreme, right? >> Savannah: Yeah. >> There's also examples of, you know natural language processing and what it does for us you know, the fact that it can break down communication barriers because we're global, right? We're all in a global environment. So if you think about conference calls in which we can actually clearly understand each other and what the intent is, and the messaging brings us closer in different ways as well. Which, which is huge, right? You don't want things lost in translation, right? So it, it helps on so many fronts. >> You're familiar with the touring test idea of, of, you know whether or not, you know, the test is if you can't discern within a certain number of questions that you're interacting with an AI versus a real human, then it passes the touring test. I think there should be a natural language processing test where basically I say, fine >> Andrea: You see if people was mad or not. >> You tell me, you tell me. >> I love this idea, David. >> You know? >> Yeah. This is great. >> Okay. AI lady, >> You tell me what I meant. >> Yeah, am I actually okay? >> How far from, that's silly example but how far do you think we are from that? I mean, what, what do you seeing out there in terms of things where you're kind of like, whoa, they did this with technology I'm responsible for, that was impressive. Or have you heard of things that are on the horizon that, you know, again, you, you know they're the big, they're the big issues. >> Yeah. >> But any, anything kind of interesting and little >> I think we're seeing it perfected and tweaked, right? >> Yeah. >> You know, I think going back to my daughter it goes from her screaming at Alexa 'cause she did hear her right the first time to now, oh she understands and modifies, right? Because we're constantly tweaking that technology to have a better experience with it. And it's a continuum, right? The voice to text capabilities, right. You know, I I'd say early on it got most of those words, right Right now it's, it's getting pretty dialed in. Right. >> Savannah: That's a great example. >> So, you know, little things, little things. >> Yeah. I think I, I love the, the this thought of your daughter as the example of training AI. What, what sort of, you get to look into the future quite a bit, I'm sure with your role. >> Andrea: Absolutely. >> Where, what is she going to be controlling next? >> The world. >> The world. >> No, I mean if you think about it just from a generational front, you know technology when I was her age versus what she's experiencing, she lives and breathes it. I mean, that's the generational change. So as these are coming out, you have new folks growing with it that it's so natural that they are so open to adopting it in their common everyday behaviors. Right? >> Savannah: Yeah. >> But they'd they never, over time they learn, oh well how it got there is 'cause of everything we're doing now, right. >> Savannah: Yeah. >> You know, one, one fun example, you know as my dad was like machines are taking over the world is not, not quite right. Even if when you look at manufacturing, there's a difference in using AI to go build a digital simulation of a factory to be able to optimize it and design it right before you're laying the foundation that saves cost, time and money. That's not taking people's jobs in that extreme event. >> Right. >> It's really optimizing for faster outcomes and, and and helping our customers get there which is better for everyone. >> Savannah: Yeah and safer too. I mean, using the factory example, >> Totally safer. >> You're able to model out what a workplace injury might be or what could happen. Or even the ergonomics of how people are using. >> Andrea: Yeah, should it be higher so they don't have to bend over? Right. >> Exactly. >> There's so many fantastic positive ways. >> Yeah so, so for your dad, you know, I mean it's going to help us, it's going to make, it's going to take away when I. Well I'm curious what you think, David when I think about AI, I think it's going to take out a lot of the boring things in life that, that we don't like >> Andrea: Absolutely. Doing. The monotony and the repetitive and let us optimize our creative selves maybe. >> However, some of the boring things are people's jobs. So, so it is, it it it will, it will it will push a transition in our economy in the global economy, in my opinion. That would be painful for some, for some period of time. But overall beneficial, >> Savannah: Yes. But definitely as you know, definitely there will be there will be people who will be disrupted and, you know. >> Savannah: Tech's always kind of done that. >> We No, but we need, I, I think we need to make sure that the digital divide doesn't get so wide that you know that, that people might not be negative, negatively affected. And, but, but I know that like organizations like Dell I believe what you actually see is, >> Andrea: Yeah. >> No, it's, it's elevating people. It's actually taking away >> Andrea: Easier. >> Yeah. It's, it's, it's allowing people to spend their focus on things that are higher level, more interesting tasks. >> Absolutely. >> David: So a net, A net good. But definitely some people disrupted. >> Yes. >> I feel, I feel disrupted. >> I was going to say, are, are we speaking for a friend or for ourselves here today on stage? >> I'm tired of software updates. So maybe if you could, if you could just standardize. So AI and ML. >> Andrea: Yeah. >> People talk about machine learning and, and, and and artificial intelligence. How would you differentiate the two? >> Savannah: Good question. >> It it, it's, it's just the different applications and the different workloads of it, right? Because you actually have artificial intelligence you have machine learning in which the learn it's learning from itself. And then you have like the deep learning in which it's diving deeper in in its execution and, and modeling. And it really depends on the workload applications as long as well as how large the data set is that's feeding into it for those applications. Right. And that really leads into the, we have to make sure we have the versatility in our offerings to be able to meet every dimension of that. Right. You know our XE products that we announced are really targeted for that, those extreme AI HPC workloads. Right. Versus we also have our entire portfolio products that we make sure we have GPU diversity throughout for the other applications that may be more edge centric or telco centric, right? Because AI isn't just these extreme situations it's also at the edge. It's in the cloud, it's in the data center, right? So we want to make sure we have, you know versatility in our offerings and we're really meeting customers where they're at in regards to the implementation and and the AI workloads that they have. >> Savannah: Let's dig in a little bit there. So what should customers expect with the next generation acceleration trends that Dell's addressing in your team? You had three exciting product announcements here >> Andrea: We did, we did. >> Which is very exciting. So you can talk about that a little bit and give us a little peek. >> Sure. So, you know, for, for the most extreme applications we have the XE portfolio that we built upon, right? We already had the XC 85 45 and we've expanded that out in a couple ways. The first of which is our very first XC 96 88 way offering in which we have Nvidia's H 100 as well as 8 100. 'Cause we want choice, right? A choice between performance, power, what really are your needs? >> Savannah: Is that the first time you've combined? >> Andrea: It's the first time we've had an eight way offering. >> Yeah. >> Andrea: But we did so mindful that the technology is emerging so much from a thermal perspective as well as a price and and other influencers that we wanted that choice baked into our next generation of product as we entered the space. >> Savannah: Yeah, yeah. >> The other two products we have were both in the four way SXM and OAM implementation and we really focus on diversifying and not only from vendor partnerships, right. The XC 96 40 is based off Intel Status Center max. We have the XE 86 40 that is going to be in or Nvidia's NB length, their latest H 100. But the key differentiator is we have air cold and we have liquid cold, right? So depending on where you are from that data center journey, I mean, I think one of the common themes you've heard is thermals are going up, performance is going up, TBPs are going up power, right? >> Savannah: Yeah. >> So how do we kind of meet in the middle to be able to accommodate for that? >> Savannah: I think it's incredible how many different types of customers you're able to accommodate. I mean, it's really impressive. I feel lucky we've gotten to see these products you're describing. They're here on the show floor. There's millions of dollars of hardware literally sitting in your booth. >> Andrea: Oh yes. >> Which is casual only >> Pies for you. Yeah. >> Yeah. We were, we were chatting over there yesterday and, and oh, which, which, you know which one of these is more expensive? And the response was, they're both expensive. It was like, okay perfect >> But assume the big one is more. >> David: You mentioned, you mentioned thermals. One of the things I've been fascinated by walking around is all of the different liquid cooling solutions. >> Andrea: Yeah. >> And it's almost hysterical. You look, you look inside, it looks like something from it's like, what is, what is this a radiator system for a 19th century building? >> Savannah: Super industrial? >> Because it looks like Yeah, yeah, exactly. Exactly, exactly. It's exactly the way to describe it. But just the idea that you're pumping all of this liquid over this, over this very, very valuable circuitry. A lot of the pitches have to do with, you know this is how we prevent disasters from happening based on the cooling methods. >> Savannah: Quite literally >> How, I mean, you look at the power requirements of a single rack in a data center, and it's staggering. We've talked about this a lot. >> Savannah: Yeah. >> People who aren't kind of EV you know electric vehicle nerds don't appreciate just how much power 90 kilowatts of power is for an individual rack and how much heat that can generate. >> Andrea: Absolutely. >> So Dell's, Dell's view on this is air cooled water cooled figure it out fit for for function. >> Andrea: Optionality, optionality, right? Because our customers are a complete diverse set, right? You have those in which they're in a data center 10 to 15 kilowatt racks, right? You're not going to plum a liquid cool power hungry or air power hungry thing in there, right? You might get one of these systems in, in that kind of rack you know, architecture, but then you have the middle ground the 50 to 60 is a little bit of choice. And then the super extreme, that's where liquid cooling makes sense to really get optimized and have the best density and, and the most servers in that solution. So that's why it really depends, and that's why we're taking that approach of diversity, of not only vendors and, and choice but also implementation and ways to be able to address that. >> So I think, again, again, I'm, you know electric vehicle nerd. >> Yeah. >> It's hysterical when you, when you mention a 15 kilowatt rack at kind of flippantly, people don't realize that's way more power than the average house is consuming. >> Andrea: Yeah, yeah >> So it's like your entire house is likely more like five kilowatts on a given day, you know, air conditioning. >> Andrea: Maybe you have still have solar panel. >> In Austin, I'm sorry >> California, Austin >> But, but, but yeah, it's, it's staggering amounts of power staggering amounts of heat. There are very real problems that you guys are are solving for to drive all of these top line value >> Andrea: Yeah. >> Propositions. It's super interesting. >> Savannah: It is super interesting. All right, Andrea, last question. >> Yes. Yes. >> Dell has been lucky to have you for the last decade. What is the most exciting part about you for the next decade of your Dell career given the exciting stuff that you get to work on. >> I think, you know, really working on what's coming our way and working with my team on that is is just amazing. You know, I can't say it enough from a Dell perspective I have the best team. I work with the most, the smartest people which creates such a fun environment, right? So then when we're looking at all this optionality and and the different technologies and, and, and you know partners we work with, you know, it's that coming together and figuring out what's that best solution and then bringing our customers along that journey. That kind of makes it fun dynamic that over the next 10 years, I think you're going to see fantastic things. >> David: So I, before, before we close, I have to say that's awesome because this event is also a recruiting event where some of these really really smarts students that are surrounding us. There were some sirens going off. They're having competitions back here. >> Savannah: Yeah, yeah, yeah. >> So, so when they hear that. >> Andrea: Where you want to be. >> David: That's exactly right. That's exactly right. >> Savannah: Well played. >> David: That's exactly right. >> Savannah: Well played. >> Have fun. Come on over. >> Well, you've certainly proven that to us. Andrea, thank you so much for being with us This was such a treat. David Nicholson, thank you for being here with me and thank you for tuning in to theCUBE a lot from Dallas, Texas. We are all things HPC and super computing this week. My name's Savannah Peterson and we'll see you soon. >> Andrea: Awesome.

>>Hello >>Everyone and welcome back to Dallas where we're live from, Super computing. My name is Savannah Peterson, joined with my co-host David, and we have a rocket of a show for you this afternoon. The doctors are in the house and we are joined by nasa, ladies and gentlemen. So excited. Please welcome Dr. Dan Duffy and Dr. Bill Putman. Thank you so much for being here, guys. I know this is kind of last minute. How's it to be on the show floor? What's it like being NASA here? >>What's exciting? We haven't, we haven't been here for three years, so this is actually really exciting to come back and see everybody, to see the showroom floor, see the innovations that have happened over the last three years. It's pretty exciting. >>Yeah, it's great. And, and so, because your jobs are so cool, and I don't wanna even remotely give even too little of the picture or, or not do it justice, could you give the audience a little bit of background on what you do as I think you have one of the coolest jobs ever. YouTube bill. >>I, I appreciate that. I, I, I run high Performance Computing Center at NASA Goddard for science. It's high performance information technology. So we do everything from networking to security, to high performance computing, to data sciences, artificial intelligence and machine learning is huge for us now. Yeah, large amounts of data, big data sets, but we also do scientific visualizations and then cloud and commercial cloud computing, as well as on premises cloud computing. And quite frankly, we support a lot of what Bill and his team does. >>Bill, why don't you tell us what your team >>Does? Yeah, so I'm a, I'm an earth scientist. I work as the associate chief at the global modeling assimilation office. And our job is to really, you know, maximize the use of all the observations that NASA takes from space and build that into a coherent, consistent physical system of the earth. Right? And we're focused on utilizing the HC that, that Dan and the folks at the nccs provide to us, to the best of our abilities to integrate those observations, you know, on time scales from hours, days to, to seasonal to to monthly time scales. That's, that's the essence of our focus at the GMA o >>Casual modeling, all of NASA's earth data. That, that in itself as a sentence is pretty wild. I imagine you're dealing with a ton of data. >>Oh, massive amounts of data. Yes, >>Probably, I mean, as much as one probably could, now that I'm thinking about it. I mean, and especially with how far things have to travel. Bill, sticking with you, just to open us up, what technology here excites you the most about the future and that will make your job easier? Let's put it that way. >>To me, it's the accelerator technologies, right? So there's the limited, the limiting factor for, for us as scientists is how fast we can get an answer. And if we can get our answer faster through accelerated technologies, you know, with the support of the, of the nccs and the computing centers, but also the software engineers enabling that for us, then we can do more, right. And push the questions even further, you know, so once we've gotten fast enough to do what we want to do, there's always something next that we wanna look for. So, >>I mean, at nasa you have to exercise such patience, whether that be data, coming back, images from a rover, doesn't matter what it is. Sometimes there's a lot of time, days, hours, years, depending on the situation. Right? I really, I really admire that. What about you, Dan? What's got you really excited about the future here? So >>Bill talked about the, the accelerated technology, which is absolutely true and, and, and is needed to get us not to only to the point where we have the compute resources to do the simulations that Bill wants to do, and also do it in a energy efficient way. But it's really the software frameworks that go around that and the software frameworks, the technology that dealing with how to use those in an energy efficient and and most efficient way is extremely important. And that's some of the, you know, that's what I'm really here to try to understand better about is how can I support these scientists with not just the hardware, but the software frameworks by which they can be successful. >>Yeah. We've, we've had a lot of kind of philosophical discussion about this, the difference between the quantitative increases in power in computing that we're seeing versus the question of whether or not we need truly qualitative changes moving forward. Where do you see the limits of, of, of, you know, if you, if you're looking at the ability to gather more data and process more data more quickly, what you can do with that data changes when you're getting updates every second versus every month seems pretty obvious. Is there a, is there, but is there, is there a near term target that you have specifically where once you reach that target, if you weren't thinking ahead of that target, you'd kind of be going, Okay, well we solved that problem, we're getting the data in so fast that you can, you can ask me, what is the temperature in this area? And you can go, Oh, well, huh, an hour ago the data said this. Beyond that, do you need a qualitative change in our ability to process information and tease insight into out of chaos? Or do you just need more quantity to be able to get to the point where you can do things like predict weather six months in advance? What are, what are your thoughts on that? Yeah, >>It's an interesting question, right? And, and you ended it with predicting whether six months in advance, and actually I was thinking the other way, right? I was thinking going to finer and finer scales and shorter time scales when you talk about having data more frequently, right? So one of the things that I'm excited about as a modeler is going to hire resolution and representing smaller scale processes at nasa, we're, we're interested in observations that are global. So our models are global and we'd like to push those to as fine a resolution as possible to do things like severe storm predictions and so forth. So the faster we can get the data, the more data we can have, and that area would improve our ability to do that as well. So, >>And your background is in meteorology, right? >>Yes, I'm a meteorologist. >>Excellent. Okay. Yeah, yeah, >>Yeah. So, so I have to ask a question, and I'm sure all the audience cares about this. And I went through this when I was talking about the ghost satellites as well. What, what is it about weather that makes it so hard to predict? >>Oh, it's the classic chaos problem. The, the butterfly effects problem, and it's just true. You know, you always hear the story of a butterfly in Africa flaps, its rings and wings, and the weather changes in, in New York City, and it's just, computers are an excellent example of that, right? So we have a model of the earth, we can run it two times in a row and get the exact same answer, but if we flip a bit somewhere, then the answer changes 10 days later significantly. So it's a, it's a really interesting problem. So, >>Yeah. So do you have any issue with the fact that your colleague believes that butterflies are responsible for weather? No, I does that, does that, is it responsible for climate? Does that bother you at all? >>No, it doesn't. As a matter of fact, they actually run those butterfly like experi experiments within the systems where they do actually flip some bits and see what the uncertainties are that happen out 7, 8, 9 days out in advance to understand exactly what he's saying, to understand the uncertainties, but also the sensitivity with respect to the observations that they're taking. So >>Yeah, it's fascinating. It is. >>That is fascinating. Sticking with you for a second, Dan. So you're at the Center for Climate Simulation. Is that the center that's gonna help us navigate what happens over the next decade? >>Okay, so I, no one center is gonna help us navigate what's gonna happen over the next decade or the next 50 or a hundred years, right. It's gonna be everybody together. And I think NASA's role in that is really to pioneer the, the, the models that that bill and others are doing to understand what's gonna happen in not just the seasonal sub, but we also work with G, which is the God Institute for Space Studies. Yeah. Which does the decatal and, and the century long studies. Our, our job is to really help that research, understand what's happening with the client, but then feed that back into what observations we need to make next in order to better understand and better quantify the risks that we have to better quantify the mitigations that we can make to understand how and, and, and affect how the climate is gonna go for the future. So that's really what we trying to do. We're trying to do that research to understand the climate, understand what mitigations we can have, but also feedback into what observations we can make for the future. >>Yeah. And and what's the partnership ecosystem around that? You mentioned that it's gonna take all of us, I assume you work with a lot of >>Partners, Probably both of you. I mean, obviously the, the, the federal agencies work huge amounts together. Nasa, Noah is our huge partnerships. Sgs, a huge partnerships doe we've talked to doe several times this, so this, this this week already. So there's huge partnerships that go across the federal agency. We, we work also with Europeans as much as we can given the, the, the, you know, sort of the barriers of the countries and the financials. But we do collaborate as much as we can with, And the nice thing about NASA, I would say is the, all the observations that we take are public, they're paid for by the public. They're public, everybody can down them, anybody can down around the world. So that's also, and they're global measurements as Bill said, they're not just regional. >>Do you have, do you have specific, when you think about improving your ability to gain insights from data that that's being gathered? Yeah. Do you set out specific milestones that you're looking for? Like, you know, I hope by June of next year we will have achieved a place where we are able to accomplish X. Yeah. Do you, do you, Yeah. Bill, do you put, what, >>What milestones do we have here? So, yeah, I mean, do you have >>Yeah. Are, are you, are you sort of kept track of that way? Do you think of things like that? Like very specific things? Or is it just so fluid that as long as you're making progress towards the future, you feel okay? >>No, I would say we absolutely have milestones that we like to keep in track, especially from the modeling side of things, right? So whether it's observations that exist now that we want to use in our system, milestones to getting those observations integrated in, but also thinking even further ahead to the observations that we don't have yet. So we can use the models that we have today to simulate those kind of observations that we might want in the future that can help us do things that we can do right now. So those missions are, are aided by the work that we do at the GBO and, and the nccs, but, >>Okay, so if we, if we extrapolate really to the, to the what if future is really trying to understand the entire earth system as best as we can. So all the observations coming in, like you said, in in near real time, feeding that into an earth system model and to be able to predict short term, midterm or even long term predictions with, with some degree of certainty. And that may be things like climate change or it may be even more important, shorter term effects of, of severe weather. Yeah. Which is very important. And so we are trying to work towards that high resolution, immediate impact model that we can, that we can, you know, really share with the world and share those results as best, as best we can. >>Yeah. I, I have a quick, I have a quick follow up on that. I I bet we both did. >>So, so if you think about AI and ml, artificial intelligence and machine learning, something that, you know, people, people talk about a lot. Yeah. There's the concept of teaching a machine to go look for things, call it machine learning. A lot of it's machine teaching we're saying, you know, hit, you know, hit the rack on this side with a stick or the other side with the stick to get it to, to kind of go back and forth. Do you think that humans will be able to guide these systems moving forward enough to tease out the insights that we want? Or do you think we're gonna have to rely on what people think of as artificial intelligence to be able to go in with this massive amount of information with an almost infinite amount of variables and have the AI figure out that, you know what, it was the butterfly, It really was the butterfly. We all did models with it, but, but you understand the nuance that I'm saying. It's like we, we, we think we know what all the variables are and that it's chaotic because there's so many variables and there's so much data, but maybe there's something we're not taking into >>A account. Yeah, I I, I'm, I'm, I'm sure that's absolutely the case. And I'll, I'll start and let Bill, Bill jump in here. Yeah, there's a lot of nuances with a aiml. And so the, the, the, the real approach to get to where we want to be with this earth system model approach is a combination of both AI ML train models as best as we can and as unbiased way as we can. And there's a, there's a big conversation we have around that, but also with a physics or physical based model as well, Those two combined with the humans or the experts in the loop, we're not just gonna ask the artificial intelligence to predict anything and everything. The experts need to be in the loop to guide the training in as best as we, as, as we can in an unbiased, equitable way, but also interpret the results and not just give over to the ai. But that's the combination of that earth system model that we really wanna see. The future's a combination of AI l with physics based, >>But there's, there's a, there's an obvious place for a AI and ML in the modeling world that is in the parameterizations of the estimations that we have to do in our systems, right? So when we think about the earth system and modeling the earth system, there are many things like the equations of motions and thermodynamics that have fixed equations that we know how to solve on a computer. But there's a lot of things that happen physically in the atmosphere that we don't have equations for, and we have to estimate them. And machine learning through the use of high resolution models or observations in training the models to understand and, and represent that, yeah, that that's the place where it's really useful >>For us. There's so many factors, but >>We have to, but we have to make sure that we have the physics in that machine learning in those, in those training. So physics informed training isn't very important. So we're not just gonna go and let a model go off and do whatever it wants. It has to be constrained within physical constraints that the, that the experts know. >>Yeah. And with the wild amount of variables that affect our, our earth, quite frankly. Yeah, yeah. Which is geez. Which is insane. My god. So what's, what, what technology or what advancement needs to happen for your jobs to get easier, faster for our ability to predict to be even more successful than it is currently? >>You know, I think for me, the vision that I have for the future is that at some point, you know, all data is centrally located, essentially shared. We have our applications are then services that sit around all that data. I don't have to sit as a user and worry about, oh, is this all this data in place before I run my application? It's already there, it's already ready for me. My service is prepared and I just launch it out on that service. But that coupled with the performance that I need to get the result that I want in time. And I don't know when that's gonna happen, but at some point it might, you know, I don't know rooting for you, but that's, >>So there are, there are a lot of technologies we can talk about. What I'd like to mention is, is open science. So NASA is really trying to make a push and transformation towards open science. 2023 is gonna be the year of open science for nasa. And what does that mean? It means a lot of what Bill just said is that we have equity and fairness and accessibility and you can find the data, it's findability, it's fair data, you know, a fair findability accessibility reproducibility, and I forget what the eye stands for, but these are, these are tools and, and, and things that we need to, as, as a computing centers and including all the HC centers here, as well as the scientists need to support, to be as transparent as possible with the data sets and the, and the research that we're doing. And that's where I think is gonna be the best thing is if we can get this data out there that anybody can use in an equitable way and as transparent as possible, that's gonna eliminate, in my opinion, the bias over time because mistakes will be found and mistakes will be corrected over time. >>I love that. Yeah. The open source science end of this. No, it's great. And the more people that have access people I find in the academic world, especially people don't know what's going on in the private sector and vice versa. And so I love that you just brought that up. Closing question for you, because I suspect there might be some members of our audience who maybe have fantasized about working at nasa. You've both been working there for over a decade. Is it as cool as we all think of it? It is on the outside. >>I mean, it's, it's definitely pretty cool. >>You don't have to be modest about it, you know, >>I mean, just being at Goddard and being at the center where they build the James web web telescope and you can go to that clean room and see it, it's just fascinating. So it, it's really an amazing opportunity. >>Yeah. So NASA Goddard as a, as a center has, you know, information technologist, It has engineers, it has scientists, it has support staff, support team members. We have built more things, more instruments that have flown in this space than any other place in the world. The James Lab, we were part of that, part of a huge group of people that worked on James. We and James, we came through and was assembled in our, our, our clean room. It's one of the biggest clean rooms in, in, in the world. And we all took opportunities to go over and take selfies with this as they put those loveness mirrors on them. Yeah, it was awesome. It was amazing. And to see what the James we has done in such a short amount of time, the successes that they've gone through is just incredible. Now, I'm not a, I'm not a part of the James web team, but to be a, to be at the same center, to to listen to scientists like Bill talk about their work, to listen to scientists that, that talk about James, we, that's what's inspiring. And, and we get that all the time. >>And to have the opportunity to work with the astronauts that service the, the Hubble Telescope, you know, these things are, >>That's literally giving me goosebumps right now. I'm sitting over >>Here just, just an amazing opportunity. And woo. >>Well, Dan, Bill, thank you both so much for being on the show. I know it was a bit last minute, but I can guarantee we all got a lot out of it. David and I both, I know I speak for us in the whole cube audience, so thank you. We'll have you, anytime you wanna come talk science on the cube. Thank you all for tuning into our supercomputing footage here, live in Dallas. My name is Savannah Peterson. I feel cooler having sat next to these two gentlemen for the last 15 minutes and I hope you did too. We'll see you again soon.

>>How do y'all, and welcome to Dallas, where we're proud to be live from Supercomputing 2022. My name is Savannah Peterson, joined here by my cohost David on the Cube, and our first guest today is a very exciting visionary. He's a leader at Dell. Please welcome Travis Vhi. Travis, thank you so much for being here. >>Thank you so much for having me. >>How you feeling? >>Okay. I I'm feeling like an exciting visionary. You >>Are. That's, that's the ideas why we tee you up for that. Great. So, so tell us, Dell had some huge announcements Yes. Last night. And you get to break it to the cube audience. Give us the rundown. >>Yeah. It's a really big show for Dell. We announced a brand new suite of GPU enabled servers, eight ways, four ways, direct liquid cooling. Really the first time in the history of the portfolio that we've had this much coverage across Intel amd, Invidia getting great reviews from the show floor. I had the chance earlier to be in the whisper suite to actually look at the gear. Customers are buzzing over it. That's one thing I love about this show is the gear is here. >>Yes, it is. It is a haven for hardware nerds. Yes. Like, like well, I'll include you in this group, it sounds like, on >>That. Great. Yes. Oh >>Yeah, absolutely. And I know David is as well, sew up >>The street. Oh, big, big time. Big time hardware nerd. And just to be clear, for the kids that will be watching these videos Yes. We're not talking about alien wear gaming systems. >>No. Right. >>So they're >>Yay big yay tall, 200 pounds. >>Give us a price point on one of these things. Re retail, suggested retail price. >>Oh, I'm >>More than 10 grand. >>Oh, yeah. Yeah. Try another order of magnitude. Yeah. >>Yeah. So this is, this is the most exciting stuff from an infrastructure perspective. Absolutely. You can imagine. Absolutely. But what is it driving? So talk, talk to us about where you see the world of high performance computing with your customers. What are they, what are they doing with this? What do they expect to do with this stuff in the future? >>Yeah. You know, it's, it's a real interesting time and, and I know that the provenance of this show is HPC focused, but what we're seeing and what we're hearing from our customers is that AI workloads and traditional HPC workloads are becoming almost indistinguishable. You need the right mix of compute, you need GPU acceleration, and you need the ability to take the vast quantities of data that are being generated and actually gather insight from them. And so if you look at what customers are trying to do with, you know, enterprise level ai, it's really, you know, how do I classify and categorize my data, but more, more importantly, how do I make sense of it? How do I derive insights from it? Yeah. And so at the end of the day, you know, you look, you look at what customers are trying to do. It's, it's take all the various streams of data, whether it be structured data, whether it be unstructured data, bring it together and make decisions, make business decisions. >>And it's a really exciting time because customers are saying, you know, the same things that, that, that, you know, research scientists and universities have been trying to do forever with hpc. I want to do it on industrial scale, but I want to do it in a way that's more open, more flexible, you know, I call it AI for the rest of us. And, and, and customers are here and they want those systems, but they want the ecosystem to support ease of deployment, ease of use, ease of scale. And that's what we're providing in addition to the systems. We, we provide, you know, Dell's one of the only providers on the on in the industry that can provide not only the, the compute, but the networking and the storage, and more importantly, the solutions that bring it all together. Give you one example. We, we have what we call a validated design for, for ai. And that validated design, we put together all of the pieces, provided the recipe for customers so that they can take what used to be two months to build and run a model. We provide that capability 18 times faster. So we're talking about hours versus months. So >>That's a lot. 18 times faster. I just wanna emphasize that 18 times faster, and we're talking about orders of magnitude and whatnot up here, that makes a huge difference in what people are able to do. Absolutely. >>Absolutely. And so, I mean, we've, you know, you've been doing this for a while. We've been talking about the, the deluge of data forever, but it's gotten to the point and it's, you know, the, the disparity of the data, the fact that much of it remains siloed. Customers are demanding that we provide solutions that allow them to bring that data together, process it, make decisions with it. So >>Where, where are we in the adoption cycle early because we, we've been talking about AI and ML for a while. Yeah. You, you mentioned, you know, kind of the leading edge of academia and supercomputing and HPC and what that, what that conjures up in people's minds. Do you have any numbers or, you know, any, any thoughts about where we are in this cycle? How many, how many people are actually doing this in production versus, versus experimenting at this point? Yeah, >>I think it's a, it's a reason. There's so much interest in what we're doing and so much demand for not only the systems, but the solutions that bring the systems together. The ecosystem that brings the, the, the systems together. We did a study recently and ask customers where they felt they were at in terms of deploying best practices for ai, you know, mass deployment of ai. Only 31% of customers said that they felt that they self-reported. 31% said they felt that they were deploying best practices for their AI deployments. So almost 70% self reporting saying we're not doing it right yet. Yeah. And, and, and another good stat is, is three quarters of customers have fewer than five AI applications deployed at scale in their, in their IT environments today. So, you know, I think we're on the, you know, if, if I, you think about it as a traditional S curve, I think we're at the first inflection point and customers are asking, Can I do it end to end? >>Can I do it with the best of breed in terms of systems? But Dell, can you also use an ecosystem that I know and understand? And I think that's, you know, another great example of something that Dell is doing is, is we have focused on ethernet as connectivity for many of the solutions that we put together. Again, you know, provenance of hpc InfiniBand, it's InfiniBand is a great connectivity option, but you know, there's a lot of care and feeding that goes along with InfiniBand and the fact that you can do it both with InfiniBand for those, you know, government class CU scale, government scale clusters or university scale clusters and more of our enterprise customers can do it with, with ethernet on premises. It's a great option. >>Yeah. You've got so many things going on. I got to actually check out the million dollar hardware that you have just casually Yeah. Sitting in your booth. I feel like, I feel like an event like this is probably one of the only times you can let something like that out. Yeah, yeah. And, and people would actually know what it is you're working >>With. We actually unveiled it. There was a sheet on it and we actually unveiled it last night. >>Did you get a lot of uz and os >>You know, you said this was a show for hardware nerds. It's been a long time since I've been at a shoe, a show where people cheer and u and a when you take the sheet off the hardware and, and, and Yes, yes, >>Yes, it has and reveal you had your >>Moment. Exactly, exactly. Our three new systems, >>Speaking of u and os, I love that. And I love that everyone was excited as we all are about it. What I wanna, It's nice to be home with our nerds. Speaking of, of applications and excitement, you get to see a lot of different customers across verticals. Is there a sector or space that has you personally most excited? >>Oh, personally most excited, you know, for, for credibility at home when, when the sector is media and entertainment and the movie is one that your, your children have actually seen, that one gives me credibility. Exciting. It's, you can talk to your friends about it at, at at dinner parties and things like that. I'm like, >>Stuff >>Curing cancer. Marvel movie at home cred goes to the Marvel movie. Yeah. But, but, but you know, what really excites me is the variety of applications that AI is being used, used in healthcare. You know, on a serious note, healthcare, genomics, a huge and growing application area that excites me. You know, doing, doing good in the world is something that's very important to Dell. You know, know sustainability is something that's very important to Dell. Yeah. So any application related to that is exciting to me. And then, you know, just pragmatically speaking, anything that helps our customers make better business decisions excites me. >>So we are, we are just at the beginning of what I refer to as this rolling thunder of cpu. Yes. Next generation releases. We re recently from AMD in the near future it'll be, it'll be Intel joining the party Yeah. Going back and forth, back and forth along with that gen five PCI e at the motherboard level. Yep. It's very easy to look at it and say, Wow, previous gen, Wow, double, double, double. It >>Is, double >>It is. However, most of your customers, I would guess a fair number of them might be not just N minus one, but n minus two looking at an upgrade. So for a lot of people, the upgrade season that's ahead of us is going to be not a doubling, but a four x or eight x in a lot of, in a lot of cases. Yeah. So the quantity of compute from these new systems is going to be a, it's gonna be a massive increase from where we've been in, in, in the recent past, like as in last, last Tuesday. So is there, you know, this is sort of a philosophical question. We talked a little earlier about this idea of the quantitative versus qualitative difference in computing horsepower. Do we feel like we're at a point where there's gonna be an inflection in terms of what AI can actually deliver? Yeah. Based on current technology just doing it more, better, faster, cheaper? Yeah. Or do we, or do we need this leap to quantum computing to, to get there? >>Yeah. I look, >>I think we're, and I was having some really interesting conversations with, with, with customers that whose job it is to run very, very large, very, very complex clusters. And we're talking a little bit about quantum computing. Interesting thing about quantum computing is, you know, I think we're or we're a ways off still. And in order to make quantum computing work, you still need to have classical computing surrounding Right. Number one. Number two, with, with the advances that we're, we're seeing generation on generation with this, you know, what, what has moved from a kind of a three year, you know, call it a two to three year upgrade cycle to, to something that because of all of the technology that's being deployed into the industry is almost more continuous upgrade cycle. I, I'm personally optimistic that we are on the, the cusp of a new level of infrastructure modernization. >>And it's not just the, the computing power, it's not just the increases in GPUs. It's not, you know, those things are important, but it's things like power consumption, right? One of the, the, the ways that customers can do better in terms of power consumption and sustainability is by modernizing infrastructure. Looking to your point, a lot of people are, are running n minus one, N minus two. The stuff that's coming out now is, is much more energy efficient. And so I think there's a lot of, a lot of vectors that we're seeing in, in the market, whether it be technology innovation, whether it be be a drive for energy efficiency, whether it be the rise of AI and ml, whether it be all of the new silicon that's coming in into the portfolio where customers are gonna have a continuous reason to upgrade. I mean, that's, that's my thought. What do you think? >>Yeah, no, I think, I think that the, the, the objective numbers that are gonna be rolling out Yeah. That are starting to roll out now and in the near future. That's why it's really an exciting time. Yeah. I think those numbers are gonna support your point. Yeah. Because people will look and they'll say, Wait a minute, it used to be a dollar, but now it's $2. That's more expensive. Yeah. But you're getting 10 times as much Yeah. For half of the amount of power boom. And it's, and it's >>Done. Exactly. It's, it's a >>Tco It's, it's no brainer. It's Oh yeah. You, it gets to the point where it's, you look at this rack of amazing stuff that you have a personal relationship with and you say, I can't afford to keep you plugged in anymore. Yeah. >>And Right. >>The power is such a huge component of this. Yeah. It's huge, huge. >>Our customer, I mean, it's always a huge issue, but our customers, especially in Amia with what's going on over there are, are saying, I, you know, I need to upgrade because I need to be more energy efficient. >>Yeah. >>Yeah. I I, we were talking about 20 years from now, so you've been at Dell over 18 years. >>Yeah. It'll be 19 in in May. >>Congratulations. Yeah. What, what commitment, so 19 years from now in your, in your second Dell career. Yeah. What are we gonna be able to say then that perhaps we can't say now? >>Oh my gosh. Wow. 19 years from now. >>Yeah. I love this as an arbitrary number too. This is great. Yeah. >>38 year Dell career. Yeah. >>That might be a record. Yeah. >>And if you'd like to share the winners of Super Bowls and World Series in advance, like the world and the, the sports element act from back to the future. So we can play ball bets power and the >>Power ball, but, but any >>Point building Yeah. I mean this is what, what, what, what do you think ai, what's AI gonna deliver in the next decade? >>Yeah. I, I look, I mean, there are are, you know, global issues that advances in computing power will help us solve. And, you know, the, the models that are being built, the ability to generate a, a digital copy of the analog world and be able to run models and simulations on it is, is amazing. Truly. Yeah. You know, I, I was looking at some, you know, it's very, it's a very simple and pragmatic thing, but I think it's, it, it's an example of, of what could be, we were with one of our technology providers and they, they were, were showing us a digital simulation, you know, a digital twin of a factory for a car manufacturer. And they were saying that, you know, it used to be you had to build the factory, you had to put the people in the factory. You had to, you know, run cars through the factory to figure out sort of how you optimize and you know, where everything's placed. >>Yeah. They don't have to do that anymore. No. Right. They can do it all via simulation, all via digital, you know, copy of, of analog reality. And so, I mean, I think the, you know, the, the, the, the possibilities are endless. And, you know, 19 years ago, I had no idea I'd be sitting here so excited about hardware, you know, here we are baby. I think 19 years from now, hardware still matters. Yeah. You know, hardware still matters. I know software eats the world, the hardware still matters. Gotta run something. Yeah. And, and we'll be talking about, you know, that same type of, of example, but at a broader and more global scale. Well, I'm the knucklehead who >>Keeps waving his phone around going, There's one terabyte in here. Can you believe that one terabyte? Cause when you've been around long enough, it's like >>Insane. You know, like, like I've been to nasa, I live in Texas, I've been to NASA a couple times. They, you know, they talk about, they sent, you know, they sent people to the moon on, on way less, less on >>Too far less in our pocket computers. Yeah. It's, it's amazing. >>I am an optimist on, on where we're going clearly. >>And we're clearly an exciting visionary, like we said, said the gate. It's no surprise that people are using Dell's tech to realize their AI ecosystem dreams. Travis, thank you so much for being here with us David. Always a pleasure. And thank you for tuning in to the Cube Live from Dallas, Texas. My name is Savannah Peterson. We'll be back with more supercomputing soon.

(inspirational music) >> The history of high performance computing is unique and storied. You know, it's generally accepted that the first true supercomputer was shipped in the mid 1960s by Controlled Data Corporations, CDC, designed by an engineering team led by Seymour Cray, the father of Supercomputing. He left CDC in the 70's to start his own company, of course, carrying his own name. Now that company Cray, became the market leader in the 70's and the 80's, and then the decade of the 80's saw attempts to bring new designs, such as massively parallel systems, to reach new heights of performance and efficiency. Supercomputing design was one of the most challenging fields, and a number of really brilliant engineers became kind of quasi-famous in their little industry. In addition to Cray himself, Steve Chen, who worked for Cray, then went out to start his own companies. Danny Hillis, of Thinking Machines. Steve Frank of Kendall Square Research. Steve Wallach tried to build a mini supercomputer at Convex. These new entrants, they all failed, for the most part because the market at the time just wasn't really large enough and the economics of these systems really weren't that attractive. Now, the late 80's and the 90's saw big Japanese companies like NEC and Fujitsu entering the fray and governments around the world began to invest heavily in these systems to solve societal problems and make their nations more competitive. And as we entered the 21st century, we saw the coming of petascale computing, with China actually cracking the top 100 list of high performance computing. And today, we're now entering the exascale era, with systems that can complete a billion, billion calculations per second, or 10 to the 18th power. Astounding. And today, the high performance computing market generates north of $30 billion annually and is growing in the high single digits. Supercomputers solve the world's hardest problems in things like simulation, life sciences, weather, energy exploration, aerospace, astronomy, automotive industries, and many other high value examples. And supercomputers are expensive. You know, the highest performing supercomputers used to cost tens of millions of dollars, maybe $30 million. And we've seen that steadily rise to over $200 million. And today we're even seeing systems that cost more than half a billion dollars, even into the low billions when you include all the surrounding data center infrastructure and cooling required. The US, China, Japan, and EU countries, as well as the UK, are all investing heavily to keep their countries competitive, and no price seems to be too high. Now, there are five mega trends going on in HPC today, in addition to this massive rising cost that we just talked about. One, systems are becoming more distributed and less monolithic. The second is the power of these systems is increasing dramatically, both in terms of processor performance and energy consumption. The x86 today dominates processor shipments, it's going to probably continue to do so. Power has some presence, but ARM is growing very rapidly. Nvidia with GPUs is becoming a major player with AI coming in, we'll talk about that in a minute. And both the EU and China are developing their own processors. We're seeing massive densities with hundreds of thousands of cores that are being liquid-cooled with novel phase change technology. The third big trend is AI, which of course is still in the early stages, but it's being combined with ever larger and massive, massive data sets to attack new problems and accelerate research in dozens of industries. Now, the fourth big trend, HPC in the cloud reached critical mass at the end of the last decade. And all of the major hyperscalers are providing HPE, HPC as a service capability. Now finally, quantum computing is often talked about and predicted to become more stable by the end of the decade and crack new dimensions in computing. The EU has even announced a hybrid QC, with the goal of having a stable system in the second half of this decade, most likely around 2027, 2028. Welcome to theCUBE's preview of SC22, the big supercomputing show which takes place the week of November 13th in Dallas. theCUBE is going to be there. Dave Nicholson will be one of the co-hosts and joins me now to talk about trends in HPC and what to look for at the show. Dave, welcome, good to see you. >> Hey, good to see you too, Dave. >> Oh, you heard my narrative up front Dave. You got a technical background, CTO chops, what did I miss? What are the major trends that you're seeing? >> I don't think you really- You didn't miss anything, I think it's just a question of double-clicking on some of the things that you brought up. You know, if you look back historically, supercomputing was sort of relegated to things like weather prediction and nuclear weapons modeling. And these systems would live in places like Lawrence Livermore Labs or Los Alamos. Today, that requirement for cutting edge, leading edge, highest performing supercompute technology is bleeding into the enterprise, driven by AI and ML, artificial intelligence and machine learning. So when we think about the conversations we're going to have and the coverage we're going to do of the SC22 event, a lot of it is going to be looking under the covers and seeing what kind of architectural things contribute to these capabilities moving forward, and asking a whole bunch of questions. >> Yeah, so there's this sort of theory that the world is moving toward this connectivity beyond compute-centricity to connectivity-centric. We've talked about that, you and I, in the past. Is that a factor in the HPC world? How is it impacting, you know, supercomputing design? >> Well, so if you're designing an island that is, you know, tip of this spear, doesn't have to offer any level of interoperability or compatibility with anything else in the compute world, then connectivity is important simply from a speeds and feeds perspective. You know, lowest latency connectivity between nodes and things like that. But as we sort of democratize supercomputing, to a degree, as it moves from solely the purview of academia into truly ubiquitous architecture leverage by enterprises, you start asking the question, "Hey, wouldn't it be kind of cool if we could have this hooked up into our ethernet networks?" And so, that's a whole interesting subject to explore because with things like RDMA over converged ethernet, you now have the ability to have these supercomputing capabilities directly accessible by enterprise computing. So that level of detail, opening up the box of looking at the Nix, or the storage cards that are in the box, is actually critically important. And as an old-school hardware knuckle-dragger myself, I am super excited to see what the cutting edge holds right now. >> Yeah, when you look at the SC22 website, I mean, they're covering all kinds of different areas. They got, you know, parallel clustered systems, AI, storage, you know, servers, system software, application software, security. I mean, wireless HPC is no longer this niche. It really touches virtually every industry, and most industries anyway, and is really driving new advancements in society and research, solving some of the world's hardest problems. So what are some of the topics that you want to cover at SC22? >> Well, I kind of, I touched on some of them. I really want to ask people questions about this idea of HPC moving from just academia into the enterprise. And the question of, does that mean that there are architectural concerns that people have that might not be the same as the concerns that someone in academia or in a lab environment would have? And by the way, just like, little historical context, I can't help it. I just went through the upgrade from iPhone 12 to iPhone 14. This has got one terabyte of storage in it. One terabyte of storage. In 1997, I helped build a one terabyte NAS system that a government defense contractor purchased for almost $2 million. $2 million! This was, I don't even know, it was $9.99 a month extra on my cell phone bill. We had a team of seven people who were going to manage that one terabyte of storage. So, similarly, when we talk about just where are we from a supercompute resource perspective, if you consider it historically, it's absolutely insane. I'm going to be asking people about, of course, what's going on today, but also the near future. You know, what can we expect? What is the sort of singularity that needs to occur where natural language processing across all of the world's languages exists in a perfect way? You know, do we have the compute power now? What's the interface between software and hardware? But really, this is going to be an opportunity that is a little bit unique in terms of the things that we typically cover, because this is a lot about cracking open the box, the server box, and looking at what's inside and carefully considering all of the components. >> You know, Dave, I'm looking at the exhibitor floor. It's like, everybody is here. NASA, Microsoft, IBM, Dell, Intel, HPE, AWS, all the hyperscale guys, Weka IO, Pure Storage, companies I've never heard of. It's just, hundreds and hundreds of exhibitors, Nvidia, Oracle, Penguin Solutions, I mean, just on and on and on. Google, of course, has a presence there, theCUBE has a major presence. We got a 20 x 20 booth. So, it's really, as I say, to your point, HPC is going mainstream. You know, I think a lot of times, we think of HPC supercomputing as this just sort of, off in the eclectic, far off corner, but it really, when you think about big data, when you think about AI, a lot of the advancements that occur in HPC will trickle through and go mainstream in commercial environments. And I suspect that's why there are so many companies here that are really relevant to the commercial market as well. >> Yeah, this is like the Formula 1 of computing. So if you're a Motorsports nerd, you know that F1 is the pinnacle of the sport. SC22, this is where everybody wants to be. Another little historical reference that comes to mind, there was a time in, I think, the early 2000's when Unisys partnered with Intel and Microsoft to come up with, I think it was the ES7000, which was supposed to be the mainframe, the sort of Intel mainframe. It was an early attempt to use... And I don't say this in a derogatory way, commodity resources to create something really, really powerful. Here we are 20 years later, and we are absolutely smack in the middle of that. You mentioned the focus on x86 architecture, but all of the other components that the silicon manufacturers bring to bear, companies like Broadcom, Nvidia, et al, they're all contributing components to this mix in addition to, of course, the microprocessor folks like AMD and Intel and others. So yeah, this is big-time nerd fest. Lots of academics will still be there. The supercomputing.org, this loose affiliation that's been running these SC events for years. They have a major focus, major hooks into academia. They're bringing in legit computer scientists to this event. This is all cutting edge stuff. >> Yeah. So like you said, it's going to be kind of, a lot of techies there, very technical computing, of course, audience. At the same time, we expect that there's going to be a fair amount, as they say, of crossover. And so, I'm excited to see what the coverage looks like. Yourself, John Furrier, Savannah, I think even Paul Gillin is going to attend the show, because I believe we're going to be there three days. So, you know, we're doing a lot of editorial. Dell is an anchor sponsor, so we really appreciate them providing funding so we can have this community event and bring people on. So, if you are interested- >> Dave, Dave, I just have- Just something on that point. I think that's indicative of where this world is moving when you have Dell so directly involved in something like this, it's an indication that this is moving out of just the realm of academia and moving in the direction of enterprise. Because as we know, they tend to ruthlessly drive down the cost of things. And so I think that's an interesting indication right there. >> Yeah, as do the cloud guys. So again, this is mainstream. So if you're interested, if you got something interesting to talk about, if you have market research, you're an analyst, you're an influencer in this community, you've got technical chops, maybe you've got an interesting startup, you can contact David, david.nicholson@siliconangle.com. John Furrier is john@siliconangle.com. david.vellante@siliconangle.com. I'd be happy to listen to your pitch and see if we can fit you onto the program. So, really excited. It's the week of November 13th. I think November 13th is a Sunday, so I believe David will be broadcasting Tuesday, Wednesday, Thursday. Really excited. Give you the last word here, Dave. >> No, I just, I'm not embarrassed to admit that I'm really, really excited about this. It's cutting edge stuff and I'm really going to be exploring this question of where does it fit in the world of AI and ML? I think that's really going to be the center of what I'm really seeking to understand when I'm there. >> All right, Dave Nicholson. Thanks for your time. theCUBE at SC22. Don't miss it. Go to thecube.net, go to siliconangle.com for all the news. This is Dave Vellante for theCUBE and for Dave Nicholson. Thanks for watching. And we'll see you in Dallas. (inquisitive music)

>>Welcome back everyone to Cube's live coverage, VMware Explorer, 2022 formerly world. I've been saying now I gotta get that out. Dave, I've been sayingm world. It just kind of comes off the tongue when I'm tired, but you know, wall to wall coverage, again, back to back interviews all day two sets. This is a wrap up here with the analyst discussion. Got one more interview after this really getting the analyst's perspective around what we've been hearing and seeing, observing, and reporting on the cube. Again, two sets blue and green. We call them here on the show floor on Moscone west with the sessions upstairs, two floors of, of amazing content sessions, keynote across ed Moscone, north and south SBI here, cloud strategists with the cube. And of course, what event wouldn't be complete without SBE weighing in on the analysis. And, and, and I'm, you know, all kidding aside. I mean that because we've had great interactions around, you know, digging in you, you're like a roving analyst out there. And what's great about what you do is you're social. You're communicating, you're touching everybody out there, but you're also picking up the puzzle pieces. And we, you know, of course we recognize that cuz that's what we do, but you're out, we're on the set you're out on the floor and you know your stuff and, and you know, clouds. So how you, this is your wheelhouse. Great to see you. Good to >>See you. I'm good guys. Thank you. Thank you for having >>Me. So I mean, Dave and I were riffing going back earlier in this event and even before, during our super cloud event, we're reminded of the old OpenStack days. If you remember, Dave OpenStack was supposed to be the open source version of cloud. And that was a great ambition. And the cloud AATI at that time was very into it because it made a lot of sense. And the vision, all the infrastructure was code. Everything was lined up. Everything was religiously was on the table. Beautiful cloud future. Okay. 20 2009, 2010, where was Amazon? Then they just went off like a rocket ship. So cloud ended up becoming AWS in my opinion. Yeah. OpenStax then settled in, did some great things, but also spawns Kubernetes. Okay. So, you know, we've lived through thiss we've seen this movie. We were actually in the trenches on the front lines present at creation for cloud computing. >>Yeah. I was at Rackspace when the open stack was open sourced. I was there in, in the rooms and discussions and all that. I think OpenStack was given to the open source like prematurely. I usually like we left a toddler on the freeway. No, the toddler >>Got behind the wheel. Can't see over the dashboard. >>So we have learned over the years in last two decades, like we have seen the open source rise of open source and we have learned quite a few lessons. And one lesson we learned from there was like, don't let a project go out in the open, tell it mature enough with one vendor. So we did that prematurely with NASA, NASA and Rackspace gave the, the code from two companies to the open source community and then likes of IBM and HPE. No. Now HPE, they kind of hijacked the whole thing and then put a lot of developers on that. And then lot of us sort of second tier startup. >>But, but, but I remember not to interject, but at that time there wasn't a lot of pushback for letting them it wasn't like they infiltrated like a, the vendors always tried to worry about vendors coming in open source, but at that time was pretty people accepted them. And then it got off the rails. Then you remember the great API debate. You >>Called it a hail Mary to against AWS, which is, is what it was, what it was. >>It's true. Yeah. Ended up being right. But the, the battle started happening when you started seeing the network perimeters being discussed, you starting to see some of the, in the trenches really important conversations around how to make essentially cross cloud or super cloud work. And, and again, totally premature it continue. And, and what does that mean today? So, okay. Is VMware too early on their cross cloud? Are they, is multi-cloud ready? >>No >>For, and is it just vaporware? >>No, they're not too early, actually on, on, on, on that side they were premature to put that out there, but this is like very mature company, like in the ops area, you know, we have been using, we VMware stuff since 2000 early 2000. I, I was at commerce one when we started using it and yeah, it was for lab manager, you know, like, you know, put the labs >>Out desktop competition. >>Yeah, yeah. Kind of thing. So it, it matured pretty fast, but now it it's like for all these years they focused on the op site more. Right. And then the challenge now in the DevOps sort of driven culture, which is very hyped, to be honest with you, they have try and find a place for developers to plug in on the left side of the sort of whole systems, life cycle management sort of line, if you will. So I think that's a, that's a struggle for, for VMware. They have to figure that out. And they are like a tap Tansu application platform services. They, they have released a new version of that now. So they're trying to do that, but still they are from the sort of get ups to the, to the right, from that point to the right on the left side. They're lot more tooling to helpers use as we know, but they are very scattered kind of spend and scattered technology on the left side. VMware doesn't know how to tackle that. But I think, I think VMware should focus on the right side from the get ups to the right and then focus there. And then how in the multi-cloud cross cloud. >>Cause my sense is, they're saying, Hey, look, we're not gonna own the developers. I think they know that. And they think they're saying do develop in whatever world you want to develop in will embrace it. And then the ops guys, we, we got you covered, we got the standards, we have the consistency and you're our peeps. You tend then take it, you know, to, to the market. Is that not? I mean, it seems like a viable strategy. I >>Mean, look at if you're VMware Dave and start, you know, this where they are right now, the way they missed the cloud. And they had to reboot that with jazzy and, and, and Raghu to do the databases deal. It's essentially VMware hosted on AWS and clients love it cuz it's clarity. Okay. It's not vCloud air. So, so if you're them right now, you seeing yourself, wow. We could be the connective tissue between all clouds. We said this from day one, when Kubernetes was hitting in the scene, whoever can make this, the interoperability concept of inter clouding and connect clouds so that there could be spanning of applications and data. We didn't say data, but we said, you know, creating that nice environment of multiple clouds. Okay. And again, in concept, that sounds simple, but if you're VMware, you could own that abstraction layer. So do you own it or do you seed the base and let it become a defacto organization? Like a super layer, super pass layer and then participate in it? Or are you the middleware yourself? We heard AJ Patel say that. So, so they could be the middleware for at all. >>Aren't they? The infrastructure super cloud. I mean, that's what they're trying to be. >>Yeah. I think they're trying, trying to do that. It's it's I, I, I have said that many times VMware is bridged to the cloud, right? >>The sorry. Say bridge to >>The cloud. Yeah. Right. For, for enterprises, they have virtualized environments, mostly on VMware stacks. And another thing is I wanna mention touch on that is the number of certified professionals on VMware stack. There it's a huge number it's in tens of thousands. Right? So people who have got these certifications, they want to continue that sort of journey. They wanna leverage that. It's like, it's a Sunco if they don't use that going forward. And that was my question to, to during the press release yesterday, like are there new certifications coming into the, into the limelight? I, I think the VMware, if they're listening to me here somewhere, they will listen. I guess they should introduce a, a cross cloud certification for their stack because they want to be cross cloud or multi-cloud sort of vendor with one sort of single pane. So does actually Cisco and so do many others. But I think VMware is in a good spot. It's their market to lose. I, I, I call it when it comes to the multi-cloud for enterprise, especially for the legacy applications. >>Well, they're not, they have the enterprise they're super cloud enabler, Dave for the, for the enterprise, cuz they're not hyperscaler. Okay. They have all the enterprise customers who come here, we see them, we speak to them. We know them will mingle, but >>They have really good relationships with all the >>Hyperscale. And so those, those guys need a way to the cloud in a way that's cloud operation though. So, so if you say enterprises need their own super cloud, I would say VMware might wanna raise their hands saying we're the vendor to provide that. Yes, totally. And then that's the middleware role. So middleware isn't your classic stack middleware it's middle tissue. So you got, it's not a stack model anymore. It's completely different. >>Maybe, maybe my, my it's >>Not a stack >>Industry. Maybe my industry super cloud is too aspirational, but so let's assume for a second. You're not gonna have everybody doing their own clouds, like Goldman Sachs and, and capital one, even though we're seeing some evidence of that, even in that case, connecting my on-prem to the cloud and modernizing my application stack and, and having some kind of consistency between your on-prem and it's just call it hybrid, like real hybrid, true hybrid. They should dominate that. I mean, who is who, if it's not it's VMware and it's what red hat who else? >>I think red hat wants it too. >>Yeah. Well, red hat and red, hat's doing it with IBM consulting and they gotta be, they have great advantage there for all the banks. Awesome. But what, what about the other 500,000 customers that are >>Out there? If VMware could do what they did with the hypervisor, with virtualization and create the new thing for super cloud, AKA connecting clouds together. That's a, that's a holy grail move right >>There. But what about this PA layer? This Tansu and area which somebody on Twitter, there was a little SNAR come that's V realized just renamed, which is not. I mean, it's, it's from talking to Raghu unless he's just totally BSing us, which I don't think he is. That's not who he is. It's this new federated architecture and it's this, their super PAs layer and, and, and it's purpose built for what they're trying to do across clouds. This is your wheelhouse. What, what do you make of that? >>I think Tansu is a great effort. They have put in lot of other older products under that one umbrella Tansu is not a product actually confuses the heck out of the market. That it's not a product. It's a set of other products put under one umbrella. Now they have created another umbrella term with the newer sort of, >>So really is some yeah. >>Two >>Umbrella on there. So it's what it's pivotal. It's vRealize it's >>Yeah. We realize pivotal and, and, and older stack, actually they have some open source components in there. So, >>So they claim that this ragus claim, it's this new architecture, this new federated architecture graph database, low latency, real time ingestion. Well, >>AJ, AJ that's AJ's department, >>It sounded good. I mean, this is that >>Actually I think the newer, newer stuff, what they announced, that's very promising because it seems like they're building something from scratch. So, >>And it won't be, it won't be hardened for, but, but >>It won't be hardened for, but, >>But those, but they have a track record delivering. I mean, they gotta say that about yeah. >>They're engineering focus company. They have engineering culture. They're their software engineers are top. Not top not, >>Yes. >>What? >>Yeah. It's all relatives. If they, if the VMware stays the way they are. Well, >>Yeah, >>We'll get to that a second. What >>Do you mean? What are you talking >>About? They don't get gutted >>The elephant in the room if they don't get gutted and then, then we'll see it happens there. But right now I love, we love VMware. We've been covering them for 12 years and we've seen the trials, not without their own issues to work on. I mean, everyone needs to work on stuff, but you know, world class, they're very proud of their innovation, but I wanna ask you, what was your observations walking around the floor, talking to people? What was the sense of the messaging? Is it real in their minds? Are they leaning in, are they like enthused? Are they nervous, apprehensive? How would you categorize the attitude of the folks here that you've talked to or observed? >>Yeah. It at the individual product level, like the people are very confident what they're building, what they're delivering, but when it comes to the telling a cohesive story, if you go to all the VMware booth there, like it's hard to find anybody who can tell what, what are all the services under tens and how they are interconnected and what facilities they provide or they can't. They, I mean, most of the people who are there, they can are walking through the economic side of things, like how it will help you save money or, or how the TCR ROI will improve. They are very focused on because of the nature of the company, right. They're very focused on the technology only. So I think that that's the, that's what I learned. And another sort of gripe or negative I have about VMware is that they have their product portfolio is so vast and they are even spreading more thinly. And they're forced to go to the left towards developers because of the sheer force of hyperscalers. On one side on the, on the right side, they are forced to work with hyperscalers to do more like ops related improvements. They didn't mention AI or, or data. >>Yeah. Data storage management. >>That that was weak. That's true. During the, the keynote as well. >>And they didn't mention security and their security story, strong >>Security. I think they mentioned it briefly very briefly, very briefly. But I think their SCO story is good actually, but no is they didn't mention it properly, I guess. >>Yeah. There wasn't prominent in the keynote. It was, you know, and again, I understand why data wasn't P I, they wanted to say about data, >>Didn't make room for the developer story. I think this was very much a theatrical maneuver for Hawk and the employee morale and the ecosystem morale, Dave, then it had to do with the nuts bolt of security. They can come back to get that security. In my opinion, you know, I, I don't think that was as bad of a call as bearing the vSphere, giving more demos, which they did do later. But the keynote I thought was, was well done as targeted for all the negative sentiment around Broadcom and Broadcom had this, the acquisition agreement that they're, they are doing, they agree >>Was well done. I mean, >>You know, if I VMware, I would've done the same thing, look at this is a bright future. We're given that we're look at what we got. If you got this, it's on you. >>And I agree with you, but the, the, again, I don't, I don't see how you can't make security front and center. When it is the number one issue for CIOs, CSOs, CSOs boards or directors, they just, it was a miss. They missed it. Yeah. Okay. And they said, oh, well, there's only so much time, but, and they had to put the application development focus on there. I get that. But >>Another thing is, I think just keynote is just one sort of thing. One moment in this whole sort of continuous period, right. They, I think they need to have that narrative, like messaging done periodically, just like Amazon does, you know, like frequent events tapping into the practitioners on regional basis. They have to do that. Maybe it's a funding issue. Maybe it is some weakness on the, no, >>I think they planning, I talked to, we talked to the CMO and she said, Explorer is gonna be a road show. They're gonna go international with, it's gonna take a global, they're gonna have a lot of wood behind the arrow. They're gonna spend a lot of money on Explorer is what, they're, what we're seeing. And that's a good thing. You got a new brand, you gotta build it. >>You know, I would've done, I would've had, I would've had a shorter keynote on day one and doing, and then I would've done like a security day, day two. I would've dedicated the whole morning, day two keynote to security cuz their stories I think is that strong? >>Yeah. >>Yeah. And I don't know the developers side of things. I think it's hard for VMware to go too much to the left. The spend on the left is very scattered. You know, if you notice the tools, developers change their tools on freaking monthly basis, right? Yeah. Yeah. So it's hard to sustain that they on the very left side and the, the, the >>It's hard for companies like VMware to your point. And then this came up in super cloud and ins Rayme mentioned that developers drive everything, the patterns, what they like and you know, the old cliche meet them where they are. You know, honestly, this is kind of what AJ says is the right they're doing. And it's the right strategy meeting that develops where they are means give them something that they like. They like self-service they like to try stuff. They like to, they don't like it. They'll throw it away. Look at the success that comes like data, dog companies like that have that kind of offering with freemium and self-service to, to continue the wins versus jamming the tooling down their throat and selling >>Totally self-serve infrastructure for the, in a way, you know, you said they missed cloud, which they did V cloud air. And then they thought of got it. Right. It kind of did the same thing with pivotal. Right. It was almost like they forced to take pivotal, you know, by pivotal, right. For 2 billion or whatever it was. All right. Do something with it. Okay. We're gonna try to do something with it and they try to go out and compete. And now they're saying, Hey, let's just open it up. Whatever they want to use, let 'em use it. So unlike and I said this yesterday, unlike snowflake has to attract developers to build on their unique platform. Okay. I think VMware's taken a different approach saying use whatever you want to use. We're gonna help the ops guys. And that, to me, a new op >>Very sensitive, >>The new ops, the new ops guys. Yes. Yes. >>I think another challenge on the right right. Is on, on the op site is like, if, if you are cloud native, you are a new company. You just, when you're a startup, you are cloud native, right. Then it's hard for VMware to convince them to, Hey, you know, come to us and use this. Right. It's very hard. It is. They're a good play for a while. At least they, they can prolong their life by innovating along the way because of the, the skills gravity, I call it of the developers and operators actually that's their, they, they have a loyal community they have and all that stuff. And by the way, the name change for the show. I think they're trying to get out of that sort of culty kind of nature of the, their communities that they force. The communities actually can force the companies, not to do certain things certain way. And I've seen that happening. And >>Well, I think, I think they're gonna learn and they already walked back their messaging. Not that they said anything overtly, but you know, the Lori, the CMO clarified this significantly, which was, they never said that they wanted to replace VM world. Although the name change implies that. And what they re amplified after the fact is that this is gonna be a continuation of the community. And so, you know, it's nuanced, they're splitting hairs, but that's, to me walking back the, you know, the, the loyalty and, and look at let's face it. Anytime you have a loyal community, you do anything of change. People are gonna be bitching and moaning. Yeah. >>But I mean, knew, worked, explore, >>Work. It wasn't bad at all. It was not a bad look. It wasn't disastrous call. Okay. Not at all. I'm critical of the name change at first, but the graphics are amazing. They did an exceptional job on the branding. They did, did an exceptional job on how they handled the new logo, the new name, the position they, and a lot of people >>Showed >>Up. Yeah. It worked >>A busy busier than all time >>It worked. And I think they, they threaded the needle, given everything they had going on. I thought the event team did an exceptional job here. I mean, just really impressive. So hats up to the event team at, at VMware pulling off now, did they make profit? I don't know. It doesn't matter, you know, again, so much going on with Broadcom, but here being in Moscone west, we see people coming down the stairs here, Dave's sessions, you know, lot of people, a lot of buzz on the content sold out sessions. So again, that's the ecosystem. The people giving the talks, you know, the people in the V brown bag, you know, got the, the V tug. They had their meeting, you know, this week here, >>Actually the, the, the red hat, the, the integration with the red hat is another highlight of, of, they announced that, that you can run that style >>OpenShift >>And red hats, not here, >>Red hat now here, but yeah, but, but, but >>It was more developers, more, you know, >>About time. I would say, why, why did it take so long? That should >>Have happened. All right. Final question. So what's the bottom line. Give us the summary. What's your take, what's your analysis of VMware explore the event, what they did, what it means, what it's gonna mean when the event's over, what's gonna happen. >>I think VMware with the VMware Explorer have bought the time with the messaging. You know, they have promised certain things with newer announcements and now it, it, it is up to them to deliver that in a very sort of fast manner and build more hooks into other sort of platforms. Right? So that is very important. You cannot just be closed system people. Don't like those systems. You have to be part of the ecosystem. And especially when you are sitting on top of the actually four or four or more public clouds, Alibaba cloud was, they were saying that they're the only VMware is only VMware based offering in mainland China on top of the Alibaba. And they, they can go to other ones as well. So I think, especially when they're sitting on top of other cloud providers, they have to build hooks into other platforms. And if they can build a marketplace of their own, that'll be even better. I think they, >>And they've got the ecosystem for it. I mean, you saw it last night. I mean, all the, all the parties were hopping. I mean, there was, there's >>A lot of buzz. I mean, I pressed, I pressed them Dave hard. I had my little, my zingers. I wanted to push the buttons on one question that was targeted towards the answer of, are they gonna try to do much more highly competitive maneuvering, you know, get that position in the middleware. Are they gonna be more aggressive with frontal competitiveness or are they gonna take the, the strategy of open collaborative and every single data point points to collaborative totally hit Culbert. I wanna do out in the open. We're not just not, we're not one company. So I think that's the right play. If they came out and said, we're gonna be this, you know? >>Yeah. The one, the last thing, actually, the, the one last little idea I'm putting out out there since I went to the Dell world, was that there's a economics of creation of software. There's economics of operations of software. And they are very good on the operation economics of operations side of things that when I say economics, it doesn't mean money only. It also means a productivity practitioner, growth. Everything is in there. So I think these vendors who are not hyperscalers, they have to distinguish these two things and realize that they're very good on the right side economics of operations. And, and that will go a long way. Actually. I think they muddy the waters by when DevOps, DevOps, and then it's >>Just, well, I think Dave, we always we've had moments in time over the past 12 years covering VMware's annual conference, formally world now floor, where there were moments of that's pat Gelsinger, spinal speech. Yeah. And I remember he was under a siege of being fired. Yeah. There was a point in time where it was touch and go, and then everything kind of came together. That was a moment. I think we're at a moment in time here with VMware Dave, where we're gonna see what Broadcom does, because I think what hop 10 and Broadcom saw this week was an EBI, a number on the table that they know they can probably get or squeeze. And then they saw a future value and net present value of future state that you could, you gotta roll back and do the analysis saying, okay, how much is it worth all this new stuff worth? Is that gonna contribute to the EBITDA number that they want on the number? So this is gonna be a very interesting test because VMware did it, an exceptional job of laying out that they got some jewels in the oven. You >>Think about how resilient this company has been. I mean, em, you know, EMC picked them up for a song. It was 640 million or whatever it was, you know, about the public. And then you, another epic moment you'll recall. This was when Joe Tuchi was like the mafia Don up on stage. And Michael Dell was there, John Chambers with all the ecosystem CEOs and there was Tucci. And then of course, Michael Dell ends up owning this whole thing, right? I mean, when John Chambers should have owned the whole thing, I mean, it's just, it's been incredible. And then Dell uses VMware as a piggy bank to restructure its balance sheet, to pay off the EMC debt and then sells the thing for $60 billion. And now it's like, okay, we're finally free of all this stuff. Okay. Now Broadcom's gonna buy you. And, >>And if Michael Dell keeps all in stock, he'll be the largest shareholder of Broadcom and own it off. >>Well, and that's probably, you know, that's a good question is, is it's gonna, it probably a very tax efficient transaction. If he takes all stock and then he can, you know, own against it. I mean, that's, that's, >>That's what a history we're gonna leave it there. Start be great to have you Dave great analysis. Okay. We'll be back with more coverage here. Day two, winding down after the short break.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Okay. We're back to wrap up HPE discover 2022. The Cube's continuous coverage is day three. John furrier, Dave ante. We had a business friend that we met during the pandemic. A really interesting gentleman, norm Ette. He's the director of global technical marketing at Hewlett Packard enterprise, a real innovator norm. Great to see you. Thanks for making time for coming on >>The cube, gentlemen. Thank you. Thank you. I appreciate that. You're giving me the opportunity to bring it home. Yeah. You know, if I'm only gonna get one shot at it, it might as well be >>The last we always, we always like to bring the energy in the last segment because you know, the cube, we grind it out for three days. I mean, it's just such a great content injection. And so we love to wrap it up, especially with someone like yourself who can really help us convey the themes, but even more so when we look around here this entire ecosystem, you and your team built this. And so take us through that. >>Well, we did, you know, and it takes a village. You know, we have the core team, HPE global technical marketing, uh, which is my team. And then of course we're partnered with other parts of the, our marketing organizations on different pieces, different aspects. And then we have a tremendous team of vendors that we work with on a regular basis. Companies such as, you know, F two B and ivory and others that, you know, really kind of pitch in. And they're, they're kind of my, I call 'em my flex force. You know, we also have another group called promote live and we bring all these people together. And, and in addition, all the vendors, we have something like 380 employees that come from all different parts of the organization to, to land in Las Vegas, to man, these booths and staff, these, uh, staff, these exhibits. >>And so for one week, we get to really work as a, as a, a team, as a family, you know, there's no organizational borders, so to speak, you know, you know, we're a big company, everybody has, you know, different objectives and different things that they're focused on, but we get a chance to all get together and work as one, one team. And so that, that the people aspect is what's so exciting, I think this week. And I think I even saw some of your broadcast earlier. So I think it kind of, it kind of came through as well. Just the joy of, of being together, you know? Sure. Human beings <laugh> >>And, and H HP's got a new spring and its step, which so much focus brought to the table from Antonio and, you know, the team is the lining. >>Yeah, we do. And that's, you know, when you go, when we start talking about the design and you know, one of the things that, you know, we work on this months ahead of time. Yeah. Right. And so it's kinda like a spinning top, you know, we, we, we keep, we, we keep spinning that thing tightening up and then this week you put it on the table and just let it go. Yeah. Right. But it's that whole multi-month process of, of, of twisting that top around and getting it going and right at the middle and right at the centerpiece. And, uh, the core design principle and an ask from, uh, Antonio is that we make sure that we major on HPE, uh, GreenLake edge to cloud platform that, you know, it, it's a, obviously you've been talking about it all week. Yeah. Uh, we've been talking about it all week. It's a big focus of our company. And so right at the very center, we have our HPE GreenLake edge to cloud platform demonstration, and then everything in the showcase then radiates from that centerpiece, uh, you know, right, right. At, right at the nexus of all the activities. So the experience starts there and propagates its >>Way. Well, I wanna get into some of the themes and the set pieces you have here. Um, you are in technical marketing and this platform is a tech play. So it's not so much just solutions that you're enabling the theme this year is very much technical marketing. So there's edge, especially cloud data and edge is the big themes security's baked in throughout the whole set, right as well. And that messaging, but it's technical marketing right now. We had, you know, platform play uett packer is a platform. Google packer enterprise is a >>Platform. It is, and it's a, it is a, it's a software platform. Um, you, it, it really completes a cloud strategy. And when you really think about it, I, again, I know some of these numbers have been floating around. Um, but, uh, you know, 70% of all data is still staying OnPrem for good reasons, you know, and then 30% of it can be out there in the public cloud. Uh, so what you kind of have is an incomplete cloud strategy, if you will. And what's happened is that organizations have gotten spoiled a little bit by the cloud experience. Mm-hmm <affirmative> right. That, you know, I, you know, your, your dev teams say go, Hey, I just, I wanna work in a Azure. I wanna work in AWS. I love how I go through this process. Why can't I do that with my on-prem stuff? Why, you know, why, you know, I want that kind of experience. So it organizations are really being challenged about how to create that, that kind of service and that experience to their customers because expectations are not because >>Data ha it has to be inclusive. It can't be exclusive to just one part of the organization. >>Yeah. And so how did you, how did that impact obviously, cause GreenLake was coming together, you know, you got the multiple months in advance planning for this big event, right. A lot of lot work goes into it. What was some of the impact to the execution of this event, um, that you can share in terms of the set pieces? Some of the displays was there was there, I won't say radical cause it's not radical. It looks, it turned out great. But what are some of the popular things happening here? What worked, what resonated with customers and what was different from, from, uh, that GreenLake enabled you to do differently? >>Well, I mean, first the first thing is that we, we kind of had a high touch experience at that center point, right. That nexus, the hub of the activity, the GreenLake edge to club platform, uh, demonstration. And it started with us just kind of, you know, having the strategy about first of all, if you sh, if you guys show this and I know, I think maybe you have, when you enter in, we've got like this big aha moment, right. And that aha moment is that platform right in the center, surrounded with wonderful visuals above, below, you know, behind, uh, all around it. But we, we, we had to think about, okay, now I'm staring at this thing. What am I, how am I gonna experience it? So, uh, when I say a high touch experience, we start with a, what I call a platform generalist that would greet you up front, engage in the conversation, you know, so realize that, you know, Dave is a network operations director, he's got some keen interests. >>He has some sort of peripheral idea about what the, uh, HPE GreenLake edge cloud platform is about, but what can it really do for him? You know, what can do, what can he use? How can he use it? So we start at that level of conversation, you know, socialize the core services, the attributes, you know, the, the technology that is actually enabling it. And then as we've identified in our conversation that you're a network geek, you know, and you want to understand, you've heard about Aruba, you know, how's Aruba central play into that. How do the networking services play into that? And so for then we take that, that, that big leap and go up two steps up onto the platform. And we go over to the network specialist, what I, what I'm calling a platform specialist, uh, who understands all the things about the platform, but then is peaked in networking. And we have that conversation and you see how the Aruba customer can benefit by this evolution, uh, and how the different platform services combine to give a holistic experience across a company. And so when I'm an it ops director, and I'm trying to service my network, guys, my storage guys, my compute guys, my external cloud services guys, that this is an environment that I can, so you >>Have an experience where they come in, they can easily move to a point quickly in the display, on the platform >>And it's tailored for them. Exactly. Right. Exactly. That's the exactly. Right. And so if I transition over to you, you know, and you're my, you know, you're my specialist, you know, you're not saying, Hey, Dave, what brings you here today? What are you today? <laugh>, you know, I, I mean, you're prequalified, it's a prequalified conversation. We jump into it. And then that specialist is armed with knowledge as to where, okay, this guy is really interested in switching technology and switches as well. Well, that's demo five 12. Mm-hmm <affirmative>, you know, let me have one of my colleagues take you over there. So then you're, you're escorted over to demo five 12 to go to the next level or perhaps, and this has happened throughout the week that people want to take a test drive of the environment. And so we have the HPE GreenLake living lab, and we have a, a test drive environment right there. >>And so we bring you right to that test drive, where you can, you know, kick the tires yourself, you fire up a live environment. We have a series of exercises that you're taken through. And, uh, I think I've just checked with one of my colleagues where like, well over, you know, well, over 1100 experiences of people doing that here. And that lab has 25 seats, but also externally. Yeah. So right off of hpe.com, that same test drive experience that we're doing here. People can launch at home. And so we got in this morning, there were like four guys logged in from New Zealand, you know, doing exercises, which is pretty neat. So, so when you ask me the question, what are the design considerations, uh, that HPE GreenLake that we baked in and thought through it's again, that, Hey, it's a, it's a big thing. Yeah. It's a big, it's an experience. Let's start with you just digesting the, you know, the comp basic concepts. Then let's talk about your persona and how it directly maps to what you can do. And then if you want to get deeper, you know, we have the solutions that we design behind it, solution demos, and, and if you wanna drive it, let you know, buckle up. Let's >>Go. Yeah, you get right to a spot, multiple monitors, great experience, high touch. Um, that's awesome. I gotta ask you another question. Cause you've been, you know, pre pandemic, you've been doing a lot of this technical marketing and events and then virtual hit right now. We're back face to face, right? It's clear, Dave and I were just talking about our, on our opening day, year on day. One, people love to see each other back. Every event we've been to face to face. People are energized to a level. We didn't even see. What are you seeing here in terms of performance? Obviously, you got sales people here, you got executives here, you got customers right. Face to face, right. >>Doing belly to belly, >>Belly to belly, as Dave says, that's a positive, what's it like, explain what it's like. >>Well, I mean, you don't, you never know what you got until it's gone, right? >>Yeah. >>You, and so people didn't really realize that, Hey, we really needed to have this kind of touch and this, this kind of activity. And it was funny because people be before the pandemic, there was also a push to do a lot of virtual stuff, you know, economies of scale. Yeah. You know, some of that stuff works. Teams are making decisions, but then it all goes away and people realize how valuable, you know, just the conversations were, you know, meeting >>Somebody, relationships, meeting >>Somebody for a coffee, you know, talking through different bumping into colleagues than that. You haven't seen for years, or you worked with somebody and now they're doing this. And then you realize you have some sort of synergy with each other and you know, you can still help each other. And just the, just, you know, just the discovery <laugh> of being at discover, you know, and running into these different types of things. So, uh, well >>You think about it norm, you know, we, we've done plenty of stuff virtually we have, but I think we've talked maybe four times this week. Yeah. You've seen you here walking around the hallways. We saw you last night, right? Yeah. You just, that just wouldn't happen in your little virtual >>World. Yeah. I mean, not at all. And during that virtual era, and I think we'll look back on that and we're still gonna do virtual stuff >>Course, and we're learning, >>It's got value, but I just want to thank you guys for just being the cube and the whole team, you know, Frank, everybody just tremendous partners through that because you can still look at that content that we produced together last year and it's still relevant. We're still sharing it. It still has impact. We, we point, you know, we tell people, Hey, here's call to action. You're leaving. Discover by the way, there's these three or four pieces out on the cube that really go with, go at this topic. >>Right. That GreenLake event we did last year was phenomenal. >>It was, it was, and it was a partnership with you guys. And I, I, you know, I, I speak on, on behalf of many of my colleagues here at HPE, we just wanna thank the cube for all the support, creativity, uh, and how we got through that >>All together. We we'll back at you because norm you were a real innovator when John and I first met you, we were like, Hey, this guy, actually, he's gonna, he's gonna push us to some new levels. Technical >>Marketing know >>That's our, our team marketing. Like our team was a little nervous, a lot nervous actually, because you know, you do, you are not only demanding, but you're super creative. Well, thank you. And so you, you helped us, you know, up, up our game. >>Yeah. Thanks a lot. Yeah. You know, Frank was getting, Hey, Frank, Dave, can you guys do this? You >>Know, so yeah, we were on the background. >>I mean, but we were, we were growing and surviving and thriving together and getting through it, but what's coming out. The other side now is a new format. You mentioned virtual. That's not going away. Hybrid is a steady state for all of us. Even the cube. Yeah. So the new protocols and the new standards are emerging. And I think the newness of it scares people also like how do you do it? Um, who, whose role is it to take the virtual and digital? So this whole new set of experiences still coming out. Yeah. What's your vision? How do you see this? Cause we're face to face clearly is what everyone wants from school kids to adults. Right. We want face to face. Right. How does digital fit in? >>Well, I mean, that's, that's a, that's a really tricky question. I'll give you a, a, I'll kind of back into the answer a little bit. Um, you guys can see this, right, right behind us. We had this whole backdrop here, greetings from the edge of virtual reality experience. Well, we built that. We built that during the COVID era, so we could have experiences with people remotely. Right. Uh, and we used it for our executive summit, you know, last year for the virtual discovery, we shipped those Oculus headsets to everybody. They, everybody jumped into it. And so I was sitting there being a host, you know, with four CTOs that were scattered all over the world. So we were in cyberspace together. Right. And so of course being good, uh, you know, good business people we realized, Hey, this is pretty fun. So let's dust it off and bring it out here for the more general public. >>So again, it was like a 200 person, you know, uh, executive level experience and all of that, but it had tremendous value, different types of experiences. I recommend you try it if you ever have the opportunity. Um, so that's a way that we start emerging virtual reality and digital experiences to try to keep that human connection, but now we're using it again. And everybody's in these little pod rooms, six of them together. So they're having this experience in cyberspace and they're having it physically. Yeah. And so I think some, and everyone's enjoying being together and still in cyber space together. So I think when we start to build assets and we start to look at different types of things and experiences, we gotta think, we, we gotta think through that now. Right. You know, how is this, how is this investment or this, this experience, how's it gonna translate, you know, outside of these four walls, right. And how can we use it outside of these four walls, uh, and create, you know, a more engaging experience. So that's a little bit of a backing into that answer, but I think I'm, I'm, >>It's emerging. It's >>Important. Well, I'm saying it more as an example of us thinking through and trying to leverage. Yeah. >>I love it though. I mean, you always, you've always been struck me as a visionary and I, I loved that answer and I can just see, it's just gonna progress by the end of the decade. This is gonna become right. Uh, a a, you know, a normal sort of practice, and we're gonna bring people in from the outside and interacting. I love what you were saying about, yeah. Even though we're here physically, we're actually creating a virtual world within this physical pod. We are. Where can people discover more about that? About, about, about the shows, the content that >>Was here? Well on hpe.com, you can just launch into discover. We have a tremendous amount of content that's been recorded, keynote sponsor sessions, the cube they're dialed in all kinds of different pieces of assets that we've done. Um, I'll plug just another couple of things just to, again, to talk about the connectivity of things that we're doing. So one of the projects that I lead, uh, I am very proud to lead is HPE space born and our space born computer space, born computer two, flying a most powerful machine, uh, computer to ever fly in space. Uh, we've been up there for a year. We've done 24 different experiments over the year to, for the benefit of the entire scientific community. Um, also, you know, doing things for the ISS national lab in NASA, our partners up there, but what we've got is we've built a scale replica of the Columbus module, right? So this is, you know, this is a 28 by 12 foot module. Hey, we're bringing her home seriously. >>They're gonna pull the plugs. They're gonna pull the >>Plug on me soon. Right. So anyway, so we have that module built, right? And this is, uh, we work with a Hollywood production company. We've had it before, but you know, we we've customized it. We have a live link to the ISS station in there. And, and so we're talking about everything that we're doing there, but also in this virtual reality experience, we have you going on a space walk, right. And so we've, we've captured that as well. So we've, we're tying this physical and virtual experience together. Uh, and, uh, so it's a fun project. So you can check that >>Out. We did exit scale together during the pandemic, and that's when I first really got into to space point. It was awesome to see frontier announced actually breaking through the exo scale barrier. We, we were on the cusp, but we, we now see it breaking through. So, yeah. Congratulations on that. Thank you >>Very much. And, you know, a couple, you know, just couple other things that we're doing, that's pretty exciting. I don't, I don't wanna give away all my tricks, uh, but you know, we've organized our demonstrations through the customer lenses. So we have these customer journeys that we see people that are using our technology, you know, so I'm, I'm not talking about the storage business unit or, you know, the networking business unit, but how are our customers really trying to, you know, advance AI and machine learning, for example, how are they actually trying to, you know, protect their data? You know, the different things, the business issues, the business issues. Yeah. And so we've organized our demos through that, and we have these, these pods and then satellites, and you, you, you give you walk through that whole thing and it's addressing different aspects of that. >>Um, and then another thing that we've done is we have tours here, uh, as well, where, cuz there's so much content that people can take tours and you know, 1400 people have taken those tours. Uh, you know, and these are guided tours, headsets, curated, big numbers, designated places to go. And we see big traffic the first day or so and by design. And so we hit the highlights and then they decide how to use their valuable time later in the showcase about what they want to deep dive on. And so that's been a tremendous success for >>Us. Well norm thanks for bringing us on the tour of discover. Yeah. Well and really, you know, sharing that with our audience and you've been an awesome partner. And as you say, a great innovator, hope I can't wait to see what's next. All right. >>You so much. Hey, thanks for letting me on here guys. Welcome to our pleasure. I'm somebody I made. You're a Cub >>Alumni alumni. You're alumni. Welcome to alumni. So >>Guys great. Our week. That's a wrap on on day three, uh, Dave Valant day, John furrier for Lisa Martin. Don't forget to go to Silicon angle.com where we've got all the news, all the interviews that we've done this week, get written up and posted on Silicon angle.com. The cube.net I publish every week. Uh, my breaking analysis on, on, on wikibon.com. It's on a podcast. So check that out. Thanks to everybody. Thanks for the crew. Everybody back at the office. Really appreciate it. Great job. And we'll see you next time. All right.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Welcome back to the Venetian convention center. You're watching the Cube's coverage of HPE discover 2022. The first discover live discover in three years, 2019 was the last one. The cube we were just talking about. This has been at H HP discover. Now HPE since 2011, my co-host John furrier. We're pleased to welcome Phil Maru. Who's the executive vice president and general manager of HPE Aruba. And he's joined by David Hughes, the chief product and technology officer at HPE Aruba gentleman. Welcome to the cube. Good to see you. Thank you. Thank >>You. >>Okay, so you guys talk a lot, Phil, about the intelligent edge. Yep. Okay. What do you, what do you mean by that? >>Yeah, so we, well, we're kind of focused on, is providing technology to customers that sits out at the edge and typically the edge would be, uh, any location out of the data center or out of the cloud. So for the most part, our customers would deploy our technology either in their office premises or maybe retail premises shops, uh, maybe deploying out of the home where their employees are on a factory floor. And we're really talking about technology to connect both people and devices back to, um, systems and technology throughout an organization. So, but >>I, I, you know, sometimes I call it the near edge and the far edge yeah. Near, near edge. Maybe as we saw home Depot up on the stage yesterday far, Edge's like space. Right. You're including all of that. Right. That's >>Edge. >>Yeah. And actually we, we, we, you know, we've got a broad range of technology that actually works within the data center as well. So, you know, what we are focused on is providing, uh, network technology, software and services. And, you know, for the most part, our heritage is at the edge, but it's more pervasive than that. So >>If you have the edge, you got connectivity and power, that's an edge. How much, um, is the physical world being connected now you're seeing robotics automation. Yeah. Ex and with machine learning specifically in compute, really driving a new acceleration at the edge. What you, how do you guys view that? What's your reaction? Yeah. >>I think, look, it, I think as connectivity is improving and that's both in terms of wifi connectivity, so, you know, wifi technology continues to, uh, advance and also you've got this new kind of private 5g area, just generally connectivity is becoming more pervasive and that's helping some industries that haven't previously embraced it. And I think industrial is, is one of the big ones. So, you know, historically it was difficult for kind of car manufacturers to really enable a factory floor. But now the connectivity is connectivity is better. That gives them the opportunity to be able to really change how they do things. So >>David, if you do take an outside in view, mm-hmm <affirmative>, uh, and, and, and when you talk to customers, what are they telling you and how is that informing your product strategy? >>Yeah, well, you >>Know, I think there's, there's several themes we hear. One is, you know, it's really important, better work from anywhere they wanna enable their employees, um, to get the same experience, whether they're at home or on the road or in their branch office or at headquarters. Um, you know, people are also concerned that as they deploy, deploy all of this IOT and pursuit of digital transformation, they don't want those devices to be a weak point where someone breaks into one device and moves naturally, um, across the network. So they want to have this great experience for their customers and their users, but they wanna make sure that they're not compromising security, um, in any way. And so it's about getting that balance between ease of use and, and security. That's one of the primary things we hear, >>You know, Dave, one of the things we talked about many, many years ago was when hybrid and was starting to come out multi-cloud was on the, on the table early on. Uh, we were, we were saying, Hey, the data center is just a big edge, right? I mean, if you have cloud operations and you see what's going on with GreenLake here now, the momentum hybrid cloud is cloud operations, right? An edge off data centers to a big edge on premises. And you got the edge as you have cloud operations, like say GreenLake, plugging in partners and diverse environments. You're connecting, not just branch offices that are per perimeter based. You have no perimeter and you have now other companies connecting mm-hmm <affirmative> so you got data and you got network. How do you guys see that transition as GreenLake has a very big ecosystem part of it, partners and whatnot. >>Yeah. So, you know, I think for us, um, the ecosystem of partners that we have is critical in terms of delivering what our customers need. And, you know, I think one of the really important areas is around verticals. So, um, you know, when you think about different verticals, they have similar problems, but you need to tailor the solutions. Um, to each of those, you know, we are talking a bit about devices and people. When you look at say a healthcare environment, there can be 30 devices there for each patient. And, um, so there's connecting all those devices securely, but we have partners that will help pull all of that together that may be focused on, um, you know, medical environment that may focused on stadiums. They may be focused on industrial. Um, so having partners that understand those verticals and working closely with them to deliver solutions is important in our go to market. >>So another kind of product question and related to what you just said, David, I got connectivity, speed, reliability, cost security, or maybe a missing something. But you, you said earlier, you gonna gotta balance those. How do you do that? And do you do that for the specific use cases? Like for instance, you just mentioned stadiums and 81 and how do you balance those and, and do you tailor those for the use cases? >>Yeah, well, I think it depends on the customer and different people have different views about where they need to be. So some people are, are so afraid about security. They wanna be air gapped and completely separate than the internet. That would be one extreme mm-hmm <affirmative> other people, you know, look at it and see what's happening with COVID with everyone working from home with people being able to work from Starbucks or the airport. And they're beginning to think, well, why is the branch that much different? And so what I think we are seeing is, you know, a reevaluation of how people connect to, um, the apps they're using and, uh, you know, you, you, you've probably for sure heard people talking about zero trust, talking about micro segmentation. You know, I think what we we see is that people wanna be able to build a network in a way where rather than any device being able to talk to any device or any person, which is where the internet started, we wanna build to build networks where people or devices can only talk to the destinations that are necessary for them to do their job. >>And so a lot of the technology that we are building into the network is really about making security intrinsic by limiting what can talk to what that's >>Actually micro, micro segmentations, zero trust, um, these all point to a modern, the modern network, as you say, Antonio Neri was just on the cube, talking about programmability, substrate, the words like that come to mind, what is the modern network look like? I mean, you have to be agile. You have to be programmable. You have to have security. Can you describe in your words, what does the modern network these days need to look like? How should customers think about architecting them? What are some of the table stakes and what are some of the differentiators that customers need to do to have a modern network? >>Yeah, well, you covered off a coup a few quarter, one there with clarity and so on. So let me pick one that you didn't mention. And, and I, you know, I think we are seeing, you know, a lot of interest around network as a service. And, you know, when we think about network as a service, we think about it broadly, um, you know, for consumers, we're getting more and more used to buying things as a service versus buying a thing. When you, when you get Alexa, you care about how well she answers your questions, you don't care about what CPU is or how much Ram Alexa has. And likewise with networking, people are caring about the outcomes of keeping their employees connected, keeping their, their devices and systems running. And so what for us, what NASA is all about is that shift of thinking about a network as being a collection of devices that get managed to being a framework for connectivity and running it from the point of view of those outcomes. >>And so whether, you know, it's about CapEx versus OPEX or about do it yourself, managing the network yourself versus outsourcing that, um, or it's about the, you know, Greenfield versus brownfield, each of our customers has got a different starting point, but they're all getting heading towards this destination of being able to treat their network as a service. And so that is, you know, a key area of innovation for us and whether it's big customers like home Depot that you heard about yesterday, um, where we kind of manage everything for them on a, as on a store basis, um, for connectivity, um, or, you know, the recent, um, skew based nest that we launched, which is a really scalable foundation for our partners to build nest offerings around. Um, we see this as a key part of network modernization. Yeah. >>And one of the things, again, that's great stuff. Uh, infrastructure is code, which was really kind of pioneer the DevOps movement in cloud kind of as platform level. And you got data ops now and AI at the top of the stack, we were always wondering when network as code was gonna come, uh, and where you actually have it, where it's programmable. I mean, we all know what policies do do. They're good. That's all great network as code. >>Yeah. >>And that's the concept that's like DevOps, it's like, make it work just seamlessly, just be always on. And >>Yeah. And smart, you know, people are always looking for the, for the easy button. Um, and so they want, they want things to operate easily. They want it to be easy to manage. And, you know, I actually think there's a little bit of a, um, a conflict between networkers code and the easy button, right? So it depends on the class of customers. Some customers like financials, for instance, have a huge software development organizations that are extremely capable that could, that can go with program ability that want things as code. But the majority of the, of, of the verticals that we deal with, um, don't have those big captive software organizations. And so they're really looking for automation and simplicity and they wanna outsource that problem. So in Aruba central, we have invested a lot to make it really easy for our customers to, um, get what they need, you know, is that movement of zero code. It's more like zero code. They want, they want something packaged now >>The headless networks. Yeah. Low code, no code >>Kind of thing. Yeah, that's right. And, you know, obviously for people that have the sophistication that want to, um, do the most advanced things, we have APIs. And so we support that kind of programmable way of doing things. But I'd say that that's that's, those are more specialized customers. So >>Phil, yeah. Uh, is that the strategy? I mean, David listed off a number of, of factors here is that Aruba's strategy to modernize networks to actually create the easy button through network as a service is as simple as dial tone. Is that how we >>Should think? I mean, the way I think about the strategy is I think about it as a triangle, really, along the bottom, we've got the products and services that we offer and we continue to add more products and services. We either buy companies such as silver peak a couple of years ago, or we build, uh, additional products and by, and by the way, that's in response to customers who are frustrated with some other suppliers and wanna move on mass over to, uh, companies like ourselves. So at the bottom layer of the product and services, and then the other side of the triangle one would be NAS, which we talked about, which is kind of move to buying network and as a service. And then the other side of the triangle is the platform, which for us is river central, which is part of HP GreenLake. And that's really all about, you know, kind of making it easy for customers to manage networks and Aruba central right now has got about 120,000 live customers on it. It connects to about 2 million devices and it's collecting a lot of data as well. So we anonymously collect data from all of our customers. We've got one and a half billion data points in the platform. And what we do is we let that data kind of look for anomalies and spot problems on the network before they happen for customers. >>So Aruba central predated, uh, uh, GreenLake GreenLake. Yeah. And, and so did you write to GreenLake through GreenLake APIs? How, what was the engineering work to accomplish that? >>Yeah, so really, um, Aruba central is kind of the Genesis of the GreenLake platform. So we took Aruba central and made it more generic okay. To build the GreenLake cloud platform. And you know, what we've done very recently is bring, bring Aruba into that unified infrastructure, along with storage and compute. So the same sign-on applies across all of HP's, um, products, the same way of managing licenses, managing devices. And so it provides us, uh, great foundation going forwards to, um, solve more comprehensively. Our customers automation requires. >>So, so just a quick follow. So Aruba actually was the main spring of GreenLake from the standpoint of okay. Sing, like you said, single sign on a platform that could evolve and become more, more generic. Yes. So, okay. So that was a nice little, um, bonus of the acquisition, you know, it's now the whole company >><laugh> Aruba taking over. >>Yeah. There's been a lot of work to, to, uh, you know, make it generic and, and widely applicable. Right. Yeah. Um, so, but >>You were purpose >>Built for yeah. Well it's foundational. Yes. So foundational for GreenLake, they built on top of it. Yeah. So you mentioned the data points, billions of data points. So I gotta ask you, cuz we're seeing this, um, copy more and more with machine learning, driving a lot of acceleration, cuz you can do simulations with machine learning and compute. We had Neil McDonal done earlier. He's a compute guy, you got networking. So with all this, um, these services and devices being put on and off the network humans, can't actually figure this out. You can discover what's on the network. How are you guys viewing the discovery and monitoring because there's no perimeter okay. On the network anymore. So I want to know what's out there. Um, how do you get through it? How does machine learning and AI play into this? >>Yeah. I mean, what we are trying to do is obviously flag trends for customers and say, Hey look, you know, we can either see something happening with your network. So there's a particular issue over here and we need to, I dunno, free up more capacity to solve that. Or we're looking at how their network is running and then comparing that with anonymized data from all of our other customers as well. So we're just helping find those problems. But yeah, you're right. I mean, I think it is becoming more of an issue for organizations, you know, how do you manage the network, >>But you see machine learning and AI playing a big part. >>Yeah, yeah. Yeah. I think, uh, AI massively and, and other technology advances as well that we make. So recently we, uh, also announced the availability of location awareness within our access points. And that might sound like a simple thing. But when network, when companies build out their networks, they often lose or they potentially could lose the records as to, well, where were the access points that we laid out and actually where are they not within, you know, 20 feet, but where actually are they? So we introduced kind of location, finding technology as well into our, uh, access points to make it easy for >>Customers. So Aruba one of the best, if not the best acquisition. I think that HP E has made, um, it's made by three par was, you know, good. It saved the storage business. Okay. That was more of a defensive play. Uh, but to see Aruba, it's a growth business. You guys report on it every quarter. Yeah. It's obviously a key ingredient to enable uh, uh, GreenLake and, and a that's another example, nimble was similar. We're much smaller sort of more narrow, but taking the AI ops piece and bringing it over. So it's, it was great to see HPE executing on some of its M and a as opposed to just leaving them alone and not really leveraging 'em. So guys, yeah. Congratulations really appreciate you guys coming on and explaining that. Congratulations on all the, all the great work and thanks for coming on the cube. Okay. >>Thank you guys. Yeah. Thanks for having us. >>All right, John, and I'll be back right after this short break. You're watching the cube, the leader in enterprise tech coverage from HPE Las Vegas, 2022. We'll be right back.

(upbeat music) >> Welcome back, everyone. It's theCUBE's coverage here in Las Vegas. I'm John Furrier, your host of theCUBE with re:MARS. Amazon re:MARS stands for machine learning, automation, robotics, and space. Lot of great content, accomplishment. AI meets meets robotics and space, industrial IoT, all things data. And we've got two great guests here to unpack the AI side of it. Manoj Suvarna, Managing Director at AI Ecosystem at Deloitte and Arte Merritt, Conversational AI Lead at AWS. Manoj, it's great to see you CUBE alumni. Art, welcome to theCUBE. >> Thanks for having me. I appreciate it. >> So AI's the big theme. Actually, the big disconnect in the industry has been the industrial OT versus IT, and that's happening. Now you've got space and robotics meets what we know is machine learning and AI which we've been covering. This is the confluence of the new IoT market. >> It absolutely is. >> What's your opinion on that? >> Yeah, so actually it's taking IoT beyond the art of possible. One area that we have been working very closely with AWS. We're strategic alliance with them. And for the past six years, we have been investing a lot in transformations. Transformation as it relate to the cloud, transformation as it relate to data modernization. The new edge is essentially on AI and machine learning. And just this week, we announced a new solution which is more focused around enhancing contact center intelligence. So think about the edge of the contact center, where we all have experiences around dealing with customer service and how to really take that to the next level, challenges that clients are facing in every part of that business. So clearly. >> Well, Conversational AI is a good topic. Talk about the relationship with Deloitte and Amazon for a second around AI because you guys have some great projects going on right now. That's well ahead of the curve on solving the scale problem 'cause there's a scale and problem, practical problem and then scale. What's the relationship with Amazon and Deloitte? >> We have a great alliance and relationship. Deloitte brings that expertise to help folks build high quality, highly effective conversational AI and enterprises are implementing these solutions to really try to improve the overall customer experience. So they want to help agents improve productivity, gain insights into the reasons why folks are calling but it's really to provide that better user experience being available 24/7 on channels users prefer to interact. And the solutions that Deloitte is building are highly advanced, super exciting. Like when we show demos of them to potential customers, the eyes light up and they want those solutions. >> John: Give an example when their eyes light up. What are you showing there? >> One solution, it's called multimodal interfaces. So what this is, is when you're call into like a voice IVR, Deloitte's solution will send the folks say a mobile app or a website. So the person can interact with both the phone touching on the screen and the voice and it's all kept in sync. So imagine you call the doctor's office or say I was calling a airline and I want to change my flight or sorry, change the seat. If they were to say, seat 20D is available. Well, I don't know what that means, but if you see the map while you're talking, you can say, oh, 20D is the aisle. I'm going to select that. So Deloitte's doing those kind of experiences. It's incredible. >> Manoj, this is where the magic comes into play when you bring data together and you have integration like this. Asynchronously or synchronously, it's all coming together. You have different platforms, phone, voice, silo databases potentially, the old way. Now, the new ways integrating. What makes it all work? What's the key to success? >> Yeah, it's certainly not a trivial feat. Bringing together all of these ecosystems of relationships, technologies all put together. We cannot do it alone. This is where we partner with AWS with some of our other partners like Salesforce and OneReach and really trying to bring a symphony of some of these solutions to bear. When you think about, going back to the example of contact center, the challenges that the pandemic posed in the last couple of years was the fact that who's a humongous rise in volume of number of calls. You can imagine people calling in asking for all kinds of different things, whether it's airlines whether it is doctor's office and retail. And then couple with that is the fact that there's the labor shortage. And how do you train agents to get them to be productive enough to be able to address hundreds or thousands of these calls? And so that's where we have been starting to, we have invested in those solutions bringing those technologies together to address real client problems, not just slideware but actual production environments. And that's where we launched this solution called TrueServe as of this week, which is really a multimodal solution that is built with preconceived notions of technologies and libraries where we can then be industry agnostic and be able to deliver those experiences to our clients based on whatever vertical or industry they're in. >> Take me through the client's engagement here because I can imagine they want to get a practical solution. They're going to want to have it up and running, not like a just a chatbot, but like they completely integrated system. What's the challenge and what's the outcome first set of milestones that you see that they do first? Do they just get the data together? Are they deploying a software solution? What's the use cases? >> There's a couple different use cases. We see there's the self-service component that we're talking about with the chatbots or voice IVR solutions. There's also use cases for helping the agents, so real-time agent assist. So you call into a contact center, it's transcribed in real time, run through some sort of knowledge base to give the agents possible answers to help the user out, tying in, say the Salesforce data, CRM data, to know more about the user. Like if I was to call the airline, it's going to say, "Are you calling about your flight to San Francisco tomorrow?" It knows who I am. It leverages that stuff. And then the key piece is the analytics knowing why folks are calling, not just your metrics around, length of calls or deflections, but what were the reasons people were calling in because you can use that data to improve your underlying products or services. These are the things that enterprise are looking for and this is where someone like Deloitte comes in, brings that expertise, speeds up the time to market and really helps the customers. >> Manoj, what was the solution you mentioned that you guys announced? >> Yeah, so this is called Deloitte TrueServe. And essentially, it's a combination of multiple different solutions combinations from AWS, from Salesforce, from OneReach. All put together with our joint engineering and really delivering that capability. Enhancing on that is the analytics component, which is really critical, especially because when you think about the average contact center, less than 10% of the data gets analyzed today, and how do you then extract value out of that data and be able to deliver business outcomes. >> I was just talking to some of the other day about Zoom. Everyone records their zoom meetings, and no one watches them. I mean, who's going to wade through that. Call center is even more high volume. We're talking about massive data. And so will you guys automate that? Do you go through every single piece of data, every call and bring it down? Is that how it works? >> Go ahead. >> There's just some of the things you can do. Analyze the calls for common themes, like figuring out like topic modeling, what are the reasons people are calling in. Summarizing that stuff so you can see what those underlying issues are. And so that could be, like I was mentioning, improving the product or service. It could also be for helping train the agents. So here's how to answer that question. And it could even be reinforcing positive experiences maybe an agent had a particular great call and that could be a reference for other folks. >> Yeah, and also during the conversation, when you think about within 60 to 90 seconds, how do you identify the intonation, the sentiments of the client customer calling in and be able to respond in real time for the challenges that they might be facing and the ability to authenticate the customer at the same time be able to respond to them. I think that is the advancements that we are seeing in the market. >> I think also your point about the data having residual values also excellent because this is a long tail of value in this data, like for predictions and stuff. So NASA was just on before you guys came on, talking about the Artemis project and all the missions and they have to run massive amounts of simulations. And this is where I've kind of seen the dots connect here. You can run with AI, run all the heavy lifting without human touching it to get that first ingestion or analysis, and then iterating on the data based upon what else happens. >> Manoj: Absolutely. >> This is now the new normal, right? Is this? >> It is. And it's transverse towards across multiple domains. So the example we gave you was around Conversational AI. We're now looking at that for doing predictive analytics. Those are some examples that we are doing jointly with AWS SageMaker. We are working on things like computer vision with some of the capabilities and what computer vision has to offer. And so when you think about the continuum of possibilities of what we can bring together from a tools, technology, services perspective, really the sky is the limit in terms of delivering these real experiences to our clients. >> So take me through a customer. Pretending I'm a customer, I get it. I got to do this. It's a competitive advantage. What are the outcomes that they are envisioning? What are some of the patterns you're seeing with customers? What outcomes are they expecting and what kind of high level upside you see them envisioning coming out of the data? >> So when you think about the CxOs today and the board, a lot of them are thinking about, okay, how do you build more efficiency in those system? How do you enable a technology or solution for them to not only increase their top line but as well as their bottom line? How do you enhance the customer experience, which in this case is spot on because when you think about, when customers go repeat to a vendor, it's based on quality, it's based on price. Customer experience is now topping that where your first experience, whether it's through a chat or a virtual assistant or a phone call is going to determine the longevity of that customer with you as a vendor. And so clearly, when you think about how clients are becoming AI fuel, this is where we are bringing in new technologies, new solutions to really push the art to the limit and the art of possible. >> You got a playbook too to do this? >> Yeah, yeah, absolutely. We have done that. And in fact, we are now taking that to the next level up. So something that I've mentioned about this before, which is how do you trust an AI system as it's building up. >> Hold on, I need to plug in. >> Yeah, absolutely. >> I put this here for a reason to remind me. No, but also trust is a big thing. Just put that trustworthy. This is an AI ethics question. >> Arte: It's a big. >> Let's get into it. This is huge. Data's data. Data can be biased from coming in >> Part of it, there are concerns you have to look at the bias in the data. It's also how you communicate through these automated channels, being empathetic, building trust with the customer, being concise in the answers and being accessible to all sorts of different folks and how they might communicate. So it's definitely a big area. >> I mean, you think about just normal life. We all lived situations where we got a text message from a friend or someone close to us where, what the hell, what are you saying? And they had no contextual bad feelings about it or, well, there's misunderstandings 'cause the context isn't there 'cause you're rapid fire them on the subway. I'm riding my bike. I stop and text, okay, I'm okay. Church response could mean I'm busy or I'm angry. Like this is now what you said about empathy. This is now a new dynamic in here. >> Oh, the empathy is huge, especially if you're say a financial institution or building that trust with folks and being empathetic. If someone's reaching out to a contact center, there's a good chance they're upset about something. So you have to take that. >> John: Calm them down first. >> Yeah, and not being like false like platitude kind of things, like really being empathetic, being inclusive in the language. Those are things that you have conversation designers and linguistics folks that really look into that. That's why having domain expertise from folks like Deloitte come in to help with that. 'Cause maybe if you're just building the chat on your own, you might not think of those things. But the folks with the domain expertise will say like, Hey, this is how you script it. It's the power of words, getting that message across clearly. >> The linguistics matter? >> Yeah, yeah. >> It does. >> By vertical too, I mean, you could pick any the tribe, whatever orientation and age, demographics, genders. >> All of those things that we take for granted as a human. When you think about trust, when you think about bias, when you think about ethics, it just gets amplified. Because now you're dealing with millions and millions of data points that may or may not be the right direction in terms of somebody's calling in depending on what age group they're in. Some questions might not be relevant for that age group. Now a human can determine that, but a bot cannot. And so how do you make sure that when you look at this data coming in, how do you build models that are ethically aware of the contextual algorithms and the alignment with it and also enabling that experience to be much enhanced than taking it backwards, and that's really. >> I can imagine it getting better with as people get scaled up a bit 'cause then you're going to have to start having AI to watch the AI at some point, as they say. Where are we in the progress in the industry right now? Because I know there's been a lot of news stories around, ethics and AI and bias and it's a moving train actually, but still problems are going to be solved. Are we at the tipping point yet? Are we still walking in before we crawl or crawling before we walk? I should say, I mean, where are we? >> I think we are in between a crawling or walk phase. And the reason for that is because it varies depending on whether you're regulated industry or unregulated. In the regulated industry, there are compliance regulations requirements, whether it's government whether it's banking, financial institutions where they have to meet Sarbanes-Oxley and all kinds of compliance requirements, whereas an unregulated industry like retail and consumer, it is anybody's gain. And so the reality of it is that there is more of an awareness now. And that's one of the reasons why we've been promoting this jointly with AWS. We have a framework that we have established where there are multiple pillars of trust, bias, privacy, and security that companies and organizations need to think about. Our data scientists, ML engineers need to be familiar with it, but because while they're super great in terms of model building and development, when it comes to the business, when it comes to the client or a customer, it is super important for them to trust this platform, this algorithm. And that is where we are trying to build that momentum, bring that awareness. One of my colleagues has written this book "Trustworthy AI". We're trying to take the message out to the market to say, there is a framework. We can help you get there. And certainly that's what we are doing. >> Just call Deloitte up and you're going to take care of them. >> Manoj: Yeah. >> On the Amazon side, Amazon Web Services. I always interview Swami every year at re:Invent and he always get the updates. He's been bullish on this for a long time on this Conversational AI. What's the update on the AWS side? Where are you guys at? What's the current trends that you're riding? What wave are you riding right now? >> So some of the trends we see in customer interest, there's a couple of things. One is the multimodal interfaces we we're just chatting about where the voice IVA is synced with like a web or mobile experience, so you take that full advantage of the device. The other is adding additional AI into the Conversational AI. So one example is a customer that included intelligent document processing as part of the chatbot. So instead of typing your name and address, take a photo of your driver's license. It was an insurance onboarding chatbot, so you could take a photo of your existing insurance policy. It'll extract that information to build the new insurance policy. So folks get excited about that. And the third area we see interest is what's called multi-bot orchestration. And this is where you can have one main chatbot. Marshall user across different sub-chatbots based on the use case persona or even language. So those things get people really excited and then AWS is launching all sorts of new features. I don't know which one is coming out. >> I know something's coming out tomorrow. He's right at corner. He's big smile on his face. He wouldn't tell me. It's good. >> We have for folks like the closer alliance relationships, we we're able to get previews. So there a preview of all the new stuff. And I don't know what I could, it's pretty exciting stuff. >> You get in trouble if you spill the beans here. Don't, be careful. I'll watch you. We'll talk off camera. All exciting stuff. >> Yeah, yeah. I think the orchestrator bot is interesting. Having the ability to orchestrate across different contextual datasets is interesting. >> One of the areas where it's particularly interesting is in financial services. Imagine a bank could have consumer accounts, merchant accounts, investment banking accounts. So if you were to chat with the chatbot and say I want to open account, well, which account do you mean? And so it's able to figure out that context to navigate folks to those sub-chatbots behind the scenes. And so it's pretty interesting style. >> Awesome. Manoj while we're here, take a minute to quickly give a plug for Deloitte. What your program's about? What customers should expect if they work with you guys on this project? Give a quick commercial for Deloitte. >> Yeah, no, absolutely. I mean, Deloitte has been continuing to lead the AI field organization effort across our client base. If you think about all the Fortune 100, Fortune 500, Fortune 2000 clients, we certainly have them where they are in advanced stages of multiple deployments for AI. And we look at it all the way from strategy to implementation to operational models. So clients don't have to do it alone. And we are continuing to build our ecosystem of relationships, partnerships like the alliances that we have with AWS, building the ecosystem of relationships with other emerging startups, to your point about how do you continue to innovate and bring those technologies to your clients in a trustworthy environment so that we can deliver it in production scale. That is essentially what we're driving. >> Well, Arte, there's a great conversation and the AI will take over from here as we end the segment. I see a a bot coming on theCUBE later and there might be CUBE be replaced with robots. >> Right, right, right, exactly. >> I'm John Furrier, calling from Palo Alto. >> Someday, CUBE bot. >> You can just say, Alexa do my demo for me or whatever it is. >> Or digital twin for John. >> We're going to have a robot on earlier do a CUBE interview and that's Dave Vellante. He'd just pipe his voice in and be fun. Well, thanks for coming on, great conversation. >> Thank you. Thanks for having us. >> CUBE coverage here at re:MARS in Las Vegas. Back to the event circle. We're back in the line. Got re:Inforce and don't forget re:Invent at the end of the year. CUBE coverage of this exciting show here. Machine learning, automation, robotics, space. That's MARS, it's re:MARS. I'm John Furrier. Thanks for watching. (gentle music)