>>Good afternoon everyone, and thank you so much for joining us. My name is Savannah Peterson, joined by my co-host Paul for the afternoon. Very excited. Oh, Savannah. Hello. I'm, I'm pumped for this. This is our first bit together. Exactly. >>It's gonna be fun. Yes. We have a great guest to kick off with. >>We absolutely do. We're at Supercomputing 2022 today, and very excited to talk to our next guest. We're gonna be talking about data at scale and data that really matters to us joining us. Kelly Gayer, thank you so much for being here and you are with tech. Tell everyone what TAC is. >>Tech is the Texas Advanced Computing Center at the University of Texas at Austin. And thank you so much for having me here. >>It is wonderful to have you. Your smile's contagious. And one of the themes that's come up a lot with all of our guests, and we just talked about it, is how good it is to be back in person, how good it is to be around our hardware, community tech. You did some very interesting research during the pandemic. Can you tell us about that? >>I can. I did. So when we realized sort of mid-March, we realized that, that this was really not normal times and the pandemic was statement. Yes. That pandemic was really gonna touch everyone. I think a lot of us at the center and me personally, we dropped everything to plug in and that's what we do. So UT's tagline is what starts here changes the world and tax tagline is powering discoveries that change the world. So we're all about impact, but I plugged in with the research group there at UT Austin, Dr. Lauren Myers, who's an epidemiologist, and just we figured out how to plug in and compute so that we could predict the spread of, of Covid 19. >>And you did that through the use of mobility data, cell phone signals. Tell us more about what exactly you were choreographing. >>Yeah, so that was really interesting. Safe graph during the pandemic made their mobility data. Typically it was used for marketing purposes to know who was going into Walmart. The offenses >>For advertising. >>Absolutely, yeah. They made all of their mobility data available for free to people who were doing research and plugging in trying to understand Covid. 19, I picked that data up and we used it as a proxy for human behavior. So we knew we had some idea, we got weekly mobility updates, but it was really mobility all day long, you know, anonymized. I didn't know who they were by cell phones across the US by census block group or zip code if we wanted to look at it that way. And we could see how people were moving around. We knew what their neighbor, their home neighborhoods were. We knew how they were traveling or not traveling. We knew where people were congregating, and we could get some idea of, of how people were behaving. Were they really, were they really locking down or were they moving in their neighborhoods or were they going outside of their neighborhoods? >>What a, what a fascinating window into our pandemic lives. So now that you were able to do this for this pandemic, as we look forward, what have you learned? How quickly could we forecast? What's the prognosis? >>Yeah, so we, we learned a tremendous amount. I think during the pandemic we were reacting, we were really trying. It was a, it was an interesting time as a scientist, we were reacting to things almost as if the earth was moving underneath us every single day. So it was something new every day. And I've told people since I've, I haven't, I haven't worked that hard since I was a graduate student. So it was really daylight to dark 24 7 for a long period of time because it was so important. And we knew, we, we knew we were, we were being a part of history and affecting something that was gonna make a difference for a really long time. And, and I think what we've learned is that indeed there is a lot of data being collected that we can use for good. We can really understand if we get organized and we get set up, we can use this data as a means of perhaps predicting our next pandemic or our next outbreak of whatever. It is almost like using it as a canary in the coal mine. There's a lot in human behavior we can use, given >>All the politicization of, of this last pandemic, knowing what we know now, making us better prepared in theory for the next one. How confident are you that at least in the US we will respond proactively and, and effectively when the next one comes around? >>Yeah, I mean, that's a, that's a great question and, and I certainly understand why you ask. I think in my experience as a scientist, certainly at tech, the more transparent you are with what you do and the more you explain things. Again, during the pandemic, things were shifting so rapidly we were reacting and doing the best that we could. And I think one thing we did right was we admitted where we felt uncertain. And that's important. You have to really be transparent to the general public. I, I don't know how well people are gonna react. I think if we have time to prepare, to communicate and always be really transparent about it. I think those are three factors that go into really increasing people's trust. >>I think you nailed it. And, and especially during times of chaos and disaster, you don't know who to trust or what to believe. And it sounds like, you know, providing a transparent source of truth is, is so critical. How do you protect the sensitive data that you're working with? I know it's a top priority for you and the team. >>It is, it is. And we, we've adopted the medical mantra, do no harm. So we have, we feel a great responsibility there. There's, you know, two things that you have to really keep in mind when you've got sensitive data. One is the physical protection of it. And so that's, that's governed by rule, federal rules, hipaa, ferpa, whatever, whatever kind of data that you have. So we certainly focus on the physical protection of it, but there's also sort of the ethical protection of it. What, what is the quote? There's lies, damn lies and statistics. >>Yes. Twain. >>Yeah. So you, you really have to be responsible with what you're doing with the data, how you're portraying the results. And again, I think it comes back to transparency is is basically if people are gonna reproduce what I did, I have to be really transparent with what I did. >>I, yeah, I think that's super important. And one of the themes with, with HPC that we've been talking about a lot too is, you know, do people trust ai? Do they trust all the data that's going into these systems? And I love that you just talked about the storytelling aspect of that, because there is a duty, it's not, you can cut data kind of however you want. I mean, I come from marketing background and we can massage it to, to do whatever we want. So in addition to being the deputy director at Tech, you are also the DEI officer. And diversity I know is important to you probably both as an individual, but also in the work that you're doing. Talk to us about that. >>Yeah, I mean, I, I very passionate about diversity, equity and inclusion in a sense of belongingness. I think that's one of the key aspects of it. Core >>Of community too. >>I got a computer science degree back in the eighties. I was akin to a unicorn in a, in an engineering computer science department. And, but I was really lucky in a couple of respects. I had a, I had a father that was into science that told me I could do anything I, I wanted to set my mind to do. So that was my whole life, was really having that support system. >>He was cheers to dad. >>Yeah. Oh yeah. And my mom as well, actually, you know, they were educators. I grew up, you know, in that respect, very, very privileged, but it was still really hard to make it. And I couldn't have told you back in that time why I made it and, and others didn't, why they dropped out. But I made it a mission probably back, gosh, maybe 10, 15 years ago, that I was really gonna do all that I could to change the needle. And it turns out that there are a number of things that you can do grassroots. There are certainly best practices. There are rules and there are things that you really, you know, best practices to follow to make people feel more included in an organization, to feel like they belong it, shared mission. But there are also clever things that you can do with programming to really engage students, to meet people and students where they are interested and where they are engaged. And I think that's what, that's what we've done over, you know, the course of our programming over the course of about maybe since 2016. We have built a lot of programming ATAC that really focuses on that as well, because I'm determined the needle is gonna change before it's all said and done. It just really has to. >>So what, what progress have you made and what goals have you set in this area? >>Yeah, that, that's a great question. So, you know, at first I was a little bit reluctant to set concrete goals because I really didn't know what we could accomplish. I really wasn't sure what grassroots efforts was gonna be able to, you're >>So honest, you can tell how transparent you are with the data as well. That's >>Great. Yeah, I mean, if I really, most of the successful work that I've done is both a scientist and in the education and outreach space is really trust relationships. If I break that trust, I'm done. I'm no longer effective. So yeah, I am really transparent about it. But, but what we did was, you know, the first thing we did was we counted, you know, to the extent that we could, what does the current picture look like? Let's be honest about it. Start where we are. Yep. It was not a pretty picture. I mean, we knew that anecdotally it was not gonna be a great picture, but we put it out there and we leaned into it. We said, this is what it is. We, you know, I hesitated to say we're gonna look 10% better next year because I'm, I'm gonna be honest, I don't always know we're gonna do our best. >>The things that I think we did really well was that we stopped to take time to talk and find out what people were interested in. It's almost like being present and listening. My grandmother had a saying, you have two errors in one mouth for a reason, just respect the ratio. Oh, I love that. Yeah. And I think it's just been building relationships, building trust, really focusing on making a difference, making it a priority. And I think now what we're doing is we've been successful in pockets of people in the center and we are, we are getting everybody on board. There's, there's something everyone can do, >>But the problem you're addressing doesn't begin in college. It begins much, much, that's right. And there's been a lot of talk about STEM education, particularly for girls, how they're pushed out of the system early on. Also for, for people of color. Do you see meaningful progress being made there now after years of, of lip service? >>I do. I do. But it is, again, grassroots. We do have a, a, a researcher who was a former teacher at the center, Carol Fletcher, who is doing research and for CS for all we know that the workforce, so if you work from the current workforce, her projected workforce backwards, we know that digital skills of some kind are gonna be needed. We also know we have a, a, a shortage. There's debate on how large that shortage is, but about roughly about 1 million unmet jobs was projected in 2020. It hasn't gotten a lot better. We can work that problem backwards. So what we do there is a little, like a scatter shot approach. We know that people come in all forms, all shapes, all sizes. They get interested for all different kinds of reasons. We expanded our set of pathways so that we can get them where they can get on to the path all the way back K through 12, that's Carol's work. Rosie Gomez at the center is doing sort of the undergraduate space. We've got Don Hunter that does it, middle school, high school space. So we are working all parts of the problem. I am pretty passionate about what we consider opportunity youth people who never had the opportunity to go to college. Is there a way that we can skill them and get, get them engaged in some aspect and perhaps get them into this workforce. >>I love that you're starting off so young. So give us an example of one of those programs. What are you talking to kindergartners about when it comes to CS education? >>You know, I mean, gaming. Yes. Right. It's what everybody can wrap their head around. So most kids have had some sort of gaming device. You talk in the context, in the context of something they understand. I'm not gonna talk to them about high performance computing. It, it would go right over their heads. And I think, yeah, you know, I, I'll go back to something that you said Paul, about, you know, girls were pushed out. I don't know that girls are being pushed out. I think girls aren't interested and things that are being presented and I think they, I >>Think you're generous. >>Yeah. I mean, I was a young girl and I don't know why I stayed. Well, I do know why I stayed with it because I had a father that saw something in me and I had people at critical points in my life that saw something in me that I didn't see. But I think if we ch, if we change the way we teach it, maybe in your words they don't get pushed out or they, or they won't lose interest. There's, there's some sort of computing in everything we do. Well, >>Absolutely. There's also the bro culture, which begins at a very early >>Age. Yeah, that's a different problem. Yeah. That's just having boys in the classroom. Absolutely. You got >>It. That's a whole nother case. >>That's a whole other thing. >>Last question for you, when we are sitting here, well actually I've got, it's two parter, let's put it that way. Is there a tool or something you wish you could flick a magic wand that would make your job easier? Where you, you know, is there, can you identify the, the linchpin in the DEI challenge? Or is it all still prototyping and iterating to figure out the best fit? >>Yeah, that is a, that's a wonderful question. I can tell you what I get frustrated with is that, that >>Counts >>Is that I, I feel like a lot of people don't fully understand the level of effort and engagement it takes to do something meaningful. The >>Commitment to a program, >>The commitment to a program. Totally agree. It's, there is no one and done. No. And in fact, if I do that, I will lose them forever. They'll be, they will, they will be lost in the space forever. Rather. The engagement is really sort of time intensive. It's relationship intensive, but there's a lot of follow up too. And the, the amount of funding that goes into this space really is not, it, it, it's not equal to the amount of time and effort that it really takes. And I think, you know, I think what you work in this space, you realize that what you gain is, is really more of, it's, it really feels good to make a difference in somebody's life, but it's really hard to do on a shoer budget. So if I could kind of wave a magic wand, yes, I would increase understanding. I would get people to understand that it's all of our responsibility. Yes, everybody is needed to make the difference and I would increase the funding that goes to the programs. >>I think that's awesome, Kelly, thank you for that. You all heard that. More funding for diversity, equity, and inclusion. Please Paul, thank you for a fantastic interview, Kelly. Hopefully everyone is now inspired to check out tac perhaps become a, a Longhorn, hook 'em and, and come deal with some of the most important data that we have going through our systems and predicting the future of our pandemics. Ladies and gentlemen, thank you for joining us online. We are here in Dallas, Texas at Supercomputing. My name is Savannah Peterson and I look forward to seeing you for our next segment.

>>We are back in the final stretch at Supercomputing 22 here in Dallas. I'm your host Paul Gillum with my co-host Dave Nicholson, and we've been talking to so many smart people this week. It just, it makes, boggles my mind are next guest. J Poso is the HPC and AI technology strategist at Dell. Jay also has a PhD in astronomy from the University of Texas. And I'm guessing you were up watching the Artemis launch the other night? >>I, I wasn't. I really should have been, but, but I wasn't, I was in full super computing conference mode. So that means discussions at, you know, various venues with people into the wee hours. >>How did you make the transition from a PhD in astronomy to an HPC expert? >>It was actually really straightforward. I did theoretical astrophysics and I was modeling what white dwarfs look like when they create matter and then explode as type one A super Novi, which is a class of stars that blow up. And it's a very important class because they blow up almost exactly the same way. So if you know how bright they are physically, not just how bright they appear in the sky, but if you can determine from first principles how bright they're, then you have a standard ruler for the universe when they go off in a galaxy, you know how far the galaxy is about how faint it is. So to model these though, you had to understand equations of physics, including electron degeneracy pressure, as well as normal fluid dynamics kinds of of things. And so you were solving for an explosive burning front, ripping through something. And that required a supercomputer to have anywhere close to the fat fidelity to get a reasonable answer and, and hopefully some understanding. >>So I've always said electrons are degenerate. I've always said it and I, and I mentioned to Paul earlier, I said, finally we're gonna get a guest to consort through this whole dark energy dark matter thing for us. We'll do that after, after, after the segment. >>That's a whole different, >>So, well I guess super computing being a natural tool that you would use. What is, what do you do in your role as a strategist? >>So I'm in the product management team. I spend a lot of time talking to customers about what they want to do next. HPC customers are always trying to be maximally productive of what they've got, but always wanting to know what's coming next. Because if you think about it, we can't simulate the entire human body cell for cell on any supercomputer day. We can simulate parts of it, cell for cell or the whole body with macroscopic physics, but not at the, you know, atomic level, the entire organism. So we're always trying to build more powerful computers to solve larger problems with more fidelity and less approximations in it. And so I help people try to understand which technologies for their next system might give them the best advance in capabilities for their simulation work, their data analytics work, their AI work, et cetera. Another part of it is talking to our great technology partner ecosystem and learning about which technologies they have. Cause it feeds the first thing, right? So understanding what's coming, and Dell has a, we're very proud of our large partner ecosystem. We embrace many different partners in that with different capabilities. So understanding those helps understand what your future systems might be. That those are two of the major roles in it. Strategic customers and strategic technologies. >>So you've had four days to wander the, this massive floor here and lots of startups, lots of established companies doing interesting things. What have you seen this week that really excites you? >>So I'm gonna tell you a dirty little secret here. If you are working for someone who makes super computers, you don't get as much time to wander the floor as you would think because you get lots of meetings with people who really want to understand in an NDA way, not just in the public way that's on the floor, but what's, what are you not telling us on the floor? What's coming next? And so I've been in a large number of customer meetings as well as being on the floor. And while I can't obviously share the everything, that's a non-disclosure topic in those, some things that we're hearing a lot about, people are really concerned with power because they see the TDP on the roadmaps for all the silicon providers going way up. And so people with power comes heat as waste. And so that means cooling. >>So power and cooling has been a big topic here. Obviously accelerators are, are increasing in importance in hpc not just for AI calculations, but now also for simulation calculations. And we are very proud of the three new accelerator platforms we launched here at the show that are coming out in a quarter or so. Those are two of the big topics we've seen. You know, there's, as you walk the floor here, you see lots of interesting storage vendors. HPC community's been do doing storage the same way for roughly 20 years. But now we see a lot of interesting players in that space. We have some great things in storage now and some great things that, you know, are coming in a year or two as well. So it's, it's interesting to see that diversity of that space. And then there's always the fun, exciting topics like quantum computing. We unveiled our first hybrid classical quantum computing system here with I on Q and I can't say what the future holds in this, in this format, but I can say we believe strongly in the future of quantum computing and that this, that future will be integrated with the kind of classical computing infrastructure that we make and that will help make quantum computing more powerful downstream. >>Well, let's go down that rabbit hole because, oh boy, boy, quantum computing has been talked about for a long time. There was a lot of excitement about it four or five years ago, some of the major vendors were announcing quantum computers in the cloud. Excitement has kind of died down. We don't see a lot of activity around, no, not a lot of talk around commercial quantum computers, yet you're deep into this. How close are we to have having a true quantum computer or is it a, is it a hybrid? More >>Likely? So there are probably more than 20 and I think close to 40 companies trying different approaches to make quantum computers. So, you know, Microsoft's pursuing a topol topological approach, do a photonics based approach. I, on Q and i on trap approach. These are all different ways of trying to leverage the quantum properties of nature. We know the properties exist, we use 'em in other technologies. We know the physics, but trying the engineering is very difficult. It's very difficult. I mean, just like it was difficult at one point to split the atom. It's very difficult to build technologies that leverage quantum properties of nature in a consistent and reliable and durable way, right? So I, you know, I wouldn't wanna make a prediction, but I will tell you I'm an optimist. I believe that when a tremendous capability with, with tremendous monetary gain potential lines up with another incentive, national security engineering seems to evolve faster when those things line up, when there's plenty of investment and plenty of incentive things happen. >>So I think a lot of my, my friends in the office of the CTO at Dell Technologies, when they're really leading this effort for us, you know, they would say a few to several years probably I'm an optimist, so I believe that, you know, I, I believe that we will sell some of the solution we announced here in the next year for people that are trying to get their feet wet with quantum. And I believe we'll be selling multiple quantum hybrid classical Dell quantum computing systems multiple a year in a year or two. And then of course you hope it goes to tens and hundreds of, you know, by the end of the decade >>When people talk about, I'm talking about people writ large, super leaders in supercomputing, I would say Dell's name doesn't come up in conversations I have. What would you like them to know that they don't know? >>You know, I, I hope that's not true, but I, I, I guess I understand it. We are so good at making the products from which people make clusters that we're number one in servers, we're number one in enterprise storage. We're number one in so many areas of enterprise technology that I, I think in some ways being number one in those things detracts a little bit from a subset of the market that is a solution subset as opposed to a product subset. But, you know, depending on which analyst you talk to and how they count, we're number one or number two in the world in supercomputing revenue. We don't always do the biggest splashy systems. We do the, the frontier system at t, the HPC five system at ENI in Europe. That's the largest academic supercomputer in the world and the largest industrial super >>That's based the world on Dell. Dell >>On Dell hardware. Yep. But we, I think our vision is really that we want to help more people use HPC to solve more problems than any vendor in the world. And those problems are various scales. So we are really concerned about the more we're democratizing HPC to make it easier for more people to get in at any scale that their budget and workloads require, we're optimizing it to make sure that it's not just some parts they're getting, that they are validated to work together with maximum scalability and performance. And we have a great HPC and AI innovation lab that does this engineering work. Cuz you know, one of the myths is, oh, I can just go buy a bunch of servers from company X and a network from company Y and a storage system from company Z and then it'll all work as an equivalent cluster. Right? Not true. It'll probably work, but it won't be the highest performance, highest scalability, highest reliability. So we spend a lot of time optimizing and then we are doing things to try to advance the state of HPC as well. What our future systems look like in the second half of this decade might be very different than what they look like right. Now. >>You mentioned a great example of a limitation that we're running up against right now. You mentioned an entire human body as a, as a, as an organism >>Or any large system that you try to model at the atomic level, but it's a huge macro system, >>Right? So will we be able to reach milestones where we can get our arms entirely around something like an entire human organism with simply quantitative advances as opposed to qualitative advances? Right now, as an example, let's just, let's go down to the basics from a Dell perspective. You're in a season where microprocessor vendors are coming out with next gen stuff and those next NextGen microprocessors, GPUs and CPUs are gonna be plugged into NextGen motherboards, PCI e gen five, gen six coming faster memory, bigger memory, faster networking, whether it's NS or InfiniBand storage controllers, all bigger, better, faster, stronger. And I suspect that systems like Frontera, I don't know, but I suspect that a lot of the systems that are out there are not on necessarily what we would think of as current generation technology, but maybe they're n minus one as a practical matter. So, >>But yeah, I mean they have a lifetime, so Exactly. >>The >>Lifetime is longer than the evolution. >>That's the normal technologies. Yeah. So, so what some people miss is this is, this is the reality that when, when we move forward with the latest things that are being talked about here, it's often a two generation move for an individual, for an individual organization. Yep. >>So now some organizations will have multiple systems and they, the system's leapfrog and technology generations, even if one is their real large system, their next one might be newer technology, but smaller, the next one might be a larger one with newer technology and such. Yeah. So the, the biggest super computing sites are, are often running more than one HPC system that have been specifically designed with the latest technologies and, and designed and configured for maybe a different subset of their >>Workloads. Yeah. So, so the, the, to go back to kinda the, the core question, in your opinion, do we need that qualitative leap to something like quantum computing in order to get to the point, or is it simply a question of scale and power at the, at the, at the individual node level to get us to the point where we can in fact gain insight from a digital model of an entire human body, not just looking at a, not, not just looking at an at, at an organ. And to your point, it's not just about human body, any system that we would characterize as being chaotic today, so a weather system, whatever. Do you, are there any milestones that you're thinking of where you're like, wow, you know, I have, I, I understand everything that's going on, and I think we're, we're a year away. We're a, we're, we're a, we're a compute generation away from being able to gain insight out of systems that right now we can't simply because of scale. It's a very, very long question that I just asked you, but I think I, but hopefully, hopefully you're tracking it. What, what are your, what are your thoughts? What are these, what are these inflection points that we, that you've, in your mind? >>So I, I'll I'll start simple. Remember when we used to buy laptops and we worried about what gigahertz the clock speed was Exactly. Everybody knew the gigahertz of it, right? There's some tasks at which we're so good at making the hardware that now the primary issues are how great is the screen? How light is it, what's the battery life like, et cetera. Because for the set of applications on there, we we have enough compute power. We don't, you don't really need your laptop. Most people don't need their laptop to have twice as powerful a processor that actually rather up twice the battery life on it or whatnot, right? We make great laptops. We, we design for all of those, configure those parameters now. And what, you know, we, we see some customers want more of x, somewhat more of y but the, the general point is that the amazing progress in, in microprocessors, it's sufficient for most of the workloads at that level. Now let's go to HPC level or scientific and technical level. And when it needs hpc, if you're trying to model the orbit of the moon around the earth, you don't really need a super computer for that. You can get a highly accurate model on a, on a workstation, on a server, no problem. It won't even really make it break a sweat. >>I had to do it with a slide rule >>That, >>That >>Might make you break a sweat. Yeah. But to do it with a, you know, a single body orbiting with another body, I say orbiting around, but we both know it's really, they're, they're both ordering the center of mass. It's just that if one is much larger, it seems like one's going entirely around the other. So that's, that's not a super computing problem. What about the stars in a galaxy trying to understand how galaxies form spiral arms and how they spur star formation. Right now you're talking a hundred billion stars plus a massive amount of inter stellar medium in there. So can you solve that on that server? Absolutely not. Not even close. Can you solve it on the largest super computer in the world today? Yes and no. You can solve it with approximations on the largest super computer in the world today. But there's a lot of approximations that go into even that. >>The good news is the simulations produce things that we see through our great telescopes. So we know the approximations are sufficient to get good fidelity, but until you really are doing direct numerical simulation of every particle, right? Right. Which is impossible to do. You need a computer as big as the universe to do that. But the approximations and the science in the science as well as the known parts of the science are good enough to give fidelity. So, and answer your question, there's tremendous number of problem scales. There are problems in every field of science and study that exceed the der direct numerical simulation capabilities of systems today. And so we always want more computing power. It's not macho flops, it's real, we need it, we need exo flops and we will need zeta flops beyond that and yada flops beyond that. But an increasing number of problems will be solved as we keep working to solve problems that are farther out there. So in terms of qualitative steps, I do think technologies like quantum computing, to be clear as part of a hybrid classical quantum system, because they're really just accelerators for certain kinds of algorithms, not for general purpose algorithms. I do think advances like that are gonna be necessary to solve some of the very hardest problem. It's easy to actually formulate an optimization problem that is absolutely intractable by the larger systems in the world today, but quantum systems happen to be in theory when they're big and stable enough, great at that kind of problem. >>I, that should be understood. Quantum is not a cure all for absolutely. For the, for the shortage of computing power. It's very good for certain, certain >>Problems. And as you said at this super computing, we see some quantum, but it's a little bit quieter than I probably expected. I think we're in a period now of everybody saying, okay, there's been a lot of buzz. We know it's gonna be real, but let's calm down a little bit and figure out what the right solutions are. And I'm very proud that we offered one of those >>At the show. We, we have barely scratched the surface of what we could talk about as we get into intergalactic space, but unfortunately we only have so many minutes and, and we're out of them. Oh, >>I'm >>J Poso, HPC and AI technology strategist at Dell. Thanks for a fascinating conversation. >>Thanks for having me. Happy to do it anytime. >>We'll be back with our last interview of Supercomputing 22 in Dallas. This is Paul Gillen with Dave Nicholson. Stay with us.

>>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)

>>Hey everyone, welcome to this Cube's special program series Women of the Cloud, brought to you by aws. I'm your host for the series, Lisa Martin. Very pleased to be joined by Patty Jordan, the VP of enabling processes and technology at Optimus. My next guest, Patty, welcome to the program. >>Hi Lisa. Thank you for having me. >>Tell me a little bit about yourself, a little bit about your role so the audience gets that understanding of exactly who you are. >>Sure thing. Hi, my name is Patty Jordan. As we mentioned, I am originally from Cameroon, Central Africa, but I was raised in the DC area. I'm called and what you call a bank brat. My father worked for an international organization, the the World Bank. Lived in, like I said, grew up in dc, moved to Austin, Texas about seven years ago. Been with Optum for the last nine years of my working career. And I've had multiple roles, but currently my role as is with the enabling technologies and processes, which means that I manage teams that support the platform of a lot of analytics products in Optum. >>Got it. All right. Bank Brett, that's a new one to me. I hadn't heard that. I love that you're a bank, Brit and proud of it. I can tell. Talk to me a little bit about your, the career path that you have navigated and what are some of your sort of tactical and also strategic recommendations for the audiences looking to grow their career in tech? >>So the interesting thing is, I did not start in tech. My background is as an economist. I have a bachelor's of economics from the women, from the College of Women, Mary. I also have a financial master's in public policy from American University. However, I did take some IT classes and as a kid I'm probably dating myself a little bit, but I programmed in dos, so I, I was always excited by it and I had internships as a programmer that helped me pay for my master's degree in when I graduated. I just felt like I was having fun and I was getting paid very well and I was able to pay off my graduate schools. So I just stayed with tech. >>Love that. But it sounds like you had that interest from when you were quite young and as a lot of us and end up in tech, we didn't start there originally. There's a lot of zigzaggy paths to get there. Sounds like you had that as well. What are some of your recommendations for people, either those that are in tech now or aren't who want to get into it and really expand and climb that ladder? >>So definitely, so one of the things to understand is tech could be many different things. Like one of the things could be programming, which I started doing and now dislike intensely. And then another thing could be like being in the business analyst in tech, getting the business requirements versus product management or even, you know, management. And what I would encourage people to do is really focus on what you feel happy doing, which for me is problem solving and collaborating and getting the right people together to solve very complex problems. And if you focus on that then you'll find your, your the role for you even in tech. >>I love that problem solving is such an important skill to be able to have and to cultivate regardless of the industry that you're in. But I'd love to know a little bit more about some of the successes that you've had helping organizations really navigate their cloud journeys, their migration to cloud as we've seen the last couple of years, a massive acceleration to the cloud that was really born outta the pandemic. Talk to me about some of the successes that you've been able to achieve. >>So the first, I guess most obvious thing is understanding the technology. What do you have at your disposal? What do you need for your team to succeed in the cloud or even OnPrem? But what I've learned most in the last four to five years with the projects that I work on, whether it was migrating from a host data center to one that we owned ourselves or migrating from that data center to AWS recently was you really need to get the business organization engaged. And that's not just getting the sponsorship and getting them this to write that check, but really helping them understand how this journey to the cloud is a combined journey between both organizations, right? And they will be able to be more successful as well with us going to the cloud with improved processing with revenue protection because we, there's more tools available with revenue expansion because now we can now expand faster address client needs faster. And you know, so there's various different aspects of going to cloud that are more than just we're using the coolest technology. >>You're a problem solver, has there. And one of the challenges with organizations and from a cloud migration standpoint that we often talk about is it's a cultural migration as well, which is really challenging to do for any type of organization regardless of industry. Do you have a favorite example where as a, as the problem solver, you came in and really helped the organization, the business side understand, be able to transform their cultural direction, understand why cloud migration can be such a facilitator of the business from the top line in a bottom line perspective. >>So from a bottom line perspective, I think the hardest thing for them to understand or what does not compute for them is you can't give them a set. This is what you're gonna cost in the cloud, right? Because the benefit of being in the cloud is being able to scale shrink, et cetera. So that's one hurdle that we're still fighting to be a hundred percent candid. But from a a top line perspective, what's what's been great is we've been able to ramp up more clients with the same, right? So we haven't had to go out and procure more servers, more storage, hire more staff because we're in the cloud and we've actually been able to scale our teams as well because we incorporated the DevOps functions and we do not need a team to manage a data center anymore. So that they absolutely understood, you know, savings ratified, but really just how do we get to market faster? How do we get to revenue faster and how do we get more revenue with the same pool of resources is something that they've really, really resonated with. >>Well, you're starting to speak their language so that to your point that resonates well, but there's so much productivity improvements, efficiencies to be gained by leveraging cloud computing that that really hit the bottom line of an organization that businesses, if you put it in the right way. And it sounds like as the problem solver you have, they understand the immense value and competitive advantage that cloud can bring to their organization and become sort of a ah, the blinders are off. I get it. >>Exactly. Exactly. You're just not trying to, to play with the latest toys, you are actually solving a business problem even before it happens. >>And that's the key solving business problems before they happen. Being able to predict and forecast is huge for businesses, especially as we've seen the last couple of years. Everybody racing to digital, to to pivot, to survive Now to be competitive. If they don't do that and embrace that emerging technology suite, there's a competitor that's right back here that if they're more culturally willing and able to, to be more agile, they're gonna take the place of a competing organization. So yeah, so it absolutely is a huge differentiator for organizations. And it sounds like you've had some great successes there in helping organizations really navigate the challenges, the cultural challenges, but the benefits of cloud computing. Yes. I do wanna talk to you a little bit about in your expertise, diversity is something that is talked about in every industry. We talk about it in tech all the time, there's still challenges there. What are, what's, what are your thoughts on diversity? What are you seeing and what are some of those challenges that are still sitting on the table? >>So I guess the first thing I would say is there's multiple facets to diversity, right? The first one we always lean to is gender and race, but there's also diversity of thought. And being in the healthcare industry is very important for us to have a diversity of thought and experiences so that we can target a lot of these health equity issues that are, you know, that, that are ongoing. So that's one thing that we've, we've been trying to do is making sure that I don't just have people that think like me on the team. And typically that also means not having people that look like me. So making sure that we have the right pipelines to hire for partnering with our, with some of our vendors. AWS for example, is a good one where they had avenues and they had non-profits that they worked with and they connected us with some of our staff augmentation people also did the same thing, really just expanding the scope of where we're looking for talent and, and that helps also bring that diversity of thought and the diversity of gender race into the, into the full >>It is. And it and, and there's also, there's so much data if we follow the data and of course in tech we're all about data. Every company these days, regardless of industry needs to be a data company. If we follow the data, we can see that organizations with, for example, females within the C-suite are far more profitable than those organizations that don't have that even that element of diversity. So the data is demonstrating there's tremendous business value, tremendous competitive advantage, faster time to market, more products and services that can be delivered if there is thought diversity among the entire organization, not just the C-suite. >>Exactly. And and since we have an impact on what is being delivered as an engineering organization, we also need that in engineering, right? One of the things that's very keen right now is machine language and ai. If we don't have the right models for example, then we either introduced bias or perpetuate by it. So we definitely need people on our teams as well that understand how these technologies work, how we can leverage 'em on our data sets so that we could run counter to this bias >>And countering that bias is incredibly important. Machine learning ai, so driven by data, the volumes of data, but the data needs to be as clean and and non-biased as possible. And that's a big challenge for organizations to undertake. Is there advice that you have for those folks watching who might be, I, I don't see me in this organization, I don't feel represented. How can I change that? >>Well, one would be to speak up, right? Even if you don't see you apply for the job, right? And one of the things that we're trying to address even in the DEI space is making sure that our job descriptions are not introducing any biases so that people will eliminate themselves immediately, right? But really just if you have the skill set and you feel like you can ramp up to the talent, then just apply for the job. Talk to somebody. You do have a network whether you realize it or not. So leverage that network. But really like there's this expression that my kid taught me saying, you miss a hundred percent of the shots you don't take, right? So if you don't try, you're not gonna make it by default. If you do try, there's a chance to make it right. At the very least, you build a connection with someone who can potentially help you down the line. >>That is one of my absolute favorite sayings. You miss a hundred percent of the shots that you don't take. So encouraging people to raise their hand there, there are stats, data, speaking of data we've been talking about that, that demonstrate that women are far less likely to apply for jobs like on LinkedIn for example, unless they need 100% of the job requirements, which we all know are quite stringent and not necessary in a lot of cases. So I love your advice of just try raise your hand, ask the question. All the can say is no. And at the end of the day, what is that? It's a word but can also be directional and and really guiding for people on their journey to wherever that, if it's an engineering, cloud, engineering, DevOps, whatever happen that happens to be, raise your hand the question. And to your point, you have a network, it is there, open that up. There's so much potential for people that just raise, I think that's to raise their hand and ask the question. >>And the corollary to that though is I would also encourage people who are in leader leadership roles to be strong allies, right? Like we need to be aware of what biases we might be introducing or candidates that we might be leaving on the table because we're being too stringent because we're not expanding our, our our search, right? So definitely that's something that I've started doing about five, six years old shortly after I moved to Austin, which I kind of beat myself up about not having done before, is really contributing to that community, helping out, being a mentor, being a coach, being a guide. Sometimes it's just reviewing somebody's resume. Other times it's talking to 'em about a role that I have and helping them map their current state to that role. But really just being an ally to everyone and anyone who wants to come into this space. >>I love that. I, and I have a feeling, Patty, that you're a great mentor and ally for those in your organization across organizations and those out there that may not know yet. Patty can be an ally for me. I'd love to get your take in our final minutes on a couple things. One, the, what's next in cloud from your perspective, the things that you've seen, what you've been able to achieve, and how do you see your role evolving in the industry at Optum? >>So what's next in cloud, and we've talked about that a lot, is data. How do we manage all this data? How do we catalog this data, how to reuse this data, how to reshift this data? We have data in various different environments. We're a multi-cloud company. So how do we make sure that we don't have the same data everywhere? Or even if we do, how do we reconcile that? So data, data, data, right? And from data, get to information so that we can monetize it and we can share it. So that's the, that's for me is really next step. I mean we, we know the applications that we can build, we know the analytics that we can build, but if we don't have the right data, we're limiting ourselves. So that's definitely one aspect that I know that we wanna drive. And as far as my role, I was fortunate enough to be provided with the leadership of development of a platform for analytics, which yes, involves data. >>So I'm very excited about this, right? Cuz that's, that's next level for me. I've been typically in roles that protect revenue in the DevOps and operations role. And now I'm in a revenue generating role and it has a shift in mindset. But I, I really appreciate it and I'm really taking everything I've learned up to now as a DevOps team. I knew when the bad things came. So now I'm trying to prevent, prevent my team from pushing bad things down the pipe, right? So I'm just really excited about what's, what's, what's to come because there's so many opportunities for improving the products that we build. And I'm so excited to be part of this platform. >>There are the, the horizon of opportunities is really endless, which is exciting. And to your point about data, like I mentioned, for every company, whether it's your grocery store, a retailer, the postal service has to become a data driven company. Cuz as consumers we expect that we bring that into our business lives and we expect to be able to transact in business as easily as we do on the consumer side. And that all requires organizations to not just have access to data, but to be able to build the right data infrastructure, toing insights to act on that, to feed the AI and ML models so that products services can get better, more personalized and meet the demands of the ever demanding consumer, which I know I, one of them. I wanna ask you one more final question and that is, what do you think some of the biggest challenges have been with, with respect to tech innovation in the workforce over the past five years? What are some of those things that, that you've seen that you think we're on the right track moving forward to eliminate some of these? >>That is a good question. I think one of the biggest challenges for me has been not to remain in the status quo, right? Like not to do something because it's what we've been doing, but being in the cloud allows us with so many opportunities where we can fail fast. That let's give it a shot, let's do a quick sprint, let's figure out whether it is a possibility or not. Eliminate it if it's not, and then keep moving, right? Like we don't have the same development methodology before that we had to do three months, five months, six months. You can iterate in two week chunks, get it done, confirm your, your statement or not, or negate it, but at the very least have an answer, right? So that for me is the biggest challenge. We're aware of the thinking we're just not doing. So it'd be very exciting when we, when we pivot from that and really start innovating because we have the time >>Innovating because we have the time, as I mentioned, you know, with the demand of consumers, whether it's consumer in, in on the personal side, business side, those demands are there. But the, the exciting thing is to your point, the innovations are there. The capabilities are there, the data is there. We have a lot of what we need to be able to take advantage of that. So it's gonna be exciting to see what happens over the next few years. Patty, it's been such a pleasure having you on the cube today. Thank you so much for joining. You are clearly a, a leader in terms of women in the cloud. We appreciate what you're doing, your insights, your recommendations, and your insights as to what you see in the future. You've been a great guest. Thank you so much for joining me today. >>Thank you for having me Lisa. >>My pleasure For Patty Jordan, I'm Lisa Martin. You're watching The Cubes coverage of Women of the Cloud, brought to you by aws, a special program series. We thank you so much for watching. Take care.

(contemplative upbeat music) >> Hello and welcome to this CUBE Conversation. I'm John Furrier, your host of theCUBE, here in Palo Alto, California. Got a great topic on expanding capabilities for urgent computing. Dan Stanzione, he's Executive Director of TACC, the Texas Advanced Computing Center, and Rajesh Pohani, VP of PowerEdge, HPC Core Compute at Dell Technologies. Gentlemen, welcome to this CUBE Conversation. >> Thanks, John. >> Thanks, John, good to be here. >> Rajesh, you got a lot of computing in PowerEdge, HPC, Core Computing. I mean, I get a sense that you love compute, so we'll jump right into it. And of course, I got to love TACC, Texas Advanced Computing Center. I can imagine a lot of stuff going on there. Let's start with TACC. What is the Texas Advanced Computing Center? Tell us a little bit about that. >> Yeah, we're part of the University of Texas at Austin here, and we build large-scale supercomputers, data systems, AI systems, to support open science research. And we're mainly funded by the National Science Foundation, so we support research projects in all fields of science, all around the country and around the world. Actually, several thousand projects at the moment. >> But tied to the university, got a lot of gear, got a lot of compute, got a lot of cool stuff going on. What's the coolest thing you got going on right now? >> Well, for me, it's always the next machine, but I think science-wise, it's the machines we have. We just finished deploying Lonestar6, which is our latest supercomputer, in conjunction with Dell. A little over 600 nodes of those PowerEdge servers that Rajesh builds for us. Which makes more than 20,000 that we've had here over the years, of those boxes. But that one just went into production. We're designing new systems for a few years from now, where we'll be even larger. Our Frontera system was top five in the world two years ago, just fell out of the top 10. So we've got to fix that and build the new top-10 system sometime soon. We always have a ton going on in large-scale computing. >> Well, I want to get to the Lonestar6 in a minute, on the next talk track, but... What are some of the areas that you guys are working on that are making an impact? Take us through, and we talked before we came on camera about, obviously, the academic affiliation, but also there's a real societal impact of the work you're doing. What are some of the key areas that the TACC is making an impact? >> So there's really a huge range from new microprocessors, new materials design, photovoltaics, climate modeling, basic science and astrophysics, and quantum mechanics, and things like that. But I think the nearest-term impacts that people see are what we call urgent computing, which is one of the drivers around Lonestar and some other recent expansions that we've done. And that's things like, there's a hurricane coming, exactly where is it going to land? Can we refine the area where there's going to be either high winds or storm surge? Can we assess the damage from digital imagery afterwards? Can we direct first responders in the optimal routes? Similarly for earthquakes, and a lot recently, as you might imagine, around COVID. In 2020, we moved almost a third of our resources to doing COVID work, full-time. >> Rajesh, I want to get your thoughts on this, because Dave Vellante and I have been talking about this on theCUBE recently, a lot. Obviously, people see what cloud's, going on with the cloud technology, but compute and on-premises, private cloud's been growing. If you look at the hyperscale on-premises and the edge, if you include that in, you're seeing a lot more user consumption on-premises, and now, with 5G, you got edge, you mentioned first responders, Dan. This is now pointing to a new architectural shift. As the VP of PowerEdge and HPC and Core Compute, you got to look at this and go, "Hmm." If Compute's going to be everywhere, and in locations, you got to have that compute. How does that all work together? And how do you do advanced computing, when you have these urgent needs, as well as real-time in a new architecture? >> Yeah, John, I mean, it's a pretty interesting time when you think about some of the changing dynamics and how customers are utilizing Compute in the compute needs in the industry. Seeing a couple of big trends. One, the distribution of Compute outside of the data center, 5G is really accelerating that, and then you're generating so much data, whether what you do with it, the insights that come out of it, that we're seeing more and more push to AI, ML, inside the data center. Dan mentioned what he's doing at TACC with computational analysis and some of the work that they're doing. So what you're seeing is, now, this push that data in the data center and what you do with it, while data is being created out at the edge. And it's actually this interesting dichotomy that we're beginning to see. Dan mentioned some of the work that they're doing in medical and on COVID research. Even at Dell, we're making cycles available for COVID research using our Zenith cluster, that's located in our HPC and AI Innovation Lab. And we continue to partner with organizations like TACC and others on research activities to continue to learn about the virus, how it mutates, and then how you treat it. So if you think about all the things, and data that's getting created, you're seeing that distribution and it's really leading to some really cool innovations going forward. >> Yeah, I want to get to that COVID research, but first, you mentioned a few words I want to get out there. You mentioned Lonestar6. Okay, so first, what is Lonestar6, then we'll get into the system aspect of it. Take us through what that definition is, what is Lonestar6? >> Well, as Dan mentioned, Lonestar6 is a Dell technology system that we developed with TACC, it's located at the University of Texas at Austin. It consists of more than 800 Dell PowerEdge 6525 servers that are powered with 3rd Generation AMD EPYC processors. And just to give you an example of the scale of this cluster, it could perform roughly three quadrillion operations per second. That's three petaFLOPS, and to match what Lonestar6 can compute in one second, a person would have to do one calculation every second for a hundred million years. So it's quite a good-size system, and quite a powerful one as well. >> Dan, what's the role that the system plays, you've got petaFLOPS, what, three petaFLOPS, you mentioned? That's a lot of FLOPS! So obviously urgent computing, what's cranking through the system there? Take us through, what's it like? >> Sure, well, there there's a mix of workloads on it, and on all our systems. So there's the urgent computing work, right? Fast turnaround, near real-time, whether it's COVID research, or doing... Project now where we bring in MRI data and are doing sort of patient-specific dosing for radiation treatments and chemotherapy, tailored to your tumor, instead of just the sort of general for people your size. That all requires sort of real-time turnaround. There's a lot AI research going on now, we're incorporating AI in traditional science and engineering research. And that uses an awful lot of data, but also consumes a huge amount of cycles in training those models. And then there's all of our traditional, simulation-based workloads and materials and digital twins for aircraft and aircraft design, and more efficient combustion in more efficient photovoltaic materials, or photovoltaic materials without using as much lead, and things like that. And I'm sure I'm missing dozens of other topics, 'cause, like I said, that one really runs every field of science. We've really focused the Lonestar line of systems, and this is obviously the sixth one we built, around our sort of Texas-centric users. It's the UT Austin users, and then with contributions from Texas A&M , and Texas Tech and the University of Texas system, MD Anderson Healthcare Center, the University of North Texas. So users all around the state, and every research problem that you might imagine, those are into. We're just ramping up a project in disaster information systems, that's looking at the probabilities of flooding in coastal Texas and doing... Can we make building code changes to mitigate impact? Do we have to change the standard foundation heights for new construction, to mitigate the increasing storm surges from these sort of slow storms that sit there and rain, like hurricanes didn't used to, but seem to be doing more and more. All those problems will run on Lonestar, and on all the systems to come, yeah. >> It's interesting, you mentioned urgent computing, I love that term because it could be an event, it could be some slow kind of brewing event like that rain example you mentioned. It could also be, obviously, with the healthcare, and you mentioned COVID earlier. These are urgent, societal challenges, and having that available, the processing capability, the compute, the data. You mentioned digital twins. I can imagine all this new goodness coming from that. Compare that, where we were 10 years ago. I mean, just from a mind-blowing standpoint, you have, have come so far, take us through, try to give a context to the level of where we are now, to do this kind of work, and where we were years ago. Can you give us a feel for that? >> Sure, there's a lot of ways to look at that, and how the technology's changed, how we operate around those things, and then sort of what our capabilities are. I think one of the big, first, urgent computing things for us, where we sort of realized we had to adapt to this model of computing was about 15 years ago with the big BP Gulf Oil spill. And suddenly, we were dumping thousands of processors of load to figure out where that oil spill was going to go, and how to do mitigation, and what the potential impacts were, and where you need to put your containment, and things like that. And it was, well, at that point we thought of it as sort of a rare event. There was another one, that I think was the first real urgent computing one, where the space shuttle was in orbit, and they knew something had hit it during takeoff. And we were modeling, along with NASA and a bunch of supercomputers around the world, the heat shield and could they make reentry safely? You have until they come back to get that problem done, you don't have months or years to really investigate that. And so, what we've sort of learned through some of those, the Japanese tsunami was another one, there have been so many over the years, is that one, these sort of disasters are all the time, right? One thing or another, right? If we're not doing hurricanes, we're doing wildfires and drought threat, if it's not COVID. We got good and ready for COVID through SARS and through the swine flu and through HIV work, and things like that. So it's that we can do the computing very fast, but you need to know how to do the work, right? So we've spent a lot of time, not only being able to deliver the computing quickly, but having the data in place, and having the code in place, and having people who know the methods who know how to use big computers, right? That's been a lot of what the COVID Consortium, the White House COVID Consortium, has been about over the last few years. And we're actually trying to modify that nationally into a strategic computing reserve, where we're ready to go after these problems, where we've run drills, right? And if there's a, there's a train that derails, and there's a chemical spill, and it's near a major city, we have the tools and the data in place to do wind modeling, and we have the terrain ready to go. And all those sorts of things that you need to have to be ready. So we've really sort of changed our sort of preparedness and operational model around urgent computing in the last 10 years. Also, just the way we scheduled the system, the ability to sort of segregate between these long-running workflows for things that are really important, like we displaced a lot of cancer research to do COVID research. And cancer's still important, but it's less likely that we're going to make an impact in the next two months, right? So we have to shuffle how we operate things and then just, having all that additional capacity. And I think one of the things that's really changed in the models is our ability to use AI, to sort of adroitly steer our simulations, or prune the space when we're searching parameters for simulations. So we have the operational changes, the system changes, and then things like adding AI on the scientific side, since we have the capacity to do that kind of things now, all feed into our sort of preparedness for this kind of stuff. >> Dan, you got me sold, I want to come work with you. Come on, can I join the team over there? It sounds exciting. >> Come on down! We always need good folks around here, so. (laughs) >> Rajesh, when I- >> Almost 200 now, and we're always growing. >> Rajesh, when I hear the stories about kind of the evolution, kind of where the state of the art is, you almost see the innovation trajectory, right? The growth and the learning, adding machine learning only extends out more capabilities. But also, Dan's kind of pointing out this kind of response, rapid compute engine, that they could actually deploy with learnings, and then software, so is this a model where anyone can call up and get some cycles to, say, power an autonomous vehicle, or, hey, I want to point the machinery and the cycles at something? Is the service, do you guys see this going that direction, or... Because this sounds really, really good. >> Yeah, I mean, one thing that Dan talked about was, it's not just the compute, it's also having the right algorithms, the software, the code, right? The ability to learn. So I think when those are set up, yeah. I mean, the ability to digitally simulate in any number of industries and areas, advances the pace of innovation, reduces the time to market of whatever a customer is trying to do or research, or even vaccines or other healthcare things. If you can reduce that time through the leverage of compute on doing digital simulations, it just makes things better for society or for whatever it is that we're trying to do, in a particular industry. >> I think the idea of instrumenting stuff is here forever, and also simulations, whether it's digital twins, and doing these kinds of real-time models. Isn't really much of a guess, so I think this is a huge, historic moment. But you guys are pushing the envelope here, at University of Texas and at TACC. It's not just research, you guys got real examples. So where do you guys see this going next? I see space, big compute areas that might need some data to be cranked out. You got cybersecurity, you got healthcare, you mentioned oil spill, you got oil and gas, I mean, you got industry, you got climate change. I mean, there's so much to tackle. What's next? >> Absolutely, and I think, the appetite for computing cycles isn't going anywhere, right? And it's only going to, it's going to grow without bound, essentially. And AI, while in some ways it reduces the amount of computing we do, it's also brought this whole new domain of modeling to a bunch of fields that weren't traditionally computational, right? We used to just do engineering, physics, chemistry, were all super computational, but then we got into genome sequencers and imaging and a whole bunch of data, and that made biology computational. And with AI, now we're making things like the behavior of human society and things, computational problems, right? So there's this sort of growing amount of workload that is, in one way or another, computational, and getting bigger and bigger. So that's going to keep on growing. I think the trick is not only going to be growing the computation, but growing the software and the people along with it, because we have amazing capabilities that we can bring to bear. We don't have enough people to hit all of them at once. And so, that's probably going to be the next frontier in growing out both our AI and simulation capability, is the human element of it. >> It's interesting, when you think about society, right? If the things become too predictable, what does a democracy even look like? If you know the election's going to be over two years from now in the United States, or you look at these major, major waves >> Human companies don't know. >> of innovation, you say, "Hmm." So it's democracy, AI, maybe there's an algorithm for checking up on the AI 'cause biases... So, again, there's so many use cases that just come out of this. It's incredible. >> Yeah, and bias in AI is something that we worry about and we work on, and on task forces where we're working on that particular problem, because the AI is going to take... Is based on... Especially when you look at a deep learning model, it's 100% a product of the data you show it, right? So if you show it a biased data set, it's going to have biased results. And it's not anything intrinsic about the computer or the personality, the AI, it's just data mining, right? In essence, right, it's learning from data. And if you show it all images of one particular outcome, it's going to assume that's always the outcome, right? It just has no choice, but to see that. So how we deal with bias, how do we deal with confirmation, right? I mean, in addition, you have to recognize, if you haven't, if it gets data it's never seen before, how do you know it's not wrong, right? So there's about data quality and quality assurance and quality checking around AI. And that's where, especially in scientific research, we use what's starting to be called things like physics-informed or physics-constrained AI, where the neural net that you're using to design an aircraft still has to follow basic physical laws in its output, right? Or if you're doing some materials or astrophysics, you still have to obey conservation of mass, right? So I can't say, well, if you just apply negative mass on this other side and positive mass on this side, everything works out right for stable flight. 'Cause we can't do negative mass, right? So you have to constrain it in the real world. So this notion of how we bring in the laws of physics and constrain your AI to what's possible is also a big part of the sort of AI research going forward. >> You know, Dan, you just, to me just encapsulate the science that's still out there, that's needed. Computer science, social science, material science, kind of all converging right now. >> Yeah, engineering, yeah, >> Engineering, science, >> slipstreams, >> it's all there, >> physics, yeah, mmhmm. >> it's not just code. And, Rajesh, data. You mentioned data, the more data you have, the better the AI. We have a world what's going from silos to open control planes. We have to get to a world. This is a cultural shift we're seeing, what's your thoughts? >> Well, it is, in that, the ability to drive predictive analysis based on the data is going to drive different behaviors, right? Different social behaviors for cultural impacts. But I think the point that Dan made about bias, right, it's only as good as the code that's written and the way that the data is actually brought into the system. So making sure that that is done in a way that generates the right kind of outcome, that allows you to use that in a predictive manner, becomes critically important. If it is biased, you're going to lose credibility in a lot of that analysis that comes out of it. So I think that becomes critically important, but overall, I mean, if you think about the way compute is, it's becoming pervasive. It's not just in selected industries as damage, and it's now applying to everything that you do, right? Whether it is getting you more tailored recommendations for your purchasing, right? You have better options that way. You don't have to sift through a lot of different ideas that, as you scroll online. It's tailoring now to some of your habits and what you're looking for. So that becomes an incredible time-saver for people to be able to get what they want in a way that they want it. And then you look at the way it impacts other industries and development innovation, and it just continues to scale and scale and scale. >> Well, I think the work that you guys are doing together is scratching the surface of the future, which is digital business. It's about data, it's about out all these new things. It's about advanced computing meets the right algorithms for the right purpose. And it's a really amazing operation you guys got over there. Dan, great to hear the stories. It's very provocative, very enticing to just want to jump in and hang out. But I got to do theCUBE day job here, but congratulations on success. Rajesh, great to see you and thanks for coming on theCUBE. >> Thanks for having us, John. >> Okay. >> Thanks very much. >> Great conversation around urgent computing, as computing becomes so much more important, bigger problems and opportunities are around the corner. And this is theCUBE, we're documenting it all here. I'm John Furrier, your host. Thanks for watching. (contemplative music)

>>from around the globe. It's the Cube presenting innovation for good, brought to you by on shape. >>Hello, everyone, and welcome to Innovation for Good Program, hosted by the Cuban. Brought to You by on Shape, which is a PTC company. My name is Dave Valentin. I'm coming to you from our studios outside of Boston. I'll be directing the conversations today. It's a very exciting, all live program. We're gonna look at how product innovation has evolved and where it's going and how engineers, entrepreneurs and educators are applying cutting edge, cutting edge product development techniques and technology to change our world. You know, the pandemic is, of course, profoundly impacted society and altered how individuals and organizations they're gonna be thinking about an approaching the coming decade. Leading technologists, engineers, product developers and educators have responded to the new challenges that we're facing from creating lifesaving products to helping students learn from home toe how to apply the latest product development techniques and solve the world's hardest problems. And in this program, you'll hear from some of the world's leading experts and practitioners on how product development and continuous innovation has evolved, how it's being applied toe positive positively affect society and importantly where it's going in the coming decades. So let's get started with our first session fueling Tech for good. And with me is John Hirschbeck, who is the president of the Suffers, a service division of PTC, which acquired on shape just over a year ago, where John was the CEO and co founder, and Dana Grayson is here. She is the co founder and general partner at Construct Capital, a new venture capital firm. Folks, welcome to the program. Thanks so much for coming on. >>Great to be here, Dave. >>All right, John. >>You're very welcome. Dana. Look, John, let's get into it for first Belated congratulations on the acquisition of Von Shape. That was an awesome seven year journey for your company. Tell our audience a little bit about the story of on shape, but take us back to Day zero. Why did you and your co founders start on shape? Well, >>actually, start before on shaping the You know, David, I've been in this business for almost 40 years. The business of building software tools for product developers and I had been part of some previous products in the industry and companies that had been in their era. Big changes in this market and about, you know, a little Before founding on shape, we started to see the problems product development teams were having with the traditional tools of that era years ago, and we saw the opportunity presented by Cloud Web and Mobile Technology. And we said, Hey, we could use Cloud Web and Mobile to solve the problems of product developers make their Their business is run better. But we have to build an entirely new system, an entirely new company, to do it. And that's what on shapes about. >>Well, so notwithstanding the challenges of co vid and difficulties this year, how is the first year been as, Ah, division of PTC for you guys? How's business? Anything you can share with us? >>Yeah, our first year of PTC has been awesome. It's been, you know, when you get acquired, Dave, you never You know, you have great optimism, but you never know what life will really be like. It's sort of like getting married or something, you know, until you're really doing it, you don't know. And so I'm happy to say that one year into our acquisition, um, PTC on shape is thriving. It's worked out better than I could have imagined a year ago. Along always, I mean sales are up. In Q four, our new sales rate grew 80% vs Excuse me, our fiscal Q four Q three. In the calendar year, it grew 80% compared to the year before. Our educational uses skyrocketing with around 400% growth, most recently year to year of students and teachers and co vid. And we've launched a major cloud platform using the core of on shape technology called Atlas. So, um, just tons of exciting things going on a TTC. >>That's awesome. But thank you for sharing some of those metrics. And of course, you're very humble individual. You know, people should know a little bit more about you mentioned, you know, we founded Solid Works, co founded Solid where I actually found it solid works. You had a great exit in the in the late nineties. But what I really appreciate is, you know, you're an entrepreneur. You've got a passion for the babies that you you helped birth. You stayed with the salt systems for a number of years. The company that quiet, solid works well over a decade. And and, of course, you and I have talked about how you participated in the the M I T. Blackjack team. You know, back in the day, a zai say you're very understated, for somebody was so accomplished. Well, >>that's kind of you, but I tend to I tend Thio always keep my eye more on what's ahead. You know what's next, then? And you know, I look back Sure to enjoy it and learn from it about what I can put to work making new memories, making new successes. >>Love it. Okay, let's bring Dana into the conversation. Hello, Dana. You look you're a fairly early investor in in on shape when you were with any A And and I think it was like it was a serious B, but it was very right close after the A raise. And and you were and still are a big believer in industrial transformation. So take us back. What did you see about on shape back then? That excited you. >>Thanks. Thanks for that. Yeah. I was lucky to be a early investment in shape. You know, the things that actually attracted me. Don shape were largely around John and, uh, the team. They're really setting out to do something, as John says humbly, something totally new, but really building off of their background was a large part of it. Um, but, you know, I was really intrigued by the design collaboration side of the product. Um, I would say that's frankly what originally attracted me to it. What kept me in the room, you know, in terms of the industrial world was seeing just if you start with collaboration around design what that does to the overall industrial product lifecycle accelerating manufacturing just, you know, modernizing all the manufacturing, just starting with design. So I'm really thankful to the on shape guys, because it was one of the first investments I've made that turned me on to the whole sector. And while just such a great pleasure to work with with John and the whole team there. Now see what they're doing inside PTC. >>And you just launched construct capital this year, right in the middle of a pandemic and which is awesome. I love it. And you're focused on early stage investing. Maybe tell us a little bit about construct capital. What your investment thesis is and you know, one of the big waves that you're hoping to ride. >>Sure, it construct it is literally lifting out of any what I was doing there. Um uh, for on shape, I went on to invest in companies such as desktop metal and Tulip, to name a couple of them form labs, another one in and around the manufacturing space. But our thesis that construct is broader than just, you know, manufacturing and industrial. It really incorporates all of what we'd call foundational industries that have let yet to be fully tech enabled or digitized. Manufacturing is a big piece of it. Supply chain, logistics, transportation of mobility or not, or other big pieces of it. And together they really drive, you know, half of the GDP in the US and have been very under invested. And frankly, they haven't attracted really great founders like they're on in droves. And I think that's going to change. We're seeing, um, entrepreneurs coming out of the tech world orthe Agnelli into these industries and then bringing them back into the tech world, which is which is something that needs to happen. So John and team were certainly early pioneers, and I think, you know, frankly, obviously, that voting with my feet that the next set, a really strong companies are going to come out of the space over the next decade. >>I think it's a huge opportunity to digitize the sort of traditionally non digital organizations. But Dana, you focused. I think it's it's accurate to say you're focused on even Mawr early stage investing now. And I want to understand why you feel it's important to be early. I mean, it's obviously riskier and reward e er, but what do you look for in companies and and founders like John >>Mhm, Um, you know, I think they're different styles of investing all the way up to public market investing. I've always been early stage investors, so I like to work with founders and teams when they're, you know, just starting out. Um, I happened to also think that we were just really early in the whole digital transformation of this world. You know, John and team have been, you know, back from solid works, etcetera around the space for a long time. But again, the downstream impact of what they're doing really changes the whole industry. And and so we're pretty early and in digitally transforming that market. Um, so that's another reason why I wanna invest early now, because I do really firmly believe that the next set of strong companies and strong returns for my own investors will be in the spaces. Um, you know, what I look for in Founders are people that really see the world in a different way. And, you know, sometimes some people think of founders or entrepreneurs is being very risk seeking. You know, if you asked John probably and another successful entrepreneurs, they would call themselves sort of risk averse, because by the time they start the company, they really have isolated all the risk out of it and think that they have given their expertise or what they're seeing their just so compelled to go change something, eh? So I look for that type of attitude experience a Z. You can also tell from John. He's fairly humble. So humility and just focus is also really important. Um, that there's a That's a lot of it. Frankly, >>Excellent. Thank you, John. You got such a rich history in the space. Uh, and one of you could sort of connect the dots over time. I mean, when you look back, what were the major forces that you saw in the market in in the early days? Particularly days of on shape on? And how is that evolved? And what are you seeing today? Well, >>I think I touched on it earlier. Actually, could I just reflect on what Dana said about risk taking for just a quick one and say, throughout my life, from blackjack to starting solid works on shape, it's about taking calculated risks. Yes, you try to eliminate the risk Sa's much as you can, but I always say, I don't mind taking a risk that I'm aware of, and I've calculated through as best I can. I don't like taking risks that I don't know I'm taking. That's right. You >>like to bet on >>sure things as much as you sure things, or at least where you feel you. You've done the research and you see them and you know they're there and you know, you, you you keep that in mind in the room, and I think that's great. And Dana did so much for us. Dana, I want to thank you again. For all that, you did it every step of the way, from where we started to to, you know, your journey with us ended formally but continues informally. Now back to you, Dave, I think, question about the opportunity and how it's shaped up. Well, I think I touched on it earlier when I said It's about helping product developers. You know, our customers of the people build the future off manufactured goods. Anything you think of that would be manufacturing factory. You know, the chair you're sitting in machine that made your coffee. You know, the computer you're using, the trucks that drive by on the street, all the covert product research, the equipment being used to make vaccines. All that stuff is designed by someone, and our job is given the tools to do it better. And I could see the problems that those product developers had that we're slowing them down with using the computing systems of the time. When we built solid works, that was almost 30 years ago. If people don't realize that it was in the early >>nineties and you know, we did the >>best we could for the early nineties, but what we did. We didn't anticipate the world of today. And so people were having problems with just installing the systems. Dave, you wouldn't believe how hard it is to install these systems. You need toe speck up a special windows computer, you know, and make sure you've got all the memory and graphics you need and getting to get that set up. You need to make sure the device drivers air, right, install a big piece of software. Ah, license key. I'm not making this up. They're still around. You may not even know what those are. You know, Dennis laughing because, you know, zero cool people do things like this anymore. Um, and it only runs some windows. You want a second user to use it? They need a copy. They need a code. Are they on the same version? It's a nightmare. The teams change, you know? You just say, Well, get everyone on the software. Well, who's everyone? You know, you got a new vendor today? A new customer tomorrow, a new employee. People come on and off the team. The other problem is the data stored in files, thousands of files. This isn't like a spreadsheet or word processor, where there's one file to pass around these air thousands of files to make one, even a simple product. People were tearing their hair out. John, what do we do? I've got copies everywhere. I don't know where the latest version is. We tried like, you know, locking people out so that only one person can change it At the time that works against speed, it works against innovation. We saw what was happening with Cloud Web and mobile. So what's happened in the years since is every one of the forces that product developers experience the need for speed, the need for innovation, the need to be more efficient with their people in their capital. Resource is every one of those trends have been amplified since we started on shape by a lot of forces in the world. And covert is amplified all those the need for agility and remote work cove it is amplified all that the same time, The acceptance of cloud. You know, a few years ago, people were like cloud, you know, how is that gonna work now They're saying to me, You know, increasingly, how would you ever even have done this without the cloud. How do you make solid works work without the cloud? How would that even happen? You know, once people understand what on shapes about >>and we're the >>Onley full SAS solution software >>as a service, >>full SAS solution in our industry. So what's happened in those years? Same problems we saw earlier, but turn up the gain, their bigger problems. And with cloud, we've seen skepticism of years ago turn into acceptance. And now even embracement in the cova driven new normal. >>Yeah. So a lot of friction in the previous environments cloud obviously a huge factor on, I guess. I guess Dana John could see it coming, you know, in the early days of solid works with, you know, had Salesforce, which is kind of the first major independent SAS player. Well, I guess that was late nineties. So his post solid works, but pre in shape and their work day was, you know, pre on shape in the mid two thousands. And and but But, you know, the bet was on the SAS model was right for Crick had and and product development, you know, which maybe the time wasn't a no brainer. Or maybe it was, I don't know, but Dana is there. Is there anything that you would invest in today? That's not Cloud based? >>Um, that's a great question. I mean, I think we still see things all the time in the manufacturing world that are not cloud based. I think you know, the closer you get to the shop floor in the production environment. Um e think John and the PTC folks would agree with this, too, but that it's, you know, there's reliability requirements, performance requirements. There's still this attitude of, you know, don't touch the printing press. So the cloud is still a little bit scary sometimes. And I think hybrid cloud is a real thing for those or on premise. Solutions, in some cases is still a real thing. What what we're more focused on. And, um, despite whether it's on premise or hybrid or or SAS and Cloud is a frictionless go to market model, um, in the companies we invest in so sass and cloud, or really make that easy to adopt for new users, you know, you sign up, started using a product, um, but whether it's hosted in the cloud, whether it's as you can still distribute buying power. And, um, I would I'm just encouraging customers in the customer world and the more industrial environment to entrust some of their lower level engineers with more budget discretionary spending so they can try more products and unlock innovation. >>Right? The unit economics are so compelling. So let's bring it, you know, toe today's you know, situation. John, you decided to exit about a year ago. You know? What did you see in PTC? Other than the obvious money? What was the strategic fit? >>Yeah, Well, David, I wanna be clear. I didn't exit anything. Really? You >>know, I love you and I don't like that term exit. I >>mean, Dana had exit is a shareholder on and so it's not It's not exit for me. It's just a step in the journey. What we saw in PTC was a partner. First of all, that shared our vision from the top down at PTC. Jim Hempleman, the CEO. He had a great vision for for the impact that SAS can make based on cloud technology and really is Dana of highlighted so much. It's not just the technology is how you go to market and the whole business being run and how you support and make the customers successful. So Jim shared a vision for the potential. And really, really, um said Hey, come join us and we can do this bigger, Better, faster. We expanded the vision really to include this Atlas platform for hosting other SAS applications. That P D. C. I mean, David Day arrived at PTC. I met the head of the academic program. He came over to me and I said, You know, and and how many people on your team? I thought he'd say 5 40 people on the PTC academic team. It was amazing to me because, you know, we were we were just near about 100 people were required are total company. We didn't even have a dedicated academic team and we had ah, lot of students signing up, you know, thousands and thousands. Well, now we have hundreds of thousands of students were approaching a million users and that shows you the power of this team that PTC had combined with our product and technology whom you get a big success for us and for the teachers and students to the world. We're giving them great tools. So so many good things were also putting some PTC technology from other parts of PTC back into on shape. One area, a little spoiler, little sneak peek. Working on taking generative design. Dana knows all about generative design. We couldn't acquire that technology were start up, you know, just to too much to do. But PTC owns one of the best in the business. This frustrated technology we're working on putting that into on shaping our customers. Um, will be happy to see it, hopefully in the coming year sometime. >>It's great to see that two way exchange. Now, you both know very well when you start a company, of course, a very exciting time. You know, a lot of baggage, you know, our customers pulling you in a lot of different directions and asking you for specials. You have this kind of clean slate, so to speak in it. I would think in many ways, John, despite you know, your install base, you have a bit of that dynamic occurring today especially, you know, driven by the forced march to digital transformation that cove it caused. So when you sit down with the team PTC and talk strategy. You now have more global resource is you got cohorts selling opportunities. What's the conversation like in terms of where you want to take the division? >>Well, Dave, you actually you sounds like we should have you coming in and talking about strategy because you've got the strategy down. I mean, we're doing everything said global expansion were able to reach across selling. We got some excellent PTC customers that we can reach reach now and they're finding uses for on shape. I think the plan is to, you know, just go, go, go and grow, grow, grow where we're looking for this year, priorities are expand the product. I mentioned the breath of the product with new things PTC did recently. Another technology that they acquired for on shape. We did an acquisition. It was it was small, wasn't widely announced. It, um, in an area related to interfacing with electrical cad systems. So So we're doing We're expanding the breath of on shape. We're going Maura, depth in the areas were already in. We have enormous opportunity to add more features and functions that's in the product. Go to market. You mentioned it global global presence. That's something we were a little light on a year ago. Now we have a team. Dana may not even know what we have. A non shape, dedicated team in Barcelona, based in Barcelona but throughout Europe were doing multiple languages. Um, the academic program just introduced a new product into that space that z even fueling more success and growth there. Um, and of course, continuing to to invest in customer success and this Atlas platform story I keep mentioning, we're going to soon have We're gonna soon have four other major PTC brands shipping products on our Atlas Saas platform. And so we're really excited about that. That's good for the other PTC products. It's also good for on shape because now there's there's. There's other interesting products that are on shape customers can use take advantage of very easily using, say, a common log in conventions about user experience there, used to invest of all they're SAS based, so they that makes it easier to begin with. So that's some of the exciting things going on. I think you'll see PTC, um, expanding our lead in SAS based applications for this sector for our our target, uh, sectors not just in, um, in cat and data management, but another area. PTC's Big and his augmented reality with of euphoria, product line leader and industrial uses of a R. That's a whole other story we should do. A whole nother show augmented reality. But these products are amazing. You can you can help factory workers people on, uh, people who are left out of the digital transformation. Sometimes we're standing from machine >>all day. >>They can't be sitting like we are doing Zoom. They can wear a R headset in our tools, let them create great content. This is an area Dana is invested in other companies. But what I wanted to note is the new releases of our authoring software. For this, our content getting released this month, used through the Atlas platform, the SAS components of on shape for things like revision management and collaboration on duh workflow activity. All that those are tools that we're able to share leverage. We get a lot of synergy. It's just really good. It's really fun to have a good time. That's >>awesome. And then we're gonna be talking to John MacLean later about that. Let's do a little deeper Dive on that. And, Dana, what is your involvement today with with on shape? But you're looking for you know, which of their customers air actually adopting. And they're gonna disrupt their industries. And you get good pipeline from that. How do you collaborate today? >>That sounds like a great idea. Um, Aziz, John will tell you I'm constantly just asking him for advice and impressions of other entrepreneurs and picking his brain on ideas. No formal relationship clearly, but continue to count John and and John and other people in on shaping in the circle of experts that I rely on for their opinions. >>All right, so we have some questions from the crowd here. Uh, one of the questions is for the dream team. You know, John and Dana. What's your next next collective venture? I don't think we're there yet, are we? No. >>I just say, as Dana said, we love talking to her about. You know, Dana, you just returned the compliment. We would try and give you advice and the deals you're looking at, and I'm sort of casually mentoring at least one of your portfolio entrepreneurs, and that's been a lot of fun for May on, hopefully a value to them. But also Dana. We uran important pipeline to us in the world of some new things that are happening that we wouldn't see if you know you've shown us some things that you've said. What do you think of this business? And for us, it's like, Wow, it's cool to see that's going on And that's what's supposed to work in an ecosystem like this. So we we deeply value the ongoing relationship. And no, we're not starting something new. I got a lot of work left to do with what I'm doing and really happy. But we can We can collaborate in this way on other ventures. >>I like this question to somebody asking With the cloud options like on shape, Wilmore students have stem opportunities s Oh, that's a great question. Are you because of sass and cloud? Are you able to reach? You know, more students? Much more cost effectively. >>Yeah, Dave, I'm so glad that that that I was asked about this because Yes, and it's extremely gratified us. Yes, we are because of cloud, because on shape is the only full cloud full SAS system or industry were able to reach. Stem education brings able to be part of bringing step education to students who couldn't get it otherwise. And one of most gratifying gratifying things to me is the emails were getting from teachers, um, that that really, um, on the phone calls that were they really pour their heart out and say We're able to get to students in areas that have very limited compute resource is that don't have an I T staff where they don't know what computer that the students can have at home, and they probably don't even have a computer. We're talking about being able to teach them on a phone to have an android phone a low end android phone. You can do three D modeling on there with on shape. Now you can't do it any other system, but with on shape, you could do it. And so the teacher can say to the students, They have to have Internet access, and I know there's a huge community that doesn't even have Internet access, and we're not able, unfortunately to help that. But if you have Internet and you have even an android phone, we can enable the educator to teach them. And so we have case after case of saving a stem program or expanding it into the students that need it most is the ones we're helping here. So really excited about that. And we're also able to let in addition to the run on run on whatever computing devices they have, we also offer them the tools they need for remote teaching with a much richer experience. Could you teach solid works remotely? Well, maybe if the student ran it had a windows workstation. You know, big, big, high end workstation. Maybe it could, but it would be like the difference between collaborating with on shape and collaborate with solid works. Like the difference between a zoom video call and talking on the landline phone. You know, it's a much richer experience, and that's what you need. And stem teaching stem is hard, So yeah, we're super super. Um, I'm excited about bringing stem to more students because of cloud yond >>we're talking about innovation for good, and then the discussion, John, you just had it. Really? There could be a whole another vector here. We could discuss on diversity, and I wanna end with just pointing out. So, Dana, your new firm, it's a woman led firm, too. Two women leaders, you know, going forward. So that's awesome to see, so really? Yeah, thumbs up on that. Congratulations on getting that off the ground. >>Thank you. Thank you. >>Okay, so thank you guys. Really appreciate It was a great discussion. I learned a lot and I'm sure the audience did a swell in a moment. We're gonna talk with on shaped customers to see how they're applying tech for good and some of the products that they're building. So keep it right there. I'm Dave Volonte. You're watching innovation for good on the Cube, the global leader in digital tech event coverage. Stay right there. >>Oh, yeah, it's >>yeah, yeah, around >>the globe. It's the Cube presenting innovation for good. Brought to you by on shape. >>Okay, we're back. This is Dave Volonte and you're watching innovation for good. A program on Cuba 3 65 made possible by on shape of PTC company. We're live today really live tv, which is the heritage of the Cube. And now we're gonna go to the sources and talkto on shape customers to find out how they're applying technology to create real world innovations that are changing the world. So let me introduce our panel members. Rafael Gomez Furberg is with the Chan Zuckerberg bio hub. A very big idea. And collaborative nonprofit was initiative that was funded by Mark Zuckerberg and his wife, Priscilla Chan, and really around diagnosing and curing and better managing infectious diseases. So really timely topic. Philip Tabor is also joining us. He's with silver side detectors, which develops neutron detective detection systems. Yet you want to know if early, if neutrons and radiation or in places where you don't want them, So this should be really interesting. And last but not least, Matthew Shields is with the Charlottesville schools and is gonna educate us on how he and his team are educating students in the use of modern engineering tools and techniques. Gentlemen, welcome to the Cuban to the program. This should be really interesting. Thanks for coming on. >>Hi. Or pleasure >>for having us. >>You're very welcome. Okay, let me ask each of you because you're all doing such interesting and compelling work. Let's start with Rafael. Tell us more about the bio hub and your role there, please. >>Okay. Yeah. So you said that I hope is a nonprofit research institution, um, funded by Mark Zuckerberg and his wife, Priscilla Chan. Um, and our main mission is to develop new technologies to help advance medicine and help, hopefully cure and manage diseases. Um, we also have very close collaborations with Universe California, San Francisco, Stanford University and the University California Berkeley on. We tried to bring those universities together, so they collaborate more of biomedical topics. And I manage a team of engineers. They by joining platform. Um, and we're tasked with creating instruments for the laboratory to help the scientist boats inside the organization and also in the partner universities Do their experiments in better ways in ways that they couldn't do before >>in this edition was launched Well, five years ago, >>it was announced at the end of 2016, and we actually started operation with at the beginning of 2017, which is when I joined, um, So this is our third year. >>And how's how's it going? How does it work? I mean, these things take time. >>It's been a fantastic experience. Uh, the organization works beautifully. Um, it was amazing to see it grow From the beginning, I was employee number 12, I think eso When I came in, it was just a nem P office building and empty labs. And very quickly we had something running about. It's amazing eso I'm very proud of the work that we have done to make that possible. Um And then, of course, that's you mentioned now with co vid, um, we've been able to do a lot of very cool work attire being of the pandemic in March, when there was a deficit of testing, uh, capacity in California, we spun up a testing laboratory in record time in about a week. It was crazy. It was a crazy project, Um, but but incredibly satisfying. And we ended up running all the way until the beginning of November, when the lab was finally shut down. We could process about 3000 samples a day. I think at the end of it all, we were able to test about 100 on the order of 100 and 50,000 samples from all over the state. We were providing free testing toe all of the Department of Public Health Department of Public Health in California, which at the media pandemic, had no way to do testing affordably and fast. So I think that was a great service to the state. Now the state has created that testing system that would serve those departments. So then we decided that it was unnecessary to keep going with testing in the other biopsy that would shut down. >>All right. Thank you for that. Now, Now, Philip, you What you do is mind melting. You basically helped keep the world safe. Maybe describe a little bit more about silver sod detectors and what your role is there and how it all works. >>Tour. So we make a nuclear bomb detectors and we also make water detectors. So we try and do our part thio keep the world from blowing up and make it a better place at the same time. Both of these applications use neutron radiation detectors. That's what we make. Put them out by import border crossing places like that. They can help make sure that people aren't smuggling. Shall we say very bad things. Um, there's also a burgeoning field of research and application where you can use neutrons with some pretty cool physics to find water so you could do things. Like what? A detector up in the mountains and measure snowpack. Put it out in the middle of the field and measure soil moisture content. And as you might imagine, there's some really cool applications in, uh, research and agronomy and public policy for this. >>All right, so it's OK, so it's a It's much more than, you know, whatever fighting terrorism, it's there's a riel edge or I kind of i o t application for what you guys >>do. We do both its's to plowshares. You might >>say a mat. I I look at your role is kind of scaling the brain power for for the future. Maybe tell us more about Charlottesville schools and in the mission that you're pursuing and what you do. >>Thank you. Um, I've been in Charlottesville City schools for about 11 or 12 years. I started their teaching, um, a handful of classes, math and science and things like that. But Thescore board and my administration had the crazy idea of starting an engineering program about seven years ago. My background is an engineering is an engineering. My masters is in mechanical and aerospace engineering and um, I basically spent a summer kind of coming up with what might be a fun engineering curriculum for our students. And it started with just me and 30 students about seven years ago, Um, kind of a home spun from scratch curriculum. One of my goals from the outset was to be a completely project based curriculum, and it's now grown. We probably have about six or 700 students, five or six full time teachers. We now have pre engineering going on at the 5th and 6th grade level. I now have students graduating. Uh, you know, graduating after senior year with, like, seven years of engineering under their belt and heading off to doing some pretty cool stuff. So it's It's been a lot of fun building a program and, um, and learning a lot in the process. >>That's awesome. I mean, you know, Cuba's. We've been passionate about things like women in tech, uh, diversity stem. You know, not only do we need more, more students and stem, we need mawr underrepresented women, minorities, etcetera. We were just talking to John Herstek and integrate gration about this is Do you do you feel is though you're I mean, first of all, the work that you do is awesome, but but I'll go one step further. Do you feel as though it's reaching, um, or diverse base? And how is that going? >>That's a great question. I think research shows that a lot of people get funneled into one kind of track or career path or set of interests really early on in their educational career, and sometimes that that funnel is kind of artificial. And so that's one of the reasons we keep pushing back. Um, so our school systems introducing kindergartners to programming on DSO We're trying to push back how we expose students to engineering and to stem fields as early as possible. And we've definitely seen the first of that in my program. In fact, my engineering program, uh, sprung out of an after school in Extracurricular Science Club that actually three girls started at our school. So I think that actually has helped that three girls started the club that eventually is what led to our engineering programs that sort of baked into the DNA and also our eyes a big public school. And we have about 50% of the students are under the poverty line and we e in Charlottesville, which is a big refugee town. And so I've been adamant from Day one that there are no barriers to entry into the program. There's no test you have to take. You don't have to have be taking a certain level of math or anything like that. That's been a lot of fun. To have a really diverse set of kids enter the program and be successful, >>that's final. That's great to hear. So, Philip, I wanna come back to you. You know, I think about maybe some day we'll be able to go back to a sporting events, and I know when I when I'm in there, there's somebody up on the roof looking out for me, you know, watching the crowd, and they have my back. And I think in many ways, the products that you build, you know, our similar. I may not know they're there, but they're keeping us safe or they're measuring things that that that I don't necessarily see. But I wonder if you could talk about a little bit more detail about the products you build and how they're impacting society. >>Sure, so There are certainly a lot of people who are who are watching, trying to make sure things were going well in keeping you safe that you may or may not be aware of. And we try and support ah lot of them. So we have detectors that are that are deployed in a variety of variety of uses, with a number of agencies and governments that dio like I was saying, ports and border crossing some other interesting applications that are looking for looking for signals that should not be there and working closely to fit into the operations these folks do. Onda. We also have a lot of outreach to researchers and scientists trying to help them support the work they're doing. Um, using neutron detection for soil moisture monitoring is a some really cool opportunities for doing it at large scale and with much less, um, expense or complication than would have been done. Previous technologies. Um, you know, they were talking about collaboration in the previous segment. We've been able to join a number of conferences for that, virtually including one that was supposed to be held in Boston, but another one that was held out of the University of Heidelberg in Germany. And, uh, this is sort of things that in some ways, the pandemic is pushing people towards greater collaboration than they would have been able to do. Had it all but in person. >>Yeah, we did. Uh, the cube did live works a couple years ago in Boston. It was awesome show. And I think, you know, with this whole trend toward digit, I call it the Force march to digital. Thanks to cove it I think that's just gonna continue. Thio grow. Rafael. What if you could describe the process that you use to better understand diseases? And what's your organization's involvement? Been in more detail, addressing the cove in pandemic. >>Um, so so we have the bio be structured in, Um um in a way that foster so the combination of technology and science. So we have to scientific tracks, one about infectious diseases and the other one about understanding just basic human biology, how the human body functions, and especially how the cells in the human body function on how they're organized to create tissues in the body. On Ben, it has this set of platforms. Um, mind is one of them by engineering that are all technology rated. So we have data science platform, all about data analysis, machine learning, things like that. Um, we have a mass spectrometry platform is all about mass spectrometry technologies to, um, exploit those ones in service for the scientist on. We have a genomics platform that it's all about sequencing DNA and are gonna, um and then an advanced microscopy. It's all about developing technologies, uh, to look at things with advanced microscopes and developed technologies to marry computation on microscopy. So, um, the scientists set the agenda and the platforms, we just serve their needs, support their needs, and hopefully develop technologies that help them do their experiments better, faster, or allow them to the experiment that they couldn't do in any other way before. Um And so with cove, it because we have that very strong group of scientists that work on have been working on infectious disease before, and especially in viruses, we've been able to very quickly pivot to working on that s O. For example, my team was able to build pretty quickly a machine to automatically purified proteins on is being used to purify all these different important proteins in the cove. It virus the SARS cov to virus Onda. We're sending some of those purified proteins all over the world. Two scientists that are researching the virus and trying to figure out how to develop vaccines, understand how the virus affects the body and all that. Um, so some of the machines we built are having a very direct impact on this. Um, Also for the copy testing lab, we were able to very quickly develop some very simple machines that allowed the lab to function sort of faster and more efficiently. Sort of had a little bit of automation in places where we couldn't find commercial machines that would do it. >>Um, eso Matt. I mean, you gotta be listening to this and thinking about Okay, So someday your students are gonna be working at organizations like like, like Bio Hub and Silver Side. And you know, a lot of young people they're just don't know about you guys, but like my kids, they're really passionate about changing the world. You know, there's way more important than you know, the financial angles and it z e. I gotta believe you're seeing that you're right in the front lines there. >>Really? Um, in fact, when I started the curriculum six or seven years ago, one of the first bits of feedback I got from my students is they said Okay, this is a lot of fun. So I had my students designing projects and programming microcontrollers raspberry, PiS and order we nose and things like that. The first bit of feedback I got from students was they said Okay, when do we get to impact the world? I've heard engineering >>is about >>making the world a better place, and robots are fun and all, but, you know, where is the real impact? And so um, dude, yeah, thanks to the guidance of my students, I'm baking that Maurin. Now I'm like day one of engineering one. We talk about how the things that the tools they're learning and the skills they're gaining, uh, eventually, you know, very soon could be could be used to make the world a better place. >>You know, we all probably heard that famous line by Jeff Hammer Barker. The greatest minds of my generation are trying to figure out how to get people to click on ads. I think we're really generally generationally, finally, at the point where young students and engineering a really, you know, a passionate about affecting society. I wanna get into the product, you know, side and understand how each of you are using on shape and and the value that that it brings. Maybe Raphael, you could start how long you've been using it. You know, what's your experience with it? Let's let's start there. >>I begin for about two years, and I switched to it with some trepidation. You know, I was used to always using the traditional product that you have to install on your computer, that everybody uses that. So I was kind of locked into that. But I started being very frustrated with the way it worked, um, and decided to give on ship chance. Which reputation? Because any change always, you know, causes anxiety. Um, but very quickly my engineers started loving it, Uh, just because it's it's first of all, the learning curve wasn't very difficult at all. You can transfer from one from the traditional product to entree very quickly and easily. You can learn all the concepts very, very fast. It has all the functionality that we needed and and what's best is that it allows to do things that we couldn't do before or we couldn't do easily. Now we can access the our cat documents from anywhere in the world. Um, so when we're in the lab fabricating something or testing a machine, any computer we have next to us or a tablet or on iPhone, we can pull it up and look at the cad and check things or make changes. That's something that couldn't do before because before you had to pay for every installation off the software for the computer, and I couldn't afford to have 20 installations to have some computers with the cat ready to use them like once every six months would have been very inefficient. So we love that part. And the collaboration features are fantastic, especially now with Kobe, that we have to have all the remote meetings eyes fantastic, that you can have another person drive the cad while the whole team is watching that person change the model and do things and point to things that is absolutely revolutionary. We love it. The fact that you have very, very sophisticated version control before it was always a challenge asking people, please, if you create anniversary and apart, how do we name it so that people find it? And then you end up with all these collection of files with names that nobody ever remembers, what they are, the person left. And now nobody knows which version is the right one. A mess with on shape on the version ING system it has, and the fact that you can go back in history off the document and go back to previous version so easily and then go back to the press and version and explore the history of the part that is truly, um, just world changing for us, that we can do that so easily on for me as a manager to manage this collection of information that is critical for our operations. It makes it so much easier because everything is in one place. I don't have to worry about file servers that go down that I have to administer that have to have I t taken care off that have to figure how to keep access to people to those servers when they're at home, and they need a virtual private network and all of that mess disappears. I just simply give give a person in accounting on shape and then magically, they have access to everything in the way I want. And we can manage the lower documents and everything in a way that is absolutely fantastic. >>Feel what was your what? What were some of the concerns you had mentioned? You had some trepidation. Was it a performance? Was it security? You know some of the traditional cloud stuff, and I'm curious as to how, How, whether any of those act manifested really that you had to manage. What were your concerns? >>Look, the main concern is how long is it going to take for everybody in the team to learn to use the system like it and buy into it? Because I don't want to have my engineers using tools against their will write. I want everybody to be happy because that's how they're productive. They're happy, and they enjoyed the tools they have. That was my main concern. I was a little bit worried about the whole concept of not having the files in a place where I couldn't quote unquote seat in some server and on site, but that That's kind of an outdated concept, right? So that took a little bit of a mind shift, but very quickly. Then I started thinking, Look, I have a lot of documents on Google Drive. Like, I don't worry about that. Why would I worry about my cat on on shape, right? Is the same thing. So I just needed to sort of put things in perspective that way. Um, the other, um, you know, the concern was the learning curve, right? Is like, how is he Will be for everybody to and for me to learn it on whether it had all of the features that we needed. And there were a few features that I actually discussed with, um uh, Cody at on shape on, they were actually awesome about using their scripting language in on shape to sort of mimic some of the features of the old cat, uh, in on, shaped in a way that actually works even better than the old system. So it was It was amazing. Yeah, >>Great. Thank you for that, Philip. What's your experience been? Maybe you could take us through your journey within shape. >>Sure. So we've been we've been using on shaped silver side for coming up on about four years now, and we love it. We're very happy with it. We have a very modular product line, so we make anything from detectors that would go into backpacks. Two vehicles, two very large things that a shipping container would go through and saw. Excuse me. Shape helps us to track and collaborate faster on the design. Have multiple people working a same time on a project. And it also helps us to figure out if somebody else comes to us and say, Hey, I want something new how we congrats modules from things that we already have put them together and then keep track of the design development and the different branches and ideas that we have, how they all fit together. A za design comes together, and it's just been fantastic from a mechanical engineering background. I will also say that having used a number of different systems and solid works was the greatest thing since sliced bread. Before I got using on shape, I went, Wow, this is amazing and I really don't want to design in any other platform. After after getting on Lee, a little bit familiar with it. >>You know, it's funny, right? I'll have the speed of technology progression. I was explaining to some young guns the other day how I used to have a daytime er and that was my life. And if I lost that daytime, er I was dead. And I don't know how we weigh existed without, you know, Google maps eso we get anywhere, I don't know, but, uh but so So, Matt, you know, it's interesting to think about, you know, some of the concerns that Raphael brought up, you hear? For instance, you know, all the time. Wow. You know, I get my Amazon bill at the end of the month that zip through the roof in, But the reality is that Yeah, well, maybe you are doing more, but you're doing things that you couldn't have done before. And I think about your experience in teaching and educating. I mean, you so much more limited in terms of the resource is that you would have had to be able to educate people. So what's your experience been with With on shape and what is it enabled? >>Um, yeah, it was actually talking before we went with on shape. We had a previous CAD program, and I was talking to my vendor about it, and he let me know that we were actually one of the biggest CAD shops in the state. Because if you think about it a really big program, you know, really big company might employ. 5, 10, 15, 20 cad guys, right? I mean, when I worked for a large defense contractor, I think there were probably 20 of us as the cad guys. I now have about 300 students doing cat. So there's probably more students with more hours of cat under their belt in my building than there were when I worked for the big defense contractor. Um, but like you mentioned, uh, probably our biggest hurdle is just re sources. And so we want We want one of things I've always prided myself and trying to do in this. Programs provide students with access two tools and skills that they're going to see either in college or in the real world. So it's one of the reason we went with a big professional cad program. There are, you know, sort of K 12 oriented software and programs and things. But, you know, I want my kids coding and python and using slack and using professional type of tools on DSO when it comes to cat. That's just that That was a really hurt. I mean, you know, you could spend $30,000 on one seat of, you know, professional level cad program, and then you need a $30,000 computer to run it on if you're doing a heavy assemblies, Um and so one of my dreams And it was always just a crazy dream. And I was the way I would always pitcher in my school system and say, someday I'm gonna have a kid on a school issued chromebook in subsidized housing, on public WiFi doing professional level bad and that that was a crazy statement until a couple of years ago. So we're really excited that I literally and you know, March and you said the forced march, the forced march into, you know, modernity, March 13th kids sitting in my engineering lab that we spent a lot of money on doing cad March 14th. Those kids were at home on their school issued chromebooks on public WiFi, uh, keeping their designs going and collaborating. And then, yeah, I could go on and on about some of the things you know, the features that we've learned since then they're even better. So it's not like this is some inferior, diminished version of Academy. There's so much about it. Well, I >>wanna I wanna ask you that I may be over my skis on this, but we're seeing we're starting to see the early days of the democratization of CAD and product design. It is the the citizen engineer, I mean, maybe insulting to the engineers in the room, But but is that we're beginning to see that >>I have to believe that everything moves into the cloud. Part of that is democratization that I don't need. I can whether you know, I think artists, you know, I could have a music studio in my basement with a nice enough software package. And Aiken, I could be a professional for now. My wife's a photographer. I'm not allowed to say that I could be a professional photographer with, you know, some cloud based software, and so, yeah, I do think that's part of what we're seeing is more and more technology is moving to the cloud. >>Philip. Rafael Anything you Dad, >>I think I mean, yeah, that that that combination of cloud based cat and then three d printing that is becoming more and more affordable on ubiquitous It's truly transformative, and I think for education is fantastic. I wish when I was a kid I had the opportunity to play with those kinds of things because I was always the late things. But, you know, the in a very primitive way. So, um, I think this is a dream for kids. Teoh be able to do this. And, um, yeah, there's so many other technologies coming on, like Arduino on all of these electronic things that live kids play at home very cheaply with things that back in my day would have been unthinkable. >>So we know there's a go ahead. Philip, please. >>We had a pandemic and silver site moved to a new manufacturing facility this year. I was just on the shop floor, talking with contractors, standing 6 ft apart, pointing at things. But through it all, our CAD system was completely unruffled. Nothing stopped in our development work. Nothing stopped in our support for existing systems in the field. We didn't have to think about it. We had other server issues, but none with our, you know, engineering cad, platform and product development in support world right ahead, which was cool, but also a in that's point. I think it's just really cool what you're doing with the kids. The most interesting secondary and college level engineering work that I did was project based, taken important problem to the world. Go solve it and that is what we do here. That is what my entire career has been. And I'm super excited to see. See what your students are going to be doing, uh, in there home classrooms on their chromebooks now and what they do building on that. >>Yeah, I'm super excited to see your kids coming out of college with engineering degrees because, yeah, I think that Project based experience is so much better than just sitting in a classroom, taking notes and doing math problems on day. I think it will give the kids a much better flavor. What engineering is really about Think a lot of kids get turned off by engineering because they think it's kind of dry because it's just about the math for some very abstract abstract concept on they are there. But I think the most important thing is just that hands on a building and the creativity off, making things that you can touch that you can see that you can see functioning. >>Great. So, you know, we all know the relentless pace of technology progression. So when you think about when you're sitting down with the folks that on shape and there the customer advisor for one of the things that that you want on shape to do that it doesn't do today >>I could start by saying, I just love some of the things that does do because it's such a modern platform. And I think some of these, uh, some some platforms that have a lot of legacy and a lot of history behind them. I think we're dragging some of that behind them. So it's cool to see a platform that seemed to be developed in the modern era, and so that Z it is the Google docks. And so the fact that collaboration and version ing and link sharing is and like platform agnostic abilities, the fact that that seems to be just built into the nature of the thing so far, That's super exciting. As far as things that, uh, to go from there, Um, I don't know, >>Other than price. >>You can't say >>I >>can't say lower price. >>Yeah, so far on P. D. C. S that work with us. Really? Well, so I'm not complaining. There you there, >>right? Yeah. Yeah. No gaps, guys. Whitespace, Come on. >>We've been really enjoying the three week update. Cadence. You know, there's a new version every three weeks and we don't have to install it. We just get all the latest and greatest goodies. One of the trends that we've been following and enjoying is the the help with a revision management and release work flows. Um, and I know that there's more than on shape is working on that we're very excited for, because that's a big important part about making real hardware and supporting it in the field. Something that was cool. They just integrated Cem markup capability. In the last release that took, we were doing that anyway, but we were doing it outside of on shapes. And now we get to streamline our workflow and put it in the CAD system where We're making those changes anyway when we're reviewing drawings and doing this kind of collaboration. And so I think from our perspective, we continue to look forward. Toa further progress on that. There's a lot of capability in the cloud that I think they're just kind of scratching the surface on you, >>right? I would. I mean, you're you're asking to knit. Pick. I would say one of the things that I would like to see is is faster regeneration speed. There are a few times with convicts, necessities that regenerating the document takes a little longer than I would like. It's not a serious issue, but anyway, I I'm being spoiled, >>you know? That's good. I've been doing this a long time, and I like toe ask that question of practitioners and to me, it It's a signal like when you're nit picking and that's what you're struggling to knit. Pick that to me is a sign of a successful product, and and I wonder, I don't know, uh, have the deep dive into the architecture. But are things like alternative processors. You're seeing them hit the market in a big way. Uh, you know, maybe helping address the challenge, But I'm gonna ask you the big, chewy question now. Then we maybe go to some audience questions when you think about the world's biggest problems. I mean, we're global pandemics, obviously top of mind. You think about nutrition, you know, feeding the global community. We've actually done a pretty good job of that. But it's not necessarily with the greatest nutrition, climate change, alternative energy, the economic divides. You've got geopolitical threats and social unrest. Health care is a continuing problem. What's your vision for changing the world and how product innovation for good and be applied to some of the the problems that that you all are passionate about? Big question. Who wants toe start? >>Not biased. But for years I've been saying that if you want to solve the economy, the environment, uh, global unrest, pandemics, education is the case. If you wanna. If you want to, um, make progress in those in those realms, I think funding funding education is probably gonna pay off pretty well. >>Absolutely. And I think Stam is key to that. I mean, all of the ah lot of the well being that we have today and then industrialized countries. Thanks to science and technology, right improvements in health care, improvements in communication, transportation, air conditioning. Um, every aspect of life is touched by science and technology. So I think having more kids studying and understanding that is absolutely key. Yeah, I agree, >>Philip, you got anything to add? >>I think there's some big technical problems in the world today, Raphael and ourselves there certainly working on a couple of them. Think they're also collaboration problems and getting everybody to be able to pull together instead of pulling separately and to be able to spur the ideas on words. So that's where I think the education side is really exciting. What Matt is doing and it just kind of collaboration in general when we could do provide tools to help people do good work. Uh, that is, I think, valuable. >>Yeah, I think that's a very good point. And along those lines, we have some projects that are about creating very low cost instruments for low research settings, places in Africa, Southeast Asia, South America, so that they can do, um, um, biomedical research that it's difficult to do in those place because they don't have the money to buy the fancy lab machines that cost $30,000 an hour. Um, so we're trying to sort of democratize some of those instruments. And I think thanks to tools like Kahn shape then is easier, for example, to have a conversation with somebody in Africa and show them the design that we have and discuss the details of it with them on. But it's amazing, right to have somebody, you know, 10 time zones away, Um, looking really life in real time with you about your design and discussing the details or teaching them how to build a machine, right? Because, um, you know, they have a three D printer. You can you can just give them the design and say like, you build it yourself, uh, even cheaper than and, you know, also billing and shipping it there. Um, so all that that that aspect of it is also super important. I think for any of these efforts to improve some of the hardest part was in the world for climate change. Do you say, as you say, poverty, nutrition issues? Um, you know, availability of water. You have that project at about finding water. Um, if we can also help deploy technologies that teach people remotely how to create their own technologies or how to build their own systems that will help them solve those forms locally. I think that's very powerful. >>Yeah, the point about education is right on. I think some people in the audience may be familiar with the work of Erik Brynjolfsson and Andrew McAfee, the second machine age where they sort of put forth the premise that, uh, is it laid it out. Look, for the first time in history, machines air replacing humans from a cognitive perspective. Machines have always replaced humans, but that's gonna have an impact on jobs. But the answer is not toe protect the past from the future. The answer is education and public policy that really supports that. So I couldn't agree more. I think it's a really great point. Um, we have We do have some questions from the audience. If if we could If I can ask you guys, um, you know, this one kind of stands out. How do you see artificial intelligence? I was just talking about machine intelligence. Um, how do you see that? Impacting the design space guys trying to infuse a I into your product development. Can you tell me? >>Um, absolutely, like, we're using AI for some things, including some of these very low cost instruments that will hopefully help us diagnose certain diseases, especially this is that are very prevalent in the Third World. Um, and some of those diagnostics are these days done by thes armies of technicians that are trained to look under the microscope. But, um, that's a very slow process. Is very error prone and having machine learning systems that can to the same diagnosis faster, cheaper and also little machines that can be taken to very remote places to these villages that have no access to a fancy microscope. To look at a sample from a patient that's very powerful. And I we don't do this, but I have read quite a bit about how certain places air using a Tribune attorneys to actually help them optimize designs for parts. So you get these very interesting looking parts that you would have never thought off a person would have never thought off, but that are incredibly light ink. Earlier, strong and I have all sort of properties that are interesting thanks to artificial intelligence machine learning in particular >>yet another. The advantage you get when when your work is in the cloud I've seen. I mean, there's just so many applications that so if the radiology scan is in the cloud and the radiologist is goes to bed at night, Radiologist could come in in the morning and and say, Oh, the machine while you were sleeping was using artificial intelligence to scan these 40,000 images. And here's the five that we picked out that we think you should take a closer look at. Or like Raphael said, I can design my part. My, my, my, my, my you know, mount or bracket or whatever and go to sleep. And then I wake up in the morning. The machine has improved. It for me has made it strider strider stronger and lighter. Um And so just when your when your work is in the cloud, that's just that's a really cool advantage that you get that you can have machines doing some of your design work for you. >>Yeah, we've been watching, uh, you know, this week is this month, I guess is AWS re invent and it's just amazing to see how much effort is coming around machine learning machine intelligence. You know Amazon has sage maker Google's got, you know, embedded you no ML and big query. Uh, certainly Microsoft with Azure is doing tons of stuff and machine learning. I think the point there is that that these things will be infused in tow R and D and in tow software product by the vendor community. And you all will apply that to your business and and build value through the unique data that your collecting, you know, in your ecosystems. And and that's how you add value. You don't have to be necessarily, you know, developers of artificial intelligence, but you have to be practitioners to apply that. Does that make sense to you, Philip? >>Yeah, absolutely. And I think your point about value is really well chosen. We see AI involved from the physics simulations all the way up to interpreting radiation data, and that's where the value question, I think, is really important because it's is the output of the AI giving helpful information that the people that need to be looking at it. So if it's curating a serious of radiation alert, saying, Hey, like these air the anomalies. You need to look at eyes it, doing that in a way that's going to help a good response on. In some cases, the II is only as good as the people. That sort of gave it a direction and turn it loose. And you want to make sure that you don't have biases or things like that underlying your AI that they're going to result in less than helpful outcomes coming from it. So we spend quite a lot of time thinking about how do we provide the right outcomes to people who are who are relying on our systems? >>That's a great point, right? Humans air biased and humans build models, so models are inherently biased. But then the software is hitting the market. That's gonna help us identify those biases and help us, you know? Of course. Correct. So we're entering Cem some very exciting times, guys. Great conversation. I can't thank you enough for spending the time with us and sharing with our audience the innovations that you're bringing to help the world. So thanks again. >>Thank you so much. >>Thank you. >>Okay. Welcome. Okay. When we come back, John McElheny is gonna join me. He's on shape. Co founder. And he's currently the VP of strategy at PTC. He's gonna join the program. We're gonna take a look at what's next and product innovation. I'm Dave Volonte and you're watching innovation for good on the Cube, the global leader. Digital technology event coverage. We'll be right back. >>Okay? Okay. Yeah. Okay. >>From around >>the globe, it's the Cube. Presenting innovation for good. Brought to you by on shape. >>Okay, welcome back to innovation. For good. With me is John McElheny, who is one of the co founders of On Shape and is now the VP of strategy at PTC. John, it's good to see you. Thanks for making the time to come on the program. Thanks, Dave. So we heard earlier some of the accomplishments that you've made since the acquisition. How has the acquisition affected your strategy? Maybe you could talk about what resource is PTC brought to the table that allowed you toe sort of rethink or evolve your strategy? What can you share with us? >>Sure. You know, a year ago, when when John and myself met with Jim Pepperman early on is we're we're pondering. Started joining PTC one of things became very clear is that we had a very clear shared vision about how we could take the on shape platform and really extended for, for all of the PTC products, particular sort of their augmented reality as well as their their thing works or the i o. T business and their product. And so from the very beginning there was a clear strategy about taking on shape, extending the platform and really investing, um, pretty significantly in the product development as well as go to market side of things, uh, toe to bring on shape out to not only the PTC based but sort of the broader community at large. So So So PTC has been a terrific, terrific, um, sort of partner as we've we've gonna go on after this market together. Eso We've added a lot of resource and product development side of things. Ah, lot of resource and they go to market and customer success and support. So, really, on many fronts, that's been both. Resource is as well a sort of support at the corporate level from from a strategic standpoint and then in the field, we've had wonderful interactions with many large enterprise customers as well as the PTC channels. So it's been really a great a great year. >>Well, and you think about the challenges of in your business going to SAS, which you guys, you know, took on that journey. You know, 78 years ago. Uh, it's not trivial for a lot of companies to make that transition, especially a company that's been around as long as PTC. So So I'm wondering how much you know, I was just asking you How about what PCP TC brought to the table? E gotta believe you're bringing a lot to the table to in terms of the mindset, uh, even things is, is mundane is not the right word, but things like how you compensate salespeople, how you interact with customers, the notion of a service versus a product. I wonder if you could address >>that. Yeah, it's a it's a really great point. In fact, after we had met Jim last year, John and I one of the things we walked out in the seaport area in Boston, one of things we sort of said is, you know, Jim really gets what we're trying to do here and and part of let me bring you into the thinking early on. Part of what Jim talked about is there's lots of, you know, installed base sort of software that's inside of PTC base. That's helped literally thousands of customers around the world. But the idea of moving to sass and all that it entails both from a technology standpoint but also a cultural standpoint. Like How do you not not just compensate the sales people as an example? But how do you think about customer success? In the past, it might have been that you had professional services that you bring out to a customer, help them deploy your solutions. Well, when you're thinking about a SAS based offering, it's really critical that you get customers successful with it. Otherwise, you may have turned, and you know it will be very expensive in terms of your business long term. So you've got to get customers success with software in the very beginning. So you know, Jim really looked at on shape and he said that John and I, from a cultural standpoint, you know, a lot of times companies get acquired and they've acquired technology in the past that they integrate directly into into PTC and then sort of roll it out through their products, are there just reached channel, he said. In some respects, John John, think about it as we're gonna take PTC and we want to integrate it into on shape because we want you to share with us both on the sales side and customer success on marketing on operations. You know all the things because long term, we believe the world is a SAS world, that the whole industry is gonna move too. So really, it was sort of an inverse in terms of the thought process related to normal transactions >>on That makes a lot of sense to me. You mentioned Sharon turns the silent killer of a SAS company, and you know, there's a lot of discussion, you know, in the entrepreneurial community because you live this, you know what's the best path? I mean today, You see, you know, if you watch Silicon Valley double, double, triple triple, but but there's a lot of people who believe, and I wonder, if you come in there is the best path to, you know, in the X Y axis. If if it's if it's uh, growth on one and retention on the other axis. What's the best way to get to the upper right on? Really? The the best path is probably make sure you've nailed obviously the product market fit, But make sure that you can retain customers and then throw gas on the fire. You see a lot of companies they burn out trying to grow too fast, but they haven't figured out, you know that. But there's too much churn. They haven't figured out those metrics. I mean, obviously on shape. You know, you were sort of a pioneer in here. I gotta believe you've figured out that customer retention before you really, You know, put the pedal to the >>metal. Yeah, and you know, growth growth can mask a lot of things, but getting getting customers, especially the engineering space. Nobody goes and sits there and says, Tomorrow we're gonna go and and, you know, put 100 users on this and and immediately swap out all of our existing tools. These tools are very rich and deep in terms of capability, and they become part of the operational process of how a company designs and builds products. So any time anybody is actually going through the purchasing process. Typically, they will run a try along or they'll run a project where they look at. Kind of What? What is this new solution gonna help them dio. How are we gonna orient ourselves for success? Longer term. So for us, you know, getting new customers and customer acquisition is really critical. But getting those customers to actually deploy the solution to be successful with it. You know, we like to sort of, say, the marketing or the lead generation and even some of the initial sales. That's sort of like the Kindle ing. But the fire really starts when customers deploy it and get successful. The solution because they bring other customers into the fold. And then, of course, if they're successful with it, you know, then in fact, you have negative turn which, ironically, means growth in terms of your inside of your install. Bates. >>Right? And you've seen that with some of the emerging, you know, SAS companies, where you're you're actually you know, when you calculate whatever its net retention or renew ALS, it's actually from a dollar standpoint. It's up in the high nineties or even over 100%. >>So >>and that's a trend we're gonna continue. See, I >>wonder >>if we could sort of go back. Uh, and when you guys were starting on shape, some of the things that you saw that you were trying to strategically leverage and what's changed, you know, today we were talking. I was talking to John earlier about in a way, you kinda you kinda got a blank slate is like doing another startup. >>You're >>not. Obviously you've got installed base and customers to service, but But it's a new beginning for you guys. So one of the things that you saw then you know, cloud and and sas and okay, but that's we've been there, done that. What are you seeing? You know today? >>Well, you know, So So this is a journey, of course, that that on shape on its own has gone through it had I'll sort of say, you know, several iterations, both in terms of of of, you know, how do you How do you get customers? How do you How do you get them successful? How do you grow those customers? And now that we've been part of PTC, the question becomes okay. One, There is certainly a higher level of credibility that helps us in terms of our our megaphone is much bigger than it was when we're standalone company. But on top of that now, figuring out how to work with their channel with their direct sales force, you know, they have, um, for example, you know, very large enterprises. Well, many of those customers are not gonna go in forklift out their existing solution to replace it with with on shape. However, many of them do have challenges in their supply chain and communications with contractors and vendors across the globe. And so, you know, finding our fit inside of those large enterprises as they extend out with their their customers is a very interesting area that we've really been sort of incremental to to PTC. And then, you know, they they have access to lots of other technology, like the i o. T business. And now, of course, the augmented reality business that that we can bring things to bear. For example, in the augmented reality world, they've they've got something called expert capture. And this is essentially imagine, you know, in a are ah, headset that allows you to be ableto to speak to it, but also capture images still images in video. And you could take somebody who's doing their task and capture literally the steps that they're taking its geo location and from their builds steps for new employees to be, we'll learn and understand how todo use that technology to help them do their job better. Well, when they do that, if there is replacement products or variation of of some of the tools that that they built the original design instruction set for they now have another version. Well, they have to manage multiple versions. Well, that's what on shape is really great at doing and so taking our technology and helping their solutions as well. So it's not only expanding our customer footprint, it's expanding the application footprint in terms of how we can help them and help customers. >>So that leads me to the tam discussion and again, as part of your strategist role. How do you think about that? Was just talking to some of your customers earlier about the democratization of cat and engineering? You know, I kind of joked, sort of like citizen engineering, but but so that you know, the demographics are changing the number of users potentially that can access the products because the it's so much more of a facile experience. How are you thinking about the total available market? >>It really is a great question, You know, it used to be when you when you sold boxes of software, it was how many engineers were out there. And that's the size of the market. The fact that matter is now when, When you think about access to that information, that data is simply a pane of glass. Whether it's a computer, whether it's a laptop, UH, a a cell phone or whether it's a tablet, the ability to to use different vehicles, access information and data expands the capabilities and power of a system to allow feedback and iteration. I mean, one of the one of the very interesting things is in technology is when you can take something and really unleash it to a larger audience and builds, you know, purpose built applications. You can start to iterate, get better feedback. You know there's a classic case in the clothing industry where Zara, you know, is a fast sort of turnaround. Agile manufacturer. And there was a great New York Times article written a couple years ago. My wife's a fan of Zara, and I think she justifies any purchases by saying, You know, Zara, you gotta purchase it now. Otherwise it may not be there the next time. Yet you go back to the store. They had some people in a store in New York that had this woman's throw kind of covering Shaw. And they said, Well, it would be great if we could have this little clip here so we can hook it through or something. And they sent a note back toe to the factory in Spain, and literally two weeks later they had, you know, 4000 of these things in store, and they sold out because they had a closed loop and iterative process. And so if we could take information and allow people access in multiple ways through different devices and different screens, that could be very specific information that, you know, we remove a lot of the engineering data book, bring the end user products conceptually to somebody that would have had to wait months to get the actual physical prototype, and we could get feedback well, Weaken have a better chance of making sure whatever product we're building is the right product when it ultimately gets delivered to a customer. So it's really it's a much larger market that has to be thought of rather than just the kind of selling A boxes software to an engineer. >>That's a great story. And again, it's gonna be exciting for you guys to see that with. The added resource is that you have a PTC, Um, so let's talk. I promise people we wanna talk about Atlas. Let's talk about the platform. A little bit of Atlas was announced last year. Atlas. For those who don't know it's a SAS space platform, it purports to go beyond product lifecycle management and you You're talking cloud like agility and scale to CAD and product design. But John, you could do a better job than I. What do >>we need to know about Atlas? Well, I think Atlas is a great description because it really is metaphorically sort of holding up all of the PTC applications themselves. But from the very beginning, when John and I met with Jim, part of what we were intrigued about was that he shared a vision that on shape was more than just going to be a cad authoring tool that, in fact, you know, in the past these engineering tools were very powerful, but they were very narrow in their purpose and focus. And we had specialty applications to manage the versions, etcetera. What we did in on shape is we kind of inverted that thinking. We built this collaboration and sharing engine at the core and then kind of wrap the CAD system around it. But that collaboration sharing and version ING engine is really powerful. And it was that vision that Jim had that he shared that we had from the beginning, which was, how do we take this thing to make a platform that could be used for many other applications inside of inside of any company? And so not only do we have a partner application area that is is much like the APP store or Google play store. Uh, that was sort of our first Stan Shih ation of this. This this platform. But now we're extending out to broader applications and much meatier applications. And internally, that's the thing works in the in the augmented reality. But there'll be other applications that ultimately find its way on top of this platform. And so they'll get all the benefits of of the collaboration, sharing the version ing the multi platform, multi device. And that's an extremely extremely, um, strategic leverage point for the company. >>You know, it's interesting, John, you mentioned the seaport before. So PTC, for those who don't know, built a beautiful facility down at the Seaport in Boston. And, of course, when PTC started, you know, back in the mid 19 eighties, there was nothing at the seaport s. >>So it's >>kind of kind of ironic, you know, we were way seeing the transformation of the seaport. We're seeing the transformation of industry and of course, PTC. And I'm sure someday you'll get back into that beautiful office, you know? Wait. Yeah, I'll bet. And, uh and but I wanna bring this up because I want I want you to talk about the future. How you how you see that our industry and you've observed this has moved from very product centric, uh, plat platform centric with sass and cloud. And now we're seeing ecosystems form around those products and platforms and data flowing through the ecosystem powering, you know, new innovation. I wonder if you could paint a picture for us of what the future looks like to you from your vantage point. >>Yeah, I think one of the key words you said there is data because up until now, data for companies really was sort of trapped in different applications. And it wasn't because people were nefarious and they want to keep it limited. It was just the way in which things were built. And, you know, when people use an application like on shape, what ends up happening is there their day to day interaction and everything that they do is actually captured by the platform. And, you know, we don't have access to that data. Of course it's it's the customer's data. But as as an artifact of them using the system than doing their day to day job, what's happening is they're creating huge amounts of information that can then be accessed and analyzed to help them both improve their design process, improve their efficiencies, improve their actual schedules in terms of making sure they can hit delivery times and be able to understand where there might be roadblocks in the future. So the way I see it is companies now are deploying SAS based tools like on shape and an artifact of them. Using that platform is that they have now analytics and tools to better understand and an instrument and manage their business. And then from there, I think you're going to see, because these systems are all you know extremely well. Architected allow through, you know, very structured AP. I calls to connect other SAS based applications. You're gonna start seeing closed loop sort of system. So, for example, people design using on shape, they end up going and deploying their system or installing it, or people use the end using products. People then may call back into the customers support line and report issues, problems, challenges. They'll be able to do traceability back to the underlying design. They'll be able to do trend analysis and defect analysis from the support lines and tie it back and closed loop the product design, manufacture, deployment in the field sort of cycles. In addition, you can imagine there's many things that air sort of as designed. But then when people go on site and they have to install it. There's some alterations modifications. Think about think about like a large air conditioning units for buildings. You go and you go to train and you get a large air conditioning unit that put up on top of building with a crane. They have to build all kinds of adaptors to make sure that that will fit inside of the particulars of that building. You know, with on shape and tools like this, you'll be able to not only take the design of what the air conditioning system might be, but also the all the adapter plates, but also how they installed it. So it sort of as designed as manufactured as stalled. And all these things can be traced, just like if you think about the transformation of customer service or customer contacts. In the early days, you used to have tools that were PC based tools called contact management solution, you know, kind of act or gold mine. And these were basically glorified Elektronik role in Texas. It had a customer names and they had phone numbers and whatever else. And Salesforce and Siebel, you know, these types of systems really broadened out the perspective of what a customer relationship? Waas. So it wasn't just the contact information it was, you know, How did they come to find out about you as a company? So all of the pre sort of marketing and then kind of what happens after they become a customer and it really was a 3 60 view. I think that 3 60 view gets extended to not just to the customers, but also tools and the products they use. And then, of course, the performance information that could come back to the manufacturer. So, you know, as an engineer, one of the things you learn about with systems is the following. And if you remember, when the CD first came out CDs that used to talk about four times over sampling or eight times over sampling and it was really kind of, you know, the fidelity the system. And we know from systems theory that the best way to improve the performance of a system is to actually have more feedback. The more feedback you have, the better system could be. And so that's why you get 16 60 for example, etcetera. Same thing here. The more feedback we have of different parts of a company that a better performance, The company will be better customer relationships. Better, uh, overall financial performance as well. So that's that's the view I have of how these systems all tied together. >>It's a great vision in your point about the data is I think right on. It used to be so fragmented in silos, and in order to take a system view, you've gotta have a system view of the data. Now, for years, we've optimized maybe on one little component of the system and that sometimes we lose sight of the overall outcome. And so what you just described, I think is, I think sets up. You know very well as we exit. Hopefully soon we exit this this covert era on John. I hope that you and I can sit down face to face at a PTC on shape event in the near term >>in the seaport in the >>seaport would tell you that great facility toe have have an event for sure. It >>z wonderful >>there. So So John McElhinney. Thanks so much for for participating in the program. It was really great to have you on, >>right? Thanks, Dave. >>Okay. And I want to thank everyone for participating. Today we have some great guest speakers. And remember, this is a live program. So give us a little bit of time. We're gonna flip this site over toe on demand mode so you can share it with your colleagues and you, or you can come back and and watch the sessions that you heard today. Uh, this is Dave Volonte for the Cube and on shape PTC. Thank you so much for watching innovation for good. Be well, Have a great holiday. And we'll see you next time. Yeah.

>>welcome back. And thanks for joining us for our second session. External data, your new leading indicators. We'll be hearing from industry leaders as they share best practices and challenges in leveraging external data. This panel will be a true conversation on the part of the possible. All right, let's get to >>it >>today. We're excited to be joined by thought spots. Chief Data Strategy Officer Cindy Housing Deloitte's chief data officer Manteo, the founder and CEO of Eagle Alfa. And it Kilduff and Snowflakes, VP of data marketplace and customer product strategy. Matt Glickman. Cindy. Without further ado, the floor is yours. >>Thank you, Mallory. And I am thrilled to have this brilliant team joining us from around the world. And they really bring each a very unique perspective. So I'm going to start from further away. Emmett, Welcome. Where you joining us from? >>Thanks for having us, Cindy. I'm joining from Dublin, Ireland, >>great. And and tell us a little bit about Eagle Alfa. What do you dio >>from a company's perspective? Think of Eagle Alfa as an aggregator off all the external data sets on a word I'll use a few times. Today is a big advantage we could bring companies is we have a data concierge service. There's so much data we can help identify the right data sets depending on the specific needs of the company. >>Yeah. And so, Emma, you know, people think I was a little I kind of shocked the industry. Going from gardener to a tech startup. Um, you have had a brave journey as well, Going from financial services to starting this company, really pioneering it with I think the most data sets of any of thes is that right? >>Yes, it was. It was a big jump to go from Morgan Stanley. Uh, leave the comforts of that environment Thio, PowerPoint deck and myself raising funding eight years ago s So it was a big jump on. We were very early in our market. It's in the last few years where there's been real momentum and adoption by various types of verticals. The hedge funds were first, maybe then private equity, but corporate sar are following quite quickly from behind. That will be the biggest users, in our view, by by a significant distance. >>Yeah, great. Thank um, it So we're going to go a little farther a field now, but back to the U. S. So, Juan, where you joining us from? >>Hey, Cindy. Thanks for having me. I'm joining you from Houston, Texas. >>Great. Used to be my home. Yeah, probably see Rice University back there. And you have a distinct perspective serving both Deloitte customers externally, but also internally. Can you tell us about that? >>Yeah, absolutely. So I serve as the Lord consultants, chief data officer, and as a professional service firm, I have the responsibility for overseeing our overall data agenda, which includes both the way we use data and insights to run and operate our own business, but also in how we develop data and insights services that we then take to market and how we serve our dealers and clients. >>Great. Thank you, Juan. And last but not least, Matt Glickman. Kind of in my own backyard in New York. Right, Matt? >>Correct. Joining I haven't been into the city and many months, but yes, um, based in New York. >>Okay. Great. And so, Matt, you and Emmett also, you know, brave pioneers in this space, and I'm remembering a conversation you and I shared when you were still a J. P. Morgan, I believe. And you're Goldman Sachs. Sorry. Sorry. Goldman. Can you Can you share that with us? >>Sure. I made the move back in 2015. Um, when everyone thought, you know, my wife, my wife included that I was crazy. I don't know if I would call it Comfortable was emitted, but particularly had been there for a long time on git suffered in some ways. A lot of the pains we're talking about today, given the number of data, says that the amount of of new data sets that are always demand for having run analytics teams at Goldman, seeing the pain and realizing that this pain was not unique to Goldman Sachs, it was being replicated everywhere across the industry, um, in a mind boggling way and and the fortuitous, um, luck to have one of snowflakes. Founders come to pitch snowflake to Goldman a little bit early. Um, they became a customer later, but a little bit early in 2014. And, you know, I realized that this was clearly, you know, the answer from first principles on bond. If I ever was going to leave, this was a problem. I was acutely aware of. And I also was aware of how much the man that was in financial services for a better solution and how the cloud could really solve this problem in particular the ability to not have to move data in and out of these organizations. And this was something that I saw the future of. Thank you, Andi, that this was, you know, sort of the pain that people just expected to pay. Um, this price if you need a data, there was method you had thio. You had to use you either ftp data in and out. You had data that was being, you know, dropped off and, you know, maybe in in in a new ways and cloud buckets or a P i s You have to suck all this data down and reconstruct it. And God forbid the formats change. It was, you know, a nightmare. And then having issues with data, you had a what you were seeing internally. You look nothing like what the data vendors were seeing because they want a completely different system, maybe model completely differently. Um, but this was just the way things were. Everyone had firewalls. Everyone had their own data centers. There was no other way on git was super costly. And you know this. I won't even share the the details of you know, the errors that would occur in the pain that would come from that, Um what I realized it was confirmed. What I saw it snowflake at the time was once everyone moves to run their actual workloads in this in the cloud right where you're now beyond your firewall, you'll have all this scale. But on top of that, you'll be able to point at data from these vendors were not there the traditional data vendors. Or, you know, this new wave of alternative data vendors, for example, like the ones that eagle out for brings together And bring these all these data sets together with your own internal data without moving it. Yeah, this was a fundamental shift of what you know, it's in some ways, it was a side effect of everyone moving to the cloud for costs and scale and elasticity. But as a side effect of that is what we talked about, You know it snowflake summit, you know, yesterday was this notion of a data cloud that would connect data between regions between cloud vendors between customers in a way where you could now reference data. Just like your reference websites today, I don't download CNN dot com. I point at it, and it points me to something else. I'm always seeing the latest version, obviously, and we can, you know, all collaborate on what I'm seeing on that website. That's the same thing that now can happen with data. So And I saw this as what was possible, and I distinctly asked the question, you know, the CEO of the time Is this possible? And not only was it possible it was a fundamental construct that was built into the way that snowflake was delivered. And then, lastly, this is what we learned. And I think this is what you know. M It also has been touting is that it's all great if data is out there and even if you lower that bar of access where data doesn't have to move, how do I know? Right? If I'm back to sitting at Goldman Sachs, how do I know what data is available to me now in this this you know, connected data network eso we released our data marketplace, which was a very different kind of marketplace than these of the past. Where for us, it was really like a global catalog that would elect a consumer data consumer. Noah data was available, but also level the playing field. Now we're now, you know, Eagle, Alfa, or even, you know, a new alternative data vendor build something in their in their basement can now publish that data set so that the world could see and consume and be aligned to, you know, snowflakes, core business, and not where we wouldn't have to be competing or having to take, um, any kind of custody of that data. So adding that catalog to this now ubiquitous access, um really changed the game and, you know, and then now I seem like a genius for making this move. But back then, like I said, we've seen I seem like instant. I was insane. >>Well, given, given that snowflake was the hottest aipo like ever, you were a genius. Uh, doing this, you know, six years in advance. E think we all agree on that, But, you know, a lot of this is still visionary. Um, you know, some of the most leading companies are already doing this. But one What? What is your take our Are you best in class customers still moving the data? Or is this like they're at least thinking about data monetization? What are you seeing from your perspective? >>Yeah, I mean, I did you know, the overall appreciation and understanding of you know, one. I got to get my house in order around my data, um, has something that has been, you know, understood and acted upon. Andi, I do agree that there is a shift now that says, you know, data silos alone aren't necessarily gonna bring me, you know, new and unique insights on dso enriching that with external third party data is absolutely, you know, sort of the the ship that we're seeing our customers undergo. Um, what I find extremely interesting in this space and what some of the most mature clients are doing is, you know, really taking advantage of these data marketplaces. But building data partnerships right there from what mutually exclusive, where there is a win win scenario for for you know, that organization and that could be, you know, retail customers or life science customers like with pandemic, right the way we saw companies that weren't naturally sharing information are now building these data partnership right that are going are going into mutually benefit, you know, all organizations that are sort of part of that value to Andi. I think that's the sort of really important criteria. And how we're seeing our clients that are extremely successful at this is that partnership has benefits on both sides of that equation, right? Both the data provider and then the consumer of that. And there has to be, you know, some way to ensure that both parties are are are learning right, gaining you insights to support, you know, whatever their business organization going on. >>Yeah, great one. So those data partnerships getting across the full value chain of sharing data and analytics Emmett, you work on both sides of the equation here, helping companies. Let's say let's say data providers maybe, like, you know, cast with human mobility monetize that. But then also people that are new to it. Where you seeing the top use cases? Well, >>interestingly, I agree with one of the supply side. One of the interesting trends is we're seeing a lot more data coming from large Corporates. Whether they're listed are private equity backed, as opposed to maybe data startups that are earning money just through data monetization. I think that's a great trend. I think that means a lot of the best. Data said it data is yet to come, um, in terms off the tough economy and how that's changed. I think the category that's had the most momentum and your references is Geo location data. It's that was the category at our conference in December 2000 and 12 that was pipped as the category to watch in 2019. On it didn't become that at all. Um, there were some regulatory concerns for certain types of geo data, but with with covert 19, it's Bean absolutely critical for governments, ministries of finance, central banks, municipalities, Thio crunch that data to understand what's happening in a real time basis. But from a company perspective, it's obviously critical as well. In terms of planning when customers might be back in the High Street on DSO, fourth traditionally consumer transaction data of all the 26 categories in our taxonomy has been the most popular. But Geo is definitely catching up your slide. Talked about being a tough economy. Just one point to contradict that for certain pockets of our clients, e commerce companies are having a field day, obviously, on they are very data driven and tech literate on day are they are really good client base for us because they're incredibly hungry, firm or data to help drive various, uh, decision making. >>Yeah, So fair enough. Some sectors of the economy e commerce, electron, ICS, healthcare are doing great. Others travel, hospitality, Um, super challenging. So I like your quote. The best is yet to come, >>but >>that's data sets is yet to come. And I do think the cloud is enabling that because we could get rid of some of the messy manual data flows that Matt you talked about, but nonetheless, Still, one of the hardest things is the data map. Things combining internal and external >>when >>you might not even have good master data. Common keys on your internal data. So any advice for this? Anyone who wants to take that? >>Sure I can. I can I can start. That's okay. I do think you know, one of the first problems is just a cataloging of the information that's out there. Um, you know, at least within our organization. When I took on this role, we were, you know, a large buyer of third party data. But our organization as a whole didn't necessarily have full visibility into what was being bought and for what purpose. And so having a catalog that helps us internally navigate what data we have and how we're gonna use it was sort of step number one. Um, so I think that's absolutely important. Um, I would say if we could go from having that catalog, you know, created manually to more automated to me, that's sort of the next step in our evolution, because everyone is saying right, the ongoing, uh, you know, creation of new external data sets. It's only going to get richer on DSO. We wanna be able to take advantage of that, you know, at the at the pacing speed, that data is being created. So going from Emanuel catalog to anonymous >>data >>catalog, I think, is a key capability for us. But then you know, to your second point, Cindy is how doe I then connect that to our own internal data to drive greater greater insights and how we run our business or how we serve our customers. Andi, that one you know really is a It's a tricky is a tricky, uh, question because I think it just depends on what data we're looking toe leverage. You know, we have this concept just around. Not not all data is created equal. And when you think about governance and you think about the management of your master data, your internal nomenclature on how you define and run your business, you know that that entire ecosystem begins to get extremely massive and it gets very broad and very deep on DSO for us. You know, government and master data management is absolutely important. But we took a very sort of prioritized approach on which domains do we really need to get right that drive the greatest results for our organization on dso mapping those domains like client data or employee data to these external third party data sources across this catalog was really the the unlocked for us versus trying to create this, you know, massive connection between all the external data that we're, uh, leveraging as well as all of our own internal data eso for us. I think it was very. It was a very tailored, prioritized approach to connecting internal data to external data based on the domains that matter most to our business. >>So if the domains so customer important domain and maybe that's looking at things, um, you know, whether it's social media data or customer transactions, you prioritized first by that, Is that right? >>That's correct. That's correct. >>And so, then, Matt, I'm going to throw it back to you because snowflake is in a unique position. You actually get to see what are the most popular data sets is is that playing out what one described are you seeing that play out? >>I I'd say Watch this space. Like like you said. I mean this. We've you know, I think we start with the data club. We solve that that movement problem, which I think was really the barrier that you tended to not even have a chance to focus on this mapping problem. Um, this notion of concordance, I think this is where I see the big next momentum in this space is going to be a flurry of traditional and new startups who deliver this concordance or knowledge graph as a service where this is no longer a problem that I have to solve internal to my organization. The notion of mastering which is again when everyone has to do in every organization like they used to have to do with moving data into the organization goes away. And this becomes like, I find the best of breed for the different scopes of data that I have. And it's delivered to me as a, you know, as a cloud service that just takes my data. My internal data maps it to these 2nd and 3rd party data sets. Um, all delivered to me, you know, a service. >>Yeah, well, that would be brilliant concordance as a service or or clean clean master data as a service. Um, using augmented data prep would be brilliant. So let's hope we get there. Um, you know, so 2020 has been a wild ride for everyone. If I could ask each of you imagine what is the art of the possible or looking ahead to the next to your and that you are you already mentioned the best is yet to come. Can you want to drill down on that. What what part of the best is yet to come or what is your already two possible? >>Just just a brief comment on mapping. Just this week we published a white paper on mapping, which is available for for anyone on eagle alfa dot com. It's It's a massive challenge. It's very difficult to solve. Just with technology Onda people have tried to solve it and get a certain level of accuracy, but can't get to 100% which which, which, which makes it difficult to solve it. If if if there is a new service coming out against 100% I'm all ears and that there will be a massive step forward for the entire data industry, even if it comes in a few years time, let alone next year, I think going back to the comment on data Cindy. Yes, I think boards of companies are Mawr and Mawr. Viewing data as an asset as opposed to an expense are a cost center on bond. They are looking therefore to get their internal house in order, as one was saying, but also monetize the data they are sitting on lots of companies. They're sitting on potentially valuable data. It's not all valuable on a lot of cases. They think it's worth a lot more than it is being frank. But in some cases there is valuable data on bond. If monetized, it can drop to the bottom line on. So I think that bodes well right across the world. A lot of the best date is yet to come on. I think a lot of firms like Deloitte are very well positioned to help drive that adoption because they are the trusted advisor to a lot of these Corporates. Um, so that's one thing. I think, from a company perspective. It's still we're still at the first base. It's quite frustrating how slow a lot of companies are to move and adopt, and some of them are haven't hired CDO. Some of them don't have their internal house in order. I think that has to change next year. I think if we have this conference at this time next year, I would expect that would hopefully be close to the tipping point for Corporates to use external data. And the Malcolm Gladwell tipping point on the final point I make is I think, that will hopefully start to see multi department use as opposed to silos again. Parliaments and silos, hopefully will be more coordinated on the company's side. Data could be used by marketing by sales by r and D by strategy by finance holds external data. So it really, hopefully will be coordinated by this time next year. >>Yeah, Thank you. So, to your point, there recently was an article to about one of the airlines that their data actually has more value than the company itself now. So I know, I know. We're counting on, you know, integrators trusted advisers like Deloitte to help us get there. Uh, one what? What do you think? And if I can also drill down, you know, financial services was early toe all of this because they needed the early signals. And and we talk about, you know, is is external data now more valuable than internal? Because we need those early signals in just such a different economy. >>Yeah, I think you know, for me, it's it's the seamless integration of all these external data sources and and the signals that organizations need and how to bring those into, you know, the day to day operations of your organization, right? So how do you bring those into, You know, you're planning process. How do you bring that into your sales process on DSO? I think for me success or or where I see the that the use and adoption of this is it's got to get down to that level off of operations for organizations. For this to continue to move at the pace and deliver the value that you know, we're all describing. I think we're going to get there. But I think until organizations truly get down to that level of operations and how they're using this data, it'll sort of seem like a Bolton, right? So for me, I think it's all about Mawr, the seamless integration. And I think to what Matt mentioned just around services that could help connect external data with internal data. I'll take that one step beyond and say, How can we have the data connect itself? Eso I had references Thio, you know, automation and machine learning. Um, there's significant advances in terms of how we're seeing, you know, mapping to occur in a auto generated fashion. I think this specific space and again the connection between external and internal data is a prime example of where we need to disrupt that, you know, sort of traditional data pipeline on. Try to automate that as much as possible. And let's have the data, you know, connect itself because it then sort of supports. You know, the first concept which waas How do we make it more seamless and integrated into, you know, the business processes of the organization's >>Yeah, great ones. So you two are thinking those automated, more intelligent data pipelines will get us there faster. Matt, you already gave us one. Great, Uh, look ahead, Any more to add to >>it, I'll give you I'll give you two more. One is a bit controversial, but I'll throw that you anyway, um, going back to the point that one made about data partnerships What you were saying Cindy about, you know, the value. These companies, you know, tends to be somehow sometimes more about the data they have than the actual service they provide. I predict you're going to see a wave of mergers and acquisitions. Um, that it's solely about locking down access to data as opposed to having data open up. Um to the broader, you know, economy, if I can, whether that be a retailer or, you know, insurance company was thes prime data assets. Um, you know, they could try to monetize that themselves, But if someone could acquire them and get exclusive access that data, I think that's going to be a wave of, um, in a that is gonna be like, Well, we bought this for this amount of money because of their data assets s. So I think that's gonna be a big wave. And it'll be maybe under the guise of data partnerships. But it really be about, you know, get locking down exclusive access to valuable data as opposed to trying toe monetize it itself number one. And then lastly, you know. Now, did you have this kind of ubiquity of data in this interconnected data network? Well, we're starting to see, and I think going to see a big wave of is hyper personalization of applications where instead of having the application have the data itself Have me Matt at Snowflake. Bring my data graph to applications. Right? This decoupling of we always talk about how you get data out of these applications. It's sort of the reverse was saying Now I want to bring all of my data access that I have 1st, 2nd and 3rd party into my application. Instead of having to think about getting all the data out of these applications, I think about it how when you you know, using a workout app in the consumer space, right? I can connect my Spotify or connect my apple music into that app to personalize the experience and bring my music list to that. Imagine if I could do that, you know, in a in a CRM. Imagine I could do that in a risk management. Imagine I could do that in a marketing app where I can bring my entire data graph with me and personalize that experience for, you know, for given what I have. And I think again, you know, partners like thoughts. But I think in a unique position to help enable that capability, you know, for this next wave of of applications that really take advantage of this decoupling of data. But having data flow into the app tied to me as opposed to having the APP have to know about my data ahead of time, >>Yeah, yeah, So that is very forward thinking. So I'll end with a prediction and a best practice. I am predicting that the organizations that really leverage external data, new data sources, not just whether or what have you and modernize those data flows will outperform the organizations that don't. And as a best practice to getting there, I the CDOs that own this have at least visibility into everything they're purchasing can save millions of dollars in duplicate spend. So, Thio, get their three key takeaways. Identify the leading indicators and market signals The data you need Thio. Better identify that. Consolidate those purchases and please explore the data sets the range of data sets data providers that we have on the thought spot. Atlas Marketplace Mallory over to you. >>Wow. Thank you. That was incredible. Thank you. To all of our Panelists for being here and sharing that wisdom. We really appreciate it. For those of you at home, stay close by. Our third session is coming right up and we'll be joined by our partner AWS and get to see how you can leverage the full power of your data cloud complete with the demo. Make sure to tune in to see you >>then

>>covering the space and cybersecurity symposium 2020 hosted by Cal poly. Hold on. Welcome to this special presentation with Cal poly hosting the space and cybersecurity symposium, 2020 virtual, um, John for your host with the cube and Silicon angle here in our Palo Alto studios with our remote guests, we couldn't be there in person, but we're going to be here remotely. Got a great session and a panel for one hour topic preparing students for the jobs of today and tomorrow, but a great lineup. Bill Britain, Lieutenant Colonel from the us air force, retired vice president for information technology and CIO and the director of the California cyber security Institute for Cal poly bill. Thanks for joining us, dr. Amy Fisher, who's the Dean of the college of engineering at Cal poly and trunk fam professor and researcher at the U S air force Academy. Folks, thanks for joining me today. >>Our pleasure got a great, great panel. This is one of my favorite topics preparing students for the next generation, the jobs for today and tomorrow. We've got an hour. I'd love you guys to start with an opening statement, to kick things off a bill. We'll start with you. Well, I'm really pleased to be, to start on this. Um, as the director for the cybersecurity Institute and the CIO at Cal poly, it's really a fun, exciting job because as a Polytechnic technology, as such a forefront in what we're doing, and we've had a, a wonderful opportunity being 40 miles from Vandenberg air force base to really look at the nexus of space and cyber security. And if you add into that, uh, both commercial government and civil space and cybersecurity, this is an expanding wide open time for cyber and space. In that role that we have with the cyber security Institute, we partner with elements of the state and the university. >>And we try to really add value above our academic level, which is some of the highest in the nation and to really merge down and go a little lower and start younger. So we actually are running the week prior to this showing a cybersecurity competition for high schools or middle schools in the state of California, that competition this year is based on a scenario around hacking of a commercial satellite and the forensics of the payload that was hacked and the networks associated with it. This is going to be done using products like Wireshark autopsy and other tools that will give those high school students. What we hope is a huge desire to follow up and go into cyber and cyber space and space and follow that career path. And either come to Cal poly or some other institution that's going to let them really expand their horizons in cybersecurity and space for the future >>Of our nation. >>Bill, thanks for that intro, by the way, it's gonna give you props for an amazing team and job you guys are doing at Cal poly, that Dex hub and the efforts you guys are having with your challenge. Congratulations on that great work. Thank you >>Star team. It's absolutely amazing. You find that much talent in one location. And I think Amy is going to tell you she's got the same amount of talent in her staff. So it's, it's a great place to be. >>Amy flasher. You guys have a great organization down there, amazing curriculum, grazing people, great community, your opening statement. >>Hello everybody. It's really great to be a part of this panel on behalf of the Cal poly college of engineering here at Cal poly, we really take preparing students for the jobs of today and tomorrow completely seriously. And we claim that our students really graduate. So they're ready day one for their first real job, but that means that in getting them to that point, we have to help them get valuable and meaningful job experience before they graduate, but through our curriculum and through multiple internship or summer research opportunities. So we focus our curriculum on what we call a learn by doing philosophy. And this means that we have a combination of practical experience and learn by doing both in and out of the classroom. And we find that to be really critical for preparing students for the workforce here at Cal poly, we have more than 6,000 engineering students. >>We're one of the largest undergraduate engineering schools in the country. Um, and us news ranks us the eighth best undergraduate engineering program in the, in the country and the top ranked state school. We're really, really proud that we offer this impactful hands on engineering education that really exceeds that of virtually all private universities while reaching a wider audience of students. We offer 14 degree programs and really we're talking today about cyber and space. And I think most of those degree programs can really make an impact in the space and cybersecurity economy. And this includes not only things like Aero and cyber directly, but also electrical engineering, mechanical engineering, computer engineering, materials, engineering, even manufacturing, civil and biomedical engineering. As there's a lot of infrastructure needs that go into supporting launch capabilities. Our aerospace program graduates hundreds of aerospace engineers, and most of them are working right here in California. >>I'm with many of our corporate partners, including Northrop Grumman, Lockheed, Boeing, Raytheon space, X, Virgin, galactic JPL, and so many other places where we have Cal poly engineer's impacting the space economy. Our cybersecurity focus is found mainly in our computer science and software engineering programs. And it's really a rapidly growing interest among our students. Computer science is our most popular major and industry interest and partnerships are integrated into our curriculum. And we do that oftentimes through support from industry. So we have partnerships with Northrop Grumman for professorship and a cyber lab and from PG and E for critical infrastructure, cybersecurity lab, and professorship. And we think that industry partnerships like these are really critical to preparing students for the future as the field's evolving so quickly and making sure we adapt our facilities and our curriculum to stay in line with what we're seeing in industry is incredibly important. >>In our aerospace program, we have an educational partnership with the air force research labs. That's allowing us to install new high performance computing capabilities and a space environments lab. That's going to enhance our satellite design capabilities. And if we talk about satellite design, Cal poly is the founding home of the cube sat program, which pioneered small satellite capabilities. And we remain the worldwide leader in maintaining the cube set standard. And our student program has launched more cube sets than any other program. So here again, we have this learn by doing experience every year for dozens of aerospace, electrical, computer science, mechanical engineering students, and other student activities that we think are just as important include ethical hacking through our white hat club, Cal poly space systems, which does really, really big rocket launches and our support program for women in both of these fields like wish, which is women in software and hardware. >>Now, you know, really trying to bring in a wide variety of people into these fields is incredibly important and outreach and support to those demographics. Traditionally underrepresented in these fields is going to be really critical to future success. So by drawing on the lived experiences by people with different types of backgrounds, while we develop the type of culture and environment where all of us can get to the best solution. So in terms of bringing people into the field, we see that research shows, we need to reach kids when they're in late elementary and middle schools to really overcome that cultural bias that works against diversity in our fields. And you heard bill talking about the cyber cybersec, the California cybersecurity institutes a year late cyber challenge. There's a lot of other people who are working to bring in a wider variety of, uh, of people into the field, like girl Scouts, which has introduced dozens of new badges over the past few years, including a whole cybersecurity series of badges and a concert with Palo Alto networks. So we have our work cut out for us, but we know what we need to do. And if we're really committed to prep properly preparing the workforce for today and tomorrow, I think our future is going to be bright. I'm looking forward to our discussion today. >>Yeah, you got a flashy for great, great comment, opening statement and congratulations. You got the right formula down there, the right mindset, and you got a lot of talent and community as well. Thank thank you for that opening statement. Next step from Colorado Springs, trunk fam, who's a professor and researcher. The us air force Academy is doing a lot of research around the areas that are most important for the intersection of space and technology trunk. >>Good afternoon, first electric and Cal poli for the opportunity. And today I want to go briefly about cyber security in S application. Whenever we talk about cyber security, the impression is got yes, a new phew that is really highly complex involving a lot of technical area. But in reality, in my personal opinion, it is in be complex because involve many disciplines. The first thing we think about is computer engineering and computer networking, but it's also involving communication sociology, law practice. And this practice of cyber security goes in on the info computer expert, but it's also info everybody else who has a computing device that is connected to the internet. And this participation is obviously every body in today's environment. When we think about the internet, we know that is a good source of information, but come with the convenience of information that we can access. >>We are constantly faced in being from the internet. Some of them, we might be aware of some of them we might not be aware of. For example, when we search on the internet, a lot of time, our browser will be saved and gotten this site is not trusted. So we will be more careful. What about the sites that we trusted? We know getting those salad chicken sites, but they're not a hundred percent good at proof. What happened? It was all side, uh, attack by hacker. And then they will be a silent source that we might not be aware of. So in the reality, we need to be more practicing the, um, cyber security from our SIBO point of view and not from a technical point of view. When we talk about space application, we should know that all the hardware, a computer based tool by computer system and therefore the hardware and the software must go through some certification process so that they can be record that air with the flight. >>What the, when we know that in the certification process is focusing on the functionality of the hardware and software, but one aspect that is explicitly and implicitly required is the security of those components. And we know that those components have to be connected with the ground control station and be communication is through the air, through the layby or signal. So anybody who has access to those communication regular signal will be able to control the space system that we put up there. And we certainly do not want our system to be hijacked by a third party. >>I'm not going to aspect of cybersecurity is we try to design the space system in a very strong manner. So it's almost impossible to hack in, but what about some August week system that might be connected to so strong system? For example, the spare system will be connected to the ground control station and on the ground control station, we have the human controller in those people have cell phone. They are allowed to use cell phones for communication, but at the same time, they are connected to the internet, to the cell phone and their cell phone might be connected to the computer that control the flight software and hardware. So what I want to say is that we try to build strong system and we protected them, but there will be some weaker system that we could not intended, but exists to be connected to our strong system. And those are the points that hacker will be trying to attack. If we know how to control the access to those points, we will be having a much better system for the space system. And when we see the cybersecurity that is requiring the participation everywhere, it's important to Merck that there is a source of opportunity for students to engage the workforce. To concede the obviously student in engineering can focus their knowledge and expertise to provide technological solution, to protect the system that we view. But we also >>Have students in business who can focus to write a business plan to reach the market. We also have student in law who can focus policy governing the cyber security. And we also have student in education who can focus the expert. She should be saying how to teach cyber security practice and students can focus the effort to implement security measures and it implies job opportunity. >>Thank you trunk for those great comments, great technology opportunities, but interesting as well as the theme that we're seeing across the entire symposium and in the virtual hallways that we're hearing conversations and you pointed out some of them, dr. Fleischer did as well. And bill, you mentioned it. It's not one thing. It's not just technology, it's different skills. And, um, Amy, you mentioned that computer science is the hottest degree, but you have the hottest aerospace program in the world. I mean, so all of this is kind of balancing it's interdisciplinary. It's a structural change before we get into some of the, um, how they prepare the students. Can you guys talk about some of the structural changes that are modern now in preparing, um, in these opportunities because societal impact is a law potentially impact it's, it's how we educate there's no cross-discipline skillsets. It's not just get the degree, see out in the field bill, you want to start. >>Well, what's really fun about this job is, is that in the air force, uh, I worked in the space and missile business and what we saw was a heavy reliance on checklist format, security procedures, analog systems, and what we're seeing now in our world, both in the government and the commercial side, uh, is a move to a digital environment. And the digital environment is a very quick and adaptive environment. And it's going to require a digital understanding. Matter of fact, um, the, uh, under secretary of the air force for acquisition, uh, rev recently referenced the need to understand the digital environment and how that's affecting acquisition. So as, as both Amy, um, and trunk said, even business students are now in the >>Cybersecurity business. And, and so, again, what we're seeing is, is the change. Now, another phenomenon that we're seeing in the space world is there's just so much data. Uh, one of the ways that we addressed that in the past was to look at high performance computing. It was a lot stricter control over how that worked, but now what we're seeing these adaptation of cloud cloud technologies in space support, space, data, command, and control. Uh, and so what we see is a modern space engineer who asked to understand digital, has to understand cloud and has to understand the context of all those with a cyber environment. That's really changing the forefront of what is a space engineer, what is a digital engineer and what does a future engineer, both commercial or government? So I think the opportunity for all of these things is really good, particularly for a Polytechnic air force Academy and others that are focusing on a more, uh, widened experiential level of cloud and engineering and other capabilities. >>And I'll tell you the part that as the CIO, I have to remind everybody, all this stuff works for the it stuff. So you've got to understand how your it infrastructures are tied and working together. Um, as we noted earlier, one of the things is, is that these are all relays from point the point, and that architecture is part of your cybersecurity architecture. So again, every component has now become a cyber aware cyber knowledgeable, and in what we'd like to call as a cyber cognizant citizen, where they have to understand the context, patients chip software, that the Fleischer talk about your perspective, because you mentioned some of the things that computer science. Remember when I'm in the eighties, when I got my computer science degree, they call the software engineers, and then you became software developers. And then, so again, engineering is the theme. If you're engineering a system, there's now software involved, um, and there's also business engineering business models. So talk about some of your comments was, you mentioned, computer science is hot. You got the aerospace, you've got these multidisciplines you got definitely diversity as well. It brings more perspectives in as well. Your thoughts on these structural interdisciplinary things. >>I think this is, this is really key to making sure that students are prepared to work in the workforce is looking at the, the blurring between fields no longer are you just a computer scientist, no longer are you just an aerospace engineer? You really have to have an expertise where you can work with people across disciplines. All of these, all of these fields are just working with each other in ways we haven't seen before. And bill brought up data, you know, data science is something that's cross cutting across all of our fields. So we want engineers that have the disciplinary expertise so that they can go deep into these fields, but we want them to be able to communicate with each and to be able to communicate across disciplines and to be able to work in teams that are across disciplines. You can no longer just work with other computer scientists or just work with other aerospace engineers. >>There's no part of engineering that is siloed anymore. So that's how we're changing. You have to be able to work across those, those disciplines. And as you, as Tron pointed out, you know, ethics has to come into this. So you can no longer try to fully separate what we would traditionally have called the, the liberal arts and say, well, that's over there in general education. No ethics is an important part of what we're doing and how we integrate that into our curriculum. So it was communication. So is working on public policy and seeing where all of these different aspects tied together to make the impact that we want to have in the world. So it, you no longer can work solo in these fields. >>Great point. And bill also mentioned the cloud. One thing about the cloud that showed us as horizontal scalability has created a lot of value and certainly data is now horizontal Trung. You mentioned some of the things about cryptography for the kids out there. I mean, you can look at the pathway for career. You can do a lot of tech and, but you don't have to go deep. Sometimes you can go, you can go as deep as you want, but there's so much more there. Um, what technology do you see, how it's going to help students in your opinion? >>Well, I'm a professor in computer science, so I'd like to talk out a little bit about computer programming. Now we, uh, working in complex project. So most of the time we design a system from scratch. We view it from different components and the components that we have either we get it from or some time we get it from the internet in the open source environment, it's fun to get the source code and then work to our own application. So now when we are looking at a Logie, when we talk about encryption, for example, we can easily get the source code from the internet. And the question is, is safe to use those source code. And my, my, my question is maybe not. So I always encourage my students to learn how to write source score distribution, where that I learned a long time ago before I allow them to use the open source environment. And one of the things that they have to be careful, especially with encryption is be quote that might be hidden in the, in the source, get the download here, some of the source. >>So open source, it's a wonderful place to be, but it's also that we have to be aware of >>Great point before we get into some of the common one quick thing for each of you like to get your comments on, you know, the there's been a big movement on growth mindset, which has been a great, I'm a big believer in having a growth mindset and learning and all that good stuff. But now that when you talk about some of these things that we're mentioning about systems, there's, there's an, there's a new trend around a systems mindset, because if everything's now a system distributed systems, now you have space in cyber security, you have to understand the consequences of changes. And you mentioned some of that Trung in changes in the source code. Could you guys share your quick opinions on the, the idea of systems thinking, is that a mindset that people should be looking at? Because it used to be just one thing, Oh, you're a systems guy or galley. There you go. You're done. Now. It seems to be in social media and data. Everything seems to be systems. What's your take dr. Fleischer, we'll start with you. >>Uh, I'd say it's a, it's another way of looking at, um, not being just so deep in your discipline. You have to understand what the impact of the decisions that you're making have on a much broader, uh, system. And so I think it's important for all of our students to get some exposure to that systems level thinking and looking at the greater impact of the decision that they're making. Now, the issue is where do you set the systems boundary, right? And you can set the systems boundary very close in and concentrate on an aspect of a design, or you can continually move that system boundary out and see, where do you hit the intersections of engineering and science along with ethics and public policy and the greater society. And I think that's where some of the interesting work is going to be. And I think at least exposing students and letting them know that they're going to have to make some of these considerations as they move throughout their career is going to be vital as we move into the future. Bill. What's your thoughts? >>Um, I absolutely agree with Amy and I think there's a context here that reverse engineering, um, and forensics analysis and forensics engineering are becoming more critical than ever, uh, the ability to look at what you have designed in a system and then tear it apart and look at it for gaps and holes and problem sets, or when you're given some software that's already been pre developed, checking it to make sure it is, is really going to do what it says it's going to do. That forensics ability becomes more and more a skillset that also you need the verbal skills to explain what it is you're doing and what you found. So the communication side, the systems analysis, >>The forensics analysis side, >>These are all things that are part of that system >>Approach that I think you could spend hours on. And we still haven't really done great job on it. So it's a, it's. One of my fortes is the really the whole analysis side of forensics and it reverse engineering >>Try and real quick systems thinking. >>Well, I'd like to share with you my experience. When I worked in the space patient program at NASA, we had two different approaches. One is a down approach where we design it from the system general point of view, where we put components to complex system. But at the same time, we have the bottom up approach where we have Ken Chile who spent time and effort the individual component. And they have to be expert in those Chinese component. That might be general component the gallery. And in the space station program, we bring together the welcome up engineer, who designed everything in detail in the system manager who manage the system design from the top down. And we meet in the middle and took the idea with compromise a lot of differences. Then we can leave a display station that we are operating to be okay, >>Great insight. And that's the whole teamwork collaboration that, that was mentioning. Thanks so much for that insight. I wanted to get that out there because I know myself as a, as a parent, I'm always trying to think about what's best for my kids in their friends, as they grow up into the workforce. I know educators and leaders in industry would love to know some of the best practices around some of the structural changes. So thanks for that insight, but this topics about students and helping them prepare. Uh, so we heard, you know, be, be multiple discipline, broaden your horizons, think like systems top down, bottom up, work together as a team and follow the data. So I got to ask you guys, there's a huge amount of job openings in cybersecurity. It's well documented and certainly at the intersection of space and cyber, it's only gonna get bigger, right? You're going to see more and more demand for new types of jobs. How do we get high school and college students interested in security as a career at the flagship? We'll start with you in this one. >>I would say really one of the best ways to get students interested in the career is to show them the impact that it's going to have. There's definitely always going to be students who are going to want to do the technology for the technology sake, but that will limit you to a narrow set of students. And by showing that the greater impact that these types of careers are going to have on the types of problems that you're going to be able to solve and the impact you're going to be able to have on the world, around you, that's the word that we really need to get out. And a wide variety of students really respond to these messages. So I think it's really kind of reaching out at the, uh, the elementary, the middle school level, and really kind of getting this idea that you can make a big difference, a big positive difference in the field with some of these careers is going to be really critical. >>Real question, follow up. What do you think is the best entry point? You mentioned middle squad in here, elementary school. This comes, there's a lot of discussions around pipelining and we're going to get into women in tech and under-represented matters later, but you know, is it too early or what's the, what's your feeling on this? >>My feeling is the earlier we can normalize it the better the, uh, if you can normalize an interest in, in computers and technology and building an elementary school, that's absolutely critical. But the dropoff point that we're seeing is between what I would call like late elementary and early middle school. Um, and just kind of as an anecdote, I, for years ran an outreach program for girl Scouts in grades four and five and grade six, seven, and eight. And we had a hundred slots in each program. And every year the program would sell out for girls in grades four and five, and every year we'd have spots remaining in grades six, seven, and eight. And that's literally where the drop-off is occurring between that late elementary and that middle school range. So that's the area that we need to target to make sure we keep those young women involved and interested as we move forward. >>Bill, how are we going to get these kids interested in security? You mentioned a few programs you got. Yeah. I mean, who wants to, who wouldn't want to be a white hat hacker? I mean, yeah, that sounds exciting. Yeah. Great questions. Let's start with some basic principles though. Is let me ask you a question, John, a name for me, one white hat, good person hacker. The name who works in the space industry and is an exemplar for students to look up to, um, you, um, Oh man. I'm hearing really. I can't, I can't, I can't, I can't imagine because the answer we normally get is the cricket sound. So we don't have individuals we've identified in those areas for them to look up to. I was going to be snarky and say, most white hackers won't even use their real name, but, um, there's a, there's an aura around their anonymity here. >>So, so again, the real question is, is how do we get them engaged and keep them engaged? And that's what Amy was pointing out too. Exactly the engagement and sticking with it. So one of the things that we're trying to do through our competition on the state level and other elements is providing connections. We call them ambassadors. These are people in the business who can contact the students that are in the game or in that, uh, challenge environment and let them interact and let them talk about what they do and what they're doing in life would give them a challenging game format. Um, a lot of computer based training, um, capture the flag stuff is great, but if you can make it hands on, if you can make it a learn by doing experiment, if you can make it am personally involved and see the benefit as a result of doing that challenge and then talk to the people who do that on a daily basis, that's how you get them involved. >>The second part is as part of what we're doing is, is we're involving partnership companies in the development of the teams. So this year's competition that we're running has 82 teams from across the state of California, uh, of those 82 teams at six students team, middle school, high school, and many of those have company partners. And these are practitioners in cybersecurity who are working with those students to participate. It's it's that adult connectivity, it's that visualization. Um, so at the competition this year, um, we have the founder of Def con red flag is a participant to talk to the students. We have Vince surf as who is of course, very well known for something called the internet to participate. It's really getting the students to understand who's in this. Who can I look up to and how do I stay engaged with them? >>There's definitely a celebrity aspect of it. I will agree. I mean, the influencer aspect here with knowledge is key. Can you talk about, um, these ambassadors and, and, and how far along are you on that program? First of all, the challenge stuff is anything gamification wise. We've seen that with hackathons is just really works well. Grades, bonding, people who create together kinda get sticky and get very high community aspect to it. Talking about this ambassador thing. What does that industry is that academic >>Absolutely partners that we've identified? Um, some of which, and I won't hit all of them. So I'm sure I'll short changes, but, uh, Palo Alto, Cisco, um, Splunk, um, many of the companies in California and what we've done is identified, uh, schools, uh, to participate in the challenge that may not have a strong STEM program or have any cyber program. And the idea of the company is they look for their employees who are in those school districts to partner with the schools to help provide outreach. It could be as simple as a couple hours a week, or it's a team support captain or it's providing computers and other devices to use. Uh, and so again, it's really about a constant connectivity and, uh, trying to help where some schools may not have the staff or support units in an area to really provide them what they need for connectivity. What that does gives us an opportunity to not just focus on it once a year, but throughout the year. So for the competition, all the teams that are participating have been receiving, um, training and educational opportunities in the game of education side, since they signed up to participate. So there's a website, there's learning materials, there's materials provided by certain vendor companies like Wireshark and others. So it's a continuum of opportunity for the, >>You know, I've seen just the re randomly, just going to random thought, you know, robotics clubs are moving den closer into that middle school area, in fact Fleischer. And certainly in high schools, it's almost like a varsity sport. E-sports is another one. My son just combined made the JV at the college Dean, you know, it's big and it's up and serious. Right. And, um, it's fun. This is the aspect of fun. It's hands on. This is part of the culture down there you learn by doing, is there like a group? Is it like, um, is it like a club? I mean, how do you guys organize these bottoms up organically interest topics? >>So, so here in the college of engineering, uh, when we talk about learning by doing, we have learned by doing both in the classroom and out of the classroom. And if we look at the, these types of, out of the classroom activities, we have over 80 clubs working on all different aspects of many of these are bottom up. The students have decided what they want to work on and have organized themselves around that. And then they get the leadership opportunities. The more experienced students train in the less experienced students. And it continues to build from year after year after year with them even doing aspects of strategic planning from year to year for some of these competitions. So, yeah, it's an absolutely great experience. And we don't define for them how their learned by doing experiences should be, we want them to define it. And I think the really cool thing about that is they have the ownership and they have the interest and they can come up with new clubs year after year to see which direction they want to take it. And, you know, we will help support those clubs as old clubs fade out and new clubs come in >>Trunk real quick. Before we go on the next, uh, talk track, what, what do you recommend for, um, middle school, high school or even elementary? Um, a little bit of coding Minecraft. I mean, what, how do you get them hooked on the fun and the dopamine of, uh, technology and cybersecurity? What's your, what's your take on that? >>On, on this aspect, I like to share with you my experience as a junior high and high school student in Texas, the university of Texas in Austin organized a competition for every high school in Texas. If we phew from poetry to mathematics, to science, computer engineering, but it's not about with university of Texas. The university of Texas is on the serving SSN for the final competition that we divide the competition to be strict and then regional, and then spit at each level, we have local university and colleges volunteering to host it competition and make it fun. >>Also students with private enterprises to raise funding for scholarship. So students who see the competition they get exposed to so they can see different option. They also get a scholarship when they attend university in college. So I've seen the combination in competition aspect would be a good thing to be >>Got the engagement, the aspiration scholarship, you know, and you mentioned a volunteer. I think one of the things I'll observe is you guys are kind of hitting this as community. I mean, the story of Steve jobs and was, was building the Mac, they call it bill Hewlett up in Palo Alto. It was in the phone book and they scoured some parts from them. That's community. This is kind of what you're getting at. So this is kind of the formula we're seeing. So the next question I really want to get into is the women in technology, STEM, underrepresented minorities, how do we get them on cybersecurity career path? Is there a best practices there, bill, we'll start with you? >>Well, I think it's really interesting. First thing I want to add is if I could have just a clarification, what's really cool that the competition that we have and we're running, it's run by student from Cal poly. Uh, so, you know, Amy referenced the clubs and other activities. So many of the, uh, organizers and developers of the competition that we're running are the students, but not just from engineering. So we actually have theater and liberal arts majors and technology for liberal arts majors who are part of the competition. And we use their areas of expertise, set design, and other things, uh, visualization of virtualization. Those are all part of how we then teach and educate cyber in our game effication and other areas. So they're all involved in their learning as well. So we have our students teaching other students. So we're really excited about that. And I think that's part of what leads to a mentoring aspect of what we're providing, where our students are mentoring the other students. And I think it's also something that's really important in the game. Um, the first year we held the game, we had several all girl teams and it was really interesting because a, they, they didn't really know if they could compete. I mean, this is their, their reference point. We don't know if they did better than anybody. I mean, they, they knocked the ball out >>Of the park. The second part then is building that confidence level that they can going back and telling their cohorts that, Hey, it's not this thing you can't do. It's something real that you can compete and win. And so again, it's building that comradery, that spirit, that knowledge that they can succeed. And I think that goes a long way and an Amy's programs and the reach out and the reach out that Cal poly does to schools to develop. Uh, I think that's what it really is going to take. It. It is going to take that village approach to really increase diversity and inclusivity for the community. >>That's the flusher. I'd love to get your thoughts. You mentioned, um, your, your outreach program and the dropoff, some of those data, uh, you're deeply involved in this. You're passionate about it. What's your thoughts on this career path opportunity for STEM? >>Yeah, I think STEM is an incredible career path opportunity for so many people. There's so many interesting problems that we can solve, particularly in cyber and in space systems. And I think we have to meet the kids where they are and kind of show them, you know, what the exciting part is about it, right. But, you know, bill was, was alluding to this. And when he was talking about, you know, trying to name somebody that you can can point to. And I think having those visible people where you can see yourself in that is, is absolutely critical and those mentors and that mentorship program. So we use a lot of our students going out into California, middle schools and elementary schools. And you want to see somebody that's like you, somebody that came from your background and was able to do this. So a lot of times we have students from our national society of black engineers or a society of Hispanic professional engineers or our society of women engineers. >>We have over a thousand members, a thousand student members in our society of women engineers who were doing these outreach programs. But like I also said, it's hitting them at the lower levels too. And girl Scouts is actually distinguishing themselves as one of the leading STEM advocates in the country. And like I said, they developed all these cybersecurity badges, starting in kindergarten. There's a cybersecurity badge for kindergarten and first graders. And it goes all the way up through late high school, the same thing with space systems. And they did the space systems in partnership with NASA. They did the cybersecurity and partnership with Palo Alto networks. And what you do is you want to build these, these skills that the girls are developing. And like bill said, work in and girl led teams where they can do it. And if they're doing it from kindergarten on, it just becomes normal. And they never think, well, this is not for me. And they see the older girls who are doing it and they see a very clear path leading them into these careers. >>Yeah. It's interesting. You used the word normalization earlier. That's exactly what it is. It's life, you get life skills and a new kind of badge. Why wouldn't learn how to be a white, white hat hacker, or have fun or learn new skills just in, in the, in the grind of your fun day. Super exciting. Okay. Trung your thoughts on this. I mean, you have a diverse diversity. It brings perspective to the table in cybersecurity because you have to think like the other, the adversary, you got to be the white headed hippie, a white hat, unless you know how black hat thinks. So there's a lot of needs here for more, more, more points of view. How are we going to get people trained on this from under represented minorities and women? What's your thoughts? >>Well, as a member of, I took a professional society of directed pool in the electronic engineer. You have the, uh, we participate in the engineering week. We'll be ploy our members to local junior high school and high school to talk about our project, to promote the discovery of engineering. But at the same time, we also participate in the science fair that we scaled up flex. As the squad organizing our engineer will be mentoring students, number one, to help them with the part check, but number two, to help us identify talents so that we can recruit them further into the field of STEM. One of the participation that week was the competition of the, what they call future CV. We're still going, we'll be doing a CT on a computer simulation. And in recent year we promote ops smart CV where CT will be connected the individual houses to be added in through the internet. >>And we want to bring awareness of cybersecurity into competition. So we deploy engineer to supervise the people, the students who participate in the competition, we bring awareness, not in the technical be challenged level, but in what we've called the compound level. So speargun will be able to know what is, why to provide cyber security for the smart city that they are building. And at the same time, we were able to identify talent, especially talent in the minority and in the room. And so that we can recruit them more actively. And we also raise money for scholarship. We believe that scholarship is the best way to get students to continue education in Epic college level. So with scholarship, it's very easy to recruit them, to give you and then push them to go further into the cyber security Eylea. >>Yeah. I mean, you know, I see a lot of the parents like, Oh, my kid's going to go join the soccer team, >>Private lessons, and maybe look at a scholarship >>Someday. Well, they only do have scholarships anyway. I mean, this is if they spent that time doing other things, it's just, again, this is a new lifestyle, like the girl Scouts. And this is where I want to get into this whole silo breaking down because Amy, you brought this up and bill, you were talking about as well, you've got multiple stakeholders here with this event. You got, you know, public, you got private and you've got educators. It's the intersection of all of them. It's again, that those, if those silos break down the confluence of those three stakeholders have to work together. So let's, let's talk about that. Educators. You guys are educating young minds, you're interfacing with private institutions and now the public. What about educators? What can they do to make cyber better? Cause there's no real manual. I mean, it's not like this court is a body of work of how to educate cybersecurity is maybe it's more recent, it's cutting edge, best practices, but still it's an, it's an evolving playbook. What's your thoughts for educators, bill? We'll start with you. >>Well, I don't really, I'm going to turn it off. >>I would say, I would say as, as educators, it's really important for us to stay on top of how the field is evolving, right? So what we want to do is we want to promote these tight connections between educators and our faculty and, um, applied research in industry and with industry partnerships. And I think that's how we're going to make sure that we're educating students in the best way. And you're talking about that inner, that confluence of the three different areas. And I think you have to keep those communication lines open to make sure that the information on where the field is going and what we need to concentrate on is flowing down into our educational process. And that, that works in both ways that, you know, we can talk as educators and we can be telling industry what we're working on and what are types of skills our students have and working with them to get the opportunities for our students to work in industry and develop those skills along the way as well. >>And I think it's just all part of this is really looking at, at what's going to be happening and how do we get people talking to each other and the same thing with looking at public policy and bringing that into our education and into these real hands on experiences. And that's how you really cement this type of knowledge with students, not by not by talking to them and not by showing them, but letting them do it. It's this learn by doing and building the resiliency that it takes when you learn by doing. And sometimes you learn by failing, but you just up and you keep going. >>And these are important skills that you develop along the way >>You mentioned, um, um, sharing too. That's the key collaborating and sharing knowledge. It's an open, open world and everyone's collaborating feel private public partnerships. I mean, there's a real private companies. You mentioned Palo Alto networks and others. There's a real intersection there there's, they're motivated. They could, the scholarship opportunities, trunk points to that. What is the public private educator view there? How do companies get involved? What's the benefit for them? >>Well, that's what a lot of the universities are doing is to bring in as part of either their cyber centers or institutes, people who are really focused on developing and furthering those public private partnerships. That's really what my role is in all these things is to take us to a different level in those areas, uh, not to take away from the academic side, but to add additional opportunities for both sides. Remember in a public private partnership, all entities have to have some gain in the process. Now, what I think is really interesting is the timing on particularly this subject space and cyber security. This has been an absolute banner year for space. The Stanhope of space force, the launch of commercial partnership, leaving commercial platforms, delivering astronauts to the space station, recovering them and bringing back the ability of a commercial satellite platform to be launched a commercial platforms that not only launch, but return back to where they're launched from. >>These are things that are stirring the hearts of the American citizens, the kids, again, they're getting interested, they're seeing this and getting enthused. So we have to seize upon that and we have to find a way to connect that public private partnerships is the answer for that. It's not one segment that can handle it all. It's all of them combined together. If you look at space, space is going to be about commercial. It's going to be about civil moving from one side of the earth, to the other via space. And it's about government. And what's really cool for us. All those things are in our backyard. Yeah. That's where that public private comes together. The government's involved, the private sector is involved. The educators are involved and we're all looking at the same things and trying to figure out like this forum, what works best to go to the future. >>You know, if people are bored and they want to look for an exciting challenge, he couldn't have laid it out any clearer. It's the most exciting discipline. It hits everything. I mean, we just talk about space. GPS is everything we do is well tested. Do with satellites. >>I have to tell you a story on that, right? We have a very unique GPS story right in our backyard. So our sheriff is the son of the father of GPS for the air force. So you can't get better than that when it comes to being connected to all those platforms. So we, we really want to say, you know, this is so exciting for all of us because >>It gives everybody a job for a long time. >>You know, the kids that don't think tick toxic, exciting, wait til they see what's going on here with you guys, this program, trunk final word on this from the public side, you're at the air force. You're doing research. Are you guys opening it up? Are you integrating into the private and educational sectors? How do you see that formula playing out? And what's the best practice for students and preparing them? >>I think it's the same in athlete university CP in the engineering program will require our students to be final project before graduation. And in this kind of project, we send them out to work in the private industry. The private company got sponsor. Then they get the benefit of having an intern working for them and they get the benefit of reviewing the students as the prospective employee in the future. So it's good for the student to gain practical experience working in this program. Some, some kind of, we call that a core program, some kind, we call that a capstone program and the company will accept the students on a trial PRCS, giving them some assignment and then pay them a little bit of money. So it's good for the student to earn some extra money, to have some experience that they can put on their resume when they apply for the final of the job. >>So the collaboration between university and private sector is really important. We, when I joined a faculty, normally they already exist that connection. It came from. Normally it came from the Dean of engineering who would whine and dine with companies. We work relationship and sign up women, but it's approach to do a good performance so that we can be credibility to continue the relationship with those company and the students that we selected to send to those company. We have to make sure that they will represent the university. Well, they will go a good job and they will make a good impression. >>Thank you very much for great insight, trunk, bill, Amy, amazing topic. I'd like to end this session with each of you to make a statement on the importance of cybersecurity to space. We'll go Trung bill and Amy Truong, the importance of cybersecurity space statement. >>We know that it's affecting components that we are using and we are connecting to. And normally we use them for personal purpose. But when we connect to the important system that the government public company put into space, so it's really important to practice cyber security and a lot of time, it's very easy to know concept. We have to be careful, but in reality, we tend to forget to partnership the way we forget how to ride safely. And with driving a car, we have a program called defensive driving that requires every two or three years to get. We can get discount. >>We are providing the cyber security practice, not to tell people about the technology, but to remind them not practicing cybersecurity. And it's a requirement for every one of us, bill, the importance of cyber security to space. It's not just about young people. It's about all of us as we grow and we change as I referenced it, you know, we're changing from an analog world to a digital world. Those of us who have been in the business and have hair that looks like mine. We need to be just as cognizant about cybersecurity practice as the young people, we need to understand how it affects our lives and particularly in space, because we're going to be talking about people, moving people to space, moving payloads, data, transfer all of those things. And so there's a whole workforce that needs to be retrained or upskilled in cyber that's out there. So the opportunity is ever expensive for all of us, Amy, the importance of cybersecurity space, >>Uh, and the, the emphasis of cybersecurity is space. Just simply, can't be over emphasized. There are so many aspects that are going to have to be considered as systems get ever more complex. And as we pointed out, we're putting people's lives at stake here. This is incredibly, incredibly complicated and incredibly impactful, and actually really exciting the opportunities that are here for students and the workforce of the future to really make an enormous impact on the world around us. And I hope we're able to get that message out to students, to children >>Today. But these are my really interesting fields that you need to consider. >>Thank you very much. I'm John foray with the cube and the importance of cybersecurity and space is the future of the world's all going to happen in and around space with technology, people and society. Thank you to Cal poly. And thank you for watching the Cypress of computer security and space symposium 2020.

>> Announcer: From around the globe, it's theCUBE, covering Space and Cybersecurity Symposium 2020, hosted by Cal Poly. >> Everyone, welcome to this special presentation with Cal Poly hosting the Space and Cybersecurity Symposium 2020 virtual. I'm John Furrier, your host with theCUBE and SiliconANGLE here in our Palo Alto studios with our remote guests. We couldn't be there in person, but we're going to be here remote. We got a great session and a panel for one hour, topic preparing students for the jobs of today and tomorrow. Got a great lineup. Bill Britton, Lieutenant Colonel from the US Air Force, retired vice president for information technology and CIO and the director of the California Cybersecurity Institute for Cal Poly. Bill, thanks for joining us. Dr. Amy Fleischer, who's the dean of the College of Engineering at Cal Poly, and Trung Pham, professor and researcher at the US Air Force Academy. Folks, thanks for joining me today. >> Our pleasure. >> Got a great- >> Great to be here. >> Great panel. This is one of my favorite topics. >> Thank you for the opportunity. >> Preparing students for the next generation, the jobs for today and tomorrow. We got an hour. I'd love you guys to start with an opening statement to kick things off. Bill, we'll start with you. >> Well, I'm really pleased to be, to start on this as the director for the Cybersecurity Institute and the CIO at Cal Poly, it's really a fun, exciting job, because as a polytechnic, technology has such a forefront in what we're doing, and we've had a wonderful opportunity being 40 miles from Vandenberg Air Force Base to really look at the nexus of space and cybersecurity. And if you add into that both commercial, government, and civil space and cybersecurity, this is an expanding wide open time for cyber and space. In that role that we have with the Cybersecurity Institute, we partner with elements of the state and the university, and we try to really add value above our academic level, which is some of the highest in the nation, and to really merge down and go a little lower and start younger. So we actually are running the week prior to this showing a cybersecurity competition for high schools and middle schools in the state of California. That competition this year is based on a scenario around hacking of a commercial satellite and the forensics of the payload that was hacked and the networks associated with it. This is going to be done using products like Wireshark, Autopsy, and other tools that will give those high school students what we hope is a huge desire to follow up and go into cyber and cyberspace and space and follow that career path and either come to Cal Poly or some other institution that's going to let them really expand their horizons in cybersecurity and space for the future of our nation. >> Bill, thanks for that intro. By the way, I just want to give you props for an amazing team and job you guys are doing at Cal Poly, the DxHub and the efforts you guys are having with your challenge. Congratulations on that great work. >> Thank you. It's a rock star team. It's absolutely amazing to find that much talent at one location. And I think Amy's going to tell you, she's got the same amount of talent in her staff, so it's a great place to be. >> Dr. Amy Fleischer. You guys have a great organization down there, amazing curriculum, amazing people, great community. Your opening statement. >> Hello everybody. It's really great to be a part of this panel on behalf of the Cal Poly College of Engineering. Here at Cal Poly, we really take preparing students for the jobs of today and tomorrow completely seriously, and we can claim that our students really graduate so they're ready day one for their first real job. But that means that in getting them to that point, we have to help them get valuable and meaningful job experience before they graduate, both through our curriculum and through multiple internship or summer research opportunities. So we focus our curriculum on what we call a learn by doing philosophy. And this means that we have a combination of practical experience and learn by doing both in and out of the classroom. And we find that to be really critical for preparing students for the workforce. Here at Cal Poly, we have more than 6,000 engineering students. We're one of the largest undergraduate engineering schools in the country. And US News ranks us the eighth best undergraduate engineering program in the country and the top ranked state school. We're really, really proud that we offer this impactful hands-on engineering education that really exceeds that of virtually all private universities while reaching a wider audience of students. We offer 14 degree programs, and really, we're talking today about cyber and space, and I think most of those degree programs can really make an impact in the space and cybersecurity economy. And this includes not only things like aero and cyber directly, but also electrical engineering, mechanical engineering, computer engineering, materials engineering, even manufacturing, civil, and biomedical engineering, as there's a lot of infrastructure needs that go into supporting launch capabilities. Our aerospace program graduates hundreds of aerospace engineers and most of them are working right here in California with many of our corporate partners, including Northrop Grumman, Lockheed, Boeing, Raytheon, SpaceX, Virgin Galactic, JPL, and so many other places where we have Cal Poly engineers impacting the space economy. Our cybersecurity focus is found mainly in our computer science and software engineering programs, and it's really a rapidly growing interest among our students. Computer science is our most popular major, and industry interests and partnerships are integrated into our cyber curriculum, and we do that oftentimes through support from industry. So we have partnerships with Northrop Grumman for professorship in a cyber lab and from PG&E for critical infrastructure cybersecurity lab and professorship. And we think that industry partnerships like these are really critical to preparing students for the future as the field is evolving so quickly and making sure we adapt our facilities and our curriculum to stay in line with what we're seeing in industry is incredibly important. In our aerospace program, we have an educational partnership with the Air Force Research Labs that's allowing us to install new high-performance computing capabilities and a space environments lab that's going to enhance our satellite design capabilities. And if we talk about satellite design, Cal Poly is the founding home of the CubeSat program, which pioneered small satellite capabilities, And we remain the worldwide leader in maintaining the CubeSat standard, and our student program has launched more CubeSats than any other program. So here again we have this learn by doing experience every year for dozens of aerospace, electrical, computer science, mechanical engineering students, and other student activities that we think are just as important include ethical hacking through our white hat club, Cal Poly Space Systems, which does really, really big rocket launches, and our support program for women in both of these fields, like WISH, which is Women In Software and Hardware. Now, you know, really trying to bring in a wide variety of people into these fields is incredibly important, and outreach and support to those demographics traditionally underrepresented in these fields is going to be really critical to future success. So by drawing on the lived experiences by people with different types of backgrounds will we develop the type of culture and environment where all of us can get to the best solution. So in terms of bringing people into the field, we see that research shows we need to reach kids when they're in late elementary and middle schools to really overcome that cultural bias that works against diversity in our fields. And you heard Bill talking about the California Cybersecurity Institute's yearly cyber challenge, and there's a lot of other people who are working to bring in a wider variety of people into the field, like Girl Scouts, which has introduced dozens of new badges over the past few years, including a whole cybersecurity series of badges in concert with Palo Alto Networks. So we have our work cut out for us, but we know what we need to do, and if we're really committed to properly preparing the workforce for today and tomorrow, I think our future is going to be bright. I'm looking forward to our discussion today. >> Thank you, Dr. Fleischer, for a great comment, opening statement, and congratulations. You got the right formula down there, the right mindset, and you got a lot of talent, and community, as well. Thank you for that opening statement. Next up, from Colorado Springs, Trung Pham, who's a professor and researcher at the US Air Force Academy. He's doing a lot of research around the areas that are most important for the intersection of space and technology. Trung. >> Good afternoon. First I'd like to thank Cal Poly for the opportunity. And today I want to go briefly about cybersecurity in space application. Whenever we talk about cybersecurity, the impression is that it's a new field that is really highly complex involving a lot of technical area. But in reality, in my personal opinion, it is indeed a complex field because it involves many disciplines. The first thing we think about is computer engineering and computer networking, but it's also involving communication, sociology, law practice. And this practice of cybersecurity doesn't only involve computer expert, but it's also involve everybody else who has a computing device that is connected to the internet, and this participation is obviously everybody in today's environment. When we think about the internet, we know that it's a good source of information but come with the convenience of information that we can access, we are constantly facing danger from the internet. Some of them we might be aware of. Some of them we might not be aware of. For example, when we search on the internet, a lot of time our browser will be saying that this site is not trusted, so we will be more careful. But what about the sites that we trusted? We know that those are legitimate sites, but they're not 100% bulletproof. What happen if those site are attacked by a hacker and then they will be a silent source of danger that we might not be aware of. So in the reality, we need to be more practicing the cybersecurity from our civil point of view and not from a technical point of view. When we talk about space application, we should know that all the hardware are computer-based or controlled by by computer system, and therefore the hardware and the software must go through some certification process so that they can be rated as airworthy or flightworthy. When we know that in the certification process is focusing on the functionality of the hardware and software, but one aspect that is explicitly and implicitly required is the security of those components. And we know that those components have to be connected with the ground control station, and the communication is through the air, through the radio signal, so anybody who has access to those communication radio signal will be able to control the space system that we put up there. And we certainly do not want our system to be hijacked by a third party. Another aspect of cybersecurity is that we try to design the space system in a very strong manner so it's almost impossible to hack in. But what about some other weak system that might be connected to the strong system? For example, the space system will be connected to the ground control station, and on the ground control station, we have the human controller, and those people have cell phone. They are allowed to use cell phone for communication. But at the same time, they are connected to the internet through the cell phone, and their cell phone might be connected to the computer that control the flight software and hardware. So what I want to say is we try to build strong system and we've protected them, but there will be some weaker system that we could not intended but exists to be connected to our strong system, and those are the points the hacker will be trying to attack. If we know how to control the access to those weak points, we will be having a much better system for the space system. And when we see the cybersecurity that is requiring the participation everywhere it's important to notice that there is a source of opportunity for students who enter the workforce to consider. Obviously students in engineering can focus their knowledge and expertise to provide technological solution to protect the system that we view. But we also have students in business who can focus their expertise to write business plan so that they can provide a pathway for the engineering advances to reach the market. We also have student in law who can focus their expertise in policy governing the internet, governing the cybersecurity practice. And we also have student in education who can focus their expertise to design how to teach cybersecurity practice, and student in every other discipline can focus their effort to implement security measure to protect the system that they are using in their field. So it's obvious that cybersecurity is everywhere and it implies job opportunity everywhere for everybody in every discipline of study. Thank you. >> Thank you, Trung, for those great comments. Great technology opportunities. But interesting, as well, is the theme that we're seeing across the entire symposium and in the virtual hallways that we're hearing conversations, and you pointed out some of them. Dr. Fleischer did, as well. And Bill, you mentioned it. It's not one thing. It's not just technology. It's different skills. And Amy, you mentioned that computer science is the hottest degree, but you have the hottest aerospace program in the world. I mean, so all this is kind of balancing. It's interdisciplinary. It's a structural change. Before we get into some of the, how they prepare the students, can you guys talk about some of the structural changes that are modern now in preparing in these opportunities, because societal impact is a, law potentially impact, it's how we educate. There's now cross-discipline skill sets. It's not just get the degree, see you out in the field. Bill, you want to start? >> Well, what's really fun about this job is that in the Air Force, I worked in the space and missile business, and what we saw was a heavy reliance on checklist format, security procedures, analog systems, and what we're seeing now in our world, both in the government and the commercial side, is a move to a digital environment, and the digital environment is a very quick and adaptive environment, and it's going to require a digital understanding. Matter of fact, the undersecretary of Air Force for acquisition recently referenced the need to understand the digital environment and how that's affecting acquisition. So as both Amy and Trung said, even business students are now in the cybersecurity business. And so again, what we're seeing is the change. Now, another phenomenon that we're seeing in the space world is there's just so much data. One of the ways that we addressed that in the past was to look at high-performance computing. There was a lot stricter control over how that worked. But now what we're seeing is adaptation of cloud, cloud technologies in space support, space data, command and control. And so what we see is a modern space engineer who has to understand digital, has to understand cloud, and has to understand the context of all those with a cyber environment. That's really changing the forefront of what is a space engineer, what is a digital engineer, and what is a future engineer, both commercial or government. So I think the opportunity for all of these things is really good, particularly for a polytechnic, Air Force Academy, and others that are focusing on a more widened experiential level of cloud and engineering and other capabilities. And I'll tell you the part that as the CIO I have to remind everybody, all this stuff works with the IT stuff. So you've got to understand how your IT infrastructures are tied and working together. As we noted earlier, one of the things is that these are all relays from point to point, and that architecture is part of your cybersecurity architecture. So again, every component has now become a cyber aware, cyber knowledgeable, and what we like to call as a cyber cognizant citizen where they have to understand the context. (speaking on mute) >> (indistinct) software Dr. Fleischer, talk about your perspective, 'cause you mentioned some of the things about computer science. I remember in the '80s when I got my computer science degree, they called us software engineers and then you became software developers. And then, so again, engineering is the theme. If you're engineering a system, there's now software involved, and there's also business engineering, business models. So talk about some of your comments, 'cause you mentioned computer science is hot. You got the aerospace. You got these multi-disciplines. You got definitely diversity, as well, brings more perspectives in, as well. Your thoughts on these structural interdisciplinary things? >> I think this is really key to making sure that students are prepared to work in the workforce is looking at the blurring between fields. No longer are you just a computer scientist. No longer are you just an aerospace engineer. You really have to have an expertise where you can work with people across disciplines. All of these fields are just working with each other in ways we haven't seen before. And Bill brought up data. You know, data science is something that's cross-cutting across all of our fields. So we want engineers that have the disciplinary expertise that they can go deep into these fields, but we want them to be able to communicate with each other and to be able to communicate across disciplines and to be able to work in teams that are across disciplines. You can no longer just work with other computer scientists or just work with other aerospace engineers. There's no part of engineering that is siloed anymore. So that's how we're changing. You have to be able to work across those disciplines. And as you, as Trung pointed out, ethics has to come into this. So you can no longer try to fully separate what we would traditionally have called the liberal arts and say, well, that's over there in general education. No, ethics is an important part of what we're doing and how we integrate that into our curriculum. So is communication. So is working on public policy and seeing where all these different aspects tie together to make the impact that we want to have in the world. So you no longer can work solo in these fields. >> That's great point. And Bill also mentioned the cloud. One thing about the cloud that's showed us is horizontal scalability has created a lot of value, and certainly data is now horizontal. Trung, you mentioned some of the things about cryptography for the kids out there, I mean, you can look at the pathway for career. You can do a lot of tech, but you don't have to go deep sometimes. You can as deep as you want, but there's so much more there. What technology do you see that's going to help students, in your opinion? >> Well, I'm a professor in computer science, so I like to talk a little bit about computer programming. Now we are working in complex projects. So most of the time we don't design a system from scratch. We build it from different components, and the components that we have, either we get it from vendors or sometimes we get it from the internet in the open source environment. It's fun to get the source code and then make it work to our own application. So now when we are looking at cryptology, when we talk about encryption, for example, we can easily get the source code from the internet. And the question, is it safe to use those source code? And my question is maybe not. So I always encourage my students to learn how to write source code the traditional way that I learned a long time ago before I allow them to use the open source environment. And one of the things that they have to be careful especially with encryption is the code that might be hidden in the source that they downloaded. Some of the source might be harmful. It might open up back gate for a hacker to get in later. We've heard about these back gates back then when Microsoft designed the operating system with the protection of encryption, and it is true that is existing. So while open source code is a wonderful place to develop complex system, but it's also a dangerous place that we have to be aware of. >> Great point. Before we get into the comments, one quick thing for each of you I'd like to get your comments on. There's been a big movement on growth mindset, which has been a great big believer in having a growth mindset and learning and all that good stuff. But now when you talk about some of these things we're mentioning about systems, there's a new trend around a systems mindset, because if everything's now a system, distributed systems now you have space and cybersecurity, you have to understand the consequences of changes. And you mention some of that, Trung, in changes in the source code. Could you guys share your quick opinions on the of systems thinking? Is that a mindset that people should be looking at? Because it used to be just one thing. Oh, you're a systems guy or gal. There you go. You're done. Now it seems to be in social media and data, everything seems to be systems. What's your take? Dr. Fleischer, we'll start with you. >> I'd say it's another way of looking at not being just so deep in your discipline. You have to understand what the impact of the decisions that you're making have on a much broader system. And so I think it's important for all of our students to get some exposure to that systems level thinking and looking at the greater impact of the decision that they're making. Now, the issue is where do you set the systems boundary, right? And you can set the systems boundary very close in and concentrate on an aspect of a design, or you can continually move that system boundary out and see where do you hit the intersections of engineering and science along with ethics and public policy and the greater society. And I think that's where some of the interesting work is going to be. And I think at least exposing students and letting them know that they're going to have to make some of these considerations as they move throughout their career is going to be vital as we move into the future. >> Bill, what's your thoughts? >> I absolutely agree with Amy. And I think there's a context here that reverse engineering and forensics analysis and forensics engineering are becoming more critical than ever. The ability to look at what you have designed in a system and then tear it apart and look at it for gaps and holes and problem sets. Or when you're given some software that's already been pre-developed, checking it to make sure it is really going to do what it says it's going to do. That forensics ability becomes more and more a skillset that also you need the verbal skills to explain what it is you're doing and what you found. So the communication side, the systems analysis side, the forensics analysis side, these are all things that are part of system approach that I think you could spend hours on and we still haven't really done a great job on it. So it's one of my fortes is really the whole analysis side of forensics and reverse engineering. >> Trung, real quick, systems thinking, your thoughts. >> Well, I'd like to share with you my experience when I worked in the space station program at NASA. We had two different approaches. One is a compound approach where we design it from the system general point of view where we put components together to be a complex system. But at the same time, we have the (indistinct) approach where we have an engineer who spent time and effort building individual component and they have to be expert in those tiny component that general component they deliver. And in the space station program, we bring together the (indistinct) engineer who designed everything in detail and the system manager who managed the system design from the top down, and we meet in the middle, and together we compromised a lot of differences and we delivered the space station that we are operating today. >> Great insight. And that's the whole teamwork collaboration that Dr. Fleischer was mentioning. Thanks so much for that insight. I wanted to get that out there because I know myself as a parent, I'm always trying to think about what's best for my kids and their friends as they grow up into the workforce. I know educators and leaders in industry would love to know some of the best practices around some of the structural changes. So thanks for that insight. But this topic's about students and helping them prepare. So we heard be multiple discipline, broaden your horizons, think like systems, top down, bottom up, work together as a team, and follow the data. So I got to ask you guys, there's a huge amount of job openings in cybersecurity. It's well-documented. And certainly with the intersection of space and cyber, it's only going to get bigger, right? You're going to see more and more demand for new types of jobs. How do we get high school and college students interested in security as a career? Dr. Fleischer, we'll start with you on this one. I would say really one of the best ways to get students interested in a career is to show them the impact that it's going to have. There's definitely always going to be students who are going to want to do the technology for the technology's sake, but that will limit you to a narrow set of students, and by showing the greater impact that these types of careers are going to have on the types of problems that you're going to be able to solve and the impact you're going to be able to have on the world around you, that's the word that we really need to get out. And a wide variety of students really respond to these messages. So I think it's really kind of reaching out at the elementary, the middle school level, and really kind of getting this idea that you can make a big difference, a big positive difference in the field with some of these careers, is going to be really critical. >> Real question to follow up. What do you think is the best entry point? You mentioned middle. I didn't hear elementary school. There's a lot of discussions around pipelining, and we're going to get into women in tech and underrepresented minorities later. But is it too early, or what's your feeling on this? >> My feeling is the earlier we can normalize it, the better. If you can normalize an interest in computers and technology and building in elementary school, that's absolutely critical. But the drop-off point that we're seeing is between what I would call late elementary and early middle school. And just kind of as an anecdote, I for years ran an outreach program for Girl Scouts in grades four and five and grade six, seven, and eight. And we had 100 slots in each program. And every year the program would sell out for girls in grades four and five, and every year we'd have spots remaining in grades six, seven, and eight. And that's literally where the drop-off is occurring between that late elementary and that middle school range. So that's the area that we need to target to make sure we keep those young women involved and interested as we move forward. >> Bill, how are we going to get these kids interested in security? You mentioned a few programs you got. >> Yeah. >> I mean, who wouldn't want to be a white hat hacker? I mean, that sounds exciting. >> So yeah, great questions. Let's start with some basic principles, though, is let me ask you a question, John. Name for me one white hat, good person hacker, the name, who works in the space industry and is an exemplar for students to look up to. >> You? >> Oh man, I'm feeling really... >> I'm only, I can't imagine a figure- >> (indistinct) the answer because the answer we normally get is the cricket sound. So we don't have individuals we've identified in those areas for them to look up to. >> I was going to be snarky and say most white hackers won't even use their real name, but... >> Right, so there's an aura around their anonymity here. So again, the real question is how do we get them engaged and keep them engaged? And that's what Amy was pointing out to exactly, the engagement and sticking with it. So one of the things that we're trying to do through our competition on the state level and other elements is providing connections. We call them ambassadors. These are people in the business who can contact the students that are in the game or in that challenge environment and let 'em interact and let 'em talk about what they do and what they're doing in life. But give them a challenging game format. A lot of computer-based training, capture the flag stuff is great, but if you can make it hands-on, if you can make it a learn by doing experiment, if you can make it personally involved and see the benefit as a result of doing that challenge and then talk to the people who do that on a daily basis, that's how you get them involved. The second part is part of what we're doing is we're involving partnership companies in the development of the teams. So this year's competition that we're running has 82 teams from across the state of California. Of those 82 teams at six students a team, middle school, high school, and many of those have company partners, and these are practitioners in cybersecurity who are working with those students to participate. It's that adult connectivity. It's that visualization. So at the competition this year, we have the founder of Defcon Red Flag is a participant to talk to the students. We have Vint Cerf, who is, of course, very well-known for something called the internet, to participate. It's really getting the students to understand who's in this, who can I look up to, and how do I stay engaged with them? >> There's definitely a celebrity aspect of it, I will agree. I mean, the influencer aspect here with knowledge is key. Can you talk about these ambassadors, and how far along are you on that program? First of all, the challenge stuff is, anything gamification-wise, we've seen that with hackathons, it just really works well. Creates bonding. People who create together can get sticky and get very high community aspect to it. Talk about this ambassador thing. What is that, industry, is that academic? >> Yeah, absolutely. >> What is this ambassador thing? >> Industry partners that we've identified, some of which, and I won't hit all of 'em, so I'm sure I'll short change this, but Palo Alto, Cisco, Splunk, many of the companies in California, and what we've done is identified schools to participate in the challenge that may not have a strong STEM program or have any cyber program. And the idea of the company is they look for their employees who are in those school districts to partner with the schools to help provide outreach. It could be as simple as a couple hours a week, or it's a team support captain or it's providing computers and other devices to use. And so again, it's really about a constant connectivity and trying to help where some schools may not have the staff or support units in an area to really provide them what they need for connectivity. What that does is it gives us an opportunity to not just focus on it once a year, but throughout the year. So for the competition, all the teams that are participating have been receiving training and educational opportunities in the gamification side since they signed up to participate. So there's a website, there's learning materials, there's materials provided by certain vendor companies like Wireshark and others. So it's a continuum of opportunity for the students. >> You know, I've seen, just randomly, just got a random thought. Robotics clubs are moving then closer into that middle school area, Dr. Fleischer, and in certainly in high schools, it's almost like a varsity sport. E-sports is another one. My son just called me. "I made the JV at the college team." It's big and serious, right? And it's fun. This is the aspect of fun. It's hands-on. This is part of the culture down there. Learn by doing. Is there, like, a group? Is it, like, a club? I mean, how do you guys organize these bottoms-up organically interest topics? >> So here in the college of engineering, when we talk about learn by doing, we have learned by doing both in the classroom and out of the classroom. And if we look at these types of out of the classroom activities, we have over 80 clubs working on all different aspects, and many of these are bottom-up. The students have decided what they want to work on and have organized themselves around that. And then they get the leadership opportunities. The more experienced students train the less experienced students. And it continues to build from year after year after year with them even doing aspects of strategic planning from year to year for some of these competitions. Yeah, it's an absolutely great experience. And we don't define for them how their learn by doing experiences should be. We want them to define it. And I think the really cool thing about that is they have the ownership and they have the interest and they can come up with new clubs year after year to see which direction they want to take it, and we will help support those clubs as old clubs fade out and new clubs come in. >> Trung, real quick, before we go on the next talk track, what do you recommend for middle school, high school, or even elementary? A little bit of coding, Minecraft? I mean, how do you get 'em hooked on the fun and the dopamine of technology and cybersecurity? What's your take on that? >> On this aspect, I'd like to share with you my experience as a junior high and high school student in Texas. The university of Texas in Austin organized a competition for every high school in Texas in every field from poetry to mathematics to science, computer engineering. But it's not about the University of Texas. The University of Texas is only serving as a center for the final competition. They divide the competition to district and then regional and then state. At each level, we have local university and colleges volunteering to host the competition and make it fun for the student to participate. And also they connected the students with private enterprises to raise fund for scholarship. So student who see the competition is a fun event for them, they get exposed to different university hosting the event so that they can see different option for them to consider college. They also get a promise that if they participate, they will be considered for scholarship when they attend university and college. So I think the combination of fun and competition and the scholarship aspect will be a good thing to entice the student to commit to the area of cybersecurity. >> Got the engagement, the aspiration, scholarship, and you mentioned a volunteer. I think one of the things I'll observe is you guys are kind of hitting this as community. I mean, the story of Steve Jobs and Woz building the Mac, they called Bill Hewlett up in Palo Alto. He was in the phone book. And they scoured some parts from him. That's community. This is kind of what you're getting at. So this is kind of the formula we're seeing. So the next question I really want to get into is the women in technology, STEM, underrepresented minorities, how do we get them on cybersecurity career path? Is there a best practices there? Bill, we'll start with you. >> Well, I think it's really interesting. First thing I want to add is, if I could, just a clarification. What's really cool, the competition that we have and we're running, it's run by students from Cal Poly. So Amy referenced the clubs and other activities. So many of the organizers and developers of the competition that we're running are the students, but not just from engineering. So we actually have theater and liberal arts majors and technology for liberal arts majors who are part of the competition, and we use their areas of expertise, set design and other things, visualization, virtualization. Those are all part of how we then teach and educate cyber in our gamification and other areas. So they're all involved and they're learning, as well. So we have our students teaching other students. So we're really excited about that. And I think that's part of what leads to a mentoring aspect of what we're providing where our students are mentoring the other students. And I think it's also something that's really important in the game. The first year we held the game, we had several all-girl teams, and it was really interesting because A, they didn't really know if they could compete. I mean, this is their reference point. We don't know if. They did better than anybody. I mean, they just, they knocked the ball out of the park. The second part, then, is building that confidence level that can, going back and telling their cohorts that, hey, it's not this obtuse thing you can't do. It's something real that you can compete and win. And so again, it's building that camaraderie, that spirit, that knowledge that they can succeed. And I think that goes a long way. And Amy's programs and the reach out and the reach out that Cal Poly does to schools to develop, I think that's what it really is going to take. It is going to take that village approach to really increase diversity and inclusivity for the community. >> Dr. Fleischer, I'd love to get your thoughts. You mentioned your outreach program and the drop-off, some of those data. You're deeply involved in this. You're passionate about it. What's your thoughts on this career path opportunity for STEM? >> Yeah, I think STEM is an incredible career path opportunity for so many people. There's so many interesting problems that we can solve, particularly in cyber and in space systems. And I think we have to meet the kids where they are and kind of show them what the exciting part is about it, right? But Bill was alluding to this when he was talking about trying to name somebody that you can point to. And I think having those visible people where you can see yourself in that is absolutely critical, and those mentors and that mentorship program. So we use a lot of our students going out into California middle schools and elementary schools. And you want to see somebody that's like you, somebody that came from your background and was able to do this. So a lot of times we have students from our National Society of Black Engineers or our Society of Hispanic Professional Engineers or our Society of Women Engineers, which we have over 1,000 members, 1,000 student members in our Society of Women Engineers who are doing these outreach programs. But like I also said, it's hitting them at the lower levels, too, and Girl Scouts is actually distinguishing themselves as one of the leading STEM advocates in the country. And like I said, they developed all these cybersecurity badges starting in kindergarten. There's a cybersecurity badge for kindergartener and first graders. And it goes all the way up through late high school. The same thing with space systems. And they did the space systems in partnership with NASA. They did the cybersecurity in partnership with Palo Alto Networks. And what you do is you want to build these skills that the girls are developing, and like Bill said, work in girl-led teams where they can do it, and if they're doing it from kindergarten on, it just becomes normal, and they never think, well, this is not for me. And they see the older girls who are doing it and they see a very clear path leading them into these careers. >> Yeah, it's interesting, you used the word normalization earlier. That's exactly what it is. It's life, you get life skills and a new kind of badge. Why wouldn't you learn how to be a white hat hacker or have some fun or learn some skills? >> Amy: Absolutely. >> Just in the grind of your fun day. Super exciting. Okay, Trung, your thoughts on this. I mean, you have a diverse, diversity brings perspective to the table in cybersecurity because you have to think like the other guy, the adversary. You got to be the white hat. You can't be a white hat unless you know how black hat thinks. So there's a lot of needs here for more points of view. How are we going to get people trained on this from underrepresented minorities and women? What's your thoughts? >> Well, as a member of the IEEE Professional Society of Electrical and Electronic Engineers, every year we participate in the engineering week. We deploy our members to local junior high school and high school to talk about our project to promote the study of engineering. But at the same time, we also participate in the science fair that the state of Texas is organizing. Our engineer will be mentoring students, number one, to help them with the project, but number two, to help us identify talent so that we can recruit them further into the field of STEM. One of the participation that we did was the competition of the, what they call Future City, where students will be building a city on a computer simulation. And in recent year, we promote the theme of smart city where city will be connected the individual houses and together into the internet. And we want to bring awareness of cybersecurity into that competition. So we deploy engineer to supervise the people, the students who participate in the competition. We bring awareness not in the technical detail level, but in what we've call the compound level so student will be able to know what required to provide cybersecurity for the smart city that they are building. And at the same time, we were able to identify talent, especially talent in the minority and in the woman, so that we can recruit them more actively. And we also raise money for scholarship. We believe that scholarship is the best way to entice student to continue education at the college level. So with scholarship, it's very easy to recruit them to the field and then push them to go further into the cybersecurity area. >> Yeah, I mean, I see a lot of the parents like, oh, my kid's going to go join the soccer team, we get private lessons, and maybe they'll get a scholarship someday. Well, they only do half scholarships. Anyway. I mean, if they spent that time doing these other things, it's just, again, this is a new life skill, like the Girl Scouts. And this is where I want to get into this whole silo breaking down, because Amy, you brought this up, and Bill, you were talking about it, as well. You got multiple stakeholders here with this event. You've got public, you've got private, and you've got educators. It's the intersection of all of them. It's, again, if those silos break down, the confluence of those three stakeholders have to work together. So let's talk about that. Educators. You guys are educating young minds. You're interfacing with private institutions and now the public. What about educators? What can they do to make cyber better? 'Cause there's no real manual. I mean, it's not like this court is a body of work of how to educate cybersecurity. Maybe it's more recent. There's cutting edge best practices. But still, it's an evolving playbook. What's your thoughts for educators? Bill, we'll start with you. >> Well, I'm going to turn to Amy and let her go first. >> Let you go. >> That's fine. >> I would say as educators, it's really important for us to stay on top of how the field is evolving, right? So what we want to do is we want to promote these tight connections between educators and our faculty and applied research in industry and with industry partnerships. And I think that's how we're going to make sure that we're educating students in the best way. And you're talking about that inner, that confluence of the three different areas. And I think you have to keep those communication lines open to make sure that the information on where the field is going and what we need to concentrate on is flowing down into our educational process. And that works in both ways, that we can talk as educators and we can be telling industry what we're working on and what types of skills our students have and working with them to get the opportunities for our students to work in industry and develop those skills along the way, as well. And I think it's just all part of this really looking at what's going to be happening and how do we get people talking to each other? And the same thing with looking at public policy and bringing that into our education and into these real hands-on experiences. And that's how you really cement this type of knowledge with students, not by talking to them and not by showing them, but letting them do it. It's this learn by doing and building the resiliency that it takes when you learn by doing. And sometimes you learn by failing, but you just pick up and you keep going. And these are important skills that you develop along the way. >> You mentioned sharing, too. That's the key. Collaborating and sharing knowledge. It's an open world and everyone's collaborating. Bill, private-public partnerships. I mean, there's a real, private companies, you mentioned Palo Alto Networks and others. There's a real intersection there. They're motivated. They could, there's scholarship opportunities. Trung points to that. What is the public-private educator view there? How do companies get involved and what's the benefit for them? >> Well, that's what a lot of the universities are doing is to bring in as part of either their cyber centers or institutes people who are really focused on developing and furthering those public-private partnerships. That's really what my role is in all these things is to take us to a different level in those areas, not to take away from the academic side, but to add additional opportunities for both sides. Remember, in a public-private partnership, all entities have to have some gain in the process. Now, what I think is really interesting is the timing on particularly this subject, space and cybersecurity. This has been an absolute banner year for space. The standup of Space Force, the launch of commercial partnership, you know, commercial platforms delivering astronauts to the space station, recovering them, and bringing them back. The ability of a commercial satellite platform to be launched. Commercial platforms that not only launch but return back to where they're launched from. These are things that are stirring the hearts of the American citizens, the kids, again, they're getting interested. They're seeing this and getting enthused. So we have to seize upon that and we have to find a way to connect that. Public-private partnerships is the answer for that. It's not one segment that can handle it all. It's all of them combined together. If you look at space, space is going to be about commercial. It's going to be about civil. Moving from one side of the Earth to the other via space. And it's about government. And what's really cool for us, all those things are in our backyard. That's where that public-private comes together. The government's involved. The private sector's involved. The educators are involved. And we're all looking at the same things and trying to figure out, like this forum, what works best to go to the future. >> You know, if people are bored and they want to look for an exciting challenge, you couldn't have laid it out any clearer. It's the most exciting discipline. It's everything. I mean, we just talk about space. GPS is, everything we do is involved, has to do with satellites. (laughs) >> I have to tell you a story on that right? We have a very unique GPS story right in our backyard. So our sheriff is the son of the father of GPS for the Air Force. So you can't get better than that when it comes to being connected to all those platforms. So we really want to say, you know, this is so exciting for all of us because it gives everybody a job for a long time. >> You know, the kids that think TikTok's exciting, wait till they see what's going on here with you guys, this program. Trung, final word on this from the public side. You're at the Air Force. You're doing research. Are you guys opening it up? Are you integrating into the private and educational sectors? How do you see that formula playing out? And what's the best practice for students and preparing them? >> I think it's the same in every university in the engineering program will require our students to do the final project before graduation. And in this kind of project, we send them out to work in the private industry, the private company that sponsor them. They get the benefit of having an intern working for them and they get the benefit of reviewing the students as the prospective employee in the future. So it's good for the student to gain practical experience working in this program. Sometimes we call that a co-op program. Sometimes we call that a capstone program. And the company will accept the student on a trial basis, giving them some assignment and then pay them a little bit of money. So it's good for the student to earn some extra money, to have some experience that they can put on their resume when they apply for the final, for the job. So the collaboration between university and private sector is really important. When I join a faculty normally there already exist that connection. It came from normally, again, from the dean of engineering, who would wine and dine with companies, build up relationship, and sign up agreement. But it's us professor who have to do the (indistinct) approach to do a good performance so that we can build up credibility to continue the relationship with those company and the student that we selected to send to those company. We have to make sure that they will represent the university well, they will do a good job, and they will make a good impression. >> Thank you very much for a great insight, Trung, Bill, Amy. Amazing topic. I'd like to end this session with each of you to make a statement on the importance of cybersecurity to space. We'll go Trung, Bill, and Amy. Trung, the importance of cybersecurity to space, brief statement. >> The importance of cybersecurity, we know that it's affecting every component that we are using and we are connecting to, and those component, normally we use them for personal purpose, but when we enter the workforce, sometimes we connect them to the important system that the government or the company are investing to be put into space. So it's really important to practice cybersecurity, and a lot of time, it's very easy to know the concept. We have to be careful. But in reality, we tend to forget to to practice it the way we forget how to drive a car safely. And with driving a car, we have a program called defensive driving that requires us to go through training every two or three years so that we can get discount. Every organization we are providing the annual cybersecurity practice not to tell people about the technology, but to remind them about the danger of not practicing cybersecurity and it's a requirement for every one of us. >> Bill, the importance of cybersecurity to space. >> It's not just about young people. It's about all of us. As we grow and we change, as I referenced it, we're changing from an analog world to a digital world. Those of us who have been in the business and have hair that looks like mine, we need to be just as cognizant about cybersecurity practice as the young people. We need to understand how it affects our lives, and particularly in space, because we're going to be talking about people, moving people to space, moving payloads, data transfer, all of those things. And so there's a whole workforce that needs to be retrained or upskilled in cyber that's out there. So the opportunity is ever expansive for all of us. >> Amy, the importance of cybersecurity in space. >> I mean the emphasis of cybersecurity is space just simply can't be over emphasized. There are so many aspects that are going to have to be considered as systems get ever more complex. And as we pointed out, we're putting people's lives at stake here. This is incredibly, incredibly complicated and incredibly impactful, and actually really exciting, the opportunities that are here for students and the workforce of the future to really make an enormous impact on the world around us. And I hope we're able to get that message out to students and to children today, that these are really interesting fields that you need to consider. >> Thank you very much. I'm John Furrier with theCUBE, and the importance of cybersecurity and space is the future of the world's all going to happen in and around space with technology, people, and society. Thank you to Cal Poly, and thank you for watching the Cybersecurity and Space Symposium 2020. (bright music)

>>from the Cube Studios >>in Palo Alto and >>Boston connecting with thought leaders all around the world. This is a cube conversation. >>Hey, welcome back here. Ready? Jeff Frick here with the Cube. We're doing a special presentation today really talking about AI and making ai really with two companies that are right in the heart of the Dell EMC as well as Intel. So we're excited to have a couple Cube alumni back on the program. Haven't seen him in a little while. First off from Intel. Lisa Spelman. She is the corporate VP and GM for the Xeon Group in Jersey on and Memory Group. Great to see you, Lisa. >>Good to see you again, too. >>And we've got Ravi Pinter. Conte. He is the SBP server product management, also from Dell Technologies. Ravi, great to see you as well. >>Good to see you on beast. Of course, >>yes. So let's jump into it. So, yesterday, Robbie, you guys announced a bunch of new kind of ai based solutions where if you can take us through that >>Absolutely so one of the things we did Jeff was we said it's not good enough for us to have a point product. But we talked about hope, the tour of products, more importantly, everything from our workstation side to the server to these storage elements and things that we're doing with VM Ware, for example. Beyond that, we're also obviously pleased with everything we're doing on bringing the right set off validated configurations and reference architectures and ready solutions so that the customer really doesn't have to go ahead and do the due diligence. Are figuring out how the various integration points are coming for us in making a solution possible. Obviously, all this is based on the great partnership we have with Intel on using not just their, you know, super cues, but FPG's as well. >>That's great. So, Lisa, I wonder, you know, I think a lot of people you know, obviously everybody knows Intel for your CPU is, but I don't think they recognize kind of all the other stuff that can wrap around the core CPU to add value around a particular solution. Set or problems. That's what If you could tell us a little bit more about Z on family and what you guys are doing in the data center with this kind of new interesting thing called AI and machine learning. >>Yeah. Um, so thanks, Jeff and Ravi. It's, um, amazing. The way to see that artificial intelligence applications are just growing in their pervasiveness. And you see it taking it out across all sorts of industries. And it's actually being built into just about every application that is coming down the pipe. And so if you think about meeting toe, have your hardware foundation able to support that. That's where we're seeing a lot of the customer interest come in. And not just a first Xeon, but, like Robbie said on the whole portfolio and how the system and solution configuration come together. So we're approaching it from a total view of being able to move all that data, store all of that data and cross us all of that data and providing options along that entire pipeline that move, um, and within that on Z on. Specifically, we've really set that as our cornerstone foundation for AI. If it's the most deployed solution and data center CPU around the world and every single application is going to have artificial intelligence in it, it makes sense that you would have artificial intelligence acceleration built into the actual hardware so that customers get a better experience right out of the box, regardless of which industry they're in or which specialized function they might be focusing on. >>It's really it's really wild, right? Cause in process, right, you always move through your next point of failure. So, you know, having all these kind of accelerants and the ways that you can carve off parts of the workload part of the intelligence that you can optimize betters is so important as you said Lisa and also Rocket and the solution side. Nobody wants General Ai just for ai sake. It's a nice word. Interesting science experiment. But it's really in the applied. A world is. We're starting to see the value in the application of this stuff, and I wonder you have a customer. You want to highlight Absalon, tell us a little bit about their journey and what you guys did with them. >>Great, sure. I mean, if you didn't start looking at Epsilon there in the market in the marketing business, and one of the crucial things for them is to ensure that they're able to provide the right data. Based on that analysis, there run on? What is it that the customer is looking for? And they can't wait for a period of time, but they need to be doing that in the near real time basis, and that's what excellent does. And what really blew my mind was the fact that they actually service are send out close to 100 billion messages. Again, it's 100 billion messages a year. And so you can imagine the amount of data that they're analyzing, which is in petabytes of data, and they need to do real time. And that's all possible because of the kind of analytics we have driven into the power It silver's, you know, using the latest of the Intel Intel Xeon processor couple with some of the technologies from the BGS side, which again I love them to go back in and analyze this data and service to the customers very rapidly. >>You know, it's funny. I think Mark Tech is kind of an under appreciated ah world of ai and, you know, in machine to machine execution, right, That's the amount of transactions go through when you load a webpage on your site that actually ideas who you are you know, puts puts a marketplace together, sells time on that or a spot on that ad and then lets people in is a really sophisticated, as you said in massive amounts of data going through the interesting stuff. If it's done right, it's magic. And if it's done, not right, then people get pissed off. You gotta have. You gotta have use our tools. >>You got it. I mean, this is where I talked about, you know, it can be garbage in garbage out if you don't really act on the right data. Right. So that is where I think it becomes important. But also, if you don't do it in a timely fashion, but you don't service up the right content at the right time. You miss the opportunity to go ahead and grab attention, >>right? Right. Lisa kind of back to you. Um, you know, there's all kinds of open source stuff that's happening also in the in the AI and machine learning world. So we hear things about tense or flow and and all these different libraries. How are you guys, you know, kind of embracing that world as you look at ai and kind of the development. We've been at it for a while. You guys are involved in everything from autonomous vehicles to the Mar Tech. Is we discussed? How are you making sure that these things were using all the available resources to optimize the solutions? >>Yeah, I think you and Robbie we're just hitting on some of those examples of how many ways people have figured out how to apply AI now. So maybe at first it was really driven by just image recognition and image tagging. But now you see so much work being driven in recommendation engines and an object detection for much more industrial use cases, not just consumer enjoyment and also those things you mentioned and hit on where the personalization is a really fine line you walk between. How do you make an experience feel good? Personalized versus creepy personalized is a real challenge and opportunity across so many industries. And so open source like you mentioned, is a great place for that foundation because it gives people the tools to build upon. And I think our strategy is really a stack strategy that starts first with delivering the best hardware for artificial intelligence and again the other is the foundation for that. But we also have, you know, Milat type processing for out of the Edge. And then we have all the way through to very custom specific accelerators into the data center, then on top about the optimized software, which is going into each of those frameworks and doing the work so that the framework recognizes the specific acceleration we built into the CPU. Whether that steel boost or recognizes the capabilities that sit in that accelerator silicon, and then once we've done that software layer and this is where we have the opportunity for a lot of partnership is the ecosystem and the solutions work that Robbie started off by talking about. So Ai isn't, um, it's not easy for everyone. It has a lot of value, but it takes work to extract that value. And so partnerships within the ecosystem to make sure that I see these are taking those optimization is building them in and fundamentally can deliver to customers. Reliable solution is the last leg of that of that strategy, but it really is one of the most important because without it you get a lot of really good benchmark results but not a lot of good, happy customer, >>right? I'm just curious, Lee says, because you kind of sit in the catbird seat. You guys at the core, you know, kind of under all the layers running data centers run these workloads. How >>do you see >>kind of the evolution of machine learning and ai from kind of the early days, where with science projects and and really smart people on mahogany row versus now people are talking about trying to get it to, like a citizen developer, but really a citizen data science and, you know, in exposing in the power of AI to business leaders or business executioners. Analysts, if you will, so they can apply it to their day to day world in their day to day life. How do you see that kind of evolving? Because you not only in it early, but you get to see some of the stuff coming down the road in design, find wins and reference architectures. How should people think about this evolution? >>It really is one of those things where if you step back from the fundamentals of AI, they've actually been around for 50 or more years. It's just that the changes in the amount of computing capability that's available, the network capacity that's available and the fundamental efficiency that I t and infrastructure managers and get out of their cloud architectures as allowed for this pervasiveness to evolve. And I think that's been the big tipping point that pushed people over this fear. Of course, I went through the same thing that cloud did where you had maybe every business leader or CEO saying Hey, get me a cloud and I'll figure out what for later give me some AI will get a week and make it work, But we're through those initial use pieces and starting to see a business value derived from from those deployments. And I think some of the most exciting areas are in the medical services field and just the amount, especially if you think of the environment we're in right now. The amount of efficiency and in some cases, reduction in human contact that you could require for diagnostics and just customer tracking and ability, ability to follow their entire patient History is really powerful and represents the next wave and care and how we scale our limited resource of doctors nurses technician. And the point we're making of what's coming next is where you start to see even more mass personalization and recommendations in that way that feel very not spooky to people but actually comforting. And they take value from them because it allows them to immediately act. Robbie reference to the speed at which you have to utilize the data. When people get immediately act more efficiently. They're generally happier with the service. So we see so much opportunity and we're continuing to address across, you know, again that hardware, software and solution stack so we can stay a step ahead of our customers, >>Right? That's great, Ravi. I want to give you the final word because you guys have to put the solutions together, it actually delivering to the customer. So not only, you know the hardware and the software, but any other kind of ecosystem components that you have to bring together. So I wonder if you can talk about that approach and how you know it's it's really the solution. At the end of the day, not specs, not speeds and feeds. That's not really what people care about. It's really a good solution. >>Yeah, three like Jeff, because end of the day I mean, it's like this. Most of us probably use the A team to retry money, but we really don't know what really sits behind 80 and my point being that you really care at that particular point in time to be able to put a radio do machine and get your dollar bills out, for example. Likewise, when you start looking at what the customer really needs to know, what Lisa hit upon is actually right. I mean what they're looking for. And you said this on the whole solution side house. To our our mantra to this is very simple. We want to make sure that we use the right basic building blocks, ensuring that we bring the right solutions using three things the right products which essentially means that we need to use the right partners to get the right processes in GPU Xen. But then >>we get >>to the next level by ensuring that we can actually do things we can either provide no ready solutions are validated reference architectures being that you have the sausage making process that you now don't need to have the customer go through, right? In a way. We have done the cooking and we provide a recipe book and you just go through the ingredient process of peering does and then off your off right to go get your solution done. And finally, the final stages there might be helped that customers still need in terms of services. That's something else Dell technology provides. And the whole idea is that customers want to go out and have them help deploying the solutions. We can also do that we're services. So that's probably the way we approach our data. The way we approach, you know, providing the building blocks are using the right technologies from our partners, then making sure that we have the right solutions that our customers can look at. And finally, they need deployment. Help weaken due their services. >>Well, Robbie, Lisa, thanks for taking a few minutes. That was a great tee up, Rob, because I think we're gonna go to a customer a couple of customer interviews enjoying that nice meal that you prepared with that combination of hardware, software, services and support. So thank you for your time and a great to catch up. All right, let's go and run the tape. Hi, Jeff. I wanted to talk about two examples of collaboration that we have with the partners that have yielded Ah, really examples of ah put through HPC and AI activities. So the first example that I wanted to cover is within your AHMAD team up in Canada with that team. We collaborated with Intel on a tuning of algorithm and code in order to accelerate the mapping of the human brain. So we have a cluster down here in Texas called Zenith based on Z on and obtain memory on. And we were able to that customer with the three of us are friends and Intel the norm, our team on the Dell HPC on data innovation, injuring team to go and accelerate the mapping of the human brain. So imagine patients playing video games or doing all sorts of activities that help understand how the brain sends the signal in order to trigger a response of the nervous system. And it's not only good, good way to map the human brain, but think about what you can get with that type of information in order to help cure Alzheimer's or dementia down the road. So this is really something I'm passionate about. Is using technology to help all of us on all of those that are suffering from those really tough diseases? Yeah, yeah, way >>boil. I'm a project manager for the project, and the idea is actually to scan six participants really intensively in both the memory scanner and the G scanner and see if we can use human brain data to get closer to something called Generalized Intelligence. What we have in the AI world, the systems that are mathematically computational, built often they do one task really, really well, but they struggle with other tasks. Really good example. This is video games. Artificial neural nets can often outperform humans and video games, but they don't really play in a natural way. Artificial neural net. Playing Mario Brothers The way that it beats the system is by actually kind of gliding its way through as quickly as possible. And it doesn't like collect pennies. For example, if you play Mary Brothers as a child, you know that collecting those coins is part of your game. And so the idea is to get artificial neural nets to behave more like humans. So like we have Transfer of knowledge is just something that humans do really, really well and very naturally. It doesn't take 50,000 examples for a child to know the difference between a dog and a hot dog when you eat when you play with. But an artificial neural net can often take massive computational power and many examples before it understands >>that video games are awesome, because when you do video game, you're doing a vision task instant. You're also doing a >>lot of planning and strategy thinking, but >>you're also taking decisions you several times a second, and we record that we try to see. Can we from brain activity predict >>what people were doing? We can break almost 90% accuracy with this type of architecture. >>Yeah, yeah, >>Use I was the lead posts. Talk on this collaboration with Dell and Intel. She's trying to work on a model called Graph Convolution Neural nets. >>We have being involved like two computing systems to compare it, like how the performance >>was voting for The lab relies on both servers that we have internally here, so I have a GPU server, but what we really rely on is compute Canada and Compute Canada is just not powerful enough to be able to run the models that he was trying to run so it would take her days. Weeks it would crash, would have to wait in line. Dell was visiting, and I was invited into the meeting very kindly, and they >>told us that they started working with a new >>type of hardware to train our neural nets. >>Dell's using traditional CPU use, pairing it with a new >>type off memory developed by Intel. Which thing? They also >>their new CPU architectures and really optimized to do deep learning. So all of that sounds great because we had this problem. We run out of memory, >>the innovation lab having access to experts to help answer questions immediately. That's not something to gate. >>We were able to train the attic snatch within 20 minutes. But before we do the same thing, all the GPU we need to wait almost three hours to each one simple way we >>were able to train the short original neural net. Dell has been really great cause anytime we need more memory, we send an email, Dell says. Yeah, sure, no problem. We'll extended how much memory do you need? It's been really simple from our end, and I think it's really great to be at the edge of science and technology. We're not just doing the same old. We're pushing the boundaries. Like often. We don't know where we're going to be in six months. In the big data world computing power makes a big difference. >>Yeah, yeah, yeah, yeah. The second example I'd like to cover is the one that will call the data accelerator. That's a publisher that we have with the University of Cambridge, England. There we partnered with Intel on Cambridge, and we built up at the time the number one Io 500 storage solution on. And it's pretty amazing because it was built on standard building blocks, power edge servers until Xeon processors some envy me drives from our partners and Intel. And what we did is we. Both of this system with a very, very smart and elaborate suffering code that gives an ultra fast performance for our customers, are looking for a front and fast scratch to their HPC storage solutions. We're also very mindful that this innovation is great for others to leverage, so the suffering Could will soon be available on Get Hub on. And, as I said, this was number one on the Iot 500 was initially released >>within Cambridge with always out of focus on opening up our technologies to UK industry, where we can encourage UK companies to take advantage of advanced research computing technologies way have many customers in the fields of automotive gas life sciences find our systems really help them accelerate their product development process. Manage Poor Khalidiya. I'm the director of research computing at Cambridge University. Yeah, we are a research computing cloud provider, but the emphasis is on the consulting on the processes around how to exploit that technology rather than the better results. Our value is in how we help businesses use advanced computing resources rather than the provision. Those results we see increasingly more and more data being produced across a wide range of verticals, life sciences, astronomy, manufacturing. So the data accelerators that was created as a component within our data center compute environment. Data processing is becoming more and more central element within research computing. We're getting very large data sets, traditional spinning disk file systems can't keep up and we find applications being slowed down due to a lack of data, So the data accelerator was born to take advantage of new solid state storage devices. I tried to work out how we can have a a staging mechanism for keeping your data on spinning disk when it's not required pre staging it on fast envy any stories? Devices so that can feed the applications at the rate quiet for maximum performance. So we have the highest AI capability available anywhere in the UK, where we match II compute performance Very high stories performance Because for AI, high performance storage is a key element to get the performance up. Currently, the data accelerated is the fastest HPC storage system in the world way are able to obtain 500 gigabytes a second read write with AI ops up in the 20 million range. We provide advanced computing technologies allow some of the brightest minds in the world really pushed scientific and medical research. We enable some of the greatest academics in the world to make tomorrow's discoveries. Yeah, yeah, yeah. >>Alright, Welcome back, Jeff Frick here and we're excited for this next segment. We're joined by Jeremy Raider. He is the GM digital transformation and scale solutions for Intel Corporation. Jeremy, great to see you. Hey, thanks for having me. I love I love the flowers in the backyard. I thought maybe you ran over to the Japanese, the Japanese garden or the Rose Garden, Right To very beautiful places to visit in Portland. >>Yeah. You know, you only get him for a couple. Ah, couple weeks here, so we get the timing just right. >>Excellent. All right, so let's jump into it. Really? And in this conversation really is all about making Ai Riel. Um, and you guys are working with Dell and you're working with not only Dell, right? There's the hardware and software, but a lot of these smaller a solution provider. So what is some of the key attributes that that needs to make ai riel for your customers out there? >>Yeah, so, you know, it's a it's a complex space. So when you can bring the best of the intel portfolio, which is which is expanding a lot, you know, it's not just the few anymore you're getting into Memory technologies, network technologies and kind of a little less known as how many resources we have focused on the software side of things optimizing frameworks and optimizing, and in these key ingredients and libraries that you can stitch into that portfolio to really get more performance in value, out of your machine learning and deep learning space. And so you know what we've really done here with Dell? It has started to bring a bunch of that portfolio together with Dell's capabilities, and then bring in that ai's V partner, that software vendor where we can really take and stitch and bring the most value out of that broad portfolio, ultimately using using the complexity of what it takes to deploy an AI capability. So a lot going on. They're bringing kind of the three legged stool of the software vendor hardware vendor dental into the mix, and you get a really strong outcome, >>right? So before we get to the solutions piece, let's stick a little bit into the Intel world. And I don't know if a lot of people are aware that obviously you guys make CPUs and you've been making great CPIs forever. But there's a whole lot more stuff that you've added, you know, kind of around the core CPU. If you will in terms of of actual libraries and ways to really optimize the seond processors to operate in an AI world. I wonder if you can kind of take us a little bit below the surface on how that works. What are some of the examples of things you can do to get more from your Gambira Intel processors for ai specific applications of workloads? >>Yeah, well, you know, there's a ton of software optimization that goes into this. You know that having the great CPU is definitely step one. But ultimately you want to get down into the libraries like tensor flow. We have data analytics, acceleration libraries. You know, that really allows you to get kind of again under the covers a little bit and look at it. How do we have to get the most out of the kinds of capabilities that are ultimately used in machine learning in deep learning capabilities, and then bring that forward and trying and enable that with our software vendors so that they can take advantage of those acceleration components and ultimately, you know, move from, you know, less training time or could be a the cost factor. But those are the kind of capabilities we want to expose to software vendors do these kinds of partnerships. >>Okay. Ah, and that's terrific. And I do think that's a big part of the story that a lot of people are probably not as aware of that. There are a lot of these optimization opportunities that you guys have been leveraging for a while. So shifting gears a little bit, right? AI and machine learning is all about the data. And in doing a little research for this, I found actually you on stage talking about some company that had, like, 350 of road off, 315 petabytes of data, 140,000 sources of those data. And I think probably not great quote of six months access time to get that's right and actually work with it. And the company you're referencing was intel. So you guys know a lot about debt data, managing data, everything from your manufacturing, and obviously supporting a global organization for I t and run and ah, a lot of complexity and secrets and good stuff. So you know what have you guys leveraged as intel in the way you work with data and getting a good data pipeline. That's enabling you to kind of put that into these other solutions that you're providing to the customers, >>right? Well, it is, You know, it's absolutely a journey, and it doesn't happen overnight, and that's what we've you know. We've seen it at Intel on We see it with many of our customers that are on the same journey that we've been on. And so you know, this idea of building that pipeline it really starts with what kind of problems that you're trying to solve. What are the big issues that are holding you back that company where you see that competitive advantage that you're trying to get to? And then ultimately, how do you build the structure to enable the right kind of pipeline of that data? Because that's that's what machine learning and deep learning is that data journey. So really a lot of focus around you know how we can understand those business challenges bring forward those kinds of capabilities along the way through to where we structure our entire company around those assets and then ultimately some of the partnerships that we're gonna be talking about these companies that are out there to help us really squeeze the most out of that data as quickly as possible because otherwise it goes stale real fast, sits on the shelf and you're not getting that value out of right. So, yeah, we've been on the journey. It's Ah, it's a long journey, but ultimately we could take a lot of those those kind of learnings and we can apply them to our silicon technology. The software optimization is that we're doing and ultimately, how we talk to our enterprise customers about how they can solve overcome some of the same challenges that we did. >>Well, let's talk about some of those challenges specifically because, you know, I think part of the the challenge is that kind of knocked big data, if you will in Hadoop, if you will kind of off the rails. Little bit was there's a whole lot that goes into it. Besides just doing the analysis, there's a lot of data practice data collection, data organization, a whole bunch of things that have to happen before. You can actually start to do the sexy stuff of AI. So you know, what are some of those challenges. How are you helping people get over kind of these baby steps before they can really get into the deep end of the pool? >>Yeah, well, you know, one is you have to have the resource is so you know, do you even have the resource is if you can acquire those Resource is can you keep them interested in the kind of work that you're doing? So that's a big challenge on and actually will talk about how that fits into some of the partnerships that we've been establishing in the ecosystem. It's also you get stuck in this poc do loop, right? You finally get those resource is and they start to get access to that data that we talked about. It start to play out some scenarios, a theorize a little bit. Maybe they show you some really interesting value, but it never seems to make its way into a full production mode. And I think that is a challenge that has faced so many enterprises that are stuck in that loop. And so that's where we look at who's out there in the ecosystem that can help more readily move through that whole process of the evaluation that proved the r a y, the POC and ultimately move that thing that capability into production mode as quickly as possible that you know that to me is one of those fundamental aspects of if you're stuck in the POC. Nothing's happening from this. This is not helping your company. We want to move things more quickly, >>right? Right. And let's just talk about some of these companies that you guys are working with that you've got some reference architectures is data robot a Grid dynamics H 20 just down the road in Antigua. So a lot of the companies we've worked with with Cube and I think you know another part that's interesting. It again we can learn from kind of old days of big data is kind of generalized. Ai versus solution specific. Ai and I think you know where there's a real opportunity is not AI for a sake, but really it's got to be applied to a specific solution, a specific problem so that you have, you know, better chatbots, better customer service experience, you know, better something. So when you were working with these folks and trying to design solutions or some of the opportunities that you saw to work with some of these folks to now have an applied a application slash solution versus just kind of AI for ai's sake. >>Yeah. I mean, that could be anything from fraud, detection and financial services, or even taking a step back and looking more horizontally like back to that data challenge. If if you're stuck at the AI built a fantastic Data lake, but I haven't been able to pull anything back out of it, who are some of the companies that are out there that can help overcome some of those big data challenges and ultimately get you to where you know, you don't have a data scientist spending 60% of their time on data acquisition pre processing? That's not where we want them, right? We want them on building out that next theory. We want them on looking at the next business challenge. We want them on selecting the right models, but ultimately they have to do that as quickly as possible so that they can move that that capability forward into the next phase. So, really, it's about that that connection of looking at those those problems or challenges in the whole pipeline. And these companies like data robot in H 20 quasi. Oh, they're all addressing specific challenges in the end to end. That's why they've kind of bubbled up as ones that we want to continue to collaborate with, because it can help enterprises overcome those issues more fast. You know more readily. >>Great. Well, Jeremy, thanks for taking a few minutes and giving us the Intel side of the story. Um, it's a great company has been around forever. I worked there many, many moons ago. That's Ah, that's a story for another time, but really appreciate it and I'll interview you will go there. Alright, so super. Thanks a lot. So he's Jeremy. I'm Jeff Frick. So now it's time to go ahead and jump into the crowd chat. It's crowdchat dot net slash make ai real. Um, we'll see you in the chat. And thanks for watching

(upbeat music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBE conversation. >> Hello, and welcome to theCUBE Studios here in Palo Alto, California. We have a special Around theCUBE segment, Unpacking AI. This is a Get Smart Series. We have three great guests. Rajen Sheth, VP of AI and Product Management at Google. He knows well the AI development for Google Cloud. Dr. Kate Darling, research specialist at MIT media lab. And Professor Barry O'Sullivan, Director SFI Centre for Training AI, University of College Cork in Ireland. Thanks for coming on, everyone. Let's get right to it. Ethics in AI as AI becomes mainstream, moves out to the labs and computer science world to mainstream impact. The conversations are about ethics. And this is a huge conversation, but first thing people want to know is, what is AI? What is the definition of AI? How should people look at AI? What is the definition? We'll start there, Rajen. >> So I think the way I would define AI is any way that you can make a computer intelligent, to be able to do tasks that typically people used to do. And what's interesting is that AI is something, of course, that's been around for a very long time in many different forms. Everything from expert systems in the '90s, all the way through to neural networks now. And things like machine learning, for example. People often get confused between AI and machine learning. I would think of it almost the way you would think of physics and calculus. Machine learning is the current best way to use AI in the industry. >> Kate, your definition of AI, do you have one? >> Well, I find it interesting that there's no really good universal definition. And also, I would agree with Rajen that right now, we're using kind of a narrow definition when we talk about AI, but the proper definition is probably much more broad than that. So probably something like a computer system that can make decisions independent of human input. >> Professor Barry, your take on the definition of AI, is there one? What's a good definition? >> Well, you know, so I think AI has been around for 70 years, and we still haven't agreed the definition for it, as Kate said. I think that's one of those very interesting things. I suppose it's really about making machines act and behave rationally in the world, ideally autonomously, so without human intervention. But I suppose these days, AI is really focused on achieving human level performance in very narrowly defined tasks, you know, so game playing, recommender systems, planning. So we do those in isolation. We don't tend to put them together to create the fabled artificial general intelligence. I think that's something that we don't tend to focus on at all, actually if that made sense. >> Okay the question is that AI is kind of elusive, it's changing, it's evolving. It's been around for awhile, as you guys pointed out, but now that it's on everyone's mind, we see it in the news every day from Facebook being a technology program with billions of people. AI was supposed to solve the problem there. We see new workloads being developed with cloud computing where AI is a critical software component of all this. But that's a geeky world. But the real world, as an ethical conversation, is not a lot of computer scientists have taken ethics classes. So who decides what's ethical with AI? Professor Barry, let's start with you. Where do we start with ethics? >> Yeah, sure, so one of the things I do is I'm the Vice-Chair of the European Commission's High-Level Expert Group on Artificial Intelligence, and this year we published the Ethics Guidelines for Trustworthy AI in Europe, which is all about, you know, setting an ethical standard for what AI is. You're right, computer scientists don't take ethical standards, but I suppose what we are faced with here is a technology that's so pervasive in our lives that we really do need to think carefully about the impact of that technology on, you know, human agency, and human well-being, on societal well-being. So I think it's right and proper that we're talking about ethics at this moment in time. But, of course, we do need to realize that ethics is not a panacea, right? So it's certainly something we need to talk about, but it's not going to solve, it's not going to rid us of all of the detrimental applications or usages of AI that we might see today. >> Kate, your take on ethics. Start all over, throw out everything, build on it, what do we do? >> Well, what we do is we get more interdisciplinary, right? I mean, because you asked, "Who decides?". Until now it has been the people building the technology who have had to make some calls on ethics. And it's not, you know, it's not necessarily the way of thinking that they are trained in, and so it makes a lot of sense to have projects like the one that Barry is involved in, where you bring together people from different areas of expert... >> I think we lost Kate there. Rajen, why don't you jump in, talk about-- >> (muffled speaking) you decide issues of responsibility for harm. We have to look at algorithmic bias. We have to look at supplementing versus replacing human labor, we have to look at privacy and data security. We have look at the things that I'm interested in like the ways that people anthropomorphize the technology and use it in a way that's perhaps different than intended. So, depending on what issue we're looking at, we need to draw from a variety of disciplines. And fortunately we're seeing more support for this within companies and within universities as well. >> Rajen, your take on this. >> So, I think one thing that's interesting is to step back and understand why this moment is so compelling and why it's so important for us to understand this right now. And the reason for that is that this is the moment where AI is starting to have an impact on the everyday person. Anytime I present, I put up a slide of the Mosaic browser from 1994 and my point is that, that's where AI is today. It's at the very beginning stages of how we can impact people, even though it's been around for 70 years. And what's interesting about ethics, is we have an opportunity to do that right from the beginning right now. I think that there's a lot that you can bring in from the way that we think about ethics overall. For example, in our company, can you all hear me? >> Yep. >> Mm-hmm. >> Okay, we've hired an ethicist within our company, from a university, to actually bring in the general principles of ethics and bring that into AI. But I also do think that things are different so for example, bias is an ethical problem. However, bias can be encoded and actually given more legitimacy when it could be encoded in an algorithm. So, those are things that we really need to watch out for where I think it is a little bit different and a little bit more interesting. >> This is a great point-- >> Let me just-- >> Oh, go ahead. >> Yeah, just one interesting thing to bear in mind, and I think Kate said this, and I just want to echo it, is that AI is becoming extremely multidisciplinary. And I think it's no longer a technical issue. Obviously there are massive technical challenges, but it's now become as much an opportunity for people in the social sciences, the humanities, ethics people. Legal people, I think need to understand AI. And in fact, I gave a talk recently at a legal symposium, and the idea of this on a parallel track of people who have legal expertise and AI expertise, I think that's a really fantastic opportunity that we need to bear in mind. So, unfortunately us nerds, we don't own AI anymore. You know, it's something we need to interact with the real world on a significant basis. >> You know, I want to ask a question, because you know, the algorithms, everyone talks about the algorithms and the bias and all that stuff. It's totally relevant, great points on interdisciplinary, but there's a human component here. As AI starts to infiltrate the culture and hit everyday life, the reaction to AI sometimes can be, "Whoa, my job's going to get automated away." So, I got to ask you guys, as we deal with AI, is that a reflection on how we deal with it to our own humanity? Because how we deal with AI from an ethics standpoint ultimately is a reflection on our own humanity. Your thoughts on this. Rajen, we'll start with you. >> I mean it is, oh, sorry, Rajen? >> So, I think it is. And I think that there are three big issues that I see that I think are reflective of ethics in general, but then also really are particular to AI. So, there's bias. And bias is an overall ethical issue that I think this is particular here. There's what you mentioned, future of work, you know, what does the workforce look like 10 years from now. And that changes quite a bit over time. If you look at the workforce now versus 30 years ago, it's quite a bit different. And AI will change that radically over the next 10 years. The other thing is what is good use of AI, and what's bad use of AI? And I think one thing we've discovered is that there's probably 10% of things that are clearly bad, and 10% of things that are clearly good, and 80% of things that are in that gray area in between where it's up to kind of your personal view. And that's the really really tough part about all this. >> Kate, you were going to weigh in. >> Well, I think that, I'm actually going to push back a little, not on Rajen, but on the question. Because I think that one of the fallacies that we are constantly engaging in is we are comparing artificial intelligence to human intelligence, and robots to people, and we're failing to acknowledge sufficiently that AI has a very different skillset than a person. So, I think it makes more sense to look at different analogies. For example, how have we used and integrated animals in the past to help us with work? And that lets us see that the answer to questions like, "Will AI disrupt the labor market?" "Will it change infrastructures and efficiencies?" The answer to that is yes. But will it be a one-to-one replacement of people? No. That said, I do think that AI is a really interesting mirror that we're holding up to ourselves to answer certain questions like, "What is our definition of fairness?" for example. We want algorithms to be fair. We want to program ethics into machines. And what it's really showing us is that we don't have good definitions of what these things are even though we thought we did. >> All right, Professor Barry, your thoughts? >> Yeah, I think there's many points one could make here. I suppose the first thing is that we should be seeing AI, not as a replacement technology, but as an assistive technology. It's here to help us in all sorts of ways to make us more productive, and to make us more accurate in how we carry out certain tasks. I think, absolutely the labor force will be transformed in the future, but there isn't going to be massive job loss. You know, the technology has always changed how we work and play and interact with each other. You know, look at the smart phone. The smart phone is 12 years old. We never imagined in 2007 that our world would be the way it is today. So technology transforms very subtly over long periods of time, and that's how it should be. I think we shouldn't fear AI. I think the thing we should fear most, in fact, is not Artificial Intelligence, but is actual stupidity. So I think we need to, I would encourage people not to think, it's very easy to talk negatively and think negatively about AI because it is such a impactful and promising technology, but I think we need to keep it real a little bit, right? So there's a lot of hype around AI that we need to sort of see through and understand what's real and what's not. And that's really some of the challenges we have to face. And also, one of the big challenges we have, is how do we educate the ordinary person on the street to understand what AI is, what it's capable of, when it can be trusted, and when it cannot be trusted. And ethics gets of some of the way there, but it doesn't have to get us all of the way there. We need good old-fashioned good engineering to make people trust in the system. >> That was a great point. Ethics is kind of a reflection of that mirror, I love that. Kate, I want to get to that animal comment about domesticating technology, but I want to stay in this culture question for a minute. If you look at some of the major tech companies like Microsoft and others, the employees are revolting around their use of AI in certain use cases. It's a knee-jerk reaction around, "Oh my God, "We're using AI, we're harming the world." So, we live in a culture now where it's becoming more mission driven. There's a cultural impact, and to your point about not fearing AI, are people having a certain knee-jerk reaction to AI because you're seeing cultures inside tech companies and society taking an opinion on AI. "Oh my God, it's definitely bad, our company's doing it. "We should not service those contracts. "Or, maybe I shouldn't buy that product "because it's listening to me." So, there's a general fear. Does this impact the ethical conversation? How do you guys see this? Because this is an interplay that we see that's a personal, it's a human reaction. >> Yeah, so if I may start, I suppose, absolutely there are, you know, the ethics debates is a critical one, and people are certainly fearful. There is this polarization in debate about good AI and bad AI, but you know, AI is good technology. It's one of these dual-use technologies. It can be applied to bad situation in ways that we would prefer it wasn't. And it can also, it's a force for tremendous good. So, we need to think about the regulation of AI, what we want it to do from a legal point of view, who is responsible, where does liability lie? We also think about what our ethical framework is, and of course, there is no international agreement on what is, there is no universal code of ethics, you know? So this is something that's very very heavily contextualized. But I think we certainly, I think we generally agree that we want to promote human well-being. We want to compute, we want to have a prosperous society. We want to protect the well-being of society. We don't want technology to impact society in any negative way. It's actually very funny. If you look back about 25-30 years ago, there was a technology where people were concerned that privacy was going to be a thing of the past. That computer systems were going to be tremendously biased because data was going to be incomplete and not representative. And there was a huge concern that good old-fashioned databases were going to be the technology that will destroy the fabric of society. That didn't happen. And I don't think we're going to have AI do that either. >> Kate? >> Yeah, we've seen a lot of technology panic, that may or may not be warranted, in the past. I think that AI and robotics suffers from a specific problem that people are influenced by science fiction and pop culture when they're thinking about the technology. And I feel like that can cause people to be worried about some things that maybe perhaps aren't the thing we should be worrying about currently. Like robots and jobs, or artificial super-intelligence taking over and killing us all, aren't maybe the main concerns we should have right now. But, algorithmic bias, for example, is a real thing, right? We see systems using data sets that disadvantage women, or people of color, and yet the use of AI is seen as neutral even though it's impinging existing biases. Or privacy and data security, right? You have technologies that are collecting massive amounts of data because the way learning works is you use lots of data. And so there's a lot of incentive to collect data. As a consumer, there's not a lot of incentive for me to want to curb that, because I want the device to listen to me and to be able to perform better. And so the question is, who is thinking about consumer protection in this space if all the incentives are toward collecting and using as much data as possible. And so I do think there is a certain amount of concern that is warranted, and where there are problems, I endorse people revolting, right? But I do think that we are sometimes a little bit skewed in our, you know, understanding where we currently are at with the technology, and what the actual problems are right now. >> Rajen, I want your thoughts on this. Education is key. As you guys were talking about, there's some things to pay attention to. How do you educate people about how to shape AI for good, and at the same time calm the fears of people at the same time, from revolting around misinformation or bad data around what could be? >> Well I think that the key thing here is to organize kind of how you evaluate this. And back to that one thing I was saying a little bit earlier, it's very tough to judge kind of what is good and what is bad. It's really up to personal perception. But then the more that you organize how to evaluate this, and then figure out ways to govern this, the easier it gets to evaluate what's in or out . So one thing that we did, was that we created a set of AI principles, and we kind of codified what we think AI should do, and then we codified areas that we would not go into as a company. The thing is, it's very high level. It's kind of like the constitution, and when you have something like the constitution, you have to get down to actual laws of what you would and wouldn't do. It's very hard to bucket and say, these are good use cases, these are bad use cases. But what we now have is a process around how do we actually take things that are coming in and figure out how do we evaluate them? A last thing that I'll mention, is that I think it's very important to have many many different viewpoints on it. Have viewpoints of people that are taking it from a business perspective, have people that are taking it from kind of a research and an ethics perspective, and all evaluate that together. And that's really what we've tried to create to be able to evaluate things as they come up. >> Well, I love that constitution angle. We'll have that as our last final question in a minute, that do we do a reset or not, but I want to get to that point that Kate mentioned. Kate, you're doing research around robotics. And I think robotics is, you've seen robotics surge in popularity from high schools have varsity teams now. You're seeing robotics with software advances and technology advances really become kind of a playful illustration of computer technology and software where AI is playing a role, and you're doing a lot of work there. But as intelligence comes into, say robotics, or software, or AI, there's a human reaction to all of this. So there's a psychology interaction to either AI and robotics. Can you guys share your thoughts on the humanization interaction between technology, as people stare at their phones today, that could be relationships in the future. And I think robotics might be a signal. You mentioned domesticating animals as an example back in the early days of when we were (laughing) as a society, that happened. Now we all have pets. Are we going to have robots as pets? Are we going to have AI pets? >> Yes, we are. (laughing) >> Is this kind of the human relationship? Okay, go ahead, share your thoughts. >> So, okay, the thing that I love about robots, and you know, in some applications to AI as well, is that people will treat these technologies like they're alive. Even though they know that they're just machine. And part of that is, again, the influence of science fiction and pop culture, that kind of primes us to do this. Part of it is the novelty of the technology moving into shared spaces, but then there's this actual biological element to it, where we have this inherent tendency to anthropomorphize, project human-like traits, behaviors, qualities, onto non-humans. And robots lend themselves really well to that because our brains are constantly scanning our environments and trying to separate things into objects and agents. And robots move like agents. We are evolutionarily hardwired to project intent onto the autonomous movement in our physical space. And this is why I love robots in particular as an AI use case, because people end up treating robots totally differently. Like people will name their Roomba vacuum cleaner and feel bad for it when it gets stuck, which they would never do with their normal vacuum cleaner, right? So, this anthropomorphization, I think, makes a huge difference when you're trying to integrate the technology, because it can have negative effects. It can lead to inefficiencies or even dangerous situations. For example, if you're using robots in the military as tools, and they're treating them like pets instead of devices. But then there are also some really fantastic use cases in health and education that rely specifically on this socialization of the robot. You can use a robot as a replacement for animal therapy where you can't use real animals. We're seeing great results in therapy with autistic children, engaging them in ways that we haven't seen previously. So there are a lot of really cool ways that we can make this work for us as well. >> Barry, your thoughts, have you ever thought that we'd be adopting AI as pets some day? >> Oh yeah, absolutely. Like Kate, I'm very excited about all of this too, and I think there's a few, I agree with everything Kate has said. Of course, you know, coming back to the remark you made at the beginning about people putting their faces in their smartphones all the time, you know, we can't crowdsource our sense of dignity, or that we can't have social media as the currency for how we value our lives or how we compare ourselves with others. So, you know, we do have to be careful here. Like, one of the really nice things about, one of the really nice examples of an AI system that was given some significant personality was, quite recently, Tuomas Sandholm and others at Carnegie Mellon produced this Liberatus poker playing bot, and this AI system was playing against these top-class Texas hold' em players. And all of these Texas hold 'em players were attributing a level of cunning and sophistication and mischief on this AI system that clearly it didn't have because it was essentially trying to just behave rationally. But we do like to project human characteristics onto AI systems. And I think what would be very very nice, and something we need to be very very careful of, is that when AI systems are around us, and particularly robots, you know, we do need to treat them with respect. And what I mean is, we do make sure that we treat those things that are serving society in as positive and nice a way as possible. You know, I do judge people on how they interact with, you know, sort of the least advantaged people in society. And you know, by golly, I will judge you on how you interact with a robot. >> Rajen-- >> We've actually done some research on that, where-- >> Oh, really-- >> We've shown that if you're low empathy, you're more willing to hit a robot, especially if it has a name. (panel laughing) >> I love all my equipment here, >> Oh, yeah? >> I got to tell ya, it's all beautiful. Rajen, computer science, and now AIs having this kind of humanization impact, this is an interesting shift. I mean, this is not what we studied in computer science. We were writin' code. We were going to automate things. Now there's notions of math, and not just math cognition, human relations, your thoughts on this? >> Yeah, you know what's interesting is that I think ultimately it boils down to the user experience. And I think there is this part of this which is around humanization, but then ultimately it boils down to what are you trying to do? And how well are you doing it with this technology? And I think that example around the Roomba is very interesting, where I think people kind of feel like this is more, almost like a person. But, also I think we should focus as well on what the technology is doing, and what impact it's having. My best example of this is Google Photos. And so, my whole family uses Google Photos, and they don't know that underlying it is some of the most powerful AI in the world. All they know is that they can find pictures of our kids and their grandkids on the beach anytime that they want. And so ultimately, I think it boils down to what is the AI doing for the people? And how is it? >> Yeah, expectations become the new user experience. I love that. Okay, guys, final question, and also humanization, we talked about the robotics, but also the ethics here. Ethics reminds me of the old security debate, and security in the old days. Do you increase the security, or do you throw it all away and start over? So with this idea of how do you figure out ethics in today's modern society with it being a mirror? Do we throw it all away and do a do-over, can we recast this? Can we start over? Do we augment? What's the approach that you guys see that we might need to go through right now to really, not hold back AI, but let it continue to grow and accelerate, educate people, bring value and user experience to the table? What is the path? We'll start with Barry, and then Kate, and then Rajen. >> Yeah, I can kick off. I think ethics gets us some of the way there, right? So, obviously we need to have a set of principles that we sign up to and agree upon. And there are literally hundreds of documents on AI ethics. I think in Europe, for example, there are 128 different documents around AI ethics, I mean policy documents. But, you know, we have to think about how are we actually going to make this happen in the real world? And I think, you know, if you take the aviation industry, that we trust in airplanes, because we understand that they're built to the highest standards, that they're tested rigorously, and that the organizations that are building these things are held account when things go wrong. And I think we need to do something similar in AI. We need good strong engineering, and you know, ethics is fantastic, and I'm a strong believer in ethical codes, but we do need to make it practical. And we do need to figure out a way of having the public trust in AI systems, and that comes back to education. So, I think we need the general public, and indeed ourselves, to be a little more cynical and questioning when we hear stories in the media about AI, because a lot of it is hyped. You know, and that's because researchers want to describe their research in an exciting way, but also, newspaper people and media people want to have a sticky subject. But I think we do need to have a society that can look at these technologies and really critique them and understand what's been said. And I think a healthy dose of cynicism is not going to do us any harm. >> So, modernization, do you change the ethical definition? Kate, what's your thoughts on all this? >> Well, I love that Barry brought up the aviation industry because I think that right now we're kind of an industry in its infancy, but if we look at how other industries have evolved to deal with some thorny ethical issues, like for example, medicine. You know, medicine had to develop a whole code of ethics, and develop a bunch of standards. If you look at aviation or other transportation industries, they've had to deal with a lot of things like public perception of what the technology can and can't do, and so you look at the growing pains that those industries have gone through, and then you add in some modern insight about interdisciplinary, about diversity, and tech development generally. Getting people together who have different experiences, different life experiences, when you're developing the technology, and I think we don't have to rebuild the wheel here. >> Yep. >> Rajen, your thoughts on the path forward, throw it all away, rebuild, what do we do? >> Yeah, so I think this is a really interesting one because of all the technologies I've worked in within my career, everything from the internet, to mobile, to virtualization, this is probably the most powerful potential for human good out there. And AI, the potential of what it can do is greater than almost anything else that's out there. However, I do think that people's perception of what it's going to do is a little bit skewed. So when people think of AI, they think of self-driving cars and robots and things like that. And that's not the reality of what AI is today. And so I think two things are important. One is to actually look at the reality of what AI is doing today and where it impacts people lives. Like, how does it personalize customer interactions? How does it make things more efficient? How do we spot things that we never were able to spot before? And start there, and then apply the ethics that we've already known for years and years and years, but adapt it to a way that actually makes sense for this. >> Okay, like that's it for the Around theCUBE. Looks like we've tallied up. Looks like Professor Barry 11, third place, Kate in second place with 13. Rajen with 16 points, you're the winner, so you get the last word on the segment here. Share your final thoughts on this panel. >> Well, I think it's really important that we're having this conversation right now. I think about back to 1994 when the internet first started. People did not have that conversation nearly as much at that point, and the internet has done some amazing things, and there have been some bad side effects. I think with this, if we have this conversation now, we have this opportunity to shape this technology in a very very positive way as we go forward. >> Thank you so much, and thanks everyone for taking the time to come in. All the way form Cork, Ireland, Professor Barry O'Sullivan. Dr. Kate Darling doing some amazing research at MIT on robotics and human psychology and like a new book coming out. Kate, thanks for coming out. And Rajen, thanks for winning and sharing your thoughts. Thanks everyone for coming. This is Around theCUBE here, Unpacking AI segment around ethics and human interaction and societal impact. I'm John Furrier with theCUBE. Thanks for watching. (upbeat music)

>>live from San Francisco. It's the Q covering Micron Insight 2019 >>Not to You, by Micron. >>Welcome back to San Francisco, everybody. This is a Micron Insight 2019 and you're watching the Cube, the leader in live coverage on Day Volonte with my co host, David Floyd. Di Mooney is here. She's the executive director of Micron gives. That's right. Give us the story. What's happening with Micron gives Tech for good. We love the tech for good stories. Tech companies are really taking this seriously. This is not just lip service. Give us the update. >>That's right. That's right. We're so proud of our company that they established a foundation 20 years ago to give back to our global communities. And since then we have given $115 million away and over 10,000 grands. So we have seen a lot of different opportunities in our global communities, and it's just been fabulous that our company supports >>you talk today about water dot or what's going on there. Why is that important in what your role there. >>So what we did is we started taking a look at an organization that we have. We have started recently binning beam or engaged with basic human needs and the grants that those support And when we were taking a look at, Really, what is the primary basic human need? Way discovered? It really is the need for water, and there are millions of people that cannot access this precious resource, and it's just was really surprising to us to think way, take it for granted so much. But yet it is very difficult to get. So as we took a look at this, there was a lot of information that this organization collects. And so we thought, Well, this will be a great opportunity for us to utilize information to enrich and bring in some of our advanced computing expertise along with our philanthropy, help them reach their mission even greater. >>This is huge. I was an event earlier this week, and the keynote speaker was an ultra marathoner, and he literally at one point he ran 4500 miles across the continent of Africa. He and two other ultra runners and people were asking what was The biggest challenge was that the heat was the painting. You know, the biggest challenge was see the challenges of of the community's getting part of the water. That was the number one thing that you know. He left the impression So I mean, this is a huge global problem. >>It really is. And our manufacturing operations were global, and we are located in water scarce areas of the world. And so what really became you know, it's a Micron issue to one of our biggest environmental issues that we talked about, and water dot org's has just been a >>leader in this space, and it has been just fabulous to work with on >>really, they have so much passion and dedication towards this. They've been ableto help. 22 million people already. >>All right, so they're lining up for the main stage. Just give us real quick some of the grants that you guys have. >>Last year at this event, we announced our advancing curiosity, and we announced three recipients last year, and since then we have four more. That's U C L. A. All right T, University of Texas at Austin and University of Washington. >>Awesome. That's great. Listen, congratulations. D on all your great work. We really appreciate your ticket sometime in the queue. All right, and thank you for watching her body. We're back with our next guest from Micron inside. 2019 on the Cube, right back.

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host Stu minimun hi I'm Stu minimun and welcome to a special cube conversation here in our Boston area studio and health happy to welcome to the program someone we've known for a long time but actually first time on the program also a Boston area native I believe yes Jim and so it's Jim Sullivan who's the CEO of nwn Jim's thanks so much for joining us let's do it's great to be here watching you guys forever and first time and happy to be here so we've got a lot of shared history we both we overlapped a little bit at a company that some people might remember was EMC before it was the largest acquisition in tech history you've worked for a number of companies we've covered here on the cube XIV actifi oh and the like so tell us first you know nwn it's not a company that you know the vast majority of people are going to know of but you know good-sized company been around for a while Waltham based tell us tell us a little bit about what brought you to nwn thanks to yet nwn is a you know solution service provider been around 10 years hundreds of millions of dollars of revenues 1,300 customers and a lot of really incredible you know platform offering service offerings and so was really excited to be able to kind of get involved with the company and begin to look at we could do for the industry and for customers all right yeah you talk about it you know an area that that's transforming greatly I mean tech in general you know we say that the the only constant in industry is change when you talk about services you talk about platforms that means a lot of things to a lot of people maybe explain a little bit that the spaces that end everyone plays in and where some of the core capability of the company are sure so if you look at as you know this a lot of everything for you know digital transformation is around the end-user experience so we all want to have great access to you know voice video you know clean network the ability to kind of have this great experience to collaborate with customers so India nwn really the core offerings unified communications which has really always been a kind of core of the company the network's underpinning those communications along with a contact center collaboration security and so security really wraps around everything and then those are the core areas where we are but the core IP of the company is the platform that can manage all those environment you know as a self-service function that the customers use or that arts contacts and her team can kind of run okay so when I hear that the solutions that you're talking about the the thing that comes kind of front and center in the industry that I've been hearing about it's the CX it's the customer experience you know what is the ultimate end users how are they interacting with as well as the employees themselves you know if you've got people at the contact centers that are running things how are you making their jobs easier so you know how does that play into you know what you're seeing in the market and how nwn you know delivers offerings in that space so everything's really tied together whether you have a device a a phone system everything's gonna be tied into the network and required really high security so the the management platform that we have allows customers to have that ability to provision in a real secure fashion a device that we can kind of deliver and manage the right phone systems that we can also deliver and manage all tied into a really secure Network and it can be anywhere they want it can be you know private cloud hybrid cloud or hosted cloud is how we deliver it today yeah there's the cloud discussion that's going on right now I was at Enterprise Connect earlier this year and you know everything seemed to be you know cloud enable an AI infused underneath from a customer standpoint you know that they can get a little bit overwhelmed with some of the jargon that's get gets thrown out there so help explain a little bit you know what solutions what is nwn build you know how does it fit in with kind of you know big tech companies that they probably have relationships with and debut and has been part of the channel for many of these products there to talk a little bit about that mix overall we're gonna deliver a solution for the customer in those areas right so in a unified communications area or a network area security so and the solutions going to be required you know some hardware you know a lot of services which is our people and then most importantly this management platform which is going to be the management capability the business analytics the knowledge center that kind of pull off from everybody right so our focus is really delivering the solution delivering it you know kind of a solution as a service so the customer has the ability that it's not outsourcing it's not managed services but we're gonna be running the service but they have the ability to self provision interact with pulling all their own analytics all their own data on their own environment so it's a much more interactive relationship than kind of the old-school managed services of the past you know I I like that term solutions as a service because we've learned the the failings of just pure outsourcing it was like oh can I get my mess for Less well no no you don't want your mess what customers need is they need to be able to deploy something today and as the business changes adjust that and you can't have something that you have to throw over the wall and say oh hey can you do this oh yeah we'll get back to you in six months maybe and here's your new bill and how that changes in the cloud era I need to be able to deploy something today and stay flexible to be able to take advantage of new technologies new innovations as they come along how do your offerings help customers stay current and you know drive that innovation adoption right so a huge part of we talk about this in a lot of industries particularly our old kind of infrastructure of days and that everything becoming more software-defined is is really everywhere or cloud offerings really everywhere and with software these changes are happening so fast so the customer gets an environment that's stable and secure deployed and managed by us but as changes happen our team and our kind of best practices capabilities allows to interact with their end users so you kind of drive the adoption which a lot of time it's more getting and training and making sure the new practices sort of happened because the efficiencies gained are huge that's sort of one and then two is is it's beginning to get adopted you're beginning to kind of roll that out across the entire enterprise so the customer gets that end user experience which it helps with employee retention you know really helps with business ROI and ultimately the investments they made are now being used and they're getting what they want so it might be excellent you know lying quality with great business analytics in a secure environment but it goes back down to you know is the network being utilized all the software capabilities being deployed and managed and really what's the business outcome for the customer so these this world is very much less speeds and feeds or technology or all of that versus okay where's the customer stand today and where do they want to bring the business to and what business outcomes they looking to drive the adoption services you know ensures that they get the business outcomes all right Jim you know what what industries what geographies gives a little bit of kind of the scope and breadth of your team right so it's 1,300 customers more than half the customers are really large enterprises you know companies like eversource the other half of the business is sled state local education so Yale University really big customer state of California we manage over 200,000 endpoints over 400 agencies so really some huge scale but it really maps to a great balance in the business of sled and enterprise accounts okay and you talked about cloud you have some of your own data centers how do you play with some of the public cloud and customer environments what's right what's kind of that mix and what are you yeah so so today customers want to have like I don't think they quite care but they want to have fast deployments really agile environments consistent costs really effective and so for us we able to provide that because we can provide private cloud on-premise we can service any public cloud for these deployments and we also have three data centers where we can provide a cloud solution for them or hybrid clouds lifts and really mapping particularly the enterprise accounts as we know they're beginning to learn like all public clouds little scary you know but if you get into a fireman where you can have really a shop that has you know private clouds that delivers a hybrid cloud environment for them much more flexible much more agile for them it's been a perfect scenario where the predominance of our customers are deployed in a cloud scenario managed by us but in their data centers in our cloud as well yeah right I think a really good point their customers are still sorting out where everything goes and you've got to have flexibility to say okay it's not one or the other it's usually more of an and right in helping customers you know move through what I do in there and for us most of these environments are you know really mission-critical applications that are gonna be rolled out whether it's the voice systems which really kind of backing and the underpinning the whole the whole customer experience it might be device as a service so when we kind of talk about end user experience it starts with really the voice that devices it's got to be really secure which is becomes a kind of a compliance issue and a lot of this is all tied together into the network so the the big differentiator for it end WN is the ability that we can have the management portal that really manages all these five environments together into one seamless into one seamless platform that they can pull the data from okay so talked about you've got team you've got technology you've got really important you've got a lot of good customers seems like you have a good relationship nwn is going through a bit of a transformation here since you've been on board just a few months now I've had a chance to look at the website and the biggest thing for me is I'll tell you from the old one to the new one the new one is simpler I really kind of grasped much faster what any of the wnd does so maybe speak a little bit to you know what nwn of today how that's different from how we might have thought of nwn in the past sure nwn been around 10 years as nwn but they've been acquiring companies and really had has incredible employees great customers really loyal customers and big accounts that were strategic too but as we really went through kind of the assessment of what's really resonating with customers we were able to really focus all the offerings down to these five core offerings that we've been talking about and then really have the right investments around all the IP that we've developed and really wanted to put against those five offerings and then have the customer success teams be able to be organized around that so the company has really focused on where 95% of the business was the ability to really put all the wood behind the arrow you know for those environments and for our customers to really focus and that's about a 50 billion dollar market in the u.s. right so that focus area is a big space big opportunity for growth and a lot of it was in the predominance of our 1,300 customers they buy one or two of these offerings from us and now the ability to really expand that but so many of these customers are so happy we're gonna kind of take it in those industries we're in probably about five core industries to really kind of take it to their peer their peer companies and really expanded in that account-based marketing sort of kind of program okay so five specific offerings we've talked about a couple of them already unified communications as a service of course we talked about contact center we touched on device as a service you talked about some of the devices security and advanced technology solutions maybe start with security you know I think one of the you know you know most important topic being discussed I looking back at my career and you know 10 or 15 years ago security was what I would call top of mind bottom of budget all right and today it is often a board level discussion there are lots of dollars lots of investment lots of concern around security so what piece is the security market does nwn playing you know what we're what's good you know what what do you what are you creating and what are you working with the ecosystem and where do we need to go sure enough space so for unified communications for the 80s you know practice around the supporting network and device as a service our security offerings are for the environment right and a lot of it is where there's a lot of tools deployed but customers you know are really okay once something happens an incident happens they have a tool that identifies something that happens but a lot of the security will be really really mapping those environments that they have a secure platform but Incident Response is really where we're gonna really be doubling down on so something's happened in one of those environments what happened and then how do you respond to that that's going to be the big focus of what nwn it's been doing and kind of what will invest more in its really Incident Response okay great advanced technology solutions talk to us a little bit about that so a lot of the core the core expertise in the company for years has been around the network but then that really expanded with doing you know full you hosted unified communication so the company today can deploy any type of networking solutions for customers along with all the connectivity so the bandwidth you know any type of a next generation networks like 5g so all of that really tied together that you have the network you know the right connectivity to kind of get to the the right performance and then mapping it to the SL A's that have to go with the the offerings of unified communications and devices of service because everything's going to be inter intertwined and you think about any like collaboration technologies I mean how many times have we been in a meeting where a collaboration technologies not really working but the performance is not really there it's not that software it's something that was tied beneath that so nwn can really bridge the two together to have that the right networking capability the right connectivity so you're getting the fast connectivity right away of what really matters to the end user experience which is that collaboration system yeah you know we talked a little bit about innovation you know where where are your customers what's exciting you that's helping your customers move forward and you know where are those areas that were still struggling a little bit you know III think back you know I worked in the you know Telecom Unified Communication space you know back in the late 90s and you know by now we were supposed to have the flying cars with the ubiquitous video everywhere and well FaceTime you know and some some things have us there a little bit sure I use my you know my webcam way more than I did five or ten years ago but yeah maybe speak a little bit where were having success and where if we still need to go number one thing for me that I learned of one of the most unique assets that NW and has is the business analytics and data capability right so a lot of these environments have been deployed we've got all these multiple different vironment but what I learned of the nwn capability is we have every piece of data of all those different environments in every customer in every customer environment so we have the ability now with our portal and they've had the ability to do this it's really any type of function that the customer wants to learn more about in kind of an automated fashion that they can self provision this data themselves we have the data so it could be billing capabilities of really what what groups are being built it could be any type of compliance so what type of calls are being made and who's doing calls any type of productivity for call centers of what capabilities we have so I think the the the biggest thing to answer your question is one the nwn capability is all the business data that we have that maps across multiple industries to deliver best practices but people have been to plot deploying networks deploying devices deploying phone systems but never really having the intelligence of what you're gonna do with that data to drive the business forward and so one it's like got to have the end user experience be like that's like table stakes where the end user experience is great but now how the business use the data of how all those systems are working together to really bring forward like okay what business decisions do we make to move forward in terms of what's working what's not working and comes back to driving the right business outcomes alright so a lot a lot of effort in the last few months yeah focus and execution doing the relaunch here let's look forward a little bit Jim as you know six or twelve months from now as we look back what are some of the key KP at KP is how for those of us the outside do we know that nwn is executing and meeting you know where you want the company to go its 100% about customer satisfaction right so it's the as we continue to expand the offerings inside customers and then add new customers will be you know solely how we're going to manage the business and that's really where it's as customers do upgrades with us the the predominance of our customers is long-term contracts so as customers continue to do renewals and add new offerings and kind of new capabilities that we bring to the table and as they tell their peer companies which is people are really excited about being references for us then we'll continue to add more companies into the mix and more more customers and grow the 1302 mm great and you know for for potential customers out there there any of the kind of key things that you would call out that they said oh I've got this issue or I'm looking to do this kind of project I want to make sure to have nwn on my short list I see a couple areas right it's it's everyone is it's a 50 billion dollar market so everyone is dealing with unified communications issues right in terms of what decisions are gonna make were an expert in that space the device is a service you know really like we manage two hundred thousand endpoints with the state of California so that's a device of the service is really a space that not a lot of people are in a lot of people doing devices but really as an end end service not really you know strong you know kind of capability and then the security requirements are for everybody so I think for these solutions than to have the right service people the right network expertise so that that five areas is kind of the core space and I think the biggest thing that I would say to customers is everything's intertwined right so it's like you can have you know one person to talk about one if you don't really tie it all together that's where the challenges and the problems usually kind of come from and we're also really sizable Ike the companies you know you know a lot a lot of large customers but the companies hundreds of millions of dollars with a lot of forty's over the last 10 years yeah so Jim last thing talk about the team in the culture you know talk about what you you want to build on what NW always has and you know are you doing some hiring either here locally in the Boston area or you know in other geographic areas sure so companies Nate you know national company so we'll be hiring sales reps solution engineers nationally and really kind of continue to scale that out the service desk function that we have and really the customer success team is continuing to expand and really supporting the growth of the business and really kind of driving it so those are really the key areas the rest of the company that people are the people and the and the culture of the company are amazing the passion commitment to customer success people have been here a long time and so they have a lot of experience and a lot of kind of patch with the company so a lot of the changes we made all came from within side right so everyone really rallied to be like hey here the things were good at then we want to get great at and that sort of been kind of the big focus and we have really strong presence in in in the Carolinas all over the Northeast California Texas and so we're gonna really look to kind of connect all those geographies together to have one national you know kind of powerhouse player across the country all right Jim Sullivan thank you so much for the updates congratulations on the progress and look forward to watching the continued growth of NW thank great to be here all right and lots more coverage here as always on the cube net on to minimun and thank you for watching the Q

>> Announcer: Live from Washington D.C. it's The Cube covering AWS Public Sector Summit, brought to you by Amazon Web Services. >> Welcome back everyone to The Cube's live coverage of the AWS Public Sector summit here in our nation's capitol, I'm your host Rebecca Knight. Co-hosting alongside analyst John Furrier. We are welcoming today Troy Bertram. He is the GM Public Business Development Worldwide Public Sector at AWS. Thanks so much for coming on The Cube, Troy >> Thanks for having me Rebecca >> Rebecca: A first timer. >> It is the first time. >> Rebecca: Welcome. >> Yes, thank you John, thank you Rebecca. >> Let's talk about your partner organization. Why don't you let our viewers know how it's structured, what its mission is, how it works. >> Yes, certainly. Our public sector partner teams work with our partners around the world that really support the mission requirements of government, education, and non-profits. Our partners are part of the large Amazon partner network, so 35,000 plus partners, but really our customers choose, Whether it's technology partners that have really focused their SaaS, PaaS, ISV solutions on government customers and worked through accreditations and certifications, or it's the consulting partners that go to market and own the prime contract vehicles. Contracts are how our customers buy in public sector. What we've done is really focused our teams from start-ups, and venture capitalists, and incubators, through technology, ISVs, PaaS and SaaS partners to our large consulting partners; global consulting partners, but also really helping curate those consulting partners that meet socioeconomic requirements. Often times governments have laws, regulations to buy small woman owned 8(a), service disabled veteran, as veteran, one of my near and dear partner subset to me, and we work with them to help navigate through and develop programs to work through the APN, and often times it's a partner to partner activity of a consulting partner working with a specialized ISV technology solution that can meet a customer's mission requirements. >> What's interesting about the cloud, we've been talking about our intro this morning is the agility and government's now seeing it benefits, and it's not just and aha moment anymore cloud is really, it's driving a lot of change. That's been lifting up a lot of your partner profiles. You have start-ups to large entities all playing together because the requirements my change based upon either the agency or the public sector entity. >> Yes. >> Have unique needs, so you have a broad range of partners. How do you guys nurture that? That's good diversity. You have nice solution set from tech to business. How do you guys nurture that? What's some of the challenges and opportunities you guys are seeing with the growth. >> Cloud is really allowed a reset for many of our partners. Whether you are born in the cloud company, that doesn't necessarily have a long legacy, and haven't built an entire infrastructure, and you don't have an infrastructure of people, but also don't have technology debt that you've been burdened with because of your prior operating models. It's nurturing that born in the cloud company that maybe a services oriented migration partner that's focused on moving our customers applications and workloads, or it's nurturing the technology and helping them build, or it's a refactor and a legacy on premise solution or those solution providers that have traditionally operated in an on-prem environment. Helping them train, certify, and really build a new practice. >> And it's exciting too. You got the ecosystem kind of approach where, you know a thousand flowers can bloom. I've got to ask you, what do you see sprouting up? What's growing most? What is some of the trends that you see in the partner ecosystem? What's growing fast? What's the demand? What's the hot area? >> The real demand is for people with skill sets. In our business, skill sets also often include security clearances, and a knowledge of the working environment that they're migrating from. We're spending an inordinate amount training and educating. Also, our partner selling community of understanding the dynamics of how to go to market, and the contract vehicles, and how to navigate. The opportunities are really immense. It's nurturing those thousand flowers, and it is a challenge for many of us. How do we nurture those thousand flowers simultaneously? >> Are you finding the right people? A big theme on The Cube here is the skills gap. I just saw a Deloitte survey. 60% of executives, and these are executives, they're not in the public sector, said a skills gap hindered their AI initiatives and hindering their cloud computing initiatives. What are you seeing? What are you hearing from the people you're talking to? >> There's a thirst for both knowledge and training, but there's also, from the executive side, we have a need to fill. There's an abundance of roles, and all of us working together. One of our initiatives is even the job boards that we're working with our educate team and Ken Eisner a peer that leads that is, we're helping our partners promote their open roles. Allowing our partners to look for and curate the same talent that Amazon is helping train and develop because when our partners can find amazing talent, our customers win. It benefits AWS and the partner ecosystem. >> Education's huge. You got to have the ongoing digital course ware. Is that a top priority for you? What are some of your top goals for this year in your plan? >> When it comes to education, top goal is training many of our new partners through our emerging partner team. Many of the new partners have a commercial practice. We're also looking at those partners and actively recruiting those partners that have built a commercial practice that are looking to enter government. Whether it's our distributors or our resellers that own the prime contract vehicles, we're doing partner to partner activities. We call it partner speed dating. It's contract vehicles that exist across state and local government, US federal, or in the international community for those ISVs that want to enter new market regions is pairing with those existing local companies that have contract vehicles and then helping train and educate on the nuances of public sector. >> We were talking with General Keith Alexander and retired General Yesthidae came on and I asked them directly, if you could a magic wand, I think I said, something along the lines of if you had a magic wand, what would you do to change the government? It could go faster. He said the technology check we're doing very well, it's moving along great, it's the procurement process. It's just too long. He mentioned contracts. This is really the key point we keep hearing. The red tape. What's the update there? I'm sure partners aren't wanting more red tape. They want to cut through it, to your point. >> No. It's really an education process. When I started at Amazon over six and a half years ago, my first role was to stand up, and it still is the core of my role, I have individuals in 22 different countries around the world, and we're helping governments and VR partners through the procurement process. We did this past week in my home state of Minnesota, our 10,000th RFX, so we consider an FRP, FRI, an RFQ a tender, I need to buy, I want to buy something. We responded to 10,000 of those in six years and two months. That's an abundance of contract that ultimately, many of them are task orders and IDIQs and GWAX. There's an abundance of pathways as General Alexander stated for customers to buy the technology. Now it's educating the contracting officers, the COs, the KOs, around the world on the existing pathways and how to leverage them. We still see old procurement methodologies being applied to the cloud, and it does slow down the end customer's mission requirements. >> And the path to value. >> Yes, the path to value. Exactly. They want to move and move fast and contracts is how we buy, but it's also what slows us down. >> You know, you're with Amazon six years plus, so you know this, so the speeds of value's been the key thing for the cloud. As you look at success now with Amazon public sector, not only in the US, but abroad and internationally, you got massive tailwinds on the success. The growth is phenomenal. How does that feel? What's some observations? What's some learnings that you can take away from the past few years and where's it going? >> It feels like it's day one. It does feel like it's day one. There are tailwinds, but there's still an abundance of customer requirements, and they're evolving, and they're more complex. I personally really like my career's been public sector. Solving the mission requirements, whether it's helping a forward deployed airman, soldier, really keeping them at the cutting edge of technology, and out of harms way, or our first responders; some of the new product demonstrations that we've seen of evolving technology that's helping a firefighter see from an aerial drone vehicle. What does it look like on the other side of this building, and how can I now communicate across different agencies? Is phenomenal. In my home state, where Army Futures Command, I live in Austin, Texas. Army Futures Command is working with the state of Texas as well as the University of Texas to really collaborate as we've never seen before. The barriers of emerging technology to legacy government, to ministries, and health defenses around the world, ministries of defense, and health agencies around the world. >> The data, the scale of Amazon cloud is going to to make that possible. Ground Station's a great example of how that's growing like a weed. The DOD has got a great charter around using agility and AI. >> Collaboration, which is so critical too, as you said. >> It is, and our VM Ware partnership with VM Ware on AWS can really help, and that's a partner play. That's partners helping migrate using the co-developed technology to really move and move faster. Use those existing apps and vacate those data centers. >> Well, thanks for coming on The Cube. Got to be a quick plug, plug the organization, share with the audience, what you're looking for, and update on the partner network. Give a quick plug for your group. >> What we're really looking for is, we've got 105 different competency partners that have really invested in their government, their education, their non-profit competency, and we want to help. I personally want to help them promote their business, and what the opportunity is to connect to either other partners or to government mission requirements. Really welcome the opportunity, John, to come on and look forward to seeing my partners on The Cube in the future. Thank you. >> Well, Troy Bertram, you are now a Cube alum, >> A Cube alum >> Thank you. (panel laughing) >> Thank you. >> I'm Rebecca Knight for John Furrier, you are watching The Cube, stay tuned for more AWS Public Sector Summit.