>> Narrator: "theCUBE's" live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (intro music) >> Good afternoon, everyone. Welcome back to "theCUBE's" day three coverage of MWC23. Lisa Martin here in Spain, Barcelona, Spain with Dave Nicholson. We're going to have a really interesting conversation next. We're going to really dig into MWC, it's history, where it's going, some of the controversy here. Please welcome our guests. We have Jim Harris, International Best Selling Author of "Blindsided." And Carolina Milanese is here, President and Principle Analyst of creative strategies. Welcome to "theCUBE" guys. Thank you. >> Thanks. So great to be here. >> So this is day three. 80,000 people or so. You guys have a a lot of history up at this event. Caroline, I want to start with you. Talk a little bit about that. This obviously the biggest one in, in quite a few years. People are ready to be back, but there's been some, a lot of news here, but some controversy going on. Give us the history, and your perspective on some of the news that's coming out from this week's event. >> It feels like a very different show. I don't know if I would say growing up show, because we are still talking about networks and mobility, but there's so much more now around what the networks actually empower, versus the network themselves. And a little bit of maybe that's where some of the controversy is coming from, carriers still trying to find their identity, right, of, of what their role is in all there is to do with a connected world. I go back a long way. I go back to when Mobile World Congress was called, was actually called GSM, and it was in Khan. So, you know, we went from France to Spain. But just looking at the last full Mobile World Congress here in Barcelona, in pre-pandemic to now, very different show. We went from a show that was very much focused on mobility and smartphones, to a show that was all about cars. You know, we had cars everywhere, 'cause we were talking about smart cities and connected cars, to now a show this year that is very much focused on B2B. And so a lot of companies that are here to either work with the carriers, or also talk about sustainability for instance, or enable what is the next future evolution of computing with XR and VR. >> So Jim, talk to us a little bit about your background. You, I was doing a little sleuthing on you. You're really focusing on disruptive innovation. We talk about disruption a lot in different industries. We're seeing a lot of disruption in telco. We're seeing a lot of frenemies going on. Give us your thoughts about what you're seeing at this year's event. >> Well, there's some really exciting things. I listened to the keynote from Orange's CEO, and she was complaining that 55% of the traffic on her network is from five companies. And then the CEO of Deutsche Telecom got up, and he was complaining that 60% of the traffic on his network is from six entities. So do you think they coordinated pre, pre-show? But really what they're saying is, these OTT, you know, Netflix and YouTube, they should be paying us for access. Now, this is killer funny. The front page today of the show, "Daily," the CO-CEO of Netflix says, "Hey, we make less profit than the telcos, "so you should be paying us, "not the other way around." You know, we spend half of the money we make just on developing content. So, this is really interesting. The orange CEO said, "We're not challenging net neutrality. "We don't want more taxes." But boom. So this is disruptive. Huge pressure. 67% of all mobile traffic is video, right? So it's a big hog bandwidth wise. So how are they going to do this? Now, I look at it, and the business model for the, the telcos, is really selling sim cards and smartphones. But for every dollar of revenue there, there's five plus dollars in apps, and consulting and everything else. So really, but look at how they're structured. They can't, you know, take somebody who talks to the public and sells sim cards, and turn 'em in, turn 'em in to an app developer. So how are they going to square this circle? So I see some, they're being disrupted because they're sticking to what they've historically done. >> But it's interesting because at the end of the day, the conversation that we are having right now is the conversation that we had 10 years ago, where carriers don't want to just be a dumb pipe, right? And that's what they are now returning to. They tried to be media as well, but that didn't work out for most carriers, right? It is a little bit better in the US. We've seen, you know, some success there. But, but here has been more difficult. And I think that's the, the concern, that even for the next, you know, evolution, that's the, their role. >> So how do they, how do they balance this dumb pipe idea, with the fact that if you make the toll high enough, being a dumb pipe is actually a pretty good job. You know, sit back, collect check, go to the beach, right? So where, where, where, where does this end up? >> Well, I think what's going to happen is, if you see five to 15 X the revenue on top of a pipe, you know, the hyperscalers are going to start going after the business. The consulting companies like PWC, McKinsey, the app developers, they're... So how do you engage those communities as a telco to get more revenue? I think this is a question that they really need to look at. But we tend to stick within our existing business model. I'll just give you one stat that blows me away. Uber is worth more than every taxi cab company in North America added together. And so the taxi industry owns billions in assets in cars and limousines. Uber doesn't own a single vehicle. So having a widely distributed app, is a huge multiplier on valuation. And I look to a company like Safari in Kenya, which developed M-Pesa, which Pesa means mo, it's mobile money in Swahili. And 25% of the country's GDP is facilitated by M-Pesa. And that's not even on smartphones. They're feature phones, Nokia phones. I call them dumb phones, but Nokia would call them "feature phones." >> Yeah. >> So think about that. Like 25, now transactions are very small, and the cut is tiny. But when you're facilitating 25% of a country's GDP, >> Yeah. >> Tiny, over billions of transactions is huge. But that's not the way telcos have historically thought or worked. And so M-Pesa and Safari shows the way forward. What do you think on that? >> I, I think that the experience, and what they can layer on top from a services perspective, especially in the private sector, is also important. I don't, I never believe that a carrier, given how they operate, is the best media company in the world, right? It is a very different world. But I do think that there's opportunity, first of all, to, to actually tell their story in a different way. If you're thinking about everything that a network actually empowers, there's a, there's a lot there. There's a lot that is good for us as, as society. There's a lot that is good for business. What can they do to start talking about differently about their services, and then layer on top of what they offer? A better way to actually bring together private and public network. It's not all about cellular, wifi and cellular coming together. We're talking a lot about satellite here as well. So, there's definitely more there about quality of service. Is, is there though, almost a biological inevitability that prevents companies from being able to navigate that divide? >> Hmm. >> Look at, look at when, when, when we went from high definition 720P, very exciting, 1080P, 4K. Everybody ran out and got a 4K TV. Well where was the, where was the best 4K content coming from? It wasn't, it wasn't the networks, it wasn't your cable operator, it was YouTube. It was YouTube. If you had suggested that 10 years before, that that would happen, people would think that you were crazy. Is it possible for folks who are now leading their companies, getting up on stage, and daring to say, "This content's coming over, "and I want to charge you more "for using my pipes." It's like, "Really? Is that your vision? "That's the vision that you want to share with us here?" I hear the sound of dead people walking- (laughing) when I hear comments like that. And so, you know, my students at Wharton in the CTO program, who are constantly looking at this concept of disruption, would hear that and go, "Ooh, gee, did the board hear what that person said?" I, you know, am I being too critical of people who could crush me like a bug? (laughing) >> I mean, it's better that they ask the people with money than not consumers to pay, right? 'Cause we've been through a phase where the carriers were actually asking for more money depending on critical things. Like for instance, if you're doing business email, then were going to charge you more than if you were a consumer. Or if you were watching video, they would charge you more for that. Then they understood that a consumer would walk away and go somewhere else. So they stopped doing that. But to your point, I think, and, and very much to what you focus from a disruption perspective, look at what Chat GTP and what Microsoft has been doing. Not much talk about this here at the show, which is interesting, but the idea that now as a consumer, I can ask new Bing to get me the 10 best restaurants in Barcelona, and I no longer go to Yelp, or all the other businesses where I was going to before, to get their recommendation, what happens to them? You're, you're moving away, and you're taking eyeballs away from those websites. And, and I think that, that you know, your point is exactly right. That it's, it's about how, from a revenue perspective, you are spending a lot of money to facilitate somebody else, and what's in it for you? >> Yeah. And to be clear, consumers pay for everything. >> Always. Always. (laughs) >> Taxpayers and consumers always pay for everything. So there is no, "Well, we're going to make them pay, so you don't have to pay." >> And if you are not paying, you are the product. Exactly. >> Yes. (laughing) >> Carolina, talk a little bit about what you're seeing at the event from some of the infrastructure players, the hyperscalers, obviously a lot of enterprise focus here at this event. What are some of the things that you're seeing? Are you impressed with, with their focus in telco, their focus to partner, build an ecosystem? What are you seeing? >> I'm seeing also talk about sustainability, and enabling telco to be more sustainable. You know, there, there's a couple of things that are a little bit different from the US where I live, which is that telcos in Europe, have put money into sustainability through bonds. And so they use the money that they then get from the bonds that they create, to, to supply or to fuel their innovation in sustainability. And so there's a dollar amount on sustainability. There's also an opportunity obviously from a growth perspective. And there's a risk mitigation, right? Especially in Europe, more and more you're going to be evaluated based on how sustainable you are. So there are a lot of companies here, if you're thinking about the Ciscos of the world. Dell, IBM all talking about sustainability and how to help carriers measure, and then obviously be more sustainable with their consumption and, and power. >> Going to be interesting to see where that goes over the years, as we talk to, every company we talk to at whatever show, has an ESG sustainability initiative, and only, well, many of them only want to work with other companies who have the same types of initiative. So a lot of, great that there's focus on sustainability, but hopefully we'll see more action down the road. Wanted to ask you about your book, "Blind," the name is interesting, "Blindsided." >> Well, I just want to tag on to this. >> Sure. >> One of the most exciting things for me is fast charging technology. And Shalmie, cell phone, or a smartphone maker from China, just announced yesterday, a smartphone that charges from 0 to 100% in five minutes. Now this is using GAN FEST technology. And the leader in the market is a company called Navitas. And this has profound implications. You know, it starts with the smartphone, right? But then it moves to the laptops. And then it'll move to EV's. So, as we electrify the $10 trillion a year transportation industry, there's a huge opportunity. People want charging faster. There's also a sustainability story that, to Carolina's point, that it uses less electricity. So, if we electrify the grid in order to support transportation, like the Tesla Semi's coming out, there are huge demands over a period. We need energy efficiency technologies, like this GAN FEST technology. So to me, this is humongous. And it, we only see it here in the show, in Shalmie, saying, "Five minutes." And everybody, the consumers go, "Oh, that's cool." But let's look at the bigger story, which is electrifying transportation globally. And this is going to be big. >> Yeah. And, and to, and to double click on that a little bit, to be clear, when we talk about fast charging today, typically it's taking the battery from a, not a zero state of charge, but a relatively low state of charge to 80%. >> Yep. >> Then it tapers off dramatically. And that translates into less range in an EV, less usable time on any other device, and there's that whole linkage between the power in, and the battery's ability to be charged, and how much is usable. And from a sustainability perspective, we are going to have an avalanche of batteries going into secondary use cases over time. >> They don't get tossed into landfills contrary to what people might think. >> Yep. >> In fact, they are used in a variety of ways after their primary lifespan. But that, that is, that in and of itself is a revolutionary thing. I'm interested in each of your thoughts on the China factor. Glaringly absent here, from my perspective, as sort of an Apple fanboy, where are they? Why aren't they talking about their... They must, they must feel like, "Well we just don't need to." >> We don't need to. We just don't need to. >> Absolutely. >> And then you walk around and you see these, these company names that are often anglicized, and you don't necessarily immediately associate them with China, but it's like, "Wait a minute, "that looks better than what I have, "and I'm not allowed to have access to that thing." What happens in the future there geopolitically? >> It's a pretty big question for- >> Its is. >> For a short little tech show. (Caroline laughs) But what happens as we move forward? When is the entire world going to be able to leverage in a secure way, some of the stuff that's coming out of, if they're not the largest economy in the world yet, they shortly will be. >> What's the story there? >> Well, it's interesting that you mentioned First Apple that has never had a presence at Mobile World Congress. And fun enough, I'm part of the GSMA judges for the GLOMO Awards, and last night I gave out Best Mobile Phone for last year, and it was to the iPhone4 Team Pro. and best disruptive technology, which was for the satellite function feature on, on the new iPhone. So, Apple might not be here, but they are. >> Okay. >> And, and so that's the first thing. And they are as far as being top of mind to every competitor in the smartphone market still. So a lot of the things that, even from a design perspective that you see on some of the Chinese brands, really remind you of, of Apple. What is interesting for me, is how there wouldn't be, with the exception of Samsung and Motorola, there's no one else here that is non-Chinese from a smartphone point of view. So that's in itself, is something that changed dramatically over the years, especially for somebody like me that still remember Nokia being the number one in the market. >> Huh. >> So. >> Guys, we could continue this conversation. We are unfortunately out of time. But thank you so much for joining Dave and me, talking about your perspectives on the event, the industry, the disruptive forces. It's going to be really interesting to see where it goes. 'Cause at the end of the day, it's the consumers that just want to make sure I can connect wherever I am 24 by seven, and it just needs to work. Thank you so much for your insights. >> Thank you. >> Lisa, it's been great. Dave, great. It's a pleasure. >> Our pleasure. For our guests, and for Dave Nicholson, I'm Lisa Martin. You're watching, "theCUBE," the leader in live and emerging tech coverage coming to you day three of our coverage of MWC 23. Stick around. Our next guest joins us momentarily. (outro music)

>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by >>Hello from Las Vegas, live at the Bellagio. Lisa Martin, with Dave Volante. We are at UI path forward for, like I said, in Las Vegas. So great to be in person, sitting at an anchor desk with a co-anchor. And I guess we're going to be talking about deploying new technologies and a large global enterprise. Nikki Harris is here. Manage your application, performing platform engineering services at Chevron Vicky. Welcome to the program. Hey, thank >>You. Happy to be >>Here. So isn't it great to be we're outdoors. Nice that everyone's nice and safe, but great to be back at an in-person event where so many hallway conversations can spark more innovation. That's one of the things I think a lot of us have been missing in the last 18 months. You've been with Chevron almost 15 years, but this is, we're talking about 142 year old organization. Talk to me about the evolution of it that you've seen. >>Very happy to do that. Um, a lot of, uh, I would say the greatest jump forward we saw in cloud and we started our cloud transformation before digital transformation came along. Uh, but it was the, really the thing that enabled us to, uh, be ready, I would say for the extra value, the extra push. And so we were so happy to be well positioned. So we started our cloud journey in 2017 and, uh, between 2018 and 19, because of the investments in automation, it just took off and today we're still receiving the benefits of that. Um, but prior to that, it took a little bit longer. Uh, also we had an agile transformation, which was very helpful because we can't really afford to move at waterfall speed anymore. Um, and so cloud and agile really helped boost that and get us started. >>So whenever we get a practitioner on, we have a million questions. So, so can we start with your role? Are you in it, that's where you're in that organization or >>I am in it. So I'm a product line manager. We support really the core for software engineers and citizen developers. So on the software engineering side, CICB pipeline, dev ops tooling, code frameworks, all of that to make our software engineers more productive and on the citizen development side, same philosophy, we want to make them more productive, not worry about how do I do it, just how to apply their business logic. So we support the citizen development programs and the underlying platforms. >>So they gave, when you talked about cloud in 2017, are you talking about infrastructure as a service platform, as a service SAS, all of the above, cause cause you have to do, I'm sure you were doing SAS before then, but how do you think about cloud? >>So that's a great question. Yes. We were always doing SAS and we continue to do SAS. Uh, so, and Chevron was one of the earlier adopters of UI path for cloud. We do want to be cloud first, always, always, always. And we are trying to really reduce and restrict our on-prem footprint. Um, but the automation we started in kind of 20 17, 20 18 is, um, I would call it infrastructure as code. Uh, so deploying everything with code, um, the same way all the time, uh, which was partly a technical shift, but also a really big cultural shift that instead of having people doing the same task, you know, 400 different ways, which is hard to sustain, it's hard to troubleshoot. Uh, so we took the pain in, in building that and there's a lot of pain in, in the transformation itself, but the upside when you're finished is amazing. >>Yeah. So that's what you just answered. My next question, which was what is the catalyst? It was seeing the clouds potential for programmable infrastructure. And that sounds like it was a game changer. >>It was a huge game changer. And that really, uh, on the software engineering side, the whole way we do infrastructure, the way we program everything. Uh, but we also found we're not touching part of the organization with that transformation. And that's where the citizen development programs and RPA comes in is, you know, Hey, we're really proud of ourselves. We did so well, but how do we get to the edge, uh, where we haven't been able to have the same impact with that automation >>For an organization that I mentioned 142 years young will say, I guess you could say old for an organization young for a person where in, in terms of the cultural change, that's hard to, to manifest across such a historic history institution. Talk to me about the appetite for automation. You said you guys started doing automation, bringing it into the organization and in the last five years or so, what's been the appetite across different lines of business to embrace it, to see it as an advantage rather than taking jobs away. >>Uh, so there's never appetite for automation on its own because you're changing someone's process. Um, but what there is appetite for is the results. Uh, and also, uh, we went through a large organizational transformation. So in addition to value, um, you know, bottom line cost savings, we have people who are just improving their, their workflow for themselves. And so there's also a sense of empowerment for them. So I would say the empowerment and then the results are much bigger drivers. And then you say, oh, if you want that, yes, by the way, this is how we get that. But it's not, you know, automation for automation sake. Uh, but people understand, they understand now the value of it and they, the more they learn, they understand that, um, doing one process 25 ways, it's not a way to run your business, >>Right. How to actually drive this outcomes that they're looking for. >>So how did it start? When did it start in? It was an it led initiative or was it a department? >>It led, >>Yes. Okay. And so, so focused on the it department. So you automating certain tasks within it or, or not necessarily >>Necessarily. So, um, it led, but as the foundation for all the business units. So again, we focus on the core, but we also focus on enablement. So anybody who's a builder maker, developer out there in the business units, we just want to make their job easier, better, faster, um, just for the business logic. So then we'd bring them in and say, here's how you do it. Um, but they bring the best ideas, right? They know their business processes. I don't know their business processes. If I sat down and said, here's where automation value is, um, we wouldn't be doing so well. They know where it is. Uh, we just give them the tools to, to find that value. And you know, it's extraordinary how they find it. If there's a lot of manual processes out there, >>A common story, when you talk to UI path, customers, that'll start maybe one person in a department and then people looking over her shoulder going, oh, I want some of that. And then it explodes. It sounds like you were taking a much more whole house approach. >>We are taking a whole house approach, but we did start early with POC. Uh, and so, and then those proved their value pretty easily and pretty quickly. And so then it was a determination of, Hey, we would like to do something bigger here than just leave this technology out there. We're just leaving all this value on the table. We're leaving all this skill sets, all this passion, all this enthusiasm in our citizen community. We don't think we can transform as a corporation. If we leave that energy motivation skill on the table >>And some color to the ROI. Have you said to POC, you're a good, quick hit, obviously. Could you give us some details on that? What can you tell us? >>What can I tell you? Okay, well, so, um, from when we started the program three years, I think we're showing about $6 million of return. Um, we, we see the value just in time savings like everybody else does. And we have, so that's with about, um, 300 automations, six over 600,000 hours I think saved. Uh, but first year it's just so easy. You can see it. It's not hard to calculate it, the hour saving, very simple calculation. So anybody who's concerned about ROI, it's so simple, it's so easy. You should be able to find it in your first year if you're not finding it in your first year. Um, I mean, obviously it grows, but if you're not finding some return in the first year, I would say, you know, take a look at what you need to adjust because it's not that hard >>CFO. Sorry. One more question. If I may, and your CFO saw that, okay. Time-savings essentially was the business result, but it wasn't necessarily it, was it hard or were they, did your CFO say, ah, that's kind of soft dollars or is it >>Both hard and soft? So, and yeah, we would never put a dollar sign next to something that doesn't hit the income statement. So I'm very careful about that. Right. Um, but yeah, it's both because some times, um, somebody actually changed their group first and they're feeling the process pain after. And so the healing of automating something. So the, just the two people can do it. Uh, we've seen that use case as well. It's harder to capture any savings because it's not really savings there, but it's, it's um, more of a job satisfaction. So there's a lot of soft benefits that go with it, but we don't usually, you know, commit, turn that into dollars. That's not very valuable. Yeah. >>Use those employee Mo employees that are far more productive are eventually helping the customers be more productive as well. I think they're directly linked. Well, you said you found ROI quickly and that's something that you iPad says about itself that customers are generally achieving an ROI of a break even within months alone. So when you talk to other professionals in oil and gas, how do you talk to them about automation being really a critical driver of that business's success and transformation? >>Uh, I think in large enterprises, whether they're in our sector or not, some of them just struggle with the sheer scale, it's almost like, where do I start? So they do see the value. Uh, but it's more about how do I, how do I start this thing? How do I scale this thing? How do I structure a program? Um, I have not found anyone that says, I don't believe the value proposition again, it's pretty easy to do. >>And the RPA POC started after cloud. Right. So it was, am I right about that? It was 18, 19 timeframe. >>Uh, I would say actually starting around the same time were done in, in 2017. So yeah. >>And so, uh, was there anything specific in your industry that you targeted? I mean, you obviously wanted to hit the high value items first. Was there anything particular there? >>Um, that's a really good question. I think we, our journey looks like other companies kind of, they start with the back office. Those are the easiest processes to, for people to understand. And just in terms of, you know, where do I have a heavy manual load? Uh, so some of our first work was with finance in currency conversion. So pretty, pretty manual intensive for a global company. Pretty big deal, lots of immediate value. Uh, but if you think of, let's talk about Wells. So, you know, we have systems for mapping, Wells drilling, Wells, uh, you'd be surprised some of those systems look kind of like your ERP. They have kind of the same challenges. So, um, as we extend outside of traditional kind of HR finance audit practices into the rest of our business, the use cases are similar. Um, I've got disparate documents. I have systems that don't talk to each other. Well, I have somebody who S and we have a lot of partners. So if you're in a project with five partners and everybody's producing a different type of document or something, how do you make some sense out of that? Uh, so use cases like that, um, we're finding in our upstream and downstream businesses also, >>And you did an RFP at the time, wrote a bunch of vendors and ran them through the cycles or >>Comparisons yeah. Early on >>While UI path, what was it about >>Strong user experience? So, uh, because this is primarily citizen enabled and so that feedback, Hey, could I learn this quickly? Was it easy to use? Those were really the most important things in selection. I mean, we always look at costs that's important too. Um, but also a company's position. So their ability to scale and grow. Um, there's a lot of people in this market, uh, because of the interest in automation. Uh, so part of it is also understanding the strength of the company behind as well. >>One of the things that was mentioned in the keynote this morning, I think it was a stat from Gartner that in 2016, or was about 2% of, um, automateable processes were automated fast forward. Now it's about 25%. There's still a tremendous amount of potential for organizations and any industry to deploy automation. You've said, you've got about 300 plus automation so far. What are some of the things that are coming next that you can see, >>Sure. What is our upside, or where do we stop or our growth taper? Um, I don't think we know, uh, we get so much from our user community in terms of what can we do now? Um, there are so empowered, so I wouldn't want to set limits on ourselves in terms of what we can do. Uh, but certainly we're looking at, um, text analytics, really, how do we manage that document? How do we extract that data, use models to get that into our data lake? Uh, but there's still always the work of finding still that last mile of process. There's many parts of our business still untouched. And so we don't, we don't let, or we don't want to let up on that. That's still important to go after all of that and keep the programs going >>W Chevron huge company. And you've got probably one of everything that's ever been invented in technology. We're seeing a trend where a lot of these, these software companies are embedding RPA into their platforms. You see it with the ERP vendors, uh, uh, acquisitions being made for service management, you know, big cloud guys ha have, uh, you know, on and on and on. And, and so how do you think about those sort of vertically integrated stacks versus what you're doing with UI path? >>So for me, I think of them the same as a code extension. So, because that was more popular a few years ago on those big platforms and you're right, we have one of everything. Um, but it's important to when you think of investment and ROI, uh, where do we actually spend money? It's in maintaining the capability, keeping the programs, doing the training, that's an investment. And so when someone comes to me and says, can you support some other tool? Um, I usually say maybe not, is there a business case for that because we want to be able to deploy to the whole enterprise, um, that isn't to say that somebody who's got a workflow that stays within that platform, that that might be inappropriate use for them, but a very sure it's not an appropriate use to extend it out of that platform somewhere else. >>Uh, and so we draw the line really, what do we, enterprise automation. We want to be very careful about the tools we use for that. And, and the reason for that is not just security, reliability, and the ability to scale those programs. Because when someone calls me and says, my stuff doesn't scale, it's like ours does. Um, and so, but the org capability investment is also it's, it's not small. Uh, and so if you've got to believe in this, you have to keep feeding it. You have to keep training new people, bringing them on. Uh, and so you can't really do that across 12 platforms, right? >>You're creating your own flywheel and that's how you can accelerate ROI. Right? >>Correct. Although, you know, the citizen developers are driving the wheel for sure. >>You, as in Chevron mean not Vicki, Inc. >>Vicky, thank you so much. We are out of time, but thanks for stopping by talking to us about automation in a large global enterprise at Chevron. I won't look at Chevron at the same again. Now I know how forward-thinking they are and how much they are embracing technology. We appreciate your time. >>It's been my pleasure. Thank you both. >>All right. For Dave Volante and Lisa Martin, we live at the Bellagio in Las Vegas UI path forward for we'll be right back.

(upbeat music) >> From around the globe, it's theCUBE. With digital coverage of Postgres Vision 2021 brought to you by EDB. >> Well, good day, everybody. John Walls here on theCUBE. We continue our coverage here at Postgres Vision in 2021. Talking today with Andy Harris, who is the Chief Technology Officer at Osirium, a leader in the Privileged Access Management Space, and Andy, good day to you. Thanks for joining us here on theCUBE. >> Good morning to you and good afternoon, yes. >> That's right. Joining us from overseas over in England, we're on this side of the big pond, but nonetheless, we're joined by the power of Zoom. So again, thanks for the time. Andy, for those who aren't familiar who are watching about Osirium, share a little bit about your various service levels of what you provide, the kind of solutions you provide, and how you've achieved a great success in this space. >> Okay. I know these things, mine will be boring. So I'll just put a little slide up now, which is the minimum I think I can get away with which is that we're all about managing privilege. So that's privileged at the endpoint, Privileged Access Management, and Privileged Process Automation. So wherever a CIS admin has to do something on a machine that needs privilege, we like to be involved. Obviously, we like to be able to delegate all the way down to the business functions with Privileged Process Automation and with the EDB or the BDR part of that functionality in EDB that really fits in to our Privileged Access Management. So what I'll do just to take you away from our product. So I'll just quickly show you a slide of the architecture, which is as simple as we have these nodes. If you like the running ADB BDR and they can perform log-ins to a target device using privileged credentials, which we control when we might be really long up to about 128 characters. >> So Andy, if you would, I think you had put together a little show and tell you a demonstration for how when these systems are perhaps under siege if you will. That there are ways in which obviously you've developed to counter this and to be able to continue secure communications, which in the privilege assets world as you know is paramount. >> Yes, indeed. So I'll show you another slide, which gives you a kind of a overview of everything that's going on and you're going to see a little demonstration of two nodes here that has the BDL technology on and they can make these logins, and we have these characters, Bob and Allison. I've just noticed how it marks in department turn Alice to Allison. they should really be Alice because you get Bob, Alice, Carol, Dave, which are the standard encryption users. And what we're going to do is we're going to demonstrate that you can have breaks in the network. So I'm just sharing the network breaks slide. I'm showing the second network break slide. And then we have this function that we've built which we're going to demonstrate for you today, which is called evil beatings. And what it does is whilst there is a politician in the network, we are going to refresh many thousands of times the credentials on the target device. And then we're going to heal the break in the network and then prove that everything is still working. So right now, I'm going to zoom over to my live connection, terminal connections to the machine. And I'm going to run this command here, which is Python EV3. And I'm going to put a hundred cycles in it which is going to do around about 10,000 password refreshes. Okay. And I'm then going to go over to Chrome, and I should have a system here waiting for me. And in this system, you'll see that I've got the device demo and I've got this come online, SSH. And if I click on this I've got a live connection to this machine. Even whilst I have a huge number of queued up and I'll just show you the queued out connections through the admin interface. The system is working extremely hard at the moment. And in fact, if I show you this slide here, you can see that I have all of these queued credential resets and that is giving our system an awful lot of grief. Yeah. I can go back to the device connection and it is all here still top. Why not? And as you can see, it is all working perfectly. And if I was a user of EDB, I think this has to be one of the demonstrations I'd be interested in because it's one of the first things that we did when we dropped that functionality into our products. We wanted to know how well it would work under extreme conditions because you don't think of extreme conditions as normal working, but whenever you have 10 nodes in different countries, there will always be a network break somewhere and someone will always need to be refreshing passwords a ridiculous rates of knots. So Andy let's talk about this kind of the notion that you're providing here, this about accountability and visibility, audit-ability, all these insights that you're providing through this kind of demonstration you've given us how critical is that today, especially when we know there are so many possible intrusions and so many opportunities with legacy systems and new apps and all of this. I mean talking about those three pillars, if you will, the importance of that and what we just saw in terms of providing that peace of mind that everybody wants in their system. >> That's a cracking question. I'm going to enjoy that question. Legacy systems, that's a really good question. If you, we have NHS, which is our national health service and we have hospitals and you have hospitals every country has hospitals. And the equipment that they use like the MRI scanners, the electro-microscope, some of the blood analysis machines, the systems in those costs multiple Gillions of dollars or should use dollars euros, dollars, pounds and the operating systems running those systems, the lifetime of that piece of equipment is much much longer than the lifetime of an operating system. So we glibly throw around this idea of legacy systems and to a hospital that's a system that's a mere five years old and has got to be delivering for another 15 years. But in reality, all of this stuff gets, acquires vulnerabilities because our adversaries the people that want to do organizations bad things ransomware and all the rest of it they are spending all that time learning about the vulnerabilities of old systems. So the beauty of what we do is being able to take those old legacy systems and put a zero trust safety shell around them, and then use extremely long credentials which can't be cracked. And then we make sure that those credentials don't go anywhere near any workstations. But what they do do, is they're inside that ADB database encrypted with a master encryption key, and they make that jump just inside the zero trust boundary so that Bob and Alice outside can get administration connections inside for them to work. So what we're doing is providing safety for those legacy systems. We are also providing an environment for old apps to run in as well. So we have something called a map server which I didn't think you'd asked us that question. I'd have to find you some slides or presentations, which we want to do. We have a map server, which is effectively a very protected window server, and you can put your old applications on them and you can let them age gracefully and carry on running. Dot net 3.5 and all of those old things. And we can map your connection into the older application and then map those connections out. But in terms of the other aspects of it is the hospital stay open 24 hours a day banks run 24 hours a day and they need to be managed from anywhere. We're in a global pandemic, people are working from home. That means that people are working from laptops and all sorts of things that haven't been provisioned by centrality and could all have all sorts of threats and problems to them. And being able to access any time is really important. And because we are changing the credentials on these machines on a regular basis, you cannot lose one. It's absolutely critical. You cannot go around losing Windows active directory domain credentials it just can't be done. And if you have a situation where you've just updated a password and you've had a failure one of those 10 nodes has the correct set of credentials. And when the system heals, you have to work out which one of the 10 it is and the one that did it last must be the one that updates all the other 10 nodes. And I think the important thing is as Osirium we have the responsibility for doing the updates and we have the responsibility for tracking all those things. But we hand the responsibility of making sure that all the other 10 nodes are up to date which just drop it into bi-directional replication and it just happens. And you've seen it happen. I mean, might be just for the fun of it, We'll go back to that demonstration Chrome, and you can see we're still connected to that machine. That's all still running fine but we could go off to our management thing, refresh it and you see that everything there is successful. I can go to a second machine and I can make a second connection to that device. Yet, in the meantime that password has been changed, Oh, I mean, I wouldn't like to tell you how many times it's been changed. I need to be on a slightly different device. I was going to do a reveal password for you, I'll make another connection but the passwords will be typically, do a top on that just to create some more load. But the passwords will typically be... I'll come back to me. They'll typically be 128 characters long. >> Andy, if I could, I mean, 'cause I think you're really showing this very complex set of challenges that you have these days, right? In terms of providing access to multiple devices across, in multiple networking challenges, when you talk to your prospective clients about the kind of how this security perimeters changed, it's very different now than it was four or five years ago. What are the key points that you want them to take away from your discussion about how they have to think about security and access especially in this day and age when we've even seen here in the States. Some very serious intrusions that I think certainly get everybody's attention. >> That's a great question again. They're all... The way that I would answer that question would definitely depend on the continent that I was talking to. But my favorite answer will be a European answer, so I'll give you a European answer. One of the things that you're doing when you come along and provide Privileged Access Management to a traditional IT team, is your taking away the sysadmins right now, before privilege access, they will know the passwords. They will be keeping the passwords in a password vault or something like this. So they own the passwords, they own the credentials. And when you come along with a product like privilege access management you're taking over management of those credentials and you're protecting those systems from a whole wide range of threats. And one of those threats is from the system administrators themselves. And they understand that. So what I would say, it's an interesting question. 'Cause I'm like, I'm thinking I've got two ways of answering I can answer as if I'm talking to management or as if I'm talking to the people who are actually going to use the products and I feel more aligned with the, I feel more aligned with the actual users. >> Yeah, I think let's just, we'll focus on that and I'll let you know, we just have a moment or two left. So if you could maybe boil it down for me a little bit. >> Boiling it down, I would say now look here CIS admins. It's really important that you get your job done but you need to understand that those privileged accounts that you're using on those systems are absolute gold dust if they get into the hands of your adversaries and you need protections income away from those adversaries, but we trust you and we are going to get you the access to your machines as fast as possible. So we're a little bit like a nightclub bouncer but we're like the Heineken of nightclub bounces. When you arrive, we know it's you and we're going to get you to your favorite machine logged on as domain admin, as fast as possible. And while you're there, we're going to cut that session recording of you. And just keep you safe and on the right side. >> All right, I'm going to enjoy my night in the nightclub. Now I can sleep easy tonight knowing that Andy Harris and Osirium are on the case. Thanks, Andy. Andy Harris speaking with us. So the Chief Technology Officer from Osirium as part of our Postgres vision, 2021, coverage here on theCUBE. (upbeat music) >> From theCUBE studios in Palo Alto, in Boston connecting with thought leaders all around the world. This is theCUBE conversation.

>>and hello, we're back. I've got my panel and we are doing things real time here. So sorry for the delay a few minutes late. So the way let's talk about things, the reason we're here and we're going around the room and introduce everybody. Got three special guests here. I got my evil or my john and the normal And we're going to talk about get ops I called it future office just because I want to think about what's the next thing for that at the end, we're gonna talk about what our ideas for what's next for getups, right? Um, because we're all starting to just get into get ups now. But of course a lot of us are always thinking about what's next? What's better? How can we make this thing better? So we're going to take your questions. That's the reason we're here, is to take your questions and answer them. Or at least the best we can for the next hour. And all right, so let's go around the room and introduce yourself. My name is Brett. I am streaming from Brett from that. From Brett. From Virginia Beach in Virginia beach, Virginia, United States. Um, and I talk about things on the internet, I sell courses on you, to me that talk about Docker and kubernetes Ive or introduce yourself. >>How's it going? Everyone, I'm a software engineer at axel Springer, currently based in Berlin and I happen to be Brett Brett's teaching assistant. >>All right, that's right. We're in, we're in our courses together almost every day. Mm john >>hey everyone, my name is john Harris, I used to work at Dhaka um, I now work at VM ware is a star field engineer. Um, so yeah, >>and normal >>awesome by the way, you are streaming from Brett Brett, >>I answered from breath to breath. >>Um I'm normal method. I'm a distinguished engineer with booz allen and I'm also a doctor captain and it's good to see either in person and it's good to see you again john it's been a little while. >>It has the pre covid times, right? You're up here in Seattle. >>Yeah. It feels, it feels like an eternity ago. >>Yeah, john shirt looks red and reminds me of the Austin T shirt. So I was like, yeah, so we all, we all have like this old limited edition doctor on E. >>T. That's a, that's a classic. >>Yeah, I scored that one last year. Sometimes with these old conference church, you have to like go into people's closets. I'm not saying I did that. Um, but you know, you have to go steal stuff, you to find ways to get the swag >>post post covid. If you ever come to my place, I'm going to have to lock the closets. That >>that's right, That's right. >>So the second I think it was the second floor of the doctor HQ in SAn Francisco was where they kept all the T shirts, just boxes and boxes and boxes floor to ceiling. So every time I went to HQ you just you just as many as you can fit in your luggage. I think I have about 10 of these. You >>bring an extra piece of luggage just for your your shirt shirt grab. Um All right, so I'm going to start scanning questions uh so that you don't have to you can you help you all are welcome to do that. And I'm going to start us off with the topic. Um So let's just define the parameters. Like we can talk about anything devops and here we can go down and plenty of rabbit holes. But the kind of, the goal here is to talk about get ups and get ups if you haven't heard about it is essentially uh using versioning systems like get like we've all been getting used to as developers to track your infrastructure changes, not just your code changes and then automate that with a bunch of tooling so that the robots take over. And essentially you have get as a central source of truth and then get log as a central source of history and then there's a bunch of magic little bits in the middle and then supposedly everything is wonderful. It's all automatic. The reality is is what it's often quite messy, quite tricky to get everything working. And uh the edges of this are not perfect. Um so it is a relatively new thing. It's probably three, maybe four years old as an official thing from. We've uh so we're gonna get into it and I'll let's go around the room and the same word we did before and um not to push on that, put you on the spot or anything. But what is, what is one of the things you either like or either hate about getups um that you've enjoyed either using it or you know, whatever for me. I really, I really love that I can point people to a repo that basically is hopefully if they look at the log a tracking, simplistic tracking of what might have changed in that part of the world or the environment. I remember many years past where, you know, I've had executive or some mid level manager wants to see what the changes were or someone outside my team went to see what we just changed. It was okay, they need access to this system into that dashboard and that spreadsheet and then this thing and it was always so complicated and now in a world where if we're using get up orbit bucket or whatever where you can just say, hey go look at that repo if there was three commits today, probably three changes happened. That's I love that particular part about it. Of course it's always more complicated than that. But um Ive or I know you've been getting into this stuff recently. So um any thoughts? Yeah, I think >>my favorite part about get ops is >>reproducibility. Um >>you know the ability to just test something and get it up and running >>and then just tear it down. >>Uh not >>being worried that how did I configure it the first time? I think that's my favorite part about >>it. I'm changing your background as we do this. >>I was going to say, did you just do it get ups pushed to like change his >>background, just a dialogue that different for that green screen equals false? Uh Change the background. Yeah, I mean, um and I mean I think last year was really my first year of actually using it on anything significant, like a real project. Um so I'm still, I still feel like I'm very new to john you anything. >>Yeah, it's weird getups is that thing which kind of crystallizes maybe better than anything else, the grizzled veteran life cycle of emotions with the technology because I think it's easy to get super excited about something new. And when I first looked into get up, so I think this is even before it was probably called getups, we were looking at like how to use guest source of truth, like everything sounds great, right? You're like, wait, get everyone knows, get gets the source of truth, There's a load of robust tooling. This just makes a sense. If everything dies, we can just apply the get again, that would be great. Um and then you go through like the trough of despair, right? We're like, oh no, none of this works. The application is super stateless if this doesn't work and what do we do with secrets and how do we do this? Like how do we get people access in the right place and then you realize everything is terrible again and then everything it equalizes and you're kind of, I think, you know, it sounds great on paper and they were absolutely fantastic things about it, but I think just having that measured approach to it, like it's, you know, I think when you put it best in the beginning where you do a and then there's a magic and then you get C. Right, like it's the magic, which is >>the magic is the mystery, >>right? >>Magic can be good and bad and in text so >>very much so yeah, so um concurrence with with john and ever uh in terms of what I like about it is the potential to apply it to moving security to left and getting closer to a more stable infrastructures code with respect to the whole entire environment. Um And uh and that reconciliation loop, it reminds me of what, what is old is new again? Right? Well, quote unquote old um in terms of like chef and puppet and that the reconciliation loop applied in a in a more uh in a cleaner interface and and into the infrastructure that we're kind of used to already, once you start really digging into kubernetes what I don't like and just this is in concurrence with the other Panelist is it's relatively new. It has um, so it has a learning curve and it's still being, you know, it's a very active um environment and community and that means that things are changing and constantly and there's like new ways and new patterns as people are exploring how to use it. And I think that trough of despair is typically figuring out incrementally what it actually is doing for you and what it's not going to solve for you, right, john, so like that's that trough of despair for a bit and then you realize, okay, this is where it fits potentially in my architecture and like anything, you have to make that trade off and you have to make that decision and accept the trade offs for that. But I think it has a lot of promise for, for compliance and security and all that good stuff. >>Yeah. It's like it's like the potentials, there's still a lot more potential than there is uh reality right now. I think it's like I feel like we're very early days and the idea of especially when you start getting into tooling that doesn't appreciate getups like you're using to get up to and use something else and that tool has no awareness of the concept so it doesn't flow well with all of the things you're trying to do and get um uh things that aren't state based and all that. So this is going to lead me to our first question from Camden asking dumb questions by the way. No dumb questions here. Um How is get apps? Not just another name for C. D. Anybody want to take that as an answer as a question. How is get up is not just another name for C. D. I have things but we can talk about it. I >>feel like we need victor foster kids. Yeah, sure you would have opinions. Yeah, >>I think it's a very yeah. One person replied said it's a very specific it's an opinionated version of cd. That's a great that's a great answer like that. Yeah. >>It's like an implement. Its it's an implementation of deployment if you want it if you want to use it for that. All right. I realize now it's kind of hard in terms of a physical panel and a virtual panel to figure out who on the panel is gonna, you know, ready to jump in to answer a question. But I'll take it. So um I'll um I'll do my best inner victor and say, you know, it's it's an implementation of C. D. And it's it's a choice right? It's one can just still do docker build and darker pushes and doctor pulls and that's fine. Or use other technologies to deploy containers and pods and change your, your kubernetes infrastructure. But get apps is a different implementation, a different method of doing that same thing at the end of the day. Yeah, >>I like it. I like >>it and I think that goes back to your point about, you know, it's kind of early days still, I think to me what I like about getups in that respect is it's nice to see kubernetes become a platform where people are experimenting with different ways of doing things, right? And so I think that encourages like lots of different patterns and overall that's going to be a good thing for the community because then more, you know, and not everything needs to settle in terms of only one way of doing things, but a lot of different ways of doing things helps people fit, you know, the tooling to their needs, or helps fit kubernetes to their needs, etcetera. Yeah, >>um I agree with that, the, so I'm gonna, since we're getting a load of good questions, so um one of the, one of the, one of the, I want to add to that real quick that one of the uh from the, we've people themselves, because I've had some on the show and one of things that I look at it is distinguishing is with continuous deployment tools, I sort of think that it's almost like previous generation and uh continuous deployment tools can be anything like we would consider Jenkins cd, right, if you if you had an association to a server and do a doctor pull and you know, dr up or dr composed up rather, or if it did a cube control apply uh from you know inside an ssh tunnel or something like that was considered considered C. D. Well get ops is much more rigid I think in terms of um you you need to apply, you have a specific repo that's all about your deployments and because of what tool you're using and that one your commit to a specific repo or in a specific branch that repo depends on how you're setting it up. That is what kicks off a workflow. And then secondly there's an understanding of state. So a lot of these tools now I have uh reconciliation where they they look at the cluster and if things are changing they will actually go back and to get and the robots will take over and will commit that. Hey this thing has changed um and you maybe you human didn't change it, something else might have changed it. So I think that's where getups is approaching it, is that ah we we need to we need to consider more than just a couple of commands that be runnin in a script. Like there needs to be more than that for a getups repo to happen anyway, that's just kind of the the take back to take away I took from a previous conversation with some people um >>we've I don't think that lost, its the last piece is really important, right? I think like for me, C d like Ci cd, they're more philosophical ideas, write a set of principles, right? Like getting an idea or a code change to environments promoting it. It's very kind of pipeline driven um and it's very imperative driven, right? Like our existing CD tools are a lot of the ways that people think about Cd, it would be triggered by an event, maybe a code push and then these other things are happening in sequence until they either fail or pass, right? And then we're done. Getups is very much sitting on the, you know, the reconciliation side, it's changing to a pull based model of reconciliation, right? Like it's very declarative, it's just looking at the state and it's automatically pulling changes when they happen, rather than this imperative trigger driven model. That's not to say that there aren't city tools which we're doing pull based or you can do pull based or get ups is doing anything creatively revolutionary here, but I think that's one of the main things that the ideas that are being introduced into those, like existing C kind of tools and pipelines, um certainly the pull based model and the reconciliation model, which, you know, has a lot in common with kubernetes and how those kind of controllers work, but I think that's the key idea. Yeah. >>Um This is a pretty specific one Tory asks, does anyone have opinions about get ops in a mono repo this is like this is getting into religion a little bit. How many repos are too many repose? How um any thoughts on that? Anyone before I rant, >>go >>for it, go for it? >>Yeah. How I'm using it right now in a monitor repo uh So I'm using GIT hub. Right, so you have what? The workflow and then inside a workflow? Yeah, mo file, I'll >>track the >>actual changes to the workflow itself, as well as a folder, which is basically some sort of service in Amman Arepa, so if any of those things changes, it'll trigger the actual pipeline to run. So that's like the simplest thing that I could figure out how to, you know, get it set up using um get hubs, uh workflow path future. Yeah. And it's worked for me for writing, you know? That's Yeah. >>Yeah, the a lot of these things too, like the mono repo discussion will, it's very tool specific. Each tool has various levels of support for branch branching and different repos and subdirectories are are looking at the defense and to see if there's changes in that specific directory. Yeah. Sorry, um john you're going to say something, >>I was just going to say, I've never really done it, but I imagine the same kind of downsides of mono repo to multiple report would exist there. I mean, you've got the blast radius issues, you've got, you know, how big is the mono repo? Do we have to pull does the tool have to pull that or cashier every time it needs to determine def so what is the support for being able to just look at directories versus you know, I think we can get way down into a deeper conversation. Maybe we'll save it for later on in the conversation about what we're doing. Get up, how do we structure our get reposed? We have super granular repo per environment, Perper out reaper, per cluster repo per whatever or do we have directories per environment or branches per environment? How how is everything organized? I think it's you know, it's going to be one of those, there's never one size fits all. I'll give the class of consultant like it depends answer. Right? >>Yeah, for sure. It's very similar to the code struggle because it depends. >>Right? >>Uh Yeah, it's similar to the to the code problem of teams trying to figure out how many repose for their code. Should they micro service, should they? Semi micro service, macro service. Like I mean, you know because too many repose means you're doing a bunch of repo management, a bunch of changes on your local system, you're constantly get pulling all these different things and uh but if you have one big repo then it's it's a it's a huge monolithic thing that you usually have to deal with. Path based issues of tools that only need to look at a specific directory and um yeah, it's a it's a culture, I feel like yeah, like I keep going back to this, it's a culture thing. Does your what is your team prefer? What do you like? What um what's painful for everyone and who's what's the loudest pain that you need to deal with? Is it is it repo management? That's the pain um or is it uh you know, is that that everyone's in one place and it's really hard to keep too many cooks out of the kitchen, which is a mono repo problem, you know? Um How do we handle security? So this is a great one from Tory again. Another great question back to back. And that's the first time we've done that um security as it pertains to get up to anyone who can commit can change the infrastructure. Yes. >>Yes. So the tooling that you have for your GIT repo and the authentication, authorization and permissions that you apply to the GIT repo using a get server like GIT hub or get lab or whatever your flavor of the day is is going to be how security is handled with respect to changes in your get ups configuration repository. So um that is completely specific to your implementation of that or ones implementation of of how they're handling that. Get repositories that the get ups tooling is looking at. To reconcile changes with respect to the permissions of the for lack of better term robot itself. Right? They get up tooling like flux or Argosy. D Um one kid would would create a user or a service account or uh other kind of authentication measures to limit the permissions for that service account that the Gaddafi's tooling needs to be able to read the repose and and send commits etcetera. So that is well within the realm of what you have already for your for your get your get um repo. Yeah. >>Yeah. A related question is from a g what they like about get apps if done nicely for a newbie it's you can get stuff done easily if you what they dislike about it is when you have too many get repose it becomes just too complicated and I agree. Um was making a joke with a team the other week that you know the developer used to just make one commit and they would pass pass it on to a QA team that would then eventually emerging in the master. But they made the commits to these feature branches or whatever. But now they make a commit, they make a pR there for their code then they go make a PR in the helm chart to update the thing to do that and then they go make a PR in the get ups repeal for Argo. And so we talked about that they're probably like four or five P. R. Is just to get their code in the production. But we were talking about the negative of that but the reality was It's just five or 4 or five prs like it wasn't five different systems that had five different methodologies and tooling and that. So I looked at it I was like well yeah that's kind of a pain in the get sense but you're also dealing with one type. It's a repetitive action but it's it's the one thing I don't have to go to five different systems with five different ways of doing it. And once in the web and one's on the client wants a command line that I don't remember. Um Yeah so it's got pros and cons I think when you >>I think when you get to the scale where those kind of issues are a problem then you're probably at the scale where you can afford to invest some time into automation into that. Right? Like what I've when I've seen this in larger customers or larger organizations if there ever at that stage where okay apps are coming up all the time. You know, there's a 10 X 100 X developer to operations folks who may be creating get repose setting up permissions then that stuff gets automated, right? Like, you know, maybe ticket based systems or whatever. Developers say I need a new app. It templates things or more often using the same model, right of reconciliation and operators and the horrific abuse of cogs that we're seeing in the communities community right now. Um You know, developers can create a crd which just says, hey, I'm creating a new app is called app A and then a controller will pick up that app a definition. It will go create a get a repo Programmatically it will add the right definitely will look up and held up the developers and the permissions that need to be able to get to that repo it will create and template automatically some name space and the clusters that it needs in the environments that it needs, depending on, you know, some metadata it might read. So I think, you know, those are definite problems and they're definitely like a teething, growing pain thing. But once you get to that scale, you kind of need to step back and say, well look, we just need to invest in time into the operational aspect of this and automating this pain away, I think. Yeah, >>yeah. And that ultimately ends in Yeah. Custom tooling, which it's hard to avoid it at scale. I mean, there's there's two, there's almost two conversations here, right. There is what I call the Solo admin Solo devops, I bought that domain Solo devops dot com because, you know, whenever I'm talking to dr khan in the real world, it's like I asked people to raise hands, I don't know how we can raise hands here, but I would ask people to raise hands and see how many of you here are. The sole person responsible for deploying the app that your team makes and like a quarter of the room would raise their hand. So I call that solo devops like those, that person can't make all the custom tooling in the world. So they really need dr like solutions where it's opinionated, the workflow is sort of built in and they don't have to wrangle things together with a bunch of glue, you know, in other words bash. Um and so this kind of comes to a conversation uh starting this question from lee he's asking how do you combine get ops with ci cd, especially the continuous bit. How do you avoid having a human uh sort of the complaint the team I was working with has, how do you avoid a human editing and get committing for every single deploy? They've settled on customized templates and a script for routine updates. So as a seed for this conference, this question I'm gonna ask you all uh instead of that specific question cause it's a little open ended. Um Tell me whether you agree with this. I I kind of look at the image, the image artifact because the doctor image or container image in general is an artifact that I I view it that way and that thing going into the registry with the right label or right part of the label. Um That tag rather not the label but the tag that to me is like one of the great demarche points of, we're kind of done with Ci and we're now into the deployment phase and it doesn't necessarily mean the tooling is a clear cut there, but that artifact being shipped in a specific way or promoted as we sometimes say. Um what do you think? Does anyone have opinions on that? I don't even know if that's the right opinion to have so mhm. >>So um I think what you're, what you're getting at is that get ups, models can trigger off of different events um to trigger the reconciliation loop. And one way to do that is if the image, if it notices a image change in the registry, the other is if there's a commit event on a specific rebo and branch and it's up to, you are up to the person that's implementing their get ups model, what event to trigger there, that reconciliation loop off of, You can do both, you can do one or the other. It also depends on the Templeton engine that you're using on top of um on top of kubernetes, such as helm or um you know, the other ones that are out there or if you're not even doing that, then, you know straight. Yeah, mo um so it kind of just depends, but those are the typically the two options one has and a combination of of those to trigger that event. You can also just trigger it manually, right? You can go into the command line and force a a, you know, a really like a scan or a new reconciliation loop to occur. So it kind of just, I don't want to say this, but it depends on what you're trying to do and what makes sense in your pipeline. Right? So if you're if you're set up where you are tag, if you're doing it based off of image tags, then you probably want to use get ups in a way that you're using the image tags. Right. And the pattern that you've established there, if you're not really doing that and you're more around, like, different branches are mapped to different environments, then triggered off of the correct branch. And that's where the permissions also come into play. Where if you don't want someone to touch production and you've got your getups for your production cluster based off of like uh you know, a main branch, then whoever can push a change to that main branch has the authority to push that change to production. Right? So that's your authentication and permissions um system same for the registry itself. Right. So >>Yeah. Yeah. Sorry, anyone else have any thoughts on that? I was about to go to the next topic, >>I was going to say. I think certain tools dictate the approach, like, if you're using Argosy d it's I think I'm correct me if I'm wrong, but I think the only way to use it right now is just through image modification. Like, the manifest changes, it looks at a specific directory and anything changes then it will do its thing. And uh Synchronize the cost there with whatever's and get >>Yeah, flux has both. Yeah, and flux has both. So it it kind of depends. I think you can make our go do that too, but uh this is back to what we were saying in the beginning, uh you know, these things are changing, right? So that might be what it is right now in terms of triggering the reconciliation loops and get ups, tooling, but there might be other events in the future that might trigger it, and it's not completely stand alone because you still need you're tooling to do any kind of testing or whatever you have in terms of like the specific pipeline. So oftentimes you're bolting in getups into some other part of broader Cfd solution. That makes sense. Yeah, >>we've got a lot of questions about secrets or people that are asking about secrets. >>So my my tongue and cheek answered the secrets question was, what's the best practices for kubernetes? Secrets? That's the same thing for secrets with good apps? Uh getups is not last time I checked and last time I was running this stuff get ups is not has nothing to do with secrets in that sense. It's just there to get your stuff running on communities. So, um there's probably a really good session on secrets at dr concept. I >>would agree with you, I agree with you. Yeah, I mean, get off stools, I mean every every project of mine handles secrets differently. Uh huh. And I think I'm not sure if it was even when I was talking to but talking to someone recently that I'm very bullish on get up actions, I love get up actions, it's not great for deployments yet, but we do have this new thing and get hub environments, I think it's called. So it allows me at least the store secrets per environment, which it didn't have the concept of that before, which you know, if you if any of you running kubernetes out there, you typically end up when you start running kubernetes, you end up with more than one kubernetes, like you're going to end up with a lot of clusters at some point, at least many multiple, more than two. Um and so if you're trying to store secret somewhere, you do have and there's a discussion happening in chat right now where people are talking about um sealed secrets which if you haven't heard of that, go look that up and just be versed on what sealed secrets is because it's a it's a fantastic concept for how to store secrets in the public. Um I love it because I'm a big P. K. I nerd but um it's not the only way and it doesn't fit all models. So I have clients that use A W. S. Secrets because they're in A W. S. And then they just have to use the kubernetes external secret. But again like like like normal sand, you know, it's that doesn't really affect get ops, get ops is just applying whatever helm charts or jahmal or images that you're, you're you're deploying, get off. It was more about the approach of when the changes happen and whether it's a push or pull model like we're talking about and you know, >>I would say there's a bunch of prerequisites to get ups secrets being one of them because the risk of you putting a secret into your git repo if you haven't figured out your community secrets architecture and start diving into getups is high and removing secrets from get repose is you know, could be its own industry, right. It's >>a thing, >>how do >>I hide this? How do I obscure this commit that's already now on a dozen machines. >>So there are some prerequisites in terms of when you're ready to adopt get up. So I think is the right way of saying the answer to that secrets being one of them. >>I think the secrets was the thing that made me, you know, like two or three years ago made me kind of see the ah ha moment when it came to get ups which, which was that the premier thing that everyone used to say about get up about why it was great. Was its the single source of truth. There's no state anywhere else. You just need to look at git. Um and then secrets may be realized along with a bunch of other things down the line that is not true and will never be true. So as soon as you can lose the dogmatism about everything is going to be and get it's fantastic. As long as you've understood everything is not going to get. There are things which will absolutely never be and get some tools just don't deal with that. They need to earn their own state, especially in communities, some controls on their own state. You know, cuz sealed secrets and and other projects like SOps and I think there are two or three others. That's a great way of dealing with secrets if you want to keep them in get. But you know, projects like vault more kind of like what I would say, production grade secret strategies. Right? And if you're in AWS or a cloud, you're more likely to be using their secrets. Your secret policy is maybe not dictated by you in large organizations might be dictated by CSO or security or Great. Like I think once if you, if you're trying to adopt getups or you're thinking about it, get the dogmatism of get as a single point of truth out of your mind and think about getups more as a philosophy and a set of best practice principles, then you will be in much better stead, >>right? Yeah. >>People are asking more questions in chat like infrastructure as code plus C d essentially get ups or C I rather, um, these are all great questions and a part of the debate, I'm actually just going to throw up on screen. I'm gonna put this in chat, but this is, this is to me the source, Right? So we worked with when they coined the term. We, a lot of us have been trying to get, if we talk about the history for a minute and then tell me if I'm getting this right. Um, a lot of us were trying to automate all these different parts of the puzzle, but a lot of them, they, some things might have been infrastructure as code. Some things weren't, some things were sort of like settings is coded, like you're going to Jenkins and type in secrets and settings or type in a certain thing in the settings of Jenkins and then that it wasn't really in get and so what we was trying to go for was a way to have almost like eventually a two way state understanding where get might change your infrastructure but then your infrastructure might also change and needs to be reflected in the get if the get is trying to be the single source of truth. Um and like you're saying the reality is that you're never gonna have one repo that has all of your infrastructure in it, like you would have to have, you have to have all your terra form, anything else you're spinning up. Right. Um but anyway, I'm gonna put this link in chat. So this guide actually, uh one of things they talk about is what it's not, so it's, it's kind of great to read through the different requirements and like what I was saying well ago um mhm. Having having ci having infrastructure as code and then trying a little bit of continuous deployment out, it's probably a prerequisite. Forget ops so it's hard to just jump into that when you don't already have infrastructure as code because a machine doing stuff on your behalf, it means that you have to have things documented and somewhere and get repo but let me put this in the in the >>chitty chat, I would like to know if the other panelists agree, but I think get apps is a okay. I would say it's a moderate level, it's not a beginner level communities thing, it's like a moderate level advanced, a little bit more advanced level. Um One can start off using it but you definitely have to have some pre recs in place or some understanding of like a pattern in place. Um So what do the other folks think about that opinion? >>I think if you're if you're trying to use get out before, you know what problem you have, you're probably gonna be in trouble. Right. It's like having a solution to it probably don't have yet. Mhm. Right. I mean if if you're just evil or and you're just typing, keep control apply, you're one person right, Get off. It doesn't seem like a big a big jump, like, I mean it doesn't like why would I do that? I'm just, I'm just gonna inside, it's the type of get commit right, I'm typing Q control apply. But I think one of the rules from we've is none of your developers and none of your admins can have cute control access to the cluster because if you can't, if you do have access and you can just apply something, then that's just infrastructure as code. That's just continuous deployment, that's, that's not really get ops um, getups implies that the only way things get into the cluster is through the get up, get automation that you're using with, you know, flux Argo, we haven't talked about, what's the other one that Victor Farsi talks about, by the way people are asking about victor, because victor would love to talk about this stuff, but he's in my next life, so come back in an hour and a half or whatever and victor is going to be talking about sys, admin list with me. Um >>you gotta ask him nothing but get up questions in the next, >>confuse them, confuse them. But anyway, that, that, that's um, it's hard, it's hard to understand and without having tried it, I think conceptually it's a little challenging >>one thing with getups, especially based off the we've works blog post that you just put up on there. It's an opinionated way of doing something. Uh you know, it's an opinionated way of of delivering changes to an environment to your kubernetes environment. So it's opinionated were often not used to seeing things that are very opinionated in this sense, in the in the ecosystem, but get apps is a opinionated thing. It's it's one way of doing it. Um there are ways to change it and like there are options um like what we were talking about in terms of the events that trigger, but the way that it's structured is an opinion opinionated way both from like a tooling perspective, like using get etcetera, but also from a devops cultural perspective, right? Like you were talking about not having anyone access cube control and changing the cluster directly. That's a philosophical opinion that get ups forces you to adopt otherwise. It kind of breaks the model and um I just I want everyone to just understand that. That is very opinion, anything in that sense. Yeah, >>polygamy is another thing. Infrastructure as code. Um someone's mentioning plummy and chat, I just had actually my life show self plug bread that live go there. I'm on Youtube every week. I did the same thing. These these are my friends um and had palami on two weeks ago uh last week, remember uh and it was in the last couple of weeks and we talked about their infrastructure as code solution. Were actually writing code instead of um oh that's an interesting take on uh developer team sort of owning coding the infrastructure through code rather than Yamil as a data language. I don't really have an opinion on it yet because I haven't used it in production or anything in the real real world, but um, I'm not sure how much they are applying trying to go towards the get up stuff. I will do a plug for Solomon hikes. Who has a, the beginning of the day, it's already happened so you can go back and watch it. It's a, it's a, what's it called? Q. Rethinking application delivery with Q. And build kit. So go look this up. This is the found co founder of Dr and former CTO Solomon hikes at the beginning of the day. He has a tool called dagger. I'm not sure why the title of the talk is delivering with Q. And built it, but the tool is showing off in there for an hour is called dagger. And it's, it's an interesting idea on how to apply a lot of this opinionated automated stuff to uh, to deployment and it's get off space and you use Q language. It's a graph language. I watched most of it and it was a really interesting take. I'm excited to see if that takes off and if they try that because it's another way that you can get a little bit more advanced with your you're get deployments and without having to just stick everything in Yemen, which is kind of what we're in today with helm charts and what not. All right. More questions about secrets, I think. I think we're not going to have a whole lot of more, a lot more about secrets basically. Uh put secrets in your cluster to start with and kubernetes in encrypted, you know, thing. And then, you know, as it gets harder, then you have to find another solution when you have five clusters, you don't wanna have to do it five times. That's when you have to go for Walton A W. S secrets and all >>that. Right? I'm gonna post it note. Yeah. Crm into the cluster. Just kidding. >>Yes, there are recordings of this. Yes, they will be later. Uh, because we're that these are all gonna be on youtube later. Um, yeah, detects secrets cushion saying detect secrets or get Guardian are absolute requirements. I think it's in reference to your secrets comment earlier. Um, Camels asking about Cuban is dropping support for Docker that this is not the place to ask for that, but it, it is uh, basically it's a Nonevent Marantz has actually just created that same plug in available in a different repos. So if you want to keep using Docker and kubernetes, you know, you can do it like it's no big deal. Most of us aren't using doctor in our communities anyway, so we're using like container D or whatever is provided to us by our provider. Um yeah, thank you so much for all these comments. These are great people helping each other and chat. I feel like we're just here to make sure the chats available so people can help each other. >>I feel like I want to pick up on something when you mentioned pollux me, I think there's a um we're talking about getups but I think in the original like the origination of that I guess was deploying applications to clusters right, picking up deployment manifest. But I think with the gloomy and I obviously terra form and things have been around a long time, folks are starting to apply this I think I found one earlier which was like um kub stack the Terror Forms get ups framework. Um but also with the advent of things like cluster A. P. I. Um in the Cuban at the space where you can declare actively build the infrastructure for your clusters and build the cluster right? We're not just talking about deploying applications, the cluster A. P. I will talk to a W. S. Spin up, VPc spin up machines, you know, we'll do the same kind of things that terra form does and and those other tools do I think applying getups principles to the infrastructure spin up right, the proper infrastructure as code stuff, constantly applying Terror form um you know, plans and whatever, constantly applying cluster Api resources spinning up stuff in those clouds. That's a super interesting. Um you know, extension of this area, I'd be curious to see if what the folks think about that. >>Yeah, that's why I picked this topic is one of my three. Uh I got I got to pick the topics. I was like the three things that there like the most bleeding edge exciting. Most people haven't, we haven't basically we haven't figured all this out yet. We as an industry, so um it's I think we're gonna see more ideas on it. Um what's the one with the popsicle as the as the icon victor talks about all the time? It's not it's another getups like tool, but it's um it's getups for you use this kubernetes limit and then we have to look it up, >>You're talking about cross plane. >>So >>my >>wife is over here with the sound effects and the first sound effect of the day that she chooses to use is one. >>All right, can we pick it? Let's let's find another question bret >>I'm searching >>so many of them. All right, so uh I think one really quick one is getups only for kubernetes, I think the main to tooling to tools that we're talking about, our Argosy D and flux and they're mostly geared toward kubernetes deployments but there's a, it seems like they're organized in a way that there's a clean abstraction in with respect to the agent that's doing the deployment and the tooling that that can interact with. So I would imagine that in the future and this might be true already right now that get ups could be applied to other types of deployments at some point in the future. But right now it's mostly focused and treats kubernetes as a first class citizen or the tooling on top of kubernetes, let's say something like how as a first class citizen? Yeah, to Brett, >>to me the field, back to you bret the thing I was looking for is cross plane. So that's another tool. Um Victor has been uh sharing a lot about it in Youtube cross plane and that is basically runs inside a kubernetes, but it handles your other infrastructure besides your app. It allows you to like get ops, you're a W. S stuff by using the kubernetes state engine as a, as a way to manage that. And I have not used it yet, but he does some really great demos on Youtube. So people are liking this idea of get off, so they're trying to figure out how do we, how do we manage state? How do we uh because the probably terra form is that, well, there's many problems, but it's always a lot of problems, but in the get outs world it's not quite the right fit yet, It might be, but you still, it's still largely as expected for people to, you know, like type the command, um, and it keeps state locally the ss, clouds and all that. And but the other thing is I'm I'm now realizing that when I saw the demo from Solomon, I'm going back to the Solomon hikes thing. He was using the demo and he was showing it apply deploying something on S three buckets, employing internet wifi and deploying it on google other things beyond kubernetes and saying that it's all getups approach. So I think we're just at the very beginning of seeing because it all started with kubernetes and now there's a swarm one, you can look up swarm, get office and there's a swarm, I can't take the name of it. Swarm sink I think is what's called swarm sink on git hub, which allows you to do swarm based getups like things. And now we're seeing these other tools coming out. They're saying we're going to try to do the get ups concepts, but not for kubernetes specifically and that's I think, you know, infrastructure as code started with certain areas of the world and then now then now we all just assume that you're going to have an infrastructure as code way of doing whatever that is and I think get off is going to have that same approach where pretty soon, you know, we'll have get apps for all the clouds stuff and it won't just be flexor Argo. And then that's the weird thing is will flex and Argo support all those things or will it just be focused on kubernetes apps? You know, community stuff? >>There's also, I think this is what you're alluding to. There is a trend of using um kubernetes and see rDS to provision and control things that are outside of communities like the cloud service providers services as if they were first class entities within kubernetes so that you can use the kubernetes um focus tooling for things that are not communities through the kubernetes interface communities. Yeah, >>yeah, even criticism. >>Yeah, yeah, I'm just going to say that sounds like cross plane. >>Yeah, yeah, I mean, I think that's that's uh there were, you know, for the last couple of years, it's been flux and are going back and forth. Um they're like frenemies, you know, and they've been going back and forth with iterating on these ideas of how do we manage this complicated thing? That is many kubernetes clusters? Um because like Argo, I don't know if the flux V two can do this, but Argo can manage multiple clusters now from one cluster, so your, you can manage other clusters, technically external things from a single entity. Um Originally flux couldn't do that, but I'm going to say that V two can, I don't actually >>know. Um I think all that is gonna, I think that's going to consolidate in the future. All right. In terms of like the common feature set, what Iver and john what do you think? >>I mean, I think it's already begun, right, I think haven't, didn't they collaborate on a common engine? I don't know whether it's finished yet, but I think they're working towards a common getups engine and then they're just going to layer on features on top. But I think, I mean, I think that's interesting, right, because where it runs and where it interacts with, if we're talking about a pull based model, it shouldn't, it's decentralized to a certain extent, right? We need get and we need the agent which is pulling if we're saying there's something else which is orchestrating something that we start to like fuzzy the model even right. Like is this state living somewhere else, then I think that's just interesting as well. I thought flux was completely decentralized, but I know you install our go somewhere like the cargo has a server as well, but it's been a while since I've looked in depth at them. But I think the, you know, does that muddy the agent only pull model? >>I'm reading a >>Yeah, I would say that there's like a process of natural selection going on as as the C. N. C. F. Landscape evolves and grows bigger and a lot of divide and conquer right now. But I think as certain things kind of get more prominent >>and popular, I think >>it starts to trend and it inspires other things and then it starts to aggregate and you know, kind of get back into like a unified kind of like core. Maybe like for instance, cross plane, I feel like it shouldn't even really exist. It should be, it like it's a communities add on, but it should be built in, it should be built into kubernetes, like why doesn't this exist already >>for like controlling a cloud? >>Yeah, like just, you know, having this interface with the cloud provider and be able to Yeah, >>exactly. Yeah, and it kinda, you're right. That kinda happens because you do, I mean when you start talking about storage providers and networking providers was very specific implementations of operators or just individual controllers that do operate and control other resources in the cloud, but certainly not universally right. Not every feature of AWS is available to kubernetes out of the box. Um and you know, it, one of the challenges across plane is you gotta have kubernetes before you can deploy kubernetes. Like there's a chicken and egg issue there where if you're going to use, if you're going to use our cross plane for your other infrastructure, but it's gotta, but it has to run on kubernetes who creates that first kubernetes in order for you to put that on there. And victor talks about one of his videos, the same problem with flux and Argo where like Argo, you can't deploy Argo itself with getups. There has to be that initial, I did a thing with, I'm a human and I typed in some commands on a server and things happened but they don't really have an easy deployment method for getting our go up and running using simply nothing but a get push to an existing system. There's something like that. So it's a it's an interesting problem of day one infrastructure which is again only day one, I think data is way more interesting and hard, but um how can we spend these things up if they're all depending on each other and who is the first one to get started? >>I mean it's true of everything though, I mean at the end of that you need some kind of big bang kind of function too, you know, I started running start everything I >>think without going over that, sorry, without going off on a tangent. I was, I was gonna say there's a, if folks have heard of kind which is kubernetes and Docker, which is a mini kubernetes cluster, you can run in a Docker container or each container will run as a as a node. Um you know, that's been a really good way to spin up things like clusters. KPI because they boot strap a local kind, install the manifests, it will go and spin up a fully sized cluster, it will transfer its resources over there and then it will die itself. Right? So that, that's kind of bootstrapping itself. And I think a couple of folks in the community, Jason to Tiberius, I think he works for Quinyx metal um has, has experimented with like an even more minimal just Api server, so we're really just leveraging the kubernetes ideas of like a reconciliation loop and a controller. We just need something to bootstrap with those C R D s and get something going and then go away again. So I think that's gonna be a pattern that comes up kind of more and more >>Yeah, for sure. Um, and uh, the next, next quick answer to the question, Angel asked what your thoughts on getups being a niche to get or versus others vcs tools? Well, if I knew anyone who is using anything other than get, I would say no, you know, get ops is a horrible name. It should just be CVS office, but that doesn't or vcs ops or whatever like that, but that doesn't roll off the tongue. So someone had to come up with the get ups phrase. Um but absolutely, it's all about version control solutions used for infrastructure, not code. Um might get doctor asks a great question, we're not gonna have time for it, but maybe people can reply and chat with what they think but about infrastructure and code, the lines being blurred and that do develop, how much of infrastructure does developer do developers need to know? Essentially, they're having to know all the things. Um so unfortunately we've had way more questions like every panel here today with all the great community, we've got way more questions we can handle in this time. So we're gonna have to wrap it up and say goodbye. Go to the next live panel. I believe the next one is um on developer, developer specific setups that's gonna be peter running that panel. Something about development in containers and I'm sure it's gonna be great. Just like this one. So let's go around the room where can people find you on the internet? I'm at Brett fisher on twitter. That's where you can usually find me most days you are? >>Yeah, I'm on twitter to um, I'll put it in the chat. It's kind of confusing because the TSR seven. >>Okay. Yeah, that's right. You can't just say it. You can also look at the blow of the video and like our faces are there and if you click on them, it tells you our twitter in Arlington and stuff, john >>John Harris 85, pretty much everywhere. Get hub Twitter slack, etc. >>Yeah >>and normal, normal faults or just, you know, living on Youtube live with Brett. >>Yeah, we're all on the twitter so go check us out there and thank you so much for joining. Uh thank you so much to you all for being here. I really appreciate you taking time in your busy schedule to join me for a little chit chat. Um Yes, all the, all the cheers, yes. >>And I think this kid apps loop has been declarative lee reconciled. >>Yeah, there we go. And with that ladies and gentlemen, uh bid you would do, we will see you in the next, next round coming up next with Peter >>bye.

>>Hello, and welcome to this special presentation. This is the cube on cloud startups, our special event of Amazon web services, startup showcase. I'm John furrier, host of the cube, and excited to be here to talk about the hottest startups around cloud cloud computing data and the future of the enterprise. We've got Rob Harris, vice president of solutions consulting for star dog. Great company, Rob. Great to see you. Thanks for coming on. So this is a showcase presentation with AWS showcase startup showcase. You guys are a fast growing startup knowledge graph. We did a video explaining kind of what we did in the cube conversation. Um, really interesting category this, uh, eight hubs cloud startups with you guys. Talk about what you got. Take a minute to explain star dog and what you got. >>Sure. Yeah, here at startup, we are really a knowledge graph platform company. So we help build a knowledge graph for our customers tying together the data inside the organization and with data on the cloud in order for them to be able to find search and understand the context and relationship of all that data within their own organization. So that's really what we try to facilitate and make successful for our customers. >>Awesome. What market are you guys targeting? What's the market opportunity. Can you explain the market space that you're building product value in and what's your focus? >>Sure. Yeah, it's, it's pretty exciting. We do a lot from an industry perspective, we target a lot, uh, life sciences or financial the services, and it just tends to be, those are the ones that are most excited and getting started with this, but we certainly have a much broader set of customers in government or in manufacturing. What we really look for is the horizontal type solution, where you have a lot of systems that you want to tie together, or you want to have that understanding of your data all within context throughout your organization. So anybody struggling with that kind of tying of your data together, whether it's on the cloud or on prem, that's what we really go after >>Disruption. Who are you disrupting as you come into the marketplace? I love Amazon so hot startups because they got an eye clean take on something, but someone usually is being impacted. Who is, who are you guys disrupting as you come into? >>Yeah, a lot of times we find we're disrupting traditional ETL, right? So centralizing of all your data into one big platform, a lot of people have gone down this path of trying to create these large repositories data lakes, data warehouses. Yeah. We try to provide the additional value on top of them by not forcing you to continue to invest in moving and centralizing all your data together, but connecting it and providing context, um, while leaving and leveraging the mid worries. >>Awesome. Cause there's a big market opportunity as data warehouses becomes modernized and horizontal control planes and cloud computing is data is the key competitive advantage. Uh, great disruption. Great opportunity. So let's talk about the business star dog. What do you guys, uh, talk about the company, uh, where the headquarters is? The, how many employees what's the business model? How do you guys make money? Yeah, >>Well, a headquarters is always a little bit tricky nowadays is we were also distributed, but officially it is in Arlington Virginia. Uh, although we are all over the globe, uh, mostly in the United States and Europe, certainly as we look at, uh, how, how do we go to market and what do we do related to that? We have a subscription-based model where we help our customers get started usually small, um, by leveraging a package that they can run either on prem or in the cloud or directly from the AWS marketplace and letting them connect to the data and then growing out as they grow within their organization, larger, more interplay enterprise wide type of installations. So that's how we kind of go after it, uh, from, from our company perspective. >>So your go to market then for the company, is it bottoms up organic growth, kind of a freemium get in there? Or is it kind of a mid, mid tier or how do you guys look at that, that entry? >>It's a great question. That's exactly right. A lot of times we do start with a freemium type of model. We do have free trials and use usability to get started very quickly without having to talk to a salesperson or without having to pay up front in order to see the value, because we want you to be able to understand the value you're going to get out of our platform right off the bat and get started. Then after you've really tried it out and you see where it could apply within your organization, we help make it enterprise. >>I have to ask you how the business model of SAS, obviously clouds. Great. Are you guys leveraging Amazon web services marketplace at all? >>We are we're on the marketplace today, um, with the, both the free trial, as well as the ability through, you know, private offers to do whole production instances. So we're really excited about being a part of the marketplace. What we found is that sometimes customers want to run on the cloud. Sometimes they want to run on prem, wherever they want to run. We want to be sure that we're there. >>Yeah. Alex, let's pull up that slide on the hybrid, uh, architecture for these guys. So I want to bring this up since you brought up the business model and you talk about hybrid. This is interesting. This gets into the business model and this is kind of transitions into kind of the technology architecture. Could you walk me through this slide, the knowledge graph and the hybrid cloud. Why is this important for you guys and why is it important for customers? >>This is great. Thank you for, uh, for pulling this up. What this is really showing is as we look toward the future, as we really look at how people are deploying knowledge, graphs, and managing their data, we see that one of the big problems they're trying to address is what about cloud, uh, data that's on the cloud would a bit dated it's on prem. Maybe it's in multiple VPCs that you have within the Amazon environment. How do you tie all this together? And we all know that moving data around between all of these zones can be expensive and time consuming and difficult. And so we've come up with an architecture that allows you to run the knowledge, graph an agent of the knowledge graph in each of these zones. And they can all talk to each other and coordinate with each other. So they can see data that exists within that zone and pass it on to the other pieces as required or as needed to minimize your kind of in and out fees. And to leverage that all that data in one, in one place >>I asked you because this comes up a lot in our coverage, um, data mobility, uh, moving data is expensive. Um, how does that impact you guys in customers? A lot of people have been looking at, Hey, you know, the economics of the cloud are phenomenal, but at some point, if you've got a lot of data, you move compute to the data or you kind of think differently, how do you guys look at that? That trend? >>Yeah, that's, that's really our key value prop is people struggle with this. As people try to figure out how do I handle this large amount of data without having to generate all this additional costs about moving it around. We really look about how do I push that compute down to the storage layers, where the data already exists. And so if you think about our product architecture and you know, we, I know we have a slide on how our product is really built and how it's pulled together. When you look at our core core architecture, we have the graph that represents that connected data, but the exciting part of our architecture, what we do differently than everyone else is by allowing you to keep the data in its existing data silos, whether it's applications or repositories documents that you already have out there, we allow you to connect to that data where it is cross zone, whether it's on prem or on the cloud. >>And by leveraging the power of start on the virtualization engine, you can connect that data and be able to represent it from one source without having to move it around. But because we also have a persistence layer that's built into our product, you can really determine where's the best home. Is it data that you're going to use a lot and thereby should be really close to where the query engine is? Or is it something where you want to federate it out and leverage that compute at that storage layer itself? That flexibility is really why our customers come to us and are excited to use, start off. >>That's awesome. Great, great stuff. Love, love. The slides. Love to look at some pictures that describe the architecture both as well as the product. I love how you got the enterprise high-grade applications and then you're integrating with other partners. I think that's a really key, uh, value. And I think if you're not integrating well in this modern era, you probably won't be surviving much longer. It's pretty much a game changer at this point when knows that a question on the technology and product. Now keeping it on this theme. What's your secret sauce. Every company's got a secret sauce. What is star dog's secret sauce? >>Our secret sauce is really how do we coordinate across all of those applications? So if you can imagine you have, you know, Oracle database or Redshift repository, and you're trying to be able to unify that data in real time across those applications. There's a lot of thought and needs to go about how to do that efficiently. You don't want to take all the database from both repositories, move them, all that data into one place and then figure it out. And so our query planner, how do we coordinate across the multiple applications is really what makes us different and special >>On the Symantec modeling that you're doing? Because I see there's a lot of data there. You got to kind of get an understanding context. Um, how do you guys look at reusability metadata on data? This has become a very key point on not just data warehouse, but it's becoming much more about addressability and discoverability in as fast as possible, low latency, uh, with intelligence, this has been a big discussion. How do you guys look at that aspect of the reusability of the data? >>Yeah, it's, it's one of the exciting parts about starting with a semantic graph and then extending into these capabilities around virtualization and reasoning and inference by starting with the semantic graph, we allow you to, you know, incrementally invest in building out your model and then being able to reuse that model as you, as you go through your implementations. Yeah. That's been a, a big failing as people have looked at the analytical movements recently is so many times people spin up a repository, they answer a particular question and they do an absolutely fine job, but then we have your next question. You have to spin up another repository, build more views, re ETL the data. And then the semantic technology is what allows you to create that common understanding and reuse it over and over and over again. And I think it's time for that to hit mainstream. You know, it's been around a while. It's something that has taken some time to get some adoption around, but now that we really have build up awareness around it and we've shelled, the technology can scale the large volumes. Uh, I think it's time to be able to leverage the value that reasonability brings. Yeah. >>One final question on the product and the technology and kind of the architecture is how do you guys connect the dots going forward as more and more edge nodes become available in the network as that architecture of hybrid that we talked earlier about becomes so complex and so connected. I mean, you could have more connectedness than ever before. Um, it's very complex networks graph theory, right? You're talking about a lot of edges and a lot of traversal it's billions and billions of edges. I mean, this is it's complicated. How do you guys create, how do you guys see that unfolding and how and why the star dog remained relevant in that configuration? >>Yeah. And the simple fact is that people need help, right? It can't be that you're going to define all those edges and connections by hand yourself through some systems or keys. It's a great way to get started, but it's not sufficient in order to really get the value out of that graph that you expect. And the ways we do that is twofold. The first bit is really an influencing or reasoning capability. Being able to look at this structure of the data, how it's composed and create connections between that data based on, you know, logical, logical rules. The second is machine learning, right? Machine learning is high. We use things like linear regression algorithms or other types of community detection algorithms in order to build more connections in the data so that you can get really unlock that value that you're looking for. When you're leveraging graph technology, >>A lot of secret sauce here, a lot of technology graph, super exciting. Let's get into the final segment around customer traction and what you guys have seen with customers. Um, what are some of the use cases that are popular and what happens if customers aren't going down this road? What are they missing out on? Um, I mean, it's the classic fear of missing out and fear of getting screwed over right. Are going out of business. I mean, that's, that's motivational at some level, but you know, there are the, do I wait and people who waited on cloud computing by the way were left behind and some never survived. So we're almost in this same dynamic with customers. At some point you got to put the toe in the water, so to speak or get going to take us through some customer examples and use cases where, >>Or this is working. Yeah. I think both of those areas are, are, uh, great ones to hit on. So when you think about what are we missing out on one of our largest customer bases really in pharmaceuticals. Yeah. And they're using this technology in order to find more connections in the data so that they can really decrease the amount of time for getting a drug to market on the research and development. They can look more at leveraging the data they've already connected using related items to be able to accelerate their investments and waiting costs them hundreds of millions, if not billions of dollars. So there are certainly ones where being able to adopt this technology early and get value out of early, really pays off in. And they're not the only ones. That's the only, that's the only the life sciences space. But there's also the idea to use it, as you said, really about what else am I missing out on? >>And the data fabric movement, this movement around, how do I lower the cost in my organization about moving data around creating more ETL jobs, leveraging all these data assets already have that the data fabric movement is the idea of how do we really automate that? How do we accelerate that? How do we make that an easier process so that it just doesn't cost as much to manage all this data in an organization. And I've observed that more and more. We have customers coming to us, really interested in this type of use cases that relates to our technology and they are getting ahead of their competitors by really lowering their, it costs in line to focus on these higher value activities. >>Life of the customers is what for you with, with startup? Why, how do they win? What's the reason why they buy and take the freemium. And when do they convert over? Well, take me through the progression of value. When do they see something and why do they increase their sure. >>Assumption? Yeah. That, I mean, the bottom line is you want to try to get more value out of your data at a lower cost and make it easier and faster to do. And so getting started in a single use case, trying out our free version, representing your data and taking a look at what it could look like under a common model, connecting it up with our virtualization services is a great way to try out the technology and really, you know, put your toe in the water to see is this something that would be a value to organization as you see that value unlock is you really understand that you can leverage these days assets with this lower time to value, you know, days in order to unlock a whole repository and connected to another repository. That's where we love to engage with you and help show you how you can make that successful in a more production environment. >>I like about some of the things you're talking about star dog has kind of that aspirin aspect, but also a growth, um, uh, vitamin E as well, in terms of the value proposition, a lot of companies are overwhelmed with the data, but yet you have this path towards more creation of value through the knowledge graph and reasoning and other other value. When does a customer, and this is kind of comes back to the customers who are out there potentially watching prospects or future customers. When do they know they need to call you guys up? Is it because they have too many sources? Could you take me through what it, what it looks like in a prospect's environment where they would really win with start a what's it look like? What are some of the signs that they need to engage, start out? >>Yeah. The two big things that we've seen repeated in our customer base over and over again, is if you have a large number of systems out there that aren't connected, that you don't see how all the data it can be pulled together between those systems, because the different data formats or different languages or different ways that the data is created in those systems start off, can certainly help. The second is if you have a large data warehouse or a data Lake, and you don't see the value being generated out of that, because people don't understand where the data is or what context it has with other data within those repositories, both of those situations are one where we think you'd get a lot of value out of start off. And we'd love to talk to you. >>So would, so just secondly, understand this. So if you have a lot of systems that either are not connected or connected, whatever, that's great, a lot of sources sitting around, you know, whether it's spreadsheets or Oracle or >>Red shift, whatever it is, we've loved it that's right. >>Ingest as much as possible from sources >>That's right. Ingest or connect. I mean, that's really the value that we bring is you don't have to pull it all in. You can just map and leverage the data where it lives. We have customers that have petabyte repositories that just mapped that data in to start off, and we can really facilitate pulling out the value of those systems without you having to move it around again, to another request, >>Ingest, connect, and visually see value. That's right. It sounds, it sounds like a tagline, um, great stuff. So just give some examples of who's using it. What big names? Um, obviously you guys, aren't hot startup coming out of the Amazon cloud showcase. Uh, congratulations. What are some names that have worked with you guys that can give an indicator of the company that you're keeping right now in terms of, >>Yeah, I mean our largest customer by far right now, our longest customer has been NASA. Um, so they've been a really exciting user of the platform we've been really to see them leverage the platform. Schneider electric has been a long time user, uh, Bayer FINRA in the U S which is a financial services watchdog organization. These are customers that are getting a lot of value out of our platform today, and we're excited to work with them. >>Awesome, Rob, great to see you. Congratulations. Uh, take a minute to just give the plug for the commercial. How do we engage? What's the culture like, um, you guys hiring, what's the, what's the state of that? What's the state of the company. >>Yeah, no, it's a, it's a great thank you for, uh, for bringing that up where, you know, we're an exciting growing company. Um, as we really reach out more and more to connect more people's data, we find that we're always looking at more resources on building out more conductivity between the individual data sources. So more understanding on that front, as well as more, a professional services type folks to help people through the process. We've really been trying to minimize the amount of effort that you have to have in order to get started, but we know that people like a helping hands. So we're always looking for people we're always growing and we're excited to have the chance to, you know, bring this technology out beyond just the semantic group that is historically been here. >>You know, you've got a great job. Vice-president solutions consulting, essentially you're in a product role, but more like a solution architect meets products, uh, customer facing, and also product century. You're kind of the center of all the action. So what's the coolest thing you've seen, um, from a customer standpoint or an architecture or, um, a deployment or an engagement that you've been involved with. That's been kind of like, Oh, wow, that's cool. That's game. That's something new that we've been, we wouldn't have seen a few years ago. Take us through just an example, anecdotal, you don't have to share the company name or you. >>That's a great question. Um, there is a company that is working on self-driving cars and being able to leverage the knowledge graph to pull together all of the videos and material they get from the vehicles themselves, as well as static information about the sensors. Uh, that's been pretty exciting to see. I, I, I just recently purchased the festival myself. So I'm excited about the whole self-driving car world and to be able to help them participate with these companies is, is pretty exciting. Um, we, we just help one of the large drug manufacturers come to market with one of their drugs earlier than expected. You know, that's a, that's a pretty exciting feeling to know that you can really help people, um, by just connecting the data they already have and letting them leverage those resources, uh, that that really is something that we're going to be very calm >>And the bridge to the future that the customers have to cross with you is also pretty compelling. You got industrial IOT and more and more data to take a quick minute to describe what that future looks like. >>Yeah. You know, as we see more and more automation in this process, we see a couple of different really, you know, exploding areas. The first off, you know, you hit the nail on the head is data being able to bring in more edge devices, being able to really process that data on the fly and be able to help answer questions as these changes in data are occur within these sources. Um, that's certainly part of the future. And the other thing that we're really excited about is this more automatic data discovery with an organization. How can we have an agent that goes out and kind of can infer really even what your data is about in the structure of your data without a lot of input for you. And so we've been working a lot with building up these models automatically and letting you have the foundation for integrating your data, um, and just the push of a button. So we're excited about walking, Alexa, our customers in this journey as well. >>It's, it's a fun area. You talk about reasoning. That's one of the key value propositions that you guys have. You talk about AI, you talk about bots and soon it's going to be thinking machines for us. They're going to be doing all the work. >>I hope they're not too soon, but I am excited about that idea as well. I can go. I do think that, uh, you know, if you look at organizations today, it's fascinating how it's not, that the problems are different, but we're trying to automate as much of it as possible so that we can work on that, the real value clumps of our organizations. And it's not that kind of drudgery work. I started as a DBA back in my career, um, just trying to keep the database up and running, you know, nowadays, you know, all these autonomous databases and self indexing, and self-correcting, it's just not a passive lead as much anymore. You know, we hope we can bring that to the data infrastructure automation. >>It's a double-edged sword gun, right. It's amazing, done wrong. It could cause some damage and flipped some, some pain and hurt. And so you got to figure it out, got to have the right data sets, gotta have the right software, um, and a great future. Rob Harris, congratulations for being a cannabis startup showcase here on the cube on cloud startups, uh, with AWS, uh, led partnership. Thank you for coming on and being part of this event. Thank you again. Okay. Rob Harris, vice president solutions consulting at star dog here for the coupon cloud. I'm John furrier. Thanks for watching. >>Yeah.

>>hello. >>Welcome to the special key conversation. I'm John ferry, host of the queue here in Palo Alto, California, featuring star dog is a great hot start-up. We've got a great guest, Rob Harris, vice president of solutions consulting for star dog here talking about some of the cloud growth, um, knowledge graphs, the role of data. Obviously there's a huge sea change. You're seeing real value coming out of this COVID as companies coming out of the pandemic, new opportunities, new use cases, new expectations, highly accelerated shift happening, and we're here to break it down. Rob, thanks for joining us on the cube conversation. Great to be here. So got, I'm excited to talk to you guys about your company and specifically the value proposition I've been talking for almost since 2007 around graph databases with Neo four J came out and looking at how data would be part of a real part of the developer mindset. Um, early on, and this more of the development. Now it's mainstream, you're seeing value being created in graph structures. Okay. Not just relational. This has been, uh, very well verified. You guys are in this business. So this is a really hot area, a lot of value being created. It's cool. And it's relevant. So tell us first, what is star dog doing? What's uh, what is the company about? >>Yeah, so I mean, we are an enterprise knowledge graph platform company. We help people be successful at standing up knowledge graphs of the data that they have both inside their company and using public data and tying that all together in order to be able to leverage that connected data and really turn it into knowledge through context and understand it. >>So how did this all come about this from a tech standpoint? What is the, what is the, uh, what was the motivation around this? Because, um, obviously the unstructured wave hit, you're seeing successes like data bricks, for instance, just absolutely crushing it on, on their valuation and their relevance. You seeing the same kind of wave hit almost kind of born back on the Hadoop days with unstructured data. Is that a big part of it? Is it just evolution? What's the big driver here? >>Yeah, no, I think it's a, it's a great question. The driver early is as these data sets have increased for so many companies trying to really bring some understanding to it as they roll it out in their organizations, you know, we've tried to just try to centralize it and that hasn't been sufficient in order to be able to unlock the value of most organization status. So being able to step beyond just, you know, pulling everything together into one place, but really putting that context and meaning around it that the graph can do. So that's where we've really got started at, uh, back in the day is we really looked at the inference and reasoning part of a knowledge graph. How do we bring more context and understanding that doesn't naturally exist within the data? And that really is how we launched off the product. >>I got to ask you around the use cases because one of the things that's really relevant right now is you're seeing a lot of front end development around agile application. Dev ops is brought infrastructure as code. You're seeing kind of this huge tsunami of new of applications, but one of the things that people are talking about in some of the developer circles and it's kind of hits the enterprise is this notion of state because you can have an application calling data, but if the data is not addressable and then keeping state and in real time and all these kinds of new, new technical problems, how do you guys look at that? When you look at trying to create knowledge graphs, because maintaining that level of connection, you need data, a ton of it it's gotta be exposed and addressable and then deal dealt with in real time. How do you guys look at it? >>Yeah, that's, that's a great question. What we've done to try to kind of move the ball forward on this is move past, trying to centralize that data into a knowledge graph that is separate from the rest of your data assets, but really build a data virtualization layer, which we have integrated into our product to look at the data where it is in the applications and the unstructured documents and the structure repositories, so that we can observe as state changes in that data and answer questions that are relevant at the time. And we don't have to worry about some sort of synchronous process, you know, loading information into the graph. So that ability to add that virtualization layer, uh, to the graph really enables you to get more of a real time, look at your data as it evolves. >>Yeah. I definitely want to double, double click on that and say, but I want to just drop step back and kind of set the table for the folks that aren't, um, getting in the weeds yet on this. There's kind of a specific definition of enterprise knowledge graph. Could you like just quickly define that? What is the enterprise knowledge graph? Sure. >>Yeah, we, we really see an enterprise knowledge graph as a connected set of data with context. So it's not just storing it like a graph, but connect again and putting meaning around that data through structure, through definitions, et cetera, across the entire enterprise. So looking at not just data within a single application or within a single silo, but broadly through your enterprise, what does your data mean? How is it connected and what does it look like within context each other? >>How should companies reuse their data? >>Boy, that's a broad question, right? Uh, you know, I mean, one of the things, uh, that I think is very important as so many companies have just collected data assets over the years, they collect more and more and more. We have customers that have eight petabytes of data within their data Lake. And they're trying to figure out how to leverage it by actually connecting and putting that context around the data. You can get a lot more meaning out of that old data or the stale data or the unknown data that the people are getting right today. So the ability to reuse the data assets with in context of meeting is where we see people really be able to make huge licks for in their organization like drug companies be able to get drugs to market faster. By looking at older studies, they've done where maybe the meeting was hidden because it was an old system. Nobody knew what the particular codes and meaning were in context of today. So being able to reuse and bring that forward brings real life application to people solving business problems today. >>Rob, I got to get your thoughts on something that we always riff on here on the cube, which is, um, you know, do you take down the data silos or do you leverage them? And you know, this came up a lot, many years ago when we first started discussing containers, for instance, and then that we saw that you didn't have to kill the old to bring in the new, um, there's one mindset of, you know, break the silos down, go horizontal scalability on the data, critical data, plane control, plane, other saying, Hey, you know what, just put it, you know, put a wrapper around those, those silos and you know, I'm oversimplifying, but you get the idea. So how should someone who's really struggling with, or, or not struggling, we're putting together an architecture around their future plans around dealing with data and data silos specifically, because certainly as new data comes in there's mechanism for that. But as you have existing data silos, what do companies do? What's the strategy in your opinion? >>Yeah, you know, it is a really interesting question. I was in data warehouse and for a long, long time and a big proponent of moving everything to one place. And, uh, then I really moved into looking into data virtualization and realized that neither of those solutions are complete, that there are some things that have to be centralized and moved the old systems aren't sufficient in order to be able to answer questions or process them. But there are many data silos that we've created within organizations that can be reused. You can leverage the compute, you can leverage the storage that already exist within us. And that's the approach we've taken at start off. We really want to be able to allow you to centralize the data that makes sense, right. To get it out of those old systems, that should be shut down from just a monetary perspective, but the systems that are have actual meeting or that it's too expensive in order to, to remove them, leverage those data silos. And by letting you have both approaches in the same platform, we hope to make this not an either or architectural decision, which is always the difficult question. >>Okay. So you got me on that one. So let me just say that. I want to leverage my data silos. What do I do? Take me through the playbook. What if I got the data silos? What is the star dog recommendation for me? >>Sure. So what, what we generally recommend is you start off with building kind of a model, uh, in the, in the lingo, we sometimes say ontology Euro, some sort of semantic understanding that puts context around what is my data and what does it mean? And then we allow you to map those data silos. We have a series of connectors in our product that whether it's an application and you're connecting through a rest connector, or whether it's a database and you're connecting through ODBC or JDBC map that data into the platform. And then when you issue queries to the startup platform, we federate those queries out to the downstream systems and answer as if that data existed on the graph. So that way we're leveraging the silos where they are without you having to move the data physically into the platform. So you guys are essentially building a >>Data fabric. >>We are, yeah. Data fabric is really the new term. That's been popping up more and more with our customers when they come to us to say, how can we kind of get past the traditional ways of doing data integration and unified data in a single place? Like you said, we don't think the answer is purely all about moving it all to one big Lake. We don't think the answer is all about just creating this virtualization plane, but really being able to leverage the festival. >>All right. So, so if you, if you believe that, then let's just go to the next level then. So if you believe that they can, don't have to move things around and to have one specific thing, how does a customer deal with their challenge of hybrid cloud and soon to be multi-cloud because that's certainly on the horizon. People want choice. There's going to be architectural. I mean, certainly a cloud operations will be in play, but this on-premise and this cloud, and then soon to be multiple cloud. How do you guys deal with that? That question? >>Yeah, that's a great question. And this is really a, an area that we're very excited about and we've been investing very heavily in is how to have multiple instances of StarTalk running in different clouds or on prem on the clown, coordinate to answer questions, to minimize data movement between the platforms. So we have the ability to run either an agent on prem. For example, if you're running the platform in the cloud or vice versa, you can run it in the cloud. You are two full instances that start off where they will actually cope plan queries to understand where does the data live? Where is it resident and how do I minimize moving data around in order to answer the question? So we really are trying to create that unified data fabric across on-prem or multiple cloud providers, so that any of the nodes in the platform can answer question from any of the datas >>S you know, complexity is always the issue. People cost go up. When you have complexity, you guys are trying to tame it. This is a huge conversation. You bring up multi-cloud and hybrid cloud. And multi-cloud when you think about the IOT edge, and you don't want to move data around, this is what everyone's saying, why move it? Why move data? It's expensive to move data processes where it is, and you kind of have this kind of flexibility. So this idea of unification is a huge concept. Is that enough? And how should customers think about the unification? Because if you can get there, it almost, it is the kind of the Holy grail you're talking about here. So, so this is kind of the prospect of, of having kind of an ideal architecture of unification. So take us, take me through that one step deeper. >>Well, it is, it is kind of interesting because as you really think about unifying your data and really bringing it together, of course it is the Holy grail. And that's what people have been talking about. Um, gosh, since I started in the industry over 20 years ago, how do I get this single plain view of my data, regardless of whether it's physically located or, uh, somehow stitched together, but what are the things that, you know, our founders really strongly believed on when they started the company? Was it isn't enough. It isn't sufficient. There is more value in your data that you don't even know. And unlocking that through either machine learning, which is, of course, we all know it's very hot right now to look at how do I derive new insights out of the data that I already have, or even through logical reasoning, right? And inference looking at, what do I understand about how that data is put together and how it's created in order to create more connections within the data and answer more questions. All those are ways to grow beyond just unifying your data, but actually getting more insights out of it. And I think that is the real Holy grail that people are looking for, not just bringing all the data together, but actually being able to get business value and insights out of that data. Yeah. >>Looking for it. You guys have obviously a pretty strong roster of clients that represent that. Um, but I got to ask you, since you brought up the founders, uh, the company, obviously having a founders' DNA, uh, mindset, um, tends to change the culture or drive the culture of the covenant change with age drives the culture of the company. What is the founder's culture inside star, dog? What is the vibe there, if you could, um, what do they talk about the most when you, when they get in that mode of being founders like, Hey, you know, this is the North star, what is, what's the rap like? What's the vibe share? It takes that, take us through some star star, dog culture. >>Sure. So our three founders came out of the rusty of Maryland, all in a PhD program around semantic reasoning and logical understanding and being able to understand data and be able to communicate that as easily as possible is really the core and the fiber of their being. And that's what we see continually under discussion every single day. How can we push the limits to take this technology and your gift easier to use more available, bring more insights to the customers beyond what we've seen in the past. And I find that really exciting to be able to constantly have conversations about how do we push the envelope? How do we look beyond even what Gartner says is five or eight years in the future, but looking even further ahead. So there >>They're into they're into this whole data scene. Then big time they are >>That they are very active in the conferences and posts and you know, all that great. >>They love this agility. They got to love dev ops. I mean, if you're into this knowledge graph scene, so I gotta, I gotta ask you, what's the machine learning angle here, obviously, AI, we know what AI is. AI is essentially combination of many things, machine learning and other computer science and data access. Um, what is the secret sauce behind the machine learning and, and the vibe and the product of, of, uh, >>Yeah, a lot of times w we, the way that we leverage machine learning or the way that we look at it is how do we create those connections between data? So you have multiple different systems and you're trying to bring all that data together. Yeah. It's not always easy to tell, is this rod Harris the same as that rod Harris is this product the same as that product. So when possible we will leverage keys or we'll leverage very, uh, you know, systematic type of understanding of these things are the same, but sometimes you need to reach beyond that. And that's where we leverage a lot of machine learning within the platform, looking at things like linear regression or other approaches around the graph, you know, connectivity, analysis, page rank, things like that to say, where are things the same so that we can build that connections in that connectivity as automatically as possible. >>You don't get a lot of talks on the cube. Also. Now that's new news, new clubhouse app, where people are talking about misinformation, obviously we're in the media business. We love the digital network effect. Everything's networks, the network economy. You starting to see this power of information and value. You guys carved the knowledge graph. So I gotta, I gotta ask you, when you look at this kind of future where you have this, um, complexity and the network effect, um, how are you guys looking at that data access? Because if you don't have the data, you're not going to have that insight, right? So you need to have that, that network connection. Is that a limitation or for companies? Is that an, um, cause usually people aren't necessarily their blind spot is their data or their lack of their data. So having things network together is going to be more of the norm in the future. How do you guys see that playing out? Yeah, >>I think you're exactly right. And I think that as you look beyond where we are today, and a lot of times we focus today on the data that a company already has, what do I know? Right. What do I know about you? What, how do I interact with you? How have I interacted with you? I think that as we look at the future, we're going to talk more about data sharing, but leveraging publicly available information about being able to take these insights and leverage them, not just within the walls of my own organization, but being able to share them and, uh, work together with other organizations to bring up a better understanding of you as a person or as a consumer that we could all interact with. Yeah, you're absolutely right. You know, Metcons law still holds true that, you know, more network connections bring more value. I certainly see that growing in the future, probably more around, you know, more data sharing and more openness about leveraging publicly available. >>You know, it's interesting. You mentioned you came from a data warehouse background. I remember when I broken the businessmen 30 years ago, when I started getting computer science, you know, it was, it was, there was, there was pain having a product and an enabling platform. You guys seem to have this enabling platform where there's no one use case. I mean, you, you have an unlimited use case landscape. Um, you could do anything with what you guys have. It's not so much, I mean, there's, low-hanging fruit. So I got to ask you, if you have that, uh, enabling platform, you're creating value for customers. What are some of the areas you see developing, like now in terms of low-hanging fruit and where's the possibilities? How do you guys see that? I'm sure you've probably got a tsunami of activity around corner cases from media to every vertical we do. And that's, you know, >>The exciting part of this job. Uh, part of the exciting part of knowledge press in general is to see all the different ways that they are allowed to use. But we do see some use cases repeated over and over again. Uh, risk management is a very common one. How do I look at all the people and the assets with an organization, the interactions they have to look at hotspots for risk, uh, that I need to correct within my organization for the pre-commercial pharma, that has been a very, very hot area for us recently. How do we look at all the that's available with an organization that's publicly available in order to accelerate drug development in this post COVID world, that's become more and more relevant, uh, for organizations to be able to move forward faster and the kind of bio industry and my sciences. Um, that's a use case that we've seen repeated over and over again. And then this growing idea of the data fabric, the data fabric, looking at metadata within the organization to improve data integration processes, to really reduce the need for moving data without or around the organization as much. Those are the use cases we've seen repeated over and over again over the last >>Awesome Rob. My last question before we wrap up is for the solution architect that's out there that has, you know, got a real tall order. They have to put together a scalable organization, people process and technology around a data architecture. That's going to be part of, um, the next gen, the next gen next level activity. And they need headroom for IOT edge and industrial edge, uh, and all use cases. Um, what's your advice to them as they have to look out at and start thinking about architecture? >>Yeah, that's, it's a great question. Uh, I really think that it's important to keep your options open as the technology in the space continues to evolve, right? It's easy to get locked into a single vendor or a single mindset. Um, I've been an architect most of my career, and that's usually a lot of the pitfalls. Things like a knowledge graph are open and flexible. They adhere to standards, which then means you're not locked into a single vendor and you're allowed to leverage this type of technology to grow beyond originally envisioned. So thinking about how you can take advantage of these modern techniques to look at things and not just keep repeating what you've done in the past, the sins of the past have, uh, you know, a lot of times do reappear. So fighting against that as much as possible as gritty is my encouragement. >>Awesome, great insight. And I love this. I love this area. I know you guys got a great trend. You're riding on a very cool, very relevant final minute. Just take a quick minute to give a plug for the company. What's the business model. How do I deploy this? How do I get the software? How do you charge for it? If I'm going to buy this solution or engage with star DOE what do I do? Take me through that. Sure. >>Yeah. We, uh, we are like, uh, you've sat through this whole thing. We are enterprise knowledge graph platform company. So we really help you get started with your business, uh, uh, leveraging and using a knowledge graph fricking organization. We have the ability to deploy on prem. We have on the cloud, we're in the AWS marketplace today. So you can take a look at our software today, who generally are subscription-based based on the size of the install. And we are happy to talk to you any time, just drop by our website, reach out we'll we'll get doctors. >>Rob. Great. Thanks for coming. I really appreciate it. That gradients said, looking forward to seeing you in person, when we get back to real life, hopefully the vaccines are coming on. Thanks to, uh, companies like you guys providing awesome analytics and intelligence for these drug companies and pharma companies. Now you have a few of them in your, on your client roster. So congratulations, looking forward to following up great, great area. Cool and relevant data architecture is changing. Some of it's broken. Some it's being fixed started off as one of the hot startups scaling up beautifully in this new era of cloud computing meets applications and data. So I'm John. Forget the cube. This is a cube conversation from Palo Alto, California. Thanks for watching.

>>Hi. Um, and thank you for inviting me to speak at the Entity Research Summit. And congratulations for NTT for setting up the neuroses club in the area. Okay, so I'm gonna talk about fully by deniable encryption and multiply the competition. And, uh, this is joint work with park from Harvard. And Santa will bring a, uh, she structurally right now in Russia during the rest. Um, so So so consider thesis, uh, two kids, which maybe some of you still remember its violence for check the incredible kids. And they are want they want to talk to each other privately without her mother learning what talking about. So here they are using this lead pipe, which is that cannot be secure Channel and and violent can say to that track that she doesn't want to do her homework and check it was the watch movie. And she knows that the judge will understand what she says. We hear what she says, but her mother, their mother, is not going to anything because it z this lead pipe. She doesn't know what they're talking about. Um and and and we know how to implement this actually in without lead pipes in the software will Do you have encryption, which, you know, you know, for I know, uh, 40 for the last 40 years or so, but actually for many more s. Oh, this is great. Encryption gives us private communication against, uh, eavesdropping adversary. So passive adversaries s but But you know that mothers can be more than passives. What if the mother he goes and asks Pilot that? What did you talk? What do you say to judge it So you know, if valid, really said, you know, used this'll end pipe. She can say whatever she wants to say. I actually said that I was study, and then the mother goes to judge. I can ask him what did about tell you, and she said that she was studied and the mother still cannot tell anything about what happened. She doesn't know trillions. Death was sent or not. Um, in fact, even if violence said that she was studying and and Jackson said something else that you know, she said she was she rather watch movie. Even then the mother doesn't know who was right. I mean, not from the pipe music. Look them in the eye and not this way, but not from the communication she doesn't. Andi. In fact, we could go on like this, and, you know, the lead type doesn't help at all to understand what really have. And this is really another very important form off this really secure channels that it doesn't allow external parties. Course, there's, uh, certain what really happened. Even when they asked to see all the internals of all the parties. In fact, even further, the Violet Jack Jack have no way to actually convince the mother that this is what happened. Even if you want, right, they have no way of actually proving to the mother that they said this and not the other thing with this lead pipe. So the question is can be obtained a similar effects with, you know, software encryption. Uh, can we have an encryption scheme that has the same sort of properties? So we know that Peoria, the total encryption doesn't have this property. That encryption leaves traces. So there's this cipher text that that the mother of the course of seized. Then when the mother goes toe the parties and you know the ballot judge, you can ask him uh, give me. Show me your randomness. Show me all the internals. I want to see what really? How you generated the text and how you decrypted it with no money. Encryption is only one way that, but inject, checking opened the suffer text, and therefore, there is no real privacy anymore. Um, so So this is the case. So so really to do to address this issue? The this this concept of deniable encryption that was considered, uh, you know, many years ago. Andi idea here is that you wanted encryption scheme that provides, uh, protection of privacy. Uh, on ability, toe keep private. You really, really, really value. And maybe, ah, fake or lie about what you say in a convincing way, even against such a course. Uh huh. So and so? So the idea is that, you know, So they actually do you think of three types here, So there is centered in apple. So we're just going us to center off the off the message. You know how How did you encrypt the message? Show me your encryption. Andalus Suing The decryption key is public. Um, and if you go to the receiver and ask him show me your decryption key. I want to see how you decrypted. And you can also think about natural case where the course actually goes to both parties and ask them for the for the internals and compares one against the other. Right? So this is the bite inability concept. Andi, you can, of course, naturally generalize it. Not just to encryption to, say, two party competition soon here, Violent and Jack. Jack. You know, uh, maybe not even trust each other fully, But they want toe compute together, you know? Or, you know, do they actually know a kid they both know and rapes in school, Right. So, So, So violent has her own list of kids, and she knows grapes and injection to, and they want to do this to Paris ST secure competition to figure out if they keep the both. And so if they have this ideal trusted party or stay for somewhere where they can actually do the security applications uh um, securely then they can, of course, learned the answer without learning anything else. And also, if the mother comes in after the fact and ask them, you know who I see that you were trying to figure out who very school, you know. So tell me what you did. Tell me your inputs them you are supposed to give me all the randomness. And And I want to know for the kids that you know, that vaping school. So if they were using such such a physically, I didn't secure gadget then, uh, then they can say You know why? You know? So So what is the state of, I don't know, anybody Invasion did Jack this theater and I got nothing into something or nothing. Jake Jackson. Consistency and off course. Mother has no way of knowing if this is true. No. And even if, uh, injected decides to tell the truth and actually tells is really important. Really put real randomness. And, uh, no randomness here and violent tells still here. Nothing. Nothing that the mother has no way of knowing which one is like. She clearly some of one of them is language. Doesn't know which one. I mean, chicken again looked deep in the eye, but not from the communication. She cannot figure out. Um, so s so we want to get something like that for for two party competition. Uh, and and and again, eso again, again, again. The case that, you know, one is like going to the truth is still don't know. Um, so the question is there a protocol that that one is still behavior, and, uh, incredible. How do you define us? Uh, and the point is that, you know, Okay, 11 further thing toe. Think about, you know, this doesn't shouldn't end with two parties can think about three or more parties on, uh, and the same thing happens. You know, just maybe the trust structure, the consistency structure becomes more complicated. Uh, you know, you could buy groups of people which is consistent with each other and not without, um Okay, so So what are our results here? So first result is regarding encryption. So we come up with the first bite, the novel communication protocol. It's not encryption because it's three messages. Uh, so it is three messages, and it is this way need a reference string, which is like, programs in the sky. And but it's a short registering. I mean, one short programs that everybody in the world uses for the encryptions for the entire duration of time. and our assumptions are some expansion, Leo in one functions, uh, and on. But just to say that what was done previously? It was just senator deniable or receiver deniable, um, And then and nothing that we do is that actually way define and also obtained this extra property, which we call off the record inability which talks with you about the case where, as I said before, that one party, uh uh, is saying one thing and the other practicing nothing they insisted. So they cannot. There is no way for them to frame each other. Um, and the way the other result is regarding a multiparty function evaluation on Dhere, we come up with the first all deniable secure function evaluation for quote Well, you know, I mean, I mean that the protocol with the adversary or the coarser expect to see all off the transcript of the competition, including all the randomness in all the internal state of all the parties eso superiors results in this area always assumed that you know, either the course only can concourse on some of the parties or if you can force all the parties and there is some some physical gadget, uh, which is crucial information about the personnel puts and you know, nobody can see inside, so no, here, we actually that the Attackers see everything. Uh, because they think they see everything on we can still provide inability onda protocol. Also, our protocols also withstand inconsistencies. Mean the case off this off the record style that one party says one thing partisans don't think. But this is only in the case of two parties and only for functions where the input size is polynomial in play. Put size. Uh, domain. Um, so in this actually interested open question how to extend it beyond that. Uh, so just to say that this is kind of it's a surprising thing that you can even do such thing, because what it allows you to do is actually such to completely rewrite history. Eso you during your competition on. Then somebody comes, and that will show me everything that happened. All the runners, all the entire transcript, the competition from beginning to the end. And you can now tell them something else. Not something that really happened. I mean, they see, you know, the public messages they see it on thistle is un contestable, but you can show different internals that there are very different than what really happened. And still nobody can catch you. So it's really some sense. Uh, who knows what's really happened? Um, so anyway, so So this is the, uh this is the result. Let's just say a few words about fully deniable encryption. Uh, just toe give a more detailed So So So So, how do you define this? Fully deniable encryption. So first I want to say that, you know, if you just, uh if the parties have appreciate key then, uh, deniability is with these because what you know, you just in orderto cryptic message just want some part of the key. And this one temple is completely deniable, right? Because you can just take this self a text and claim that it was any message encryption off any message off your choice. But just, you know, extra it. But just coming up with the key, which is the Solvents Architects as a message of futures. So this is completely diamond by both parties, and even it's off the record because if the two parties say different things, there's no way to know what's right. So Eh, so what? But it means that, you know, the hard part is actually had to come up with this shirt key, uh, in a deniable way. So you can actually later argued that this key was an, um so s so we need kind of deniable key exchange, and then this is what we do. So we come up with this idea by by the application of what? This what this means. So it's a protocol, you know, for two parties, uh, change, keep with messages and which gives you the ability to life. Somebody asked you which was key and claim it was anything, uh, later. So more formally. So we have two parties. One You know, this is the key change protocol for one party, and this is the kitchen for the other party in each party also is equipped with this faking algorithm. This is s faking arctic. I keep, you know, Senator, receiver, Even though it's not teach change, it's affecting and breaking. Allows you to come up with fake randomness. That demonstrate kills anything and we want correctly since semantic security as usual and we want toe this s fake takes a transcript and the randomness and the old key in the nuclear that you want. Andi comes up with fake randomness such that, uh um and this is you know, that that consistent with this new key, k prime and the same for the receiver. It comes up with a new randomness. The assistant to the crime and the requirement is that, uh, the attack. I cannot tell the difference between the experiment when you know the key key was exchanged. These transcripts respecto the real key or the case where the key was exchanged, and then the faking accurately going folk What? The adversary seizes the actual transcript, but then opening to a different. So there's a distinguished group. Um, And then what if the parties that were okay then there is another requirement there that says that even if the parties you know, one of them face, the other one doesn't and they then you can't tell which one will effect in which one wants to tell the truth. Onda point is that this to this to produce properties together really give you what you would like for my dearly your channel, even with respect toe courses. Um, so just to point out that you know this, this properties hold only if the parties in the follow the protocol during the execution actually choose randomness is they should. Otherwise things does work. In fact, otherwise, there's nothing that could work because the party's chief from the beginning and just use the terroristic protocol instead of randomized or just, you know, just randomness, which is predetermined. And, of course, nothing you can do. Uh, however, you know, there are, of course, interesting situations where it is. You know, it's reasonable to trust that the parties are actually using the randomness Aziz instructed during the execution of the protocol, for instance, we're thinking about voting this something can be forced, uh, by the voting booth, but you know, other situations. But this is kind of like essentially eso maybe another minute to say a few words about, you know, just like construction. How it kind of works in, you know, in general. So So we have, like, a three months, three rounds protocols. So we have four programs, you know, two from each party don't to deal with the three messages. Then we have a faking program for each party, so the way it works, you know, first, the violent here is has this is Harris randomness and actually chooses the key that they're going Thio agree ahead of time. It inputs to the first program which is going to think of it is the office care program black box program. And there's the message. First message is basically a harsh appear f off the K and then the, uh and then the responder gets this message has its own randomness and outputs. Another message, which is the hash off the first message agronomists. And then the third message now is going to be a new encryption off the key on the hashes and the end to a previous messages. This is, ah, company encryption off this one long spring and then the fourth with the fourth program just takes the randomness off the receiver and the two messages and put it in. And then I'll put the key, which is decrypted essentially the Crips, the subtextual from here in the old checks, right? And then the faking programs. What they do, they just take those. The transcript and the cookie and the new key and the striking program here are puts a new randomness for the senator and this one There's a new randomness for the receiver and the way it does near random estrogen offering work eyes, uh, is again It's kind of fact natural a t least the face of it. It uses the seeking hidden triggers idea off, off, so high in waters for descending on the inability that, you know, trigger each one of those programs toe put actually write message even when you get this, uh, crime on eventually this k problems are Well, the problem is that this scene in triggers, you know, give you local consistency for each problem by itself. This was this was the east their goal. But there is no global consistency about those six programs together and and get the six programs together to be consistent with the fact that the key would actually keep prominent K is high in contribute. And this is something that we become the main challenge of this work. This also, I did this three messages because if you have only to then there is no way to get a double consistency. Ah, s O s. So this is, uh this is the test on just to say about, you know, the future. So definitely we want stronger than ability for for MPC. As I said, we just give partial results there on. Then there is kind of, like some very interesting questions. One is like in general, You know, we know that your is very nice, but in many cases, we actually can do things without, uh but in this situation with prosecution, but maybe the inability of one of the very few cases where actually, we don't have any other way to do things out of the Neo. Is it really essential? Can we prove it? You know, and if not, can we do without? Can we get around CRS? Can you actually do with public friend of mysterious? Uh, you know, and more generally? Uh, no. We actually, uh, sweated a lot. You know, spit blood. In order to make this thing work with Leo and because I always really hard to work with, you know, would agree toe, find some some some general set of tools to work more easily. I was there. Um, Louis, thank you very much on death's

>>Hi, Maya. Mr England. And I am an associate professor of electrical engineering and computer science at M I T. It's been fantastic to be part of this team that Professor Yamamoto put together, uh, for the entity Fire program. It's a great pleasure to report to you are update from the first year I will talk to you today about our recent work in photonic accelerators for machine intelligence. You can already get a flavor of the kind of work that I'll be presenting from the photonic integrated circuit that services a platonic matrix processor that we are developing to try toe break some of the bottle next that we encounter in inference, machine learning tasks in particular tasks like vision, games control or language processing. This work is jointly led with Dr Ryan heavily, uh, scientists at NTT Research, and he will have a poster that you should check out. Uh, in this conference should also say that there are postdoc positions available. Um, just take a look at announcements on Q P lab at m i t dot eu. So if you look at these machine learning applications, look under the hood. You see that a common feature is that they used these artificial neural networks or a and ends where you have an input layer of, let's say, and neurons and values that is connected to the first layer of, let's Say, also and neurons and connecting the first to the second layer would, if you represented it biomatrix requiring and biomatrix that has of order and squared free parameters. >>Okay, now, in traditional machine learning inference, you would have to grab these n squared values from memory. And every time you do that, it costs quite a lot of energy. Maybe you can match, but it's still quite costly in energy, and moreover, each of the input values >>has to be multiplied by that matrix. And if you multiply an end by one vector by an end square matrix, you have to do a border and squared multiplication. Okay, now, on a digital computer, you therefore have to do a voter in secret operations and memory access, which could be quite costly. But the proposition is that on a photonic integrated circuits, perhaps we could do that matrix vector multiplication directly on the P. I C itself by encoding optical fields on sending them through a programmed program into parameter and the output them would be a product of the matrix multiplied by the input vector. And that is actually the experiment. We did, uh, demonstrating that That this is, you know, in principle, possible back in 2017 and a collaboration with Professor Marine Soldier Judge. Now, if we look a little bit more closely at the device is shown here, this consists of a silicon layer that is pattern into wave guides. We do this with foundry. This was fabricated with the opposite foundry, and many thanks to our collaborators who helped make that possible. And and this thing guides light, uh, on about of these wave guides to make these two by two transformations Maxine and the kilometers, as they called >>input to input wave guides coming in to input to output wave guides going out. And by having to phase settings here data and five, we can control any arbitrary, uh, s U two rotation. Now, if I wanna have any modes coming in and modes coming out that could be represented by an S u N unitary transformation, and that's what this kind of trip allows you to dio and That's the key ingredient that really launched us in in my group. I should at this point, acknowledge the people who have made this possible and in particular point out Leon Bernstein and Alex lots as well as, uh, Ryan heavily once more. Also, these other collaborators problems important immigrant soldier dish and, of course, to a funding in particular now three entity research funding. So why optics optics has failed many times before in building computers. But why is this different? And I think the difference is that we now you know, we're not trying to build an entirely new computer out of optics were selective in how we apply optics. We should use optics for what it's good at. And that's probably not so much from non linearity, unnecessarily I mean, not memory, um, communication and fan out great in optics. And as we just said, linear algebra, you can do in optics. Fantastic. Okay, so you should make use of these things and then combine it judiciously with electronic processing to see if you can get an advantage in the entire system out of it, okay. And eso before I move on. Actually, based on the 2017 paper, uh, to startups were created, like intelligence and like, matter and the two students from my group, Nick Harris. And they responded, uh, co started this this this jointly founded by matter. And just after, you know, after, like, about two years, they've been able to create their first, uh, device >>the first metrics. Large scale processor. This is this device has called Mars has 64 input mode. 64 Promodes and the full program ability under the hood. Okay. So because they're integrating wave guides directly with Seamus Electron ICS, they were able to get all the wiring complexity, dealt with all the feedback and so forth. And this device is now able to just process a 64 or 64 unitary majors on the sly. Okay, parameters are three wants total power consumption. Um, it has ah, late and see how long it takes for a matrix to be multiplied by a factor of less than a nanosecond. And because this device works well over a pretty large 20 gigahertz, you could put many channels that are individually at one big hurts, so you can have tens of S U two s u 65 or 64 rotations simultaneously that you could do the sort of back in the envelope. Physics gives you that per multiply accumulate. You have just tens of Tempted jewels. Attn. A moment. So that's very, very competitive. That's that's awesome. Okay, so you see, plan and potentially the breakthroughs that are enabled by photonics here And actually, more recently, they actually one thing that made it possible is very cool Eyes thes My face shifters actually have no hold power, whereas our face shifters studios double modulation. These use, uh, nano scale mechanical modulators that have no hold power. So once you program a unitary, you could just hold it there. No energy consumption added over >>time. So photonics really is on the rise in computing on demand. But once again, you have to be. You have to be careful in how you compare against a chance to find where is the game to be had. So what I've talked so far about is wait stationary photonic processing. Okay, up until here. Now what tronics has that also, but it doesn't have the benefits of the coherence of optical fields transitioning through this, uh, to this to this matrix nor the bandwidth. Okay, Eso So that's Ah, that is, I think a really exciting direction. And these companies are off and they're they're building these trips and we'll see the next couple of months how well this works. Uh, on the A different direction is to have an output stationary matrix vector multiplication. And for this I want to point to this paper we wrote with Ryan, Emily and the other team members that projects the activation functions together with the weight terms onto a detector array and by the interference of the activation function and the weight term by Hamad and >>Affection. It's possible if you think about Hamad and affection that it actually automatically produces the multiplication interference turn between two optical fields gives you the multiplication between them. And so that's what that is making use of. I wanna talk a little bit more about that approach. So we actually did a careful analysis in the P R X paper that was cited in the last >>page and that analysis of the energy consumption show that this device and principal, uh, can compute at at an energy poor multiply accumulate that is below what you could theoretically dio at room temperature using irreversible computer like like our digital computers that we use in everyday life. Um, so I want to illustrate that you can see that from this plot here, but this is showing. It's the number of neurons that you have per layer. And on the vertical axis is the energy per multiply accumulate in terms of jewels. And when we make use of the massive fan out together with this photo electric multiplication by career detection, we estimate that >>we're on this curve here. So the more right. So since our energy consumption scales us and whereas for a for a digital computer it skills and squared, we, um we gain mawr as you go to a larger matrices. So for largest matrices like matrices of >>scale 1,005,000, even with present day technology, we estimate that we would hit and energy per multiply accumulate of about a center draw. Okay, But if we look at if we imagine a photonic device that >>uses a photonic system that uses devices that have already been demonstrated individually but not packaged in large system, you know, individually in research papers, we would be on this curve here where you would very quickly dip underneath the lander, a limit which corresponds to the thermodynamic limit for doing as many bit operations that you would have to do to do the same depth of neural network as we do here. And I should say that all of these numbers were computed for this simulated >>optical neural network, um, for having the equivalent, our rate that a fully digital computer that a digital computer would have and eso equivalent in the error rate. So it's limited in the error by the model itself rather than the imperfections of the devices. Okay. And we benchmark that on the amnesty data set. So that was a theoretical work that looked at the scaling limits and show that there's great, great hope to to really gain tremendously in the energy per bit, but also in the overall latency and throughput. But you shouldn't celebrate too early. You have to really do a careful system level study comparing, uh, electronic approaches, which oftentimes happened analogous approach to the optical approaches. And we did that in the first major step in this digital optical neural network. Uh, study here, which was done together with the PNG who is an electron ICS designer who actually works on, uh, tronics based on c'mon specifically made for machine on an acceleration. And Professor Joel, member of M I t. Who is also a fellow at video And what we studied there in particular, is what if we just replaced on Lee the communication part with optics, Okay. And we looked at, you know, getting the same equivalent error rates that you would have with electronic computer. And that showed that that way should have a benefit for large neural networks, because large neural networks will require lots of communication that eventually do not fit on a single Elektronik trip anymore. At that point, you have to go longer distances, and that's where the optical connections start to win out. So for details, I would like to point to that system level study. But we're now applying more sophisticated studies like this, uh, like that simulate full system simulation to our other optical networks to really see where the benefits that we might have, where we can exploit thes now. Lastly, I want to just say What if we had known nominee Garrity's that >>were actually reversible. There were quantum coherent, in fact, and we looked at that. So supposed to have the same architectural layout. But rather than having like a sexual absorption absorption or photo detection and the electronic non linearity, which is what we've done so far, you have all optical non linearity, okay? Based, for example, on a curve medium. So suppose that we had, like, a strong enough current medium so that the output from one of these transformations can pass through it, get an intensity dependent face shift and then passes into the next layer. Okay, What we did in this case is we said okay. Suppose that you have this. You have multiple layers of these, Uh um accent of the parameter measures. Okay. These air, just like the ones that we had before. >>Um, and you want to train this to do something? So suppose that training is, for example, quantum optical state compression. Okay, you have an optical quantum optical state you'd like to see How much can I compress that to have the same quantum information in it? Okay. And we trained that to discover a efficient algorithm for that. We also trained it for reinforcement, learning for black box, quantum simulation and what? You know what is particularly interesting? Perhaps in new term for one way corner repeaters. So we said if we have a communication network that has these quantum optical neural networks stationed some distance away, you come in with an optical encoded pulse that encodes an optical cubit into many individual photons. How do I repair that multi foot on state to send them the corrected optical state out the other side? This is a one way error correcting scheme. We didn't know how to build it, but we put it as a challenge to the neural network. And we trained in, you know, in simulation we trained the neural network. How toe apply the >>weights in the Matrix transformations to perform that Andi answering actually a challenge in the field of optical quantum networks. So that gives us motivation to try to build these kinds of nonlinear narratives. And we've done a fair amount of work. Uh, in this you can see references five through seven. Here I've talked about thes programmable photonics already for the the benchmark analysis and some of the other related work. Please see Ryan's poster we have? Where? As I mentioned we where we have ongoing work in benchmarking >>optical computing assed part of the NTT program with our collaborators. Um And I think that's the main thing that I want to stay here, you know, at the end is that the exciting thing, really is that the physics tells us that there are many orders of magnitude of efficiency gains, uh, that are to be had, Uh, if we you know, if we can develop the technology to realize it. I was being conservative here with three orders of magnitude. This could be six >>orders of magnitude for larger neural networks that we may have to use and that we may want to use in the future. So the physics tells us there are there is, like, a tremendous amount of gap between where we are and where we could be and that, I think, makes this tremendously exciting >>and makes the NTT five projects so very timely. So with that, you know, thank you for your attention and I'll be happy. Thio talk about any of these topics

>>From the cube studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is a cute conversation. Welcome to this cube conversation. I'm Lisa Martin pleased to be joined once again by the co CEO of mem sequel, Raj Verma, Raj, welcome back to the program. >>Thank you very much, Lisa. Great to see you as always. >>It's great to see you as well. I always enjoy our conversations. So why don't you start off because something that's been in the news the last couple of months besides COVID is one of your competitors, snowflake confidentially filed IPO documents with the sec a couple months ago. Just wanted to get your perspective on from a market standpoint. What does that signify? >>Yeah. Firstly, congratulations to the snowflake team. Uh, you know, I've, I have a bunch of friends there, you know, John McMahon, my explosives on the board. And I remember having a conversation with him about seven years ago and it was just starting off and I'm just so glad for him and Bob Mobileye. And, and as I said, a bunch of my friends who are there, um, they're executed brilliantly and, uh, I'm thrilled for that. So, um, we are hearing as to what the outcomes are likely to be. And, uh, it just seems like, uh, you know, it's going to be a great help. Um, and I think what it signifies is firstly, if you have a bit technology and if you execute well, good things happen and there's enough room for innovation here. So that is one, the second aspect is I think, and I think more importantly, what it signifies is a change of thought in the database market. >>If you really see, um, and know if my memory serves me right in the last two decades or probably two and a half buckets, we just had one company go public in the database space and that was Mongo. And, um, and that was in, I think October, 2017 and then, uh, two and a half years. So three years we've seen on other ones and uh, from the industry that we know, um, you know, there are going to be a couple that are going to go out in the next 18 months, 24 months as well. So the fact is that we had a, the iron grip on the database market for almost, you know, more than two decades. It was Oracle, IBM that a bit of Sybase and SAP HANA. And now there are a bunch of companies which are helping solve the problems of tomorrow with the technology of the month. >>And, uh, and that is, um, that is snowflake is a primary example of that. Um, so that's a, that's good change. God is good. I do think the incumbents are gonna find it harder and harder going forward. And also if you really see the evolution of the database market, the first sort of workloads that moved to the cloud with the developer workloads and the big benefactor that that was the no secret movement and one company that executed in my opinion, the best was Mongol. And they were the big benefactor of that, that sort of movement to the cloud. The second was the very large, but Moisey database data warehouse market, and a big benefactor of that has been snowflake big queries, the other one as well. However, the biggest set of tsunami of data that's we are seeing move to the cloud is the operational data, which is the marriage of historical data with real time data to give you real time insights as, or what we call the now are now. >>And that's going to be much, much bigger than, uh, than both the, you know, sequel or the developer data movement and the data warehouse. And we hope to be a benefactor of that. And then the shake up that happens in the database market and the change that's happening there, isn't a vendor take on market anymore, and that's good because you don't then have the stranglehold that Oracle had and you know, some of the ways that are treated as customers and help them to run some, et cetera, um, yeah. And giving customers choice so that they can choose what's best for the business is going to be, it's going to be great. And me are going to see seven to 10 really good database companies in large, in the next decade. And we surely hope them secret as one of them of, we definitely have the, have the potential to be one of them. >>You have the market, we have the product, we have the customers. So, you know, as I tell my team, it's up to us as to what we make of it. And, um, you know, we don't worry that much about competition. You did mention snowflake being advantage station. We, yeah, sure. You know, we do compete on certain opportunities. However, their value proposition is a little more single-threaded than ours. So they are more than the Datavail house space are. Our vision of the board is that, uh, you know, you should have a single store for data, whether it's database house, whether it's developer data or whether it's operational data or DP data. And, uh, you know, watch this space from orders. We make somebody exciting announcements. >>So dig into that a little bit more because some of the news and the commentary Raj in the last, maybe six weeks since the snowflake, um, IPO confidential information was released was, is the enterprise data warehouse dead. And you just had a couple of interesting things we're talking about now, we're seeing this momentum, huge second database to go public in two and a half bigots. That's huge, but that's also signifying to a point you made earlier. There's, there's a shift. So memes SQL isn't, we're not talking about an EDW. We're talking about operational real time. How do you see that if you're not looking in the rear view mirror, those competitors, how do you see that market and the opportunities? >>Yeah, I, I don't think the data warehouse market is dead at thought. I think the very fact that, you know, smoke makers going out at whatever valuation they go out, which is, you know, tens of billions of dollars is, um, is a testimony to the fact that, you know, it's a fancy ad master. This is what it is. I mean, data warehouses have existed for decades and, uh, there is a better way of doing it. So it's a fancy of mousetrap and, and that's great. I mean, that's way to money and it's clearly been demonstrated. Now what we are saying is that I think that is a better way to manage the organization's data rather than having them categorized in buckets of, you know, data warehouse, data developer, data DP, or transactional data, you know, uh, analytical data. Is there a way to imagine the future where there is one single database that you can quit eat, or data warehouse workloads for operational workloads, for OLTB work acknowledge and gain insights. And that's not a fancier mousetrap that is a data strategy reimagine. And, uh, and that's our mission. That's our purpose in life right now and are very excited about it's going to be hard. It's not, it's not a given it's a hard problem to solve. Otherwise, if you can solve it before we have the, uh, we have the goods to deliver and the talent, the deliberate, and, um, we are, we are trying it out with some very, very marquee customers. So we've been very excited about, >>Well, changing of the guard, as you mentioned, is hard. The opposite is easy, the opposite, you know, ignoring and not wanting to get out of that comfort zone. That's taken the easy route in my opinion. So it seems like we've got in the market, this, this significant changing of the guard, not just in, you know, what some of your competition is doing, but also from a customer's perspective, how do you help customers, especially institutions that have been around for decades and decades and decades pivot quickly so that the changing of the guard doesn't wipe them out. >>Yeah. Um, I actually think slightly differently. I think changing of the guard, um, wiping out a customer is if they stick or are resistant to the fact that there is a change of God, you know, and if they, if they hold on to, as we said in our previous conversation, if you stick onto the decisions of yesterday, you will not see the Sundays of tomorrow. So I do think that, uh, you know, change, you have a, God is a, is a symbolism, not even a symbolism as a statement to our customers to say, there is a better way of doing, uh, what you are doing to solve tomorrow's problem. And then doesn't have to be the Oracles and the BB tools and the psychosis of the world. So that's, that's one aspect of it. The second thing is, as I've always said, you're not really that obsessed about, uh, competition. >>The competition will do what they do. Uh, we are really very focused on having an impact in the shortest period of time on our customers and, uh, hopefully a positive impact. And if you can't do it, then, you know, I've had conversations with a few of them saying, maybe be not the company for you. Uh, it's not as if I have to sort of, software's a good one. I supply to the successful customers in the bag to do the unsuccessful with customers. The fact is that, you know, in certain, certain places there isn't an organizational alignment and you don't succeed. However, we do have young, we have in the last 14 months or so made tremendous investments into really ease of use of flexibility of architecture, which is hybrid and tactile, and that shrinking the total time to value for our customers. Because if I, if I believe you, if you do these three things, you will have an impact, a positive impact on the customer, in the sharpest, uh, amount of time and your Lindy or yourself. And I think that is more important than worrying needlessly about competition. And then the competition will do what they do. But if you keep your customers happy by having a positive impact, um, successes, only amount of time, >>Customers and employees are essential to that. But I like that you talked about customer obsession because you see it all over the place. Many people use it as descriptors of themselves and their LinkedIn profiles, for example, but for it actually to be meaningful, you talked about the whole objective is to make an impact for your customers. How do you define that? So that it's not just, I don't want to say marketing term, but something that everyone says they're customer obsessed showing it right within the pudding. >>It's easy to say we are customer obsessed. I mean, this organization is going to say we don't care about our customer. So, you know, of course we all want our customers to be successful. How do you, that's easy, you know, having a cultural value that we put our customers first is, was easy, but we didn't choose to do that. What we said is how do you have an impact on your customer in the shortest amount of time, right? That is, that is what you have. I'm sequel and Lee have now designed every process in mem sequel to align with that word. If, if that is a decision that we have to make a B essentially lenses through the fact of what is in the best interest of our customer and what will get us to have an impact, a positive impact on the customer in the shortest amount of time, that is a decision, which is a buy decision for us to make. >>A lot of times it's more expensive. It's a, a lot duffel. It stresses the, um, the, the, the organization, um, and the people in it. But that's, uh, that's what you have to do if you are. Um, if you are, you know, as, as they say, customer obsessed, um, it is, it's just a term which is easy to use, but very difficult to put here too. And we want to be a tactic. It right to be, we are going to continue to learn. It's a, it's not a destination, it's a journey. And we continue to take decisions and refine our processes do, as I said, huh, impact on our customers in the shortest amount of time. Now, obsessiveness, a lot of times is seen as a negative in the current society that we live in. And there's a reason for that because the, they view view obsession, but I view obsession and aggression is that is a punishing expression, which is really akin to just being cruel, you know, leading by fear and all the rest of it, which is as no place in any organization. >>And I actually think that in society at large, nothing, I believe that doesn't have any place in society. And then there's something which I dumb as instrumentalists, which is, this is where we were. This is where we are. This is where we are going and how do we track our progress on a daily, weekly, monthly basis? And if we, aren't sort of getting to that level that we believe we should get to, if our customers, aren't seeing the value of dramas in the shortest amount of time, what is it that we need to do better? Um, is that obsession, our instrumental aggression is, is, is what we are all about. And that brings with it a level of intensity, which is not what everyone, but then when you are, you know, challenging the institutions which have, uh, you know, the also has to speak for naked, it's gonna take a Herculean effort to ask them. And, uh, you know, the, the basically believed that instrumental aggression in terms of the, uh, you know, having an impact on customer in the shop to smile at time is gonna get us there. And a, and B are glad to have people who actually believe in that. And, uh, and that's why we've made tremendous progress over the course of last, uh, two years. >>So instrumental aggression. Interesting. How you talked about that, it's a provocative statement, but the way that you talk about it almost seems it's a prescriptive, very strategic, well thought out type of moving the business forward, busting through the old guard. Cause let's face it, you know, the big guys, the Oracles they're there, they're not easy for customers to rip and replace, but instrumental aggression seems to kind of go hand in hand with the changing of the guard. You've got to embrace one to be able to deliver the other, right. >>Yeah. So ducks, I think even a fever inventing something new. Um, I mean, yeah, it just requires instrumental aggression, I believe is a, uh, uh, anchor core to most successful organizations, whether in IP or anywhere else. That is a, that is a site to that obsession. And not, I'm not talking about instrumental aggression here, but I'm really talking about the obsession to succeed, uh, which, uh, you know, gave rise to what I think someone called us brilliant jerks and all the rest of it, because that is the sort of negative side of off obsession. And I think the challenge of leadership in our times is how do you foster the positivity of obsession, which needs to change a garden? And that's the instrumental aggression as a, as a tool to, to go there. And how do you prevent the negative side of it, which says that the end justifies the means and, and that's just not true. >>Uh, there is, there is something that's right, and there's something that's wrong. And, uh, and if that is made very clear that the end does not justify the meanings, it creates a lot of trust between, um, Austin, our customers, also not employees. And when their inherent trust, um, happens, then you foster, as I said, the positive side of obsession and, um, get away from the negative side of obsession that you've seen in certain very, very large companies. Now, the one thing that instrumental aggression and obsession brings to a company is that, uh, it makes a lot of people uncomfortable, and this is what I continue to tell. Um, our, our employees and my audience is, um, you know, be comfortable being uncomfortable because what you're trying to do is odd. And it's going to take a, as I say, a Herculean effort. So let's, uh, let's be comfortable being uncomfortable, uh, and have fun doing it. If there's, uh, how many people get a chance to change, uh, industry, which was dominated by a few bears and have such a positive impact, not only on our estimates, but society at large. And, uh, I think it's a privilege. Pressure is a privilege. And, uh, I'm grateful for the opportunity that's been afforded to me and to my colleagues. And, uh, >>It's a great way. Sorry. That's a great way of looking at it. Pressure is a privilege. If you think about, I love what you said, I always say, get, you know, get comfortably uncomfortable. It is a heart in any aspect, whether it's your workouts or your discipline, you know, working from home, it's a hard thing to do to your point. There's a lot of positivity that can come from it. If we think of what's happening this week alone and the U S political climate changing of the old guard, we've got Kamala Harris as our first female VP nominee and how many years, but also from a diversity angle, from a women leadership perspective, blowing the door wide open. >>It's great to see that, um, you know, we have someone that my daughter's going to look up to and say that, uh, you know, yes, there is, there is a place for us in society and we can have a meaningful contribution to society. So I actually think that San Antonio versus nomination is, um, you know, it's a simple ism of change of God, for sure. Um, I have no political agendas, um, at all. Then you can see how it pans out in November, but the one thing is for sure, but it's going to make a lot of people uncomfortable, a change of God, or this makes a lot of people. And, and, uh, and you know, I was reflecting back on something else and in everything that I've actually achieved, which is, is something I'm proud of. I had to go through a zone, but I was extremely uncomfortable. >>Uh, Gould only happens when you have uncomfortable, um, girl to happens in your conference room. And, um, whether it's, um, you know, running them sequel, uh, or are having a society change, uh, if you stick to your comfort zone, you stick to your prejudices and viruses because it's just comfortable there, there's a, uh, wanting to be awkward. And, uh, and, and I think that that's that essential change of God. As I said, at the cost of repeating myself will make a lot of people uncomfortable, but I honestly believe will move the society forward. And, uh, yeah, I, um, I couldn't be more proud of, uh, having a California San Diego would be nominated and it's a, she brings diversity multicultural. And what I loved about it was, you know, we talk about culture and all the rest of it. And she, she was talking about how our parents who were both, uh, uh, at the Berkeley when she was growing up, we were picking up from and she be, you know, in our, in our prime going to protests and Valley. >>And so it was just, uh, it was ingrained in her to be able to challenge the status school and move the society forward. And, uh, you know, she was comfortable being uncomfortable when she was in that, you know, added that. And that's good. Maybe not. I think we sort of, uh, yeah, I, yeah, let's see, let's see what November brings to us, but, um, I think just a nomination has, uh, exchanged a lot of things and, uh, if it's not this time, it can be the next time, but at the time off the bat, but you're going to have a woman by woman president in my lifetime. Um, that's um, I minced about them, uh, and that's just great. >>Well, I should hope so too. And there's so many, I know we've got to wrap here, but so many different data points that show that that technology company actually, companies, excuse me, with women in leadership position are significantly 10, 20% more profitable. So the changing of the guard is hard as you said, but it's time to get uncomfortable. And this is a great example of that as well as the culture that you have at mem sequel Raja. It's always a pleasure and a philosophical time talking with you. I thank you for joining me on the cube today. >>Thank you me since I'm just stay safe, though. >>You as well for my guest, Raj Burma, I'm Lisa Martin. Thank you for watching this cube conversation.

>> from Austin, Texas. It's Theo Cube, covering pure storage. Accelerate 2019. Brought to you by pure storage. >> Welcome back to the Cube, The leader and live tech coverage. I'm Lisa Martin with David Dante. We got a pretty cool guests coming up next, guys, you may have seen him here on the Q before. He has back Matt Harris, the head of I T for Mercedes AMG, Petronas Motor Sport. Matt, Welcome back. >> Often a >> way got the car over there with excitement. One of the coolest sports I've ever become involved with. Formula One is this incredible mix of technology strategy. All these crazy things you guys that Mercedes have been partners, customers a cure for about what? 45 years? >> 2015. As a customer, we became partners in 2016. >> I wonder if they like to save Mercedes AMG Petunias Motor Sport has had five consecutive years of both constructors championships driver's championships. You're a great position on both for 2019. It was a little bit of a history about the product that you put out on truck every other week and how pure storage is a facilitator of that. >> Yeah, okay, so it's an interest in a story for those that are interested in Formula One, because what you see on the track looks the same. But realistically, every time he goes out, the guarantee will be different. That level of difference could be a simple wing change or configuration, always based on data that we're learning from during a race again. But every week we also have a different car dependent on the track we're going to. So we have two different worlds that basically were to rate on a minute by minute, hour by hour and day by day at the track. But in the factory, that could be the same sort of it oration. But it could also be into weekly or monthly or year for a car. So all of that is based on data. So everything we do is that businesses revolves around data. We never make a change to the car without me now to back it up with empirical knowledge. Even if the driver turns around and tells us they feel something called, they believe something, we will always make sure we have data to back up that decision, So access to data is critical. Compute performance whether it's high performance, compute for our safety, for instance, whether it's for you as an end user, access to data is critical across everything that we do is time critical Time is our currency really as a business if we slow down your job? Generally, that probably means that you've got less time to make the correct decision. Or maybe you have to turn into a guess or a hunch, which that's never a good place to be in our sport. >> No, I would think not. >> I've I recall, from our conversation last year their rules that say, How many people you can have in your entourage like 60. I think it was yes, and at the time I think you said you got, like, 15 Allocated to data. Is that ratio kind of still holding? I >> still exactly the same in our tracks. On environment, they're still the same in the factory. We have more than that, depending on how many people on what time of day, what day of the week. So on a Friday race day, practice day, we can have a minimum. There'll be 30 people in our race support room will be looking at data along with those other 15. But you can have the whole Aargh department or design department or logistics. Whoever could still be looking at data from the track real time, so we can have as many as 4 to 500 looking at data if they want to. And if that's the right thing going on earlier in the season, you generally get more people looking As the season goes on. It's probably more aargh focused, maybe mechanically if we got something new, or maybe the engine division again in a completely separate building in the U. K 40 miles apart, they've got another set of people that will be looking and trolling through data riel time from the but looking really at the power unit rather than the chassis side. >> And you're generating, like roughly half a terabyte a weekend on a race weekend. Is that still about the same? Or is that growing a car >> perspective? It's just under half a terabyte, but we produce up to another half a terabyte of other supporting data with that GPS data, weather data, video, audio, whatever it would be other information to help with the strategy side of things So we're around 77 50 to 1 terabyte for race weekend, >> and each car has about 300 sensors. I think when we spoke with you last year, or maybe you're half ago is about 200 so that's increasing in terms of all the data being captured every race weekend. But one of the things that I love that matter sizes, you know, we're idea at Mercedes is not that unlike I t at other groups who really rely on high performance systems. But you do put out a new product every two weeks and this really extreme range of conditions, your product is extremely expensive as pretty sexy. Like the portability factor. You have to set up a tea shop, have any 20 weekends a year and set it up in what, 36 hours and take it down in six. >> And a nine year old joke about the taking it down in six is a bit like a Benny Hill sketch. It's obviously choreographed and, well, well rehearsed, but we have all the same systems as any normal business would have the tracks. That environment is very different, though we don't have air conditioning in so all the IittIe equipment has to work at the natural ambient air temperature of the country. We're in this year. Believe it or not, Germany and hungry have been our biggest challenge. We've had for the last 43 to 4 years because they had 45 degree air ambient air temperature. So forget humidity for a minute, which is Another kettle of fish probably affects us a bit more, maybe, than the systems, but we're only chucking that air as fast as we can across the components. So we're not putting any cooling into what is probably around the tolerance of most I T systems. So we have to rely basically on air throughput to terminate. Keep kit. Cool. Now the benefit with pure is actually doesn't create any heat, either. There's no riel heat generation, so it's quite tolerant, which helps us get it doesn't create Maur, but the environment we put it into is quite special. But what we're doing is what any business would want to do. Access toe email file systems. What we're trying to do is give it in a performance fashion. People need to make a decision. So in qualifying, for instance, those 300 sensors. That information that we've got from the car, we've got minutes to make a decision based on data. If it takes you too long to get the data off, you can't then look at the data to make a decision. So we have to make sure data in just from the car and then basically multi access from everybody in the factory or the track side is performance enough to make a decision before the car goes back out again. Otherwise, we're wasting track time. >> So you've always had data in this business. Early days was all analog, and it obviously progressed and thinking about what you want to do, Going forward with data. What kind of information or capabilities don't you have? Where that technology in the future could address >> s so interesting. One is technology of the future. If you know what it is, let me know with what we know right now, I think a lot of it's gonna be about having the ability to have persistent storage. But actually the dynamic of the compute resource eso looking at things like kubernetes or anything like that to turn around and have dynamic resource spin up as and when required to do high performance computer calculations based on the data, maybe to start giving us some automated information, I'm gonna be careful of the M l A. I is for our businesses, it's not quite as simple as others because our senior management very technically capable, and they just see it as advanced statistical analysis. So unless you program, it is not gonna give you an answer. Now we've started to see some things this year were actually the computer is teaching us things we didn't ask it to. So we have got some areas where we're beginning to learn that. That's not necessarily the case now, but for us that access to data moving forward, it's probably gonna be compute. Combined with that underlying storage platform, there's going to be critical onstage. You you heard Robin people talking about the ability to have that always present storage layer with the right computer. That's something for us is going to be critical, because otherwise we're gonna waste money and have resource sat doing nothing. >> Is security >> an issue for you? I mean, it's an issue for everybody, but there isn't a game of honor because you got this, you know, little community that you guys trying to hack each other systems. >> So it's an interesting one inside the sport, Actually, no. Because a few years ago there was a very high profile case where data went between two teams and there was £100 million fine's exclusion from the sport for a season. So that's that's >> too big. You don't mess with that. >> But also, if you think of that from our perspective, we've got the Daimler star on here. We cannot afford to have any of that Brenda brand reputational rubbing off on Damon's. So that's a no no other teams I can't talk for. But we're all fairly sensible between ourselves. What will be interesting moving forward is what technologies air in our sport, but actually of the whether their motor manufacturers or not, is their technology in there that they're interested in. Maybe the battery technology from the power unit side of things is that the power unit itself. So are other things actually more interesting to those other >> places. It legal for you, you know, by the rules of sports, a monitor, just data or captured data, whether it's visual, whatever from your competitors. Eso anything, >> this public? Yes, it's fair game. Okay, so we get given all the teams. Actually, we get a standard set of three or four different streams of information around GPS timing on some video feeds and audio feeds on their publicly consumable by the team's. When I say public for a second on those feeds, we can do what we like. You know that there for us to infer information, which we do a lot off, is what helps our strategy team to turn around and actually predict what we might or might not need to do as far as a pit stop or tire degradation. >> And that's where the human element must come into understanding the competent, like to football coaches who who know each other right? >> Well, yes. And now, if you think if you add to that the human element off Well, what happens if one team strategy person changes? Are they gonna make a different call based on the same data? Is their hunch different? Do they think they know better within a team? You can have that discussion. So what happens in another team where they're cars, not as performance so their mindset. Maybe they're thinking differently. Or maybe a team's got the most performance car of the moment and they think that they're going to do X. And we're like, Well, we're gonna do something different than to try and actually catch them out. So do we. Now don't do the normal thing. >> So let's hope >> Gamification I love it. >> Let's look at all. Make a prediction. 2019 is gonna be another Mercedes AMG way. So at the end of the season, all of the data that you have collected from the cars, all the sensors, all the weather data, GPS, et cetera how does pure facilitate in the off season the design of the 2020 car, for example, Where does where does things like computational fluid dynamics? >> Okay, so all of our production data is on pure, whether it's on a ray or blade somewhere, it's on pure storage across the site. So they're involved. Whether you're talking about design, whether you're talking about final element analysis for hyper a ll, the C f. D. Using high performance computer systems, everything some pure so from that point of view, is making sure we're using the right resource in the right place to get the best performance. Now, see if he's an interesting one because we're regulated by the F A a. About the amount of compute that weaken you. He's now. Because of that, you want it to be as efficient as you possibly can. It's not speed but the efficient use off CPU time. So if a CPU is waiting for data, that's wasted, Okay, so for us, it's trying to make sure that whole ecosystem is as efficient as we can. That's obviously an integral part of everything we do, so whether we're wind tunnel testing, whether we're in the dino, the simulators, but everything basically comes back to trying to understand and correlate the six or seven different places we generate data, trying to make sure that when there's a change in the simulator, we understand that change in the real world or in a diner or in safety. So all of that, what pure do is allow us to have that single place to go and look how I perform and always available. And for me, I don't have to have a story. Jasmine. Yeah, we've got a team of people that actually are thinking about that for us at Pure, You know, there is invested in us these days. Yeah, I walk around here, I'm very fortunate. I get to see all of the senior guys here and there. They are asking me what's going on and how's things with sequel Oracle Because they know exactly what we're doing and they're they're trying to say what's coming. So things like object engine Pierre So we've been talking to pure about using that over the coming months. But what? We're not having it at the moment. Go out and learn it. Actually, they coming in and they're telling us all about it. So they become a virtual extension to my team, which is just amazing. >> Yeah, far more efficient. You're able to focus on a much more things that drive value for the business. As we look at some of the things like the Evergreen business model. What were some of the big ah ha we hear is the right solution for us back in 2015. Is that >> so? Evergreen and love. Your stories were two things at the time that we're just incredible for us because love your storage was basically you could have an array and basically you could use it. And there was no commitment, no anything. But if you like that, you could keep it, obviously, paying for it. Ah, nde. When we did that in the factory, basically, within a week of being in there that the team were like, Whoa, hang on, that's going nowhere. So that was That was a nice, easy one. But Evergreen was an interesting one, which has only really, truly for me. I've always bought into it. But the last probably 18 months we've used it time and time and time again because the improvements with the speed of light x 90 coming envy Emmy drives. When we were looking at capacity, what we did was we turned round and said, Well, actually, we can buy more dense units in the next 90 so we're only buying the extra capacity, but we were getting new technology. So nations, all the innovation that you're putting into their products were getting it. So today, when they were talking about the memory based access, and if your things always sat there going, I can use that. Oh, and there's no there's no work for me, there's no effort. The only thing I gotta worry about is whether I've got capacity for that. Those modules to go in. So Evergreen has worked several times because I don't have to go back to the cap export and go. Could I have another x £1,000,000 please? Why? I need some more storage. Yeah, but you bought some of the other day. Yeah, well, that one. I need to get rid of it because I need a bigger one. And I don't have to do that. Now. I just go in. I'm telling them what the increases for which actually, they can choose Then if they want to increase, they know what the business benefit is rather than just I t has got to turn around and either replace it because of age or the new version doesn't support is not an uplift, not upgrade from the old. One >> I've seen was looking at some of your stats and the case study that's currently online on. Imagine these numbers have gone up 68% reduction in data center Rackspace and saving £100,000 a year and operating costs >> those that would have been probably two years ago. Ish roughly those figures. And the operating cost is a huge improvement for us. Cap Ex is probably the biggest one for me. They were moving forward with cost caps coming into Formula One. That type of thing is gonna be invaluable. Does not happen to do a forklift upgrade of your storage. Well, I wouldn't know what I would do if I had to upgrade what I now own from pure I can't even imagine what? I don't want to turn around town my bosses what that's >> gonna cost. Well, it sounds like you really attacked the op X side with R and D with pure r and D. I kind of like that shifting, you know, labor toe are Andy because you don't want to spend labour on managing storage a raise, make no sense for your business. Okay. What do you want? Pure toe spend? R and D are now, what problem can they saw for? You mean >> so racy is gonna help If I'm really honest, that's actually is gonna help fill a whole quite well for us because we weren't really sure what to put some of that less hot data we were like, Well, where we going to start to put this now? Because we were beginning to fill up the array and the blades. Actually, with a racy no, we can actually use that different class of storage actually, to keep it still online. Still be out to do some machine learning A. I in the future when that comes around. But actually I can now have Maur longevity out of my existing array and blades. So that's brilliant and coming, I think, having I need to be careful, I know some things that are coming. Uh, the active sinking array is brilliant, and we've been using that since it came out. Having that similar or same ability in Blade when it comes will be a very advantageous having those played enclosures. We've gone to multi chassis flash played over the last six weeks, so that for us is great. Once we can start to synchronize between those two, then that's ah, that's another big one for us, for resiliency, for fault, tolerance, but also workload movement. That thing I said about persistent stories, layer, I'm not gonna need to care where it is, and it will be worked out by the storage in the orchestration layer so it can have the storage in the computer in the right place. >> Wow. Great story, Matt, as always. And I think it's Pierre calls this the unfair advantage coming to life. Best of luck for the rest of the 2019 season. >> I'll take it. >> All right, We'll see you next time. >> Thank you. >> Keep before >> for David Dante. I am Lisa Martin. You're watching the Cube from Cure Accelerate in Austin, Texas.

>> Hey, welcome back. You're ready, Jeff? Rick! Here with the Cube were Oracle Park recently, A T and T Park just renamed. It's a beautiful day home in San Francisco Giants. They're on the road. We're here at a pretty interesting event is called Sports Tech. Tokyo World Demo Day brought together a coalition of about 100 startups. 25 of them are given demos today on technology as it relates to sports. But even more importantly, that can then be used in other in others. Beyond sports. We're excited to have an athlete on not just another tech crazy guy. He's Brendan Harris. He's an athlete in residence at 76 Capital. Brendan. Thanks for stopping by. >> Thanks for having me. >> So what is the effort, Principles and entrepreneur in residence? Where is the athlete residents do? It is >> essentially a play on the entrepreneur in residence. I was introduced to 76 Capital finished playing in 15 and I was doing my MBA at Warden and in Philly and got introduced Thio Wayne and the guys at 76. And they are kind of putting together an athlete venture group. Whether they're bringing in a lot of athletes don't wannabe investors and kind of providing them access to deal >> flow and >> um, >> and then also leveraging their social capital. So, uh, he was He was kind of tickled when he came when he coined the term athlete residents and he threw it on my business card. And and that's where we're at, >> right? So I'm just curious your perspective as an athlete as you look around at all the technology that's going into sports, right? Kind of the big categories are, you know that which helps the players play better. There's that which helps the people run, the team's better. And then there's that, which is really kind of part of the fan experience. I mean, you actually to go down and try to put wood on a ball coming at you in 90 plus miles an hour. All this other stuff. Do you see it as is it interesting is distraction. Is it entertaining? I mean, how do you look at it from an athlete's perspective? >> So yeah, so a lot to impact. So first of all, I have this ah, equally the equal view of fascination and frustration where a lot of this wasn't he wasn't around when I when I was playing it, certainly from the field. Now we're taking in things like recovery and rest and sleep. Ah, but I think players and me personally are fascinated with How can we improve on field performance? And I think baseball. It's such a perfect game and you fail so often, being able to turn to turn things that were previously subjective and applied data and in tech to make them objective and give you answers. I think it's fascinating and the ways that we can use data to to kind of promote performance and health and and all those things air Very fascinating. So from players, point of view, we're all about it. But at the same time, I think it certainly says why I've loved to get into sports. Tech is there's a lot of data that's just noise that's coming in and things. And so the tough part is, um, kind of weeding through and what is actionable info on what can actually help improve the on field performance? And then along with that, you know, we want to feel the product on the field, but also what the service is for the consumer and the fans are. And how can we improve that and then engage them? Because certainly sports are part of the culture and part of life now, and it's fascinating. These fans want to know more and more and more, certainly what's going >> on. And it's been It's been a >> great journey, >> right? So on the fan experience specifically, and we've been we've been here a number of years. Bill Styles, a good friend of mine off another word and other work. Brad and and, you know, talking about high density WiFi and you know the app on your phone and delivered, you know, food delivered to your seats. I mean, >> as a as an >> athlete on the field. Do you look at kind of all these things is as a distraction. Do you appreciate? It's kind of a more competitive environment these days in terms of people's attention and kind of that entertainment dollar. But I would imagine from between the lines it looks like Hey, you know, the game's down here people. It's been >> interesting because, um, you know, one of the problems of a major league baseball's been trying to address his pace of games right. And if you really look at the data, they're not that much longer. What's different? We're wired differently, right? So our attention spans are short and we're constantly so our technology. So these, you know, guys like Bill, you are trying to leverage that and try to have your food delivered and try to increase the social component. Increased the value in the in venue experience so that you're not only watching the game, but you're socially enjoying at the same time and kind of fill in those gaps. Ah, lot of it is yes on. And I think there's been balls flying into the stands since baseball's been playing, but they need to put the netting up. Has come a lot of times because nobody's watching. Some people aren't not nobody, but a lot of people aren't watching. The games are getting hit with a lot of these foul balls. So there is that component where you know there's there's some unbelievable things are going off on the sides. But um, you know it's baseball is still gonna be kind of very somewhat within within the confines. >> The other piece that I find really interesting on the data side, right? Is there so much data? Right? There's data data data. Obviously, baseball is built on data and arguments about data and conversations about data, but now it's kind of gone to this next Gen with, you know, wins over replacement and all these other things. But sometimes it's funny to me. It feels like they're forgetting the object of the game is to win the game. And it feels like sometimes the metadata has now become more important than the data. Did you win or lose and is not necessarily being used as a predictor for future performance? But it's almost like a standalone game in and of itself. Like we forget. The object is to win the game and win a championship, not to have the highest war number views since that frustration is that sound? Yeah, I think what you're getting >> into a lot of times is our know how are we making decisions right? And in the game? A lot of times people forget that human beings are out there performing and so I think that's how we've gotten into Moneyball 2.0, looking at development and certainly mental health in focus and game preparation have come into play more and you're seeing some managers. I mean, Mickey Callaway just came out and said 80% my, you know, Susan's go against the data, which which I thought was a little bit interesting, but, ah, so there is that fine line right where you have to filter in what's noise and what's actionable. And at the same time, um, you know, allow you know, your managers and your decision makers some flexibility to go with, You know, they're they're in the heat of the battle and they kind of know their guys. And they know the human element that's involved. So it's it's an interesting, you know, trying to balancing act, >> right? So from your from your new job in your new role, what are some of the things you hope to see today? What are some things that you're excited about? Um, you know, from kind of an investor. And having played the game as well. As you know, I'm looking forward to the evolution of sports. Two >> things specifically how the, uh certainly bias the performs on the field in the human element. And certainly everybody wants workout secrets, and I don't feel like it's whether it's athletes or the kind of weekend warrior or people that are, you know, kind of your senior citizens. And I don't think it's a simple as this has worked, and you should do this. It's a very personalized experience now. And I think some of this personalized digital fitness is fascinating to me on and then how it relates to and how your body relates to, you know, your diet and nutrition, your sleep, your recovery. I think all those air fascinating that, uh, advances that I want to look into more. And the second is a CZ, I kind of mentioned is the fan engagement aspect. How do we drive those those fans that digital, >> um, and >> make it actionable and monetize, right? So that you know, you have your fans that are following you know, your Facebook, twitter and all those things. And so how do you not only gauge them, but collect that data and then kind of personalized that experience? Engage your fan in a way that can kind of grow your brand. Yeah, it's interesting to me, >> really interesting to have to have your perspective, and I'm sure will be a great day and you see all kinds of crazy stuff. So thanks for taking a few minutes. >> Yeah, Any time. >> All right. He's Brendan. I'm Jeff. You're watching The Cube were at Oracle Park in San Francisco. Thanks for watching. We'll see you next time.

(upbeat music) >> Hey welcome back everybody, Jeff Rick here with theCUBE. We're at Oracle Park, recently AT&T Park just renamed, it's a beautiful day. Home of San Francisco Giants, they're on the road, we're here at a pretty interesting event, it's called Sports Tech Tokyo World Demo Day, brought together coalition of about 100 startups. 25 of them are giving demos today on technology as it relates to sports but even more importantly, that can then be used in others beyond sports. We're excited to have an athlete on, not just another tech, crazy guy. He's Brendan Harris, he's an athlete and resident at SeventySix Capital. Brendan, thanks for stopping by. >> Thanks for having me. >> So what is that, I've heard principles and entrepreneur residence\\\, what does a athlete residence do? >> It is essentially a play on the entrepreneuring residence. I was introduced to SeventySix Capital, I finished playing at 15 and I was doing my MBA at Wharton and in Philly, and got introduced to Wayne and the guys at SeventySix and they are kind of putting together an athlete venture group where they're bringing in a lot of athletes that want to be investors and kind of providing them access to deal flow. And then also leveraging their social capitals, so, he was kind of tickled when he coined the term athlete in residence and threw it on my business card and that's where we're at. >> Right so I'm just curious, your perspective as an athlete as you look around at all the technology that's going into sports, right. Kind of the big categories are that which helps the players play better, there's that which helps the people run the teams better, and then there's that which is really kind of part of the fan experience, I mean, you actually had to go down and try to put wood on a ball coming at you 90 plus miles an hour, all this other stuff, do you see it as interesting, is it a distraction, is it entertaining? How do you look at from an athlete's perspective? >> So, yeah, so a lot to impact, so, first of all, I have this equal view of fascination and frustration where a lot of this wasn't around when I was playing, certainly from the field, now we're taking in things like recovery and rest and sleep, but I think players and me personally, are fascinated with how can we improve on field performance and I think baseball's such an imperfect game and you fail so often. Being able to turn things that were previously subjective and apply data and tech to make them objective and give you answers, I think it's fascinating. The ways that we can use data to kind of promote performance and health and all those things are very fascinating. So from a player's point of view, we are all about it but at the same time, I think this is why I've loved to get into sports tech is there's a lot of data that's just noise that's coming in and things and so the tough part is kind of weeding through and what is actionable info and what can actually help improve beyond field performance and then, along with that, we want to feel the product on the field, but also what what the services for the consumer and the fans are and how can we improve that and then engage them because certainly sports are a part of the culture and part of life now and it's fascinating, these fans want to know more and more and more, certainly what's going on and it's been a great journey. >> Right so on the fan experience specifically, we've been here a number of years, Bill Styles' a good friend of mine, and another Wharton grad. And talking about high density WiFi and the app on your phone and food delivered to your seat, I mean as an athlete on the field, do you look at kind of of all these things as a distraction, do you appreciate it's more competitive environment these days in terms of people's attention and kind of that entertainment dollar but I would imagine from the between the lines it looks like, hey, the game's down here people. >> Yeah. (laughing) It's been interesting because one of the problems major league baseball's been trying to address is pace of games right? And if you really look at the data, they're not that much longer. What's different, we're wired differently, right? So our attention spans are shorter and we're constantly addicted to our technology. So these guys like Bill, are trying to leverage that and try to have your food delivered and try to increase the social component, increase the value in the in-venue experience so that you're not only watching the game but you're social enjoying it at the same time and kind of filling those gaps. A lot of it is, yes, and I think, there has been balls flying into the stands since baseball's been playing but the need to put the netting up has come a lot of times because nobody's watching. Some people aren't, not nobody, but a lot of people aren't watching the games are getting hit with a lot of these foul balls. So there's that component, where there's some unbelievable things are going off on the sides but it's baseball still going to be kind of very similar within the confines of lines. >> The other piece that I find really interesting on the data side right, is there's so much data, right? There's data, data, data. Obviously baseball's built on data and arguments about data and conversations about data. But now it's kind of gone to this next gen with wins over replacement and all these other things, but sometimes it's funny to me. It feels like they're forgetting the object of the game is to win the game and it feels like sometimes the metadata has now become more important than the data. Did you win or lose and it's not necessarily being used as a predictor for future performance but it's almost like a stand alone game in and of itself. We forget the object is to win the game and win a championship, not to have the highest award number. Do you sense that frustration, does that sound like something you see-- >> Yeah, I think what you're getting into a lot of times is how are we making decisions, right and in the game a lot of times people forget that human beings are out there performing and so I think that's how we've gotten into Moneyball 2.0 when looking at development. Certainly mental health in focus and game preparation have come into play more and you're seeing some managers, Mickey Callaway just came out said 80% of my distances go against the data which I thought was a little bit interesting but so there is that fine line where you have to filter in what's noise and what's actionable and at the same time, allow your managers and your decision makers some flexibility to go with they're there in the heat of the battle and they kind of of know their guys and they know the human element that's involved. It's an interesting balancing act. >> Right so from your new job and your new role, what are some of the things you hope to see today, what are somethings that you're excited about from an investor and in having played the game as well as looking forward to the evolution of sports? >> Two things, specifically how the, I'm certainly biased to the performance on the field, and the human element and certainly, everybody wants workout secrets and I don't feel like it's, whether it's athletes or the kind of weekend warrior or people that are senior citizens. I don't think it's as simple as, this is work and you should do this, it's a very personalized experience now and I think some of this personalized digital fitness is fascinating to me and then how it relates to and how your body relates to your diet, your nutrition, your sleep, your recovery, I think all those are fascinating that advances that I want to look into more. And then second is, as I kind of mentioned, is the fan engagement aspect and how do we drive those fans, that digital, and make it actionable and monetized, right. So that you have your fans that are following your Facebook, your Twitter, and all those things and so how do you, not only engage them but collect that data and then kind of personalize that experience, engage your fan in a way that can kind of grow your brand. It will be interesting to me. >> Really interesting to have your perspective and I'm sure it will be a great day and you'll see all kind of crazy stuff. So thanks for taking a few minutes. >> Yeah, anytime, thanks for having me. >> All right, he's Brendan, I'm Jeff, you're watching theCUBE. We are at Oracle Park in San Francisco, thanks for watching, we'll see you next time. (upbeat music)

>> Live from Stanford University. It's the Cube covering global Women in Data Science conference brought to you by Silicon Angle media. >> Welcome back to the Cubes. Continuing coverage of the fourth annual Women and Data Science Conference with Hashtag with twenty nineteen to join the conversation. Lisa Martin joined by one of the speakers on the career panel today at Stanford. Natalie Evans Harris, the cofounder and head of strategic initiatives at right hive. Natalie. It's a pleasure to have you on the program so excited to be here. Thank you. So you have, which I can't believe twenty years experience advancing the public sectors. Strategic use of data. Nearly twenty. I got more. Is your career at the National Security Agency in eighteen months with the Obama administration? You clearly were a child prodigy, of course. Of course, I was born in nineteen ninety two s. So tell me a little bit about how you got involved with was. This is such an interesting movement because that's exactly what it is in such a short time period. They of a mask. You know, they're expecting about twenty thousand people watching the live stream today here from Stanford. But there's also fifty plus countries participating with one hundred fifty plus a regional events. You're here on the career panel. Tell me a little bit about what attracted you to wits and some of the advice and learnings that you're going to deliver this afternoon. Sure, >> absolutely So Wits and the Women and Data Science Program and Conference on what it's evolved to are the exact type of community collective impact initiatives we want to say. When we think about where we want data science to grow, we need to have diversity in the space. There's already been studies that have come out to talk about the majority of innovations and products that come out are built by white men and built by white men. And from that lens you often lose out on the African American experience or divers racial or demographic experiences. So you want communities like women and data science to come together and show we are a part of this community. We do have a voice and a seat at the table, and we can be a part of the conversation and innovation, and that's what we want, right? So to come together and see thousands of people talking and walking into a room of diverse age and diverse experience, it feels good, and it makes me hopeful about the future because people is what the greatest challenge to data science is going to be in the future. >> Let's talk about that because a lot of the topics around data science relate to data privacy and ethics. Cyber security. But if we look at the amount of data that's generated every day, two point five quintillion pieces of data, tremendous amount of impact for the good. You think of cancer research and machine learning in cancer research. But we also think, Wow, we're at this data revolution. I read this block that you co authored it about a year ago called It's time to Talk About Data Ethics, and I found it so interesting because how how do we get control around this when we all know that? Yes, there is so many great applications for data that were that we benefit from every day. But there's also been a lack of transparency on a growing scale. In your perspective, how do what's the human capital element and how does that become influenced to really manage data in a responsible way? I think that >> we're recognizing that data can solve all of these really hard problems and where we're collecting these quintillion bytes of data on a daily basis. So there's acknowledgment that there's things that humans just can't d'oh so a I and machine learning our great ways to increase access to that data so we can use it to start to solve problems. But we also need to recognize is that no matter how good A I gets, there's still humans that need to be a part of that context because the the algorithms air on Lee as strong as the people that have developed them. So we need data scientist. We need women with diverse experiences. We need people with diverse thoughts because they're the ones we're going to create, those algorithms that make the machine learning and the and the algorithms in the technology more powerful, more diverse and more equal. So we need to see more growth and experiences and people and learning the things that I talk about. When I when others asked me and what I'll mention on the career panel is when you think about data science. It's not just about teaching the technical skills. There's this empathy that needs to be a part of it. There's this skill of being able to ask questions in really interesting ways of the data. When I worked at National Security Agency and helped build the data science program there, every data scientist that came into the building, we, of course taught them about working in our vitamins. But we also made every single one of them take a class on asking questions. The same class that we had our intelligence analyst take so the same ways of the history and the foreign language experts needed to learn how to ask questions of data we needed, Our data scientist told. Learn that as well. That's how you start to look beyond just the ones and zeros and start to really think about not just data but the people that are impacted by the use of the data. >> Well, it's really one of the things I find interesting about data. Science is how diverse on I use that word, specifically because we talked about thought diversity. But it's not just the technical skills as you mentioned. It's empathy. It's communication. It's collaboration on DH those air. So it's such a like I said, Diverse opportunity. One of the things I think I read about in your blawg. If we look at okay, we need to not just train the people on how to analyze the data but howto be confident enough to raise their hand and ask questions. How do you also train the people? >> Two. >> Handle data responsibly. You kind of mentioned there's this notion of sort of like a Hippocratic oath that medical doctors take for data scientist. And I thought that was really intriguing. Tell me a little bit more about that. And how do you think that data scientists in training and those that are working now can be trained? Yeah, influenced to actually take something like that in terms of really individualizing that responsibility for ethical treatment of data. So, towards the >> end of my time at the White House, we it was myself deejay Patil and a number of experts and thought leaders in the space of of news and ethics and data science came together and had this conversation about the future of data ethics. And what does it look like? Especially with the rise of fake news and misinformation and all of these things? And born out of that conversation was just this. This realization that if you believe that, inherently people want to do the good thing, want to do the right thing? How do they do that? What does that look like? So I worked with Data for Democracy and Bloomberg to Teo issue a study and just say, Look, data scientist, what keeps you up at night? What are the things that as you as you build these algorithms and you're doing this? Data sharing keeps you up at night. And the things that came out of those conversations and the working groups and the community of practice. Now we're just what you're talking about. How do we communicate responsibly around this? How do we What does it look like to know that we've done enough to protect the data, to secure the data, to, to use the data in the most appropriate ways? And when we >> see a problem, what do >> we do to communicate that problem and address it >> out of >> that community of practice? And those principles really came the starts of what an ethics. Oh, the Hippocratic oath could look like it's a set of principles. It's not the answer, but it's a framework to help guide you down. Your own definition of what ethical behaviour looks like when you use data. Also, it became a starting point for many companies to create their own manifestos and their own goals to say as a company, these are the values that we're going to hold true to as we use data. And then they can create the environments that allow for data scientists to be able to communicate how they feel about what is happening around them and effect change. It's a form of empowerment. Amazing. I love >> that in the last thirty seconds, I just want to get your perspective on. Here we are spring of twenty nineteen. Where are we as a society? Mon data equaling trust? >> Oh, I love that we're having the conversation. And so we're at that point of just recognizing that data's more than ones and zeroes. And it's become such an integral part of who people are. And so we need some rules to this game. We need to recognize that privacy is more than just virus protection, that there is a trust that needs to be built between the individuals, the communities and the companies that are using this data. What the answers are is what we're still figuring out. I argue that a large part of it is just human capital. It's just making sure that you have a diverse set of voices, almost a brain trust as a part of the conversation. So you're not just going to the same three people and saying, What should we d'Oh But you're growing and each one teach one and building this community around collectively solving these problems. Well, >> Natalie's been such a pleasure talking with you today. Thank you so much for spending some time and joining us on the Cuban. Have a great time in the career panel this afternoon. Atwood's. >> Thank you so much. This is a lot of fun. >> Good. My pleasure. We want to thank you. You're watching the Cube from the fourth annual Women and Data Science Conference alive from Stanford University. I'm Lisa Martin. I'll be back with my next guest after a short break

>> From San Francisco, it's The Cube covering Girls in Tech Catalyst Conference, brought to you by Girls in Tech. >> Hey, welcome back, everybody. Jeff Frick here with The Cube. We're in downtown San Francisco at the Girls in Tech Catalyst Conference 2018. About 700 professionals, mainly women, a couple of men, a couple of busloads of younger people coming in to get inspired. And we're excited to be here. It's a single track event, two days, probably 20 presentations per day of people really sharing their story. And we're excited to have Diana Cappello. She's the lead solutions engineer from Clari. Just before you get into your talk, right? >> Exactly, yes. >> So welcome. >> Thank you. >> So, what's your talk going to be on? >> I'm leading a panel on the topic of innovation. So we've got four amazing women, two co-founders, two product managers. >> Okay, so clearly, diversity of opinion, diversity of thought, diversity of point of view, diversity of problem solving. It's a huge piece of the innovation game. >> Absolutely. And so, that was the challenge for me, is with this broad set of speakers, how do you tie it together in a theme? So we're focusing on emerging technologies. So AI, big data number crunching. >> Right. So it seems to me that the solution to innovation, one of the solutions, there's a couple simple things, one is kind of just give more people access to the data, give more people access to the tools to manipulate the data, and then give more people the access to actually do something once they get the data out of tools on top of the data so they can actually be empowered to make change. And a lot of companies never have done that in the past. But really with the democratization of the data, the tools, and hopefully the control, that's one of the big engines that we see. What do you think? >> That's absolutely the key. So we are thinking of it in the reverse in our panel. What's the problem that you're trying to solve, and then how can you leverage big data and these merging technologies to solve that problem in the real world. >> Right. So how do you, in your day to day life, how do you make sure that you guys are staying innovative? How do you make sure that the quiet voice in the back actually gets heard? Or the person that doesn't necessarily have the social capital, or the title capital, or whatever the capital is to make an influence, that that voice gets added to the conversation? >> So that's my role as a lead solutions engineer, is to listen. The number one thing that we do when we meet a customer is listen to the problems that they're experiencing, and then listen to the goals that they have, the objectives that they want, the outcomes. And then we think about how can we meet their need with the technology. So, number one thing for lead solution engineer, and for anyone else in tech, is listen to your customer. >> You don't just stand up in front and tell them all the great stuff that you do? >> I would love to. (laughing) I could talk all day. >> No, it's so funny, right? 'Cause so many people, that's what they do. Instead, they don't listen. They're just, they're so excited. And I think, especially in a product management role, you see it a lot where people are just so excited, so passionate about the things that they built that sometimes that's all they want to do is just ell that story, and maybe more the story than the customer needs to hear, is ready to hear, or cares about hearing. But really, it's listening that's the more important skill. >> Yep, I mean, we have seven modules in our product. If I showed you all seven, yes, you would find something of value there, but it would be so much more valuable for your time and mine if I showed you that one thing. >> Right. >> In the context of what you want to do with it. >> So shifting gears a little bit, have you been to Catalyst before? >> This is my second one. >> Right. >> I'm really excited to come back two years in a row. Can't wait to come next year. >> So I'm just curious, from a professional point of view, where do you see the value? Obviously, you're excited now. You're participating. To take a minute out of your day job. We're all busy. We have too many emails, and too many meetings, and too many calls, but to really kind of take a break form that and come, and spend a day, and spend time on the panel, how do you find that valuable? >> For me, it's all about career development. I am making connections. I'm learning so much. I got to speak to Parker Harris this morning about AI and applied AI. I would never have had that opportunity if I stayed at my desk. >> Yeah, well, great. So good luck on your panel. >> Thank you. >> And we'll be watching, and hopefully you'll get some good questions. >> She's Diana. I'm Jeff. You're watching The Cube from Catalyst 2018. Thanks for watching. (upbeat music)