(upbeat music) >> Hello, welcome to the Cube's coverage of International Women's Day 2023. I'm John Furrier, host of the CUBE series of profiles around leaders in the tech industry sharing their stories, advice, best practices, what they're doing in their jobs their vision of the future, and more importantly, passing it on and encouraging more and more networking and telling the stories that matter. Our next guest is a great executive leader talking about how to lead in challenging times. Krista Satterthwaite, who is Senior Vice President and GM of Mainstream Compute. Krista great to see you're Cube alumni. We've had you on before talking about compute power. And by the way, congratulations on your BPT and Black Professional Tech Network 2023 Black Tech Exec of the Year Award. >> Thank you very much. Appreciate it. And thanks for having me. >> I knew I liked you the first time we were doing interviews together. You were so smart and so on top of it. Thanks for coming on. >> No problem. >> All kidding aside, let's get into it. You know, one of the things that's coming out on these interviews is leadership is being showcased and there's a network effect happening in the industry and you're starting to see people look and hear stories that they may or may not have heard before or news stories are coming out. So, one of the things that's interesting is that also in the backdrop of post pandemic, there's been a turn in the industry a little bit, there's a little bit of headwind in certain areas, some tailwinds in cloud and other areas. Compute, your area is doing very well. It could be challenging. And as a leader, has the conversation changed? And where are you at right now in the network of folks you're working with? What's the mood? >> Yeah, so actually I, things are much better. Obviously we had a chip shortage last year. Things are much, much better. But I learned a lot when it came to going through challenging times and leadership. And I think when we talk to customers, a lot of 'em are in challenging situations. Sometimes it's budget, sometimes it's attracting and retaining talent and sometimes it's just demands because, it's really exciting that technology is behind everything. But that means the demands on IT are bigger than ever before. So what I find when it comes to challenging times is that there's really three qualities that are game changers when it comes to leading and challenging times. And the first one is positivity. People have to feel like there's a light at the end of the tunnel to make sure that, their attitudes stay up, that they stay working really really hard and they look to the leader for that. The second one is communication. And I read somewhere that communication is leadership. And we had a great example from our CEO Antonio Neri when the pandemic hit and everything shut down. He had an all employee meeting every week for a month and we have tens of thousands of employees. And then even after that month, we had 'em very regularly. But he wanted to make sure that everybody heard from, him his thoughts had all the updates, knew how their peers were doing, how we were helping customers. And I really learned a lot from that in terms of communicating and communicating more during tough times. And then I would say the third one is making sure that they are informed and they feel empowered. So I would say a leader who is able to do that really, really stands out in a challenging time. >> So how do you get yourself together? Obviously you the chip shortage everyone knows in the industry and for the folks not in the tech industry, it was an economic potential disaster, because you don't get the chips you need. You guys make servers and technology, chips power everything. If you miss a shipment, it could cause a lot of backlash. So Cisco had an earnings impact. It has impact to the business. When do you have that code red moment where it's like, okay, we have to kind of put the pause and go into emergency mode. And how do you handle that? >> Well, you know, it is funny 'cause when it, when we have challenges, I come to learn that people can look at challenges and hard work as a burden or a mission and they behave totally different. If they see it as a burden, then they're doing the bare minimum and they're pointing fingers and they're complaining and they're probably not getting a whole lot done. If they see it as a mission, then all of a sudden they're going above and beyond. They're working really hard, they're really partnering. And if it affects customers for HPE, obviously we, HPE is a very customer centric company, so everyone pays attention and tries to pitch in. But when it comes to a mission, I started thinking, what are the real ingredients for a mission? And I think it's important. I think it's, people feel like they can make an impact. And then I think the third one is that the goal is clear, even if the path isn't, 'cause you may have to pivot a lot if it's a challenge. And so when it came to the chip shortage, it was a mission. We wanted to make sure that we could ship to customers as quickly as possible. And it was a mission. Everybody pulled together. I learned how much our team could pull off and pull together through that challenge. >> And the consequences can be quantified in economics. So it's like the burn the boats example, you got to burn the boats, you're stuck. You got to figure out a solution. How does that change the demands on people? Because this is, okay, there's a mission it they're not, it's not normal. What are some of those new demands that arise during those times and how do you manage that? How do you be a leader? >> Yeah, so it's funny, I was reading this statement from James White who used to be the CEO of Jamba Juice. And he was talking about how he got that job. He said, "I think it was one thing I said that really convinced them that I was the right person." And what he said was something like, "I will get more out of people than nine out of 10 leaders on the planet." He said, "Because I will look at their strengths and their capabilities and I will play to their passions." and their capabilities and I will play their passions. and getting the most out people in difficult times, it is all about how much you can get out of people for their own sake and for the company's sake. >> That's great feedback. And to people watching who are early in their careers, leading is getting the best out of your team, attitude. Some of the things you mentioned. What advice would you give folks that are starting to get into the workforce, that are starting to get into that leadership track or might have a trajectory or even might have an innate ability that they know they have and they want to pursue that dream? >> Yeah so. >> What advice would you give them? >> Yeah, what I would say, I say this all the time that, for the first half of my career I was very job conscious, but I wasn't very career conscious. So I'd get in a role and I'd stay in that role for long periods of time and I'd do a good job, but I wasn't really very career conscious. And what I would say is, everybody says how important risk taking is. Well, risk taking can be a little bit of a scary word, right? Or term. And the way I see it is give it a shot and see what happens. You're interested in something, give it a shot and see what happens. It's kind of a less intimidating way of looking at risk because even though I was job conscious, and not career conscious, one thing I did when people asked me to take something on, hey Krista, would you like to take on more responsibility here? The answer was always yes, yes, yes, yes. So I said yes because I said, hey I'll give it a shot and see what happens. And that helped me tremendously because I felt like I am giving it a try. And the more you do that, the the better it is. >> It's great. >> And actually the the less scary it is because you do that, a few times and it goes well. It's like a muscle that builds. >> It's funny, a woman executive was on the program. I said, the word balance comes up a lot. And she stopped and said, "Let's just talk about balance for a second." And then she went contrarian and said, "It's about not being unbalanced. It's about being, taking a chance and being a little bit off balance to put yourself outside your comfort zone to try new things." And then she also came up and followed and said, "If you do that alone, you increase your risk. But if you do it with people, a team that you trust and you're authentic and you're vulnerable and you're communicating, that is the chemistry." And that was a really good point. What's your reaction? 'Cause you were talking about authentic conversations good communications with Antonio. How does someone get, feel, find that team and do you agree with it? And what was your, how would you react to that? >> Yes, I agree with that. And when it comes to being authentic, that's the magic and when someone isn't, if someone's not really being themselves, it's really funny because you can feel it, you can sense it. There's kind of a wall between you and them. And over time people won't be able to put their finger on it, but they'll feel a distance from you. But when you're authentic and you share who you are, what you find is you find things in common with other people. 'Cause you're sharing more of who you are and it's like, oh, I do that too. Oh, I'm interested in that too. And build the bonds between people and the authenticity. And that's what people crave. They want people to be authentic and people can tell when you're authentic and when you're not. >> Is managing and leading through a crisis a born talent or can you learn it? >> Oh, definitely learned. I think that we're born knowing nothing and I once read people are nurtured into greatness and I think that's true. So yeah, definitely learned. >> What are some examples that can come out of a tough time as folks may look at a crisis and be shy away from it? How do they lean into it? What advice would you give folks? How do you handle it? I mean, everyone's got different personality. Okay, they get to a position but stepping through that door. >> Yeah, well, I do this presentation called, "10 things I Wish I Knew Earlier in my Career." And one of those things is about the growth mindset and the growth mindset. There's a book called "Mindset" by Carol Dweck and the growth mindset is all about learning and not always having to know everything, but really the winning is in the learning. And so if you have a growth mindset it makes you feel better about everything because you can't lose. You're winning because you're learning. So when I've learned that, I started looking at things much differently. And when it comes to going through tough times, what I find is you're exercising muscles that you didn't even know you had, which makes you stronger when the crisis is over, obviously. And I also feel like you become a lot a much more creative when you're in challenging times. You're forced to do things that you hadn't had to do before. And it also bonds the team. It's almost like going through bootcamp together. When you go through a challenge together it bonds you for life. >> I mean, you could have bonding, could be trauma bonding or success bonding. People love to be on the success side because that's positive and that's really the key mindset. You're always winning if you have that attitude. And learnings is also positive. So it's not, it's never a failure unless you make it. >> That's right, exactly. As long as you learn from it. And that's the name of the game. So, learning is the goal. >> So I have to ask you, on your job now, you have a really big responsibility HPE compute and big division. What's the current mindset that you have right now in your career, where you're at? What are some of the things on your mind that you think about? We had other, other seniors leaders say, hey, you know I got the software as my brain and the hardware's my body. I like to keep software and hardware working together. What is your current state of your career and how you looking at it, what's next and what's going on in your mind right now? >> Yeah, so for me, I really want to make sure that for my team we're nurturing the next generation of leadership and that we're helping with career development and career growth. And people feel like they can grow their careers here. Luckily at HPE, we have a lot of people stay at HPE a long time, and even people who leave HPE a lot of times they come back because the culture's fantastic. So I just want to make sure I'm contributing to that culture and I'm bringing up the next generation of leaders. >> What's next for you? What are you looking at from a career personal standpoint? >> You know, it's funny, I, I love what I'm doing right now. I'm actually on a joint venture board with H3C, which is HPE Joint Venture Company. And so I'm really enjoying that and exploring more board service opportunities. >> You have a focus of good growth mindset, challenging through, managing through tough times. How do you stay focused on that North star? How do you keep the reinforcement of the mission? How do you nurture the team to greatness? >> Yeah, so I think it's a lot of clarity, providing a lot of clarity about what's important right now. And it goes back to some of the communication that I mentioned earlier, making sure that everybody knows where the North Star is, so everybody's focused on the same thing, because I feel like with the, I always felt like throughout my career I was set up for success if I had the right information, the right guidance and the right goals. And I try to make sure that I do that with my team. >> What are some of the things that you could share as we wrap up here for the folks watching, as the networks increase, as the stories start to unfold more and more on digital like we're doing here, what do you hope people walk away with? What's working, what needs work, and what is some things that people aren't talking about that should be discussed publicly? >> Do you mean from a career standpoint or? >> For career? For growing into tech and into leadership positions. >> Okay. >> Big migration tech is now a wide field. I mean, when I grew up, broke into the eighties, it was computer science, software engineering, and three degrees in engineering, right? >> I see huge swath of AI coming. So many technical careers. There's a lot more women. >> Yeah. And that's what's so exciting about being in a technical career, technical company, is that everything's always changing. There's always opportunity to learn something new. And frankly, you know, every company is in the business of technology right now, because they want to closer to their customers. Typically, they're using technology to do that. Everyone's digitally transforming. And so what I would say is that there's so much opportunity, keep your mind open, explore what interests you and keep learning because it's changing all the time. >> You know I was talking with Sue, former HP, she's on a lot of boards. The balance at the board level still needs a lot of work and the leaderships are getting better, but the board at the seats at the table needs work. Where do you see that transition for you in the future? Is that something on your mind? Maybe a board seat? You mentioned you're on a board with HPE, but maybe sitting on some other boards? Any, any? >> Yes, actually, actually, we actually have a program here at HPE called the Board Ready Now program that I'm a part of. And so HPE is very supportive of me exploring an independent board seat. And so they have some education and programming around that. And I know Sue well, she's awesome. And so yes, I'm looking into those opportunities right now. >> She advises do one no more than two. The day job. >> Yeah, I would only be doing one current job that I have. >> Well, kris, it was great to chat with you about these topics and leadership and challenging times. Great masterclass, great advice. As SVP and GM of mainstream compute for HPE, what's going on in your job these days? What's the most exciting thing happening? Share some of your work situations. >> Sure, so the most exciting thing happening right now is HPE Gen 11, which we just announced and started shipping, brings tremendous performance benefit, has an intuitive operating experience, a trusted security by design, and it's optimized to run workloads so much faster. So if anybody is interested, they should go check it out on hpe.com. >> And of course the CUBE will be at HPE Discover. We'll see you there. Any final wisdom you'd like to share as we wrap up the last minute here? >> Yeah, so I think the last thing I'll say is that when it comes to setting your sights, I think, expecting it, good things to happen usually happens when you believe you deserve it. So what happens is you believe you deserve it, then you expect it and you get it. And so sometimes that's about making sure you raise your thermostat to expect more. And I always talk about you don't have to raise it all up at once. You could do that incrementally and other people can set your thermostat too when they say, hey, you should be, you should get a level this high or that high, but raise your thermostat because what you expect is what you get. >> Krista, thank you so much for contributing to this program. We're going to do it quarterly. We're going to do getting more stories out there, so we'll have you back and if you know anyone with good stories, send them our way. And congratulations on your BPTN Tech Executive of the Year award for 2023. Congratulations, great prize there and great recognition for your hard work. >> Thank you so much, John, I appreciate it. >> Okay, this is the Cube's coverage of National Woodman's Day. I'm John Furrier, stories from the front lines, management ranks, developers, all there, global coverage of international events with theCUBE. Thanks for watching. (soft music)

(uplifting music) >> Hello, welcome back to theCUBE's coverage of CloudNativeSecurityCon, the inaugural event, in Seattle. I'm John Furrier, host of theCUBE, here in the Palo Alto Studios. We're calling it theCUBE Center. It's kind of like our Sports Center for tech. It's kind of remote coverage. We've been doing this now for a few years. We're going to amp it up this year as more events are remote, and happening all around the world. So, we're going to continue the coverage with this segment focusing on the data stack, entrepreneurial opportunities around all things security, and as, obviously, data's involved. And our next guest is a friend of theCUBE, and CUBE alumni from 2013, entrepreneur himself, turned, now, venture capitalist angel investor, with his own firm, Opher Kahane, Managing Director, Sonoma Ventures. Formerly the founder of Origami, sold to Intuit a few years back. Focusing now on having a lot of fun, angel investing on boards, focusing on data-driven applications, and stacks around that, and all the stuff going on in, really, in the wheelhouse for what's going on around security data. Opher, great to see you. Thanks for coming on. >> My pleasure. Great to be back. It's been a while. >> So you're kind of on Easy Street now. You did the entrepreneurial venture, you've worked hard. We were on together in 2013 when theCUBE just started. XCEL Partners had an event in Stanford, XCEL, and they had all the features there. We interviewed Satya Nadella, who was just a manager at Microsoft at that time, he was there. He's now the CEO of Microsoft. >> Yeah, he was. >> A lot's changed in nine years. But congratulations on your venture you sold, and you got an exit there, and now you're doing a lot of investments. I'd love to get your take, because this is really the biggest change I've seen in the past 12 years, around an inflection point around a lot of converging forces. Data, which, big data, 10 years ago, was a big part of your career, but now it's accelerated, with cloud scale. You're seeing people building scale on top of other clouds, and becoming their own cloud. You're seeing data being a big part of it. Cybersecurity kind of has not really changed much, but it's the most important thing everyone's talking about. So, developers are involved, data's involved, a lot of entrepreneurial opportunities. So I'd love to get your take on how you see the current situation, as it relates to what's gone on in the past five years or so. What's the big story? >> So, a lot of big stories, but I think a lot of it has to do with a promise of making value from data, whether it's for cybersecurity, for Fintech, for DevOps, for RevTech startups and companies. There's a lot of challenges in actually driving and monetizing the value from data with velocity. Historically, the challenge has been more around, "How do I store data at massive scale?" And then you had the big data infrastructure company, like Cloudera, and MapR, and others, deal with it from a scale perspective, from a storage perspective. Then you had a whole layer of companies that evolved to deal with, "How do I index massive scales of data, for quick querying, and federated access, et cetera?" But now that a lot of those underlying problems, if you will, have been solved, to a certain extent, although they're always being stretched, given the scale of data, and its utility is becoming more and more massive, in particular with AI use cases being very prominent right now, the next level is how to actually make value from the data. How do I manage the full lifecycle of data in complex environments, with complex organizations, complex use cases? And having seen this from the inside, with Origami Logic, as we dealt with a lot of large corporations, and post-acquisition by Intuit, and a lot of the startups I'm involved with, it's clear that we're now onto that next step. And you have fundamental new paradigms, such as data mesh, that attempt to address that complexity, and responsibly scaling access, and democratizing access in the value monetization from data, across large organizations. You have a slew of startups that are evolving to help the entire lifecycle of data, from the data engineering side of it, to the data analytics side of it, to the AI use cases side of it. And it feels like the early days, to a certain extent, of the revolution that we've seen in transition from traditional databases, to data warehouses, to cloud-based data processing, and big data. It feels like we're at the genesis of that next wave. And it's super, super exciting, for me at least, as someone who's sitting more in the coach seat, rather than being on the pitch, and building startups, helping folks as they go through those motions. >> So that's awesome. I want to get into some of these data infrastructure dynamics you mentioned, but before that, talk to the audience around what you're working on now. You've been a successful entrepreneur, you're focused on angel investing, so, super-early seed stage. What kind of deals are you looking at? What's interesting to you? What is Sonoma Ventures looking for, and what are some of the entrepreneurial dynamics that you're seeing right now, from a startup standpoint? >> Cool, so, at a macro level, this is a little bit of background of my history, because it shapes very heavily what it is that I'm looking at. So, I've been very fortunate with entrepreneurial career. I founded three startups. All three of them are successful. Final two were sold, the first one merged and went public. And my third career has been about data, moving data, passing data, processing data, generating insights from it. And, at this phase, I wanted to really evolve from just going and building startup number four, from going through the same motions again. A 10 year adventure, I'm a little bit too old for that, I guess. But the next best thing is to sit from a point whereby I can be more elevated in where I'm dealing with, and broaden the variety of startups I'm focused on, rather than just do your own thing, and just go very, very deep into it. Now, what specifically am I focused on at Sonoma Ventures? So, basically, looking at what I refer to as a data-driven application stack. Anything from the low-level data infrastructure and cloud infrastructure, that helps any persona in the data universe maximize value for data, from their particular point of view, for their particular role, whether it's data analysts, data scientists, data engineers, cloud engineers, DevOps folks, et cetera. All the way up to the application layer, in applications that are very data-heavy. And what are very typical data-heavy applications? FinTech, cyber, Web3, revenue technologies, and product and DevOps. So these are the areas we're focused on. I have almost 23 or 24 startups in the portfolio that span all these different areas. And this is in terms of the aperture. Now, typically, focus on pre-seed, seed. Sometimes a little bit later stage, but this is the primary focus. And it's really about partnering with entrepreneurs, and helping them make, if you will, original mistakes, avoid the mistakes I made. >> Yeah. >> And take it to the next level, whatever the milestone they're driving with. So I'm very, very hands-on with many of those startups. Now, what is it that's happening right now, initially, and why is it so exciting? So, on one hand, you have this scaling of data and its complexity, yet lagging value creation from it, across those different personas we've touched on. So that's one fundamental opportunity which is secular. The other one, which is more a cyclic situation, is the fact that we're going through a down cycle in tech, as is very evident in the public markets, and everything we're hearing about funding going slower and lower, terms shifting more into the hands of typical VCs versus entrepreneur-friendly market, and so on and so forth. And a very significant amount of layoffs. Now, when you combine these two trends together, you're observing a very interesting thing, that a lot of folks, really bright folks, who have sold a startup to a company, or have been in the guts of the large startup, or a large corporation, have, hands-on, experienced all those challenges we've spoken about earlier, in turf, maximizing value from data, irrespective of their role, in a specific angle, or vantage point they have on those challenges. So, for many of them, it's an opportunity to, "Now, let me now start a startup. I've been laid off, maybe, or my company's stock isn't doing as well as it used to, as a large corporation. Now I have an opportunity to actually go and take my entrepreneurial passion, and apply it to a product and experience as part of this larger company." >> Yeah. >> And you see a slew of folks who are emerging with these great ideas. So it's a very, very exciting period of time to innovate. >> It's interesting, a lot of people look at, I mean, I look at Snowflake as an example of a company that refactored data warehouses. They just basically took data warehouse, and put it on the cloud, and called it a data cloud. That, to me, was compelling. They didn't pay any CapEx. They rode Amazon's wave there. So, a similar thing going on with data. You mentioned this, and I see it as an enabling opportunity. So whether it's cybersecurity, FinTech, whatever vertical, you have an enablement. Now, you mentioned data infrastructure. It's a super exciting area, as there's so many stacks emerging. We got an analytics stack, there's real-time stacks, there's data lakes, AI stack, foundational models. So, you're seeing an explosion of stacks, different tools probably will emerge. So, how do you look at that, as a seasoned entrepreneur, now investor? Is that a good thing? Is that just more of the market? 'Cause it just seems like more and more kind of decomposed stacks targeted at use cases seems to be a trend. >> Yeah. >> And how do you vet that, is it? >> So it's a great observation, and if you take a step back and look at the evolution of technology over the last 30 years, maybe longer, you always see these cycles of expansion, fragmentation, contraction, expansion, contraction. Go decentralize, go centralize, go decentralize, go centralize, as manifested in different types of technology paradigms. From client server, to storage, to microservices, to et cetera, et cetera. So I think we're going through another big bang, to a certain extent, whereby end up with more specialized data stacks for specific use cases, as you need performance, the data models, the tooling to best adapt to the particular task at hand, and the particular personas at hand. As the needs of the data analysts are quite different from the needs of an NL engineer, it's quite different from the needs of the data engineer. And what happens is, when you end up with these siloed stacks, you end up with new fragmentation, and new gaps that need to be filled with a new layer of innovation. And I suspect that, in part, that's what we're seeing right now, in terms of the next wave of data innovation. Whether it's in a service of FinTech use cases, or cyber use cases, or other, is a set of tools that end up having to try and stitch together those elements and bridge between them. So I see that as a fantastic gap to innovate around. I see, also, a fundamental need in creating a common data language, and common data management processes and governance across those different personas, because ultimately, the same underlying data these folks need, albeit in different mediums, different access models, different velocities, et cetera, the subject matter, if you will, the underlying raw data, and some of the taxonomies right on top of it, do need to be consistent. So, once again, a great opportunity to innovate, whether it's about semantic layers, whether it's about data mesh, whether it's about CICD tools for data engineers, and so on and so forth. >> I got to ask you, first of all, I see you have a friend you brought into the interview. You have a dog in the background who made a little cameo appearance. And that's awesome. Sitting right next to you, making sure everything's going well. On the AI thing, 'cause I think that's the hot trend here. >> Yeah. >> You're starting to see, that ChatGPT's got everyone excited, because it's kind of that first time you see kind of next-gen functionality, large-language models, where you can bring data in, and it integrates well. So, to me, I think, connecting the dots, this kind of speaks to the beginning of what will be a trend of really blending of data stacks together, or blending of models. And so, as more data modeling emerges, you start to have this AI stack kind of situation, where you have things out there that you can compose. It's almost very developer-friendly, conceptually. This is kind of new, but kind of the same concept's been working on with Google and others. How do you see this emerging, as an investor? What are some of the things that you're excited about, around the ChatGPT kind of things that's happening? 'Cause it brings it mainstream. Again, a million downloads, fastest applications get a million downloads, even among all the successes. So it's obviously hit a nerve. People are talking about it. What's your take on that? >> Yeah, so, I think that's a great point, and clearly, it feels like an iPhone moment, right, to the industry, in this case, AI, and lots of applications. And I think there's, at a high level, probably three different layers of innovation. One is on top of those platforms. What use cases can one bring to the table that would drive on top of a ChatGPT-like service? Whereby, the startup, the company, can bring some unique datasets to infuse and add value on top of it, by custom-focusing it and purpose-building it for a particular use case or particular vertical. Whether it's applying it to customer service, in a particular vertical, applying it to, I don't know, marketing content creation, and so on and so forth. That's one category. And I do know that, as one of my startups is in Y Combinator, this season, winter '23, they're saying that a very large chunk of the YC companies in this cycle are about GPT use cases. So we'll see a flurry of that. The next layer, the one below that, is those who actually provide those platforms, whether it's ChatGPT, whatever will emerge from the partnership with Microsoft, and any competitive players that emerge from other startups, or from the big cloud providers, whether it's Facebook, if they ever get into this, and Google, which clearly will, as they need to, to survive around search. The third layer is the enabling layer. As you're going to have more and more of those different large-language models and use case running on top of it, the underlying layers, all the way down to cloud infrastructure, the data infrastructure, and the entire set of tools and systems, that take raw data, and massage it into useful, labeled, contextualized features and data to feed the models, the AI models, whether it's during training, or during inference stages, in production. Personally, my focus is more on the infrastructure than on the application use cases. And I believe that there's going to be a massive amount of innovation opportunity around that, to reach cost-effective, quality, fair models that are deployed easily and maintained easily, or at least with as little pain as possible, at scale. So there are startups that are dealing with it, in various areas. Some are about focusing on labeling automation, some about fairness, about, speaking about cyber, protecting models from threats through data and other issues with it, and so on and so forth. And I believe that this will be, too, a big driver for massive innovation, the infrastructure layer. >> Awesome, and I love how you mentioned the iPhone moment. I call it the browser moment, 'cause it felt that way for me, personally. >> Yep. >> But I think, from a business model standpoint, there is that iPhone shift. It's not the BlackBerry. It's a whole 'nother thing. And I like that. But I do have to ask you, because this is interesting. You mentioned iPhone. iPhone's mostly proprietary. So, in these machine learning foundational models, >> Yeah. >> you're starting to see proprietary hardware, bolt-on, acceleration, bundled together, for faster uptake. And now you got open source emerging, as two things. It's almost iPhone-Android situation happening. >> Yeah. >> So what's your view on that? Because there's pros and cons for either one. You're seeing a lot of these machine learning laws are very proprietary, but they work, and do you care, right? >> Yeah. >> And then you got open source, which is like, "Okay, let's get some upsource code, and let people verify it, and then build with that." Is it a balance? >> Yes, I think- >> Is it mutually exclusive? What's your view? >> I think it's going to be, markets will drive the proportion of both, and I think, for a certain use case, you'll end up with more proprietary offerings. With certain use cases, I guess the fundamental infrastructure for ChatGPT-like, let's say, large-language models and all the use cases running on top of it, that's likely going to be more platform-oriented and open source, and will allow innovation. Think of it as the equivalent of iPhone apps or Android apps running on top of those platforms, as in AI apps. So we'll have a lot of that. Now, when you start going a little bit more into the guts, the lower layers, then it's clear that, for performance reasons, in particular, for certain use cases, we'll end up with more proprietary offerings, whether it's advanced silicon, such as some of the silicon that emerged from entrepreneurs who have left Google, around TensorFlow, and all the silicon that powers that. You'll see a lot of innovation in that area as well. It hopefully intends to improve the cost efficiency of running large AI-oriented workloads, both in inference and in learning stages. >> I got to ask you, because this has come up a lot around Azure and Microsoft. Microsoft, pretty good move getting into the ChatGPT >> Yep. >> and the open AI, because I was talking to someone who's a hardcore Amazon developer, and they said, they swore they would never use Azure, right? One of those types. And they're spinning up Azure servers to get access to the API. So, the developers are flocking, as you mentioned. The YC class is all doing large data things, because you can now program with data, which is amazing, which is amazing. So, what's your take on, I know you got to be kind of neutral 'cause you're an investor, but you got, Amazon has to respond, Google, essentially, did all the work, so they have to have a solution. So, I'm expecting Google to have something very compelling, but Microsoft, right now, is going to just, might run the table on developers, this new wave of data developers. What's your take on the cloud responses to this? What's Amazon, what do you think AWS is going to do? What should Google be doing? What's your take? >> So, each of them is coming from a slightly different angle, of course. I'll say, Google, I think, has massive assets in the AI space, and their underlying cloud platform, I think, has been designed to support such complicated workloads, but they have yet to go as far as opening it up the same way ChatGPT is now in that Microsoft partnership, and Azure. Good question regarding Amazon. AWS has had a significant investment in AI-related infrastructure. Seeing it through my startups, through other lens as well. How will they respond to that higher layer, above and beyond the low level, if you will, AI-enabling apparatuses? How do they elevate to at least one or two layers above, and get to the same ChatGPT layer, good question. Is there an acquisition that will make sense for them to accelerate it, maybe. Is there an in-house development that they can reapply from a different domain towards that, possibly. But I do suspect we'll end up with acquisitions as the arms race around the next level of cloud wars emerges, and it's going to be no longer just about the basic tooling for basic cloud-based applications, and the infrastructure, and the cost management, but rather, faster time to deliver AI in data-heavy applications. Once again, each one of those cloud suppliers, their vendor is coming with different assets, and different pros and cons. All of them will need to just elevate the level of the fight, if you will, in this case, to the AI layer. >> It's going to be very interesting, the different stacks on the data infrastructure, like I mentioned, analytics, data lake, AI, all happening. It's going to be interesting to see how this turns into this AI cloud, like data clouds, data operating systems. So, super fascinating area. Opher, thank you for coming on and sharing your expertise with us. Great to see you, and congratulations on the work. I'll give you the final word here. Give a plugin for what you're looking for for startup seats, pre-seeds. What's the kind of profile that gets your attention, from a seed, pre-seed candidate or entrepreneur? >> Cool, first of all, it's my pleasure. Enjoy our chats, as always. Hopefully the next one's not going to be in nine years. As to what I'm looking for, ideally, smart data entrepreneurs, who have come from a particular domain problem, or problem domain, that they understand, they felt it in their own 10 fingers, or millions of neurons in their brains, and they figured out a way to solve it. Whether it's a data infrastructure play, a cloud infrastructure play, or a very, very smart application that takes advantage of data at scale. These are the things I'm looking for. >> One final, final question I have to ask you, because you're a seasoned entrepreneur, and now coach. What's different about the current entrepreneurial environment right now, vis-a-vis, the past decade? What's new? Is it different, highly accelerated? What advice do you give entrepreneurs out there who are putting together their plan? Obviously, a global resource pool now of engineering. It might not be yesterday's formula for success to putting a venture together to get to that product-market fit. What's new and different, and what's your advice to the folks out there about what's different about the current environment for being an entrepreneur? >> Fantastic, so I think it's a great question. So I think there's a few axes of difference, compared to, let's say, five years ago, 10 years ago, 15 years ago. First and foremost, given the amount of infrastructure out there, the amount of open-source technologies, amount of developer toolkits and frameworks, trying to develop an application, at least at the application layer, is much faster than ever. So, it's faster and cheaper, to the most part, unless you're building very fundamental, core, deep tech, where you still have a big technology challenge to deal with. And absent that, the challenge shifts more to how do you manage my resources, to product-market fit, how are you integrating the GTM lens, the go-to-market lens, as early as possible in the product-market fit cycle, such that you reach from pre-seed to seed, from seed to A, from A to B, with an optimal amount of velocity, and a minimal amount of resources. One big difference, specifically as of, let's say, beginning of this year, late last year, is that money is no longer free for entrepreneurs, which means that you need to operate and build startup in an environment with a lot more constraints. And in my mind, some of the best startups that have ever been built, and some of the big market-changing, generational-changing, if you will, technology startups, in their respective industry verticals, have actually emerged from these times. And these tend to be the smartest, best startups that emerge because they operate with a lot less money. Money is not as available for them, which means that they need to make tough decisions, and make verticals every day. What you don't need to do, you can kick the cow down the road. When you have plenty of money, and it cushions for a lot of mistakes, you don't have that cushion. And hopefully we'll end up with companies with a more agile, more, if you will, resilience, and better cultures in making those tough decisions that startups need to make every day. Which is why I'm super, super excited to see the next batch of amazing unicorns, true unicorns, not just valuation, market rising with the water type unicorns that emerged from this particular era, which we're in the beginning of. And very much enjoy working with entrepreneurs during this difficult time, the times we're in. >> The next 24 months will be the next wave, like you said, best time to do a company. Remember, Airbnb's pitch was, "We'll rent cots in apartments, and sell cereal." Boy, a lot of people passed on that deal, in that last down market, that turned out to be a game-changer. So the crazy ideas might not be that bad. So it's all about the entrepreneurs, and >> 100%. >> this is a big wave, and it's certainly happening. Opher, thank you for sharing. Obviously, data is going to change all the markets. Refactoring, security, FinTech, user experience, applications are going to be changed by data, data operating system. Thanks for coming on, and thanks for sharing. Appreciate it. >> My pleasure. Have a good one. >> Okay, more coverage for the CloudNativeSecurityCon inaugural event. Data will be the key for cybersecurity. theCUBE's coverage continues after this break. (uplifting music)

(upbeat music) >> Welcome to this Cube Conversation about women in tech and women in cybersecurity, two things I'm very passionate about. Lisa Martin here, with two guests, Debbie Briggs joins us, the Area Vice President, and Chief Security Officer at NETSCOUT, and Tyler Cohen Wood is here as well, the Founder and CEO of MyConnectedHealth. Ladies, it's an honor to have you on the program. I'm excited to talk to you. >> Thank you so much for having us. >> Completely agree. Tyler and I talked a couple of minutes last week and she has a lot to offer to this. >> I know, I was looking at both of your backgrounds. Very impressive. Tyler, starting with you. I see that you are a nationally recognized Cybersecurity Intelligence, National Security Expert, and former Director of Cyber Risk Management for AT&T. And I also saw that you just won a Top 50 Women in Tech Influencers to Follow for 2021 Award. Congratulations, that's amazing. I would love to know way back in the day, how did you even first become interested in tech? >> Well, it was kind of inevitable that I would go into something like tech because as a kid, I was kind of nerdy. I was obsessed with "Star Trek". I would catalog my "Star Trek" tapes by Stardate. I was just really into it. But when I was in college, I mean, it was the late 90's. Cybersecurity just really wasn't a thing. So I went into music and I worked for a radio station. I loved it, but the format of the radio station changed and I wanted to do something different. And I thought, well, computers. I'll move to San Francisco, and I'm sure I can get a job, 'cause they were hiring anyone with a brain, 'cause it was really the dot com boom. And that's really how I got into it. It was just kind of one of those things. (laughs) >> Did you have, was it like network connection, going from music to tech is quite a jump? >> It's a huge jump. It was, but you know, I was young. I was still fresh out of school. I was really interested in learning and I really wanted to get involved in cyber in some capacity, because I became really fascinated with it. So it was just kind of one of those things, that just sort of happened. >> What an interesting talk about a zig-zaggy path. That's a very, very interesting one. And I have to talk about music with you later. That would be interesting. And Debbie, you also have, as Tyler does, 20 years plus experience in cybersecurity. You've been with NETSCOUT since '04. Were you always interested in tech? Did you study engineering or computer science in school, Debbie? >> Yeah, so I think my interest in tech, just like Tyler started at a very young age. I was always interested in how things worked and how people worked. And some day over a drink, I will tell you some funny stories about things I took apart in my parents house, to figure out how it worked. (Lisa and Tyler laughing) They still don't know it. So I guess I- >> I love that. >> I just love that putting it back together, but I took a more traditional route than Tyler did. I do have a degree in Computer Science, went to school a little bit earlier than Tyler. What I would say is, when I was in college, the Computer Science Center was in the basement of the library and we had these really tiny windows and they sort of hit you in the dark. And I think it was my senior year and I went, "I don't want to sit in a room by myself and write code all day and talk to no one." So, you know, I'm a senior and I'm like, "Okay, I got to, this is not, I did not want to write code all day." And so I happened to fall into a great company and moved onto PCs. And from there went to messaging, to networking and into that, I fell into cybersecurity. So I took that more traditional route and I think I've done every job in IT, except for programming, which is what I really got my degree in. >> But you realized early on, you know, "I don't quite think this is for me." And that's an important thing for anybody in any career, to really listen to your gut. It's telling you something. I love how you both got into cybersecurity, which is now, especially in the last 18 months, with what we've seen with the threat landscape, such an incredible opportunity for anyone. But I'd like to know there's not a lot of women in tech, as we know we've been talking about this for a long time now. We've got maybe a quarter of women at the technology roles are filled by women. Tyler, talk to me about some of the challenges that you faced along your journey to get where you are today. >> Well, I mean, you know, like I said, when I started, it was like 1999, 2000. And there were even less women in cybersecurity and in these tech roles than there are now. And you know, it was difficult because, you know, I remember at my first job, I was so interested in learning about Unix and I would learn everything, I read everything about it. And I ended up getting promoted over all of my male colleagues. And you know, it was really awkward because there was the assumption, they would just say things like, "Oh, well you got that because you're a woman." And that was not the case, but it's that type of stereotyping, you know, that we've had to deal with in this industry. Now I do believe that is changing. And I've seen a lot of evidence of that. We're getting there, but we're not there yet. >> And I agree. I agree completely with what Tyler said. You know, when I started, you were the only woman in the room, you got promoted over your male counterparts. You know, I would say even 10 years ago, you know, someone was like, "Well, you could go for any CISCO role and you'd get the job because you're a woman." And I've had to go and say, "No, I might get an interview because I'm a woman, but you don't get the job just because, you know, you check a box." You know, some of that is still out there, but Tyler you're right, things are changing. I think, you know, three things that we all need to focus in on to continue to move us forward and get more women into tech is the first thing is we have to start younger. I think by high school, a lot of girls and young women have been turned off by technology. So maybe, we need to start in the middle school and ensuring that we've got young girls interested. The second thing is, is we have to have mentors. And I always say, if you're in the security industry, you have to turn around and help the next person out. And if that person is a woman, that's great, but we have to mentor others. And it can be young girls, it could be young gentlemen, but we need to mentor that next group up. And you know, if you're in the position to offer internships during the summer, we don't have to stay to the traditional role and go, "Oh, let me hire just intern from the you know IT, they're getting degrees in IT." You can get creative. And my best worker right now was an intern that worked for me, was an intern for me six years ago. And she has a degree in Finance, so nontraditional route into cyber security. And the third thing I think we need to do is, is there things the industry could do to change things and make things, I don't want to say even 'cause they're not uneven, but for example, I forget what survey it was, but if a woman reads a job description and I can do half of it, I'm not going to apply because I don't feel I'll qualify, where men, on the other hand, if they can do three out of ten they'll apply. So do we need to look at the way we write job descriptions, and use different words, you know, rather than must have these skills. You know, sort of leave it a little bit open, like here are the skills we'd like you to have, or have, you know, a handful of the following. So soften some of those job descriptions. And the second thing is once we get women in, we have to be a little bit more, I'll say inclusive. So, if you're a high tech company, look at, you know, your sales organization. When you go to big shows, do you pay more attention to men on the floor than women on the floor? If you have a sales event where you get different customers together, is it a golf outing or is it something that's maybe a little bit more inclusive than just male? So those are the three things I think as an industry we have to focus in on, start younger, get them, you know, work on mentorships specifically in cyber, and the third thing is, look at some of the things that we're doing, as companies both in our HR and sales practices. >> That's a great, that last piece of advice, Debbie is fantastic. That's one that I hadn't thought about, but you're right. If a job description is written, for must have all of these things and a woman that goes, "I only got three out of the ten. I'm not going to even get past, you know, the recruiter here." How can we write things differently? I also loved your idea of bringing in people with diverse backgrounds. I've been in marketing for 16 years and I've met very few people that actually have marketing degrees, a lot of people. So you get that diversity of thought. Tyler, what are some of your thoughts about how we can help expand the role of women in technology? Do you agree with some of the things that Debbie said? >> I love what Debbie said. I agree 100%. And I started laughing because I was thinking about all the golf outings that I've been on and I don't play golf. (all laughing) I think that there is an untapped resource because there's a lot of women who are now interested in changing their careers and that's a big pool of people. And I think that making it more accessible and making it so that people understand what the different cyber security or cyber jobs are, because a lot of people just assume that it's coding, or it's, you know, working on AI, but that's not necessarily true. I mean, there's so many different avenues. There's marketing, there's forensics, there's incident response. I mean, I could go on and on and on. And oftentimes if people don't know that these types of jobs exist, they're not even going to look for them. So making that more well-known, what the different types of opportunities are to people, I think that that would help kind of open more doors. >> And that goes along beautifully with what Debbie was talking about with respect to mentorship. And I would even add sponsorship in there, but becoming a sponsor of a younger female, who's maybe considering tech or is already in tech to help her navigate the career. Look for the other opportunities. Tyler, as you mentioned, there's a lot to cybersecurity, that is beyond coding and AI for example. So maybe getting the awareness out there more. Did either of you have sponsors when you were early in your career? Are you a sponsor now? Debbie, let's start with you. >> So, I'll answer your first question. I guess I was really fortunate that my first job out of college, I had an internship and I happened to have a female boss. And so, although we may not have called it sponsorship or mentor, she taught me and showed me that, you know, women can be leaders. And she always believed in us and always pushed us to do things beyond what we may have thought we were capable of. Throughout the years, someone once told me that we should all have our own personal board of directors. You know, a group of people that when we're making a decision, that may be life-changing or we're unsure, rather than just having one mentor, having a group of people that you, that you know, they don't have to be in cybersecurity. Yeah, I want someone that's on my board of directors that maybe, is a specialist in cybersecurity, but having other executives in other companies, that can also give you that perspective. You know, so I've always had a personal board of directors. I think I've had three or four different mentors. Some of them, I went out and found. Some of them I have joined organizations that have been fortunate enough to become not only a mentor, but a mentee. And I've kept those relationships up over three or four years. And all those people are now on my personal board of directors, that, you know, if I have a life-changing question, I've got a group of people that I can go back on. >> That is brilliant advice. I love that having a... Isn't that great Tyler? Having a personal- >> Yes Yes! >> Board of directors, especially as we look at cybersecurity and the cybersecurity skills gap Tyler has been, I think it's in its 5th year now, which is there's so much opportunity. What we saw in the threat landscape in the last 18, 19 months during the pandemic was this explosion and the attack surface, ransomware becoming a word that even my mom knows these days. What do you advise Tyler for, you talked about really making people much more aware of all of the opportunities within cyber, but when you think about how you would get women interested in cybersecurity specifically, what are some of the key pieces of advice you would offer? >> Well, again, I think I love the board of directors. I love that. That is brilliant, but I really think that it is about finding mentors, and it is about doing the research, and really asking questions. Because if you reach out to someone on LinkedIn, you know, they may just not respond, but chances are some someone will and, you know, most people in this community are very willing to help. And, you know, I found that to be great. I mean, I've got my board of directors too. I realize that now. (Debbie laughs) But I also like to help other people as well, that are just kind of entering into the field or if they're changing their careers. And it's not necessarily just women, it's people that are interested in getting into an aspect of this industry. And this is a industry where, you know, you can jump from this, to this, to this, to this. I mean, I think that I've had six different major career shifts still within the cybersecurity realm. So, just because you start off doing one thing doesn't mean that that's what you're going to do forever. There're so many different areas. And it's really interesting. I think about my 11 year old niece and she may very well have a job someday, that doesn't even exist right now. That's how quickly cyber and everything connected is moving. And if you think about it, we are connected, there is a cyber component to every single thing that we do, and that's going to continue to expand and continue to grow. And we need more people to be interested, and to want to get into these careers. And I think also it's important for younger girls to let them know these careers are really fun and they're extremely rewarding. And I mean, I hate to use this as an incentive, but there's also a lot of money that can be made too, and that's an incentive to get, you know, women and girls into these careers as well. >> And Tyler, I think you're right. In addition to that, you're always going to have a job. And I think cyber is a great career for someone that are lifelong learners, because like you said, your 11 year old niece, the job, when she graduates from college, she may have, probably doesn't even exist today. And so I think you have to be a lifelong learner. I think one of the things that people may not be aware of is, you know, for women who may have gone the non-traditional route and got degrees later in life, or took time off to raise children and want to come back to work, cyber security is something that, you know, doesn't have to be a nine to five job. I have, it happens to be a gentlemen on my team, who has to get kids on the bus and off the bus. And so we figured out how, you know, he gets up and he works for a couple hours, puts kids on the bus, is in the office. And then he gets the kids off. And once they've had dinner and gone to bed, he puts in a couple more hours. And I think, you know, people need to be aware of, there is some flexibility, there is flexibility in cyber jobs. I mean, it's not a nine to five job, it's not like banking. Well, if you were teller, and your hours are when the bank is open, cyber is 7/24 and jobs can be flexible. And I think people need to be aware of that. >> I agree on the flexibility front, and people also need to be flexible themselves. I do want to ask you both, we're getting low on time, but I've got to ask you, how do you get the confidence, to be, like you said, back in the day, in the room, maybe the only female and I've been in that as well, even in marketing, product marketing years ago. How do you get the confidence to continue moving forward? Even as someone says, "You're only here because you're a female." Tyler, what's your advice to help young women and young men as well fight any sort of challenges that are coming their way? >> I had a mentor when I first moved to the Defense Intelligence Agency, I had an Office Chief and she said to me, "Tyler, you're a Senior Intelligence Officer, you always take a seat at the table. Do not let anyone tell you that you cannot have a seat at the table." And you know, that was good advice. And I think confidence is great. But courage is something that's much more important, because courage is what leads up to confidence. And you really have to believe in yourself and do things that you know are right for you, not because you think it's going to make other people happy. And I think, you know, as women, it's really finding that courage to be brave and to be strong and to be willing to stand out, you know, alone on something, because it's what you care about and what you believe in. And that's really what helps kind of motivate me. >> I love that courage. Debbie, what are your thoughts? >> (laughs) So I was going to say, this is going to be really hard to believe, but when I was 16 years old, I was so shy that if I went to a restaurant and someone served me stone cold food, I wouldn't say a word. I would just eat it. If I bought something in a store and I didn't like it, I'd refuse, I just couldn't bring myself to go to that customer service desk and return it. And my first job in high school, was it a fast food place. And I worked for a gentleman who was a little bit of a tyrant, but you know, I learned how to get a backbone very quickly. And I would have to say now looking back, he was probably my first mentor without even trying to do that. He mentored me on how to believe in myself and how to stand up for what's right. So, Tyler, I completely agree with you. And you know, that's something that people think when they get a mentorship, sometimes it's someone going to mentor them on, you know, something tactical, something they want to know how to do, but sometimes what you need to be mentored in, could be, "How do I believe in myself?" Or "How do I find the courage to be that the only female in the room?" And I think that is where some of that mentorship comes from and, you know, I think, you know, if we go back to mentoring at the middle school, there's lots of opportunities, career fairs, the first robotically, get the middle school level, gives all of us an opportunity to sort of mentor girls at that level. And for all the guys out there who have daughters, this is, you know, how to... It's not like you can get a parenting checklist, "Teach my kid courage." And Tyler, I love that word, but I think that's something that we all need to aspire to bring out in others. >> I love that. I love that. >> Okay with that, I think I love both of your stories, are zig-zaggy in certain ways, one in a more direct cybersecurity path, Debbie with yours. Tyler, yours, very different coming from the music industry. But you both have such great advice. It's really, I would say, I'm going to add that, open your mind to be open to, you can do anything. As Tyler said, there's a very great possibility that right now the job that your niece who's 11 is going to get in the next 10 years, doesn't exist yet. How exciting is that? To have the opportunity to be open-minded enough and flexible enough to say, "I'm going to try that." And I'm going to learn from my mentors, whether it's a fast food cook, which I wouldn't think would be a direct mentor, and recognizing years later, "Wow, what an impact that person had on me, having the courage to do what I have." And so I would ask you like each one more question in terms of just your inspiration for what you're currently doing. Debbie, as the leader of security for NETSCOUT, what inspires you to continue in your current role and seek more? >> So, I'm a lifelong learner. So, I love to learn cybersecurity. You know, every day is a different day. So, it's definitely the ability to continue to learn and to do new things. But the second thing is, is I think I've always been, I don't want to call it a fixer-upper because cybersecurity isn't a fixer-upper, I'm just always wanted to improve upon things. If I've seen something that I think can do better, or a product that could have something new or better in it, you know, that's what excites me is to give people that feedback and to improve on what we've had out there. You know, you had mentioned, we've got this block of jobs that we can't fill. We have to give feedback and how we get the tools and what we have today smarter, so that if there are less of us, we're working smarter and not harder. And so if there is some low-level tasks that we could put back into tools, and talk to vendors and have them do this for us, that's how I think we start to get our way sort of out of the hole. Tyler, any thoughts on that? >> I again, I love that answer. I mean, I think for me, you know, I do like, it's that problem solving thing too. But for me it's also about, it's about compassion. And when I see, you know, a story of some child that's been involved in some kind of cyber bullying attack, or a company that has been broken into, I want to do whatever I can to help people, and to teach people to really protect themselves, so that they feel empowered and they're not afraid of cyber security. So for me, it's also really that drive to really make a difference and really help people. >> And you've both done, I'm sure, so much of that made such a big difference in many communities in which you're involved. I thank you so much for sharing your journeys with me on the program today, and giving such great pointed advice to young men and women, and even some of the older men and women out there that might be kind of struggling about, where do I go next? Your advice is brilliant, ladies. Thank you so much. It's been a pleasure talking with you. >> Thank you. >> Thank you. >> For Debbie Briggs and Tyler Cohen Wood, I'm Lisa Martin. You've been watching this Cube Conversation. (upbeat music)

(upbeat music) >> Welcome to this Cube Conversation about women in tech and women in cybersecurity, two things I'm very passionate about. Lisa Martin here, with two guests, Debbie Briggs joins us, the Area Vice President, and Chief Security Officer at NETSCOUT, and Tyler Cohen Wood is here as well, the Founder and CEO of MyConnectedHealth. Ladies, it's an honor to have you on the program. I'm excited to talk to you. >> Thank you so much for having us. >> Completely agree. Tyler and I talked a couple of minutes last week and she has a lot to offer to this. >> I know, I was looking at both of your backgrounds. Very impressive. Tyler, starting with you. I see that you are a nationally recognized Cybersecurity Intelligence, National Security Expert, and former Director of Cyber Risk Management for AT&T. And I also saw that you just won a Top 50 Women in Tech Influencers to Follow for 2021 Award. Congratulations, that's amazing. I would love to know way back in the day, how did you even first become interested in tech? >> Well, it was kind of inevitable that I would go into something like tech because as a kid, I was kind of nerdy. I was obsessed with "Star Trek". I would catalog my "Star Trek" tapes by Stardate. I was just really into it. But when I was in college, I mean, it was the late 90's. Cybersecurity just really wasn't a thing. So I went into music and I worked for a radio station. I loved it, but the format of the radio station changed and I wanted to do something different. And I thought, well, computers. I'll move to San Francisco, and I'm sure I can get a job, 'cause they were hiring anyone with a brain, 'cause it was really the dot com boom. And that's really how I got into it. It was just kind of one of those things. (laughs) >> Did you have, was it like network connection, going from music to tech is quite a jump? >> It's a huge jump. It was, but you know, I was young. I was still fresh out of school. I was really interested in learning and I really wanted to get involved in cyber in some capacity, because I became really fascinated with it. So it was just kind of one of those things, that just sort of happened. >> What an interesting talk about a zig-zaggy path. That's a very, very interesting one. And I have to talk about music with you later. That would be interesting. And Debbie, you also have, as Tyler does, 20 years plus experience in cybersecurity. You've been with NETSCOUT since '04. Were you always interested in tech? Did you study engineering or computer science in school, Debbie? >> Yeah, so I think my interest in tech, just like Tyler started at a very young age. I was always interested in how things worked and how people worked. And some day over a drink, I will tell you some funny stories about things I took apart in my parents house, to figure out how it worked. (Lisa and Tyler laughing) They still don't know it. So I guess I- >> I love that. >> I just love that putting it back together, but I took a more traditional route than Tyler did. I do have a degree in Computer Science, went to school a little bit earlier than Tyler. What I would say is, when I was in college, the Computer Science Center was in the basement of the library and we had these really tiny windows and they sort of hit you in the dark. And I think it was my senior year and I went, "I don't want to sit in a room by myself and write code all day and talk to no one." So, you know, I'm a senior and I'm like, "Okay, I got to, this is not, I did not want to write code all day." And so I happened to fall into a great company and moved onto PCs. And from there went to messaging, to networking and into that, I fell into cybersecurity. So I took that more traditional route and I think I've done every job in IT, except for programming, which is what I really got my degree in. >> But you realized early on, you know, "I don't quite think this is for me." And that's an important thing for anybody in any career, to really listen to your gut. It's telling you something. I love how you both got into cybersecurity, which is now, especially in the last 18 months, with what we've seen with the threat landscape, such an incredible opportunity for anyone. But I'd like to know there's not a lot of women in tech, as we know we've been talking about this for a long time now. We've got maybe a quarter of women at the technology roles are filled by women. Tyler, talk to me about some of the challenges that you faced along your journey to get where you are today. >> Well, I mean, you know, like I said, when I started, it was like 1999, 2000. And there were even less women in cybersecurity and in these tech roles than there are now. And you know, it was difficult because, you know, I remember at my first job, I was so interested in learning about Unix and I would learn everything, I read everything about it. And I ended up getting promoted over all of my male colleagues. And you know, it was really awkward because there was the assumption, they would just say things like, "Oh, well you got that because you're a woman." And that was not the case, but it's that type of stereotyping, you know, that we've had to deal with in this industry. Now I do believe that is changing. And I've seen a lot of evidence of that. We're getting there, but we're not there yet. >> And I agree. I agree completely with what Tyler said. You know, when I started, you were the only woman in the room, you got promoted over your male counterparts. You know, I would say even 10 years ago, you know, someone was like, "Well, you could go for any CISCO role and you'd get the job because you're a woman." And I've had to go and say, "No, I might get an interview because I'm a woman, but you don't get the job just because, you know, you check a box." You know, some of that is still out there, but Tyler you're right, things are changing. I think, you know, three things that we all need to focus in on to continue to move us forward and get more women into tech is the first thing is we have to start younger. I think by high school, a lot of girls and young women have been turned off by technology. So maybe, we need to start in the middle school and ensuring that we've got young girls interested. The second thing is, is we have to have mentors. And I always say, if you're in the security industry, you have to turn around and help the next person out. And if that person is a woman, that's great, but we have to mentor others. And it can be young girls, it could be young gentlemen, but we need to mentor that next group up. And you know, if you're in the position to offer internships during the summer, we don't have to stay to the traditional role and go, "Oh, let me hire just intern from the you know IT, they're getting degrees in IT." You can get creative. And my best worker right now was an intern that worked for me, was an intern for me six years ago. And she has a degree in Finance, so nontraditional route into cyber security. And the third thing I think we need to do is, is there things the industry could do to change things and make things, I don't want to say even 'cause they're not uneven, but for example, I forget what survey it was, but if a woman reads a job description and I can do half of it, I'm not going to apply because I don't feel I'll qualify, where men, on the other hand, if they can do three out of ten they'll apply. So do we need to look at the way we write job descriptions, and use different words, you know, rather than must have these skills. You know, sort of leave it a little bit open, like here are the skills we'd like you to have, or have, you know, a handful of the following. So soften some of those job descriptions. And the second thing is once we get women in, we have to be a little bit more, I'll say inclusive. So, if you're a high tech company, look at, you know, your sales organization. When you go to big shows, do you pay more attention to men on the floor than women on the floor? If you have a sales event where you get different customers together, is it a golf outing or is it something that's maybe a little bit more inclusive than just male? So those are the three things I think as an industry we have to focus in on, start younger, get them, you know, work on mentorships specifically in cyber, and the third thing is, look at some of the things that we're doing, as companies both in our HR and sales practices. >> That's a great, that last piece of advice, Debbie is fantastic. That's one that I hadn't thought about, but you're right. If a job description is written, for must have all of these things and a woman that goes, "I only got three out of the ten. I'm not going to even get past, you know, the recruiter here." How can we write things differently? I also loved your idea of bringing in people with diverse backgrounds. I've been in marketing for 16 years and I've met very few people that actually have marketing degrees, a lot of people. So you get that diversity of thought. Tyler, what are some of your thoughts about how we can help expand the role of women in technology? Do you agree with some of the things that Debbie said? >> I love what Debbie said. I agree 100%. And I started laughing because I was thinking about all the golf outings that I've been on and I don't play golf. (all laughing) I think that there is an untapped resource because there's a lot of women who are now interested in changing their careers and that's a big pool of people. And I think that making it more accessible and making it so that people understand what the different cyber security or cyber jobs are, because a lot of people just assume that it's coding, or it's, you know, working on AI, but that's not necessarily true. I mean, there's so many different avenues. There's marketing, there's forensics, there's incident response. I mean, I could go on and on and on. And oftentimes if people don't know that these types of jobs exist, they're not even going to look for them. So making that more well-known, what the different types of opportunities are to people, I think that that would help kind of open more doors. >> And that goes along beautifully with what Debbie was talking about with respect to mentorship. And I would even add sponsorship in there, but becoming a sponsor of a younger female, who's maybe considering tech or is already in tech to help her navigate the career. Look for the other opportunities. Tyler, as you mentioned, there's a lot to cybersecurity, that is beyond coding and AI for example. So maybe getting the awareness out there more. Did either of you have sponsors when you were early in your career? Are you a sponsor now? Debbie, let's start with you. >> So, I'll answer your first question. I guess I was really fortunate that my first job out of college, I had an internship and I happened to have a female boss. And so, although we may not have called it sponsorship or mentor, she taught me and showed me that, you know, women can be leaders. And she always believed in us and always pushed us to do things beyond what we may have thought we were capable of. Throughout the years, someone once told me that we should all have our own personal board of directors. You know, a group of people that when we're making a decision, that may be life-changing or we're unsure, rather than just having one mentor, having a group of people that you, that you know, they don't have to be in cybersecurity. Yeah, I want someone that's on my board of directors that maybe, is a specialist in cybersecurity, but having other executives in other companies, that can also give you that perspective. You know, so I've always had a personal board of directors. I think I've had three or four different mentors. Some of them, I went out and found. Some of them I have joined organizations that have been fortunate enough to become not only a mentor, but a mentee. And I've kept those relationships up over three or four years. And all those people are now on my personal board of directors, that, you know, if I have a life-changing question, I've got a group of people that I can go back on. >> That is brilliant advice. I love that having a... Isn't that great Tyler? Having a personal- >> Yes Yes! >> Board of directors, especially as we look at cybersecurity and the cybersecurity skills gap Tyler has been, I think it's in its 5th year now, which is there's so much opportunity. What we saw in the threat landscape in the last 18, 19 months during the pandemic was this explosion and the attack surface, ransomware becoming a word that even my mom knows these days. What do you advise Tyler for, you talked about really making people much more aware of all of the opportunities within cyber, but when you think about how you would get women interested in cybersecurity specifically, what are some of the key pieces of advice you would offer? >> Well, again, I think I love the board of directors. I love that. That is brilliant, but I really think that it is about finding mentors, and it is about doing the research, and really asking questions. Because if you reach out to someone on LinkedIn, you know, they may just not respond, but chances are some someone will and, you know, most people in this community are very willing to help. And, you know, I found that to be great. I mean, I've got my board of directors too. I realize that now. (Debbie laughs) But I also like to help other people as well, that are just kind of entering into the field or if they're changing their careers. And it's not necessarily just women, it's people that are interested in getting into an aspect of this industry. And this is a industry where, you know, you can jump from this, to this, to this, to this. I mean, I think that I've had six different major career shifts still within the cybersecurity realm. So, just because you start off doing one thing doesn't mean that that's what you're going to do forever. There're so many different areas. And it's really interesting. I think about my 11 year old niece and she may very well have a job someday, that doesn't even exist right now. That's how quickly cyber and everything connected is moving. And if you think about it, we are connected, there is a cyber component to every single thing that we do, and that's going to continue to expand and continue to grow. And we need more people to be interested, and to want to get into these careers. And I think also it's important for younger girls to let them know these careers are really fun and they're extremely rewarding. And I mean, I hate to use this as an incentive, but there's also a lot of money that can be made too, and that's an incentive to get, you know, women and girls into these careers as well. >> And Tyler, I think you're right. In addition to that, you're always going to have a job. And I think cyber is a great career for someone that are lifelong learners, because like you said, your 11 year old niece, the job, when she graduates from college, she may have, probably doesn't even exist today. And so I think you have to be a lifelong learner. I think one of the things that people may not be aware of is, you know, for women who may have gone the non-traditional route and got degrees later in life, or took time off to raise children and want to come back to work, cyber security is something that, you know, doesn't have to be a nine to five job. I have, it happens to be a gentlemen on my team, who has to get kids on the bus and off the bus. And so we figured out how, you know, he gets up and he works for a couple hours, puts kids on the bus, is in the office. And then he gets the kids off. And once they've had dinner and gone to bed, he puts in a couple more hours. And I think, you know, people need to be aware of, there is some flexibility, there is flexibility in cyber jobs. I mean, it's not a nine to five job, it's not like banking. Well, if you were teller, and your hours are when the bank is open, cyber is 7/24 and jobs can be flexible. And I think people need to be aware of that. >> I agree on the flexibility front, and people also need to be flexible themselves. I do want to ask you both, we're getting low on time, but I've got to ask you, how do you get the confidence, to be, like you said, back in the day, in the room, maybe the only female and I've been in that as well, even in marketing, product marketing years ago. How do you get the confidence to continue moving forward? Even as someone says, "You're only here because you're a female." Tyler, what's your advice to help young women and young men as well fight any sort of challenges that are coming their way? >> I had a mentor when I first moved to the Defense Intelligence Agency, I had an Office Chief and she said to me, "Tyler, you're a Senior Intelligence Officer, you always take a seat at the table. Do not let anyone tell you that you cannot have a seat at the table." And you know, that was good advice. And I think confidence is great. But courage is something that's much more important, because courage is what leads up to confidence. And you really have to believe in yourself and do things that you know are right for you, not because you think it's going to make other people happy. And I think, you know, as women, it's really finding that courage to be brave and to be strong and to be willing to stand out, you know, alone on something, because it's what you care about and what you believe in. And that's really what helps kind of motivate me. >> I love that courage. Debbie, what are your thoughts? >> (laughs) So I was going to say, this is going to be really hard to believe, but when I was 16 years old, I was so shy that if I went to a restaurant and someone served me stone cold food, I wouldn't say a word. I would just eat it. If I bought something in a store and I didn't like it, I'd refuse, I just couldn't bring myself to go to that customer service desk and return it. And my first job in high school, was it a fast food place. And I worked for a gentleman who was a little bit of a tyrant, but you know, I learned how to get a backbone very quickly. And I would have to say now looking back, he was probably my first mentor without even trying to do that. He mentored me on how to believe in myself and how to stand up for what's right. So, Tyler, I completely agree with you. And you know, that's something that people think when they get a mentorship, sometimes it's someone going to mentor them on, you know, something tactical, something they want to know how to do, but sometimes what you need to be mentored in, could be, "How do I believe in myself?" Or "How do I find the courage to be that the only female in the room?" And I think that is where some of that mentorship comes from and, you know, I think, you know, if we go back to mentoring at the middle school, there's lots of opportunities, career fairs, the first robotically, get the middle school level, gives all of us an opportunity to sort of mentor girls at that level. And for all the guys out there who have daughters, this is, you know, how to... It's not like you can get a parenting checklist, "Teach my kid courage." And Tyler, I love that word, but I think that's something that we all need to aspire to bring out in others. >> I love that. I love that. >> Okay with that, I think I love both of your stories, are zig-zaggy in certain ways, one in a more direct cybersecurity path, Debbie with yours. Tyler, yours, very different coming from the music industry. But you both have such great advice. It's really, I would say, I'm going to add that, open your mind to be open to, you can do anything. As Tyler said, there's a very great possibility that right now the job that your niece who's 11 is going to get in the next 10 years, doesn't exist yet. How exciting is that? To have the opportunity to be open-minded enough and flexible enough to say, "I'm going to try that." And I'm going to learn from my mentors, whether it's a fast food cook, which I wouldn't think would be a direct mentor, and recognizing years later, "Wow, what an impact that person had on me, having the courage to do what I have." And so I would ask you like each one more question in terms of just your inspiration for what you're currently doing. Debbie, as the leader of security for NETSCOUT, what inspires you to continue in your current role and seek more? >> So, I'm a lifelong learner. So, I love to learn cybersecurity. You know, every day is a different day. So, it's definitely the ability to continue to learn and to do new things. But the second thing is, is I think I've always been, I don't want to call it a fixer-upper because cybersecurity isn't a fixer-upper, I'm just always wanted to improve upon things. If I've seen something that I think can do better, or a product that could have something new or better in it, you know, that's what excites me is to give people that feedback and to improve on what we've had out there. You know, you had mentioned, we've got this block of jobs that we can't fill. We have to give feedback and how we get the tools and what we have today smarter, so that if there are less of us, we're working smarter and not harder. And so if there is some low-level tasks that we could put back into tools, and talk to vendors and have them do this for us, that's how I think we start to get our way sort of out of the hole. Tyler, any thoughts on that? >> I again, I love that answer. I mean, I think for me, you know, I do like, it's that problem solving thing too. But for me it's also about, it's about compassion. And when I see, you know, a story of some child that's been involved in some kind of cyber bullying attack, or a company that has been broken into, I want to do whatever I can to help people, and to teach people to really protect themselves, so that they feel empowered and they're not afraid of cyber security. So for me, it's also really that drive to really make a difference and really help people. >> And you've both done, I'm sure, so much of that made such a big difference in many communities in which you're involved. I thank you so much for sharing your journeys with me on the program today, and giving such great pointed advice to young men and women, and even some of the older men and women out there that might be kind of struggling about, where do I go next? Your advice is brilliant, ladies. Thank you so much. It's been a pleasure talking with you. >> Thank you. >> Thank you. >> For Debbie Briggs and Tyler Cohen Wood, I'm Lisa Martin. You've been watching this Cube Conversation. (upbeat music)

>> Hi, and welcome to data cloud catalyst women in tech round table panel discussion. I am so excited to have three fantastic female executives with me today who have been driving transformation through data throughout their entire career. With me today is Lisa Davis SVP and CIO of Blue Shield of California. We also have Nishita Henry who is the chief innovation officer at Deloitte and Teresa Briggs, who is on a variety of board of directors, including our very own Snowflake. Welcome, ladies. >> Thank you. So I'm just going to dive right in. You all have really amazing careers and resumes behind you. I'm really curious, throughout your career, how have you seen the use of data evolve throughout your career? And Lisa, I'm going to start with you. >> Thank you. Having been in technology my entire career, technology and data has really evolved from being the province of a few in an organization to frankly being critical to everyone's business outcomes. But now every business leader really needs to embrace data analytics and technology. We've been talking about digital transformation probably the last five, seven years. We've all talked about disrupt or be disrupted. At the core of that digital transformation is the use of data, data, and analytics that we derive insights from and actually improve our decision-making by driving a differentiated experience and capability into market. So data has involved as being, I would say, almost tactical in some sense over my technology career to really being a strategic asset of what we leveraged personally in our own careers, but also what we must leverage as companies to drive a differentiated capability to experience and remain relative in the market today. >> Nishita curious your take on, how you've seen data evolve? >> Yeah, I agree with Lisa, it has definitely become the lifeblood of every business, right? It used to be that there were a few companies in the business of technology. Every business is now a technology business. Every business is a data business. It is the way that they go to market, shape the market and serve their clients. Whether you're in construction, whether you're in retail, whether you're in healthcare doesn't matter, right? Data is necessary for every business to survive and thrive. And I remember at the beginning of my career, data was always important, but it was about storing data. It was about giving people individual reports. It was about supplying that data to one person or one business unit in silos. And it then evolved right over the course of time and to integrating data and to saying, all right, how does one piece of data correlate to the other? And how can I get insights out of that data? Now let's go on to the point of how do I use that data to predict the future? How do I use that data to automate the future? How do I use that data not just for humans to make decisions but for other machines to make decisions, right? Which is a big leap and a big change in how we use data, how we analyze data and how we use it for insights and evolving our businesses. >> Yeah. It's really changed so tremendously, just in the past five years, it's amazing. So Teresa, we've talked a lot about the data cloud, where do you think we're heading with that? And also how can future leaders really guide their careers in data, especially in those jobs where we don't traditionally think of them in the data science space, curious your thoughts on that. >> Yeah. Well, since I'm on the Snowflake board, I'll talk a little bit about the Snowflake data cloud that we're getting your company's data out of the silos that exist all over your organization. We're bringing third party data in to combine with your own data and we're wrapping a governance structure around it and feeding it out to your employees so that they can get their jobs done. And it's as simple as that, I think we've all seen the pandemic accelerated the digitization of our work. And if you ever doubted that the future of work is here, it is here. And companies are scrambling to catch up by providing the right amount of data, collaboration tools, workflow tools for their workers to get their jobs done. Now it used to be, as prior, people have mentioned that in order to work with data, you had to be a data scientist. But I was an auditor back in the day and we used to work on 16 columns spreadsheet. And now if you're an accounting major coming out of college, joining an auditing firm, you have to be tech and data savvy because you're going to be extracting, manipulating, analyzing, and auditing data. That massive amounts of data that sit in your client's IT systems. I'm on the board of Warby Parker. And you might think that their most valuable asset is their amazing frame collection but it's actually their data. There are 360 degree view of the customer. And so if you're a merchant or you're in strategy or marketing or talent or the co-CEO, you're using data every day in your work. And so I think it's going to become a ubiquitous skill that any anyone who's a knowledge worker has to be able to work with data. >> Now, I think it's just going to be organic to every role going forward in the industry. >> So Lisa curious about your thoughts about data cloud, the future of it, and how people can really leverage it in their jobs from future leaders. >> Yeah, absolutely. Most enterprises today are, I would say, hybrid multi-cloud enterprises. What does that mean? That means that we have data sitting on prem. We have data sitting in public clouds through software, as a service applications. We have a data everywhere. Most enterprises have data everywhere. Certainly those that have owned infrastructure or weren't born on the web. One of the areas that I'd love that data cloud is addressing is the area around data portability and mobility. Because I have data sitting in various locations through my enterprise, how do I aggregate that data to really drive meaningful insights out of that data to drive better business outcomes. And at Blue Shield of California, one of our key initiatives is what we call an experience cube. What does that mean? It means how do I drive transparency of data between providers and members and payers so that not only do I reduce overhead on providers and provide them a better experience or hospital systems or doctors, but ultimately how do we have the member have at their power of their fingertips the value of their data holistically so that we're making better decisions about their healthcare? One of the things Teresa was talking about was the use of this data. And I would drive to data democratization. We got to put the power of data into the hands of everyone, not just data scientists. Yes, we need those data scientists to help us build AI models to really drive and tackle these tougher challenges and business problems that we may have in our environments. But everybody in the company, both on the IT side, both on the business side, really need to understand of how do we become a data insights driven enterprise, put the power of the data into everyone's hands so that we can accelerate capabilities, right? And leverage that data to ultimately drive better business results. So as a leader, as a technology leader, part of our responsibility, our leadership is to help our companies do that. And that's really one of the exciting things that I'm doing in my role now at Blue Shield of California. >> Yeah. It's really, really exciting time. I want to shift gears a little bit and focus on women in tech. So I think in the past 5 to 10 years there has been a lot of headway in this space but the truth is women are still underrepresented in the tech space. So what can we do to attract more women into technology? Quite honestly. So Nishita curious what your thoughts are on that? >> Great question. And I am so passionate about this for a lot of reasons, not the least of which is I have two daughters of my own and I know how important it is for women and young girls to actually start early in their love for technology and data and all things digital, right? So I think it's one very important to start early, starting early education, building confidence of young girls that they can do this, showing them role models. We at Deloitte just partnered with LOV engineer to actually make comic books centered around young girls and boys in the early elementary age to talk about how heroes in techs solve everyday problems. And so really helping to get people's minds around tech is not just in the back office, coding on a computer, tech is about solving problems together that help us as citizens as customers, right? And as humanity. So I think that's important. I also think we have to expand that definition of tech as we just said, it's not just about database design. It's not just about Java and Python coding. It's about design, it's about the human machine interfaces. It's about how do you use it to solve real problems and getting people to think in that kind of mindset makes it more attractive and exciting. And lastly, I'd say, look we have a absolute imperative to get a diverse population of people, not just women but minorities, those with other types of backgrounds, disabilities, et cetera, involved because this data is being used to drive decision-making, and if we're all involved and how that data makes decisions, it can lead to unnatural biases that no one intended but can happen just 'cause we haven't involved a diverse enough group of people around it. >> Absolutely. Lisa, I'm curious about your thoughts on this. >> Oh, I agree with everything Nishita said. I've been passionate about this area. I think it starts with first, we need more role models. We need more role models as women in these leadership roles throughout various sectors. And it really is, it starts with us and helping to pull other women forward. So I think it certainly it's part of my responsibility. I think all of us as female executives that if you have a seat at the table to leverage that seat at the table to drive change to bring more women forward, more diversity forward into the boardroom and into our executive suites. I also want to touch on a point Nishita made about women. We're the largest consumer group in the company yet we're consumers, but we're not builders. This is why it's so important that we start changing that perception of what tech is. And I agree that it starts with our young girls. We know the data shows that we lose our young girls by middle school, very heavy peer pressure. It's not so cool to be smart or do robotics or be good at math and science. We start losing our girls in middle school. So they're not prepared when they go to high school and they're not taking those classes in order to major in these STEM fields in college. So we have to start the pipeline early with our girls. And then I also think it's a measure of what your boards are doing. What is the executive leadership and your goals around diversity and inclusion? How do we invite more diverse population to the decision-making table? So it's really a combination of efforts. One of the things that certainly is concerning to me is during this pandemic, I think we're losing one in four women in the workforce now because of all the demands that our families are having to navigate through this pandemic. The last statistic I saw in the last four months is we've lost 850,000 women in the workforce. This pipeline is critical to making that change in these leadership positions. >> Yeah, it's really a critical time. And now we're coming to the end of this conversation. I want to ask you Teresa, what would be a call to action to everyone listening, both men and women since it needs to be solved by everyone to address the gender gap in the industry. >> I'd encourage to you to become an active sponsor. Research shows that women and minorities are less likely to be sponsored than white men. Sponsorship is a much more active form than mentorship. Sponsorship involves helping someone identify career opportunities and actively advocating for them in those roles, opening your network, giving very candid feedback. And we need men to participate too. There are not enough women in tech to pull forward and sponsor the high potential women that are in our pipelines. And so we need you to be part of the solution. >> Nishita, real quickly, what would be your call to action to everyone? >> I'd say, look around your teams, see who's on them and make deliberate decisions about diversifying those teams, as positions open up, make sure that you have a diverse set of candidates. Make sure that there are women that are part of that team and make sure that you are actually hiring and putting people into positions based on potential, not just experience. >> And real quickly, Lisa, we'll close it out with you. What would your call to action be? >> Well, it's hard to, but Nishita and what Teresa shared, I think were very powerful actions. I think it starts with us taking action at our own table, making sure you're driving diverse panels and hiring, setting goals for the company, having your board engaged and holding us accountable and driving to those goals will help us all see a better outcome with more women at the executive table and diverse populations. >> So I want to talk to you all about a pivotal moment in your career. It could have been a mentorship. It could have been maybe a setback in your career or maybe a time that you really took a risk and it paid off big, something that really helped define your career going forward. Curious what those moments were for you all in your career. Teresa, we'll start with you. >> Sure. I had a great sponsor and he was a white male by the way. He identified some potential in me when I was early in my career about five years in and he really helped pave the way for a number of decisions I made along the way to take different roles in the firm. I was at Deloitte, he's still in my life today. We get together a couple of times a year. And even though we're both retired from Deloitte, we still have that relationship and what that tell me was how to be a great sponsor. And so one of the most satisfying things I did in my career was when I finally got to the place where I was no longer reaching for the next rank of the ladder for myself, I got to turn around and pull through all of these amazing future leaders into roles that were going to help them accelerate their careers. >> What about you, Lisa? >> I think there's been many of those moments. One I'll speak about is having spin 20, 25 years in technology, I had spent my first career in department of defense, moved over to academia and then went to a high-tech firm on their IT side, really in hopes of getting the CIO role having been a CIO, I did not get the CIO role, and really had a decision to make. One of the opportunities that was presented to me was to move to the business side to run a $9 billion P&L on one of the core business units within the company. And of course, I was terrified. It was a very risky decision having never run a P&L before and not starting small going right to the billion dollar mark in terms of (laughs) what that would look like. And frankly decided to seize that opportunity and I've certainly learned in my career that those opportunities that really push you out of your comfort zone that take you down a really completely different path or where the greatest opportunities for growth and learning occur. So I did that role for three and a half years before coming into my current role back to a CIO role at Blue Shield of California in healthcare, and just a tremendous amount of learning, having been on the business side and managing a P&L that I now apply to how I engage with my partners at Blue Shield. >> I couldn't agree more. I think forcing yourself out of that comfort zone is so critical for learning and driving your career for sure. Nishita, what about you? >> Yeah, I agree. Lots of pivotal moments, but I'll talk about one very early in my career, actually was an intern and one of my responsibilities was to help research back then facial recognition technology. And I had to go out there and evaluate vendors and take meetings with vendors and figure out, all right, which ones do we want to actually test? And I remember I was leading a meeting, two of my kind of supervisors were with us. And I know I went through the list of questions and then the meeting kind of ended. And I didn't speak up at that point in time to kind of say here are the next steps or here's what I recommend. I kind of looked at my supervisors to do that. Just assuming they should be wrapping it up and they should be the ones to make a final decision or choice. And after that meeting, he came to me and he's like you know Nishita you did a really nice job in bringing these technologies forward but I wish you would have spoken up because you're the one who've done the most research. And you're the one who has the most background on what we should do next. Next time don't stand by and let someone else be your voice. And it was so powerful for me and I realized, wow, I should have more confidence in myself to be able to actually use my voice and do what I was asked to do versus leave it to someone else because I assumed that I was too junior or I assumed I didn't have enough experience. So that was really pivotal for me early in my career to learn how to use my voice. >> I'm really curious for you, Nishita. What drew you to the industry of data? What was something when you were young that drew you into that space? >> Yeah. So my background is actually in engineering and it's actually funny. It's an electrical engineering and I probably couldn't do another thermal dynamics equation to save my life anymore (laughs). But what drew me to technology was problem solving, right? It was all about how do I take a bunch of data and information and create a new solution, right? Whether it was, how do I create a device? I remember in college, right? Creating a device to go down stadium steps and clean, right? How do I take data for how this machine will interact with the environment in order to create it? So I always viewed it as problem solving and that's what has always attracted me into the field. >> That's great. So, Teresa, I'm curious, at what point did you feel that you really found your voice in your career, in yourself as a part of your professional life? >> Yeah. About 12 years into my career I started working as an M&A partner and I was working with a private equity firm along with their lawyers and other advisors, bankers and so forth. And what I realized in that situation was that I was the expert in what I did. And so, I mean, I found my voice before that in many other ways but that was sort of a moment where I felt like, "I'm here to deliver an expertise to this group of people. And none of them have the expertise that I have. And so I need to just stand firm in my shoes and deliver that expertise with confidence." So that was my example. >> That's great. Well, Lisa, what about you? What was that moment that you felt that you just found your voice kind of in your groove and that confidence kicked in? >> No, I don't know if it was exactly a moment but it was certainly a realization. Right out of college, I was working for the federal government in department of defense and certainly male dominated. And through that realized that to be heard, I had to become very good at what I do. So I built that confidence, frankly, by delivering results and capability and becoming an expert in the work, essentially the services that I provide. And when you become very good at what you do, regardless of what you look like, then people will start to listen. So I think it starts with delivering results. I think you have to build your confidence and through that you find to use your voice so that you are being heard, having worked in department of defense and academia and high tech, I've had to leverage that throughout my entire career ultimately for my voice to be heard, and to be represented within the roles that I was playing. >> That's great. I know one of the things that we've also talked about is just the value, the business value, the importance of having a diverse workforce and a diverse team and the value that that brings to the outcomes. What are some of your strategies to create those types of teams? What, as leaders in your company, you manage a team and what is your advice to them, your strategies to get a diverse pool of candidates and a diverse team. Nishita, what about you? >> I think it's looking beyond what the individual role is, right? So a lot of times we have a role description and you want these certain skills and so (indistinct), or you get a certain set of candidates. I think it's taking a step back and saying, "What are the objectives of my team? What am I trying to accomplish? What types of business acumen do I need on that team? What types of tech acumen, what types of personalities? Do I want people who know how to work with others and therefore bring them together? Do I need people who are also drivers and know how to get things done, right?" It's finding the right chemistry. We have a business chemistry, talk track around. We don't need all different kinds to make a really good team. So I think it's taking a step back and understanding what you need the makeup of your team to be, understanding the hard skills and the soft skills. And then thinking about what are all the sources you could really go to for them and being a little bit non-traditional and saying, "Do I need a full-time person all the time to do this job that's sitting here? Can I be more diverse in finding people from the crowd? Can I have part-time resources? Can I use different pieces and parts of the ecosystem to actually bring together the full team that represents the diversity?" It's just expanding our mind and stop thinking about a role to person, start thinking about it as the makeup of a team, to the outcome you desire. >> It's really about being creative and just thinking in new ways. Teresa, I'm super curious, since you sit on a bunch of different boards, what kind of strategies do you see companies taking to attract different talent? >> So I can address that from the board lens, for sure. And boards are probably one of the least diverse bodies in business right now, but that is changing, and for the better, obviously they were traditionally kind of white male dominated. And then we've had this wave of women joining boards. And now we're starting to see a wave of diverse individuals join boards. And with each person who's diverse that joins a board that I'm on, the dynamic of the discussion changes because they bring a different perspective. They bring a different way of thinking. They came from a different background or a different functional skillset or a different geography or you name, whatever element of diversity you want to see. We just added the head of Apple music to the service in our board. And so you might scratch your head and say, "Wow, the head of Apple music and an enterprise software company that is a B2B software company." But he thinks deeply about how the end user consumes in his case content and in our case software. And so he's able to bring just a completely different perspective to the discussion we have at the board table. And I think at the end of the day, that's what diversity is all about, is improving the outcome of whatever it is. If you're producing something or making important decisions like we do in board rooms. >> That's amazing. Lisa, real quickly, what are some of your strategies? >> Yeah. Well, we know diverse teams actually produce better business results. So there's no reason, there's absolutely no reason why we shouldn't think in that lens. I think it starts with our hiring and the makeup of our teams. I think it requires more than creativity though. You have to be very purposeful. I'm in the process of hiring four leadership positions on my team. And it's really to me, almost like a puzzle piece of diverse perspectives and knowledge and capabilities that come together that ultimately create a high performing team. But I can't tell you how many times I got to go back to HR and say, "I need to see more diverse talent. Are there any more women in the pool?" One of the things we've struggled, we have to get more women into the roles is, and we heard this from Sheryl Sandberg, as women, we feel we need to meet every qualification on an application. Whereas men, "I got a couple I'm good to go." And they throw their name in the hat. They take much more risk than we do as women. So we need to encourage our women to get out of your comfort zone. You don't need to meet every qualification. What Nishita was saying of thinking more broadly about what this role requires and the type of individual that we're looking for, but be purposeful in terms of driving to diversity as our end result. >> That is so true. What you just said. Thank you so much for sharing your insights. It's really interesting to hear all your strategies and thanks for sharing. >> And you're clear.

>> Announcer: From around the globe, it's theCUBE. Covering the UPGRADE 2020, the NTT Research Summit. Presented by NTT research. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. Welcome back to our ongoing coverage of UPGRADE 2020. It's the NTT Research Labs Summit, and it's all about upgrading reality. Heavy duty basic research around a bunch of very smart topics. And we're really excited to have our next guest to kind of dive in. I promise you, it'll be the deepest conversation you have today, unless you watch a few more of these segments. So our first guest we're welcoming back Kazuhiro Gomi He's the president and CEO of NTT research, Kaza great to see you. >> Good to see you. And joining him is Yoshi Yamamoto. He is a fellow for NTT Research and also the director of the Physics and Informatics Lab. Yoshi, great to meet you as well. >> Nice to meet you. >> So I was teasing the crew earlier, Yoshi, when I was doing some background work on you and I pulled up your Wikipedia page and I was like, okay guys, read this thing and tell me what a, what Yoshi does. You that have been knee deep in quantum computing and all of the supporting things around quantum heavy duty kind of next gen computing. I wonder if you can kind of share a little bit, you know, your mission running this labs and really thinking so far in advance of what we, you know, kind of experience and what we work with today and this new kind of basic research. >> NTT started the research on quantum computing back in 1986 87. So it is already more than 30 years. So, the company invested in this field. We have accumulated a lot of sort of our ideas, knowledge, technology in this field. And probably, it is the right time to establish the connection, close connection to US academia. And in this way, we will jointly sort of advance our research capabilities towards the future. The goal is still, I think, a long way to go. But by collaborating with American universities, and students we can accelerate NTT effort in this area. >> So, you've been moving, you've been working on quantum for 30 years. I had no idea that that research has been going on for such a very long time. We hear about it in the news and we hear about it a place like IBM and iSensor has a neat little demo that they have in the new sales force period. What, what is, what makes quantum so exciting and the potential to work so hard for so long? And what is it going to eventually open up for us when we get it to commercial availability? >> The honest answer to that question is we don't know yet. Still, I think after 30 years I think of hard working on quantum Physics and Computing. Still we don't know clean applications are even, I think we feel that the current, all the current efforts, are not necessarily, I think, practical from the engineering viewpoint. So, it is still a long way to go. But the reason why NTT has been continuously working on the subject is basically the very, sort of bottom or fundamental side of the present day communication and the computing technology. There is always a quantum principle and it is very important for us to understand the quantum principles and quantum limit for communication and computing first of all. And if we are lucky, maybe we can make a breakthrough for the next generation communication and computing technology based on quantum principles. >> Right. >> But the second, is really I think just a guess, and hope, researcher's hope and nothing very solid yet. >> Right? Well, Kazu I want to go, go to you cause it really highlights the difference between, you know, kind of basic hardcore fundamental research versus building new applications or building new products or building new, you know, things that are going to be, you know, commercially viable and you can build an ROI and you can figure out what the customers are going to buy. It really reflects that this is very different. This is very, very basic with very, very long lead times and very difficult execution. So when, you know, for NTT to spend that money and invest that time and people for long, long periods of time with not necessarily a clean ROI at the end, that really, it's really an interesting statement in terms of this investment and thinking about something big like upgrading reality. >> Yeah, so that's what this, yeah, exactly that you talked about what the basic research is, and from NTT perspective, yeah, we feel like we, as Dr. Yamamoto, he just mentioned that we've been investing into 30 plus years of a time in this field and, you know, and we, well, I can talk about why this is important. And some of them is that, you know, that the current computer that everybody uses, we are certainly, well, there might be some more areas of improvement, but we will someday in, I don't know, four years, five years, 10 years down the road, there might be some big roadblock in terms of more capacity, more powers and stuff. We may run into some issues. So we need to be prepared for those kinds of things. So, yes we are in a way of fortunate that we are, we have a great team to, and a special and an expertise in this field. And, you know, we have, we can spend some resource towards that. So why not? We should just do that in preparation for that big, big wall so to speak. I guess we are expecting to kind of run into, five, 10 years down the road. So let's just looking into it, invest some resources into it. So that's where we are, we're here. And again, I I'm, from my perspective, we are very fortunate that we have all the resources that we can do. >> It's great. Right, as they give it to you. Dr. Yamamoto, I wonder if you can share what it's like in terms of the industry and academic working together. You look at the presentations that are happening here at the event. All the great academic institutions are very well represented, very deep papers. You at NTT, you spend some time at Stanford, talk about how it is working between this joint development with great academic institutions, as well as the great company. >> Traditionally in the United States, there has been always two complementary opportunities for training next generation scientists and engineers. One opportunity is junior faculty position or possible position in academia, where main emphasis is education. The other opportunity is junior researcher position in industrial lab where apparently the focus emphasis is research. And eventually we need two types of intellectual leaders from two different career paths. When they sort of work together, with a strong educational background and a strong research background, maybe we can make wonderful breakthrough I think. So it is very important to sort of connect between two institutions. However, in the recent past, particularly after Better Lab disappeared, basic research activity in industrial lab decreases substantially. And we hope MTT research can contribute to the building of fundamental science in industry side. And for that purpose cross collaboration with research Universities are very important. So the first task we have been working so far, is to build up this industry academia connection. >> Huge compliment NTT to continue to fund the basic research. Cause as you said, there's a lot of companies that were in it before and are not in it any more. And when you often read the history of, of, of computing and a lot of different things, you know, it goes back to a lot of times, some basic, some basic research. And just for everyone to know what we're talking about, I want to read a couple of, of sessions that you could attend and learn within Dr. Yamamoto space. So it's Coherent nonlinear dynamics combinatorial optimization. That's just one session. I love it. Physics successfully implements Lagrange multiplier optimization. I love it. Photonics accelerators for machine learning. I mean, it's so it's so interesting to read basic research titles because, you know, it's like a micro-focus of a subset. It's not quantum computing, it's all these little smaller pieces of the quantum computing stack. And then obviously very deep and rich. Deep dives into those, those topics. And so, again, Kazu, this is the first one that's going to run after the day, the first physics lab. But then you've got the crypto cryptography and information security lab, as well as the medical and health information lab. You started with physics and informatics. Is that the, is that the history? Is that the favorite child you can lead that day off on day two of the event. >> We did throw a straw and Dr. Yamamoto won it Just kidding (all laugh) >> (indistinct), right? It's always fair. >> But certainly this quantum, Well, all the topics certainly are focuses that the basic research, that's definitely a commonality. But I think the quantum physics is in a way kind of very symbolic to kind of show that the, what the basic research is. And many people has a many ideas associated with the term basic research. But I think that the quantum physics is certainly one of the strong candidates that many people may think of. So well, and I think this is definitely a good place to start for this session, from my perspective. >> Right. >> Well, and it almost feels like that's kind of the foundational even for the other sessions, right? So you talk about medical or you talk about cryptography in information, still at the end of the day, there's going to be compute happening to drive those processes. Whether it's looking at, at, at medical slides or trying to do diagnosis, or trying to run a bunch of analysis against huge data sets, which then goes back to, you know, ultimately algorithms and ultimately compute, and this opening up of this entirely different set of, of horsepower. But Dr. Yamamoto, I'm just curious, how did you get started down this path of, of this crazy 30 year journey on quantum computing. >> The first quantum algorithm was invented by David Deutsch back in 1985. These particular algorithm turned out later the complete failure, not useful at all. And he spent seven years, actually, to fix loophole and invented the first successful algorithm that was 1992. Even though the first algorithm was a complete failure, that paper actually created a lot of excitement among the young scientists at NTT Basic Research Lab, immediately after the paper appeared. And 1987 is actually, I think, one year later. So this paper appeared. And we, sort of agreed that maybe one of the interesting future direction is quantum information processing. And that's how it started. It's it's spontaneous sort of activity, I think among young scientists of late twenties and early thirties at the time. >> And what do you think Dr. Yamamoto that people should think about? If, if, if again, if we're at a, at a cocktail party, not with not with a bunch of, of people that, that intimately know the topic, how do you explain it to them? How, how should they think about this great opportunity around quantum that's kept you engaged for decades and decades and decades. >> The quantum is everywhere. Namely, I think this world I think is fundamentally based on and created from quantum substrate. At the very bottom of our, sort of world, consist of electrons and photons and atoms and those fundamental particles sort of behave according to quantum rule. And which is a very different from classical reality, namely the world where we are living every day. The relevant question which is also interesting is how our classical world or classical reality surfaces from the general or universal quantum substrate where our intuition never works. And that sort of a fundamental question actually opens the possibility I think by utilizing quantum principle or quantum classical sort of crossover principle, we can revolutionize the current limitation in communication and computation. That's basically the start point. We start from quantum substrate. Under classical world the surface is on top of quantum substrate exceptional case. And we build the, sort of communication and computing machine in these exceptional sort of world. But equally dig into quantum substrate, new opportunities is open for us. That's somewhat the fundamental question. >> That's great. >> Well, I'm not, yeah, we can't get too deep cause you'll lose me, you'll lose me long before, before you get to the bottom of the, of the story, but, you know, I really appreciate it. And of course back to you this is your guys' first event. It's a really bold statement, right? Upgrade reality. I just wonder if, when you look at the, at the registrant's and you look at the participation and what do you kind of anticipate, how much of the anticipation is, is kind of people in the business, you know, kind of celebrating and, and kind of catching up to the latest research and how much of it is going to be really inspirational for those next, you know, early 20 somethings who are looking to grab, you know, an exciting field to hitch their wagon to, and to come away after this, to say, wow, this is something that really hooked me and I want to get down and really kind of advance this technology a little bit, further advance this research a little bit further. >> So yeah, for, from my point of view for this event, I'm expecting, there are quite wide range of people. I'm, I'm hoping that are interested in to this event. Like you mentioned that those are the, you know, the business people who wants to know what NTT does, and then what, you know, the wider spectrum of NTT does. And then, and also, especially like today's events and onwards, very specific to each topic. And we go into very deep dive. And, and so to, to this session, especially in a lot of participants from the academia's world, for each, each subject, including students, and then some other, basically students and professors and teachers and all those people as well. So, so that's are my expectations. And then from that program arrangement perspective, that's always something in my mind that how do we address those different kind of segments of the people. And we all welcoming, by the way, for those people. So to me to, so yesterday was the general sessions where I'm kind of expecting more that the business, and then perhaps some other more and more general people who're just curious what NTT is doing. And so instead of going too much details, but just to give you the ideas that the what's that our vision is and also, you know, a little bit of fla flavor is a good word or not, but give you some ideas of what we are trying to do. And then the better from here for the next three days, obviously for the academic people, and then those who are the experts in each field, probably day one is not quite deep enough. Not quite addressing what they want to know. So day two, three, four are the days that designed for that kind of requirements and expectations. >> Right? And, and are most of the presentations built on academic research, that's been submitted to journals and other formal, you know, peer review and peer publication types of activities. So this is all very formal, very professional, and very, probably accessible to people that know where to find this information. >> Mmh. >> Yeah, it's great. >> Yeah. >> Well, I, I have learned a ton about NTT and a ton about this crazy basic research that you guys are doing, and a ton about the fact that I need to go back to school if I ever want to learn any of this stuff, because it's, it's a fascinating tale and it's it's great to know as we've seen these other basic research companies, not necessarily academic but companies kind of go away. We mentioned Xerox PARC and Bell Labs that you guys have really picked up that mantle. Not necessarily picked it up, you're already doing it yourselves. but really continuing to carry that mantle so that we can make these fundamental, basic building block breakthroughs to take us to the next generation. And as you say, upgrade the future. So again, congratulations. Thanks for sharing this story and good luck with all those presentations. >> Thank you very much. >> Thank you. >> Thank you. Alright, Yoshi, Kazu I'm Jeff, NTT UPGRADE 2020. We're going to upgrade the feature. Thanks for watching. See you next time. (soft music)

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum, World 2019 brought to you by the M Wear and its ecosystem partners. >> Hello, Welcome back, everyone to the Cubes Live coverage of the Emerald 2019. I'm John Career with Lycos Day, Volante Dave. 10 years covering the Q Weird Mosconi and 2010 boy Lots changed, but >> it's still the >> platform that Palmer Ritz laid out. But the stuff filling in 10 years later. >> Okay, you call that software mainframe and Robin came in so I can't call Mainframe Way >> Have leaders from PM Wears Largest business unit. The Cloud Platform Business Kid Colbert to CTO and Christmas R S v P and General Manager Guys, Thanks for coming on The key. Appreciate. >> Yeah, that's for having us. The >> world's your business units smoking hot. It's very popular, like you run around doing meetings. Cloud platform is the software model that's 10 years later actually happening at scale. Congratulations. What's the What's the big news? What's the big conversation for you guys? >> Yeah, the biggest news this week is the announcement of project specific, and, um, it's about taking the platform a Jess, um, hundreds of thousands of customers on it and bringing together communities were just now very popular with the developers and that black form together so that operators, on the one hand, can just deal with the platform they love. And the developers can deal with the kubernetes layer that they love. >> It's interesting to watch because, you know, the whole end user computing stack that was laid out 10 years ago is actually happening now, Assassin see, sass business models. We all see the and half of them is on the success of Cloud. But interesting to see kubernetes, which we've been following since the report started. Open stack days. You saw that emerging. Everyone kind of saw that. And it really became a nice layer. And the industry just create as a de facto. Yeah, you guys were actually driving that more forward. So congratulations on that. >> That's sitting it >> natively in V sphere is interesting because you guys spend a ton of time. This is a core product for you guys. So you're bringing something native into V sphere? I'm sure there's a lot of debates internally how to do that, kid. What's that? What is the relevance workers. You guys have a lot of efficiencies and be severe, but bring in kubernetes is gonna give you some new things. What, >> So the thinking is really you know, it's Christmas mentioning. How do we take this proven platform? Move it forward. Customers have moved millions of work clothes on top of the sphere, operate them in production, the Prussian great capabilities, and so they'd be able to be very successful in that. And so the question is, how do we help them move forward in the kubernetes? You know, you mentioned Crew readies is still fairly young, the ecosystem around. It's still somewhat immature, still growing right, and it's a very different environment than what folks are used to who used the sphere. So there's a big challenge that customers have around managing multiple environments. All the training that's different, all the tools that are different so we can actually take their investments. They've already made into V sphere leverage and extend those into the kubernetes world that's really powerful. We'll help our customers take all these millions of workloads and move them forward. It's >> interesting because we were always speculating about being where I started Jerry Chan when he was on yesterday. He's been of'em where since early days, you know, but looking at VM where when they went to their you guys went back to your core When we be cloud air kind of win its way and then you deal them is on since the stock price has been going great, So great chair older takeover value there. But you got clarity around what cloud was. And as you look at the operator target audience, you guys have the operators and the devil and ops is critical. So you guys have been operating a lot of work, Liz and I think this is fascinating. So the role of containers is super relevant because you got V EMS and containers. So again, the debate continues. >> Well, I think >> Tainer is wrong. Where Bond, It's interesting conversation because kubernetes is orchestrating all that >> while the snarky treat tweet Oh day and you guys feel free to come. It was Oh, I thought we started launch pivotal. So we didn't have to run containers on virtual machines. Yeah, we know that people run containers on bare metal. They run containers and virtual machines, but >> yeah, It's a debate that that we hear pop up on the on the snarky Twitter feeds and so forth. We'll talk to customers about it. You know, this whole VM versus container debate, I think, really misses the point because it's not really about that. What it's about is how do I actually operate? These were close in production, right? This kind of this three pillows we talk about build, run, manage. Custer's want to accelerate that They won't do that with enterprise, great capabilities with security. And so that's where it really gets challenging. And I think you know, we've built this amazing ecosystem around desire to achieve that. And so that's what we're taking forward here. And, yes, the fact that we're using fertilization of the covers, that's an implementation detail. Almost. What's more, valuables? All the stuff above that the manageability, the operational capabilities. That's a real problem. It seems to >> me, to the business impact because, okay, people going to go to the cloud, they're gonna build cloud native acts. But you've got all these incumbent companies trying not to get disrupted to trying to find new opportunities, playing offense and defense at the same time, they need tooling to be able to do that. They don't want to take their e r p ap and stick it in the cloud, right? They want to modernize it. And you know you're not gonna build that overnight in the cloud anyway, so they need help. >> That's the the key move that we made here. If you if you think about it, customers don't have kubernetes experts right today and most of them in their journey to the mortar naps. They're saying, Hey, we need to set up two stacks. At least we are if we immerse stack that we love. And now communities are developers laws. So we have to stand up and they don't have any in house experts to do that right? And with this one move, we have actually collapsed it back to one stack. >> Yeah, I think it's a brilliant move. Actually, it's brilliant because the Dev ops ethos has proven everyone wants to be there, all right. And the question is, who's leading? Who is lagging? So ops has traditionally lagged. If you look at it from the developer standpoint, you guys have not been lagging on the we certainly have tons of'em virtualization been standardized. Its unifying. Yeah, the two worlds together, and it really as we've been calling it cloud two point. Oh, because if you look at what hybrid really is, it's cloud two point. Oh, yeah. Cloud one data was Dev Ops Storage and compute Amazon. You're born in the cloud. We we have no I t department 50 people. Why would we ever and developers are the operators? Yeah, so we shall. Enterprise scale. It's not that easy. So I love to get your thoughts on how you guys would frame the cloud two point. Oh, Visa vi. If cloud one does storage and compute and Amazon like scale, what is cloud to point out to you? >> Yeah, well, I think so. Let's talk about the cloud journey. I think that's what you're getting at here. So here's how it discuss it with customers. You are where you are today. You have your existing apse. A lot of them are monolithic. You're slow to update. Um, you know, so forthright. And then you have some of the cloud NATO nirvana over here. We're like everything's re architected. It's Micro Service's got all these containers off, so >> it doesn't run my business >> well, yeah, well, that's what I want to get to. I think the challenge, the challenge is it's a huge amount of effort to get there, right, All the training we're talking about, all the tooling and the all the changes there, and people tend to look at. This is a very binary thing, right that you're there. Here where you are, you're in the club, New Nirvana. People don't often talk about what's in the middle and the fact that it's a spectrum. And I think what we used to get a V M, where is like, let's meet customers where they are, You know, I think one of the big realizations we had, it's not. Everyone needs to get every single application on this far side over here. Some halfs, your pieces, whatever you know, it's fine to get them a little bit of the way there, and so one of the things that we saw with the M A coordinated us, for example, was that people there was a pent up demand to move to the public cloud. But it was challenging because to go from a visa environment on Prem to an eight of US native environment to change a bunch of things that tooling changes like the environment a little bit different, but with a mark, our native us, there's no modifications at all. You just little evey motion it. And some people have you motioning things like insanely fast now, without modifying the half you can't get you know something you have to suddenly better scalable. But you get other cloud benefits. You get things like, Oh, my infrastructure is dynamic. I can add host dynamically only pay for what I need. Aiken consume this as a service. And so we help moving. We have to move there. There were clothes a little bit in the middle of the spectrum there, and I think what we're doing with Project Pacific and could realise is the same thing. They start taking advantage of these great kubernetes capabilities for their existing APs without modification. So again, kind of moving them further in that middle spectrum and then, you know, for the absolute really make a difference to their business. They can put in the effort to get all the way over there, >> and we saw that some of the evidence of some challenges of that shiny new trend within the dupe ecosystem. Big data objects to army. Who doesn't love that concept, right? Yeah, map produced. But what happened was is that the infrastructure costs on the personnel human capital cost was so massive that and then cloud cloud came along and >> just go out. There is also the other point about just just just a bespoke tooling that >> technology, right, Then the disruptions to create, you know to that, then the investments that it takes. Two >> you had a skill and you had a skills gap in terms of people have been. So that brings us back to So how do you address that problem? Because most of the audience out here, not developers. Yeah. Yeah. Total has the developers connection. So >> this is one of the really cool things about Pacific that what we've done with Pacific when you look at it from an I T. Operations, one of you that person sees v sphere the tool they already know and use understand it. Well, when a developer looks at it, they see kubernetes. And so this is two different viewpoints. Got like, you know, the blind men around the elephant. But, um but the thing is is actually a singular thing in the back end, right? You know, they have these two different views. And so the cool thing about us, we can actually bring items and developers together that they can use their own language tools process. But there's a common thing that they're talking about. They have common visibility into that, and that's super, super powerful. And when you look at, it also is happening on the kubernetes side is fully visible in the V's here side. So all these tools that already work against the sphere suddenly light up and support kubernetes automatically. So again, without any work, we suddenly get so much more benefit. >> And the category Buster's, they're going on to that. You're changing your taking software approach that your guys No, you're taking it to the software developer world. It's kind of changing the game. One of things. I want to get your thoughts on Cloud to point out because, you know, if computing storage was cloud one dato, we're seeing networking and security and data becoming critical ingredients that are problems statement areas people are working on. Certainly networking you guys are in that. So as cloud chip one is gonna take into the fact that messy middle between, you know, I'm on here and then I want the Nirvana, as always, the origination story and the outcomes and stories. Always great. But the missing messy middle. As you were pointing out, it's hard. How do you guys? >> And if you look at the moves that we made in the Do You know about the big fusion acquisition that remained right, which happened, like a month ago, and it was about preparing the platform, our foray I animal or clothes? So really, what we're trying to do is really make sure that the history of platform is ready for the modern applications, right? I am along one side communities applications, you know, service oriented applications. All of them can land on the same platform and more and more. Whether it's the I am l or other application, they're being written on top of communities that structures code. Yeah, nothing like Jenna's well, so enable incriminating will help us land all the modern applications on top of the same platform that our customers are used to. So it's a huge kind of a inflection point in the industry from my >> wealthy earlier point, every CEO I talked to said, I want to get from point A to point B and I wanna spend a billion dollars to get there. I don't wanna have to hire some systems integrator and outsource to get any there. Show me how I get without, you know, destroying my >> business. How did we meet the customers where they're at, right? Like what? The problem with this, the kind of either or model you're here you're there is that there's a huge opportunity costs. And again, Well, if you will just need a little bit of goodness, they don't need the full crazy nirvana Goodness right? And so we enable them to get that very easily in automated way, right? If you'd just been any time re factoring or thinking through this app that takes months or even a year or more, and so you know that this the speed that we can unleash her The velocity for these customers is >> the benefit of that. Nirvana is always taken out of context because people look at the outcome over over generations and saying, Well, I want to be there but it all starts with a very variable basis in shadow. I used to call it, but don't go in the cloud and do something really small, simple. And then why? This is much more official. I like this stack or this approach. That's ultimately how it gets there. So I got to get I got to get that point for infrastructures code because this is what you're enabling. Envies, fearful when I see I want to get your reaction. This because the world used to be. And I ask Elsa on this years ago, and he kind of validated it. But because he's old school, Intel infrastructure dictated to the applications what it could do based on what it could do. Now it's flipped upside down with cloud platform platform and implies enabling something enabling platform. Whatever you call the APs are dictating for the infrastructure. I need this. That's infrastructure is code. That's kind of what you're saying is that >> I mean, look kubernetes broader pattern time. It said, Hey, I can declare what I want, right, and then the system will take care of it and made in that state. I decided state execution is what it brought to the table, and the container based abs, um, have already been working that way. What this announcement does with Project Pacific is that the BM applications that our customers built in the past they are going to be able to take advantage of the same pattern, just the infrastructure escort declarative and decide state execution That that's going to happen even for the old workload, said our customer service >> and they still do viens. I mean, they're scaled 1000 the way >> they operate the same pattern. I >> mean, Paul Morris doesn't get enough credit for the comedy made in 2010. He called it the hardened top. Do you really care what's underneath if it's working effectively? >> Well, I mean, I think you know the reality today is that even though containers that get all get a lot of coverage and attention, most were close to being provisioned. New workloads even are being provisioning v EMS, right? If you look at AWS, the public clouds, I mean, is the E c to our ah go compute engine. Those service's those VM so once they're getting heavily used. And so the way we look at it, if we want to support everything. And it's just going to give customers a bunch of tools in their tool box. And let's put on used the right tool for the right job. Right? That's what the mentality >> that's really clouds. You know, Chris, I want to get your you know, I want to nail you down on the definition of two point. Uh, what is your version? Come on. We keep dodging around, get it out. Come on. >> I think we touched on all aspects of it. Which one is the interesting, less court allowing the consumer of the cloud to be able to dictate the environment in which the applications will operate and the consumer is defining it or the developers to defining it. In this case, that, to me, is the biggest shift that we have gone through in the Colorado. Yeah, and we're just making our platform come to life to support >> that. We're taking the cube serving. We'll put all together, and we want the community to define it, not us. What does it explain? The honest what it means to be a project and has a project Get into it. An offering? >> I mean, so Project Pacific is vey sphere, right? I mean, this is a massive, rethinking re architecture of Easter. Like pretty much every major subsystem component within Visa has been updated with this effort. Um, what we're doing here is what we've technically announced is actually what we call a technical preview. So saying, Hey, this is technology we're working on. We think it's really interesting We want to share with the public, get the public's feedback, you know, figure out a way on the right direction or not. We're not making any commitment, releasing it or any time frames yet. Um, but so part of that needed a name, right? And so because it is easier, but it's a specific thing. We're doing the feast here, so that's where the project comes from. I think it also gives that, you know, this thing has been a huge effort internally, right? There's a lot of work that's gone into it. So you know, it has some heft and deserves a name Min itself. >> It's Dev Ops to pointed. Your reds bring in. You making your infrastructure truly enable program out from amble for perhaps a tsunami. >> The one thing I would say is we wouldn't announce it as a project if it was not coming soon. I mean, we still are in the process. Getting feedback will turn it on or not. But it it's not something that is way out. Then it's It is going to come. >> It's a clear direction. It's a statement of putting investment into his code and going on to course correct. Get some feedback at exactly. But it's pretty obvious you can go a lot of pain. Oh, yeah, isn't easy button for combat. He's >> easy on the >> future. I think it's a great move. Congratulations. We're big fans of kubernetes. So the guys last night having a little meeting Marriott thinking up the next battle plans for game plan for you guys. So, yeah, I >> thought this is just the tip of the iceberg. We had a lot of really, really cool stuff we're doing. >> We're gonna be following the cloud platform. Your progress? Certainly. Recovering. Cloud two point. Oh, looking at these new categories that are emerging again. The end state is Dev Ops Program ability. Apple cases, the Cube coverage, 10th year covering VM world. We're in the lobby of Mosconi in San Francisco. I'm John Favorite Day Volonte. Thanks for watching

>> From Palo Alto, California it's theCUBE, covering VMware Women Transforming Technology 2019. Brought to you by VMware. >> Hi Lisa Martin on the ground with theCUBE at VMware Palo Alto California at the 4th annual Women Transforming Technology event wt². And pleased to welcome to theCUBE for the first time Rashim Mogha, the Head of Product at Automation Anywhere. Rashim it's great to have you on theCUBE. >> Thank you so much Lisa very excited to be here >> And good to see you again you and I were, moderating the together woman achieve event a few months ago that Dell sponsors back in I want to say November 2018 >> Yeah. >> where you one of the exciting things in that swag bag was one of your five books, Fast-Track Your Leadership Career. Tell me about the book what inspired it what can readers learn in that book. >> Absolutely so I come from a project management background and for me everything has to be in the form of a template and that's how it works, right? So when I was new to my leadership career, I would read all these leadership books but they would just focus on one area so you had to read like so many books and skim through all those books to extract what worked for you. Now for me it was important to kind of templatize that and when I templatized it, I actually started talking about it at various events, one of them was Women Transforming Technology last year and as I gave that after I finished that session and we started I started walking out, one of the attendees came to me and said, this was such great information do you have a book? and I said no I don't but I'll have one soon and then I met with my publisher whom I met through one of the speakers at WT2 and we started working on it and in September we had a book. >> September 2018 and then, probably surprisingly to you 11 hours later, this book was on the Amazon number-one bestseller list. >> Yes it was >> that must have been like whiplash what? >> It was a very emotional day it was a roller coaster so we had thought about my publishers had more belief than I did in terms of the book having the potential to be an Amazon bestseller. And number one bestseller to be precise and I was like okay let's give it a try. So I was supposed to go to Grace Hopper Conference last year at that time, and I decided to stay back because the book launch was planned on that day. So we launched we started telling everybody that the book is on Amazon, at about ten o'clock in the morning and by seven o'clock I got an got a text message from my publisher with the screenshot, saying it was number one. >> So yeah very exciting it it took me a few days to realize what it really meant to be an Amazon bestseller. >> I bet that feels amazing. So tell me a little bit before we dig into the book and what you're doing here at wt² today, tell me a little bit about your career path in technology so we can understand some of the recommendations that you're giving the current and subsequent generations about how to fast-track it. Where did you start was it I was a stem interested kid to college. >> Yeah so I was actually studying to be a doctor because I come from India so in India they're just three careers, you're either a doctor or an engineer or you're nobody right so and this was when I was growing up so I actually unfortunately fell sick and could not take my medical exam and missed it actually took the exam, missed it by a few points and and did not know what to do because all my life I had thought about becoming a doctor and it just so happened that there was a computer science program that was out there and my mom saw, saw in a scholarship opportunity over there and she said well just give it a try if you get the scholarship then we'll talk about it and then fortunately for me I got 75% scholarship in that. So I was like okay I'll give it a try so I botany majored and did computer science and that's where my journey started into into the technology field. And got an opportunity to be absorbed within that group the same company absorbed me as as a developer. And within six months I get an opportunity to write a book and that was amazing because I never thought that I could be a teacher or be in front of anybody because I am so impatient as a person right? So so then we started when I started writing the book I realized , this is a great way to empower people and you know and it's a it's a great way to use my technical skills but also my writing abilities. And then you know six months down the line, I got an opportunity to be a project manager I took that so in my life if you see if my career path I've kind of bounced around a little bit, taken risks early on in my career and I continue to take risks in my career because if you don't give it a try you would never know. >> Exactly. >> So and that's what I tell women today like when you come out of college or even if you are in somewhere in your mid-career. You know don't don't tie yourself to a particular job role, or to a particular area try out different things and if there's an opportunity that's given to you, grab it with both your hands and then figure out how you're going to do the job well. >> I like that I always think if you have a goal that doesn't give you butterflies, it's not worth having. >> Yeah >> So in in just giving our viewers a little bit of a snapshot what are some of the things that they can learn and take away from Fast-Track Your Leadership Career book. >> Yeah so first and foremost is understanding your superpower right? How are you different from other people what do you bring to the table that others do not. Because in today's day and age, almost everybody does a great job right? What sets you apart for the next role is what you should always know. Building your personal brand most often we introduce ourselves as what job title we have and the company that we work for. It's important to know and have your identity beyond the company. The third piece is understanding the difference between sponsors and mentors. And that is the place where I think women really need to invest some time because we normally seek mentors. We very rarely go out and look at people and say you know what this person is going to be my sponsor and she or he is actually going to be my cheerleader when I'm not there in the room and and recommend me for that next job. >> So that's the difference between a sponsor I like that a sponsor and a mentors. Mentor is giving you advice and guidance, a sponsor is actually out there championing, >> Absolutely >> why you should hire a Rashim bring her into your team, these are all the great things that she does. >> Absolutely and then then there are other topics that we cover we cover navigating work politics. Most of us tend to stay away from politics but actually how to get into that you know understanding that I would call it work force intelligence if you will and leveraging it to further your projects in a good way. And then also building your support system now typically when we women talk about support system, we think about just two aspects. Emotional support system and the logistic support system but but there is also financial support system and intellectual support system and that's what you need to start building, to be able to further your career. >> I got to get a copy of this book. You probably have some, I'm guessing (mumbles). So you have a couple of sessions here at WT wt², building voice experiences through Alexa skills but one that I want to dig into in the last few minutes that we have. Project you a DevOps approach to a leadership career. Tell me about that pan and that breakout. >> Yeah so if you if you really look at the concept of DevOps it's or CI/CD model its development and then pushing it into operations and then moving into development again and then operations. So when you actually start preparing for your leadership career, that's the way you go. You you rinse and repeat the cycle what works for you in this role, will not work for you in your next role. So how are you continuously preparing yourself and using that DevOps approach, to kind of move to the next level, is what we'll cover in that session. >> That's fantastic. So one thing I also want to mention is that so we talked about becoming a number one Amazon bestseller, the book Fast-Track Your Leadership Career, just about six months ago in fall of 2018. It also inspired you to found, an initiative called eWOW, empowered Women of the World. Tell me a little bit about eWOW and why this book book number five being so instantly successful was so inspirational for eWOW. >> Yeah so I come from a training and enablement background so for me it was and and you know when you when you look at my personal brand, it's all about enabling and empowering people. So I wanted to basically find avenues, to be able to empower other woman. And essentially you know at eWOW, we believe that every woman, has the capability or is a leader in her own, you know her own right. And all that she needs is an intellectual platform and a framework and that's where eWOW came into being. We started off with just podcast, doing weekly podcast picking up topics around leadership and technical topics, we have audience in about 20 countries right now and then as an extension to that, we also launched five Alexa skills and that's going to be the topic that I'm going to be speaking about later today and it was all about you know different ways of enabling and empowering people. >> I love that. Well Rashim it's been such a pleasure, to have you on theCUBE. We thank you for giving us some of your time and we look forward to talking with you again about, maybe book number six? >> Well you never know. Last time I walked out of this conference, I had a book in ring so you never know what's up. >> You never know. But thank you so much. Your story is very inspiring and and i can't wait to, get my hands on a copy of that book. >> Thank you so much. >> My pleasure, Lisa Martin with theCUBE on the ground at wt² from VMware. Thanks for watching. (upbeat music)

>> Live from Las Vegas. It's the Cube covering Adobe Summit twenty nineteen brought to you by X Ensure Interactive. >> Hey, welcome back, everyone. Day two of live coverage of the Cube here in Las Vegas for Adobe Summit twenty nineteen. I'm John Career with Jeff Brick, Our next guest needing Stallman, managing director of a Censure Interactive. Welcome to the Cube. Thanks for joining us. >> Thank you for having me. >> You can't miss your booth when you walk in. Got a nice set up there. You guys got a big prominent location to show. Tell us about Ascension Interactive. And what you guys doing the show? >> Oh, yeah. So thanks again for having us is a great a great summit. A great conference. It's one of our big kind of showcases for the year. We've got a couple of different experiences Were demo ing this year. We've got some really cool X are experiences that people are coming by the booth and putting device is on and it really interacting with and having fun with. We've got some interesting topics around Trends in content creation, headless content, train three D, etcetera. So some great topix around kind of Howard disrupting marketing and content with our clients today. >> Contest becomes so important now, Not only is it you have content development creatives. You have all kinds of applications now. Integrating was once kind of a cottage industry of creative doing cool stuff. Now that's kind of table stakes. It's a whole another level of cloud computing meets creative, so it's kind of an interesting growth curve right now, you're seeing a lot of adoption, a lot of the kind of tools from Tech in with the creative talk about that dynamic, because that's kind of the whole show here. It's all about not just marketing Cloud, and it's about creative experiences and now the new cool stuff out there and people try to figure out how to do it. I want that dynamic of creative tech coming together. >> Yeah, it's enemy from Accenture Interactive. That's really kind of where we've built our business around having that as a technology company that's really drawing a lot of specific talent to build out that creative tak kind of talent mindset. It's a different way of kind of operating and working and building those experiences, so we're kind of first and foremost and experience agency S O. We're all about building experiences for our clients, and it's a kind of ah maybe unique patch that we've we've carved out for ourselves. To say you have to consider technology is part of it and data and effectiveness and analytics. But then, actually, how do you build experiences that are really engage our customers and be really innovative? So certainly has its center at interactive. That's our That's our remit. And we're working out some really exciting work with clients in that area >> about the difference between center interactive and century proper. Because we've done a lot of enemies with center you guys, we're different talked about. The difference is that you guys have and what what's your mission? >> So it's enter. Active are first and foremost. We are an experience agencies. So again, those experiences could be everything from your typical kind of website experience. And how do you best in engage consumers at your site to commerce? Teo X are so we've got a Z mentioned it, several different applications of experiences and x r that we're demo ing here, and we're working on with our clients, um, a R V r as well as sale stools. So in the centre interactive, we take it, we take a creator first, like what is the experience. We really need to build, do the right type of research and then bring in the design, talent and the unique kind of optimization, talent and technology talent to be able to ensure that whatever we're building for a client is actually scaleable for more than just kind of that one exciting news case they've got. But how do you ensure that that's really going to be the right platform in experience? They can scale for other parts of the enterprise of the parts of the business, etcetera. We're proud of who we are >> seriously, because you guys are involved in a lot of things. You keep saying x r for extended reality, and I think it's interesting because some people think it's got to be one hundred percent immersive or not. But if you guys air pioneering, this is a lot of places to kind of extend reality. Blend the rial and the C g. I. And it kind of had this mixed combo experience. So where people using that what are some of the interesting opportunities beyond no trying on a dress from the computer with your with your avatar that you guys are working on >> right, So so definitely have our share of kind of cool consumer experiences and, you know, wanting interesting. That's things that's happening in the market is consumers. They're expecting as they start to engage with RVR, even like immersive commerce. And, um, you're online configurations for shopping and it kind of configuring your own products. They're expecting the same level of, like, hi and visualization that they're getting in the programs and media that they're consuming at home. So getting that right is that's That's a challenge for a lot of brands, and it's a challenge. And technologies, they're changing pretty rapidly to support that. So we've got an experience here were demo ing this week, which is is really on kind of that high end past, which is allowing your design your own your own bathroom experience with countertops, and it's so realistic that you can literally you feel like you could touch that. You could appreciate the textures. You can touch the experience. So it's it's really helping to kind of give customers give consumers back control, but they don't have to rely on a contractor and other types of design services. They really have many options. They can see what that looks like in their own space. I can do that from the convenience of my home, etcetera, and that's kind of one end around. And it's still consumer facing and how to brands create more amorous of shopping experience and make that pass to purchase easier, effective, faster like and, you know, close well. The other types of experiences that I think you're really, really powerful and really interesting is it's starting to use x r for training purposes. So we just want to go home. Oh, actually at Mobile World Congress for PR experience that we built to train foster care professionals on go on making incredibly complicated is around what to do with families and children and really trained them. So how do you take a very subjective experience and train people for the different scenarios to make the right judgment calls? And so that's an interesting kind of application of X r. We're also doing X are in the field of service service technician, so working on automotives and ensuring your using hand, our virtual technology to be able Tio I understand, is that the right party should be working on and what are the best practices around around, whether it's a home technician that's going out and trying to install our complex device or working at an automotive so >> so practical use cases. And then there's also the glamorous ones, like Game of Thrones. Talk about you guys. The relationship with game of thrones is a dynamic. Their share want the shows so that the Cube we Go game of thrones fan. So you guys were somewhat involved in that Such share. >> Yeah, so on. And it's very timely. Obviously, with the final season coming out of the fourteenth, and for like, super fans like myself, it's It's been an exciting year for us. So, um, Extension Interactive has done a very deliberate Siri's of acquisitions over the past ten years, and last year we acquired MCA Vision. So Maga Vision was renowned internationally for their CD I and special effects work on DH. No. One of the most exciting words they've received is an Emmy for outstanding visual effects for game of thrones. So So you got a lot of buzz at the time saying, What is extension interactive? What's what's the kind of thought process, their game of thrones, visual effects, and it really was all about this idea of, you know, again, consumers are expecting this level of visual and this level of experience in how they're interacting with you. So, Mac, a vision was a very we needed a way to be more innovative and how we're bringing the right talent and capabilities to building X. Our experiences, product configurations, etcetera and maka vision had unique capability around three visualisation CG I visual effects and really that again, that whole package of kind of art and technology to create these very high end visualization experiences. So So it's been a really exciting here for us. Um, and starting to now take that model and start to bring that Teo marketing teams that were working within the brands e commerce teams and starting to say, How do we create these type of >> bond? That >> it's It's a nice looking the MCA vision sight and and some of the you know, they have some of the cool movie stuff. But I was fascinated by the car stuff, right? They have these beautiful car shots for car commercials, and I'm curious after hearing about, you know, a be testing and you know all the things that you could do with your experience in the dental experience. Interactive are seeing that now with I got forty seven versions of that car commercial because now if I'm doing it with Mac Division, I don't have to shoot forty seven versions. I can manipulate the CG I car in a very different way because I know that you said super high gloss, super high glam. But it's programmable, so you can do stuff with it without having to call the team together and hope for a beautiful day in Carmel to go over the bridge. >> Exactly all those variables. So I mean brands right now, as they're trying to kind of create trying tio react and set up models to support hyper personalization programmatic content in it that is so challenging. It's so challenging because traditional >> means of >> going out and doing the shoot that you're talking about and doing. Even product shots and tons of photography like you have to create so many versions so expensive to be able to support all of your products. All the variations when you put global into the mix and you've got different labels and different languages etcetera. So, again, it's a It's a scale problem today. I think a lot of people think it's a technology problem, but it's actually it's actually that that's a solution. But it's definitely it's a human problem. And so in our practice, we focus on content creation models. And so this is why Macrovision acquisition so essential is we were disrupting the way continents created, whether it's for brands and their their commercial spots or it's their commerce content. Or or there social media content. By using this idea of taking a digital twin of, let's say, the Mercedes or the Mercedes car and being able to take engineering data and visualize a product digitally before it even exists before I mean literally, the prototype is not available. You know this amazing flexibility. Teo certainly configure that in many different ways, digitally. For these shoots, all you need is some some background in Madrid, etcetera, to be able to roll the car through, um, and Tamar and Magic. But you're able, Tio, you're now able Teo, represent that product, get your media created and put it into market to start generating buzz presales, et cetera. I mean, that's that's so powerful. You're getting ahead of product launch. >> How did how are the cost dynamics changing? Because before you said, it's expensive to do is shoot Yes, but now you can do multiple flavors within the computer is just radically different economics, because I'm sure when they come in and say, I want you guys to game of thrones I want that kind of production value like, yeah, that's really the expectancy. Yeah, To do it in software is a completely different kind of approach. >> I mean, I don't know how brands are not going to give it to this model because they cannot possibly they cannot. They're goingto exponential cross to be able Teo, keep pace with again, even just the variation of product, much less starting to now. Personalize that or be ableto dynamically. Render that so. The cost model today is is is exorbitant, and it's just growing. And so this because you're now able to configure things digitally and again used the right tools to be able tio represent different versions of product changed. The backgrounds, change, change, any of the factors that you need to be able to say this is a new piece of content that. I think it's better targeted at this segment. You want to test that out a little bit. I don't want to kind of double down on that and ending for all of that cost to go do this. You gives you a ton of flexibility, especially, and how you're bringing you no talent in wants to shoot it once and then and that enviable to swap. For example, I may change the bracelet on the talent to do five different ads out instead of >> risk management to a swells testing. Knowing what you're looking at, getsem visibility into what success looks like then, kind of figuring it out. One thing I want to ask you is that in the tech business, we've always been fascinated by Moore's law doubling the speed of the processors. That's Intel thing. But if you look at what you guys do with the game of thrones on the high end with CG, I see the C g I and all the cool stuff. The experiences that people have today become the expectations or the expectations become the new experiences. So you've seen an accelerated user experience. Visually, you got gaming, culture, gaming environments. I mean fortnight wasn't around two years ago. Right? Half the world pretty much plays the game or you got game of thrones. So he's now will soon become table stakes, these kinds of experience. So I got to see where you guys are going with that. How does that change how you guys operate because you gotta look at the expectations of the users consumer. That might be the new experience. How to figure out that dynamic is challenging. How do you guys do that? What's the What's the guiding philosophy around that? That trend? >> Yes. So we have, um we're maniacal about ensuring that the experience for designing is really well thought through with the right research in the right input from us. We're on the right contact. So while it may sound like a great idea and it may sound like something you need, like, how do we make sure we're doing the right thing? Right? Diligence, Tio to build the red experience and represent the product in the right way. And then we also a maniacal on the back end of testing and after optimizing that so being very realistic about is it effective is a driving is driving. Whatever the K p I is, even if it's just innovation, is it driving the KP eyes, uh, that you need and then adjusting? Because nothing could be stagnant? He's >> super exciting area. I mean, there's so much opportunity and change going on. Awesome final questions about the relationship with the job You guys are here. Adobes got a whole growth strategy in front, and that looks really strongly gotta cloud technology platform. Now they're integrating data across multiple their modules in their suites. How does that impact you guys? What's your relationship with Adobe? Yes, >> so we are. We are very big partner of Adobe. We've had a accolades throughout the years of being partner of the year. So we have a large practice dedicated Teo helping clients really look at how to implement the stack howto build content and campaign delivery models on top of that. So it's, um, both the technology and an implement implementation focus, but quite frankly, and I think what's unique is a is a process and kind of how do you operational as that focus? Like I said, you know, everyone's talking about atomic comic, the atomic content these days and certainly, I mean the adobe stack. Absolutely. Khun support that And really power personalized dynamic content for you is a brand but operational operational izing. That is a totally different story. So we're really working with the Adobe team closely on with our customers. Tio kind of build the model on top of the stack and say, How do you need to change your organization to really, really get the value out of out of these tools and really deliver the experiences that are going to be differentiated? >> We've heard that all along all week here and other events we go to is that it's not the tech problem. It's these new capabilities being operationalized older cultures as a people process problem. >> Yeah, it seems >> to be the big, big story. >> It's a it's it's. And I would say it's an ongoing challenge for the brands we work within, and they're constantly getting additional. Um, uh, market demands to be able to kind of continue changing their model. Like I said, programmatic particularly and hyper personalization is is really putting that into practice is is >> great practice Navy. Thanks for coming on. Sharing your insights here on the I do appreciate it. Thank you very much >> for having me >> live coverage here in Dopey Summit twenty nineteen in Las Vegas. To keep coverage day to continue. Stay with us for more after this short break.

>> From our studios in the heart of Silicon Valley. HOLLOWAY ALTO, California It is a cube conversation. >> Welcome to the special. Keep conversation here in Palo Alto, California. I'm John for a co host of the Cube. Were Arsenal was a C I S O. C. So for Microsoft also corporate vice President, Chief information security. Thanks for joining me today. >> Thank you. >> Appreciate it. Thanks. So you have a really big job. You're a warrior in the industry, security is the hardest job on the planet. >> And hang in sight >> of every skirt. Officer is so hard. Tell us about the role of Microsoft. You have overlooked the entire thing. You report to the board, give us an overview of what >> happens. Yeah. I >> mean, it's you know, obviously we're pretty busy. Ah, in this world we have today with a lot of adversaries going on, an operational issues happening. And so I have responsibility. Accountability for obviously protecting Microsoft assets are customer assets. And then ah, And for me, with the trend also responsibility for business continuity Disaster recovery company >> on the sea. So job has been evolving. We're talking before the camera came on that it's coming to CEO CF roll years ago involved to a business leader. Where is the sea? So roll now in your industry is our is a formal title is it establishes their clear lines of reporting. How's it evolved? What's the current state of the market in terms of the sea? So it's roll? >> Yeah, the role is involved. A lot. Like you said, I think like the CIA or twenty years ago, you know, start from the back room of the front room and I think the, you know, one of things I look at in the role is it's really made it before things. There's technical architecture, there's business enablement. There's operational expert excellence. And then there's risk management and the older ah, what does find the right word? But the early see so model was really about the technical architecture. Today. It's really a blend of those four things. How do you enable your business to move forward? How do you take calculated risks or manage risks? And then how do you do it really effectively and efficiently, which is really a new suit and you look at them. You'LL see people evolving to those four functions. >> And who's your boss? Would you report to >> I report to a gentleman by the name of a curtain. Little Benny on DH. He is the chief digital officer, which would be a combination of Seo did officer and transformation as well as all of Microsoft corporate strategy >> and this broad board visibility, actually in security. >> Yeah, you >> guys, how is Microsoft evolved? You've been with the company for a long time >> in the >> old days ahead perimeters, and we talk about on the Cube all the time. When a criminalist environment. Now there's no perimeter. Yeah, the world's changed. How is Microsoft evolved? Its its view on security Has it evolved from central groups to decentralize? How is it how how was it managed? What's the what's the current state of the art for security organization? >> Well, I think that, you know, you raise a good point, though things have changed. And so in this idea, where there is this, you know, perimeter and you demanded everything through the network that was great. But in a client to cloak cloud world, we have today with mobile devices and proliferation or cloud services, and I ot the model just doesn't work anymore. So we sort of simplified it down into Well, we should go with this, you know, people calls your trust, I refer to It is just don't talk to strangers. But the idea being is this really so simplified, which is you've got to have a good identity, strong identity to participate. You have to have managed in healthy device to participate, to talk to, ah, Microsoft Asset. And then you have to have data in telemetry that surrounds that all the time. And so you basically have a trust, trust and then verify model between those three things. And that's really the fundamental. It's really that simple. >> David Lava as Pascal senior with twenty twelve when he was M. C before he was the C E O. V M. Where he said, You know his security do over and he was like, Yes, it's going to be a do over its opportunity. What's your thoughts on that perspective? Has there been a do over? Is it to do over our people looking at security and a whole new way? What's your thoughts? >> Yeah, I mean, I've been around security for a long time, and it's there's obviously changes in Massa nations that happened obviously, at Microsoft. At one point we had a security division. I was the CTO in that division, and we really thought the better way to do it was make security baked in all the products that we do. Everything has security baked in. And so we step back and really change the way we thought about it. To make it easier for developers for end users for admin, that is just a holistic part of the experience. So again, the technology really should disappear. If you really want to be affected, I think >> don't make it a happy thought. Make it baked in from Day one on new product development and new opportunity. >> Yeah, basically, shift the whole thing left. Put it right in from the beginning. And so then, therefore, it's a better experience for everyone using it. >> So one of things we've observed over the past ten years of doing the Cube when do first rolled up with scene, you know, big data role of date has been critical, and I think one of the things that's interesting is, as you get data into the system, you can use day that contextually and look at the contextual behavioral data. It's really is create some visibility into things you, Meyer may not have seen before. Your thoughts and reaction to the concept of leveraging data because you guys get a lot of data. How do you leverage the data? What's the view of data? New data will make things different. Different perspectives creates more visibility. Is that the right view? What's your thoughts on the role of Data World Data plays? >> Well, they're gonna say, You know, we had this idea. There's identity, there's device. And then there's the data telemetry. That platform becomes everything we do, what there's just security and are anomalous behavior like you were talking about. It is how do we improve the user experience all the way through? And so we use it to the service health indicator as well. I think the one thing we've learned, though, is I was building where the biggest data repositories your head for some time. Like we look at about a six point five trillion different security events a day in any given day, and so sort of. How do you filter through that? Manage? That's pretty amazing, says six point five trillion >> per day >> events per day as >> coming into Microsoft's >> that we run through the >> ecosystem your systems. Your computers? >> Yeah. About thirty five hundred people. Reason over that. So you can Certainly the math. You need us. Um, pretty good. Pretty good technology to make it work effectively for you and efficiently >> at RC A Heard a quote on the floor and on the q kind of echoing the same sentiment is you can't hire your way to success in this market is just not enough people qualified and jobs available to handle the volume and the velocity of the data coming in. Automation plays a critical role. Your reaction to that comment thoughts on? >> Well, I think I think the cure there, John, those when you talk about the volume of the data because there's what we used to call speeds and feeds, right? How big is it? And I used to get great network data so I can share a little because we've talked, like from the nineties or whatever period that were there. Like the network was everything, but it turns out much like a diverse workforce creates the best products. It turns out diverse data is more important than speeds and feeds. So, for example, authentication data map to, you know, email data map to end point data map. TEO SERVICE DATA Soon you're hosting, you know, the number of customers. We are like financial sector data vs Healthcare Data. And so it's the ability Teo actually do correlation across that diverse set of data that really differentiates it. So X is an example. We update one point two billion devices every single month. We do six hundred thirty billion authentications every single month. And so the ability to start correlating those things and movement give us a set of insights to protect people like we never had before. >> That's interesting telemetry you're getting in the marketplace. Plus, you have the systems to bring it in >> a pressure pressure coming just realized. And this all with this consent we don't do without consent, we would never do without consent. >> Of course, you guys have the terms of service. You guys do a good job on that, But I think the point that I'm seeing there is that you guys are Microsoft. Microsoft got a lot of access. Get a lot of stuff out there. How does an enterprise move to that divers model because they will have email, obviously. But they have devices. So you guys are kind of operating? I would say tear one of the level of that environment cause you're Microsoft. I'm sure the big scale players to that. I'm just an enterprising I'm a bank or I'm an insurance company or I'm in oil and gas, Whatever the vertical. Maybe. What do I do if I'm the sea? So they're So what does that mean, Diversity? How should they? >> Well, I think they have a diverse set of data as well. Also, if they participate, you know, even in our platform today, we you know, we have this thing called the security graph, which is an FBI people can tap into and tap into the same graph that I use and so they can use that same graph particular for them. They can use our security experts to help them with that if they don't have the all the resource and staff to go do that. So we provide both both models for that to happen, and I think that's why a unique perspective I should think should remind myself of which is we should have these three things. We have a really good security operations group we have. I think that makes us pretty unique that people can leverage. We build this stuff into the product, which I think is good. But then the partnership, the other partners who play in the graph, it's not just us. So there's lots of people who play on that as well. >> So like to ask you two lines of questions. Wanting on the internal complex is that organizations will have on the external complexity and realities of threats and coming in. How do they? How do you balance that out? What's your vision on that? Because, you know, actually, there's technology, his culture and people, you know in those gaps and capabilities on on all three. Yeah, internally just getting the culture right and then dealing with the external. How does a C so about his company's balance? Those realities? >> Well, I think you raised a really good point, which is how do you move the culture for? That's a big conversation We always have. And that was sort of, you know, it's interesting because the the one side we have thirty five hundred people who have security title in their job, But there's over one hundred thousand people who every day part of their job is doing security, making sure they'LL understand that and know that is a key part we should reinforce everyday on DSO. But I think balancing it is, is for me. It's actually simplifying just a set of priorities because there's no shortage of, you know, vendors who play in the space. There's no shortage of things you can read about. And so for us it was just simplifying it down and getting it. That simplifies simplified view of these are the three things we're going to go do we build onerous platform to prioritize relative to threat, and then and then we ensure we're building quality products. Those five things make it happen. >> I'd like to get your thoughts on common You have again Before I came on camera around how you guys view simplification terminal. You know, you guys have a lot of countries, the board level, and then also you made a common around trust of security and you an analogy around putting that drops in a bucket. So first talk about the simplification, how you guys simplifying it and why? Why is that important? >> You think we supply two things one was just supplying the message to people understood the identity of the device and making sure everything is emitting the right telemetry. The second part that was like for us but a Z to be illustrative security passwords like we started with this technology thing and we're going to do to FAA. We had cards and we had readers and oh, my God, we go talk to a user. We say we're going to put two FAA everywhere and you could just see recoil and please, >> no. And then >> just a simple change of being vision letters. And how about this? We're just going to get rid of passwords then People loved like they're super excited about it. And so, you know, we moved to this idea of, you know, we always said this know something, know something new, how something have something like a card And they said, What about just be something and be done with it? And so, you know, we built a lot of the capability natively into the product into windows, obviously, but I supported energies environment. So I you know, I support a lot of Mac clinics and IOS and Android as well So you've read it. Both models you could use by or you could use your device. >> That's that. That's that seems to be a trend. Actually, See that with phones as well as this. Who you are is the password and why is the support? Because Is it because of these abuses? Just easy to program? What's the thought process? >> I think there's two things that make it super helpful for us. One is when you do the biometric model. Well, first of all, to your point, the the user experience is so much better. Like we walk up to a device and it just comes on. So there's no typing this in No miss typing my password. And, you know, we talked earlier, and that was the most popular passwords in Seattle with Seahawks two thousand seventeen. You can guess why, but it would meet the complexity requirements. And so the idea is, just eliminate all that altogether. You walk up machine, recognize you, and you're often running s o. The user experience is great, but plus it's Actually the entropy is harder in the biometric, which makes it harder for people to break it, but also more importantly, it's bound locally to the device. You can't run it from somewhere else. And that's the big thing that I think people misunderstanding that scenario, which is you have to be local to that. To me, that's a >> great example of rethinking the security paradigm. Exactly. Let's talk about trust and security. You you have an opinion on this. I want to get your thoughts, the difference between trust and security so they go hand in hand at the same time. They could be confused. Your thoughts on this >> well being. You can have great trust. You can, so you can have great security. But you generally and you would hope that would equate like a direct correlation to trust. But it's not. You need to you build trust. I think our CEO said it best a long time ago. You put one bucket of water, one bucket. Sorry, one truffle water in the bucket every time. And that's how you build trust. Over time, my teenager will tell you that, and then you kick it over and you put it on the floor. So you have to. It's always this ratcheting up bar that builds trust. >> They doing great you got a bucket of water, you got a lot of trust, that one breach. It's over right, >> and you've got to go rebuild it and you've got to start all over again. And so key, obviously, is not to have that happen. But then, that's why we make sure you have operational rigor and >> great example that just totally is looking Facebook. Great. They have massive great security. What really went down this past week, but still the trust factor on just some of the other or societal questions? >> Yeah, >> and that something Do it. >> Security. Yeah, I think that's a large part of making sure you know you're being true. That's what I said before about, you know, we make sure we have consent. We're transparent about how we do the things we do, and that's probably the best ways to build trust. >> Okay, so you guys have been successful in Microsoft, just kind of tight the company for second to your role. It's pretty well documented that the stock prices at an all time high. So if Donatella Cube alumni, by the way, has been on the cue before he he took over and clear he didn't pivot. He just said we'd go in the cloud. And so the great moves, he don't eat a lot of great stuff. Open source from open compute to over the source. And this ship has turned and everything's going great. But that cheering the cloud has been great for the company. So I gotta ask you, as you guys move to the cloud, the impact to your businesses multi fold one products, ecosystem suppliers. All these things are changing. How has security role in the sea? So position been impact that what have you guys done? How does that impact security in general? Thoughts? >> Yeah, I think we obviously were like any other enterprise we had thousands of online are thousands of line of business applications, and we did a transformation, and we took a method logical approach with risk management. And we said, Okay, well, this thirty percent we should just get rid of and decommission these. We should, you know, optimize and just lifting shifting application. That cloud was okay, but it turns out there's massive benefit there, like for elasticity. Think of things that quarterly reporting or and you'll surveys or things like that where you could just dynamically grow and shrink your platform, which was awesome linear scale that we never had Cause those events I talk about would require re architectures. Separate function now becomes linear. And so I think there is a lot of things from a security perspective I could do in a much more efficient must wear a fish. In fact, they're then I had to have done it before, but also much more effective. I just have compute capability. Didn't have I have signal I didn't have. And so we had to wrap her head around that right and and figure out how to really leverage that. And to be honest, get the point. We're exploited because you were the MySpace. I have disaster and continent and business. This is processed stuff. And so, you know, everyone build dark fiber, big data centers, storage, active, active. And now when you use a platform is a service like on that kind of azure. You could just click a Bach and say, I want this thing to replicate. It also feeds your >> most diverse data and getting the data into the system that you throw a bunch of computer at that scale. So What diverse data? How does that impact the good guys and the bad guys? That doesn't tip the scales? Because if you have divers date and you have his ability, it's a race for who has the most data because more data diversity increases the aperture and our visibility into events. >> Yeah, I you >> know, I should be careful. I feel like I always This's a job. You always feel like you're treading water and trying to trying to stay ahead. But I think that, um, I think for the first time in my tenure do this. I feel there's an asymmetry that benefits. They're good guys in this case because of the fact that your ability to reason over large sets of data like that and is computed data intensive and it will be much harder for them like they could generally use encryption were effectively than some organization because the one the many relationship that happens in that scenario. But in the data center you can't. So at least for now, I feel like there's a tip This. The scales have tipped a bit for the >> guy that you're right on that one. I think it's good observation I think that industry inside look at the activity around, from new fund adventures to overall activity on the analytics side. Clearly, the data edge is going to be an advantage. I think that's a great point. Okay, that's how about the explosion of devices we're seeing now. An explosion of pipe enabled devices, Internet of things to the edge. Operational technologies are out there that in factory floors, everything being I P enables, kind of reminds me of the old days. Were Internet population you'd never uses on the Internet is growing, and >> that costs a lot >> of change in value, creation and opportunities devices. Air coming on both physical and software enabled at a massive rate is causing a lot of change in the industry. Certainly from a security posture standpoint, you have more surface area, but they're still in opportunity to either help on the do over, but also create value your thoughts on this exploding device a landscape, >> I think your Boston background. So Metcalfe's law was the value the net because the number of the nodes on the network squared right, and so it was a tense to still be true, and it continues to grow. I think there's a huge value and the device is there. I mean, if you look at the things we could do today, whether it's this watch or you know your smartphone or your smart home or whatever it is, it's just it's pretty unprecedented the capabilities and not just in those, but even in emerging markets where you see the things people are doing with, you know, with phones and Lauren phones that you just didn't have access to from information, you know, democratization of information and analysis. I think it's fantastic. I do think, though, on the devices there's a set of devices that don't have the same capabilities as some of the more markets, so they don't have encryption capability. They don't have some of those things. And, you know, one of Microsoft's responses to that was everything. Has an M see you in it, right? And so we, you know, without your spirit, we created our own emcee. That did give you the ability to update it, to secure, to run it and manage it. And I think that's one of the things we're doing to try to help, which is to start making these I, O. T or Smart devices, but at a very low cost point that still gives you the ability because the farm would not be healed Update, which we learn an O. T. Is that over time new techniques happen And you I can't update the system >> from That's getting down to the product level with security and also having the data great threats. So final final talk Tracking one today with you on this, your warrior in the industry, I said earlier. See, so is a hard job you're constantly dealing with compliance to, you know, current attacks, new vector, new strains of malware. And it's all over the map. You got it. You got got the inbound coming in and you got to deal with all that the blocking and tackling of the organization. >> What do you What do >> you finding as best practice? What's the what if some of the things on the cso's checklist that you're constantly worried about and or investing in what some of >> the yeah, >> the day to day take us through the day to day life >> of visited a lot? Yeah, it >> starts with not a Leslie. That's the first thing you have to get used to, but I think the you know again, like I said, there's risk Manager. Just prioritize your center. This is different for every company like for us. You know, hackers don't break and they just log in. And so identity still is one of the top things. People have to go work on him. You know, get rid of passwords is good for the user, but good for the system. We see a lot in supply chain going on right now. Obviously, you mentioned in the Cambridge Analytical Analytics where we had that issue. It's just down the supply chain. And when you look at not just third party but forthe party fifth party supply and just the time it takes to respond is longer. So that's something that we need to continue to work on. And then I think you know that those are some of the other big thing that was again about this. How do you become effective and efficient and how you managed that supply chain like, You know, I've been on a mission for three years to reduce my number of suppliers by about fifty percent, and there's still lots of work to do there, but it's just getting better leverage from the supplier I have, as well as taking on new capability or things that we maybe providing natively. But at the end of the day, if you have one system that could do what four systems going Teo going back to the war for talent, having people, no forces and versus one system, it's just way better for official use of talent. And and obviously, simplicity is the is the friend of security. Where is entropy is not, >> and also you mentioned quality data diversity it is you're into. But also there's also quality date of you have quality and diverse data. You could have a nice, nice mechanism to get machine learning going well, but that's kind of complex, because in the thie modes of security breaches, you got pre breached in breech post breach. All have different data characteristics all flowing together, so you can't just throw that answer across as a prism across the problem sets correct. This is super important, kind of fundamentally, >> yeah, but I think I >> would I would. The way I would characterize those is it's honestly, well, better lessons. I think I learned was living how to understand. Talk with CFO, and I really think we're just two things. There's technical debt that we're all working on. Everybody has. And then there's future proofing the company. And so we have a set of efforts that go onto like Red Team. Another actually think like bad people break them before they break you, you know, break it yourself and then go work on it. And so we're always balancing how much we're spending on the technical, that cleanup, you know, modernizing systems and things that are more capable. And then also the future proofing. If you're seeing things coming around the corner like cryptography and and other other element >> by chain blockchain, my supply chain is another good, great mechanism. So you constantly testing and R and D also practical mechanisms. >> And there in the red team's, which are the teams that attacking pen everything, which is again, break yourself first on this super super helpful for us >> well bred. You've seen a lot of ways of innovation have been involved in multiple ways computer industry client server all through the through the days, so feel. No, I feel good about this you know, because it reminds me and put me for broken the business together. But this is the interesting point I want to get to is there's a lot of younger Si SOS coming in, and a lot of young talent is being attractive. Security has kind of a game revived to it. You know, most people, my friends, at a security expert, they're all gamers. They love game, and now the thrill of it. It's exciting, but it's also challenging. Young people coming might not have experience. You have lessons you've learned. Share some thoughts over the years that scar either scar tissue or best practices share some advice. Some of the younger folks coming in breaking into the business of, you know, current situation. What you learned over the years it's Apple Apple. But now the industry. >> Yeah, sadly, I'd probably say it's no different than a lot of the general advice I would have in the space, which is there's you value experience. But it turns out I value enthusiasm and passion more here so you can teach about anybody whose passion enthusiastic and smart anything they want. So we get great data people and make them great security people, and we have people of a passion like you know, this person. It's his mission is to limit all passwords everywhere and like that passion. Take your passion and driver wherever you need to go do. And I >> think the nice >> thing about security is it is something that is technically complex. Human sociology complex, right? Like you said, changing culture. And it affects everything we do, whether it's enterprise, small, medium business, large international, it's actually a pretty It's a fasten, if you like hard problem. If you're a puzzle person, it's a great It's a great profession >> to me. I like how you said Puzzle. That's I think that's exactly it. They also bring up a good point. I want to get your thoughts on quickly. Is the talent gap is is really not about getting just computer science majors? It's bigger than that. In fact, I've heard many experts say, and you don't have to be a computer scientist. You could be a lot of cross disciplines. So is there a formula or industry or profession, a college degree? Or is it doesn't matter. It's just smart person >> again. It depends if your job's a hundred percent. Security is one thing, but like what we're trying to do is make not we don't have security for developers you want have developed to understand oppa security and what they build is an example on DSO. Same with administrators and other components. I do think again I would say the passion thing is a key piece for us, but But there's all aspects of the profession, like the risk managers air, you know, on the actuarial side. Then there's math people I had one of my favorite people was working on his phD and maladaptive behavior, and he was super valuable for helping us understand what actually makes things stick when you're trying to train their educate people. And what doesn't make that stick anthropologist or super helpful in this field like anthropologist, Really? Yeah, anthropologist are great in this field. So yeah, >> and sociology, too, you mentioned. That would think that's a big fact because you've got human aspect interests, human piece of it. You have society impact, so that's really not really one thing. It's really cross section, depending upon where you want to sit in the spectrum of opportunity, >> knowing it gives us a chance to really hire like we hire a big thing for us has been hard earlier in career and building time because it's just not all available. But then also you, well, you know, hire from military from law enforcement from people returning back. It's been actually, it's been a really fascinating thing from a management perspective that I didn't expect when I did. The role on has been fantastic. >> The mission. Personal question. Final question. What's getting you excited these days? I mean, honestly, you had a very challenging job and you have got attend all the big board meetings, but the risk management compliance. There's a lot of stuff going on, but it's a lot >> of >> technology fund in here to a lot of hard problems to solve. What's getting you excited? What what trends or things in the industry gets you excited? >> Well, I'm hopeful we're making progress on the bad guys, which I think is exciting. But honestly, this idea the you know, a long history of studying safety when I did this and I would love to see security become the air bags of the technology industry, right? It's just always there on new president. But you don't even know it's there until you need it. And I think that getting to that vision would be awesome. >> And then really kind of helping move the trust equation to a whole other level reputation. New data sets so data, bits of data business. >> It's total data business >> breath. Thanks for coming on the Q. Appreciate your insights, but also no see. So the chief information security officer at Microsoft, also corporate vice president here inside the Cuban Palo Alto. This is cute conversations. I'm John Career. Thanks for watching. >> Thank you.

>> System partners. Lie from Barcelona, Spain. It's the cue covering Sisqo Live Europe, brought to you by Cisco and its ecosystem partners. >> Hello and welcome Back to the Cubes Live coverage Day two of three days of wall to wall coverage here in Europe in Barcelona, Spain. Francisco Live twenty nineteen I'm John Career with Dave. A long takes too many man hosting great loaded interviews this week here. Francisco live guys kicking off day to day one was all the big announcement Cisco putting in all the announcement's really is setting in and the messaging coming together, the product portfolios filling out. Clearly, Cisco is adopting and path to the cloud, taking their data center business, securing that bring that data center into the cloud kind of hybrid multi cloud, big messes around multi cloud and then under the hood data center traffic patterns, air changing. Its not a ribbon replaces extension to the environment. Cisco's intent based networking plus Cloud plus Cloud center management. A lot of stuff we discussed that yesterday, but I want your take. Is Cisco's positioning viable? And what does it mean, Visa VI? The competition, because Cisco is a blue chip tech player, certainly have zillions of customers very relevant. This is a huge impact. How their position themselves do. >> Yeah, so So John Roemer a few years ago we were saying, Hyper clouds going Teo hybrid. The hyper scale clouds, the public loud provide you going to take over the world and boy Cisco's in trouble because if a third or half of the market all of a sudden evaporate from them, those enterprise buyers of switches and routers and everything else like that, Cisco is doomed. Well, you know, we listen to the keynote yesterday and Cisco's talking about all of their solutions anywhere. And when you go through the ecosystem of Public Cloud hybrid Cloud multi Cloud, say this Cisco have a play there, and the answer is absolutely, you know, it's not just the you know, after empty acquisition, which has software in a ws. But, you know, S t win is going to be a critical component to get from my data centers to the public clouds on DH. Cisco has software and solutions and consulting TTO help customers in all of these environment. So we always know that there's partnerships and there's competition. There's a lot of players out there, but you know, it was good to see them. You know, talking. You know a lot about what they're doing with Cooper Netease with Amazon because you can't talk about cloud either public cloud or multi cloud without first talking about Amazon. Last year we were a little critical John and said, OK, Google's great, but Google's number three or four. So you've got to be there was Amazon got to be there with Microsoft and certified that we've already interviewed a couple of service writers always been a strength for Sisko to be in there on. So, you know, good positioning. Well, you know, we talked yesterday a bunch about the bridge to possible on where to go. But the more I think about that anywhere is what Cisco's branded everything. And that's when when you talk multicolored multi clouds, really a whole bunch of clouds and a whole bunch of things. And therefore I need a player that's going to help give me coverage in all of these environment and Cisco's making a strong case to be >> there. And Dave. So I mean Stew's, right? A couple years ago, we were critical of Cisco and I think rightfully so. I think the whole industry looked at them as not in the middle of the fairway and certainly the recovery shot. Francisco is really strong because a lot changed. Go back a few years. They didn't have a good ecosystem for developers. They didn't have a good open source position. They kind of work, you know. Do I go up to stack or not? But they had the court networking, so there's a lot of people are saying, Hey, if Cisco doesn't make a move, they're doomed. We were one of them, so lots changed. You seeing the adoption of micro services containers, AP eyes the growth of definite That Suzy we has initiated is clear proof in my opinion. Then you've got the data center guys saying, Hey, what could take networking and and take this and enable clouds. So Cisco, making good moves, put themselves in pole position for growth? >> Well, I think the first point is if you roll back ten years ago, we've not Francisco. We were critical. What? All of it. It was clear to us that cloud was going to be where all the growth wass and if you didn't have a public cloud, you are going to be in trouble unless you developed a cloud strategy. So certainly Cisco de Liam see now you know William c. V. M. Where none of them really owned a public cloud strategy. And five years ago, they had to figure it out. Well, they've figured out that actually, managing multi clouds is a great opportunity. And so Francisco's got a viable strategy. Networks between clouds are going to flatten their going to need management specifically as it relates to Cisco and maybe their competition. They have TTo position themselves as R multi cloud management system is higher performance and more secure than the competition. That's what they have to sell their customers on. And the second piece of that is they got a transition from selling ports to selling software on there, making that transition. So I like their strategy, By the way, I also like VM wear strategy. They capitulated to a ws and now they're tight with a w s. IBM went out, paid two million dollars for soft layer, so they've got a cloud strategy. Oracles got a cloud strategy. Microsoft got a great cloud stress. So if you go through and >> tickle at the hole and they have clouds, so let's let's just understand something. There's clouds and then clouds strategies. Right? So thirty >> four billion dollars that IBM paying for Red Hat is giving them a multi cloud strategy. More than just saying, we have a bunch of data centers in their medals. But it >> was both, maybe not so much in the public cloud, right? I would say I would argue that their public cloud has failed to meet their expectations. That's funnel cloud IBM. And that's why they had to pay thirty four billion dollars for for Red Hat, I would say just the opposite about Microsoft. Their public cloud strategy has been an enormous success, and they're very well positioned for multi cloud. >> Okay, so let's just put on the table. So Cisco looks at the public cloud as partners, not competitors. So Amazon Azure Google aren't competing with Cisco. There are there ways or they're partnering. We'll we'll come understand. Competition is all about understanding, Absolutely as a cloud. So I would say Cisco's strategy to partner just like he did, just like everyone else. And l did. That's the competitive, not cloud So. Or maybe this is the question. Are the public clouds competitive to Sisko >> that their frenemies John? Uh, >> you know, the answer's. Yes, there's no question about this. They're growing at twenty, thirty, forty percent a year. Francisco and IBM, HP. They're growing it, you know, much lower. So single digits. If that's >> so such on, we know if Amazon if there is a profitable space that they can offer competitive service, they will. You know, security. You said Cisco's got a great position Security, both what they've had for a long time, and they've done acquisitions like duo. More recently on DH, you know, we've seen lots of pieces of the public cloud ecosystem that Cisco's bought over the last few years. Clicker was one on one we spent some time talking about, but absolutely, you know, Amazon goes after some of those pieces, so they're gonna partner Cisco's Got it. Last I checked it at least three dozen products in the eight of us marketplace. But you know it is. They can live there, but there will be competition. So >> this girl's got some huge assets in this game. They've got eight hundred thousand plus customers. They, you know, sixty percent of the networking market, so they own the install base. It's really the only market that you can think of that's a major market where they're the dominant player still owns, you know, sixty percent of market never just go for >> networking, and VM wear for the hyper visor are very similar. In that case, Dave and both have now have a similar strategy as to how they're going. >> That's the most interesting competitive dynamic, in my view, is V M wearing this acquisition of Nice era and obviously, Cisco. Cisco is not going to take this lying down. They've got a C. I A and no, they claim number one. They didn't say whose data that was I was looking squinting for is that I D C. Guard divorce her. But, >> well, let's talk about growth because you know how I always complain about market. Researchers aren't on the mark in terms of the reality of where the market is, So you mentioned growth. So are we. If we're early on cloud growth and that's where the growth is, what is the cloud adoption going to look like over the next ten to twenty years? Is it going to look more like public Cloud or is going to look more like on premises evolving to cloud operations And if the growth of cloud operations is all things wide area Network mentioned the wind, then there's more growth coming. So that's the case. Is Sisko going to be able to capture that growth for the future? >> Well, I mean, in terms of growth, I think eight of us is on its way to being a one hundred billion dollars revenue company, and that's pretty impressive given where they are today. I mean, they're gonna triple in revenue, so that's that's where the growth is. So now Cisco's already participating in a huge TAM. What they've got to do is hold on to that business and identify new opportunities where they could manage multi cloud instances and compete effectively with V M. Where who's coming at it from the hyper visor? And now, they said yesterday, trying to do to networks in storage what it did for systems and then IBM Red hat coming out. It really, from the applications perspective and with the services view Microsoft with a foot in both camps, You got Oracle in its little niche. Just really interest. >> We got an install a base that's moving to the cloud. You got net new company they're going to be started might have on premise. Orgel Full Cloud. This is the question that everyone's going to ask. I think Cisco can take their existing base with moving packets from Point A to Point B and storing and making datum or intelligence moving Date around is a big networking phenomenon. >> Here's the question. Here's a question, Andy Jassy would say. We believe they're going to be far fewer data centers in the future that most data is going to live in the public lounge. The likes of Michael Dell, Yeah, Charles Robbins, et cetera. I think they see the world is a hybrid world, right? That there's going to be Mohr data that's in a hybrid on Prem Plus Cloud, then is going to be in the >> public. You know, I love Andy Jazzy, but I'll just say first of all I understand is bias in his perspective. And I think he's right at one level. Why wouldn't Amazon see people moving data centers to the flower? I get that I say that it's going to be in the networks. That's where the action will be. Where are the networks of the networks? In the cloud of the networks on premise. Are the networks on a phone? I OT So if coyote and edge coming together, it's all one network. Yeah, you're gonna have The value is going to be in the network. Not necessarily. The clouds we say or is shared values. >> Yeah. I mean, you talk about EJ computing and Io ti. Cisco's got muraki, which is growing strong. SD LAN is a critical component for this multi cloud piece. There really posed toe, you know, drive this next generation of five G not something we've dug into a lot yet, but, you know, it is finally coming, you know, really soon here. And Cisco has a lot of those pieces to be able to hit the next. >> It always went back to the data, in my opinion, and the leverage points for data are Saso. Yeah, if your own the applications business, you're doing well there, You're in a good position. All the data's running over Cisco Networks, so that puts them in A in a really good position. And and as we know the likes of a Ws and Microsoft Alibaba senator, they're trying to get as much data into their clouds as possible. >> And what I loved yesterday in the keynote is data was actually one of the central components that they talked about, which the Cisco I know of ten or twenty years ago. I was just bitch that ran over our pipes. So they understand the value of data. And they're driving to that mark. >> Well, we've been saying on the Cube now for nine years days at the center of the value proposition Data at the Centre Data Center. Value proposition. This is actually happening. It's really going way. See? A lot of growth and cloud, Dave. Good commentaries do. Well done. We have Sergeant Gupta, one of the bank. All the leaders coming on the Cube here. Francisco breakdown. I'm gonna ask him the tough questions. Stay with us for day two. Coverage here in the Cube live in Barcelona for a stupid him in David want breaking down all the action. We'll be right back with more after this short break

- [Announcer] Live, from New York, it's theCUBE. Covering theCUBE New York City 2018. Brought to you by SiliconANGLE Media, and its ecosystem partners. - Hello everyone, welcome back to CUBE NYC. This is a CUBE special presentation of something that we've done now for the past couple of years. IBM has sponsored an influencer panel on some of the hottest topics in the industry, and of course, there's no hotter topic right now than AI. So, we've got nine of the top influencers in the AI space, and we're in Hell's Kitchen, and it's going to get hot in here. (laughing) And these guys, we're going to cover the gamut. So, first of all, folks, thanks so much for joining us today, really, as John said earlier, we love the collaboration with you all, and we'll definitely see you on social after the fact. I'm Dave Vellante, with my cohost for this session, Peter Burris, and again, thank you to IBM for sponsoring this and organizing this. IBM has a big event down here, in conjunction with Strata, called Change the Game, Winning with AI. We run theCUBE NYC, we've been here all week. So, here's the format. I'm going to kick it off, and then we'll see where it goes. So, I'm going to introduce each of the panelists, and then ask you guys to answer a question, I'm sorry, first, tell us a little bit about yourself, briefly, and then answer one of the following questions. Two big themes that have come up this week. One has been, because this is our ninth year covering what used to be Hadoop World, which kind of morphed into big data. Question is, AI, big data, same wine, new bottle? Or is it really substantive, and driving business value? So, that's one question to ponder. The other one is, you've heard the term, the phrase, data is the new oil. Is data really the new oil? Wonder what you think about that? Okay, so, Chris Penn, let's start with you. Chris is cofounder of Trust Insight, long time CUBE alum, and friend. Thanks for coming on. Tell us a little bit about yourself, and then pick one of those questions. - Sure, we're a data science consulting firm. We're an IBM business partner. When it comes to "data is the new oil," I love that expression because it's completely accurate. Crude oil is useless, you have to extract it out of the ground, refine it, and then bring it to distribution. Data is the same way, where you have to have developers and data architects get the data out. You need data scientists and tools, like Watson Studio, to refine it, and then you need to put it into production, and that's where marketing technologists, technologists, business analytics folks, and tools like Watson Machine Learning help bring the data and make it useful. - Okay, great, thank you. Tony Flath is a tech and media consultant, focus on cloud and cyber security, welcome. - Thank you. - Tell us a little bit about yourself and your thoughts on one of those questions. - Sure thing, well, thanks so much for having us on this show, really appreciate it. My background is in cloud, cyber security, and certainly in emerging tech with artificial intelligence. Certainly touched it from a cyber security play, how you can use machine learning, machine control, for better controlling security across the gamut. But I'll touch on your question about wine, is it a new bottle, new wine? Where does this come from, from artificial intelligence? And I really see it as a whole new wine that is coming along. When you look at emerging technology, and you look at all the deep learning that's happening, it's going just beyond being able to machine learn and know what's happening, it's making some meaning to that data. And things are being done with that data, from robotics, from automation, from all kinds of different things, where we're at a point in society where data, our technology is getting beyond us. Prior to this, it's always been command and control. You control data from a keyboard. Well, this is passing us. So, my passion and perspective on this is, the humanization of it, of IT. How do you ensure that people are in that process, right? - Excellent, and we're going to come back and talk about that. - Thanks so much. - Carla Gentry, @DataNerd? Great to see you live, as opposed to just in the ether on Twitter. Data scientist, and owner of Analytical Solution. Welcome, your thoughts? - Thank you for having us. Mine is, is data the new oil? And I'd like to rephrase that is, data equals human lives. So, with all the other artificial intelligence and everything that's going on, and all the algorithms and models that's being created, we have to think about things being biased, being fair, and understand that this data has impacts on people's lives. - Great. Steve Ardire, my paisan. - Paisan. - AI startup adviser, welcome, thanks for coming to theCUBE. - Thanks Dave. So, uh, my first career was geology, and I view AI as the new oil, but data is the new oil, but AI is the refinery. I've used that many times before. In fact, really, I've moved from just AI to augmented intelligence. So, augmented intelligence is really the way forward. This was a presentation I gave at IBM Think last spring, has almost 100,000 impressions right now, and the fundamental reason why is machines can attend to vastly more information than humans, but you still need humans in the loop, and we can talk about what they're bringing in terms of common sense reasoning, because big data does the who, what, when, and where, but not the why, and why is really the Holy Grail for causal analysis and reasoning. - Excellent, Bob Hayes, Business Over Broadway, welcome, great to see you again. - Thanks for having me. So, my background is in psychology, industrial psychology, and I'm interested in things like customer experience, data science, machine learning, so forth. And I'll answer the question around big data versus AI. And I think there's other terms we could talk about, big data, data science, machine learning, AI. And to me, it's kind of all the same. It's always been about analytics, and getting value from your data, big, small, what have you. And there's subtle differences among those terms. Machine learning is just about making a prediction, and knowing if things are classified correctly. Data science is more about understanding why things work, and understanding maybe the ethics behind it, what variables are predicting that outcome. But still, it's all the same thing, it's all about using data in a way that we can get value from that, as a society, in residences. - Excellent, thank you. Theo Lau, founder of Unconventional Ventures. What's your story? - Yeah, so, my background is driving technology innovation. So, together with my partner, what our work does is we work with organizations to try to help them leverage technology to drive systematic financial wellness. We connect founders, startup founders, with funders, we help them get money in the ecosystem. We also work with them to look at, how do we leverage emerging technology to do something good for the society. So, very much on point to what Bob was saying about. So when I look at AI, it is not new, right, it's been around for quite a while. But what's different is the amount of technological power that we have allow us to do so much more than what we were able to do before. And so, what my mantra is, great ideas can come from anywhere in the society, but it's our job to be able to leverage technology to shine a spotlight on people who can use this to do something different, to help seniors in our country to do better in their financial planning. - Okay, so, in your mind, it's not just a same wine, new bottle, it's more substantive than that. - [Theo] It's more substantive, it's a much better bottle. - Karen Lopez, senior project manager for Architect InfoAdvisors, welcome. - Thank you. So, I'm DataChick on twitter, and so that kind of tells my focus is that I'm here, I also call myself a data evangelist, and that means I'm there at organizations helping stand up for the data, because to me, that's the proxy for standing up for the people, and the places and the events that that data describes. That means I have a focus on security, data privacy and protection as well. And I'm going to kind of combine your two questions about whether data is the new wine bottle, I think is the combination. Oh, see, now I'm talking about alcohol. (laughing) But anyway, you know, all analogies are imperfect, so whether we say it's the new wine, or, you know, same wine, or whether it's oil, is that the analogy's good for both of them, but unlike oil, the amount of data's just growing like crazy, and the oil, we know at some point, I kind of doubt that we're going to hit peak data where we have not enough data, like we're going to do with oil. But that says to me that, how did we get here with big data, with machine learning and AI? And from my point of view, as someone who's been focused on data for 35 years, we have hit this perfect storm of open source technologies, cloud architectures and cloud services, data innovation, that if we didn't have those, we wouldn't be talking about large machine learning and deep learning-type things. So, because we have all these things coming together at the same time, we're now at explosions of data, which means we also have to protect them, and protect the people from doing harm with data, we need to do data for good things, and all of that. - Great, definite differences, we're not running out of data, data's like the terrible tribbles. (laughing) - Yes, but it's very cuddly, data is. - Yeah, cuddly data. Mark Lynd, founder of Relevant Track? - That's right. - I like the name. What's your story? - Well, thank you, and it actually plays into what my interest is. It's mainly around AI in enterprise operations and cyber security. You know, these teams that are in enterprise operations both, it can be sales, marketing, all the way through the organization, as well as cyber security, they're often under-sourced. And they need, what Steve pointed out, they need augmented intelligence, they need to take AI, the big data, all the information they have, and make use of that in a way where they're able to, even though they're under-sourced, make some use and some value for the organization, you know, make better use of the resources they have to grow and support the strategic goals of the organization. And oftentimes, when you get to budgeting, it doesn't really align, you know, you're short people, you're short time, but the data continues to grow, as Karen pointed out. So, when you take those together, using AI to augment, provided augmented intelligence, to help them get through that data, make real tangible decisions based on information versus just raw data, especially around cyber security, which is a big hit right now, is really a great place to be, and there's a lot of stuff going on, and a lot of exciting stuff in that area. - Great, thank you. Kevin L. Jackson, author and founder of GovCloud. GovCloud, that's big. - Yeah, GovCloud Network. Thank you very much for having me on the show. Up and working on cloud computing, initially in the federal government, with the intelligence community, as they adopted cloud computing for a lot of the nation's major missions. And what has happened is now I'm working a lot with commercial organizations and with the security of that data. And I'm going to sort of, on your questions, piggyback on Karen. There was a time when you would get a couple of bottles of wine, and they would come in, and you would savor that wine, and sip it, and it would take a few days to get through it, and you would enjoy it. The problem now is that you don't get a couple of bottles of wine into your house, you get two or three tankers of data. So, it's not that it's a new wine, you're just getting a lot of it. And the infrastructures that you need, before you could have a couple of computers, and a couple of people, now you need cloud, you need automated infrastructures, you need huge capabilities, and artificial intelligence and AI, it's what we can use as the tool on top of these huge infrastructures to drink that, you know. - Fire hose of wine. - Fire hose of wine. (laughs) - Everybody's having a good time. - Everybody's having a great time. (laughs) - Yeah, things are booming right now. Excellent, well, thank you all for those intros. Peter, I want to ask you a question. So, I heard there's some similarities and some definite differences with regard to data being the new oil. You have a perspective on this, and I wonder if you could inject it into the conversation. - Sure, so, the perspective that we take in a lot of conversations, a lot of folks here in theCUBE, what we've learned, and I'll kind of answer both questions a little bit. First off, on the question of data as the new oil, we definitely think that data is the new asset that business is going to be built on, in fact, our perspective is that there really is a difference between business and digital business, and that difference is data as an asset. And if you want to understand data transformation, you understand the degree to which businesses reinstitutionalizing work, reorganizing its people, reestablishing its mission around what you can do with data as an asset. The difference between data and oil is that oil still follows the economics of scarcity. Data is one of those things, you can copy it, you can share it, you can easily corrupt it, you can mess it up, you can do all kinds of awful things with it if you're not careful. And it's that core fundamental proposition that as an asset, when we think about cyber security, we think, in many respects, that is the approach to how we can go about privatizing data so that we can predict who's actually going to be able to appropriate returns on it. So, it's a good analogy, but as you said, it's not entirely perfect, but it's not perfect in a really fundamental way. It's not following the laws of scarcity, and that has an enormous effect. - In other words, I could put oil in my car, or I could put oil in my house, but I can't put the same oil in both. - Can't put it in both places. And now, the issue of the wine, I think it's, we think that it is, in fact, it is a new wine, and very simple abstraction, or generalization we come up with is the issue of agency. That analytics has historically not taken on agency, it hasn't acted on behalf of the brand. AI is going to act on behalf of the brand. Now, you're going to need both of them, you can't separate them. - A lot of implications there in terms of bias. - Absolutely. - In terms of privacy. You have a thought, here, Chris? - Well, the scarcity is our compute power, and our ability for us to process it. I mean, it's the same as oil, there's a ton of oil under the ground, right, we can't get to it as efficiently, or without severe environmental consequences to use it. Yeah, when you use it, it's transformed, but our scarcity is compute power, and our ability to use it intelligently. - Or even when you find it. I have data, I can apply it to six different applications, I have oil, I can apply it to one, and that's going to matter in how we think about work. - But one thing I'd like to add, sort of, you're talking about data as an asset. The issue we're having right now is we're trying to learn how to manage that asset. Artificial intelligence is a way of managing that asset, and that's important if you're going to use and leverage big data. - Yeah, but see, everybody's talking about the quantity, the quantity, it's not always the quantity. You know, we can have just oodles and oodles of data, but if it's not clean data, if it's not alphanumeric data, which is what's needed for machine learning. So, having lots of data is great, but you have to think about the signal versus the noise. So, sometimes you get so much data, you're looking at over-fitting, sometimes you get so much data, you're looking at biases within the data. So, it's not the amount of data, it's the, now that we have all of this data, making sure that we look at relevant data, to make sure we look at clean data. - One more thought, and we have a lot to cover, I want to get inside your big brain. - I was just thinking about it from a cyber security perspective, one of my customers, they were looking at the data that just comes from the perimeter, your firewalls, routers, all of that, and then not even looking internally, just the perimeter alone, and the amount of data being pulled off of those. And then trying to correlate that data so it makes some type of business sense, or they can determine if there's incidents that may happen, and take a predictive action, or threats that might be there because they haven't taken a certain action prior, it's overwhelming to them. So, having AI now, to be able to go through the logs to look at, and there's so many different types of data that come to those logs, but being able to pull that information, as well as looking at end points, and all that, and people's houses, which are an extension of the network oftentimes, it's an amazing amount of data, and they're only looking at a small portion today because they know, there's not enough resources, there's not enough trained people to do all that work. So, AI is doing a wonderful way of doing that. And some of the tools now are starting to mature and be sophisticated enough where they provide that augmented intelligence that Steve talked about earlier. - So, it's complicated. There's infrastructure, there's security, there's a lot of software, there's skills, and on and on. At IBM Think this year, Ginni Rometty talked about, there were a couple of themes, one was augmented intelligence, that was something that was clear. She also talked a lot about privacy, and you own your data, etc. One of the things that struck me was her discussion about incumbent disruptors. So, if you look at the top five companies, roughly, Facebook with fake news has dropped down a little bit, but top five companies in terms of market cap in the US. They're data companies, all right. Apple just hit a trillion, Amazon, Google, etc. How do those incumbents close the gap? Is that concept of incumbent disruptors actually something that is being put into practice? I mean, you guys work with a lot of practitioners. How are they going to close that gap with the data haves, meaning data at their core of their business, versus the data have-nots, it's not that they don't have a lot of data, but it's in silos, it's hard to get to? - Yeah, I got one more thing, so, you know, these companies, and whoever's going to be big next is, you have a digital persona, whether you want it or not. So, if you live in a farm out in the middle of Oklahoma, you still have a digital persona, people are collecting data on you, they're putting profiles of you, and the big companies know about you, and people that first interact with you, they're going to know that you have this digital persona. Personal AI, when AI from these companies could be used simply and easily, from a personal deal, to fill in those gaps, and to have a digital persona that supports your family, your growth, both personal and professional growth, and those type of things, there's a lot of applications for AI on a personal, enterprise, even small business, that have not been done yet, but the data is being collected now. So, you talk about the oil, the oil is being built right now, lots, and lots, and lots of it. It's the applications to use that, and turn that into something personally, professionally, educationally, powerful, that's what's missing. But it's coming. - Thank you, so, I'll add to that, and in answer to your question you raised. So, one example we always used in banking is, if you look at the big banks, right, and then you look at from a consumer perspective, and there's a lot of talk about Amazon being a bank. But the thing is, Amazon doesn't need to be a bank, they provide banking services, from a consumer perspective they don't really care if you're a bank or you're not a bank, but what's different between Amazon and some of the banks is that Amazon, like you say, has a lot of data, and they know how to make use of the data to offer something as relevant that consumers want. Whereas banks, they have a lot of data, but they're all silos, right. So, it's not just a matter of whether or not you have the data, it's also, can you actually access it and make something useful out of it so that you can create something that consumers want? Because otherwise, you're just a pipe. - Totally agree, like, when you look at it from a perspective of, there's a lot of terms out there, digital transformation is thrown out so much, right, and go to cloud, and you migrate to cloud, and you're going to take everything over, but really, when you look at it, and you both touched on it, it's the economics. You have to look at the data from an economics perspective, and how do you make some kind of way to take this data meaningful to your customers, that's going to work effectively for them, that they're going to drive? So, when you look at the big, big cloud providers, I think the push in things that's going to happen in the next few years is there's just going to be a bigger migration to public cloud. So then, between those, they have to differentiate themselves. Obvious is artificial intelligence, in a way that makes it easy to aggregate data from across platforms, to aggregate data from multi-cloud, effectively. To use that data in a meaningful way that's going to drive, not only better decisions for your business, and better outcomes, but drives our opportunities for customers, drives opportunities for employees and how they work. We're at a really interesting point in technology where we get to tell technology what to do. It's going beyond us, it's no longer what we're telling it to do, it's going to go beyond us. So, how we effectively manage that is going to be where we see that data flow, and those big five or big four, really take that to the next level. - Now, one of the things that Ginni Rometty said was, I forget the exact step, but it was like, 80% of the data, is not searchable. Kind of implying that it's sitting somewhere behind a firewall, presumably on somebody's premises. So, it was kind of interesting. You're talking about, certainly, a lot of momentum for public cloud, but at the same time, a lot of data is going to stay where it is. - Yeah, we're assuming that a lot of this data is just sitting there, available and ready, and we look at the desperate, or disparate kind of database situation, where you have 29 databases, and two of them have unique quantifiers that tie together, and the rest of them don't. So, there's nothing that you can do with that data. So, artificial intelligence is just that, it's artificial intelligence, so, they know, that's machine learning, that's natural language, that's classification, there's a lot of different parts of that that are moving, but we also have to have IT, good data infrastructure, master data management, compliance, there's so many moving parts to this, that it's not just about the data anymore. - I want to ask Steve to chime in here, go ahead. - Yeah, so, we also have to change the mentality that it's not just enterprise data. There's data on the web, the biggest thing is Internet of Things, the amount of sensor data will make the current data look like chump change. So, data is moving faster, okay. And this is where the sophistication of machine learning needs to kick in, going from just mostly supervised-learning today, to unsupervised learning. And in order to really get into, as I said, big data, and credible AI does the who, what, where, when, and how, but not the why. And this is really the Holy Grail to crack, and it's actually under a new moniker, it's called explainable AI, because it moves beyond just correlation into root cause analysis. Once we have that, then you have the means to be able to tap into augmented intelligence, where humans are working with the machines. - Karen, please. - Yeah, so, one of the things, like what Carla was saying, and what a lot of us had said, I like to think of the advent of ML technologies and AI are going to help me as a data architect to love my data better, right? So, that includes protecting it, but also, when you say that 80% of the data is unsearchable, it's not just an access problem, it's that no one knows what it was, what the sovereignty was, what the metadata was, what the quality was, or why there's huge anomalies in it. So, my favorite story about this is, in the 1980s, about, I forget the exact number, but like, 8 million children disappeared out of the US in April, at April 15th. And that was when the IRS enacted a rule that, in order to have a dependent, a deduction for a dependent on your tax returns, they had to have a valid social security number, and people who had accidentally miscounted their children and over-claimed them, (laughter) over the years them, stopped doing that. Well, some days it does feel like you have eight children running around. (laughter) - Agreed. - When, when that rule came about, literally, and they're not all children, because they're dependents, but literally millions of children disappeared off the face of the earth in April, but if you were doing analytics, or AI and ML, and you don't know that this anomaly happened, I can imagine in a hundred years, someone is saying some catastrophic event happened in April, 1983. (laughter) And what caused that, was it healthcare? Was it a meteor? Was it the clown attacking them? - That's where I was going. - Right. So, those are really important things that I want to use AI and ML to help me, not only document and capture that stuff, but to provide that information to the people, the data scientists and the analysts that are using the data. - Great story, thank you. Bob, you got a thought? You got the mic, go, jump in here. - Well, yeah, I do have a thought, actually. I was talking about, what Karen was talking about. I think it's really important that, not only that we understand AI, and machine learning, and data science, but that the regular folks and companies understand that, at the basic level. Because those are the people who will ask the questions, or who know what questions to ask of the data. And if they don't have the tools, and the knowledge of how to get access to that data, or even how to pose a question, then that data is going to be less valuable, I think, to companies. And the more that everybody knows about data, even people in congress. Remember when Zuckerberg talked about? (laughter) - That was scary. - How do you make money? It's like, we all know this. But, we need to educate the masses on just basic data analytics. - We could have an hour-long panel on that. - Yeah, absolutely. - Peter, you and I were talking about, we had a couple of questions, sort of, how far can we take artificial intelligence? How far should we? You know, so that brings in to the conversation of ethics, and bias, why don't you pick it up? - Yeah, so, one of the crucial things that we all are implying is that, at some point in time, AI is going to become a feature of the operations of our homes, our businesses. And as these technologies get more powerful, and they diffuse, and know about how to use them, diffuses more broadly, and you put more options into the hands of more people, the question slowly starts to turn from can we do it, to should we do it? And, one of the issues that I introduce is that I think the difference between big data and AI, specifically, is this notion of agency. The AI will act on behalf of, perhaps you, or it will act on behalf of your business. And that conversation is not being had, today. It's being had in arguments between Elon Musk and Mark Zuckerberg, which pretty quickly get pretty boring. (laughing) At the end of the day, the real question is, should this machine, whether in concert with others, or not, be acting on behalf of me, on behalf of my business, or, and when I say on behalf of me, I'm also talking about privacy. Because Facebook is acting on behalf of me, it's not just what's going on in my home. So, the question of, can it be done? A lot of things can be done, and an increasing number of things will be able to be done. We got to start having a conversation about should it be done? - So, humans exhibit tribal behavior, they exhibit bias. Their machine's going to pick that up, go ahead, please. - Yeah, one thing that sort of tag onto agency of artificial intelligence. Every industry, every business is now about identifying information and data sources, and their appropriate sinks, and learning how to draw value out of connecting the sources with the sinks. Artificial intelligence enables you to identify those sources and sinks, and when it gets agency, it will be able to make decisions on your behalf about what data is good, what data means, and who it should be. - What actions are good. - Well, what actions are good. - And what data was used to make those actions. - Absolutely. - And was that the right data, and is there bias of data? And all the way down, all the turtles down. - So, all this, the data pedigree will be driven by the agency of artificial intelligence, and this is a big issue. - It's really fundamental to understand and educate people on, there are four fundamental types of bias, so there's, in machine learning, there's intentional bias, "Hey, we're going to make "the algorithm generate a certain outcome "regardless of what the data says." There's the source of the data itself, historical data that's trained on the models built on flawed data, the model will behave in a flawed way. There's target source, which is, for example, we know that if you pull data from a certain social network, that network itself has an inherent bias. No matter how representative you try to make the data, it's still going to have flaws in it. Or, if you pull healthcare data about, for example, African-Americans from the US healthcare system, because of societal biases, that data will always be flawed. And then there's tool bias, there's limitations to what the tools can do, and so we will intentionally exclude some kinds of data, or not use it because we don't know how to, our tools are not able to, and if we don't teach people what those biases are, they won't know to look for them, and I know. - Yeah, it's like, one of the things that we were talking about before, I mean, artificial intelligence is not going to just create itself, it's lines of code, it's input, and it spits out output. So, if it learns from these learning sets, we don't want AI to become another buzzword. We don't want everybody to be an "AR guru" that has no idea what AI is. It takes months, and months, and months for these machines to learn. These learning sets are so very important, because that input is how this machine, think of it as your child, and that's basically the way artificial intelligence is learning, like your child. You're feeding it these learning sets, and then eventually it will make its own decisions. So, we know from some of us having children that you teach them the best that you can, but then later on, when they're doing their own thing, they're really, it's like a little myna bird, they've heard everything that you've said. (laughing) Not only the things that you said to them directly, but the things that you said indirectly. - Well, there are some very good AI researchers that might disagree with that metaphor, exactly. (laughing) But, having said that, what I think is very interesting about this conversation is that this notion of bias, one of the things that fascinates me about where AI goes, are we going to find a situation where tribalism more deeply infects business? Because we know that human beings do not seek out the best information, they seek out information that reinforces their beliefs. And that happens in business today. My line of business versus your line of business, engineering versus sales, that happens today, but it happens at a planning level, and when we start talking about AI, we have to put the appropriate dampers, understand the biases, so that we don't end up with deep tribalism inside of business. Because AI could have the deleterious effect that it actually starts ripping apart organizations. - Well, input is data, and then the output is, could be a lot of things. - Could be a lot of things. - And that's where I said data equals human lives. So that we look at the case in New York where the penal system was using this artificial intelligence to make choices on people that were released from prison, and they saw that that was a miserable failure, because that people that release actually re-offended, some committed murder and other things. So, I mean, it's, it's more than what anybody really thinks. It's not just, oh, well, we'll just train the machines, and a couple of weeks later they're good, we never have to touch them again. These things have to be continuously tweaked. So, just because you built an algorithm or a model doesn't mean you're done. You got to go back later, and continue to tweak these models. - Mark, you got the mic. - Yeah, no, I think one thing we've talked a lot about the data that's collected, but what about the data that's not collected? Incomplete profiles, incomplete datasets, that's a form of bias, and sometimes that's the worst. Because they'll fill that in, right, and then you can get some bias, but there's also a real issue for that around cyber security. Logs are not always complete, things are not always done, and when things are doing that, people make assumptions based on what they've collected, not what they didn't collect. So, when they're looking at this, and they're using the AI on it, that's only on the data collected, not on that that wasn't collected. So, if something is down for a little while, and no data's collected off that, the assumption is, well, it was down, or it was impacted, or there was a breach, or whatever, it could be any of those. So, you got to, there's still this human need, there's still the need for humans to look at the data and realize that there is the bias in there, there is, we're just looking at what data was collected, and you're going to have to make your own thoughts around that, and assumptions on how to actually use that data before you go make those decisions that can impact lots of people, at a human level, enterprise's profitability, things like that. And too often, people think of AI, when it comes out of there, that's the word. Well, it's not the word. - Can I ask a question about this? - Please. - Does that mean that we shouldn't act? - It does not. - Okay. - So, where's the fine line? - Yeah, I think. - Going back to this notion of can we do it, or should we do it? Should we act? - Yeah, I think you should do it, but you should use it for what it is. It's augmenting, it's helping you, assisting you to make a valued or good decision. And hopefully it's a better decision than you would've made without it. - I think it's great, I think also, your answer's right too, that you have to iterate faster, and faster, and faster, and discover sources of information, or sources of data that you're not currently using, and, that's why this thing starts getting really important. - I think you touch on a really good point about, should you or shouldn't you? You look at Google, and you look at the data that they've been using, and some of that out there, from a digital twin perspective, is not being approved, or not authorized, and even once they've made changes, it's still floating around out there. Where do you know where it is? So, there's this dilemma of, how do you have a digital twin that you want to have, and is going to work for you, and is going to do things for you to make your life easier, to do these things, mundane tasks, whatever? But how do you also control it to do things you don't want it to do? - Ad-based business models are inherently evil. (laughing) - Well, there's incentives to appropriate our data, and so, are things like blockchain potentially going to give users the ability to control their data? We'll see. - No, I, I'm sorry, but that's actually a really important point. The idea of consensus algorithms, whether it's blockchain or not, blockchain includes games, and something along those lines, whether it's Byzantine fault tolerance, or whether it's Paxos, consensus-based algorithms are going to be really, really important. Parts of this conversation, because the data's going to be more distributed, and you're going to have more elements participating in it. And so, something that allows, especially in the machine-to-machine world, which is a lot of what we're talking about right here, you may not have blockchain, because there's no need for a sense of incentive, which is what blockchain can help provide. - And there's no middleman. - And, well, all right, but there's really, the thing that makes blockchain so powerful is it liberates new classes of applications. But for a lot of the stuff that we're talking about, you can use a very powerful consensus algorithm without having a game side, and do some really amazing things at scale. - So, looking at blockchain, that's a great thing to bring up, right. I think what's inherently wrong with the way we do things today, and the whole overall design of technology, whether it be on-prem, or off-prem, is both the lock and key is behind the same wall. Whether that wall is in a cloud, or behind a firewall. So, really, when there is an audit, or when there is a forensics, it always comes down to a sysadmin, or something else, and the system administrator will have the finger pointed at them, because it all resides, you can edit it, you can augment it, or you can do things with it that you can't really determine. Now, take, as an example, blockchain, where you've got really the source of truth. Now you can take and have the lock in one place, and the key in another place. So that's certainly going to be interesting to see how that unfolds. - So, one of the things, it's good that, we've hit a lot of buzzwords, right now, right? (laughing) AI, and ML, block. - Bingo. - We got the blockchain bingo, yeah, yeah. So, one of the things is, you also brought up, I mean, ethics and everything, and one of the things that I've noticed over the last year or so is that, as I attend briefings or demos, everyone is now claiming that their product is AI or ML-enabled, or blockchain-enabled. And when you try to get answers to the questions, what you really find out is that some things are being pushed as, because they have if-then statements somewhere in their code, and therefore that's artificial intelligence or machine learning. - [Peter] At least it's not "go-to." (laughing) - Yeah, you're that experienced as well. (laughing) So, I mean, this is part of the thing you try to do as a practitioner, as an analyst, as an influencer, is trying to, you know, the hype of it all. And recently, I attended one where they said they use blockchain, and I couldn't figure it out, and it turns out they use GUIDs to identify things, and that's not blockchain, it's an identifier. (laughing) So, one of the ethics things that I think we, as an enterprise community, have to deal with, is the over-promising of AI, and ML, and deep learning, and recognition. It's not, I don't really consider it visual recognition services if they just look for red pixels. I mean, that's not quite the same thing. Yet, this is also making things much harder for your average CIO, or worse, CFO, to understand whether they're getting any value from these technologies. - Old bottle. - Old bottle, right. - And I wonder if the data companies, like that you talked about, or the top five, I'm more concerned about their nearly, or actual $1 trillion valuations having an impact on their ability of other companies to disrupt or enter into the field more so than their data technologies. Again, we're coming to another perfect storm of the companies that have data as their asset, even though it's still not on their financial statements, which is another indicator whether it's really an asset, is that, do we need to think about the terms of AI, about whose hands it's in, and who's, like, once one large trillion-dollar company decides that you are not a profitable company, how many other companies are going to buy that data and make that decision about you? - Well, and for the first time in business history, I think, this is true, we're seeing, because of digital, because it's data, you're seeing tech companies traverse industries, get into, whether it's content, or music, or publishing, or groceries, and that's powerful, and that's awful scary. - If you're a manger, one of the things your ownership is asking you to do is to reduce asset specificities, so that their capital could be applied to more productive uses. Data reduces asset specificities. It brings into question the whole notion of vertical industry. You're absolutely right. But you know, one quick question I got for you, playing off of this is, again, it goes back to this notion of can we do it, and should we do it? I find it interesting, if you look at those top five, all data companies, but all of them are very different business models, or they can classify the two different business models. Apple is transactional, Microsoft is transactional, Google is ad-based, Facebook is ad-based, before the fake news stuff. Amazon's kind of playing it both sides. - Yeah, they're kind of all on a collision course though, aren't they? - But, well, that's what's going to be interesting. I think, at some point in time, the "can we do it, should we do it" question is, brands are going to be identified by whether or not they have gone through that process of thinking about, should we do it, and say no. Apple is clearly, for example, incorporating that into their brand. - Well, Silicon Valley, broadly defined, if I include Seattle, and maybe Armlock, not so much IBM. But they've got a dual disruption agenda, they've always disrupted horizontal tech. Now they're disrupting vertical industries. - I was actually just going to pick up on what she was talking about, we were talking about buzzword, right. So, one we haven't heard yet is voice. Voice is another big buzzword right now, when you couple that with IoT and AI, here you go, bingo, do I got three points? (laughing) Voice recognition, voice technology, so all of the smart speakers, if you think about that in the world, there are 7,000 languages being spoken, but yet if you look at Google Home, you look at Siri, you look at any of the devices, I would challenge you, it would have a lot of problem understanding my accent, and even when my British accent creeps out, or it would have trouble understanding seniors, because the way they talk, it's very different than a typical 25-year-old person living in Silicon Valley, right. So, how do we solve that, especially going forward? We're seeing voice technology is going to be so more prominent in our homes, we're going to have it in the cars, we have it in the kitchen, it does everything, it listens to everything that we are talking about, not talking about, and records it. And to your point, is it going to start making decisions on our behalf, but then my question is, how much does it actually understand us? - So, I just want one short story. Siri can't translate a word that I ask it to translate into French, because my phone's set to Canadian English, and that's not supported. So I live in a bilingual French English country, and it can't translate. - But what this is really bringing up is if you look at society, and culture, what's legal, what's ethical, changes across the years. What was right 200 years ago is not right now, and what was right 50 years ago is not right now. - It changes across countries. - It changes across countries, it changes across regions. So, what does this mean when our AI has agency? How do we make ethical AI if we don't even know how to manage the change of what's right and what's wrong in human society? - One of the most important questions we have to worry about, right? - Absolutely. - But it also says one more thing, just before we go on. It also says that the issue of economies of scale, in the cloud. - Yes. - Are going to be strongly impacted, not just by how big you can build your data centers, but some of those regulatory issues that are going to influence strongly what constitutes good experience, good law, good acting on my behalf, agency. - And one thing that's underappreciated in the marketplace right now is the impact of data sovereignty, if you get back to data, countries are now recognizing the importance of managing that data, and they're implementing data sovereignty rules. Everyone talks about California issuing a new law that's aligned with GDPR, and you know what that meant. There are 30 other states in the United States alone that are modifying their laws to address this issue. - Steve. - So, um, so, we got a number of years, no matter what Ray Kurzweil says, until we get to artificial general intelligence. - The singularity's not so near? (laughing) - You know that he's changed the date over the last 10 years. - I did know it. - Quite a bit. And I don't even prognosticate where it's going to be. But really, where we're at right now, I keep coming back to, is that's why augmented intelligence is really going to be the new rage, humans working with machines. One of the hot topics, and the reason I chose to speak about it is, is the future of work. I don't care if you're a millennial, mid-career, or a baby boomer, people are paranoid. As machines get smarter, if your job is routine cognitive, yes, you have a higher propensity to be automated. So, this really shifts a number of things. A, you have to be a lifelong learner, you've got to learn new skillsets. And the dynamics are changing fast. Now, this is also a great equalizer for emerging startups, and even in SMBs. As the AI improves, they can become more nimble. So back to your point regarding colossal trillion dollar, wait a second, there's going to be quite a sea change going on right now, and regarding demographics, in 2020, millennials take over as the majority of the workforce, by 2025 it's 75%. - Great news. (laughing) - As a baby boomer, I try my damnedest to stay relevant. - Yeah, surround yourself with millennials is the takeaway there. - Or retire. (laughs) - Not yet. - One thing I think, this goes back to what Karen was saying, if you want a basic standard to put around the stuff, look at the old ISO 38500 framework. Business strategy, technology strategy. You have risk, compliance, change management, operations, and most importantly, the balance sheet in the financials. AI and what Tony was saying, digital transformation, if it's of meaning, it belongs on a balance sheet, and should factor into how you value your company. All the cyber security, and all of the compliance, and all of the regulation, is all stuff, this framework exists, so look it up, and every time you start some kind of new machine learning project, or data sense project, say, have we checked the box on each of these standards that's within this machine? And if you haven't, maybe slow down and do your homework. - To see a day when data is going to be valued on the balance sheet. - It is. - It's already valued as part of the current, but it's good will. - Certainly market value, as we were just talking about. - Well, we're talking about all of the companies that have opted in, right. There's tens of thousands of small businesses just in this region alone that are opt-out. They're small family businesses, or businesses that really aren't even technology-aware. But data's being collected about them, it's being on Yelp, they're being rated, they're being reviewed, the success to their business is out of their hands. And I think what's really going to be interesting is, you look at the big data, you look at AI, you look at things like that, blockchain may even be a potential for some of that, because of mutability, but it's when all of those businesses, when the technology becomes a cost, it's cost-prohibitive now, for a lot of them, or they just don't want to do it, and they're proudly opt-out. In fact, we talked about that last night at dinner. But when they opt-in, the company that can do that, and can reach out to them in a way that is economically feasible, and bring them back in, where they control their data, where they control their information, and they do it in such a way where it helps them build their business, and it may be a generational business that's been passed on. Those kind of things are going to make a big impact, not only on the cloud, but the data being stored in the cloud, the AI, the applications that you talked about earlier, we talked about that. And that's where this bias, and some of these other things are going to have a tremendous impact if they're not dealt with now, at least ethically. - Well, I feel like we just got started, we're out of time. Time for a couple more comments, and then officially we have to wrap up. - Yeah, I had one thing to say, I mean, really, Henry Ford, and the creation of the automobile, back in the early 1900s, changed everything, because now we're no longer stuck in the country, we can get away from our parents, we can date without grandma and grandpa setting on the porch with us. (laughing) We can take long trips, so now we're looked at, we've sprawled out, we're not all living in the country anymore, and it changed America. So, AI has that same capabilities, it will automate mundane routine tasks that nobody wanted to do anyway. So, a lot of that will change things, but it's not going to be any different than the way things changed in the early 1900s. - It's like you were saying, constant reinvention. - I think that's a great point, let me make one observation on that. Every period of significant industrial change was preceded by the formation, a period of formation of new assets that nobody knew what to do with. Whether it was, what do we do, you know, industrial manufacturing, it was row houses with long shafts tied to an engine that was coal-fired, and drove a bunch of looms. Same thing, railroads, large factories for Henry Ford, before he figured out how to do an information-based notion of mass production. This is the period of asset formation for the next generation of social structures. - Those ship-makers are going to be all over these cars, I mean, you're going to have augmented reality right there, on your windshield. - Karen, bring it home. Give us the drop-the-mic moment. (laughing) - No pressure. - Your AV guys are not happy with that. So, I think the, it all comes down to, it's a people problem, a challenge, let's say that. The whole AI ML thing, people, it's a legal compliance thing. Enterprises are going to struggle with trying to meet five billion different types of compliance rules around data and its uses, about enforcement, because ROI is going to make risk of incarceration as well as return on investment, and we'll have to manage both of those. I think businesses are struggling with a lot of this complexity, and you just opened a whole bunch of questions that we didn't really have solid, "Oh, you can fix it by doing this." So, it's important that we think of this new world of data focus, data-driven, everything like that, is that the entire IT and business community needs to realize that focusing on data means we have to change how we do things and how we think about it, but we also have some of the same old challenges there. - Well, I have a feeling we're going to be talking about this for quite some time. What a great way to wrap up CUBE NYC here, our third day of activities down here at 37 Pillars, or Mercantile 37. Thank you all so much for joining us today. - Thank you. - Really, wonderful insights, really appreciate it, now, all this content is going to be available on theCUBE.net. We are exposing our video cloud, and our video search engine, so you'll be able to search our entire corpus of data. I can't wait to start searching and clipping up this session. Again, thank you so much, and thank you for watching. We'll see you next time.

>> From the Amazon meeting Center in downtown Seattle, it's theCUBE, covering IMAGINE: A Better World, a global education conference sponsored by Amazon Web Services. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're in Seattle, Washington at the first ever AWS IMAGINE education conference. I think they said there was 900 registrants. Teresa Carlson did the key note, just finished, really fantastic. 900 people, it's funny, she equated it to AWS Public Sector which, seven years ago, had 50 people. And this year it had, I think, 15,000 people. So I think we'll see a similar growth here. Really, application of all the things that AWS does for education specifically, and there's all the cost saving and shutting down data centers and all that kind of stuff. But much more importantly is educating the workforce and getting a new class of kids and educators involved in cloud computing 'cause, let's face it, it's the dominant paradigm going forward. I don't think there's much question about that. So we're excited to be here, talk to some of the great people, all educators. And our first guest is Dr. David Dimmett. He's the SVP and Chief Engagement Officer at Project Lead the Way. David, great to see you. >> Yeah, great, thanks for having us here. So we're excited to be here as part of this first ever education conference that AWS is hosting. So great event, lots of fantastic energy, excited to present later today on diversity inclusion and computer science education, a space where we're doing a lot of really great work. And want to share, and also here to learn. >> Great, so give us the overview on Project Lead the Way. >> Sure, so Project Lead the Way, we are a 20-year-old national nonprofit. We were started in upstate New York, and we're working today with over three million students in pre-K all the way through 12th grade in high school. And we work with them in computer science education, biomedical science engineering; our job is to inspire kids. We want them to have access to a lifetime of opportunity. We know these skills are essential. Students who have these skills have opportunities, have doors open to them. Students without these skills really, today, face a lifetime of consequences. >> Right, so how do you get the skills into the education? It's such a frustration, and typical K through 12 education, computer science has not been part of the standard curriculum. There's the math track, which you take trig and calc, and there's the science track with bio and physics and chem, but computer science really hasn't done a great job of weaseling its way into the standard curriculum that everybody takes. So how do you get this curriculum in? How do you get the education to the kids? >> Sure, and we're seeing some movement in this area, which is really exciting. AWS has been a big part of that. But what we look at, we for the last 20 years have really put an emphasis on testing students primarily in those subjects that are easy to test, so core academic content; we definitely need students to have knowledge in those areas. What's been missing for a long time is the connection to that core academic knowledge to real-world problem solving. And that's where kids come in to a Project Lead the Way classroom and get excited. So we're starting with them early as pre-K, working all the way through, and it's, like I said, all those career pathways. But they're applying what they're learning in their algebra class, they're applying what they're learning in their physics class. And we know the research indicates that students decide really early if they like or are good at math or science. And gone are the days where it's okay to just brush off those content areas. We need to rethink the way kids get excited and inspired at an early age. >> So do you pull them, then, into a separate classroom experience outside of their everyday at school? How does the mechanics actually work? >> Right, so we're working with about 14,000 programs all across the country this year, all 50 states. And there are a variety of implementation models. In the early grades, in pre-K through five, a lot of times that's integrating into the homeroom or into the primary classroom. So we're training teachers all across buildings in a lot of elementary schools all across the country. When you work your way into middle school and high school, students rotate through, sometimes as an elective. But increasingly we're seeing schools require those courses because it exposes students to some of the careers that they may not understand and opportunities that they don't know exist. >> Right, it's so funny, right? 'Cause technology, over and over and over again, back to the Luddites, right, destroys certain industries, creates new industries, right? You don't want to be the guy making buggy whips anymore; it's probably not a great industry. But there didn't use to be web developers. There didn't use to be integration specialists. There didn't use to be SEO people. So there's a whole new class of applications that continue to be created with each of these huge information technology transformations. >> Yeah, it really is, and we have an increasing gap, really, unfortunately, in equality of opportunity. Increasingly today, we see students who have access to these opportunities in their pre-K, 12 experiences. Those students have a chance to go on to all kinds of careers, whether it's AWS, Verizon, Toyota, Lockheed Martin, you can go down the list. Companies are recruiting students that have these skills. Students who happen to not get exposed to these opportunities early really struggle to catch up later in life or later in their education system. So we really look at a variety of on-ramps for students. We work in the school day primarily. We also support a lot of work outside the school day. One of the key things that we do is we help teachers gain confidence in these areas. We were talking earlier about the skills gap that exists for adults in getting into some of these careers; same thing exists for teachers. We have teacher shortages all across the country. And what we're really looking to do is inspire not just students but the teachers who teach them. We'll train over 10,000 teachers this summer and get them ready to go in and inspire and prepare their students. >> It's really interesting, especially you get smarter kids once they're in high school and college. And they're looking for that connection. "Come on, Dad, what am I taking in chemistry? "I'm not going to be a doctor, "I'm not going to be a chemical scientist. "How does it relate to what I'm going to do "or philosophy or whatever." But these types of skills are really, really cogent. And not to mention that, but the kids are interacting with these types of applications all the day. So the connection between what I'm doing at school versus what I might be doing when I get out of school has got to be so much tighter than when you take a philosophy class or an American lit class. >> Yeah, we're rolling out, and with AWS's support. AWS has provided us with subject matter experts with a lot of the technological tools to help us deliver a brand new cybersecurity course this year all across the country. We're really excited about that. And you look at what's happening in terms of the cybersecurity threats that our country faces, that other countries face. It's both an economic issue but also a national security issue. And we just don't have the skilled workforce to be effective in those areas. We're inspiring kids, through AWS's help, to get excited and not just get excited but to have the skills to go out and be successful. So what I love, too, is a lot of the advances that we anticipate in healthcare are not going to be necessarily biomedical advancements. They will be, but they'll also be technological advances. We've worked with Cerner to train teachers in our computer science courses; they're one of the world's largest medical records companies. How do we provide data and information, big data, to medical providers, so that they can provide the best targeted treatment to their students? And so one of the things that we thrive on in our work is the connection to business and industry. And we want to provide that talent, that workforce, of the future. >> Right, so let me just drill in on that a little bit in terms of the role. You said you've been around for 20 years, your foundation. The role of private companies in general, and AWS specifically in helping on some of these really big problems, these really big efforts. 'Cause we know the public school systems never have enough money, getting pulled in a ton of different directions. So what kind of impact does somebody like AWS coming in help you complete your mission? >> Right, so AWS, AWS Educate have provided us with a variety of supports, and they're really helping us do a lot of really great work for students all across the country. A couple of specific examples. I mentioned subject matter experts. Having AWS come in and help us not just with this cybersecurity course but also how do we infuse into our other computer science coursework cloud career skilled development? And so we're doing that now with AWS's support. And Ken Eisner and his team have really helped us for the last couple of years; it's a great partnership. Additionally, providing us with the infrastructure, the applications, the AWS ecosystem of supports are helping us do a variety of things to secure student data, to also drive down cost to schools. All of those things together provide a great opportunity to the students that we're serving, three million plus, all across the country. >> Three million plus, that's great. So there's a real specific program that I want to give you a chance to talk about, the Kentucky Cloud Careers Pathways. That's kind of an example; give us a little bit more color. And we talked before, I got a lot of family in Kentucky, so it touched me a little bit. And, of course, Teresa's from there as well. >> So Kentucky is one of our strongest states for Project Lead the Way and has been for a lot of years. The governor and his cabinet have really done a lot of work to advance career opportunities, workforce development, economic development. And what we have and what we announced last year in Kentucky is the Cloud Career Pathway program. And that is a partnership between AWS; Project Lead the Way; the community college system in Kentucky; the governor's economic, labor, development, education departments; all of us working together to get kids exposed to cloud careers early in their education experience. And we've started training teachers to that end this year. We think it's going to be a real model for the country. >> David, I think you said it in every one of your answers, adding the "and the teachers, too." Such an important part, right? Such a key enabler to make this thing actually go. It can't just be about the kids. >> Absolutely, teachers are the bedrock of what we do in education. I say that as a lifelong educator. We've got a lot of work to do, and teachers are under attack in some places. And you've seen this last year, the work that's happened to put teachers in a position to be successful. And we've got a lot of work to do there. But our job, we want to go out and inspire the country's best teachers to go in and work in some of the most difficult work situations that exist in our country and inspire kids and with limited resources. And teachers are pouring their hearts out to do that. We think we've got a great opportunity, but we trained 10,000 plus teachers this year alone. And we see those teachers gain confidence. They go back to their classrooms, they're excited, and they know more about the opportunities that exist for their students. And I say that as a lifelong educator. In fact, my wife and I met 20 years ago as first-year teachers, so that, to me, is really core to what we do. >> Well, I see the passion in your eyes. So thank you for following up on this mission and doing good work and spending a few minutes with us on theCUBE. >> Yeah, that's great, thanks Jeff. >> All right, he's David, I'm Jeff. You're watching theCUBE from AWS IMAGINE Educate. Thanks for watching. (electronic music)

>> Narrator: Live from the Computer History Museum in Mountain View, California. It's theCUBE, covering DevNet Create 2018, brought to you by Cisco. >> Welcome back everyone, live here in Silicon Valley in Mountain View, California, it's theCUBE coverage of DevNet Create. This is Cisco's cloud developer, DevOps, cloud native developer environment. This is different from DevNet, that's their Cisco developer conference, so we're here covering it. This is where all the action in Kubernetes, DevOps, and a lot more. I'm John Furrier with my co-host Lauren Cooney. Our next guest is Heidi Waterhouse, Developer Advocate for Launch Darkly. Welcome to theCUBE. >> Hi, thank you! I'm glad to be here. >> Thanks for coming on. So first of all, take a minute to talk about what you guys do as a company, then we'll talk about some specific DevOps questions that we have for you. >> Excellent. So, what we do as a company is, I summarize it as feature flags as a service. We are giving people a control surface to be able to deploy their code safely in the daytime, so nobody has to stay up on a deploy bridge, and then control who sees it very precisely, and roll out individually or do work to do intricate testing with user groups or we sometimes use it, imagine if sales could turn on a feature, a test feature for one client without needing to go to development and get approval for all of that. So it gives us the ability to let people be richer in their expression of software. >> So is it software as a service? Is it cloud-based? >> Yes >> It is 100 percent cloud-based. >> So, subscriptions, free? >> We charge by developer seat, and all we are saying is, go ahead and use it, we have the capacity to handle it. We're handling about 25 billion flags a day right now. >> So it's a great tool, so it's not like a big over the top feature cost. >> Oh, no. >> It's like nice lightweight usability, the more you use it, the better utility. >> Yeah, it's very light. It's a couple SDKs and then a code snippet about this long, depending on your language. The Java one's a little longer. And what it gives people is the ability to do feature flags, which lots of people are already doing, in a manageable way, with a structured API, so that people can keep track of what's happening. And make sure that they are only allowing the right people to turn flags on, because you don't want everybody to be able to hit the kill switch. You want a kill switch on the feature if it starts spitting out garbage, but you don't want it to be universally accessible. >> I think you also want it to be consistent, right? In that environment and those environments, where the developers are trying to understand what that looks like. >> Right, and auditable. We give you the ability to see every change that's happened to a flag and who made it. >> So DevOps is going on almost a 10-year run now. If you look back on the original kind of DevOps ethos, really was kind of coming in late in the 2007 time frame, the real hardcore DevOps were building their own stuff. So we're 10 years into what I would call the true DevOps, maybe earlier. You could argue a little bit earlier when Amazon hit the table, but can you tell about the kinds of things that you guys are doing is really large DevOps environments, where you want agility, you want real-time, push code all the time, but be reliable. This is more of a mature-looking dev team. How has that evolved there? What are some of the key things? This is kind of probably an indicator, of where everything else is going. What are some of the developer concerns? Is it A/B testing? That's kind of a trivial example, but I often imagine all kinds of new software methodologies are coming out of this. What are you seeing? >> So what we're seeing is, for 20 years, we've been teaching and preaching branch-based development. But it turns out the very largest software organizations, like Google, are doing trunk-based development, because branches are just a way to cry. Once you try and merge something back in, you find out that you have conflicts, and then you have to have more discussions about who gets cherry-picked, and it's catastrophic. I have said for a long time that maybe my second career is just going to be a trauma therapist, specializing in GitHub, and I think I can make money at that. So we have this inherent belief that branches are just how we code, and what we've been seeing is, people are pulling back more and more into trunk-based development, so that everybody is aware of what's going on all the time, and you can just have one through-line in your code and not have people spoiling off into branches that are unproductive. >> And how you do you manage that? So your tool manages that, or is it more of a philosophy discipline? >> No, it is a side effect of our tool, because the reason we have branches is because we don't want to show people our work in process. But if you can hide it behind a feature flag, and only deploy it, only activate it when you're ready, it gives you a good chance to test it in production. There's nothing that says you can't build your feature, test it in production at full scale, with all your microservices distributed, all of the data flow, everything, but you're the only one who sees it. And being able to target that is really important. It's going to give you a lot of capacity to test things. >> Yeah, and we've seen that, too, all the time, where people are saying, "Hey, you know what, I want to test it before I invest in it." That's a big thing. >> Yeah, it is. And internally being able to test things is going to give you a lot of capacity. So, we find that it is not our, we're not enforcing anything on anyone. That's not our role or our goal. What we're trying to do is offer people a tool that helps facilitate the best of what they're doing. >> Yeah, and when you look at developer tools, I think that's absolutely critical in bringing that to the table for different environments and things along those lines. >> And one of those things I was going to ask you is, when you look at the developer environment, is the developer environments, in your mind, in a spot where people can do this? In other words, will they be able to pull it off in open source, because if someone's got all this open source information going on, let's just say hypothetically, they got the trunk thing going on, but a lot of open source is driving this, so there's some discipline involved, there's some psychology, counseling, as you mentioned, so how do you pull it off? What's the best use case? >> You have to make it advantageous. You have to make it work for them, because people aren't going to do things that don't work for them. I teach a workshop, I was doing a workshop here about documentation, and people were like, "How do you get developers to document?" I'm like, "Well, have you ever fired a developer "for not documenting something?" "Have you ever given them a raise for documenting something? "If you haven't, you don't actually care about them "doing documentation." In the same way, moving culture means that we have to incentivize doing the right thing. We have to make the barrier to entry low, and we have to make it possible for people to just do the right thing more easily than the wrong thing. >> The other thing that I was thinking about, too, is, this is just kind of my personal opinion, 'cause the things you mentioned are really important, and that is that, doing testing at scale is a big deal, because if you think about all the wasted time that goes into, just the politics, whether it's politics or lobbying to get something in, a feature built, I mean, you're talking about months, weeks, I mean, it's a nightmare. So imagine a capability to say, and this is the promise of DevOps, this is ultimately why this is so awesome. >> So, this is like, move fast and don't break things very much. And I like to think of, every plane you get on is a little bit broken, it has an error budget, and if it exceeds the error budget in any direction, even if it's like an overhead latch bin, they ground the plane. But our organizations also need to be that resilient. We need to have that flexibility, and I think the way we can do that is by being able to instrument our features and turn them off if they're causing problems, or turn them down if we're getting flooded, or whatever it is we need to do, we need to do it at a finer grain than we've currently been doing. I don't ever want to have blackouts, like maybe a brownout. >> And Heidi, the other thing I think is interesting with what you guys are doing is that, this whole event here at DevNet Create, and all the other events that are, I call cutting edge developer events, the vendors who sell stuff, like Cisco, whether they're big, and new vendors, the old model of preaching and jamming solutions down your throat is not the way it works anymore. All the enablements has to be there, but the co-creations happening, really from the people who are building their own stuff, so that's kind of going to have to be a dynamic, creative environment, so you need to have a really pure DevOps environment. Well, not pure DevOps, I mean an environment that's going to be facilitating creativity, risk-taking, >> Yes. >> experimentation, building concepts, not, "Oh, I'm constrained, because this psychologically doesn't support," >> Yeah, it's hard to do advanced thinking when you are not psychologically safe. But I do think that you don't have to be operating in the purest of DevOps in order to be taking in some of these tools and techniques and using them effectively. I think there are a lot of people who have, for instance, taken up blameless post-mortems. Even if they're not doing anything else in the DevOps sphere, they're like, "Oh, wait, we could talk about "root causes that weren't, like people screwed up," and I want us to say whatever you can do that's going to improve your environment. I don't want people to feel like they have to absolutely transform everything, because that's too big an ask. >> Yeah, it's disruptive, too, to operations. You want to be just enough disruptive. Alright, I want to get your thoughts on something that I've been thinking about for a while, been talking about on theCUBE, and that is, I come from the old, when I was growing into the business, it was all waterfall-based software development, Agile comes along and it de-risks everything, because the old days was you created a product, you crafted it, you shipped it and you don't know if it was going to work or not, right? And you did QA, all that, you prayed. Now, with Agile, that got de-risked, so you, you're shipping code, you're iterating, but I'm arguing that the craftmanship has kind of gone out of it, because you're constantly programming, and so, that's kind of my opinion. Some people will debate that, but, now we're seeing a move towards, with the Agile Methodology, which I love, and a role of craftmanship, where cloud is kind of going to the next level, you're starting to see people think about crafting the product. So, as Agile goes to the next level, what's your opinion, view, of crafting process, now the user experience has gone beyond just look and feel and being good, mission-based applications, you're seeing new kinds of psychology of how people use things. So diversity becomes important, but the role of crafting and the methodology, is there a spot for that? How does that fit in? I mean, if you're constantly shipping code, push, push, push, are you crafting it? Is there, what do think, is there an art? Where's the artistry of it? >> Where is the artistry? Well, artistry isn't replicable. So this is sort of a problem, because what we really want is consistency. So I think eventually we'll become sort of like novelty ice cube molds. There's somebody who carves the original novelty ice cube mold, and then we all use it to make novelty ice cubes that fill our heart with delight. There is an artistry, but we're going to have to pay people to do it, and currently, we're only paying them to cool our drinks. And until we really make some time to say, "It is saving me time, it is saving me money "to have a well-crafted product," we're not going to change. And I think that's an interesting thing about serverless and function as a service, is it really pays to have a super well-constructed system. Those microseconds do count there, in a way that they haven't in the age of eternal storage and basically all the bandwidth we can consume. And I'd like to see that applied backward toward people who have very low bandwidth. I would love it if one day a month, everybody dialed down their corporate internet to the speed that rural America is getting, and see how they feel about their apps then, because there's a lot of people out there who do not have our big fat pipes. >> And also outside of the United States, too. Again, I'm not saying that there's not good software. I'm just kind of seeing a trend where, certainly I have seen this in DC and outside of the US, where mission-driven enterprises have completely different criteria for the product. And so I'm just trying to, I'm seeing some early signals around that the software methodology might, not shift, but it just feels like it's some action there, and I always kind of keep an eye on that. >> So the thing that I think is going to happen, and this is my weird futurist hat, is, I think we are going to have more and more modular, snap-together assemblies, and the product manager is going to rise from the ash heap and be the person who says, "Look, these are all the things that we need to assemble. "Please go find the parts, "so that we can build this that we want," in a way that we haven't prioritized in a realm where we're like, "Well, developers tell me how to do this." >> So componentized feature. >> Yeah, a componentized feature, I see us really moving strongly toward that. I think that's a lot of what we're doing with serverless, and software as a service is like, "Why build it yourself if somebody has already done it?" Like, "Please don't roll your own." Don't roll your own authentication, don't roll your own LDAP. It's a solved problem. Buy it and snap it together in a way that serves your customer. >> Jim Zemlin said this at the Open Source Summit in LA last year, he called it the open source sandwich, only 10% of the solutions are a unique IP, 90% of it is the bread that's from open source. So, to your point, this has already kind of going there, the exponential growth in open source is becoming significant. So with that in mind, that's going to play a part in that futuristic view, it's happening now. Your thoughts on open source, you mentioned that you could be a crisis counselor (laughing), a therapist, or whatever, I mean, there's a lot going on that's now tier one, it's multi-generational now, it's not the old days, renegade second-tier citizen, open source is powering the world. Your thoughts on the current state of open source? >> I think open source is a fascinating example of doing what we need and how it helps other people. And so, almost all open source projects, even now, start with personal pain. And then we expand them to other people. And I would like us to remember that the reason it's open is because we care about other people's pain, and it's really easy as we corporatize open source to forget that that's where we came from. >> And it's community-driven, and it's done in the open. >> Yeah, exactly, and revealing everything that we're doing is an excellent value, even if we're not necessarily licensing it. You can go and look at all of Launch Darkly's APIs. We have them out there, but we're not an open source company, we're just-- >> Transparent. >> Those are values that we have, that we want to be able, we want people to trust us, so we're going to show them. >> Well, congratulations, it's great to have you on. Great conversation. >> Thank you! >> Love the futuristic view, riffing on some concepts we've been thinking about, also. Got a great service, making possible to operate at scale, get new features tested and fire those capabilities. Appreciate it. >> Alright! >> Thanks for coming on theCUBE. >> Thank you! >> Thanks! >> We're here at DevNet Create, Cisco's cloud DevOps developer get-together. I'm John Furrier. We'll be back with more coverage after this short break.

(electronic music) >> Narrator: Live from Boston, Massachusetts it's The Cube covering OpenStack Summit 2017. Brought to you by the OpenStack Foundation, RedHat and additional ecosystem support. >> Welcome back, I'm Stu Miniman joined by my cohost John Troyer. We always want to give the community what they want. and I think from the early returns on day one, we brought back Mark Shuttleworth. So Mark, founder of Canonical, had you on yesterday. A lot of feedback from the communities, so welcome back. >> Thank you, great to be here and looking forward to questions from the community and you. >> Yeah, so let's start with, we love at the show you get some of these users up on stage and they get to talk about what they're doing. We were actually, John and I, were catching up with a friend of ours that talked about how a private cloud, the next revision is going to use OpenStack, so really, OpenStack's been a little under the covers in many ways. The composability of OpenStack now, we're going to see pieces of it show up a lot of places. We've heard a lot about the Telco places, maybe talk about some of the emerging areas, enterprise customers, that you find for Ubuntu and OpenStack specifically? >> Sure. Well it seems as if every industry has a different name for the same phenomenon, right. So, for some it's "digital", for other's it's essentially a transformation of some aspect of what they're doing. The Telcos call it NFV, in media you have OTT as a sort of emerging threat and the response, in every case, is really to empower developers. That's why it's such a fun time to be a software developer, because the established guys realize that if they aren't already competing with Silicon Valley, they're going to be competing with Silicon Valley. So in each industry there's a sort of challenges or labels that they give this process of kind of unleashing developers and it's fun for us, because we get to be part of that in many cases. I think the big drivers under the hood, other than the operational and economic dynamics of cloudification, I think the really big changes are going to be machine learning, which seems to be moving very quickly into every industry. Retailers are using it for predictive analytics on what to put in store or what to recommend online. It just has this huge effect on almost any business when you figure out how to use your data in that way. All of that is developer driven, all of that needs this kind of underlying infrastructure to power it and it's kind of relevant to every industry. For us media is a key prospect, you know that we've done very, very well in Telco. Media is now a sort-of critical focus. Companies like Bloomberg for example us Ubuntu as an elastic platform for agility for the developers. They're a pretty astonishing operation; media company, but very tech-centric, very tech-savvy. I don't know if you've had them on the show. In retail, Ebay, PayPal it's kind of a crossover finance. They're all using Ubuntu in that sort of way. They may now see the major financials who are looking at the intersection of machine learning and transactions systems effectively as the driver for that kind of change. >> Stu: So in our last interview we talked about are companies making money in OpenStack and your answer, resoundingly, was yes. >> Mark: For us, certainly, yeah. >> One of the things we always look at is kind of the open source model itself. I was at DockerCon a few weeks ago, it's like everybody's using Docker. How do they make money? The question I get from a number of people in the community is, everybody I talk to knows Ubuntu, uses Ubuntu, when do they transition to paying for some of the products? >> Well so one of our key tenants is that we want to put no friction in front of developers. So many of the people that you'll meet here or that you'll meet at other developer-centric summits, they're developer-oriented. They're creatives, effectively. So our products, our commercial products aren't really designed to tax developers effectively. What we want is developers to have the latest and greatest platforms, to have that absolutely free, to be able to have confidence in the fact that it can go into production. When applications get into production, a whole different set of people get involved. For example the security guys will say, does this comply with FIPS security? And that's a commercial capability that customers get from Canonical if they wanted so we're now getting a set of security certifications that enable people to take apps on Ubuntu into production inside defense industries or other high security industries. Similarly if you look at the support life cycle, our standard public free support maintenance window is five years, which is a long time, but for certain applications it turns out the app needs to be in production for 10 years and again that's a driver for a different set of people. Not the developers, but for compilers and system administration operation types to engage with Canonical commercially. Sometimes we would walk through the building and the developers love us as everything's free and then the ops guys love us because we will support them for longer than we would support the developers. >> Can we talk about Open Source as a component of business models in general maybe, and how you would like to see the ecosystem growing, and even Canonical's business model. In the course of the last decade in the industry itself, right, a lot of people sniping at each other; "Well, you know open core is the way to go, open source is not a business model" there's a lot of yelling. You've been around, you know what works. How do you a set of healthy companies that use open source develop in our ecosystem? >> So this is a really, really interesting topic and I'll start at the high end. If you think of the Googles, and the Facebooks, and the Amazons, and the Microsofts, and the Oracles, I think for them open source is now a weapon. It's a way to commoditize something that somebody else attaches value to and in the game of love and war, or Go, or chess, or however you want to think of it, between those giants open source very much has become a kind of root to market in order to establish standards for the next wave. Right now in machine learning for example we see all of these major guys pushing stuff out as open source. People wouldn't really ask "what's the business model" there 'cause they understand that this is these huge organizations essentially trying to establish standards for the next wave through open source. Okay, so that's one approach. On the startup side it's a lot more challenging and there I think we need to do two things. So right now I would say, if you're a single app startup it's very difficult with open source. If you've got a brilliant idea for a database, if you've got a brilliant idea for a messaging system, it's very, very difficult to do that with open source and I think you've seen the consequences of that over the years. That's actually not a great result for us in open source. At the end of the day, what drives brilliant folks to invest 20 hours a day for three years of their life to create something new, part of it is the sense they'll get a return on that and so, actually, we want that innovation. Not just from the Googles, and the Oracles, and the Microsofts, but we want innovation from real startups in open source. So one of the things I'd like to see is that I'd like to see the open source community being more generous of spirit to the startups who are doing that. That's not Canonical, particularly, but it is the Dockers of the world, it is the RethinkDBs, as a recent example. Those are great guys who had really good ideas and we should caution open source folks when they basically piss on the parade of the startup. It's a very short-sighted approach. The other thing that I do need to do is we need to figure out the monetization strategy. Selling software the old way is really terrible. There's a lot of friction associated with it. So one of the things that I'm passionate about is hacking Ubuntu to enable startups to innovate as open source if they want to, but then deliver their software to the enterprise market. Everywhere where you can find Ubuntu, and you know now that's everywhere right? Every Global 2000 company is running Ubuntu. Whether we can call them a customer or not is another question. But how can we enable all those innovators and startups to deliver their stuff to all of those companies and make money doing it? That's really good for those companies, and it's really good for the startups, and that's something I'm very passionate about. >> We've seen such a big transformation. I mean, the era of the shrink wrapped software is gone. An era that I want to get your long term perspective on is, when it comes to internet security. Back to your first company, we had Edward Snowden and the keynote this morning talking about security, and he bashed the public cloud guys and said "We need private cloud, and you need to control a lot more there" any comments on his stuff, the public/private era and internet security in general today? Are we safer today than we were back in '99? >> We certainly are safer in part because of Edward Snowden. Awareness is the only way to start the process of getting stuff better. I don't think it's simplistically that you can bash the public clouds. For example Google does incredible work around security and there's a huge amount of stuff in the Linux stack today around security specifically that we have Google to thank for. Amazon and others are also starting to invest in those areas. So I think the really interesting question is, how do we make security easy in the field and still make it meaningful? That's something we can have a big impact on because security when you touch it it can often feel like friction. So for example we use AppArmor. Now AppArmor is a more modern of the SC Linux ideas that is just super easy to use which means people don't even know that they're using it. Every copy of Ubuntu out there is actually effectively as secure as if you've turned on SC Linux, but administrators don't ever have to worry about that because the way AppArmor works is designed to be really, really easy to just integrate and that allows each piece of the ecosystem, the upstreams, the developers, the end users to essentially upgrade their security without really have to think about that as a budget item or a work ticket item, or something that's friction. >> Mark, any conversations on the show surprise you? Excite you? There's always such a great collection of some really smart and engaged people at this show. I'm curious what your experience has been so far. >> Sure. I think it's interesting. Open Stack moved so quickly from idea to superstar. I guess it's like a child prodigy, you know, a child TV star. The late teens can be a little rocky, right? (Mark laughs) I think it will emerge from all of that as quite a thoughtful community. There were a ton of people who came to these shows who were just stuffed, effectively, there by corporates who just wanted to do something in cloud. Now I think the conversation is much more measured. You've got folks here who really want these pieces to fit together and be useful. Our particular focus is the consumption of OpenStack in a way that is really economically impactful for enterprises. But the people who I see continuing to make meaningful contributions here are people who really want something to work. Whether that's networking, or storage, or compute, or operations as in our case but they're the folks who care about that infrastructure really working rather than the flash in the pan types and I think that's a good transition for the community to be making. >> Can you say a little more about the future of OpenStack and the direction you see the community going. I don't know. If you had a magic wand and you look forward a couple of years. We talked a lot about operability and maintainability, upgradeability, ease of use. That seems to be one of the places that you're trying to drive the ecosystem. >> One of the things that I think the community is starting to realize is that if you try to please everybody, you'll end up with something nobody can really relate to. I think if you take the mission of OpenStack as to say, look, open source is going to do lots of complicated things but if we can essentially just deliver virtualized infrastructure in a super automated way so that nobody has to think about it, the virtual machines, virtual disks, virtual networks on demand. That's an awesome contribution to the innovation stack. There are a ton of other super shiny things that could happen on any given culture and ODS but if we just get that piece right, we've made a huge contribution and I think for a while OpenStack was trying to do everything for everybody. Lots of reasons why that might be the case but now I think there's a stronger sense of "This is the mission" and it will deliver on that mission, I have great confidence. It was contrarian then to say we shouldn't be doing everything, it's contrarian now to say "actually, we're fine". We're learning what we need to be. >> The ebb and flows of this community have been really interesting. NASA helped start it. NASA went to Amazon, NASA went back to OpenStack. >> Think about the economics of cars, right. It's kind of incredible that I can sit outside the building and pull up the app, and I have a car. It's also quite nice to own a car. People do both. The economics of ownership and the economics of renting, they're pretty well understood and most institutions or most people can figure out that sometimes they'll do a bit of either. What we have to do is, at the moment we have a situation where if you want to own your infrastructure the operations are unpredictable. Whereas if you rent it it's super predictable. If we can just put predictability of price and performance into OpenStack, which is, for example what the manage services, what BootStack does. Also what JUJU and MAAS do. They allow you to say, I can do that. I can do that quickly, and I don't have to go and open a textbook to do that or hire 50 people to do it. That essentially allows people now to make the choice between owning and renting in a very natural way, and I think once people understand that that's what this is all about it'll give them a sense of confidence again. >> Curious your viewpoint on the future of jobs in tech. We talked a little bit before about autonomous vehicles. It has the opportunity to be a great boon from a technology standpoint but could hollow out this massive amount of jobs globally. Is technology an enabler of some of these things? Do we race with the machines? We interviewed Erik Brynjolfsson and Andy McAfee from the MIT Sloan School. Did you personally have some thoughts on that? In places where Canonical looks about our future workforce, do we end up with "coding becomes the new blue collar job"? >> I don't know if I can speak to a single career but I think the simple fact is there's nothing magical about the brain. The brain is a mesh network competing flows and it makes decisions, and I think we will simulate that pretty soon and we'll suddenly realize there's nothing magical about the brain but there is something magical about humans and so, what is a job? A job is kind of how we figure out what we want to do most of the day and how we want to define ourselves in some sense. That's never going to go away. I think it's highly likely that humans are obsolete as decision makers and surprisingly soon. Simply because there's nothing magic about the brain and we'll build bigger and better brains for any kind of decision you can imagine. But the art of being human? That's kind of magical, and humans will find a way to evolve into that time. I'm not too worried about it. >> Okay. Last thing I want to ask is, what's exciting you these days? We've talked about space exploration a few times. Happy to comment on it. I mean, the last 12 months has been amazing to watch for those of us. I grew up studying engineering. You always look up to the stars. What's exciting you these days? >> Well the commercialization of space, the commercial access to space is just fantastic to see, sure, really dawning and credit to the Bezoses and the Musks who are kind of shaking up the status quo in those industries. We will be amongst the stars. I have no doubt about it. It will be part of the human experience. For me personally, I expect I'll go back to space and do something interesting there. It'll get easier and easier and so I can pack my walking stick and go to the moon, maybe. But right now from a love of technology and business point of view, IoT is such rich pickings. You can't swing a cat but find something that can be improved in a very physical way. It's great to see that intersection of entrepreneurship and tinkering suddenly come alive again. You don't have to be a giant institution to go and compete with the giant institutions that are driving the giant clouds. You just have to be able to spot a business opportunity in real life around you and how the right piece of software in the right place with the right data can suddenly make things better and so it's just delicious the sort of things people are doing. Ubuntu again is a great platform for innovating around that. It's just great fun for me to see really smart people who three years ago would say, do I really want to go work at a giant organization in Silicon Valley? Or can I have fun with something for a while that's really mine and whether that's worth 12 bucks or 12 billion who knows? But it just feels fun and I'm enjoying that very much, seeing people find interesting things to do at the edge. >> Mark Shuttleworth, appreciate being able to dig into a lot more topics with you today and we'll be right back with lots more coverage here from OpenStack 2017 in Boston. You're watching the cube. (electronic music)