>>Live from Miami, Florida. It's the cube covering IBM's data and AI forum brought to you by IBM. >>Welcome back to downtown Miami. Everybody. We're here at the Intercontinental hotel covering the IBM data AI form hashtag data AI forum. My name is Dave Volante and you're watching the cube, the leader in live tech coverage. Ritika gunner is here. She's the vice president of data and AI expert labs and learning at IBM. Ritika, great to have you on. Again, always a pleasure to be here. Dave. I love interviewing you because you're a woman executive that said a lot of different roles at IBM. Um, you know, you've, we've talked about the AI ladder. You're climbing the IBM ladder and so it's, it's, it's, it's awesome to see and I love this topic. It's a topic that's near and dear to the cubes heart, not only women in tech, but women in AI. So great to have you. Thank you. So what's going on with the women in AI program? We're going to, we're going to cover that, but let me start with women in tech. It's an age old problem that we've talked about depending on, you know, what statistic you look at. 15% 17% of, uh, of, of, of the industry comprises women. We do a lot of events. You can see it. Um, let's start there. >>Well, obviously the diversity is not yet there, right? So we talk about women in technology, um, and we just don't have the representation that we need to be able to have. Now when it comes to like artificial intelligence, I think the statistic is 10 to 15% of the workforce today in AI is female. When you think about things like bias and ethicacy, having the diversity in terms of having male and female representation be equal is absolutely essential so that you're creating fair AI, unbiased AI, you're creating trust and transparency, set of capabilities that really have the diversity in backgrounds. >>Well, you work for a company that is as chairman and CEO, that's, that's a, that's a woman. I mean IBM generally, you know, we could see this stuff on the cube because IBM puts women on a, we get a lot of women customers that, that come on >>and not just because we're female, because we're capable. >>Yeah. Well of course. Right. It's just because you're in roles where you're spokespeople and it's natural for spokespeople to come on a forum like this. But, but I have to ask you, with somebody inside of IBM, a company that I could say the test to relative to most, that's pretty well. Do you feel that way or do you feel like even a company like IBM has a long way to go? >>Oh, um, I personally don't feel that way and I've never felt that to be an issue. And if you look at my peers, um, my um, lead for artificial intelligence, Beth Smith, who, you know, a female, a lot of my peers under Rob Thomas, all female. So I have not felt that way in terms of the leadership team that I have. Um, but there is a gap that exists, not necessarily within IBM, but in the community as a whole. And I think it goes back to you want to, you know, when you think about data science and artificial intelligence, you want to be able to see yourself in the community. And while there's only 10 to 15% of females in AI today, that's why IBM has created programs such as women AI that we started in June because we want strong female leaders to be able to see that there are, is great representation of very technical capable females in artificial intelligence that are doing amazing things to be able to transform their organizations and their business model. >>So tell me more about this program. I understand why you started it started in June. What does it entail and what's the evolution of this? >>So we started it in June and the idea was to be able to get some strong female leaders and multiple different organizations that are using AI to be able to change their companies and their business models and really highlight not just the journey that they took, but the types of transformations that they're doing and their organizations. We're going to have one of those events tonight as well, where we have leaders from Harley Davidson in Miami Dade County coming to really talk about not only what was their journey, but what actually brought them to artificial intelligence and what they're doing. And I think Dave, the reason that's so important is you want to be able to understand that those journeys are absolutely approachable. They're doable by any females that are out there. >>Talk about inherent bias. The humans are biased and if you're developing models that are using AI, there's going to be inherent bias in those models. So talk about how to address that and why is it important for more diversity to be injected into those models? >>Well, I think a great example is if you took the data sets that existed even a decade ago, um, for the past 50 years and you created a model that was to be able to predict whether to give loans to certain candidates or not, all things being equal, what would you find more males get these loans than females? The inherent data that exists has bias in it. Even from the history based on what we've had yet, that's not the way we want to be able to do things today. You want to be able to identify that bias and say all things being equal, it is absolutely important that regardless of whether you are a male or a female, you want to be able to give that loan to that person if they have all the other qualities that are there. And that's why being able to not only detect these things but have the diversity and the kinds of backgrounds of people who are building AI who are deploying this AI is absolutely critical. >>So for the past decade, and certainly in the past few years, there's been a light shined on this topic. I think, you know, we were at the Grace Hopper conference when Satya Nadella stuck his foot in his mouth and it said, Hey, it's bad karma for you know, if you feel like you're underpaid to go complain. And the women in the audience like, dude, no way. And he, he did the right thing. He goes, you know what, you're right. You know, any, any backtrack on that? And that was sort of another inflection point. But you talk about the women in, in AI program. I was at a CDO event one time. It was I and I, an IBM or had started the data divas breakfast and I asked, can I go? They go, yeah, you can be the day to dude. Um, which was, so you're seeing a lot of initiatives like this. My question is, are they having the impact that you would expect and that you want to have? >>I think they absolutely are. Again, I mean, I'll go back to, um, I'll give you a little bit of a story. Um, you know, people want to be able to relate and see that they can see themselves in these females leaders. And so we've seen cases now through our events, like at IBM we have a program called grow, which is really about helping our female lead female. Um, technical leaders really understand that they can grow, they can be nurtured, and they have development programs to help them accelerate where they need to be on their technical programs. We've absolutely seen a huge impact from that from a technology perspective. In terms of more females staying in technology wanting to go in the, in those career paths as another story. I'll, I'll give you kind of another kind of point of view. Um, Dave and that is like when you look at where it starts, it starts a lot earlier. >>So I have a young daughter who a year, year and a half ago when I was doing a lot of stuff with Watson, she would ask me, you know, not only what Watson's doing, but she would say, what does that mean for me mom? Like what's my job going to be? And if you think about the changes in technology and cultural shifts, technology and artificial intelligence is going to impact every job, every industry, every role that there is out there. So much so that I believe her job hasn't been invented yet. And so when you think about what's absolutely critical, not only today's youth, but every person out there needs to have a foundational understanding, not only in the three RS that you and I know from when we grew up have reading, writing and arithmetic, we need to have a foundational understanding of what it means to code. And you know, having people feel confident, having young females feel confident that they can not only do that, that they can be technical, that they can understand how artificial intelligence is really gonna impact society. And the world is absolutely critical. And so these types of programs that shed light on that, that help bridge that confidence is game changing. >>Well, you got kids, I >>got kids, I have daughters, you have daughter. Are they receptive to that? So, um, you know, I think they are, but they need to be able to see themselves. So the first time I sent my daughter to a coding camp, she came back and said, not for me mom. I said, why? Because she's like, all the boys, they're coding in their Minecraft area. Not something I can relate to. You need to be able to relate and see something, develop that passion, and then mix yourself in that diverse background where you can see the diversity of backgrounds. When you don't have that diversity and when you can't really see how to progress yourself, it becomes a blocker. So as she started going to grow star programs, which was something in Austin where young girls coded together, it became something that she's really passionate about and now she's Python programming. So that's just an example of yes, you need to be able to have these types of skills. It needs to start early and you need to have types of programs that help enhance that journey. >>Yeah, and I think you're right. I think that that is having an impact. My girls who code obviously as a some does some amazing work. My daughters aren't into it. I try to send them to coder camp too and they don't do it. But here's my theory on that is that coding is changing and, and especially with artificial intelligence and cognitive, we're a software replacing human skills. Creativity is going to become much, much more important. My daughters are way more creative than my sons. I shouldn't say that, but >>I think you just admitted that >>they, but, but in a way they are. I mean they've got amazing creativity, certainly more than I am. And so I see that as a key component of how coding gets done in the future, taking different perspectives and then actually codifying them. Your, your thoughts on that. >>Well there is an element of understanding like the outcomes that you want to generate and the outcomes really is all about technology. How can you imagine the art of the possible with technology? Because technology alone, we all know not useful enough. So understanding what you do with it, just as important. And this is why a lot of people who are really good in artificial intelligence actually come from backgrounds that are philosophy, sociology, economy. Because if you have the culture of curiosity and the ability to be able to learn, you can take the technology aspects, you can take those other aspects and blend them together. So understanding the problem to be solved and really marrying that with the technological aspects of what AI can do. That's how you get outcomes. >>And so we've, we've obviously talking in detail about women in AI and women in tech, but it's, there's data that shows that diversity drives value in so many different ways. And it's not just women, it's people of color, it's people of different economic backgrounds, >>underrepresented minorities. Absolutely. And I think the biggest thing that you can do in an organization is have teams that have that diverse background, whether it be from where they see the underrepresented, where they come from, because those differences in thought are the things that create new ideas that really innovate, that drive, those business transformations that drive the changes in the way that we do things. And so having that difference of opinion, having healthy ways to bring change and to have conflict, absolutely essential for progress to happen. >>So how did you get into the tech business? What was your background? >>So my background was actually, um, a lot in math and science. And both of my parents were engineers. And I have always had this unwavering, um, need to be able to marry business and the technology side and really figure out how you can create the art of the possible. So for me it was actually the creativity piece of it where you could create something from nothing that really drove me to computer science. >>Okay. So, so you're your math, uh, engineer and you ended up in CS, is that right? >>Science. Yeah. >>Okay. So you were coded. Did you ever work as a programmer? >>Absolutely. My, my first years at IBM were all about coding. Um, and so I've always had a career where I've coded and then I've gone to the field and done field work. I've come back and done development and development management, gone back to the field and kind of seen how that was actually working. So personally for me, being able to create and work with clients to understand how they drive value and having that back and forth has been a really delightful part. And the thing that drives me, >>you know, that's actually not an uncommon path for IBM. Ours, predominantly male IBM, or is in the 50 sixties and seventies and even eighties. Who took that path? They started out programming. Um, I just think, trying to think of some examples. I know Omar para, who was the CIO of Aetna international, he started out coding at IBM. Joe Tucci was a programmer at IBM. He became CEO of EMC. It was a very common path for people and you took the same path. That's kind of interesting. Why do you think, um, so many women who maybe maybe start in computer science and coding don't continue on that path? And what was it that sort of allowed you to break through that barrier? >>No, I'm not sure why most women don't stay with it. But for me, I think, um, you know, I, I think that every organization today is going to have to be technical in nature. I mean, just think about it for a moment. Technology impacts every part of every type of organization and the kinds of transformation that happens. So being more technical as leaders and really understanding the technology that allows the kinds of innovations and business for informations is absolutely essential to be able to see progress in a lot of what we're doing. So I think that even general CXOs that you see today have to be more technically acute to be able to do their jobs really well and marry those business outcomes with what it fundamentally means to have the right technology backbone. >>Do you think a woman in the white house would make a difference for young people? I mean, part of me says, yeah, of course it would. Then I say, okay, well some examples you can think about Margaret Thatcher in the UK, Angela Merkel, and in Germany it's still largely male dominated cultures, but I dunno, what do you think? Maybe maybe that in the United States would be sort of the, >>I'm not a political expert, so I wouldn't claim to answer that, but I do think more women in technology, leadership role, CXO leadership roles is absolutely what we need. So, you know, politics aside more women in leadership roles. Absolutely. >>Well, it's not politics is gender. I mean, I'm independent, Republican, Democrat, conservative, liberal, right? Absolutely. Oh yeah. Well, companies, politics. I mean you certainly see women leaders in a, in Congress and, and the like. Um, okay. Uh, last question. So you've got a program going on here. You have a, you have a panel that you're running. Tell us more about. >>Well this afternoon we'll be continuing that from women leaders in AI and we're going to do a panel with a few of our clients that really have transformed their organizations using data and artificial intelligence and they'll talk about like their backgrounds in history. So what does it actually mean to come from? One of, one of the panelists actually from Miami Dade has always come from a technical background and the other panelists really etched in from a non technical background because she had a passion for data and she had a passion for the technology systems. So we're going to go through, um, how these females actually came through to the journey, where they are right now, what they're actually doing with artificial intelligence in their organizations and what the future holds for them. >>I lied. I said, last question. What is, what is success for you? Cause I, I would love to help you achieve that. That objective isn't, is it some metric? Is it awareness? How do you know it when you see it? >>Well, I think it's a journey. Success is not an endpoint. And so for me, I think the biggest thing I've been able to do at IBM is really help organizations help businesses and people progress what they do with technology. There's nothing more gratifying than like when you can see other organizations and then what they can do, not just with your technology, but what you can bring in terms of expertise to make them successful, what you can do to help shape their culture and really transform. To me, that's probably the most gratifying thing. And as long as I can continue to do that and be able to get more acknowledgement of what it means to have the right diversity ingredients to do that, that success >>well Retika congratulations on your success. I mean, you've been an inspiration to a number of people. I remember when I first saw you, you were working in group and you're up on stage and say, wow, this person really knows her stuff. And then you've had a variety of different roles and I'm sure that success is going to continue. So thanks very much for coming on the cube. You're welcome. All right, keep it right there, buddy. We'll be back with our next guest right after this short break, we're here covering the IBM data in a AI form from Miami right back.

(upbeat music) >> From New York City, it's theCUBE. Covering "Welcome To The New Edge." Brought to you by Pensando Systems. >> Hey, welcome back here ready. Jeff Frick here with theCUBE. We are high atop Goldman Sachs in downtown Manhattan, I think it's 43 floors, for a really special event. It's the Pensando launch. It's really called welcome to the new edge and we talked about technology. We had some of the founders on but, these type of opportunities are really special to talk to some really senior leaders and we're excited to have John Chambers back on, who as you know, historic CEO of Cisco for many, many years. Has left that, is doing his own ventures he's writing books, he's investing and he's, happens to be chairman of the board of Pensando. So John, thanks for taking a few minutes with us. >> Well, more than a few minutes, I think what we talked about today is a major industry change and so to focus on that and focus about the implications will be a lot of fun. >> So let's jump into it. So, one of the things you led with earlier today was kind of these 10 year cycles and they're not exactly 10 years, but you outlined a series of them from mainframe, mini client server everybody knows kind of the sequence. What do you think it is about the 10 year kind of cycle besides the fact that it's easy and convenient for us to remember, that, kind of paces these big disruptions? >> Well, I think it has to do with once a company takes off they tend to, dominate that segment of the industry for so long that even if a creative idea came up they were just overpowering. And then toward the end of a 10 year cycle they quit reinventing themselves. And we talked earlier about the innovator's dilemma and the implications for it. Or an architecture that was designed that suddenly can't go to the next level. So I think it's probably a combination of three or four different factors, including the original incumbent who broke the glass, disrupted others, not disrupting themselves. >> Right, but you also talked about a story where you had to shift focus based on some customer feedback and you ran Cisco for a lot longer than 10 years. So how do you as a leader kind of keep your ears open to something that's a disruptive change that's not your regular best customer and your regular best salesman asking for a little bit faster, a little bit cheaper, a little bit of more the same versus the significant disruptive transformational shift? >> Well this goes back to one of my most basic views in life is I think we learn more from our setbacks or setbacks we were part of, or even the missteps or mistakes than you ever do your successes. Everybody loves to talk about successes and I'm no different there. But when you watched a great state like West Virginia that was the chemical center of the world and the coal mining center of the world, the 125,000 coal mines, six miners very well paid, 6,000 of the top engineers in the world, it was the Silicon Valley of the chemical industry and those just disappear. And because our state did not reinvent itself, because the education system didn't change, because we didn't distract attract a new set of businesses in we just kept doing the right thing too long, we got left behind. Then I went to Boston, it was the Silicon Valley of the world. And Route 128 around Boston was symbolic with the Silicon Valley and I-101 and 280 around it. And we had the top university at that time. Much like Stanford today, but MIT generating new companies. We had great companies, DEC, Wang, Data General. Probably a million jobs in the area and because we got stuck in a segment of the market, quit listening to our customers and missed the transitions, not only did we lose probably 1.2 million jobs on it, 100,000 out of DEC, 32,000 out of Wang, etc, we did not catch the next generation of technology changes. So I understand the implications if you don't disrupt yourself. But I also learned, that if you're not regularly reinventing yourself, you get left behind as a leader. And one of my toughest competitors came up to me and said, "John, I love the way you're reinventing Cisco "and how you've done that multiple times." And then I turned and I said "That's why a CEO has got to be in the job "for more than four or five years" and he said, "Now we disagree again." Which we usually did and he said, "Most people can't reinvent themselves." And he said "I'm an example." "I'm a pretty good CEO" he's actually a very good CEO, but he said, "After I've been there three or four years "I've made the changes, that I know "I've got to go somewhere else." And he could see I didn't buy-in and then he said, "How many of your top 100 people "you've been happy with once they've been "in the job for more than five years?" I hesitated and I said "Only one." And he's right, you've got to move people around, you've got to get people comfortable with disruption on it and, the hardest one to disrupt are the companies or the leaders who've been most successful and yet, that's when you got to think about disruption. >> Right, so to pivot on that a little bit in terms of kind of the government's role in jobs, specifically. >> Yes. >> We're in this really strange period of time. We have record low unemployment, right, tiny, tiny unemployment, and yet, we see automation coming in aggressively with autonomous vehicles and this and that and just to pick truck drivers as a category, everyone can clearly see that autonomous vehicles are going to knock them out in the not too distant future. That said, there's more demand for truck drivers today than there's every been and they can't fill the positions So, with this weird thing where we're going to have a bunch of new jobs that are created by technology, we're going to have a bunch of old jobs that get displaced by technology, but those people aren't necessarily the same people that can leave the one and go to the other. So as you look at that challenge, and I know you work with a lot of government leaders, how should they be thinking about taking on this challenge? >> Well, I think you've got to take it on very squarely and let's use the U.S. as an example and then I'll parallel what France is doing and what India is doing that is actually much more creative that what we are, from countries you wouldn't have anticipated. In the U.S. we know that 50% of the Fortune 500 will probably not exist in 10 years, 12 at the most. We know that the large companies will not incrementally hire people over this next decade and they've often been one of the best sources of hiring because of AI and automation will change that. So, it's not just a question of being schooled in one area and move to another, those jobs will disappear within the companies. If we don't have new jobs in startups and if we don't have the startups running at about three to four times the current volumes, we've got a real problem looking out five to 10 years. And the startups where everyone thinks we're doing a good job, the app user, third to a half of what they were two decades ago. And so if you need 25 million jobs over this next decade and your startups are at a level more like they were in the 90s, that's going to be a challenge. And so I think we've got to think from the government perspective of how we become a startup nation again, how we think about long-term job creation, how we think about job creation not taking money out of one pocket and give it to another. People want a real job, they want to have a meaningful job. We got to change our K through 12 education system which is broken, we've got to change our university system to generate the jobs for where people are going and then we've got to retrain people. That is very doable, if you got at it with a total plan and approach it from a scale perspective. That was lacking. And one of the disappointing things in the debate last night, and while I'm a republican I really want who's going to really lead us well both at the presidential level, but also within the senate, the house. Is, there was a complete lack of any vision on what the country should look like 10 years from now, and how we're going to create 25 million jobs and how we're going to create 10 million more that are going to be displaced and how we're going to re-educate people for it. It was a lot of finger pointing and transactional, but no overall plan. Modi did the reverse in India, and actually Macron, in all places, in France. Where they looked at GDP growth, job creation, startups, education changes, etc, and they executed to an overall approach. So, I'm looking for our government really to change the approach and to really say how are we going to generate jobs and how are we going to deal with the issues that are coming at us. It's a combination of all the the above. >> Yep. Let's shift gears a little bit about the education system and you're very involved and you talked about MIT. Obviously, I think Stanford and Cal are such big drivers of innovation in the Bay area because smart people go there and they don't leave. And then there's a lot of good buzz now happening in Atlanta as an investment really piggy-backing on Georgia Tech, which also creates a lot of great engineers. As you look at education, I don't want to go through K through 12, but more higher education, how do you see that evolving in today's world? It's super expensive, there's tremendous debt for the kids coming out, it doesn't necessarily train them for the new jobs. >> Where the jobs are. >> How do you see, kind of the role of higher education and that evolving into kind of this new world in which we're headed? >> Well, the good news and bad news about when I look at successful startups around the world, they're always centered around a innovative university and it isn't just about the raw horse power of the kids, It starts with the CEO of the university, the president of the university, their curriculum, their entrepreneurial approach, do they knock down the barriers across the various groups from engineering to business to law, etc? And are they thinking out of box? And if you watch, there is a huge missing piece between, Georgia Tech more of an exception, but still not running at the level they need to. And the Northeast around Boston and New York and Silicon Valley, The rest of the country's being left behind. So I'm looking for universities to completely redo their curriculum. I'm looking for it really breaking down the silos within the groups and focus on the outcomes. And much like Steve Case has done a very good job on focusing, about the Rust Belt and how do you do startups? I'm going to learn from what I saw in France at Polytechnique and the ITs in India, and what occurred in Stanford and MIT used to occur is, you've got to get the universities to be the core and that's where they kids want to stay close to, and we've got to generate a whole different curriculum, if you will, in the universities, including, continuous learning for their graduates, to be able to come back virtually and say how do I learn about re-skilling myself? >> Yeah. >> The current model is just not >> the right model >> It's broken. >> For the, for going forward. >> K through 12 is >> hopelessly broken >> Yeah. >> and the universities, while were still better than anywhere else in the world, we're still teaching, and some of the teachers and some of the books are what I could have used in college. >> Right, right >> So, we got to rethink the whole curriculum >> darn papers on the inside >> disrupt, disrupt >> So, shifting gears a little bit, you, played with lots of companies in your CEO role you guys did a ton of M&A, you're very famous for the successful M&A that you did over a number of years, but in an investor role, J2 now, you're looking at a more early stage. And you said you made a number of investments which is exciting. So, as you evaluate opportunities A. In teams that come to pitch to you >> Yeah. >> B. What are the key things you look for? >> In the sequence you've raised them, first in my prior world, I was really happy to do 180 acquisitions, in my current world, I'm reversed, I want them to go IPO. Because you add 76% of your headcount after an IPO, or after you've become a unicorn. When companies are bought, including what I bought in my prior role, their headcount growth is pretty well done. We'd add engineers after that, but would blow them through our sales channel, services, finance, etc. So, I want to see many more of these companies go public, and this goes back to national agenda about getting IPO's, not back to where they were during the 90's when it was almost two to three times, what you've seen over the last decade. But probably double, even that number the 90's, to generate the jobs we want. So, I'm very interested now about companies going public in direction. To the second part of your question, on what do I look for in startups and why, if I can bridge it, to am I so faired up about Pensando? If I look for my startups and, it's like I do acquisitions, I develop a playbook, I run that playbook faster and faster, it's how I do digitization of countries, etc. And so for a area I'm going to invest in and bet on, first thing I look at, is their market, technology transition, and business model transition occurring at the same time. That was Amazon of 15 years ago as an example. The second thing I look at, is the CEO and ideally, the whole founding team but it's usually just the CEO. The third thing I look for, is what are the customers really say about them? There's only one Steve Jobs, and it took him seven years. So, I go to the customers and say "What do you really think of this company?" Fourth thing I look for, is how close to an inflection point are they. The fifth thing I look for, is what they have in their ecosystem. Are they partnering? Things of that type. So, if I were to look at Pensando, Which is really the topic about can they bring to the market the new edge in a way that will be a market leading force for a whole decade? Through a ecosystem of partners that will change business dramatically and perhaps become the next major tech icon. It's how well you do that. Their vision in terms of market transitions, and business transitions 100% right. We've talked about it, 5G, IOT, internet of things, going from 15 billion devices to 500 billion devices in probably seven years. And, with the movement to the edge the business models will also change. And this is where, democratization, the cloud, and people able to share that power, where every technology company becomes a business becomes a, every business company becomes a technology company. >> Right. >> The other thing I look at is, the team. This is a team of six people, myself being a part of it, that thinks like one. That is so unusual, If you're lucky, you get a CEO and maybe a founder, a co-founder. This team, you've got six people who've worked together for over 20 years who think alike. The customers, you heard the discussions today. >> Right. >> And we've not talked to a single cloud player, a single enterprise company, a single insurance provider, or major technology company who doesn't say "This is very unique, let's talk about "how we work together on it." The inflection point, it's now you saw that today. >> Nobody told them it's young mans game obviously, they got the twenty-something mixed up >> No, actually were redefining (laughs) twenty-something, (laughs) but it does say, age is more perspective on how you think. >> Right, right. >> And Shimone Peres, who, passed away unfortunately, two years ago, was a very good friend. He basically said "You've got all your life "to think like a teenager, "and to really think and dream out of box." And he did it remarkably well. So, I think leaders, whether their twenty-something, or twenty-some years of experience working you've got to think that way. >> Right. So I'm curious, your take on how this has evolved, because, there was data and there was compute. And networking brought those two thing together, and you were at the heart of that. >> Mm-hmm. Now, it's getting so much more complex with edge, to get your take on edge. But, also more importantly exponential growth. You've talked about going from, how ever many millions the devices that were connected, to the billions of devices that are connected now. How do you stay? How do you help yourself think along exponential curves? Because that is not easy, and it's not human. But you have to, if you're going to try to get ahead of that next wave. >> Completely agree. And this is not just for me, how do I do it? I'm sharing it more that other people can learn and think about it perhaps the same way. The first thing is, it's always good to think of the positive, You can change the world here, the positive things, But I've also seen the negatives we talked about earlier. If you don't think that way, if you don't think that way as a leader of your company, leader of your country, or the leader of a venture group you're going to get left behind. The implications for it are really bad. The second is, you've got to say how do you catch and get a replicable playbook? The neat thing about what were talking about, whether it's by country in France, or India or the U.S., we've got replicable playbooks we know what to run. The third element is, you've got to have the courage to get outside your comfort zone. And I love change when it happens to you, I don't like it when it happens to me And I know that, So, I've got to get people around me who push me outside my comfort zone on that. And then, you've got to be able to dream and think like that teenager we talked about before. But that's what we were just with a group of customers, who were at this event. And they were asking "How do we get "this innovation into our company?" "How do we get the ability to innovate, through not just strategic partnerships with other large companies or partnerships with startups?" But "How do we build that internally?" It's comes down to the leader has to create that image and that approach. Modi's done it for 1.3 billion people in India. A vision, of the future on GDP growth. A digital country, startups, etc. If they can do it for 1.3 billion, tell me why the U.S. can not do it? (laughs) And why even small states here, can't do it. >> Yeah. Shifting gears a little bit, >> All right. >> A lot of black eyes in Silicon Valley right now, a lot of negativity going on, a lot of problems with privacy and trading data for currency and, it's been a rough road. You're way into tech for good and as you said, you can use technology for good you can use technology for bad. What are some things you're doing on the tech for good side? Because I don't think it gets the spotlight that it probably should, because it doesn't sell papers. >> Well, actually the press has been pretty good we just need to do it more on scale. Going back to Cisco days, we never had any major issues with governments. Even though there was a Snowden issue, there were a lot of implications about the power of the internet. Because we work with governments and citizens to say "What are the legitimate needs so that everybody benefits from this?" And where the things that we might have considered doing that, governments felt strongly about or the citizens wouldn't prosper from we just didn't do it. And we work with democrats and republicans alike and 90% of our nation believed tech was for good. But we worked hard on that. And today, I think you got to have more companies doing this and then, what, were doing uniquely in JC2, is were literally partnering with France on tech is for good and I'm Macron's, global tech ambassador and we focus about job creation and inclusion. Not just in Paris, or around Station F but throughout all the various regions in the country. Same thing within India, across 26 different states with Modi on how do you drive it through? And then if we can do it in France or India why can't we do it in each state in the U.S.? Partnering with West Virginia, with a very creative, president of the university there West Virginia University. With the democrats and republicans in their national senate, but also within the governor and speaker of the house and the president and senate within West Virginia, and really saying were going to change it together. And getting a model that you can then cookie cut across the U.S. if you change the curriculum, to your earlier comments. If you begin to focus on outcomes, not being an expert in one area, which is liable not to have a job >> Right. >> Ten years later. So, I'm a dreamer within that, but I think you owe an obligation to giving back, and I think they're all within our grasps >> Right >> And I think you can do, the both together. I think at JC2 we can create a billion dollar company with less than 10 people. I think you can change the world and also make a very good profit. And I think technology companies have to get back to that, you got to create more jobs than you destroy. And you can't be destroying jobs, then telling other people how to live their lives and what their politics should be. >> Yeah. >> That just doesn't work in terms of the environment. >> Well John, again, thanks for your time. Give you the last word on >> Sure >> Account of what happened here today, I mean you're here, and Tony O'Neary was here or at the headquarters of Goldman. A flagship launch customer, for the people that weren't here today why should they be paying attention? >> Well, if we've got this market transition right, the technology and business model, the next transition will be everything goes to the edge. And as every company or every government, or every person has to be both good in their "Area of expertise." or their vertical their in, they've got to also be good in technology. What happened today was a leveling of the playing field as it relates to cloud. In terms of everyone should have choice, democratization there, but also in architecture that allows people to really change their business models, as everything moves to the edge where 75% of all transactions, all data will be had and it might even be higher than that. Secondly, you saw a historic first never has anybody ever emerged from stealth after only two and a half years of existing as a company, with this type of powerhouse behind them. And you saw the players where you have a customer, Goldman Sachs, in one of the most leading edge areas, of industry change which is obviously finance leading as the customer who's driven our direction from the very beginning. And a company like NetApp, that understood the implication on storage, from two and a half years ago and drove our direction from the very beginning. A company like HP Enterprise's, who understood this could go across their whole company in terms of the implications, and the unique opportunity to really change and focus on, how do they evolve their company to provide their customer experience in a very unique way? How do you really begin to think about Equinix in terms of how they changed entirely from a source matter prospective, what they have to do in terms of the direction and capabilities? And then Lightspeed, one of the most creative intra capital that really understands this transition saying "I want to be a part of this." Including being on the board and changing the world one more time. So, what happened today? If we're right, I think this was the beginning of a major inflection point as everything moves to the edge. And how ecosystem players, with Pensando at the heart of that ecosystem, can take on the giants but also really use this technology to give everybody choice, and how they really make a difference in the future. As well as, perhaps give back to society. >> Love it. Thank you John >> My pleasure, that was fun. >> Appreciate it. You're John, I'm Jeff you're watching theCUBE. Thanks for watching, we'll see you next time. (upbeat music)

>> from Cambridge, Massachusetts. It's the Cube covering M I T. Chief data officer and information quality Symposium 2019. Brought to you by Silicon Angle Media. >> Welcome back to M I. T. Everybody. This is the Cube. The leader in live coverage. My name is David wanted. I'm here with my co host, Paul Gill, in this day to coverage of the M I t cdo I Q conference. A lot of acronym stands for M I. T. Of course, the great institution. But Chief Data officer information quality event is his 13th annual event. Lars to Maria's here is the managing partner of Brass Rat Capital. Cool name Lars. Welcome to the Cube. Great. Very much. Glad I start with a name brass around Capitol was That's >> rat is reference to the M I t school. Okay, Beaver? Well, he is, but the students call it a brass rat, and I'm third generation M i t. So it's just seen absolutely appropriate. That is a brass rods and capital is not a reference to money, but is actually referenced to the intellectual capital. They if you have five or six brass rats in the same company, you know, we Sometimes engineers arrive and they could do some things. >> And it Boy, if you put in some data data capital in there, you really explosions. We cause a few problems. So we're gonna talk about some new regulations that are coming down. New legislation that's coming down that you exposed me to yesterday, which is gonna have downstream implications. You get ahead of this stuff and understand it. You can really first of all, prepare, make sure you're in compliance, but then potentially take advantage for your business. So explain to us this notion of open government act. >> Um, in the last five years, six years or so, there's been an effort going on to increase the transparency across all levels of government. Okay, State, local and federal government. The first of federal government laws was called the the Open Data Act of 2014 and that was an act. They was acted unanimously by Congress and signed by Obama. They was taking the departments of the various agencies of the United States government and trying to roll up all the expenses into one kind of expense. This is where we spent our money and who got the money and doing that. That's what they were trying to do. >> Big picture type of thing. >> Yeah, big picture type thing. But unfortunately, it didn't work, okay? Because they forgot to include this odd word called mentalities. So the same departments meant the same thing. Data problem. They have a really big data problem. They still have it. So they're to G et o reports out criticizing how was done, and the government's gonna try and correct it. Then in earlier this year, there was another open government date act which said in it was signed by Trump. Now, this time you had, like, maybe 25 negative votes, but essentially otherwise passed Congress completely. I was called the Open as all capital O >> P E >> n Government Data act. Okay, and that's not been implemented yet. But there's live talking around this conference today in various Chief date officers are talking about this requirement that every single non intelligence defense, you know, vital protection of the people type stuff all the like, um, interior, treasury, transportation, those type of systems. If you produce a report these days, which is machine, I mean human readable. You must now in two years or three years. I forget the exact invitation date. Have it also be machine readable. Now, some people think machine riddle mil means like pdf formats, but no, >> In fact, what the government did is it >> said it must be machine readable. So you must be able to get into the reports, and you have to be able to extract out the information and attach it to the tree of knowledge. Okay, so we're all of sudden having context like they're currently machine readable, Quote unquote, easy reports. But you can get into those SEC reports. You pull out the net net income information and says its net income, but you don't know what it attaches to on the tree of knowledge. So, um, we are helping the government in some sense able, machine readable type reporting that weaken, do machine to machine without people being involved. >> Would you say the tree of knowledge You're talking about the constant >> man tick semantic tree of knowledge so that, you know, we all come from one concept like the human is example of a living thing living beast, a living Beeston example Living thing. So it also goes back, and they're serving as you get farther and farther out the tree, there's more distance or semantic distance, but you can attach it back to concept so you can attach context to the various data. Is this essentially metadata? That's what people call it. But if I would go over see sale here at M I t, they would turn around. They call it the Tree of Knowledge or semantic data. Okay, it's referred to his semantic dated, So you are passing not only the data itself, but the context that >> goes along with the data. Okay, how does this relate to the financial transparency? >> Well, Financial Transparency Act was introduced by representative Issa, who's a Republican out of California. He's run the government Affairs Committee in the House. He retired from Congress this past November, but in 2017 he introduced what's got referred to his H R 15 30 Um, and the 15 30 is going to dramatically change the way, um, financial regulators work in the United States. Um, it is about it was about to be introduced two weeks ago when the labor of digital currency stuff came up. So it's been delayed a little bit because they're trying to add some of the digital currency legislation to that law. >> A front run that Well, >> I don't know exactly what the remember soul coming out of Maxine Waters Committee. So the staff is working on a bunch of different things at once. But, um, we own g was asked to consult with them on looking at the 15 30 act and saying, How would we improve quote unquote, given our technical, you know, not doing policy. We just don't have the technical aspects of the act. How would we want to see it improved? So one of the things we have advised is that for the first time in the United States codes history, they're gonna include interesting term called ontology. You know what intelligence? Well, everyone gets scared by the word. And when I read run into people, they say, Are you a doctor? I said, no, no, no. I'm just a date. A guy. Um, but an intolerant tea is like a taxonomy, but it had order has important, and an ontology allows you to do it is ah, kinda, you know, giving some context of linking something to something else. And so you're able Thio give Maur information with an intolerant that you're able to you with a tax on it. >> Okay, so it's a taxonomy on steroids? >> Yes, exactly what? More flexible, >> Yes, but it's critically important for artificial intelligence machine warning because if I can give them until ology of sort of how it goes up and down the semantics, I can turn around, do a I and machine learning problems on the >> order of 100 >> 1000 even 10,000 times faster. And it has context. It has contacts in just having a little bit of context speeds up these problems so dramatically so and it is that what enables the machine to machine? New notion? No, the machine to machine is coming in with son called SP R M just standard business report model. It's a OMG sophistication of way of allowing the computers or machines, as we call them these days to get into a standard business report. Okay, so let's say you're ah drug company. You have thio certify you >> drugged you manufactured in India, get United States safely. Okay, you have various >> reporting requirements on the way. You've got to give extra easy the FDA et cetera that will always be a standard format. The SEC has a different format. FERC has a different format. Okay, so what s p r m does it allows it to describe in an intolerant he what's in the report? And then it also allows one to attach an ontology to the cells in the report. So if you like at a sec 10 Q 10 k report, you can attach a US gap taxonomy or ontology to it and say, OK, net income annual. That's part of the income statement. You should never see that in a balance sheet type item. You know his example? Okay. Or you can for the first time by having that context you can say are solid problem, which suggested that you can file these machine readable reports that air wrong. So they believe or not, There were about 50 cases in the last 10 years where SEC reports have been filed where the assets don't equal total liabilities, plus cheryl equity, you know, just they didn't add >> up. So this to, >> you know, to entry accounting doesn't work. >> Okay, so so you could have the machines go and check scale. Hey, we got a problem We've >> got a problem here, and you don't have to get humans evolved. So we're gonna, um uh, Holland in Australia or two leaders ahead of the United States. In this area, they seem dramatic pickups. I mean, Holland's reporting something on the order of 90%. Pick up Australia's reporting 60% pickup. >> We say pick up. You're talking about pickup of errors. No efficiency, productivity, productivity. Okay, >> you're taking people out of the whole cycle. It's dramatic. >> Okay, now what's the OMG is rolling on the hoof. Explain the OMG >> Object Management Group. I'm not speaking on behalf of them. It's a membership run organization. You remember? I am a >> member of cold. >> I'm a khalid of it. But I don't represent omg. It's the membership has to collectively vote that this is what we think. Okay, so I can't speak on them, right? I have a pretty significant role with them. I run on behalf of OMG something called the Federated Enterprise Risk Management Group. That's the group which is focusing on risk management for large entities like the federal government's Veterans Affairs or Department offense upstairs. I think talking right now is the Chief date Officer for transportation. OK, that's a large organization, which they, they're instructed by own be at the, um, chief financial officer level. The one number one thing to do for the government is to get an effective enterprise worst management model going in the government agencies. And so they come to own G let just like NIST or just like DARPA does from the defense or intelligence side, saying we need to have standards in this area. So not only can we talk thio you effectively, but we can talk with our industry partners effectively on space. Programs are on retail, on medical programs, on finance programs, and so they're at OMG. There are two significant financial programs, or Sanders, that exist once called figgy financial instrument global identifier, which is a way of identifying a swap. Its way of identifying a security does not have to be used for a que ce it, but a worldwide. You can identify that you know, IBM stock did trade in Tokyo, so it's a different identifier has different, you know, the liberals against the one trading New York. Okay, so those air called figgy identifiers them. There are attributes associated with that security or that beast the being identified, which is generally comes out of 50 which is the financial industry business ontology. So you know, it says for a corporate bond, it has coupon maturity, semi annual payment, bullets. You know, it is an example. So that gives you all the information that you would need to go through to the calculation, assuming you could have a calculation routine to do it, then you need thio. Then turn around and set up your well. Call your environment. You know where Ford Yield Curves are with mortgage backed securities or any portable call. Will bond sort of probabilistic lee run their numbers many times and come up with effective duration? Um, And then you do your Vader's analytics. No aggregating the portfolio and looking at Shortfalls versus your funding. Or however you're doing risk management and then finally do reporting, which is where the standardized business reporting model comes in. So that kind of the five parts of doing a full enterprise risk model and Alex So what >> does >> this mean for first? Well, who does his impact on? What does it mean for organizations? >> Well, it's gonna change the world for basically everyone because it's like doing a clue ends of a software upgrade. Conversion one's version two point. Oh, and you know how software upgrades Everyone hates and it hurts because everyone's gonna have to now start using the same standard ontology. And, of course, that Sarah Ontology No one completely agrees with the regulators have agreed to it. The and the ultimate controlling authority in this thing is going to be F sock, which is the Dodd frank mandated response to not ever having another chart. So the secretary of Treasury heads it. It's Ah, I forget it's the, uh, federal systemic oversight committee or something like that. All eight regulators report into it. And, oh, if our stands is being the adviser Teff sock for all the analytics, what these laws were doing, you're getting over farm or more power to turn around and look at how we're going to find data across the three so we can come up consistent analytics and we can therefore hopefully take one day. Like Goldman, Sachs is pre payment model on mortgages. Apply it to Citibank Portfolio so we can look at consistency of analytics as well. It is only apply to regulated businesses. It's gonna apply to regulated financial businesses. Okay, so it's gonna capture all your mutual funds, is gonna capture all your investment adviser is gonna catch her. Most of your insurance companies through the medical air side, it's gonna capture all your commercial banks is gonna capture most of you community banks. Okay, Not all of them, because some of they're so small, they're not regularly on a federal basis. The one regulator which is being skipped at this point, is the National Association Insurance Commissioners. But they're apparently coming along as well. Independent federal legislation. Remember, they're regulated on the state level, not regularly on the federal level. But they've kind of realized where the ball's going and, >> well, let's make life better or simply more complex. >> It's going to make life horrible at first, but we're gonna take out incredible efficiency gains, probably after the first time you get it done. Okay, is gonna be the problem of getting it done to everyone agreeing. We use the same definitions >> of the same data. Who gets the efficiency gains? The regulators, The companies are both >> all everyone. Can you imagine that? You know Ah, Goldman Sachs earnings report comes out. You're an analyst. Looking at How do I know what Goldman? Good or bad? You have your own equity model. You just give the model to the semantic worksheet and all turn around. Say, Oh, those numbers are all good. This is what expected. Did it? Did it? Didn't you? Haven't. You could do that. There are examples of companies here in the United States where they used to have, um, competitive analysis. Okay. They would be taking somewhere on the order of 600 to 7. How 100 man hours to do the competitive analysis by having an available electronically, they cut those 600 hours down to five to do a competitive analysis. Okay, that's an example of the type of productivity you're gonna see both on the investment side when you're doing analysis, but also on the regulatory site. Can you now imagine you get a regulatory reports say, Oh, there's they're out of their way out of whack. I can tell you this fraud going on here because their numbers are too much in X y z. You know, you had to fudge numbers today, >> and so the securities analyst can spend Mme. Or his or her time looking forward, doing forecasts exactly analysis than having a look back and reconcile all this >> right? And you know, you hear it through this conference, for instance, something like 80 to 85% of the time of analysts to spend getting the data ready. >> You hear the same thing with data scientists, >> right? And so it's extent that we can helped define the data. We're going thio speed things up dramatically. But then what's really instinct to me, being an M I t engineer is that we have great possibilities. An A I I mean, really great possibilities. Right now, most of the A miles or pattern matching like you know, this idea using face shield technology that's just really doing patterns. You can do wonderful predictive analytics of a I and but we just need to give ah lot of the a m a. I am a I models the contact so they can run more quickly. OK, so we're going to see a world which is gonna found funny, But we're going to see a world. We talk about semantic analytics. Okay. Semantic analytics means I'm getting all the inputs for the analysis with context to each one of the variables. And when I and what comes out of it will be a variable results. But you also have semantics with it. So one in the future not too distant future. Where are we? We're in some of the national labs. Where are you doing it? You're doing pipelines of one model goes to next model goes the next mile. On it goes Next model. So you're gonna software pipelines, Believe or not, you get them running out of an Excel spreadsheet. You know, our modern Enhanced Excel spreadsheet, and that's where the future is gonna be. So you really? If you're gonna be really good in this business, you're gonna have to be able to use your brain. You have to understand what data means You're going to figure out what your modeling really means. What happens if we were, You know, normally for a lot of the stuff we do bell curves. Okay, well, that doesn't have to be the only distribution you could do fat tail. So if you did fat tail descriptions that a bell curve gets you much different results. Now, which one's better? I don't know, but, you know, and just using example >> to another cut in the data. So our view now talk about more about the tech behind this. He's mentioned a I What about math? Machine learning? Deep learning. Yeah, that's a color to that. >> Well, the tech behind it is, believe or not, some relatively old tech. There is a technology called rd F, which is kind of turned around for a long time. It's a science kind of, ah, machine learning, not machine wearing. I'm sorry. Machine code type. Fairly simplistic definitions. Lots of angle brackets and all this stuff there is a higher level. That was your distracted, I think put into standard in, like, 2000 for 2005. Called out. Well, two point. Oh, and it does a lot at a higher level. The same stuff that already f does. Okay, you could also create, um, believer, not your own special ways of a communicating and ontology just using XML. Okay, So, uh, x b r l is an enhanced version of XML, okay? And so some of these older technologies, quote unquote old 20 years old, are essentially gonna be driving a lot of this stuff. So you know you know Corbett, right? Corba? Is that what a maid omg you know, on the communication and press thing, do you realize that basically every single device in the world has a corpus standard at okay? Yeah, omg Standard isn't all your smartphones and all your computers. And and that's how they communicate. It turns out that a lot of this old stuff quote unquote, is so rigidly well defined. Well done that you can build modern stuff that takes us to the Mars based on these old standards. >> All right, we got to go. But I gotta give you the award for the most acronyms >> HR 15 30 fi G o m g s b r >> m fsoc tarp. Oh, fr already halfway. We knew that Owl XML ex brl corba, Which of course >> I do. But that's well done. Like thanks so much for coming. Everyone tried to have you. All right, keep it right there, everybody, We'll be back with our next guest from M i t cdo I Q right after this short, brief short message. Thank you

>> From our studios in the heart of Silicon Valley. HOLLOWAY ALTO, California It is a cube conversation >> high on Peter Birds and welcome to another cube conversation from our beautiful Palo Alto studios. One of the things that makes a cube so exciting as we get great guest from great companies coming on here and talking about some of their new products that they're trying to get in the marketplace of customers Khun Doom or with their technology. And we've got that today. Eric Herzog, cmon VP of worldwide storage channels that IBM storage. He's here to talk about some new things that IBM is doing that especially relevant to high performance, closer, more down market, branch oriented kinds of applications. Eric, welcome to the Cube. >> Thank you, Peter. Really appreciate. Very excited to be with Cuba's Always. >> All right, So what? Start Give us the quick business update and IBM, And let's talk about how that inform some of the new announcement. You >> sure? So two thousand eighteen was a great year for IBM storage. Lots of new introductions and portfolio continue with our multi cloudiness. Everything we've doing now for seven years, all about my multi cloud hybrid private, multiple public cloud providers would continue that mantra. You always something very interesting from a storage array system level perspective brought out extensive portfolio around Envy Me the newest high performance protocol, both inside of a storage array and connecting a storage rate into a network fabric for storage. >> Now let's talk about that. Envy me because envy Me has been associate ID a little bit more higher and stuff. Some of the new things you're doing are bringing envy me and related classes of technology flash to a new class of workload. New class of Hugh's case. Tell us about it. >> Absolutely so what we're doing is bringing out the >> brand new >> refresh store wise portfolio. We start with R V seven thousand, which has envy me both inside the array and support for envy him Over Fibre channel. We have our fifty one hundred just below that, also supporting Envy me in the storage system. We're bringing out a new version of our fifty thirty called the fifty thirty at the very entry space are fifty tenny. These solutions all deliver dramatic performance gains but incredible price discounts as well. For example, the fifty ten e is not only twice as fast as the older fifty ten, but it happens to be up to twenty five percent less expensive. More for the money. That's the key watchword in the store. Wai's family. >> So tell us a little bit more about the fifty Tenney. What kind of use you love talking about applications, workload? Use cases? What kinds of applications were close use cases Are we talking about? >> So we've done a couple things. So first of all, we're leading with all flash across the portfolio. Yes, we still sell hybrids and hard drive a ways, and we'LL still do that in the fifty Tenney, for example. So if you're using hard drive, raise backup in archive work loads. Of course. Now, when using all flash arrays in a smaller shop, it could be your primary storage. Herzog's Barn Grill. That might be the great way to go when you're thinking more of the broader enterprises. It's great for edge. So branches of a bank, all of the outlets of a retail location and even a core data center. Not every workload is even not every data set is even so. Certain things need more expensive arrays and other ways you can go with an entry product. Still deliver the availability, the reliability of the performance you need, but you don't need to spend the most amount of money and stories gives you. That breath gives you the right price point the right software, and it even gives you six nines of availability, which is only thirty one seconds of downtime in a full year on an entry product. That's incredible. >> Well, I would think that the fifty thirty he would be especially relevant for some of those scale at work loves. Tell us about that. >> So in the fifty thirty, we can scale out into two note cluster up to thirty two petabytes, but we start small. You could get it at twelve. Same thing two. Ex Performance. Up to thirty percent less money and all of the store West family comes with our award winning Spectrum Virtualized software, which delivers enterprise class data services. Such a snapshot replication data rest, encryption, tearing, migration, et cetera, et cetera, not only for IBM store wise portfolio, but actually could work with over four hundred fifty raise, most of which are not ours. Great value for the money. Great software and bring better performance at a lower price. The fifty thirty and the whole portfolio includes our spectrum virtually software family. >> Now that's important because as we think about that, the relationship between these and other IBM or other products in the portfolio and multi cloud I know there's some work that's being done there tell us a bit about some of the some of the new updates that you've made. How that spectrum family is becoming even more relevant in the multi club so >> well, when you look at the whole family, everything in the spectrum family has heavy clarification in a multi cloud environment. Let's take spectrum protect not new from an announcement perspective of what we're doing and what we're launching on what we're doing from a new perspective. But it's been ableto backup to the cloud for years. In fact, over three hundred fifty cloud providers use spectrum protect as the engine further back. Oppa's a service portfolio Spectrum virtualized Computer Club. But we also have spectrum virtualized for public cloud that allows you to do staff shot replication only for IBM arrays, but for competitive a raise out to a public loud and even supports a rhe air gapping with a snapshot so you don't have to worry about ransomware malware, that's all. With Spectrum Virtualized family are spectrum sale product can automatically tear to the cloud IBM clad object storage could go from on premise toe off premise. So the big thing we've done with all of our portfolio, the software and then the arrays that sit on it when the case of spectrum protect backup is make sure we can work with any and almost every single cloud in the industry. Whether it's a big cloud like IBM Cloud, Amazon or Microsoft or a small cloud provider, you may want to use a local cloud provider depending on where you're located, not use one of the big club fighters. We work with that cloud provider to, But you made >> some made some special for spectrum virtual eyes. I mean spectrum virtualized. You're adding a new brother to the portfolio >> so that spectrum virtualized Republic Cloud. We first brought it out on IBM Cloud only. It now supports a ws. We know customers multi cloud most end users and you guys have written about it extensively at Weeki Bond in the Cube and silicon angle. That and users will not use one public loud. They will have four, five, six different public clouds. So spectrum virtualized republic loud delivers to onsite arrays. All the capability spectrum virtualized for public cloud sits in a V m wear virtualized in stand station out of the public cloud provider. Giving all those enterprise class functionalities and allowing us to move data back and forth to IBM. Cloud allows to move data back and forth to an Amazon cloud not only first store wise but also for again over four hundred fifty Raise that aren't ours using the spectrum virtualized software. So that's a great edition. We had it for IBM Cloud now for Amazon. As Republican Stanley first brought it out last year. It will also be extended to more clouds in the future as well. >> So store rise gonna refresh nooooo spectrum virtualized for public cloud Also getting, you know, adding to the portfolio great stuff. How do you anticipate that customers are gonna respond? >> Well, we've already had a great response for those customers we talked to under a non disclosure agreement. Now we're public with this new portfolio. What's not to like? You get extensive software capably spectrum virtualized with our fifty one hundred store wise and are seven thousand stories. Now get thie Envy Me technology, which is white hot performance technology in the storage injury, except at a much lower price point that when our competitors are brought out. So he brought Andrea me high end technology into the entry price point space, which is great. And we also have a nice portfolio that gives you certain products. Accuse the court data center other pranks that you would use the edge like banking and all the locations or in retail. So you're not going to put the most expensive practice. But you have a great six nines of availability, extensive software, twice the performance, and I said up to twenty five percent or thirty percent less, depending on which of our products than the older product. Bigger, faster, better, cheaper. >> So, Eric, let me be one of first congratulate you thie IBM storage journey since you and Ed Assualt have shown up at IBM or come backto idea in some cases has it's been a great thing to watch. You really refreshed portfolio made some great strides and we're getting great feedback from customers about the effort. So congratulations. >> Great. Thank you. And the new store lives is the latest in that and look for more just like we did in two thousand eighteen. Refresh across the plug. There's more coming in the second half here in other elements of our portfolio. >> Great sea IBM back and relevant in storage World Eric Herds on CMO VP of worldwide store channels, IBM Storage Thanks once again for being on the Cube. >> Thank you, Peter on. >> I'm Peter Burroughs. Thanks for listening until next time. Thanks for participating in this cube conversation.

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Welcome back to the Cube here in Mosconi North at IBM. Think twenty nineteen. I'm stupid. And my CLO host for the segment is Day Volante. We have four days, a water wall. Coverage of this big show happened. Welcome back to the program. Jason McGee, who is an IBM fellow, and he's the vice president. CTO of Cloud Platform at IBM. Jason, Great to see a >> guy to have fair. >> All right, So, Jason, we spoke with you at Que Con Way. We're saying it's a slightly different audience. A little bit bigger here. Not as many hoodies and jeans and T shirts a little bit more of a business crowd were still talking about clouds. So let's talk about your kind of your role here at the show. What's gonna keep you busy all week? >> S o? I mean, obviously, cloud is a huge part of what's going on. I think talking a lot about both public and private, about hybrid and some are multi called management capabilities. You know, my role as the leader called Platform. I'm talking a lot about platform as a service and communities and containers in the studio and kind of all the new technologies that people are using to help build the next generation of applications. >> All right, so we've had a few interviews today already talk about some of the multi cloud pieces. We had Sandberg on alien talk about eternity. So first you're gonna help correct the things that he got >> anything. Gang >> and service measures have been a really hot conversation the last year or so SDO envoy and the like t talk to us about where IBM fits into this discussion of service meshes. >> Yeah, so you know, I think >> we've been on this kind of journey as an industry of last year's to build anew at platform on DH service meshes kind of fit the part of the problem, which is, How does everything talk to each other and how to actually control that and get visibility into it? You know, IBM has had a founding role in that project. My team at IBM and Google got together with the guys, a lift to create it. Theo, what I'm most excited about, I think a twenty nineteen is that's that technology is really transitioning into something people are using in production and their applications. It's becoming more of kind of the default stack that people are using Really helping them do security invisibility control over their applications? >> Yeah. What? One thing that I heard just from the community and wonder if you could tell me is, you know, is dio itself. The governance model is still not fully into CNC s. Yeah, I heard a little bit, hasn't he? On some envoy? Of course. Out there in the like. So, you know, where are we? What needs to happen to kind of >> move forward? Yeah, you're right. So we're not there quite yet. We're pushing hard to make that happen. Certainly. From an IBM perspective, we absolutely believe that CNC F is the right home for Osteo as you mentioned some of the pieces like Envoy or they're ready. You know, C N c f has done such a tremendous job over the last eighteen months. Really rallying all the core technologies that make up this new coordinate A platform that we're building on costo is no out there's one. Oh, it's been sure people are using it. You know, that last step needs to happen to get into the community. >> So I have to ask you So things move so fast in this world, you go back to the open stack days, and that was going to change the world. And then Dakar Containers. And then Cooper netease, usto I can't help but thinking, Okay, This isn't the end of the line. What's Jason? What's the underlying trend here that's going on in the coding world? Yeah, sure. I'll put it in, maybe in >> my own lens. Given my history, you nominal WebSphere app server guy. You know that in the first half of my career I built that Andi, >> I think the fundamental >> problem solving is actually exactly the same. It's like, how do you build a platform that's app developers focus on building their APS, and I'll focus on all the plumbing and the infrastructure for running those aps. We did that twenty years ago in Java with APP servers, and we're doing it now with cloud, and we're doing it on top of containers. Things like usto like, while they're important in their own right there really actually Mohr important because they're just part of this bigger puzzle that we're putting together. And I think for the average suffer developer, they shouldn't really have to care about. What part of this deal will part is is Cuban eighties. And which part is K native like all that needs to come together into a single platform that they can use to build their APS and run them security. Right? And and I think it's Seo is just recognizing that next piece. You know, I think we've all agreed on containers and communities. We all talk about it all the time, and it's tio Is that next layer I catalyze securing >> control things. Yeah. So you teed it up nicely because we want out. Developers just be able to worry about the application. So you mentioned K native. The whole server list trend is one where you know the idea, of course, is I shouldn't have to worry about the infrastructure layer it just be taking care of me. We've talked about it for pass for a number of years. There are various ways to do it. So at, uh, Cube Colin and we've been looking for about the last year. Now you know, Where does you No, Crew, Burnett, ease and surveillance. How do they fit together? And K Native looks to be a pieces. Toe bridge. Some of those barrels? Absolutely. Where are we and what? What? What's? What's IBM doing there? >> So I think >> you rightly say that they should fit together like they're all part of this continuum of how developers build APS. And, you know, if you look at server, less applications, you know, there's the servos to mention I'm personally not a big service terminology fan. I think they're Maura about event oriented computing. And how do you have a good model for event oriented systems today? With Cuba Netease, anise Teo, I think we've built the base platform, I think, with a native what we're doing is bringing server lists and also just kind of twelve factor applications into the fold in a more formal way on when we get all those pieces together and we integrate them. I think then developers really unleashed to just build their application, whatever way it makes the most sense for what they're doing. And some things like server lists of Anna Marie. And it's going to be easier. And some problems. Straight containers will be an easier way to do >> it. You know, you say you don't like survivalists you like event better a function. So so explain that to the audience, like Why? Why should we care? And why is that different? How is that different? Yeah, I think, for >> a couple things. First off, the idea of server lists applies much more broadly than just what we think of this kind of function based program. You know, like any system that does a good job of managing and masking the infrastructure below me, you could consider a surveillance system, right? So when you just say server Lis, it's kind of like secondhand for functions. I'd rather we just kind of say, functions because that's actually a different programming model where you kind of trigger off of events and you write a functional piece of code and the system takes care of those details. You could argue that caught foundries, a server list system in the sense that you just as a developer anyway, you just see if push your code and it just runs and its scales and it does whatever you need, right? So part of my mission, you know, part of what I look at a lot is how do we bring all these things together in a way that is easy for the developer to stay focused. It steals a great example. You know, one of things were announcing this week is managed osteo support as part of our community service. What does that really mean? It means the developer can use the capability Viste without worrying about How do I install in Rennes D'oh, which they don't really care about? They just really care about how they get value out of its capability. >> Yeah, that's one of the things that having watched all these crew Benetti system and the like is how many companies really need to understand how to build this and run that because can I just get it delivered to me as a service? And therefore that you know that whole you know what I want out of cloud? I want a simple model to be able to consume, Not necessarily. I want to build the stuff that's important to me and not the rest of you. >> And I think if you look at the industry, there's really, I think, kind of two dominant consumption models that have actually emerged for people really using these things, there's public cloud platforms you're delivering things as a service. And then there's kind of platform software stacks like open shifts like I've been called private, which take all of these pieces and bring them together. And I think for most developers, they'll consume in one of those two ways because they don't really want the task of how to assemble all these pieces together. >> Tio, go back to the service piece like what? One distinction I heard made is okay. If I can really scale it down to zero, if I don't need to make it, then that can be serve a list. But there there's alternatives coming out there like what K native has. If I want to run this in my own environment, it's not turbulence because I do need toe. It might be functions, but I need to manage this environment. The infrastructure is my responsibility, not some >> service provider, right? And I think if you'll get server list to me, I was personally, I always think of it in kind of two scenarios. There's like surveillance as ah program remodel in a technology and surveillance as a business model, right? As a consumption model for payment. I think this programming model parts applicable in lots of cases, including private clouds. And in Custer, the business model parties, I think, frankly, unique to public. I'll thing that says I can just pay for the milliseconds of CPU, Compute that amusing and nothing more. >> That's a good thing for consumers. For >> the consumer, it's actually good thing for cloud providers because it gives us a way Tio reuse our infrastructure and creative ways, Right? But I think first and foremost, we have to get Mohr adoption of it as a programming model that developers used to build their applications and do it combined with other things. Because I think most realistic APs aren't gonna all be cirrhosis or all B Cooper nineties. They're going to be something. >> Yeah, right. It's like everything else. It's it's you know, what percent into the applications? Will this takeover? We had this discussion with virtual ization. We've been having this discussion with cloud and certain list, of course, is is pretty early in that environment. K native did I hear is there's some announcement this week that IBM >> so Soak a native, obviously is a project is kind of much earlier in its maturation and something like Castillo is. But we're making that available as part of our Republican private cards as well, Really? So people can get started with the ideas of K native. They can have an easy way to get that environment stood up, and they can start building those applications on DSO. That's now something that, you know, we're kind of bringing out as we work in the community to actually mature the project itself. >> Excellent. One of the things everybody's, of course, keeping an eye on. I saw Arvin Christian talking about the clouds. Tragedy is how red hat fits into all this. So we know you can't talk about kind of post acquisition. But red hats involved in K native. They're involved in a lot of the >> services and developers you gotta be exciting for. Yeah, >> it is. And obviously, like, Look, we've been partners for many years, you know, in on the open source side of things. We've worked closely with Red Hat for a long time. We actually view the world in very similar ways. You know, like you said, we're working on a native together. We've been working on Open West Feather. We obviously work in Cuban eighties together. So personally, I'm pretty excited about them coming in IBM. Assuming that acquisition goes through, they, you know, they fit into our strategy really well. And I think we'll just kind of enhance what we've all been working to build. >> All right, Jason, what else? What's looking? You talk about the maturity of these solutions, give us, um, guide post for the people watching the industry that we should be looking at as twenty nineteen rolls through >> us. So I think there's a >> couple things that, you know, I think this unified application platform notion that we've been kind of touching on here, I think will really come into its own in twenty nineteen. And and I would really love to see people kind of embraced that idea that we don't need. Three container stacks were not tryingto build these seven things. You know, one of things I'm kind of excited about with a native is by bringing server lists and twelve factor into Cuba Netease. It allows each of those frameworks to be kind of the best they can be at their part of the problem space and not solved unrelated problems. You know, I looked at the kind of server less versus coop camps, you know, the purest. And both think all problems will be solved in their camp. Which means they tried to solve all problems. Like, how do I do state full systems and server, Wes. And how do I bring in storage and solve all these things that maybe containers is better at. So I think this unification that I see happening will allow us to have really high efficiency, twelve factor and surveillance in the context of Koob and will change how people are able to use these platforms. I think twenty nineteen is really about adoption of all of this stuff. You know, we still are really early, frankly, in the kind of container adoption landscape, and I think most people in the broader industry or just kind of getting their feet wet they all agree that they're all trying, but they're just starting, and he knows a lot of interesting work. >> Jason, are there any anything that air holding people back? Anything that you You know what? What do you see is some of the things that might help accelerate some of this adoption? >> Yeah, I think one of the things that's >> holding people back is just the diversity of options that exists in the cognitive space means you guys have all probably rising like the C in C F landscape chart. I've never seen so many icons on something in my life. That's really frightening for the average enterprise. To look at a picture like that and go like which of these things are going to be useful, which are going to exist in a year like how Doe, I bet, make that sort >> of those things. So I think that's actually >> help people back a lot. I think that kind of agreement around communities that happened in the last eighteen months or so was really liberating, for a lot of people have helped them kind of move forward there. I think if we can all agree on a few more pieces around this deal, reckon native like it'll really help kind of unlock people and get them trying actually doing it. And I don't think it's anything more than picking a project and starting. I think a lot of enterprises over analyze everything, and they just need to pick something and go and learn. And they'll >> so pick some narrow use case pick, pick an app, pick >> a use case and go do it right and you'll learn and you'll figure out how it works for you. And then you do the second and the fourth in the tenth. And before you know it, you're on your way. That's what we did at IBM ourselves, and you know, now we're running our whole entire public out on top of communities. >> Jason and any any warnings from that kind of experience that you trade to users? A CZ. They looked forward. >> Yeah, we had a >> lot of learnings from music. One is we could run a heck of a lot more diverse work less than we thought when we started. You know, we're running databases where any data warehouses, running machine learning. We're running Blockchain. We're running every kind of application you didn't think could ever work on containers on containers s so one of the lessons Wass. It's much more flexible than you think. It isthe right. The >> other thing is you >> really have to rethink everything. Like the way you do compliance, the way you do security, the way you monitor the system. Like all of those things I need to change because the underlying kind of container system enables you to solve them in such a powerful way. And so if you go into it just thinking, Oh, I'm just going to change this one part of how I do aps and the rest will change. I think you'll find in a year that you're changing the whole operating model around your environment. >> Well, Jason, rethink everything we're here at IBM. Thing up twenty nineteen. Thinks is always for catching up with Thanks for everything going on for David. Want a, um, stew? Minutemen got three more days of live coverage here for Mosconi North. If you hear, stop by and say hi or reach out to us on the interwebs. Thanks so much for watching the cues.

>> From Sand Hill Road in the heart of Silicon Valley, it's theCUBE. Presenting, the People First Network; insights from entrepreneurs and tech leaders. >> Hello everyone, we are here for CUBE conversation in San Francisco. I'm John Furrier with siliconANGLE media theCUBE. We are in San Francisco with John Zimmer, who is the co-founder of president of Lyft, the famous ride sharing company that's dominating the world and changing the game in transportation. We all use Lyft, we love it. John, great to see you here for this People First Network special conversation. Thanks for spending the time. >> Thanks for having me. >> I know you're super busy, you guys are growing, billions of dollars in raised capital. You guys are growing like a weed on a rocket ship. A lot of things happening. But, you know, it's interesting, you guys are not that old of a company and the growth has just been fantastic. So, as you continue to ride the wave here, there's a lot of lessons that you've learned. So, tell the story about how you guys got started. You and your co-founder have a great relationship, and this has been a part of the culture at Lyft. How did it all get started? >> Yeah, so I'll start with Logan, my co-founder. He grew up in L.A. surrounded by traffic and he hated that. And he wanted to find a better way to get around. So when he went to college, he went to UC Santa Barbara, he did not take his car. He rode the bus, he car pooled, he had friends with cars. And then he went to start a car sharing program before Zipcar was around on college campuses. He got the attention of the local transit board, he got elected as the youngest member ever on the transit board. And he fell in love with the promise of public transportation. Affortable, accessible transportation for everyone. But frustrated by the reality that it was dependent on tax money. So, he wanted to create a better solution and he started coding his own website, named Zimride, named after a trip he took to Zimbabwe, for long distance car pooling. My own journey was I was on the east coast. I did not know Logan, was in love with hospitality, making people happy through great service. So I went to Cornell Hotel School, I took a city planning course, and I saw that the most important hospitality experience we have in society today is the city itself, and yet unfortunately we've designed cities for cars, and not people. What I mean by that is most of our cities are paved over. There's roads, there's parking lots, and if you design a city instead for people, pedestrians, safe places to bike, and don't need people to own cars in order to get around, then you could have a much more durable place to live. So we came together in 2007 to work on Zimride. And then a few years later, in 2012, we launched Lyft. >> So this is a transportation problem, ultimately, to solve. But the itch you guys were scratching was just the need for transportation. You saw it as more of a convenience thing as well. The hospitality thing kind of comes together, boom, Lyft is born. Then you guys enter the market, and the transportation problems are still there, and then you have the growth of mobile, so sort of a perfect storm coming together. What is the biggest challenge and exciting things that you guys see in this transportation scheme? Is it it's antiquated and inadequate? Is it a technical thing? What are some of the challenges that you guys are exited about? >> Well I think the biggest thing is this fact that the American dream has almost become, or been, historically, synonymous with a car in every garage. And that everyone should own a car. And that was your sense of freedom. But the reality is not quite that. American families spend more on their car than they do on food. It's the second highest household expense. A new car costs, on average, an American family $9,000 per year to own and operate. And so, there's a lot of ingrained behaviors, and designs of cities so that it does cater to needing to own a car. So we're trying to break that down piece by piece and making progress. But we're about 1% of the way there. >> Yeah, it's a cultural change too. But I also want to get to that in a second about culture, both with Lyft and and into your audience, which is the cities and the environments you guys deploy in, but also the users. But the founding and the story of you guys growing is interesting, because startups are all about execution and culture. You've had an interesting relationship with your co-founder. And this is the secret sauce of startups. It's documented somewhat, but it's a people first mindset, where you get a good team early on, you kind of feel your way through those first couple of years. Talk about that relationship with the founders, because this is something that's important. It's not just a number on a cap table, it's a little more than that. Talk about the relationship. >> I mean Logan has become my best friend. We actually carpool to work, still. Almost every day. And we weren't friends prior. So, a lot of times you have friends that start a company together. We were two people that were incredibly passionate about our mission, which is to improve people's lives with the best transportation. So we shared this passion, we share this vision, and we're two completely different people. So our approaches were different. His approach is often product-oriented and my approach is often hospitality-oriented. And the fact is, for transportation, you need to combine those two pieces. So it worked out really well for us. So I think having a co-founder is a massive advantage, because you can have two different people and then you want to find the thing in common, which is the thing you're fighting for, within our case the mission. >> How did you guys work together to play off each other, to get that innovation spark. Because when you get into the ride sharing, certainly it's a brand new category, huge demand, and there's a lot of build up, a lot of things you've got to stand up for the business. At the same time, you also want to differentiate and be innovative. You're kind of a first mover, with Uber, these guys are out there too. You guys are building a business, and growing really fast. So, how do you guys nurture that innovation? How do you put a twist on it? How do you keep it alive, versus the blocking and tackling and standing up the basic business activities? >> Well I think because we, you know at the beginning, we created a new category. We're the first to do peer-to-peer ride sharing. Uber existed, but they were doing cabs and limos. And we said, that may work for 1% of the population, but we wanted to use this under-utilized asset, which is the car that's sitting in everyone's parking spot or garage. And so that DNA of innovation, that DNA of being the underdog, the challenger, has always been true to us, but also the people that we we've brought on and hired. People and the hiring is something that, over the last ten years, is probably the one activity we've spent the most time on. Because that's the best way to keep those values, keep that focus on vision. >> And certainly these days, people want to work for a company that has a purpose. And that has a mission. When you hear the word people first, what pops into your head? >> Obvious. It just feels, in everything I've tried to do as a person, whether that was studying- like hospitality is the business of people first. How do you give people a great service and a great experience. And so I think often times, when people think about technology, they think about the what, which is I made this phone, I made this device, or I made this app, when way more important to that, is the why. Why did you do that? Who are you doing that for? And so we try to start everything we do with the person we're trying to- you know our mission is to improve people's lives with the world's best transportation. It's not to build the worlds best transportation. >> So that's your why. I was talking about how you guys scaled to a world-class organization. You guys have build a world-class team, certainly got great investors, Floodgate, Mayfield and then the rest is all on the web. You guys raised a lot of money, but you can't just throw money at the problem, you have to have that foundation and culture. How do you scale up a world-class organization? What's the learnings, can you share your perspective? >> Yeah, so first having clarity on the mission, which we've talked about, but also having clarity on core values. So we have three core values that have been true for a very long time. So, one is to be yourself. It also sounds very simple, like people first, but a lot of corporate environments have made spaces where people aren't comfortable being themselves, where there's group think, where people don't feel comfortable bringing their full self, and therefore their most productive self, to work. So be yourself, respecting the diversity of our team, has been critical from the beginning. The second is uplift others. So we use that both internally and externally. Life's short, we spend a lot of our time working. We might as well enjoy what we're doing. Again, all these values are both the right thing to do, make for a better place to work, and lead to better productivity and business success. And the last is make it happen. That's pretty self explanatory. Be an owner, go out and take action and get stuff done. And so with those three simple core values, looking for amazing, talented people, who also care about our mision. People are mission oriented, people want to care about what they're working on. And if you're fortunate to have a choice where you work, what we've seen is that people will follow a mission. >> Yeah, it's totally true. I can see that in culture here. And I've also seen you guys got kind of a cool factor too in the way I've seen some of your activations out in the marketplace. You kind of got a cool factor going on as well. But I think what's interesting, and I want to get your reaction to this, I think this points to some of the cultural discussions, just recently during the elections I saw you guys really wanted to make an effort to help people to get to the polls. Here in California, the disasters of wildfires are really tragic. You guys are doing some work there. This speaks to the culture. You say, hey, Lyft's available, and you're helping people out. Talk about what that means to you and the team here, and the culture at Lyft. >> Yeah, at the end of the day, when we look back on the work we've done, we want to make sure it has improved people's lives. And when we see opportunities to take our ability to provide transportation that will benefit people in a meaningful way, whether it was, you know, in the last- not this most recent election, but in the last election, in the last presidential election, I believe it was about 15 million people listed transportation as a reason why they couldn't vote. >> They've got a way, hey! >> Yeah, let's solve that. We can. When you think about unfortunate natural disasters, if we can help people get to safety, or help a horrible situation, then we should do that. I think that's just a moral and civic responsibility. It allows us to be aware and proud of the solution we've created, and I think it keeps our team extremely motivated. >> And I think it's one of those intangibles in terms of the mission, changing the transportation industry sounds academic and corporate. But here, you're changing lives by one, the voting, and two, saving lives potentially, with the disasters. So, great job. Okay, so what I thought, let's talk about the growth okay. I had a great conversation with the CEO of Amazon Web Services, Andy Jassy, a few years ago, talking about the early days of AWS. You have to be misunderstood for a while, and get through that early on, if you're going to be successful, because most big things are misunderstood. He also made a point about the key learnings during the early days. When you're trying to do stuff, things going so fast, that there's learnings that come out of it. And if you can persevere through it, that sets the culture. Share a story around something that you guys have been through at Lyft, where you persevered through it. It might have been some scar tissue. It might have been you got a little bloody, a little dirty. But you got through it and you learned from it. You applied it, and changed the culture. >> Well I think there's two main ones that come to mind. So, you know, people may think Lyft, in the last five years, has really come out of nowhere, but Logan and I have been working together for eleven years. And the first idea was Zimride, was long distance car pooling. And we built a team of 20, 25 people, we got this to break even. That's actually the company that Mayfield invested in, or the product. But it didn't have product-market fit in a massive way. It wasn't a massive success. And then so we tried to reinvent ourselves five years later, and that was Lyft. And at this point, that was a crazy idea. To have people riding in what everyone thought of as a stranger's other vehicle. And so that was a reinvention, an acknowledgement that the first solution we created did not fully work in the way that we wanted it to. The second was about four to five years ago, we wake up and Uber raises three billion dollars. And we have a hundred million dollars in the bank and about five months left. And everyone said Lyft is done. There is no way that they can survive this, it's a winner take all market, Uber is way more aggressive. And we proved that wrong. By focusing and staying true to our values and to our mission. By having an incredible team. An amazing community of drivers providing great service to our customers, we've gone from the early days of single digit market share to nearly 40% market share, amidst that pressure and belief that we couldn't survive. >> Game's on. Either rally or fold, right? It's a cultural test really. What's your mindset around the capital market. I know, I've done a lot of startups myself, I know a lot of fellow entrepreneurs, and when you raise that money, and you guys had that product-market fit, post the first venture, where you got through that. Then you get lightning in a bottle, whoa, let's double down on this. I want to go back to the early stages when you were thinking about investment. Was there any cautions around VC, cause a lot of startups have that conversation. What was the narrative for you guys at that time? Hey, let's go to Mayfield, should we raise money, should we bootstrap and make it cashflow positive. What was your mindset as founders, at that time when you were doing the venture round? >> Well, I think we knew that we needed a certain amount of capital to get to a scale that was interesting to us. So, not every business needs as much capital. But for they type of transportation infrastructure that we wanted to change, the type of scale we wanted to get to, we knew that it was important to raise VC money. So, money that was substantial and also understood the level of risk we were taking. So, at that point, we were fortunate to have a firm like Mayfield believe in us. And what we were looking for was people that care about who we were, cared about our mission, and understood what it was like to be an entrepreneur and an operator, not just an investor. >> What's the rallying call now for the team as you guys look out a6nd continue to have this growth? Obviously you guys cleared the runway in a big way. And there's still a lot more work to do, the market's still early. You know, you think about transportation and the regulatory environment and how technology and policy are coming together. A lot of forces out there, you got some tailwinds and some headwinds. How do you guys look at the future? What's the next mountain you're going to climb? >> Yeah, so, we've now done a billion rides. Since inception. And we're focused on providing a full alternative to car ownership. So I don't think people grasp that. The idea is not to provide an alternative to a taxi, or a late ride home. It's to completely replace car ownership. And so, we are 1% of the way there. Those that are joining our team and our mission get to be there for the 99% rest of that. And at the same time, as we go towards the next billion rides, we want to stay focused and rally around the individual stories behind each ride. So, every single week, we have over ten million rides happening, where two people are coming together. They could be two people that helped each other have a better day. They could be a Democrat and a Republican sitting next to each other and finding common ground. And so to us, yes we have big milestones and big opportunities ahead, but also care about each ride that's happening on the platform. >> And the other thing I love about your background in hospitality is you're bringing an experience as well. Not just math, in terms of the bottom line numbers. There's a lot of people doing the math and saying hmm, should I have a car? But I got to ask you a question. So what you learned at school, Cornell great school, great Lacrosse team, great Ivy League school, they teach you the textbook, the old hospitality. This is a new era we're living in. What is happening in your world that they don't teach you in the textbook from a hospitality standpoint? As you look at the experience of ride sharing and transportation for users, what is different, what's the twist in hospitality that has not yet been written in the textbooks, that you're exploring or thinking about? >> I actually think the old basics are more important than ever. There's all this flashy technology and opportunity to do it at larger scale, and to use data, that's new. To use data in ways that help inform providing great service. But, the basics of human interaction, communication, and treating people with respect, can get you pretty far. >> And happy customers, right? Final question, I know you got to go, I appreciate your time. Share a story or something about Lyft that people might not know about. First of all, everyone knows about your brass, you guys are doing a great job out there with the market share. But tell a story about Lyft, or something a datapoint, anecdotal piece of information, that they might not know about, that they should know about. Share an inside story or factoid about Lyft, that people should know about that they might not know about. >> I think it's really deep, deep in the mission. That people may not understand what gets us out of bed in the morning. You know, every time I have a new hire orientation, I try to talk to every new hire that comes to the company and really emphasize the importance of every driver, every passenger. And I read a story about a driver and passenger that really helped each other. And don't really want to provide the details because they're private to those individuals, but it's incredibly powerful to hear about. And so, I would just, we may look like a big company or brand at this point, but we care deeply about each individual that's on the platform. >> The fabric of society is being changed by you guys, really appreciate the work you've done, and congratulations, and a lot more work to do. Thanks for the conversation. >> Yeah, thanks. >> I'm John Furrier, here in San Francisco at Lyft's headquarters, talking with John Zimmer, who's the co-founder and President of Lyft, sharing his stories and successes, and a lot more work to do here at the People First conversations. With theCUBE, and Mayfield, I'm John Furrier, thanks for watching. (outro music)

Silicon Valley, it's theCUBE covering People First Network. Brought to you by Mayfield. >> Hello, I'm John Furrier here in Palo Alto for an exclusive conversation, CUBE conversation, part of the People First Network with theCUBE and Mayfield fund. I'm here with John Chambers at his house in Palo Alto. John Chambers is the former CEO/Chairman of Cisco Systems, now running J2C, JC2 Ventures. Great to see you, thanks for spending time! >> It's a pleasure to be together again. >> I'm here for two reasons. One, I wanted a conversation about People First and technology waves, but also, I want to talk about your new book, which is exciting, called Connecting the Dots. And it's not your standard business book, where, you know, hey, rah-rah, you know, like a media post these days on the internet; it's some personal stories weaved in with the lessons you've learned through the interactions you've had with many people over the years, so exciting book and I'm looking forward to talking about that. >> Thank you! >> Again, John Chambers, legend, Cisco, 1991 when you joined the company from Wang before that. 400 employees, one product, 70 million in revenue. And when you retired in 2015, not so much retired, 'cos you've got some--. >> I'm working on my next chapter! >> You've got your next chapter (laughs)! 180 acquisitions, 447 billion in revenue, you made 10,000 people millionaires, you created a lot of value, probably one of the biggest inflection points in computer history, the evolution of inter-networking and tying systems together, it was probably one of the biggest waves somewhat before the wave we're on now. So an amazing journey, now you're running JC2 Ventures and investing in game-changing start-ups. So you're not retired? >> No. It was only my next chapter. I made my decision almost 10 years before I left Cisco first, to make for a very smooth transition because it's my family, and out of the 75,000 people, I hired all but 23 of them! And in terms of what I wanted to do next, I really wanted to both give back, create more jobs, get our start-up engine going again in this country, and it's currently broken, and I want to do that on a global basis, in places like France and India as well. So I'm on to my next chapter, but the fun part in this chapter is that I do the things that I love. >> And you've got a great team behind you, but also, you have a great personal network. And I want to get into that, of your personal stories as well as your social network in business and in the community; but one of the things I want to get up front, because I think this is important for this conversation is, you've been very strong. I've seen you present many times over the years, going way back into the 90's. You're eloquent, you're people-oriented, but you have a knack for finding the waves, seeing transitions, you've been through many waves. >> Yes I have, good and bad. >> Good and bad. But one of the big ones, how do you spot those transitions? And what wave are we in now? I mean, talk about the wave that's happening now, it's unprecedented on many levels, but, different, but it's still a wave. >> It is, and outgoing market transitions and often combined with either economic changes or business model changes with technology. And part of the reason that I've been fortunate to be able to identify many of them is I listen to customers very carefully, but also, you're often a product of your prior experiences. Having experienced West Virginia, one of the top states in the US in terms of the chemical industry, uh, during the 40's and 50's and 60's when I was growing up there, and literally more millionaires in West Virginia than there were in the entire Great Britain. We were on top of the world in the chemical industry, and the coal industry, and yet, because we missed transitions, and we should've seen them coming, the state fell a long way, so now we're trying to correct that with some of the start-up activity we'll talk about later. As you see this, and then I went to Boston, 128, we were talking earlier, Wang Laboratories, the mini-computer era, but I was in IBM first out of the central part of the nation, so I watched IBM and Mainframes, and then I watched them miss on going to the mini-computer, and then miss in terms of the internet. So I was able to see the transitions that occurred in Boston, Route 128, where we were the Silicon Valley of the world, and we knew it, and this unusual area out in California called Silicon Valley, we paid almost no attention to, and we didn't realize we failed to make a transition from the mini-computer era to the pc and the internet era. Then I joined Cisco, and saw the internet era. So part of it is, you're a product of your experiences, and know the tremendous pain that occurs, because Boston 128 is nowhere near what it used to be, so there's no entitlement in this new world out of the thousand high-tech companies that I was associated with, including four or five giants in mini-computers, none of them are really in existence today, so it shows you, if you don't identify the transitions, number one, you're going to have an opportunity to benefit by them, but number two, you sure have an opportunity to get hurt by them. >> And you know, these waves also create a lot of wealth and value; not just personal wealth, but community wealth, and Cisco in particular had a good thing going for them, you know, TCP-IP was a defact-- not even a standard, it was a defacto standard at that time, IBM and these kinds of digital equipment corporations dominated the network protocol. Even today, people are still trying to take out Cisco competitively, and they can't because they connected the world. Now the world's connected with digital, it's connected with mobile, so we're kind of seeing this connected wave globally. How do you think about that, now that you've seen the movie at the plumbing levels at Cisco, you now have been traveling the world, we're all connected. >> We are. And it's important to understand that I'm completely arms-length with Cisco, it's their company to run now, and I'm excited about their future. But I'm focused on the next chapter in my life, and while I think about the people at Cisco everyday, I'm into the start-up world now, so how do I think about it now? I think most of the innovation over the next decade will come from start-ups. The majority of the top engineering students, for example, at a Stanford or an MIT or a Polytechnique in France, which is the top engineering school, I think, in Europe, or at the ITs in India, they are all thinking about going to start-ups, which means this is where innovations going to come from. And if you think about a digital world going from the time you and I, we almost recruited you to Cisco, and then we finally did; there's only a thousand devices connected then when Cisco was founded. Today there are about 20 billion devices connected to the internet; in the future, it's going to be 500 billion in a decade, and so this concept of digitalization combined with artificial intelligence, all of a sudden we'll get the right information at the right time to the right person or machine to make the right decision, sounds complex, and it is. And it's ability to do that, I think start-ups are well-positioned to play a key role in, especially in innovation. So while the first stage of the internet, and before that were all dominated by the very large companies, I think you're going to see, in this next phase of digitalization, you're going to see a number of start-ups really emerge, in terms of the innovation leaders, and that's what I'm trying to do with my 16 investments I've made, but also coaching probably another 50 uh, start-ups around the world on a regular basis. >> And the impact of outside Silicon Valley, globally, how do you see that ecosystem developing with the entrepreneurship models that are now globally connected in with these connection points like Silicon Valley? >> It will partially in parallel, partially, it's a new phenomenon. I sold the movie of Boston 128, as I said earlier, and on top of the world, and there is no entitlement. The same thing's true with Cisco, um, sorry, of Silicon Valley today; there's no entitlement for the future, and just because we've led up until this point in time, doesn't mean we will in 10 years, so you can't take anything for granted. What you are seeing, since almost all job creation will be from start-ups, and small companies getting bigger, the large companies in total will probably not add any head count over this next decade because of artificial intelligence and digitization, and so you're now going to see job growth coming from those smaller companies, if these small companies don't get a forum to all 50 states, if they don't get a chance to grow their head count there, and the economic benefits of that, then we're going to leave whole states behind. So I think it's very important that we look at the next wave of innovation, I think there's a very good probability that it will be more inclusive, both by geography, by gender, and all diversity measures, and I'm optimistic about the future, but there are no guarantees, and we'll see how it plays out. >> Let's talk about your next chapter. I was going to wait, but I want to jump while we're on the topic. JC2 is a global start-up, game-changing start-up focus that you have. What is the thesis? What are you looking for, and talk about your mission? >> Well, our mission is very simple. I had a chance to change the world one time with Cisco, and many people, when I said Cisco's going to change the way the world works, lives, learns, and plays by enabling the internet, everybody said nice marketing, but you're a router company. And yet, I think most people would agree, probably more than any other company, we had the leadership role in changing the internet and the direction going on, and now, a chance to do it again, because I think the next wave of innovation will come from the start-ups, and it doesn't come easy. They need coaches, they need strategic partners, they need mentors as much as they need the venture capitalists, so I would think of as this focusing on disruptive start-ups that get very excited in these new areas of technology, ranging from physical and virtual worlds coming together, to artificial intelligence and automation everywhere, to the major capabilities on cyber security across that to the internet of things, so we're trying to say, how do we help these companies grow in skill? But if I was just after financial returns, I'd stay right here in the Valley. I can channel anybody, VC's here that I trust and they trust me, and it would be a better financial return. But I'm after, how do you do this across a number of states, already in seven states, and how do you do it in France and India as role models? >> It's got a lot of purpose. It's not just a financial purpose. I mean, entrepreneurs want to make money, too, but you've made some good money over the years, but this is a mission for you, this is a purpose. >> It is, but you referred to it in your opening comments. When we were at Cisco, I've always believed that the most successful owe an obligation to give back, and we did. We won almost every corporate social responsibility award there was. We won it from the Democrats and the Republicans, from Condie Rice and George Bush and from Hillary Clinton and President Obama. We also, as you said, made 10,000 Cisco employees millionaires just in the first decade. And we tried to give back to society with training programs like Network Academies and trained seven million students. And I think it's very important for the next generation of leaders here in the Valley to be good at giving back. And it's something that I think they owe an obligation to do, and I think we're in danger now of not doing it as well as we should, and for my start-ups, I try to pick young CEOs that understand, they want to make a financial return, and they want to get a great product out of this, but they also want to be fair and giving back to society and make it a win-win, if you will. >> And I think that's key. Mission-driven companies are attracting the best talent, too, these days, because people are more cognizant of that. I want to get into some of your personal stories. You mentioned giving back. And reading your book, your parents have had a big role in your life--. >> Yes, they have. >> And being in West Virginia has had a big role in your life. You mentioned it having a prosperity environment, and then missing that transition. Talk about the story of West Virginia and the role your parents played, because, they were doctors, so they were in the medical field. The combination of those two things, the culture where you were brought up, and your family impacted your career. >> I'm very proud of being from West Virginia, and very proud of the people in West Virginia, and you see it as you travel around the world. All of us who, whether we're in West Virginia, or came out of it, care about the state a great deal. The people are just plain good people, and I think they care about treating people with respect. If I were ever run off a road at night in the middle of the night, I'd want to be in West Virginia, (both laugh) when I go up to knock on that door. And I think it carries through. And also, the image of our state is one that people tend to identify in terms of a area that you like the people. Now what I'm trying to do in West Virginia, and what we just announced since last week, was to take the same model we did on doing acquisitions, 180 of them, and say here's the playbook, the innovation playbook for doing acquisitions better than anyone else, and take the model that we did on country digitization, which we did in Israel and France and India with the very top leaders, with Netanyahu and Shimon Peres in Israel, with Macron in France and with Modi in India, and drove it through, and then do the same thing in terms of how we take the tremendous prosperity and growth that you see in Silicon Valley, and make it more uniform across the country, especially as traditional business won't be adding head count. And while I'd like to tell you the chemical industry will come back to West Virginia and mining industry will come back in terms of job creation, they probably won't, a lot of that will be automated in the future. And so it is the ability to get a generation of start-ups, and do it in a unique way! And the hub of this has to be the university. They have to set the pace. Gordon Gee, the President there, gets this. He's created a start-up mentality across the university. The Dean of the business school, Javier Reyes is going across all of the university, in terms of how you do start-ups together with business school, with engineering, with computer science, with med school, et cetera. And then how do you attract students who will want to really be a part of this, how do you bring in venture capital, how do you get the Governor and the President and the Senate and the Speaker of the House on board? How do you get our two national senators, Shelly Moore Capito and also Joe Manchin, a Democrat and a Republican working together on common goals? And then how do you say here's what's possible, write the press release, be the model for how a country, or a state, comes from behind and that at one time, then a slow faller, how do we leap frog? And before you say it can't be done, that was exactly what people said first about India, when I said India would be the strongest growing economy in the world, and it is today, probably going to grow another seven to 10%. That means you double the per capita of everyone in India, done right, every seven to 10 years. And France being the innovation engine in Europe to place your new business, you and I would have said John, no way, just five years ago, yet it has become the start-up engine for Europe. >> It's interesting, you mentioned playbook, and I always see people try to replicate Silicon Valley. I moved out here from the East Coast in 1999, and it's almost magical here, it's hard to replicate, but you can reproduce some things. One of the common threads, though, is education. The role of education in the ecosystem of these new environments seems to be a key ingredient. Your thoughts about how education's going to play a role in these ecosystems, because education and grit, and entrepreneurial zeal, are kind of the magic formula. >> Well they are in many ways. It's about leadership, it's about the education foundation, it's about getting the best and brightest into your companies, and then having the ability to dream, and role models you can learn from. We were talking about Hewlett-Packard earlier, a great role model of a company that did the original start-up and Lou Platt, who was the President of HP when I came out here, I called him up and said, you don't know me, Lou, I'm with a company you've probably never heard of, and we have 400 people, but I don't know the Valley, can you teach me? And he did, and he met with me every quarter for three years, and then when I said what can I do to repay you back, because at that time, Cisco was on a roll, he said John, do it for the next generation. And so, that's what I'm trying to do, in terms of, you've got to have role models that you can learn from and can help you through this. The education's a huge part. At the core of almost all great start-up engines is a really world-class university. Not just with really smart students, but also with an entrepreneur skill and the ability to really create start-ups. John Hennessey, Stanford did an amazing thing over the last 17 years on how to create that here at Stanford, the best in the world, probably 40% of the companies, when I was with Cisco, we bought were direct or indirect outgrowth of Stanford. Draw a parallel. Mercury just across the way, and this isn't a Stanford/CAL issue, (both laugh) equally great students, very good focus on interdisciplinary activities, but I didn't buy a single company out of there. You did not see the start-ups grow with anywhere near the speed, and that was four times the number of students. This goes back to the educational institution, it has to have a focus on start-ups, it has to say how they drive it through, this is what MIT did in Boston, and then lost it when 128 lost it's opportunity, and this is what we're trying to do at West Virginia. Make a start-up engine where you've got a President, Gordon Gee, who really wants to drive this through, bring the political leaders in the state, and bring the Mountaineers, the global Mountaineers to bare, and then bring financial resources, and then do it differently. So to your point, people try to mimic Silicon Valley, but they do it in silos. What made Silicon Valley go was an ecosystem, an education system, a environment for risk-taking, role models that you could steal people from--. >> And unwritten rules, too. They had these unwritten rules like pay it forward, your experience with Lou Platt, Steve Jobs talks about his relationship with David Packard, and this goes on and on and on. This is an important part. Because I want to just--. >> Debt for good is a big, big issue. Last comment on education, it's important for this country to know, our K through 12 system is broken. We're non-competitive. People talk about STEM, and that's important, but if I were only educating people in three things, entrepreneurship, how to use technology, and artificial intelligence; I would build that into the curriculum where we lose a lot of our diversity, especially among females in the third, fourth, fifth grade, so you haveta really, I think, get people excited about this at a much earlier age. If we can become an innovation engine again, in this country, we are not today. We're not number one in innovation, we're number 11! Imagine that for America? >> I totally agree with ya! And I don't want to rant and waste a lot of time, but my rants are all on Facebook and Twitter. (both laugh) Education's a problem. It's like linear, it's like a slow linear train wreck, in my opinion, but now you have that skills gaps, you mentioned AI. So AI and community are two hot trends right now. I'm going to stay with community for a minute. You mentioned paying it forward. Open source software, these new forms of operational scale, cloud computing, open source software, that all have this ethos of pay it forward; community. And now, community is more important than ever. Not just from the tech world, but you're talking about in West Virginia, now on a global scale. How does the tech industry, how can the tech industry, in your opinion, nurture community at local, regional, global scale? >> This is a tough one John, and I'd probably answer it more carefully if I was still involved directly with Cisco. But the fun thing is, now I represent myself. >> In your own opinion, not Cisco. There's a cultural thing. This is, Silicon Valley has magic here, and community is part of it. >> Yes, well it's more basic than that. I think, basically, we were known for two decades, not just Cisco, but all of the Valley as tech for good, and we gave back to the communities, and we paid it forward all the time, and I use the example of Cisco winning the awards, but so do many of our peers. We're going to Palestine and helping to rebuild Palestine in terms of creating jobs, et cetera. We went in with the Intels of the world, and the Oracles and the other players and HP together, even though at times we might compete. I think today, it's not a given. I think there is a tug of war going on here, in terms of what is the underlying purpose of the Valley. Is it primarily to have major economic benefits, and a little bit of arm's length from the average citizen from government, or is it do well financially, but also do very well in giving back and making it inclusive. That tug of war is not a given. When you travel throughout the US, today, or around the world, there are almost as many people that view tech for bad as they do tech for good, so I think it's going to be interesting to watch how this plays out. And I do think there are almost competing forces here in the Valley about which way should that go and why. The good news is, I think we'll eventually get it right. The bad news is, it's 50/50 right now. >> Let's talk about the skill gap. A lot of leaders in companies right now are looking at a work force that needs to be leveled up, and as new jobs are coming online that haven't been trained for, these openings they don't have skills for because they haven't been taught. AI is one example, IOT you mentioned a few of those. How do great leaders, proactively and reactively, too, get the skills gaps closed? What strategies can you do, what's the playbook there? >> Well two separate issues. How do they get it closed, in terms of their employees, and second issue, how do we train dramatically better than we've done before? Let's go to the first one. In terms of the companies, I think that your ability to track the millennials, the young people, is based upon your vision of doing more than quote just making a profit, and you want to be an exciting place to work with a great culture, and part of that culture should be giving back. Having said that, however, the majority of the young people today, and I'm talking about the tops out of the key engineering schools, et cetera, they want to go to start-ups. So what you're going to see is, how well established companies work with start-ups, in a unique partnership, is going to be one of the textbook opportunities for the future, because most companies, just like they didn't know how to acquire tech companies and most of all tech acquisitions failed, even through today. We wrote the textbook on how to do it differently. I think how these companies work with start-ups and how they create a strategic relationship with a company they know has at least a 50/50 probability of going out of business. And how do you create that working relationship so that you can tap into these young innovative ideas and partnerships, and so, what you see with the Spark Cognition, 200 people out of Texas, brilliant, brilliant CEO there in terms of what he is focused on, partnering with Boeing in that 50/50 joint venture, 50/50 joint venture to do the next FAA architecture for unmanned aircraft in this country. So you're going to see these companies relate to these start-ups in ways they haven't done before. >> Partnership and collaboration and acquisitions are still rampant on the horizon, certainly as a success for you. Recently in the tech industry we're seeing big acquisitions, Dell, EMC, IBM bought Red Hat, and there's some software ones out there. One was just going public and got bought, just recently, by SAP, how do you do the acqui-- you've done 180 of them? How do you do them successfully without losing the innovation and losing the people before they invest and leave; and this is a key dynamic, how do companies maintain innovation in an era of collaboration, partnerships, and enmity? >> I had that discussion this morning at Techonomy with David Kirkpatrick, and David said how do you do this. And then as I walked out of the room, I had a chance to talk with other people and one of them from one of the very largest technology companies said, John, we've watched you do this again and again; we assumed that when we acquired a company, we'd get them to adjust to our culture and it almost never worked, and we lost the people at a tremendously fast pace, especially after their lock-in of 18 to 24 months came up. We did the reverse. What we did was develop a replicatible innovation playbook, and I talk about it in that book, but we did this for almost everything we did at Cisco, and I would've originally called that, bureaucracy, John. (both laugh) I would've said that's what slow companies do. And actually, if done right, allows you to move with tremendous speed and agility, and so we'd outline what we'd look for in terms of strategy and vision; if our cultures weren't the same, we didn't acquire them. And if we couldn't keep the people, to generate the next generation of product, that was a bad financial decision for us, as well. So our attrition rate averaged probably about 5% or over while I was at Cisco for 20 years. Our voluntary attrition rate of our acquired companies, which normally runs 20% in these companies, we had about four. So we kept the people, we got the next generation product out, and we went in with that attitude in terms of you're acquiring to be able to keep the people and make them a part of your family and culture. And I realize that that might sound corny today, but I disagree. I think to attract people, to get them to stay at your company, it is like a family, it is like how you succeed and occasionally lose together, and how you build that family attitude under every employee, spouse, or their children that was life-threatening, and we were there for them in the ways that others were not. So you're there when your employees have a crisis, or your customer does, and that's how you form trust in relationships. >> And here's the question, what does People First mean to you? >> Well people first is our customer first. It means your action and everything you do puts your customers and your people first, that's what we did at Cisco. Any customer you would talk to, almost every customer I've ever met in my life would do business with us again, or with me again, because your currency in today's world is trust, track record, and relationships, and we built that very deep. Same thing with the employees. I still get many, many notes from people we helped 10 or 15 years ago; here's the picture of my child that you all helped make a difference in, Cisco and John, and you were there for us when we needed you most. And then in customers. It surprises you, when you help them through a crisis, they remember that more than when you helped them be successful, and they're there for you. >> Talk about failure and successes. You talk about this in the book. This is part of entrepreneurship, you can't succeed without failures. Handling failures is just as important as handling successes, your thoughts on people should think about that from a mindset standpoint? >> Well, you know, what's fun is those of you who are parents, or who will be parents in the future, when your child scores a goal in soccer or makes a good grade on a test, you're proud for them, but that isn't what worries you. What worries you is when they have their inevitable setbacks, everybody has that in life. How do you learn to deal with them? How do you understand how much were self-inflicted and how much of it was done by other causes, and how they navigate through that determines who they are. Point back to the West Virginia roots, I'm dyslexic, which means that I read backwards. Some people in early grade school thought I might not even graduate from high school much less go to college. My parents were doctors, they got it, but how I handled that was key. And while I write in the book about our successes, I spend as much time on when disaster strikes, how you handle that determines who you are in the future. Jack Welch told me in the 90's, he said John, you have a very good company, and I said Jack, you're good at teaching me something there, we're about to become the most valuable company in the world, we've won all of the leadership awards and everything else, what does it take to have a great company? He said a near-death experience. At the time I didn't understand it. At the end of 2001 after the dot com bubble, he called me up, he said, you now have a great company, I said Jack, it doesn't feel like it. Our stock price is down dramatically, people are questioning can I even run the company now, many of the people who were so positive turned very tough and--. >> How did you handle that? How did you personally handle that, 'cos--. >> It's a part of leadership. It's easy to be a leader when everything goes well, it's how you handle when things are tough, and leadership is lonely, you're by yourself. No matter how many friends you have around you, it's about leadership, and so you'd lead it through it. So 2001, took a real hard look, we made the mistake of focusing, me, on the numbers, and my numbers in the first week of December were growing at 70% year over year. We'd never had anything negative to speak of, much less below even 30% growth, and by the middle of January, we were -30%. And so you have to be realistic, how much was self-inflicted, how much the market, I felt the majority of it was market-inflicted, I said at the time it's a hundred year flood. I said to the employees, here's how we're going to go forward, we need to bring our head count back in line to a new reality, and we did it in 51 days. And then you paint the picture from the very beginning of what you look like as you recover and in the future and why your employees want to stay here, your customers stay with you and your shareholders. It wiped out most of our competitors. Jack Welch said, John, this is probably your best leadership year ever, and I said Jack, you're the only one that's going to say that. He said probably, and he has been. >> And you've got the scar tissue to prove it. And I love this story. >> But you're a product of your scars. And do you learn how to deal with them? >> Yeah, and how you-- and be proud of them, it's what, who you are. >> I don't know if proud's the right word. >> Well, badge of honor. (both laugh) >> Red badge of honor, they're painful! >> Just don't do it again twice, right? >> We still make the same mistake twice, but at the same time when I teach all these start-ups, I expect you to make mistakes. If you don't make mistakes, you're not taking enough risk. And while people might've, might say John, one of your criticisms is that you spread yourself a little bit too thin in the company at times, and you were too aggressive. After thinking about it, I respectfully disagree. If I had to do it over, I'd be even bolder, and more aggressive, and take more risks, and I would dream bigger dreams. With these start-ups, that's what I'm teaching them, that's what I'm doing myself. >> And you know, this is such a big point, because the risk is key. Managing risk is actually, you want to be as risky as possible, just don't cut an artery, you know, do the right things. But in your book, you mention this about how you identify transitions, but also you made the reference to your parents again. This is, I think, important to bring up, because we have an expression in our company: let's put the patient on the table and let's look at the problem. Solving the problems and not going out of business at that time, but your competitors did, you had to look at this holistically, and in the book, you mentioned that experience your parents taught you, being from West Virginia, that it changed how you do problem solving. Can you share what that, with that in conscience? >> Well, both parents were doctors, and the good news is, you got a lot of help, the bad news is, you didn't get a lot of self 'cos they'd fix you. But they always taught me to focus on the real, underlying issue, to your point. What is the real issue, not what the symptom is, the temperature, or something else. And then you want to determine how much of that was self-inflicted, and how much of it was market, and if your strategy's working before, continue, if your strategy was starting to get long in the tooth, how do you change it, and then you got to have the courage to reinvent yourself again and again. And so they taught me how to deal with that. I start off the book by talking about how I almost drowned at six years of age, and as I got pulled down through the rapids, I could still see my dad in my mind today running down the side of the river yelling hold on to the fishing pole. It was an ugly fishing pole. Might've cost $5. But he was concerned about the fishing pole, so therefore I obviously couldn't be drowning so I focused both hands on the fishing pole and as I poked my head above water, I could still see him running down. He got way down river, swam out, pulled me in, set me on the side, and taught me about how you deal when you find yourself with major setbacks. How do you not panic, how do you not try to swim against the tide or the current, how you be realistic of the situation that you're in, work your way to the side, and then you know what he did? He put me right back in the rapids and let me do it myself. And taught me how to deal with it. Dad taught me the business picture and how you deal with challenges, Mom, uh, who was internal medicine, psychiatry, taught me the emotional IQ side of the house, in terms of how you connect with people, and I believe, this whole chapter, I build relationships for life. And I really mean it. I think your currency is trust, relationships, and track record. >> And having that holistic picture to pull back and understand what to focus on, and this is a challenge for entrepreneurs. You're now dealing with a lot of entrepreneurs and coaching them; a lot of times they get caught in the forest and miss the trees, right? Or have board meetings or have, worry about the wrong metrics, or hey, I got to get financing. How should an entrepreneur, or even a business leader, let's talk about entrepreneur first and then business leader, handle their advisors, their investors, how do they manage that, how do they tap into that? A lot of people say, ah, they don't add much value, I just need money. This is important, because this could save them, this could be the pole for them. >> It could, or it could also be the pole that causes the tent to collapse (both laugh). So I think the first thing when you advise young entrepreneurs, is realize you're an advisor, not a part of management. And I only take young entrepreneurs who want to be coached. And as I advise them, I say all I'm asking is that you listen to my thoughts and then you make the decision, and I'll support you either way you go, once you've listened to the trade-offs. And I think you want to very quickly realize where they are in vision and strategy, and where they are on building the right team and evolving the team and changing the team, where they are in culture, and where they are on their communication skills because communication skills were important to me, they might not have been to Jack Welch, the generation in front of me, but they were extremely important to ours. And today, your communication mismatch on social media could cost your company a billion dollars. If you're not good at listening, if you're not good at communicating with people and painting the picture, you've got a problem. So how do you teach that to the young players? Then most importantly, regardless of whether you're in a big company or a small company, public or private sector, you know what you know and know what you don't. Many people who, especially if they're really good in one area, assume that carries over to others, and assume they'll be equally as good in the others, that's huge mistake; it's like an engineer hiring a good sales lead, very rarely does it happen. They recruit business development people who appeals to an engineer, not the customer. (both laugh) So, know what you know, know what you don't. For those things you don't know, surround yourself with those people in your leadership team and with your advisors to help you navigate through that. And I had, during my career, through three companies, I always had a number of advisors, formal and informal, that I went to and still go to today. Some of them were very notable players, like our President Clinton or President Bush, Shimon Peres, Henry Kissinger, or names that were just really technical leads within companies, or people that really understood PR like Thomas Freedman out of the New York Times, or things of that. >> You always love being in the trenches. I noticed that in Cisco as an observer. But now that you're in start-ups, it's even more trenches deeper (laughs) and you've got to be seeing the playing field, so I got to ask ya a personal question. How do you look back at the tech trends that's happening right now, globally, both political, regulatory technology, what advice would you give your 23-year-old self if you were breaking into the business, you were at Wang and you were going to make your move; in this world today, what's going on, what would you be doing? >> Well the first thing on the tech trend is, don't get too short-term focused. Picture the ones that are longer term, what we refer to as digitization, artificial intelligence, et cetera. If I were 23 years old, or better yet, 19 years old, and were two years through college and thinking what did I want to do in college and then on to MBA school and perhaps beyond that, legal degree if I'd followed the prior path. I would focus on entrepreneurship and really understand it in a lot more detail. I learned it over 40 years in the business. And I learned it from my dad and my mom, but also from the companies I went into before. I would focus on entrepreneurship, I'd focus on technology that enables entrepreneurship, I would probably focus on what artificial intelligence can do for that and that's what we're doing at West Virginia, to your point earlier. And then I would think about security across that. If you want really uh, job security and creativity for the future, if you're a really good entrepreneur, with artificial intelligence capability, and security capability, you're going to be a very desired resource. >> So, we saw you, obviously networking is a big part of it. You got to be networking with other people and in the industry, would you be hosting meet ups? Young John Chambers right now, tech meet ups, would you be at conferences, would you be writing code, would you be doing a start-up? >> Well, if we were talking about me advising them? >> No, you're 23-years-old right now. >> No, I'd just be fooling around. No, I'd be in MBA school and I'd be forming my own company. (both laugh) And I would be listening to customers. I think it's important to meet with your peers, but while I developed strong relationships in the high-tech industry, I spent the majority of time with my customers and with our employees. And so, I think at that age, my advice to people is there was only one Steve Jobs. He just somehow knew what to build and how to build it. And when you think about where they were, it still took him seven years (laughs). I would say, really get close to your customers, don't get too far away; if there's one golden rule that a start-up ought to think about, it's learning and staying close to your customers. There too, understand your differentiation and your strategy. Well John, thanks so much. And the book, Connecting the Dots, great read, it's again, not a business book in the sense of boring, a lot of personal stories, a lot of great lessons and thanks so much for giving the time for our conversation. >> John, it was my pleasure. Great to see you again. >> I'm John Furrier here with the People First interview on theCUBE, co-created content with Mayfield. Thanks for watching! (upbeat electronic music)

from San Francisco it's the queue covering Red Hat summit 2018 brought to you by Red Hat hey welcome back everyone live here in San Francisco California Moscone West is the cubes live coverage of Red Hat Summer 2018 I'm John furry and my co-host John Troyer our next guest is Denise Dumas vice president software engineering operating system group the Red Hat welcome back to the cube good to see you thank you so much great to be here with you so operating systems Linux the base base with everything yeah now you got all those other goodness going on you have some acquisitions permit bit we were just talking about before he came on a lot of action going on yeah what's new well you know you think that the world of operating systems would be boring but honest to god it is so not especially now right because there is a whole generation of change going on in the hardware and when the hardware changes the operating system has got to change to keep up right you look at the stuff that's going on with GPUs with FPGA right I mean and that's just like tip of the iceberg yeah and everything has to be programmable so you need software to keep track of it so it's not just the patches you gotta keep on top of the DevOps automations a big part of it and security models are changing with the cloud there's no perimeter so you have to have maybe chip level encryption os the way up this is challenging so what is it what's the impact to Red Hat as these new things come on because you know you got you know fishing out there sphere fishing is a big problem you got to handle it all how do you guys handle all the security challenges well you know it's it's actually interesting because rel is the base the core of Red Hat's product line which means that we provide the firm underpinning for everything else in the portfolio so we have the FIP certification we're doing the Common Criteria certification we provide the reliable crypto that everybody else can just expect to have in their world and we have to be the really firm basis for everything that layers on top and it's really great to have the additional products in the portfolio working very closely with us to make sure that we can be end-to-end secure end-to-end compliant and that we're looking at the bigger problems because it's not about the operating system it's about the infrastructure and what you're going to run on top of it right a lot of people have been saying security oh it's hard to do security open source is actually a problem for security and then the world shifts back and says wait a minute open source is better to attack security problem because it's out more people working on it versus the human problem of having proprietary so obviously open source is a good thing - security what's the modern approach that you see now that that that you guys are watching and building around that because that's the number one question that coot at kubernetes con we saw a great thing do some kubernetes we saw is do service meshes but Security's got to be thought of on the front end of all the application developers that means it's on you put it into the OS and it's a different world right because the application developers are not accustomed to having to deal with that because that was always the job of the IT guys right that was a problem for the infrastructure to deal with and so clearly we have to provide better security better better tooling available to them but the operations guys right they still they need help in this new world as well because suddenly there's this explosion of containers in their environment and who knows what's in those containers right we've got to have the ability to scan the containers and make sure that they get patched regularly right so it's just it's a whole different set of problems but it all starts with making sure it's secure underneath all the rest of it well so that's that brings up the console of this concept of layers right there's all the operational things there's the apps and the containers and then you know rail is running underneath that that's the hardware and the micro code and all the rest of the stuff so this year we the whole entire IT industry - the kind of a gasp with with the meltdown inspector problems that that surfaced or you know I guess it was in January I think yeah when they were Republican what that was that was how the colonel team spent their Christmas vacation oh my goodness yeah I the colonel team the performance team the security team the virtualization team all those guys so Red Hat shuts down for a week at Christmastime if they didn't yeah that was exciting I mean we've been trained security is one of these things but there's another one coming because cyber attacks are there what's that what's the viewpoint how do you keep on how do you how do you keep on top of it yeah well you know we have a fabulous security team so if you happen to get up to the second floor go talk with chrome Chris Robinson his guys they monitor what's going on in the upstreams they work with mitre they work with the organization's right and when they discover that something is in the wind they come to us and disclose people as needed and then we get to go and figure out how we're gonna get fixes in usually a lot of this stuff happens as you know under embargo so we really we can't talk about it that's a real problem if a lot of the upstream hasn't been read in right so like for instance with meltdown inspector a lot of that was going on not so much in the upstream so there were kind of divergent patches that we got to bring back together that was really we knew that well we had a really strong suspicion that the embargo was gonna break early there that's why my guys were over Christmas right they had to have something ready secure for when it broke and then we could worry about the performance afterwards yeah right and then you had to roll that out into the entire customer base there's some fairly standard mechanisms was there anything special with that because it was fairly high priority I suppose yeah well I mean anything like that we make available a synchronously cuz we want to have it available that the day that that embargo goes public right because that's when we're gonna be getting the phone calls that's when people say oh my god now what do I do but if but the hard part with this one was that you had to have the microcode as well right but we had to do a lot of Education because this was this the side channel attacks it's just a different way of thinking right it's not so much a flaw in the code as in the overall hardware architecture that we get to deal with that stuff what did you learn what's the learnings that were magnifying we have to be as transparent as we can possibly be because security researchers are going to keep on looking for this kind of flaw and we you know we just have to be able to work as much in the open as we can but we also have to have an education function right this is not an area of core expertise for a lot of people who are working in databases right or who are who are designing Java apps and yet we have to be able to explain to them why there's a performance impact on some of the stuff that they're doing and how we can work together to try to get back some of that performance over time no meltdown inspector that's kind of off my radar now but I don't think we're completely out of it right you people have had to patch and reboot and and update but it sounds like we're not I don't think we're at 100% for sure of all systems yeah well you know IT infrastructure right there's your window in which you can actually afford to reboot your systems and I think a lot of those are very tightly scheduled I mean we have customers who get you know ten minutes a year yeah up times of years and years I mean old rebooting is kind of old fashioned at this point yeah really right as it should be as it should be but but when it's the minor code you're kind of stuck yeah I mean that's a hardware thing getting back to the hardware still hardware's even though cloud is extracting away the complexities Hardware still is out there so you never gonna go away for you and as you said it's changing look at the GPU side and you got all kinds of new things coming on the horizon like blockchain and decentralized infrastructure that's encrypted amen right so you know this is you know systems level code mm-hmm with software guys who don't know micro code mm-hmm so you guys got to be on top of it so so I guess the big question is is that operating system that you guys have is very reliable and the support is phenomenal use of industries how do you take the support and the engineering in rel and operating systems and bring that operate system mindset to the next level up as you move up the stack kubernetes new OpenStack as well openshift yeah and apps they all want the same reliability you all want the same kind of robustness nature of an ecosystem at the same time more people are being certified yeah so you have a balance of growth and reliability how do you how do you guys see that and it's also speed and time to market right which is the other factor because there's so much pressure on any emerging technology to get the features out there that you end up carrying the technical debt right or you end up not being able to be as hardened as you might like to be the instant that you go out the door and so it's always gonna be a balancing act and a trade-off so you I know you guys were just talking with Mark Oh bill Peter and he was probably talking about how we're trying to focus on use cases right we need to understand the use cases that our customers have and now those are clearly across the entire product portfolio right but those are the test scenarios that I need to get in flight and those are also the the paths that I need to make sure we've optimized for right and so it's a partnership with the rest of the products in the portfolio and we really do a lot to work together as tightly as we can which is one of the benefits of being at the core right I'm working with everybody yeah and you got the instrumentation too so the other theme yeah the automation big time theme here is breaking down the two of real granular level sets of services which actually is a good thing because if you can instrument it then it's just easy to manage because then he can isolate things so I mean this is a good thing in the OS people love this because you can see couple and make things work well but the instrumentation if you have the API API and you need the instrumentation and looking in so how is that created a challenge because it's all those great for Red Hat's business and then you see in the the forecast and the analysts are seeing the growth you guys are seeing the successes but it makes your job harder a bit that one's a harder but I mean it's you know you get it right more code and make glue layers of abstraction layers yeah but I wouldn't want it to be boring well I do want it to I want it to be boring for our customers I want our customers to just be able to pick up and no drum and exciting homes not ringing with no spectra again it's working like a charm no problem yeah drama llama does not live here yeah yeah that's an interesting point though just a lot of talk about the whole Red Hat stack here right and you got as we've said you the base of it where does where does Linux where is this Linux and especially rail go from here what are you looking at that over the next few years some different technologies you're looking to pull it etc mm-hmm there's always I mean we have to keep up with the hardware advances clearly right but then there's let's oh look at our permaban what a great ad right so perma bit for people who don't know they do a video virtual data optimizer so they do D dupe and compression on the fly on the path to the disk and with rail 75 as part of your subscription you get so we buy we buy companies and we open-source their soft code side their software and we make it available to you as part of your subscription right how good is that so is when you deploy 75 in your environment now suddenly you're gonna need a whole lot less storage right depending on of course it depends upon your data footprint right but but you might find that you're able to shrink the amount of all that expensive storage and expensive cloud storage particularly that you need significantly and you get the compression right was avenge compression was very popular we know we followed in fallen permit bit question on permit bit for you was that open source was that they build their front open stores because now and are you guys open sourcing that that's okay so you have to go gain and and then open it up and do a review and clean it up and yeah yeah and we have to help them get it into an upstream right so they actually they were fabulous the perma because they have been so fabulous to work with best acquisition ever seems to be pretty good at acquiring companies and incorporating their tacit that seems to be part of the culture here yeah that's cuz we're not you know people think we're like big and scary right I'll tell you I have worked for companies that are big and scary Red Hat is not it we're really open and it's really in many ways in engineering culture which is wonderful it's a great fit if you happen to be from a startup culture because we don't overwhelm you with process right I mean we a lot of smart people again I can attest to my interactions over the years smart people very humble a lot of systems people to which is cooperating system hello the world's turning into an operating system good for that but humble and plays the long game you guys I've been you deserve credit for that and that's that's attracting and reason why you successful but you know the thing is we really believe in our core values right we really truly honest-to-god believe in open source and the power that it has to change the world that you know you say oh yeah sure right she's part of the management change she's gonna see him anyway yeah but you guys are growing so I mean over the years again since we started the cube nine years ago we've watched red add just in that time span grow significantly I'll see it's well documented an alternative to the other proprietary os's second-tier citizen now running the world the first tier great job so the youth success business model of open source is now mainstream but you got to onboard more people more ecosystem partners in a really dynamic big wave of innovation coming yeah how do you maintain the recruiting how do you get the great people how do you preserve the culture I'm sure these are questions how do you the more inclusion and diversity questions this is all happening right they're gonna have to catch him at nine years old and grown I mean although honest to god we do a lot of university outreach right if you look in the Czech Republic for instance we have a huge operation in Brno which is the second largest city there and we are so tied in to the university system we bring in lots and lots and lots of interns and it's wonderful right because we want to teach people about open-source we find people who have passion projects and we bring them in this is this is our world right we don't we want non-traditional people as well as traditional computer science majors open-source is a great leveler your CV is online I mean imagine right you're you want to change careers you want a new life you love to code you've been working on writing games in your in your spare time you are our people that's the code your code is who you are your code is it's your CV well this is what Oh doing your things on the open means and also it's been great for your business and we had gym writers on earlier there's no a/b testing they just go into the community and find out what's they want and they just that's the a B C's e testing it's just right there you guys do the due diligence sometimes make big time real fun decisions on features based upon what is in demand practically speaking not just focusing on the new tech that's a good business model we hope so cuz you know I mean as as one of our former CFO I said there are a lot of people a lot of Associates at Red Hat who are dependent on Red Hat for a paycheck and it's very important to us that we remain profitable stable and and really good for our people right we've got a lot of people that we need to take care of in the time it's a good place to be in the timing spray with kubernetes and containers we're taking it up a notch and bringing that extensibility you know just beyond stand-alone Linux so congratulations Denise thanks for coming on and sharing your perspective as always we love these conversations in the cube talk and everything from operating systems to core OS and kubernetes and culture as the cue here out in the open on the floor at Moscone West John Troy yer stay with us we'll be back with more day two of three days of live coverage on the cube net we'll be right back

>> We're here, about to go live, here in a selfie on the pre Silicon Valley Friday Show, about to go live for our show, for some live Friday. We've got a great lineup, it's on my Twitter. Donald Trump and all his viral tweets and now there's an algorithm out there that creates a shorting stock called Trump and Dump, we're going to be talking to the inventor of that new app. Bunch of other great stuff, controversy around Silicon Valley and Intel, controversy on Google, and we'll be watching a great show, well, hopefully you'll be watching. >> Male Announcer: Live, from Cube headquarters in Palo Alto, California it's the Silicon Valley Friday Show, with John Furrier. (serene techno music) >> Hello, everyone, and welcome to the Silicon Valley Friday Show, I'm John Furrier, we are here live in Palo Alto, California for the Silicon Valley Friday Show every Friday morning we broadcast what's going on in Silicon Valley, what's going on in the streets, we call up people and find out what's going on, this show we've got a great lineup. We're going to talk about, I'll say, the news, Twitter, but we've got this fun segment where we have an algorithm, a bot, an AI bot that goes out there and takes all of Donald Trump's tweets and creates a shorting of the stock and creates making money, apparently, Donald Trump's tweets do move the market. We're going to talk about Snapchat, Snap Inc's IPO, and a refiling and some controversy going around that. Also, controversy around Intel Corporation that just announced a fab plant in Arizona and the CEO is in the White House making the announcement, giving the impression that Donald Trump was all behind this, turns out the CEO is a Republican and supports Donald Trump, when apparently this has been in the works for multiple years, so, not sure that's going to be a game changer for Trump but certainly Intel's taking advantage of the schmooze factor and the PR stunt that has people in Silicon Valley up in arms. Obviously, Intel is pro-immigration, bringing people in, obviously, Andy Grove was an immigrant, legend of Intel. And we have also tons of stuff going on, we're going to preview Mobile World Congress the big show in Barcelona at the end of the month. We're doing a two day special here, live in Pal Alto, we're going to do a special, new Silicon Valley version of Mobile World Congress. We'll give you a preview, we're going to talk to some analysts. And also, the fake news, fake accuracy, and all the stuff that's going on, what is fake news? What is inaccurate news? Is there a difference? Does it matter? It certainly does, we have an opinion on that so, great show lineup. First, is actually Twitter earnings are out and they kind of missed and hit their up on the monthly active uniques by two million people. A total of I think 300 million people are using the number here, just on my notes here says, that there are up to 319 million active, monthly active users. And of course, Trump has been taking advantage of Twitter and the Trump bump did not happen for Twitter, although some say Trump kept it alive. But Trump is using Twitter. And he's been actively on Twitter and is causing a lot of people, we've talked about it many times on the show, but the funniest thing that we've seen, and probably the coolest thing that's interesting is that there's an entrepreneur out there, an agency guy named Brian, Ben Gaddis, I'm sorry, president of T3. He's a branding guy, created viral videos on NPR, all over the news, went viral, he created an AI chatbot that essentially takes Donald Trump's tweets, analyzes any company mentioned and then instantly shorts the stock of that company. And apparently it's working, so we're going to take a look at that. We're also going to talk to him and find out what's going on. We're going to have Ben Rosenbaum on, we're going to have someone from Intel on, we have a lot of great guests, so let's take a look at this clip of the Trump and Dump and then we're going to talk to Ben right after. >> Announcer: T3 noticed something interesting about Twitter lately, particularly when this guy gets hold of it. Anytime a company mentions moving to Mexico or overseas or just doing something bad, he's on it, he tweets, the stock tanks. Tweet, tank. Tweet, tank. Tweet, tank. Everyone's talking about how to make sense of all this. T3 thought the unpredictability of it created a real opportunity. Meet the Trump and Dump automated trading platform. Trump and Dump is a bot powered by a complex algorithm that helps us short stocks ahead of the market. Here's how. Every time he tweets, the bot analyzes the tweet to see if a publicly traded company is mentioned. Then, the algorithm runs an instant sentiment analysis of the tweet in less than 20 milliseconds. It figures, positive or negative. A negative tweet triggers the bot to short the stock. Like earlier this month, his Toyota tweet immediately tanked the stock. But the Trump and Dump bot was out ahead of the market. It shorted the second after his tweet. As the stock tanked, we closed our short and we made a profit, huge profit. Oh, and we donated our profits here. So now, when President Trump tweets, we save a puppy. It's the Trump and Dump automated trading platform. Twitter monitoring, sentiment analysis, complex algorithms, real time stock trades. All fully automated, all in milliseconds. And all for a good cause. From your friends at T3. >> Okay, we're back here in Silicon Valley Friday Show, I'm John Furrier and you just saw the Trump and Dump, Trump and Dump video and the creator, that is Ben Gaddis on the phone, president of T3, a privately owned think tank focused on branding. Ben, thanks for joining us today. >> Thanks for having me, John. Excited to talk with you. >> So, big news NPR had on their page, which had the embed on there and it went viral. Great video, but first talk about the motivation, what's going on behind this video? This is very cool, explain to the folks out there what this Trump and Dump video is about, why did you create it, and how does it work? >> So, we had just like, I think, almost everyone in the United States, we were having a conversation about what do you do with the fact that President Trump is tweeting and tweeting about these companies, and in many cases negatively. So we saw articles talking about it and actually one day a guy in our New York office came up with this idea that we ought to follow those tweets in real time and if he mentions a publicly traded company negatively, short the stock. And so, we kicked that idea around over slack and in about 30 minutes we had an idea for the platform. And about two days later one of our engineers had actually built it. And so what the platform does is it's really actually simple yet complex. It listens to every tweet that the president puts out and then it does two things: it determines if there's a publicly traded company mentioned and if there is, and it actually does sentiment analysis in real time, so, in about 20 milliseconds, it can tell if the tweet is positive or negative. If it's negative, we've seen the stocks typically go down and we short sell that stock. And so, the profit that we develop from that, then we donate it to the ASPCA and then hopefully we save a puppy or two in the process. >> Yeah, and that's key, I think that's one thing I liked about this was you weren't arbitraging, you weren't like a real time seller like these finance guys on Wall Street, which by the way, have all these complex trading algorithms. Yours is very specific, the variables are basically Donald Trump, public company, and he tends to be kind of a negative Tweeter so, mostly to do with moving to Mexico or some sort of you know, slam or bullying kind of Tweet he does. And which moves the market, and this is interesting though, because you're teasing out something clever and cool on the AI kind of side of life and you know, some sort of semantic bot that essentially looks at some context and looks at the impact. But this is kind of the real world we're living in now, these kinds of statements from a president of the United States, or anyone who's in a position of authority, literally moves the market, so you're not doing it to make money you're doing it to prove a point which is that the responsibility here is all about getting exposed in the sense that you got to be careful of what you say on Twitter when you're the president of the United States. I mean, if it was me saying it, I mean, I'm not going to move the market but certainly, you know, the press who impact large groups of people and certainly the president does that so, did you guys have that in mind when you were thinking about this? >> Well, we did. I mean, I think, you know, our goal was, this is what we do for a living, we help big brands monitor all their digital presences and build digital strategy. So, we're already monitoring sentiment around Twitter and around social platforms so, it's pretty core to what we do. But we're also looking at things that are happening in pop culture and societally, what kind of impact social might have on business. And so, the fact that we're able to take an action and deliver a social action, and deliver a real business outcome is pretty core to what we do. What's different here and what's so unique is the fact that we've never really seen things like, policy, whether it's monetary policy, or just general policy be distributed through one platform like Twitter and have such a big impact. So, we think it's kind of a societal shift that is sort of the new norm. That, I don't know that if everyone has figured out what to do with yet and so our goal is to experiment and decide one, can we consume the information fast enough to take an action? And then how do we build through AI platforms that allow us to be smarter in the world that we're living in today that is very, very unpredictable. >> We have Ben Gaddis, as president of T3 also part of the group that did the Trump and Dump video but he brings out a great point about using data and looking at the collective impact of information in real time. And this interesting, I was looking at some of the impact last night in this and Nordstrom's had a tweet about Ivanka Trump and apparently Nordstrom's stock is up so, is there a flaw in the algorithm here? What's the take on that? Because in a way, that's the reverse of the bullying, he's defensive on that one so, is there a sentiment of him being more offensive or defensive? >> It's pretty standard. So, we're starting to see a pattern. So, what happens is that actually, the Nordstrom stock actually did go down right after the tweet. And so, we saw that that's a pattern that's typical when the president tweets negatively. When he tweets positively, we don't see that much of a bump. When he tweets negatively, typically the stock drops anywhere between one and four percent, sometimes even greater than that. But it rebounds very quickly. So, a big part of what we're trying to do with the bot and the algorithm is understand how long do we hold, and what is that timeframe before people actually come back to more of a rational state and start to buy back a stock that's valuable. Now what's really interesting, you mentioned, you know, the algorithm and whether there's a flaw in it, we learned something very interesting yesterday about Nordstrom's. So, the president tweeted and in that tweet he talked negatively about Nordstrom's, but he also talked very positively about his daughter, Ivanka. And so, the algorithm actually picked up that tweet and registered it as 61.5% positive. So, it didn't trade. So, we actually got kind of lucky on that one. >> You bring up a good point, and this is something that I want to get your thoughts on. You know, we live in an era of fake news, and it's just Snapchat just filed IPO filing to make a change in their filing to show that Amazon is going to be a billion dollar partner as well, which wasn't in the filing. So, there's a line between pure, fake news, which is essentially just made up stuff, and inaccurate news, so what you're kind of pointing out is a new mechanism to take advantage of the collective intelligence of real time information. And so this is kind of a new concept in the media business. And brands, who used to advertise with big media companies, are now involved in this so, as someone who's, you know, an architect for brand and understanding data, how are brands becoming more data driven? >> Well, I think what brands are realizing is that they live in this world that is more real time, that's such a buzzword. But more real time than I think they even thought would ever be possible, the fact that someone like the president can tweet and have literally cut off billions of dollars in market cap value in a moment's time is something that they have to figure out. So, I think the first thing is having the tools in place to actually monitor and understand, and then having a plan in place to react to things that are really quite unpredictable. So, not only, I don't think that you can have a plan for everything but you have to at least have a plan for understanding how you get legal approval on a response. Who would be responsible for that. You know, who do you work with, either through partners or inside of your organization to, you know, to be able to respond to something when you need to get back in promoting, you know, minutes versus hours. The thing that we don't hear people talk near as much about is, our goal was to see how close we can get to the information so we can zoom the data from Twitter's fire hose, so we get it hopefully when everyone else does. And then our goal is to take an action on that quicker than anybody else, and that delta is where we'll make a profit. What's really interesting to me is that the only person closer to that information than the president is Twitter. >> Ben, great to have you on, appreciate it, love to get you back on as a guest. We love to talk about is our model here, it's looking angle, it's extracting the signal from the noise. And certainly the game is changing, you're working with brands and the old model of ad agencies, this is a topic we love to cover here, the old ad agency model's certainly becoming much more platform oriented with data, these real time tools really super valuable, having a listening engine, having some actionable mechanisms to go out there and be part of and influence the conversation with information. Seems to be a good trend that you guys are really riding. Love to have you back on. >> We'd love to be back on, and thanks for the time, we enjoyed it. >> That was Ben Gaddis, who's the president of T3, the firm behind the Trump and Dump, but more importantly highlighting a really big megatrend which is the use of data, understanding its impact, having some analysis, and trying to figure out what that means for people. Be right back with more after this short break. >> [Female Announcer] Why wait for the future? The next evolution in IT infrastructure is happening now. 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Unify your data center with Cisco UCS. >> Male Announcer: You're listening to Cube Fridays, brought to you by Silicon Angle Media. Now, here's John Furrier. >> Okay, welcome back to the Silicon Valley Friday Show, I'm John Furrier, great show today. Our next guest is Dan Rosenbaum, who is the editor of Wearable Tech Insider, Media Probe, been around the industry for years, been a journalist, reporter, editor, variety through his career, knows the tech business certainly on the infrastructure level with the device. Okay, welcome to the show, great to have you, thanks for being available, he's in New York so, Palo Alto, New York connection here. >> Yeah, we got about maybe an hour or so of snow left. But you know, it's February, it does this in New York. >> Great to have you on, we were just talking on our earlier segment before the break about the guy who created the Trump and Dump video which is a chat bot that goes out, looks at Donald Trump's tweets, and then identifies if there's a public company, shorts the stock, and donates to save puppies. So, they're not doing it for profit but they're, you know, they have their intelligence and listening, and we were just riffing on the concept of that there's been fake news and inaccuracy and a new dynamic that's impacting the media business, which is real time information, data, and certainly the world that you're in with Wearables, this new internet of things, which is hard to understand for most common people but it's really the AI new connected network. It's really impacting things, certainly how people get information, how fast they create data, and it's changing the industry landscape certainly from a media standpoint. You get on TV and the mainstream... >> It really is. When the press secretary stood up and said that that the administration sees the media as the adversary, you know, everyone got sort of upset about it but you know, in a lot of ways it's true. That's a fitting way that the media and any administration, any power structure should be facing each other. There's been such a hop in the media to report the truth as best as it can determine and as accurately as it can. Now, there are differing impacts depending on which sphere you're in, and in politics there's always going to be sort of the tension, well, we think, we look at these facts and we think that and we look at those facts and think the other. >> I think ultimately this new formats that are developing really comes back down to I would add to that as trust. This is a collision course of a complete re-transformation of the media landscape and technology's at the heart of it and, you know, you're in the middle of it. With Wearables, you're seeing that at the edge of the network, these are new phenomenons. What's your take on this new trend of, you know, of computing? And I'm not saying singularity, as Ray Kurzweil would say, but you know, ultimately, it is going down to the point now where it's on your body, potentially in your body, but this is a new form of connection. What's your thoughts on this? >> 12 years ago, I was at the party where they launched MSNBC, and I ran into Andrew Lack, who's the CEO of MSNBC at the time, and asked him, why NBC was cutting this collaboration deal with Microsoft, because remember that's how it was started, when there wasn't any means for the news to go upwards. There was no way for citizen news gathering to be represented on this Microsoft-NBC co-venture. And Andrew actually looked down his nose at me, sneered, and goes, "Who in the world would want "people to be contributing to the news?" Well, now we're 10 or 12 years later and as you say, Snapchat and Skype, and all these mobile technologies have just transformed how people get their information, because they're now witnesses, and there are witnesses everywhere. One of the big transformations in, or about wearable technology is that computing infrastructure has moved from islands of stand-alone, massive computers, to networks of massive computers to stand-alone PCs, to networks to PCs, and now the model for computing and communication is the personal area network, the idea of sensor-based technologies is going to change, or already has changed the world of news, it's in the process of changing the world of medicine, it's in the process of changing the way we build houses, the construction business, with the smartphone, the way that we build and relate to cities. >> So, we're here with Dan Rosenbaum, he's the editor of Wearable Tech Insider, but more importantly he's been a tech insider in media going way back, he's seen the cycles of innovation. Love your point about the flowing conversations coming out of the MSNBC kind of executive in the old broadcast models. I mean, I have four kids, my oldest is 21, they don't use, they don't really care about cable TV anymore so, you know, this is now a new narrative so, those executives that are making those comments are either retired or will be dinosaurs. You now have Amazon, you have Netflix, you have, you know, folks, trying to look at this internet TV model where it's fully synchronous so, now you have collective intelligence of vertical markets that have real time ability to surface information up to bigger outlets. So, this collective media intelligence is happening, and it's all being driven by mobile technology. And with that being said, you know, you're in the business, we've got Mobile World Congress coming up, what is that show turning into? Because it's not about the mobile device anymore, the iPhone's 10 years old, that's a game changer. It's growing up. The impact of mobile is now beyond the device. >> Mobile World Congress is all about wireless infrastructure. It goes from everything from a one millimeter square sensor to the national grade wireless network. But what's really cool about Mobile World is that it's the place where communications or telecom ministers get together with infrastructure carriers, get together with the hardware manufacturers, and they hash out the problems that won't resolve five, 10, 15 years down the road in new products and new services. This is the place where everyone comes together. The back rooms at Mobile World Congress are the hottest place, and the back rooms are the places that you can't get into. >> We're here with Dan Rosenbaum, who's an industry veteran, also in the media frontlines in wireless technology, I mean, wearable technology and among other things, good view of the landscape. Final point, I want to just get a quick comment from ya, I was watching on Facebook, you had a great post around Facebook is feeding you an ad for a $19 million staid-in, let's feel Connecticut. And then you said, "One of us as the wrong idea, so you must be really loaded." This retargeting bullshit on Facebook is just ridiculous, I mean, come on, this bad, big data, isn't it? >> (laughing) Yeah, I mean, the boast of Google is that they want to make, you know, ads so relevant that they look like content. Well, in the process to getting there, there's going to be misses. You know, if this real estate agent decides that they want to hit everyone in my zip code, or everyone in my county, or whatever, and they wanted pay the five dollars so that I'd see that video, god bless 'em, let 'em do it, it's not going to make me, it's not going to overcome any kind of sales resistance. I don't know that I wanted to move up to Litchfield, Connecticut anyway, but if I did, sure, a $19 million house would be really nice. >> You could take a chopper into Manhattan, you know, just drop into Manhattan with a helicopter. >> They would want to take it. >> Alright, we can always take the helicopter in from Litchfield, you know, right at the top of your building. Dan, thanks so much for spending the time, really appreciate it, and we'll have to bring, circle back with you on our two day Mobile World Congress special in Palo Alto we'll be doing, so appreciate the time. Thanks a lot. >> Love to do it, thanks for having me. >> Okay, that was Dan Rosenbaum, really talking about, going down in the weeds a little bit but really more importantly, this Mobile World Congress, what's going on with this new trend, digital transformation really is about the impact to the consumer. And what's going on Silicon Valley right now is there's some hardcore tech that is changing the game from what we used to know as a device. The iPhone's only 10 years old, yet 10 years old, before the iPhone, essentially it was a phone, you made phone calls, maybe surf the Web through some bad browser and do text messages. That's now completely transforming, not just the device, it's the platform, so what we're going to see is new things that are happening and the tell signs are there. Self driving cars, autonomous vehicles, drones delivering packages from Amazon, a completely new, digitized world is coming. This is the real trend and we're going to have an executive from Intel on next to tell us kind of what's going on because Intel is at the ground zero of the innovation with Moore's Law and the integrated circuit. But they're bringing their entire Intel inside as a global platform, and this is really going to be driven through a ton of 5G, a new technology so, we're going to dig in on that, and we're going to have a call-in from her, she's going to be coming in from Oregon and again, we're going to get down to the engineers, the people making the chips under the hood and bringing that to you here on the Silicon Valley Friday Show, I'm John Furrier, we'll be right back after this short break. >> My name is Dave Vellante, and I'm a long-time industry analyst. So, when you're as old as I am you've seen a lot of transitions. Everybody talks about industry cycles and waves, I've seen many, many waves. I've seen a lot of industry executives and I'm a little bit of an industry historian. When you interview many thousands of people, probably five or six thousand people as I have over the last half of the decade, you get to interact with a lot of people's knowledge. And you begin to develop patterns so, that's sort of what I bring is an ability to catalyze a conversation and, you know, share that knowledge with others in the community. Our philosophy is everybody is an expert at something, everybody's passionate about something and has real deep knowledge about that something. Well, we want to focus in on that area and extract that knowledge and share with our communities. This is Dave Vellante, and thanks for watching the Cube. (serene techno music) >> Male Announcer: You're listening to the Silicon Valley Friday Show with John Furrier. >> Okay, welcome back to the Silicon Valley Friday Show, I'm John Furrier, we're here in Palo Alto for this Friday Show, we're going to go under the hood and get into some technology impact around what's going on in the industry, specifically kind of as a teaser for Mobile World Congress at the end of the month, it's a big show in Barcelona, Spain where the whole mobile and infrastructure industry comes together, it's kind of like CES, Consumer Electronics Show, in the mobile world but it's evolved in a big way and it's certainly impacting everyone in the industry and all consumers and businesses. This is Intel's Lynn Comp and this is Intel who, we know about Moore's Law, we know all about the chips that make everything happen, Intel has been the engine of innovation of the PC revolutions, it's been the engine of innovation now in the Cloud and as Intel looks at the next generation, they are the key player in this transformation that we are seeing with AI, wearable computers, internet of things, self driving cars, AI, this is all happening, new stuff's going on. Lynn, welcome to the program. >> Thank you so much, it's great to be here. >> So, you're up in Oregon, thanks for taking the time to allow us to talk via phone, appreciate it. Obviously, Intel, we've been following you guys, and I've been a big fan since 1987, when I almost worked there right out of college. Went to Hewlett Packard instead, but that's a different story but, great, great innovation over the years, Intel has been the bell weather in the tech industry, been a big part of the massive change. But now, as you look at the next generation, I mean, I have four kids and they don't watch cable TV, they don't like, they don't do the things that we used to do, they're on the mobile phone all the time. And the iPhone is now 10 years old as of this year, this early winter part of this, Steve Jobs announced it 10 years ago. And what a change has it been, it's moved from telephone calls to a computer that happens to have software that makes telephone calls. This is a game changer. But now it seems that Mobile World Congress has changed from being a telephone centric, voice centric, phone device centric show to a software show, it seems to be that software is eating the world just like CES is turning into an automotive show. What is Mobile World Congress turning into? What's the preview from Intel's perspective? >> You know, it's a really fascinating question because many years ago, you would only see a bunch of very, very intense base station design, you know, it was very, very oriented around wireless, wireless technology, and radios, and those are really important because they're an engine of fabric that you can build capabilities onto. But last year, just as a reference point for how much it's changed, we have Facebook giving one of the main keynotes. And they're known for their software, they're known for social media, and so you'll see Facebook and Google with an exhibitor there last year as well, so you're not just seeing suppliers into the traditional wireless industry for equipment and the operators who are the purchaser, you're seeing many, many different players show up very much like how you said CES has a lot of automotives there now. >> Yeah, we've seen a lot of revolutions in the computer industry, Intel created a revolution called the Computer Revolution, the PC Revolution, and then it became kind of an evolution, that seems to be the big trends you see, that cycle. But it seems now that we are, kind of been doing the evolution of mobile computing, and my phone gets better, 10 years down to the iPhone, 3G, 4G, LT, okay, I want more bandwidth, of course, but is there a revolution? Where can you point to? Where is the revolution, versus just standard evolutionary kind of trends? Is there something coming out of this that we're going to see? >> That is such a great question because when you look at the first digital wireless technologies that came out and then you had 2G, and 3G, and 4G, those really were evolutionary. And what we're finding with 5G that I believe is going to be a huge theme at Mobile World Congress this year is it is a completely different ballgame, I would say it's more of an inflection point or very revolutionary. And there's a couple reasons for that, both tie up in how ITU is specifying the use cases, it's licensed and unlicensed spectrum which is kind of unusual for how it's been done if you will get 2, 3, and 4G. The other thing that's really interesting about 5G, that it's an inflection point is there's a lot more intelligence assumed in the network and it helps address some of the challenges I think that the industry is seeing a different industry with some of the IoT promise we'll roll out where some of the macro design networks that we'd seen in the past, the ability to have the right latency, the right bandwidth, and the right cost matched to the needs of a specific IoT use case was much more limited in the past and I think we'll see a lot more opportunities moving forward. >> Great, great stuff, we're with Lynn Comp with the Network Platforms Group at Intel. You know, you bring up some, I like the way you're going with this, there's so much like, impact to society going on with these big, big trends. But also I was just having a conversation with some young folks here in Palo Alto, high school kids and some college kids and they're all jazzed up about AI, you can almost see the... I don't want to say addiction but fascination and intoxication with technology. And there's some real hardcore good tech going on here, could you just share your thoughts on, you know, what are some of those things that are going to, 'cause I mean, 5G to wireless, I get that, but I mean, you know, these kids that we talked to and folks that are in the next generation, they love the autonomous vehicles. But sometimes I can't get a phone signal, how are cars going to talk to each other? I mean, how does this, I mean, you've got to pull this together. And these kids are like, and it's into these new careers. What's your thoughts on what are some of the game changing tech challenges that are coming out of this? >> Let's just start with something that was a great example this year 'cause I think I have kids a similar age. And I had been skeptical of things like even just virtual reality, a augmented or virtual reality. And then we had this phenomena last summer that really was just a hint, it wasn't really augmented reality, but it was a hint of the demand that could be met by it and it's Pokemon Go. And so, an example with that, I mean, it really wasn't asking a significantly higher amount of data off the network, but it did change the use profile for many of the coms service providers and many of the networks where they realized I actually have to change the architecture, not just of what's at the edge but in my core network, to be more responsive and flexible, you are going to see something even more so with autonomous driving, even if it's just driver assist. And similar to how the auto pilot evolution happened, you're still going to have these usage patterns where people have too many demands, too much information coming at them, they do want that assistance, or they do want that augmented experience to interact with a brand, and it's going to really stress the network and there's going to have to be a lot of innovation about where some of these capabilities are placed and how much intelligence is close to the user as opposed to just a radio, probably going to need a lot more analytics and a lot more machine learning capabilities there as well. >> We had a segment earlier in the show, it was the entrepreneur who created the Trump and Dump chat bot that would go out and read Donald Trump's tweets and then short all public companies that were mentioned because the trend is, they would do that, but this is an example of some of these chat bots and some of this automation that's going on and it kind of brings the question up to some of the technology challenges that we're looking out at the landscape that we're discussing is the role of data really is a big deal and software and data now have an interaction play where you got to move data around the networks, networks are now ubiquitous, networks are now on people, networks are now in cars, networks are now part of all this, I won't say unstructured networks, but omni-connected fabric. So, data can really change what looks like an optimal architecture to a failed one, if you don't think about it properly. So, how do you guys at Intel think about the role of data? I mean, how do you build the new chips and how do you look at the landscape? And it must be a big consideration, what's your thoughts about the role of data? Because it can happen at any time, a tsunami of data could hit anything. >> Right, the tsunami of data. So for us, it's any challenge, and this is just in Intel's DNA, historically, we'll get challenges as opportunities because we love to solve these really big problems. And so, when you're talking about data moving around a network you're talking about transformation of the network. We've been having a lot of discussions with operators where they see the data tsunami, they're already seeing it, and they realized, I have got to reconfigure the architecture of my network to leverage these technologies and these capabilities in a way that's relevant for the regulatory environment I'm in. But I still have to be flexible, I have to be agile, I have to be leveraging programmability instead of having to rewrite software every generation or every time a new app comes out. >> Lynn, thanks so much for coming on. Like we always say, you know, engine room more power, you can never have enough compute power available in network bandwidth, as far as I'm concerned. You know, we'd love to increase the power, Moore's Law's been just a great thing, keeps on chugging along. Thanks for your time and joining us on the Silicon Valley Friday Show, appreciate it. Thanks so much. >> Thank you. >> Alright, take care. Okay, this is Silicon Valley Friday Show, I'm John Furrier, thanks so much for listening. I had Ben Gaddis on, Dan Rosenbaum, and Lynn Comp from Intel really breaking it down and bringing you all the best stories of the week here on the Silicon Valley, thanks for watching. (techno music) (bright instrumental music)

>>Hi buddy, we're back. This is Dave Volante with the cube goes out to the shows. We extract the signal from the noise. Nate Silver's here. Nate, we've been saying that since 2010, rip you off. Hey Marcus feeder. Oh, you have that trademarks. Okay. So anyway, welcome to the cube. You man who needs no introduction, but in case you don't know Nate, uh, he's a very famous author, five 30 eight.com. Statistician influence, influential individual predictor of a lot of things including presidential elections. And uh, great to have you here. Great to be here. So we listened to your keynote this morning. We asked earlier if some of our audience, can you tweet it and you know, what would you ask Nate silver? So of course we got the predictable, how the red Sox going to do this year? Who's going to be in the world series? Are we going to attack Syria? >>Uh, will the fed E's or tightened? Of course we're down here. Who'd you vote for? Or they, you know, they all want to know. And of course, a lot of these questions you can't answer because it's too far out. But, uh, but anyway, again, welcome, welcome to the cube. Um, so I want to start by, uh, picking up on some of the themes in your keynote. Uh, you're here at the Tableau conference. Obviously it's all about about data. Uh, and you, your basic, one of your basic premises was that, um, people will misinterpret data, they'll just use data for their own own biases. You have been a controversial figure, right? A lot of people have accused you of, of bias. Um, how, what do you F how do you feel about that as a person who's, uh, you know, statistician, somebody who loves data? >>I think everyone has bias in the sense that we all have one relatively narrow perspective as compared to a big set of problems that we all are trying to analyze or solve or understand together. Um, you know, but I do think some of this actually comes down to, uh, not just bias, but kind of personal morality and ethics really. It seems weird to talk about it that way, but there are a lot of people involved in the political world who are operating to manipulate public opinion, um, and that don't really place a lot of value on the truth. Right. And I consider that kind of immoral. Um, but people like that I think don't really understand that someone else might act morally by actually just trying to discover the way the objective world is and trying to use science and research to, to uncover things. >>And so I think it's hard people to, because if they were in your shoes, they would try and manipulate the forecast and they would cheat and put their finger on their scale. They assume that anyone else would do the same thing cause they, they don't own any. Yeah. So will you, you've made some incredibly accurate predictions, uh, in the face of, of, of others that clearly had bias that, that, that, you know mispredicted um, so how did you feel when you got those, those attacks? Were you flabbergasted? Were you pissed? Were you hurt? I mean, all of the above having you move houses for, for you? I mean you get used to them with a lot of bullshit, right? You're not too surprised. Um, I guess it surprised me how, but how much the people who you know are pretty intelligent are willing to, to fool themselves and how specious arguments where meet and by the way, people are always constructing arguments for, for outcomes they happen to be rooting for. >>Right? It'd be one thing if you said, well I'm a Republican, but boy I think Obama's going to crush Romney electoral college or vice versa. But you should have an extra layer of scrutiny when you have a view that diverges from the consensus or what kind of the markets are saying. And by the way, you can go and they're betting Margaret's, you can go and you could have bet on the outcome of election bookies in the UK, other countries. Right. And they kind of had forecast similar to ours. We were actually putting their money where their mouth was. Agree that Obama was a. Not a lot, but a pretty heavy favorite route. Most of the last two months in the election. I wanted to ask you about prediction markets cause as you probably know, I mean the betting public are actually very efficient. Handicappers right over. >>So I'll throw a two to one shot is going to be to three to one is going to be a four to one, you know, more often than not. But what are your thoughts on, on prediction markets? I mean you just sort of betting markets, you'd just alluded it to them just recently or is that a, is that a good, well there a lot there then then I think the punditry right. I mean, you know, so with, with prediction markets you have a couple of issues. Number one is do you have enough, uh, liquidity, um, and my volume in the markets for them to be, uh, uh, optimal. Right. And I think the answer right now is maybe not exactly. And like these in trade type markets, knowing trade has been, has been shut down. In fact, it was pretty light trading volumes. It might've had people who stood to gain or lose, um, you know, thousands of dollars. >>Whereas in quote, unquote real markets, uh, the stakes are, are several orders of magnitude higher. If you look at what happened to, for example, just prices of common stocks a day after the election last year, um, oil and gas stocks lost billions of dollars of market capitalization after Romney lost. Uh, conversely, some, you know, green tech stocks or certain types of healthcare socks at benefit from Obamacare going into play gain hundreds of millions, billions of dollars in market capitalization. So real investors have to price in these political risks. Um, anyway, I would love to have see fully legal, uh, trading markets in the U S people can get bet kind of proper sums of money where you have, um, a lot of real capital going in and people can kind of hedge their economic risk a little bit more. But you know, they're, they're bigger and it's very hard to beat markets. They're not flawless. And there's a whole chapter in the book about how, you know, the minute you assume that markets are, are clairvoyant and perfect, then that's when they start to fail. >>Ironically enough. But they're very good. They're very tough to beat and they certainly provide a reality check in terms of providing people with, with real incentives to actually, you know, make a bet on, on their beliefs and people when they have financial incentives, uh, uh, to be accurate then a lot of bullshit. There's a tax on bullshit is one way. That's okay. I've got to ask him for anyway that you're still a baseball fan, right? Is that an in Detroit fan? Right. I'm a tiger. There's my bias. You remember the bird? It's too young to remember a little too. I, so I grew up, I was born in 78, so 84, the Kirk Gibson, Alan Trammell teams are kind of my, my earliest. So you definitely don't remember Mickey Lola cha. I used to be a big guy. That's right fan as well. But so, but Sony, right when Moneyball came out, we just were at the Vertica conference. >>We saw Billy being there and, and uh, when, when, when, when, when that book came out, I said Billy Bean's out of his mind for releasing all these secrets. And you alluded to in your talk today that other teams like the rays and like the red Sox have sort of started to adopt those techniques. At the same time, I feel like culturally when another one of your V and your Venn diagram, I don't want you vectors, uh, that, that Oakland's done a better job of that, that others may S they still culturally so pushing back, even the red Sox themselves, it can be argued, you know, went out and sort of violated the, the principles were of course Oakland A's can't cause they don't have a, have a, have a budget to do. So what's your take on Moneyball? Is the, is the strategy that he put forth sustainable or is it all going to be sort of level playing field eventually? >>I mean, you know, the strategy in terms of Oh fine guys that take a lot of walks, right? Um, I mean everyone realizes that now it's a fairly basic conclusion and it was kind of the sign of, of how far behind how many biases there were in the market for that, you know, use LBP instead of day. And I actually like, but that, that was arbitrage, you know, five or 10 years ago now, um, put butts in the seat, right? Man, if they win, I guess it does, but even the red Sox are winning and nobody goes to the games anymore. The red Sox, tons of empty seats, even for Yankees games. Well, it's, I mean they're also charging 200 bucks a ticket or something. you can get a ticket for 20, 30 bucks. But, but you know, but I, you know, I, I, I mean, first of all, the most emotional connection to baseball is that if your team is in pennant races, wins world series, right then that produces multimillion dollar increases in ticket sales and, and TV contracts down the road. >>So, um, in fact, you know, I think one thing is, is looking at the financial side, like modeling the martial impact of a win, but also kind of modeling. If you do kind of sign a free agent, then, uh, that signaling effect, how much does that matter for season ticket sales? So you could do some more kind of high finance stuff in baseball. But, but some of the low hanging fruit, I mean, you know, almost every team now has a Cisco analyst on their payroll or increasingly the distinctions aren't even as relevant anymore. Right? Where someone who's first in analytics is also listening to what the Scouts say. And you have organizations that you know, aren't making these kind of distinctions between stat heads and Scouts at all. They all kind of get along and it's all, you know, finding better ways, more responsible ways to, to analyze data. >>And basically you have the advantage of a very clear way of measure, measure success where, you know, do you win? That's the bottom line. Or do you make money or, or both. You can isolate guys Marshall contribution. I mean, you know, I am in the process now of hiring a bunch of uh, writers and editors and developers for five 38 right? So someone has a column and they do really well. How much of that is on the, the writer versus the ed or versus the brand of the site versus the guy at ESPN who promoted it or whatever else. Right. That's hard to say. But in baseball, everyone kind of takes their turn. It's very easy to measure each player's kind of marginal contribution to sort of balance and equilibrium and, and, and it's potentially achieved. But, and again, from your talk this morning modeling or volume of data doesn't Trump modeling, right? >>You need both. And you need culture. You need, you need, you know, you need volume of data, you need high quality data. You need, uh, a culture that actually has the right incentives align where you really do want to find a way to build a better product to make more money. Right? And again, they'll seem like, Oh, you know, how difficult should it be for a company to want to make more money and build better products. But, um, when you have large organizations, you have a lot of people who are, uh, who are thinking very short term or only about only about their P and L and not how the whole company as a whole is doing or have, you know, hangups or personality conflicts or, or whatever else. So, you know, a lot of success I think in business. Um, and certainly when it comes to use of analytics, it's just stripping away the things that, that get in the way from understanding and distract you. >>It's not some wave a magic wand and have some formula where you uncover all the secrets in the world. It's more like if you can strip away the noise there and you're going to have a much clearer understanding of, of what's really there. Uh, Nate, again, thanks so much for joining us. So kind of wanna expand on that a little bit. So when people think of Nate silver, sometimes they, you know, they think Nate silver analytics big data, but you're actually a S some of your positions are kind of, you take issue with some of the core notions of big data really around the, the, the importance of causality versus correlation. So, um, so we had Kenneth kookier on from, uh, the economist who wrote a book about big data a while back, the strata conference. And you know, he, in that book, they talk a lot about it really doesn't matter how valid anymore, if you know that your customers are gonna buy more products based on this dataset or this correlation that it doesn't really matter why. >>You just try to try to try to exploit that. Uh, but in your book you talk about, well and in the keynote today you talked about, well actually hypothesis testing coming in with some questions and actually looking for that causality is also important. Um, so, so what is your, what is your opinion of kind of, you know, all this hype around big data? Um, you know, you mentioned volume is important, but it's not the only thing. I mean, like, I mean, I'll tell you I'm, I'm kind of an empiricist about anything, right? So, you know, if it's true that merely finding a lot of correlations and kind of very high volume data sets will improve productivity. And how come we've had, you know, kind of such slow economic growth over the past 10 years, where is the tangible increase in patent growth or, or different measures of progress. >>And obviously there's a lot of noise in that data set as well. But you know, partly why both in the presentation today and in the book I kind of opened up with the, with the history is saying, you know, let's really look at the history of technology. It's a kind of fascinating, an understudied feel, the link between technology and progress and growth. But, um, it doesn't always go as planned. And I certainly don't think we've seen any kind of paradigm shift as far as, you know, technological, economic productivity in the world today. I mean, the thing to remember too is that, uh, uh, technology is always growing in and developing and that if you have roughly 3% economic growth per year exponential, that's a lot of growth, right? It's not even a straight line growth. It's like exponential growth. And to have 3% exponential growth compounding over how many years is a lot. >>So you're always going to have new technologies developing. Um, but what I, I'm suspicious that as people will say this one technology is, is a game changer relative to the whole history of civilization up until now. Um, and also, you know, again, a lot of technologies you look at kind of economic models where you have different factors or productivity. It's not usually an additive relationship. It's more a multiplicative relationships. So if you have a lot of data, but people who aren't very good at analyzing it, you have a lot of data but it's unstructured and unscrutinised you know, you're not going to get particularly good results by and large. Um, so I just want to talk a little bit about the, the kind of the, the cultural issue of adopting kind of analytics and, and becoming a data driven organization. And you talk a lot about, um, you know, really what you do is, is setting, um, you know, try to predict the probabilities of something happening, not really predicting what's going to happen necessarily. >>And you talked to New York, you know, today about, you know, knowledging where, you know, you're not, you're not 100% sure acknowledging that this is, you know, this is our best estimate based on the data. Um, but of course in business, you know, a lot of people, a lot of, um, importance is put on kind of, you know, putting on that front that you're, you know, what you're talking about. It's, you know, you be confident, you go in, this is gonna happen. And, and sometimes that can actually move markets and move decision-making. Um, how do you balance that in a, in a business environment where, you know, you want to keep, be realistic, but you want to, you know, put forth a confident, uh, persona. Well, you know, I mean, first of all, everyone, I think the answer is that you have to, uh, uh, kind of take a long time to build the narrative correctly and kind of get back to the first principles. >>And so at five 38, it's kind of a case where you have a dialogue with the readers of the site every day, right? But it's not that you can solve in one conversation. If you come in to a boss who you never talked to you before, you have to present some PowerPoint and you're like, actually this initiative has a, you know, 57% chance of succeeding and the baseline is 50% and it's really good cause the upside's high, right? Like you know, that's going to be tricky if you don't have a good and open dialogue. And it's another barrier by the way to success is that uh, you know, none of this big data stuff is going to be a solution for companies that have poor corporate cultures where you have trouble communicating ideas where you don't everyone on the same page. Um, you know, you need buy in from, from all throughout the organization, which means both you need senior level people who, uh, who understand the value of analytics. >>You also need analysts or junior level people who understand what business problems the company is trying to solve, what organizational goals are. Um, so I mean, how do you communicate? It's tricky, you know, maybe if you can't communicate it, then you find another firm or go, uh, go trade stocks and, and uh, and short that company if you're not violating like insider trading rules of, of various kinds. Um, you know, I mean, the one thing that seems to work better is if you can, uh, depict things visually. People intuitively grasp uncertainty. If you kind of portray it to them in a graphic environment, especially with interactive graphics, uh, more than they might've just kind of put numbers on a page. You know, one thing we're thinking about doing with the new 580 ESPN, we're hiring a lot of designers and developers is in case where there is uncertainty, then you can press a button, kind of like a slot, Michigan and simulate and outcome many times, then it'll make sense to people. Right? And they do that already for, you know, NCAA tournament stuff or NFL playoffs. Um, but that can help. >>So Nate, I asked you my, my partner John furry, who's often or normally the cohost of this show, uh, just just tweeted me asking about crowd spotting. So he's got this notion that there's all this exhaust out there, the social exhaustive social data. How do you, or do you, or do you see the potential to use that exhaust that's thrown off from the connected consumer to actually make predictions? Um, so I'm >>a, I guess probably mildly pessimistic about this for the reason being that, uh, a lot of this data is very new and so we don't really have a way to kind of calibrate a model based on it. So you can look and say, well, you know, let's say Twitter during the Republican primaries in 2016 that, Oh, Paul Ryan is getting five times as much favorable Twitter sentiment as Rick Santorum or whatever among Republicans. But, but what's that mean? You know, to put something into a model, you have to have enough history generally, um, where you can translate X into Y by means of some function or some formula. And a lot of data is so new where you don't have enough history to do that. And the other thing too is that, um, um, the demographics of who is using social media is changing a lot. Where we are right now you come to conference like this and everyone has you know, all their different accounts but, but we're not quite there yet in terms of the broader population. >>Um, you have a lot of kind of thought leaders now a lot of, you know, kind of young, smart urban tech geeks and they're not necessarily as representative of the population as a whole. That will over time the data will become more valuable. But if you're kind of calibrating expectations based on the way that at Twitter or Facebook were used in 2013 to expect that to be reliable when you want a high degree of precision three years from now, even six months from now is, is I think a little optimistic. Some sentiment though, we would agree with that. I mean sentiment is this concept of how many people are talking about a thumbs up, thumbs down. But to the extent that you can get metadata and make it more stable, longer term, you would see potential there is, I mean, there are environments where the terrain is shifting so fast that by the time you know, the forecast that you'd be interested in, right? >>Like things have already changed enough where like it's hard to do, to make good forecast. Right? And I think one of the kind of fundamental themes here, one of my critiques is some of the, uh, of, uh, the more optimistic interpretations of big data is that fundamentally people are, are, most people want a shortcut, right? Most people are, are fairly lazy like labor. What's the hot stock? Yeah. Right. Um, and so I'm worried whenever people talk about, you know, biased interpretations of, of the data or information, right? Whenever people say, Oh, this is going to solve my problems, I don't have to work very hard. You know, not usually true. Even if you look at sports, even steroids, performance enhancing drugs, the guys who really get the benefits of the steroids, they have to work their butts off, right? And then you have a synergy which hell. >>So they are very free free meal tickets in life when they are going to be gobbled up in competitive environments. So you know, uh, bigger datasets, faster data sets are going to be very powerful for people who have the right expertise and the right partners. But, but it's not going to make, uh, you know anyone to be able to kind of quit their job and go on the beach and sip my ties. So ne what are you working on these days as it relates to data? What's exciting you? Um, so with the, with the move to ESPN, I'm thinking more about, uh, you know, working with them on sports type projects, which is something having mostly cover politics. The past four or five years I've, I've kind of a lot of pent up ideas. So you know, looking at things in basketball for example, you have a team of five players and solving the problem of, of who takes the shot, when is the guy taking a good shot? >>Cause the shot clock's running out. When does a guy stealing a better opportunity from, from one of his teammates. Question. We want to look at, um, you know, we have the world cup the summer, so soccer is an interest of mine and we worked in 2010 with ESPN on something called the soccer power index. So continuing to improve that and roll that out. Um, you know, obviously baseball is very analytics rich as well, but you know, my near term focus might be on some of these sports projects. Yeah. So that the, I have to ask you a followup on the, on the soccer question. Is that an individual level? Is that a team level of both? So what we do is kind of uh, uh, one problem you have with the national teams, the Italian national team or Brazilian or the U S team is that they shift their personnel a lot. >>So they'll use certain guys for unimportant friendly matches for training matches that weren't actually playing in Brazil next year. So the system soccer power next we developed for ESPN actually it looks at the rosters and tries to make inferences about who is the a team so to speak and how much quality improvement do you have with them versus versus, uh, guys that are playing only in the marginal and important games. Okay. So you're able to mix and match teams and sort of predict on your flow state also from club league play to make inferences about how the national teams will come together. Um, but soccer is a case where, where we're going into here where we had a lot more data than we used to. Basically you had goals and bookings, I mean, and yellow cards and red cards and now you've collected a lot more data on how guys are moving throughout the field and how many passes there are, how much territory they're covering, uh, tackles and everything else. So that's becoming a lot smarter. Excellent. All right, Nate, I know you've got to go. I really appreciate the time. Thanks for coming on. The cube was a pleasure to meet you. Great. Thank you guys. All right. Keep it right there, everybody. We'll be back with our next guest. Dave Volante and Jeff Kelly. We're live at the Tableau user conference. This is the cube.

>>Okay. We're back here, live in New York city for big data week. This is siliconangle.tvs, exclusive coverage of Hadoop world strata plus Hadoop world big event, a big data week. And we just wrote a blog post on siliconangle.com calling this the south by Southwest for data geeks and, and, um, it's my prediction that this is going to turn into a, quite the geek Fest. Uh, obviously the crowd here is enormous packed and an amazing event. And, uh, we're excited. This is siliconangle.com. I'm the founder John ferry. I'm joined by cohost update >>Volante of Wiki bond.org, where people go for free research and peers collaborate to solve problems. And we're here with Jack Norris. Who's the vice president of market marketing at map are a company that we've been tracking for quite some time. Jack, welcome back to the cube. Thank you, Dave. I'm going to hand it to you. You know, we met quite a while ago now. It was well over a year ago and we were pushing at you guys and saying, well, you know, open source and nice look, we're solving problems for customers. We got the right model. We think, you know, this is, this is our strategy. We're sticking to it. Watch what happens. And like I said, I have to hand it to you. You guys are really have some great traction in the market and you're doing what you said. And so congratulations on that. I know you've got a lot more work to do, but >>Yeah, and actually the, the topic of openness is when it's, it's pretty interesting. Um, and, uh, you know, if you look at the different options out there, all of them are combining open source with some proprietary. Uh, now in the case of some distributions, it's very small, like an ODBC driver with a proprietary, um, driver. Um, but I think it represents that that any solution combining to make it more open is, is important. So what we've done is make innovations, but what we've made those innovations we've opened up and provided API. It's like NFS for standard access, like rest, like, uh, ODBC drivers, et cetera. >>So, so it's a spectrum. I mean, actually we were at Oracle open world a few weeks ago and you listen to Larry Ellison, talk about the Oracle public cloud mix of actually a very strong case that it's open. You can move data, it's all Java. So it's all about standards. Yeah. And, uh, yeah, it from an opposite, but it was really all about the business value. That's, that's what the bottom line is. So, uh, we had your CEO, John Schroeder on yesterday. Uh, John and I both were very impressed with, um, essentially what he described as your philosophy of we, we not as a product when we have, we have customers when we announce that product and, um, you know, that's impressive, >>Is that what he was also given some good feedback that startup entrepreneurs out there who are obviously a lot of action going on with the startup community. And he's basically said the same thing, get customers. Yeah. And that's it, that's all and use your tech, but don't be so locked into the tech, get the cutters, understand the needs and then deliver that. So you guys have done great. And, uh, I want to talk about the, the show here. Okay. Because, uh, you guys are, um, have a big booth and big presence here at the show. What, what did you guys are learning? I'll say how's the positioning, how's the new news hitting. Give us a quick update. So, >>Uh, a lot of news, uh, first started, uh, on Tuesday where we announced the M seven edition. And, uh, yeah, I brought a demo here for me, uh, for you all. Uh, because the, the big thing about M seven is what we don't have. So, uh, w we're not demoing Regents servers, we're not demoing compactions, uh, we're not demoing a lot of, uh, manual administration, uh, administrative tasks. So what that really means is that we took this stack. And if you look at HBase HBase today has about half of dupe users, uh, adopting HBase. So it's a lot of momentum in the market, uh, and, you know, use for everything from real-time analytics to kind of lightweight LTP processing. But it's an infrastructure that sits on top of a JVM that stores it's data in the Hadoop distributed file system that sits on a JVM that stores its data in a Linux file system that writes to disk. >>And so a lot of the complexity is that stack. And so as an administrator, you have to worry about how data gets permit, uh, uh, you know, kind of basically written across that. And you've got region servers to keep up, uh, when you're doing kind of rights, you have things called compactions, which increased response time. So it's, uh, it's a complex environment and we've spent quite a bit of time in, in collapsing that infrastructure and with the M seven edition, you've got files and tables together in the same layer writing directly to disc. So there's no region servers, uh, there's no compactions to deal with. There's no pre splitting of tables and trying to do manual merges. It just makes it much, much simpler. >>Let's talk about some of your customers in terms of, um, the profile of these guys are, uh, I'm assuming and correct me if I'm wrong, that you're not selling to the tire kickers. You're selling to the guys who actually have some experience with, with a dupe and have run into some of the limitations and you come in and say, Hey, we can solve some of those problems. Is that, is that, is that right? Can you talk about that a little bit >>Characterization? I think part of it is when you're in the evaluation process and when you first hear about Hadoop, it's kind of like the Gartner hype curve, right. And, uh, you know, this stuff, it does everything. And of course you got data protection, cause you've got things replicated across the cluster. And, uh, of course you've got scalability because you can just add nodes and so forth. Well, once you start using it, you realize that yes, I've got data replicated across the cluster, but if I accidentally delete something or if I've got some corruption that's replicated across the cluster too. So things like snapshots are really important. So you can return to, you know, what was it, five minutes before, uh, you know, performance where you can get the most out of your hardware, um, you know, ease of administration where I can cut this up into, into logical volumes and, and have policies at that whole level instead of at an individual file. >>So there's a, there's a bunch of features that really resonate with users after they've had some experience. And those tend to be our, um, you know, our, our kind of key customers. There's a, there's another phase two, which is when you're testing Hadoop, you're looking at, what's possible with this platform. What, what type of analytics can I do when you go into production? Now, all of a sudden you're looking at how does this fit in with my SLS? How does this fit in with my data protection, uh, policies, you know, how do I integrate with my different data sources? And can I leverage existing code? You know, we had one customer, um, you know, a large kind of a systems integrator for the federal government. They have a million lines of code that they were told to rewrite, to run with other distributions that they could use just out of the box with Matt BARR. >>So, um, let's talk about some of those customers. Can you name some names and get >>Sure. So, um, actually I'll, I'll, I'll talk with, uh, we had a keynote today and, uh, we had this beautiful customer video. They've had to cut because of times it's running in our booth and it's screaming on our website. And I think we've got to, uh, actually some of the bumper here, we kind of inserted. So, um, but I want to shout out to those because they ended up in the cutting room floor running it here. Yeah. So one was Rubicon project and, um, they're, they're an interesting company. They're a real-time advertising platform at auction network. They recently passed a Google in terms of number one ad reach as mentioned by comScore, uh, and a lot of press on that. Um, I particularly liked the headline that mentioned those three companies because it was measured by comScore and comScore's customer to map our customer. And Google's a key partner. >>And, uh, yesterday we announced a world record for the Hadoop pterosaur running on, running on Google. So, um, M seven for Rubicon, it allows them to address and replace different point solutions that were running alongside of Hadoop. And, uh, you know, it simplifies their, their potentially simplifies their architecture because now they have more things done with a single platform, increases performance, simplifies administration. Um, another customer is ancestry.com who, uh, you know, maybe you've seen their ads or heard, uh, some of their radio shots. Um, they're they do a tremendous amount of, of data processing to help family services and genealogy and figure out, you know, family backgrounds. One of the things they do is, is DNA testing. Uh, so for an internet service to do that, advanced technology is pretty impressive. And, uh, you know, you send them it's $99, I believe, and they'll send you a DNA kit spit in the tube, you send it back and then they process that and match and give you insights into your family background. So for them simplifying HBase meant additional performance, so they could do matches faster and really simplified administration. Uh, so, you know, and, and Melinda Graham's words, uh, you know, it's simpler because they're just not there. Those, those components >>Jack, I want to ask you about enterprise grade had duped because, um, um, and then, uh, Ted Dunning, because he was, he was mentioned by Tim SDS on his keynote speech. So, so you have some rockstars stars in the company. I was in his management team. We had your CEO when we've interviewed MC Sri vis and Google IO, and we were on a panel together. So as to know your team solid team, uh, so let's talk about, uh, Ted in a minute, but I want to ask you about the enterprise grade Hadoop conversation. What does that mean now? I mean, obviously you guys were very successful at first. Again, we were skeptics at first, but now your traction and your performance has proven this is a market for that kind of platform. What does that mean now in this, uh, at this event today, as this is evolving as Hadoop ecosystem is not just Hadoop anymore. It's other things. Yeah, >>There's, there's, there's three dimensions to enterprise grade. Um, the first is, is ease of use and ease of use from an administrator standpoint, how easy does it integrate into an existing environment? How easy does it, does it fit into my, my it policies? You know, do you run in a lights out data center? Does the Hadoop distribution fit into that? So that's, that's one whole dimension. Um, a key to that is, is, you know, complete NFS support. So it functions like, uh, you know, like standard storage. Uh, a second dimension is undependability reliability. So it's not just, you know, do you have a checkbox ha feature it's do you have automated stateful fail over? Do you have self healing? Can you handle multiple, uh, failures and, and, you know, automated recovery. So, you know, in a lights out data center, can you actually go there once a week? Uh, and then just, you know, replace drives. And a great example of that is one of our customers had a test cluster with, with Matt BARR. It was a POC went on and did other things. They had a power field, they came back a week later and the cluster was up and running and they hadn't done any manual tasks there. And they were, they were just blown away to the recovery process for the other distributions, a long laundry list of, >>So I've got to ask you, I got to ask you this, the third >>One, what's the third one, third one is performance and performance is, is, you know, kind of Ross' speed. It's also, how do you leverage the infrastructure? Can you take advantage of, of the network infrastructure, multiple Knicks? Can you take advantage of heterogeneous hardware? Can you mix and match for different workloads? And it's really about sharing a cluster for different use cases and, and different users. And there's a lot of features there. It's not just raw >>The existing it infrastructure policies that whole, the whole, what happens when something goes wrong. Can you automate that? And then, >>And it's easy to be dependable, fast, and speed the same thing, making HBase, uh, easy, dependable, fast with themselves. >>So the talk of the show right now, he had the keynote this morning is that map. Our marketing has dropped the big data term and going with data Kozum. Is that true? Is that true? So, Joe, Hellerstein just had a tweet, Joe, um, famous, uh, Cal Berkeley professor, computer science professor now is CEO of a startup. Um, what's the industry trifecta they're doing, and he had a good couple of epic tweets this week. So shout out to Joe Hellerstein, but Joel Hellison's tweet that says map our marketing has decided to drop the term big data and go with data Kozum with a shout out to George Gilder. So I'm kind of like middle intellectual kind of humor. So w w w what's what's your response to that? Is it true? What's happening? What is your, the embargo, the VP of marketing? >>Well, if you look at the big data term, I think, you know, there's a lot of big data washing going on where, um, you know, architectures that have been out there for 30 years or, you know, all about big data. Uh, so I think there's a, uh, there's the need for a more descriptive term. Um, the, the purpose of data Kozum was not to try to coin something or try to, you know, change a big data label. It was just to get people to take a step back and think, and to realize that we are in a massive paradigm shift. And, you know, with a shout out to George Gilder, acknowledging, you know, he recognized what the impact of, of making available compute, uh, meant he recognized with Telekom what bandwidth would mean. And if you look at the combination of we've got all this, this, uh, compute efficiency and bandwidth, now data them is, is basically taking those resources and unleashing it and changing the way we do things. >>And, um, I think, I think one of the ways to look at that is the new things that will be possible. And there's been a lot of focus on, you know, SQL interfaces on top of, of Hadoop, which are important. But I think some of the more interesting use cases are taking this machine J generated data that's being produced very, very rapidly and having automated operational analytics that can respond in a very fast time to change how you do business, either, how you're communicating with customers, um, how you're responding to two different, uh, uh, risk factors in the environment for fraud, et cetera, or, uh, just increasing and improving, um, uh, your response time to kind of cost events. We met earlier called >>Actionable insight. Then he said, assigning intent, you be able to respond. It's interesting that you talk about that George Gilder, cause we like to kind of riff and get into the concept abstract concepts, but he also was very big in supply side economics. And so if you look at the business value conversation, one of things we pointed out, uh, yesterday and this morning, so opening, um, review was, you know, the, the top conversations, insight and analytics, you know, as a killer app right now, the app market has not developed. And that's why we like companies like continuity and what you guys are doing under the hood is being worked on right at many levels, performance units of those three things, but analytics is a no brainer insight, but the other one's business value. So when you look at that kind of data, Kozum, I can see where you're going with that. >>Um, and that's kind of what people want, because it's not so much like I'm Republican because he's Republican George Gilder and he bought American spectator. Everyone knows that. So, so obviously he's a Republican, but politics aside, the business side of what big data is implementing is massive. Now that I guess that's a Republican concept. Um, but not really. I mean, businesses is, is, uh, all parties. So relative to data caused them. I mean, no one talks about e-business anymore. We talking to IBM at the IBM conference and they were saying, Hey, that was a great marketing campaign, but no one says, Hey, uh, you and eat business today. So we think that big data is going to have the same effect, which is, Hey, are you, do you have big data? No, it's just assumed. Yeah. So that's what you're basically trying to establish that it's not just about big. >>Yeah. Let me give you one small example, um, from a business value standpoint and, uh, Ted Dunning, you mentioned Ted earlier, chief application architect, um, and one of the coauthors of, of, uh, the book hoot, which deals with machine learning, uh, he dealt with one of our large financial services, uh, companies, and, uh, you know, one of the techniques on Hadoop is, is clustering, uh, you know, K nearest neighbors, uh, you know, different algorithms. And they looked at a particular process and they sped up that process by 30,000 times. So there's a blog post, uh, that's on our website. You can find out additional information on that. And I, >>There's one >>Point on this one point, but I think, you know, to your point about business value and you know, what does data Kozum really mean? That's an incredible speed up, uh, in terms of, of performance and it changes how companies can react in real time. It changes how they can do pattern recognition. And Google did a really interesting paper called the unreasonable effectiveness of data. And in there they say simple algorithms on big data, on massive amounts of data, beat a complex model every time. And so I think what we'll see is a movement away from data sampling and trying to do an 80 20 to looking at all your data and identifying where are the exceptions that we want to increase because there, you know, revenue exceptions or that we want to address because it's a cost or a fraud. >>Well, that's what I, I would give a shout out to, uh, to the guys that digital reasoning Tim asked he's plugged, uh, Ted. It was idolized him in terms of his work. Obviously his work is awesome, but two, he brought up this concept of understanding gap and he showed an interesting chart in his keynote, which was the date explosion, you know, it's up and, you know, straight up, right. It's massive amount of data, 64% unstructured by his calculation. Then he showed out a flat line called attention. So as data's been exploding over time, going up attention mean user attention is flat with some uptick maybe, but so users and humans, they can't expand their mind fast enough. So machine learning technologies have to bridge that gap. That's analytics, that's insight. >>Yeah. There's a big conversation now going on about more data, better models, people trying to squint through some of the comments that Google made and say, all right, does that mean we just throw out >>The models and data trumps algorithms, data >>Trumps algorithms, but the question I have is do you think, and your customer is talking about, okay, well now they have more data. Can I actually develop better algorithms that are simpler? And is it a virtuous cycle? >>Yeah, it's I, I think, I mean, uh, there are there's, there are a lot of debate here, a lot of information, but I think one of the, one of the interesting things is given that compute cycles, given the, you know, kind of that compute efficiency that we have and given the bandwidth, you can take a model and then iterate very quickly on it and kind of arrive at, at insight. And in the past, it was just that amount of data in that amount of time to process. Okay. That could take you 40 days to get to the point where you can do now in hours. Right. >>Right. So, I mean, the great example is fraud detection, right? So we used the sample six months later, Hey, your credit card might've been hacked. And now it's, you know, you got a phone call, you know, or you can't use your credit card or whatever it is. And so, uh, but there's still a lot of use cases where, you know, whether is an example where modeling and better modeling would be very helpful. Uh, excellent. So, um, so Dana custom, are you planning other marketing initiatives around that? Or is this sort of tongue in cheek fun? Throw it out there. A little red meat into the chum in the waters is, >>You know, what really motivated us was, um, you know, the cubes here talking, you know, for the whole day, what could we possibly do to help give them a topic of conversation? >>Okay. Data cosmos. Now of course, we found that on our proprietary HBase tools, Jack Norris, thanks for coming in. We appreciate your support. You guys have been great. We've been following you and continue to follow. You've been a great support of the cube. Want to thank you personally, while we're here. Uh, Matt BARR has been generous underwriter supportive of our great independent editorial. We want to recognize you guys, thanks for your support. And we continue to look forward to watching you guys grow and kick ass. So thanks for all your support. And we'll be right back with our next guest after this short break. >>Thank you. >>10 years ago, the video news business believed the internet was a fat. The science is settled. We all know the internet is here to stay bubbles and busts come and go. But the industry deserves a news team that goes the distance coming up on social angle are some interesting new metrics for measuring the worth of a customer on the web. 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