 Live from New York, it's theCUBE. Covering Big Data New York City, 2016. Brought to you by headline sponsors, Cisco, IBM, NVIDIA, and our ecosystem sponsors. Now here's your host, Dave Vellante. We're back in New York City. This is day four of Big Data NYC. We run Big Data NYC Concurrent to Strata plus Hadoop World. This is the seventh year that theCUBE has been at Hadoop World. Peter Burst is here with me, Jeff Frick, and we have a special guest, Abhi Mehta, is here, he's the founder and CEO of Trasada. Abhi, great, what a surprise, seeing you pop in. Boom, always for the, always at the ready. I gave you forewarning yesterday, but yes. Right, I tweeted you, I said, stop by, you did, perfect, perfect time, it couldn't be better. Thank you for having me, as always. So, you're welcome, and you know, down memory lane, John Furrier and I, remember our first Hadoop World, which was the second ever Hadoop World. You were our top guest that time, and you continue to be one of our top guests. Thank you. So, take us back, seven years ago, you were at B of A, and you were sort of educating us all on what this Hadoop thing was, knowing that there was something else coming, so. Yes, a lot of good things coming. Like a loss leader, or bait and switch, which one is that? No, neither, it was foretelling the future. It is refreshing to see, first of all, not just the success that the communities had, success all of us have had, because I remember theCUBE, you know, the desk of two, there was no tablecloth at the time, but it's just refreshing to see that we have built successfully, Truseta, theCUBE, and a complete community on open source, a technology that we had set at the time will revolutionize the world. The business world, not the technology world, and seeing those predictions come true is very, very fulfilling, because it's always bad to be early in a fool, but it's really good to be early and right, and it's really good to see the success of the community at large. I don't think even with our confidence that this new tech revolution will enable an industrial revolution like none other, is I would not have predicted how big it will become so quickly, because seven years in tech life is seven minutes. Well, I think it's gone totally mainstream, but what do you make of the semi-backlash, right? People writing about how big data hasn't lived up to their promises, people struggling, the ecosystem is so complex. Not just people, us. Especially Peter. So what do you make of that, right? The ecosystem is fragmented, complexity, yet another project, you know, Cloudera and Hortonworks struggled to keep up with all the committers. Nobody's making any money, except maybe you guys. Yes, pretty much. I like to take a step back, Dave, like I think we do so well, and look at the big picture. And I think the big picture at least continues to inform me and embolden me personally and then to see it as a company around what would the emerging business models be? I think that's the question, right? I think that's what Peter, and I love talking to Peter because he challenges me and I like, I love getting challenged. I think what we haven't discussed enough is what will the emerging business models be? Not just for industry, but for technology. So if I take a step back and I go back to our original prediction, second industrial revolution, data is the new fuel, and it'll be trillions of dollars of value. We had said seven years ago that this revolution will be trillions of dislocation, not billions, right? And we are absolutely right. So if you look back at that concept of an industrial revolution, all revolutions are fueled by three main things. Technology, talent, and tools. In every revolution that the world has seen, you can just be the second or third doesn't really matter, you can never charge for technology. Technology by its very nature to fuel a revolution has to be free, has to be open, and easily available. And what we are seeing early on in this phase is the technology powering the revolution, people are struggling to make money on, as you should. Because where the money sits in revolutions, and if you remember the gold rush in California, you didn't make money digging for gold, you made money selling shovels. So when you think about what powers revolutions, the tools and the talent are yet to emerge. Because it's hard, it's hard to figure out the tooling using technology on where the value will be added. So technology is gonna be free. It's plentiful. The technology has to be splentiful, it has to be open, the standards have to be set, which I think the ecosystems are a really good job with those dynamics of technology, but you can't make money in revolutions on technology. The money sits in tools and talent. And that's where we have been successful. We were very early on that said I will not commercialize any technology that should be the foundation or utilitarian in nature. So whether it's databases, security, algorithms, they're all free, we've said publicly many times before. But the combination of all of them and the tools to enable automation of anti-money laundering, automation of population health, automation of self-driving cars and transportation, that's where the money sits and we haven't yet seen the emergence in the technology industry of the tools. That is where the commercialization and the rubber will hit the road. Because in technology, and I love, it's very hard to make money in open source, if not impossible. Only one company's proven it, Red Hat. Red Hat of everything. Of everything. And my prediction, since day zero has been, in fact, we actually discussed this seven years ago, you'd ask me what happens to the Hadoop ecosystem, which is the player you want to see emerge, and I said Red Hat should be the player. And I think we may yet see that. Yeah, Red Hat will be the Red Hat of... Big data, yeah. Or big data, yeah, exactly, Hadoop or whatever the technology trend may be. But we have to remember that industrial evolution's by its very nature, the underlying technology is utilitarian in its use and cannot be commercialized as a business model. The other thing we said was that the practitioners are going to make the trillions. Absolutely. Your customers are really the ones that are really going to drive a lot of the value. Because every single business model will be redone. We entered healthcare six months ago. So now we've got the perfect storm for Trasera, right? We had wealth figured out, we have health figured out, what else is there worry about in humanity, right? So the two biggest things in humanity, health and wealth. Well, the wealth is going into the... And the wealth is going into the... The wealth is going into the... But to your point, both, I'm sorry, my apologies, but to your point, every single healthcare model will get redone. Every single banking model, every single transportation, telecommunications, retail will get redone on the fundamentals of those three things, technology, talent and tools. And I think the people who create the tools will be incredibly successful and make a lot of money. But the difference between evolution and revolution is what? The leaders get knocked out. Yes, of course they do. And so you said revolution many, many times. And yet we're seeing some of the old incumbents try to make the move so they don't kick that. I mean, last night at the IBM thing, or two nights ago, Pichiano said, we're going to innovate at the speed of open source. Wow, who would have thought that? Rich, he led this incredible presentation in a nature event with that statement. I'm taking it all in. So look, I think, first of all, I don't fundamentally disagree with most of what you're saying, but if we put it in perspective of what's happening right now. Yes. First off, the whole thing, the thing you're really saying is talent, technology and tools all boil down to, once you develop the intellectual property, how does it get commercialized? Because all three of them represent intellectual property. A technology is a codification of intellectual property. A tool is a codification of a method, intellectual property. You determine whether or not somebody has talent based on whether or not they can enact the intellectual property. So it's all intellectual property. So really what you're saying is that technology, intellectual property, which is the infrastructure, which is the baseline pieces, and we'll see. We're still going to see people make money. But we're talking about, if we're talking about, as you said, and I don't think you're too far off, $30 trillion, $40 trillion economy, whatever it is, and we're talking about in the next 10 years, some percentage of that being disrupted and probably more than a trillion when you come right down to it, that we're not going to see 500 billion of that end up in technology companies. But we will see tens and 20s and 50s and maybe even 100 billions of dollars end up in technology companies. But the vast majority will be in the tooling because the tooling is how we diffuse the intellectual property that we create with talent. And so if we think about what's got to happen and our basic thesis right now about open source is actually quite simple. And we had some people on who kind of vehemently disagreed with us and put their fists up at me, but no, we'll see what happens. We're sticking to it. But the bottom line is that in the historical open source model, you had, you had a, at least, let's talk about Linux. In the Linux model, you had millions of people who understood what Unix was. Significant experience about the use case of a Unix operator. Very comfortable with adopting Linux. Exactly. They didn't need a lot of help with your point. They didn't need a lot of help and they were more than happy to underwrite the diffusion profits of the intellectual property associated with Linux. Same thing with Jboss. And a billion dollars from IBM help too, back when a billion dollars was really a lot of money. Yes, a billion was a lot of money. Here's the challenge and my concern, our concern, because we agree, we think that this is an incredibly important undertaking and we think we'll get through it. But there's a rough patch right now because of the presumption that there are similarly large numbers of individuals with talent. There was talent in the Unix world. There's not as much talent in the big data world. And so the open source model is struggling because it doesn't fund that approach to how you diffuse that intellectual property because the tools aren't there yet. They're getting there. And Peter, you just reinforced my point. By the way, I completely agree with you. Everything, and I'm glad that people are holding back their punches or not holding back their punches because the very nature of dislocations, we are undergoing a massive dislocation. This is Galapagos for technology because the biggest thing technology was built on the last 50 years is under threat. Every single thing that I, at least you know, you are younger than I am, Dave, at least I built my career on, storage, databases, analytical tools, visualization, or BI is up for grabs because fundamentally, and I offer a small edit toward Mark Andreessen said, software will lead the world. I see open source software will lead the world. Utilitarian pieces or utilitarian parts of the revolution utilitarian parts of the revolution have to live on very thin margins. So yes, will there be billions in the technology layer of the next revolution? Absolutely. Will it be a high margin, high profit business? No, it won't. It's not supposed to be. Because what you're doing with technology and building a technology is highly capital intensive to feed and fuel a revolution whether you wanna call it, you know, laying down the train tracks for tool vendors to live on, that just takes time. The reason on talent changes. So I have said this multiple times, three big parts of the large GDP, any global GDP economic system, agriculture, manufacturing and services. Whenever a tier of our economic system got machined, it moved to the next tier. It's been 50 years since we had our last large machining. It was called manufacturing automation. What we are seeing is the beginnings of a service industry automation. So the talent problem will not get solved by adding more people or just retraining them. It will get solved with what we call a twist on AI, augmented intelligence, whether it's almost like augmented human being. We will have things that will make someone as smart as Dave, even smarter, dramatically increase productivity by automating simple, incredibly utilitarian and common sense tasks. It started already, right? Email, calendar, reminders for birthdays. Airport kiosks. Airport kiosks. But see, here's where we gotta be careful about this. And I know you don't, we gotta be a little bit careful about time. This would be a great, great top to continue at some point in time. At the end of the day, Dave's, the determination of how smart Dave is, is still a relative determination. Of course it is. When everybody has access to the same tools, everybody gets picked, everybody is lifted. Absolutely. And so this is my concern about the whole notion of automation. We will automate certain tasks, but those tasks will be automated for everybody and everybody's gonna get a chance to pick up their game. Maybe I'm the glass, always the glass half full guy, but I look at, oh actually, and this is not even a glass anymore, this is a cauldron, you know, of just immense innovation. I call it, I look at the other side of it and say if we are able to lift humanity's intelligence, humanity's productivity, we are gonna see a renaissance. We are gonna be able to solve problems that have been cracktable. Exactly. Since time immemorial. That's the most, that's the bottom line. That excites me. And it's a renaissance that our kids will live in an era of wealth and health, sorry, I keep going back to the same thing, that we can only imagine today. And it excites me. It excites me to look at Truseta as a player that can enable it. We are very early by the way because even we can't comprehend today. If open source becomes this massive platform that can enable tools and talent to collectively raise the bar, right? A rising tide lifts all boats. This is gonna be a creation of economic wealth like never before. Not just money, but true social economic wealth. And I'm very excited about it. And humans will be part of that. We have to go, but I'll close with the story of Gary Kasparov when he lost to the supercomputer, the deep blue, instead of giving up, he said I'm gonna beat the computer and how he did it was he got his own supercomputer and he put it together with humans. Exactly. Each year they get together and there's a contest, right? And the best chess player in the world is not a computer. It's a human plus a computer. I think just to my last point on that, that's why I think AI needs to be redefined as augmented intelligence or artificial. Nothing about this revolution is artificial. It's very real, it's very human. We have to remember big data is about making life easier and better and cheaper and faster and more prolific for human beings. And we forget that in these technology conversations we have because the technology is gonna be free and massive and a standardized way in a utilitarian way that we haven't seen before. But if we forget, how can we solve problems and make human life better? Our motto at Truseta, we are buried at three years ago, is enrich life. That's what I wanna be known for. I wanna be known for out thinking somebody. I wanna be known for creating ways to go into water vapor. I wanna be known for enriching life. And that's our motto in mission. Hey, thanks so much my friend for stopping by. It's really a pleasure. Absolutely, thanks for having me. Always a blast. You're welcome, all right. This is theCUBE, the worldwide leader in live tech coverage. We'll be right back. Making life better. And I'll see, right after this word.