 I'm John Furrier, the founder of SiliconANGLE.com. This is SiliconANGLE.tv's theCUBE. It's our flagship telecast where we go out with our HD studio to the top tech events and we talk to the smartest people we can find, the smart nodes. We extract the signal from the noise and share that with you and hope we can change the world with our content. And we would not be here without the support of O'Reilly Media and O'Reilly Media is headed out by Tim O'Reilly, the founder of O'Reilly Media. Tim, welcome back to theCUBE again. Strata year two. Yeah, thanks. And Dave Vellante, my co-host. I want to just ask you, you're rolling in Strata as a huge success. Your team's done a great job. It's been a fantastic conference. Range of topics from business, changing the business and society to the tech conversations from innovations around Hadoop and then also the existing players like Data Warehouse and Business Intelligence. So it's been fantastic. My first question to you is what are you thinking about these days? I know you've been doing a lot of traveling and Strata is again about big data, changing society, all kinds of themes here from government, changing society, social media, changing elections, possibly things like Twitter, Facebook, et cetera. What are you thinking about these days? What's on your mind? Well, one of the things I have been chewing on a lot lately is a piece that I read back in the 70s called The Closed Line Paradox by a guy named Steve Bayer. It was published in Stuart Brand's Co-Ovolution Quarterly and it stuck in my mind. It came up again recently and it was a piece about alternative energy and it made the case that we were undercounting the impact of renewables in our energy economy. Of course, this is what 30 plus years ago and it used a humble analogy. It said when somebody decides not to put their clothes in the dryer and instead hangs them on the clothesline, it doesn't move from our fossil fuel column of our accounting to our renewables column, it just disappears from our accounting. And the point was that our accounting doesn't necessarily match the real world. And this occurred to me recently in thinking about our economy in a variety of contexts. I was very engaged with the SOPA Pipe of Protests, for example, and it struck me that the movie industry and the record industry were trotting out all kinds of what seemingly fairly bogus statistics about the economic impact of piracy. And on the internet side, we were talking about freedom. And I said, no, actually, we need to talk about the economic side too. What is this new economy that's growing up on the internet for, for example, music creators who are making money on YouTube or with live events? It's kind of like the clothesline paradox. It's showing up in places that are not being counted. And I've been thinking about that also around this notion that I have kind of a slogan we have at O'Reilly, create more value than you capture. You know, we have, you know, it's a terrific example in Goldman Sachs and other financial firms leading up to the crash of 2008 of companies that were extracting enormous amounts of value from the economy, but clearly actually destroying value for the economy as a whole. On the other hand, you have things like the web created by Tims Berners-Lee, put in the public domain or open source software, which have created enormous value and yet not a lot of value capture. And we kind of tend to disc, you know, we talk about innovation and we talk about value creation, but we don't actually measure it. You know, so how, you know, all we measure is the capture by people. You know, so if you ask people to quantify the open source economy, they might say, well, you know, Red Hat's such and such size company and MySQL was so such and such size before it got bought and, you know, and of course would totally miss the point of all these companies that exist because of this open source software. And so I think the same thing applies to a lot of what's happening with Strata. We're starting to build all kinds of new services using data. Some of those data services have been well monetized. Other ones are still very much in their infancy. And if you look at that sort of curve of value creation versus value capture, we need to get a lot better at understanding that ultimately you will be able to capture value downstream from this creation. It might be captured by different people, but I'm trying to rethink the economy. You just might not be able to count it. You know, we just came up with a study at Wikibon. It was sort of a tongue in cheek to quantify the size of the big data market because nobody else was doing it. So we did it. And of course, you know how we did it. We did the value capture. We counted up the value capture and quickly realized that it's virtually impossible to count this stuff because the value creation is so enormous. Right, but what you can do is you can start to, you know, if, particularly if you show your work, you know, which then helps people to evaluate, you know, are you thinking in a reasonable way? You can, you can draw some assumptions. So an example, I recently, I was working with a company called Bluehost, which is a web hosting firm. And, you know, they're looking at the notion they've been able to deliver low cost services to small and medium sized businesses because they're able to use this free open source software. And, you know, there's actually, there are studies of the economic impact to a small business of having a web presence. You know, people can measure that and count that. So you can work backwards. And so we're talking about putting together a study based on their customer base that would allow us to say, okay, here is an economic impact from the use of open source software. Tim, let's talk about that a little further. Let's riff on that concept of value creation. And, you know, you're a little bit older than I am, but we've all seen the cycles before. I mean, I remember when I was in college in the 80s, you know, studying computer science and systems programming. That was really the generation of that PC revolution. And I've heard you talk many times about the PC revolution, talking about Microsoft and all the stuff that industry that was created. It was the PC industry. It was really a group of people that started that industry and it grew up together and created a lot of different value for people. Then you had little cycles of innovation, client server, the web, and now we're kind of in this mobile craze and cloud mobile social. But, with big data, Dave and I were talking with our guests this week, talking about how big data seems to be a new industry by itself because of the massive innovations and value it creates. And that it's kind of comparable to the PC revolution in a sense that we have no other way to draw an analogy to it. So, it feels like that now. Is that, what's your perspective on where we are with big data? Because it's not just one industry, it's not just the computer industry, it's not just tech, it's a lot of things. It's everything, quite honestly. As we realize that, as we're really moving into this era of a networked economy, we've used that term for decades, but each decade it becomes more true. You realize just how much data is the currency of that economy. It's the currency of science, it's the currency of entertainment, it's the currency of business. And so, in one sense, Strata is about the infrastructure and the tools that support that entire economy. So, in that sense it's sort of like having a computing conference. It's like computers are now part of everything. You can't buy a device that's not a computer. So to your point about the clothesline effect there, there's always, you can look at any kind of business analogy or whatever, there's always a ramp up before you can really harvest and that's a risk on business. You have to ramp up to grow with growth. You have challenges. So, how do we start establishing some accounting and we're in this ramp of innovation and invention, not just within Silicon Valley, but globally, with data because, we're talking to Avi Mehta, one of your speakers here about just the fraud data capture, a data creation value around what that impacts. It's trillions of dollars. It's not just 50 billion as we fork asset and the big data market size. So, it has to be a ramp in the community. That's an expense if you want to look at it that way, but it's a cost and it's an innovation cost and then it'll kick in to some harvest. So, where are we, what's your perspective on that? And because it has to be accounted for and you can talk about SOPA, these things kind of play into that. Yeah. Well, maybe I'll take this in a slightly different direction. There are, I forget who it was, Corey Doctor quotes this line and I always forget who said it originally, which is every complex system has its parasites. Very complex ecosystem has its parasites. And when you look at the value that's being created, there are people who are free riders. There are people who are outright pirates. One of my favorite comments to, in the subject of piracy comes up, the real pirates are probably patent trolls. If you look at the real negative impact on our economy and from a tech point of view, you look at the way that financial firms became pirates, whereas the people who are often referred to as a betters of piracy by the music industry are actually enabling this new value economy that just hasn't been measured yet. So, I think we're in this really interesting phase where there are all kinds of claims and counterclaims about who's creating value and who's destroying it. And probably the most important thing to recognize in a phase like that is that we don't really know the answers yet. I think Larry Lessig made this point way back when he wrote his first book, A Code and Other Laws of Cyberspace, which was simply to emphasize that let's not get the legal system involved, let's not write new laws until we let things run for a while and we understand exactly how this is going to evolve. Last year on theCUBE, when we were here at Strata, it was the inaugural event, you were pretty humble. You said, I'm just a trend spotter and I kind of make observations from the cheap seats. I think it was your line. I think you want to give you- Good memory there. I've seen it so many times and I get so many comments on email from our audience. But I want to give you a little credit. I kind of view you as a social scientist because you have the intellectual and all practical experience, but also we're living in an age where social science is intersecting with computer science. That's the motto, Silicon Angle. And one of the things that Dave Vellante and I are tracking right now is as we move from this Wild West social web where anonymous, people are anonymous, you have anonymous hackers, there's a trend around identity and trust now becoming mainstream where this new generations of users are looking at trust paradigms where identity and trust is fundamentally a core tenant now in the equation. I know you have a lot of discussions in the past around identity and trust, but how is that playing out today? And what do you see identity and trust playing in the future around, as big data analytics makes the world more transparent, society is measurable now in an instrument. We can actually instrument a global society and actually see behavior. And so trust and identity take a whole new dimension. What's your perspective on this? You know, kind of got some new thoughts. I was just down at TED and Reed Hoffman gave a talk there about the shift from the information age to the network age. And the contrast he gave was that, you know, we used to just sort of collect information and now we actually have to see networks. And trust is a great example of that. You know, you can try to measure and model trust by collecting a lot of information about someone, or you can measure and model trust by looking at the network of other people who trust them. But, you know, that's also a kind of information. But I think we're still in the early stages of moving out of, you know, kind of the model of, you know, we're establishing a history for someone based on all of their transactions and into a model where we're understanding more about people on the basis of the networks that they belong to. And I think Reed has sort of been somebody who's seen pretty deeply into that, probably more deeply than other, you know, social networks that are better known than LinkedIn. It's a fascinating conversation. We're here with Tim O'Reilly, the founder of Reilly Media here. It's his conference, Stratoconference, is really changing the world for society. And also for the technology side of it, my final question, and if Dave wants to jump in, it's great if he wants to have some more specific questions, but what are you seeing around data changing the world? Because that always has been kind of a hallway conversation in some sessions here at Strata and a lot of the O'Reilly events that you guys have been, you know, and for us, you do have a good business, it's very profitable and growing rapidly, but your company also gives back to the world, and I know that's a mantra for you guys. But now, as we have- That's self-interest, by the way. You know, if you create a healthy ecosystem and you play a good role in that ecosystem, then you'll do well. And I think one of the things that a lot of companies forget is if you take out more value than you create, the whole ecosystem eventually falls down, and so it's kind of like everything from the environment to the financial crisis to business, really, we forget those simple rules of how to live well. We're talking about human capital involvement in data. We're seeing companies like Accenture and other consulting companies have old models around how they deploy human capital to serve needs to their customers, now with machines and data, there's still a human capital element. We are living in a data economy and data society, and yet there's a lot of public data, but as data becomes the scarce resource that creates value to your point, as more data becomes private, it's less accessible. What trends are you seeing, and what are you watching around data? Well, first off, data doesn't have to be free and public to be valuable for the public good. So, for example, I was talking just the other day with Nathan Wolfe of the Global Virus Forecasting Institute. They're kind of like, and they're becoming a kind of virtual CDC for developing countries that don't have the resources. They're looking at how to turn that into a business, but it's still for the public good, because identifying disease outbreaks through collective intelligence is really valuable. So I think the biggest lesson I would have for anybody who wants to think about the public good is the public good is not just the province of nonprofits and NGOs. The public good is the province of anyone who thinks rightly about creating value in this world. I think of O'Reilly, we're a for-profit company, but we think a lot about creating value in the world. My career has been influenced right out of college in the late 80s by Bill Hewlett and Dave Packard. I went right to HP and they were still around and it's still kind of a little bit older, but still doing the hallway management by walking around. But HP was really at that time, the old HP. Citizenship was really big as part of HP. And citizenship is, you don't hear that in conversation in companies anymore about citizenship. What do we need to do as these private entities acquire data and have real-time capabilities to add value? How does citizenship from in companies, like you said, I agree, you don't have to be a non-profit to add value to the world, is it changing citizenship, changing? Well, absolutely. I mean, look at Kickstarter. What an amazing citizenship engine. It's funny because you can look at a lot of other ways that people are trying to crowdsource social good, but Kickstarter is an amazing one. Here, it's like funding for the arts, you know? It's an astonishing engine. So the internet is throwing up wonderful new examples all the time of ways to be a citizen. You think about that kind of philanthropy that used to be reserved for wealthy people. And now we've crowdsourced that kind of patronage. And I think we've also crowdsourced, to some extent, other kinds of philanthropy. You look at the microlending and the like. Bit by bit, we're finding interesting ways to act as citizens. Jen Palkadena, Ted just gave a great talk about that. And one of her concluding line was, well, she talked specifically about we can't fix government without fixing citizenship. But she ended up with, you know, when it comes to tackling the big problems, do we just want to be a crowd of voices, or do we want to be a crowd of hands? And so crowdsourcing to actually get stuff done is a big element. If we can get that into the accounting, that would be fantastic. I want to throw in a word for, there's a great organization, a great project out of the UN, UN Global Pulse, that's very much lined up with this idea of data for the public good, where they're trying to, you know, gather data from NGOs and from UN activities and create it as a service layer. So I think there's a lot of, there's a lot of people who are thinking about this. If I can change gears, just to draw someone on your personal experience, because you've been in the industry, again, the computer industry, you've been a big part of that and a big contributor of knowledge through O'Reilly Media. But I want to get to draw your perspective as someone who's been in the industry, looking at the big players, the big conglomerates who have made money, a lot of them are here with booths. The data warehousing business intelligence marketplace has been a very big lucrative industry and it's kind of old and being retooled. At the same time, a Greenfield opportunity with Hadoop and Analytics are changing the world for all the good reasons we've been covering here on theCUBE at SiliconANGLE.com. What's your advice to the industry folks who are here, the big whales, the big guys who are trying to evolve with this new trend because they have legacy infrastructure and product state, kind of like the mainframe back in the day, I guess. What's your advice to them? Or is the whole thing a do-over? No, well, I mean, there's a couple of different layers of thinking about it. Is this the technology layer and will they be disrupted by new players using new technology? But I'd like actually to just talk a little bit about how to think about business intelligence and data and the deep change that I see. And it's the change from a model in which the human is presented with data in order to make a decision, which is really the old model of business intelligence. We're gonna analyze a bunch of data, we're gonna present it to a human who will then make a decision to a model in which the role of visualization, the role of business intelligence is to help someone design an algorithm. So that's a fundamental shift that I don't think a lot of companies have completely understood. That the end game here is the design of systems that do the right thing in response to data faster than we can do them. Again, just look at hedge funds. They're not sitting there with this sort of visualization display for their traders so they can make choices. I mean, I guess there's some element of that. No, they're writing algorithms that do trading much faster than humans can. When you're flying a plane, the plane is really flying itself and you're watching it, not actually using, the human isn't in the decision loop except at certain times. And I gave a talk recently about the Google Autonomous Vehicle and I started with a slide that said, this used to be a book. It was a publishing talk on a show in Atlas and now it's a car. And this notion that, this idea that here's a business intelligence thing. What's near me? I'm going to look at a map and we've got all this fabulous thing. It's dynamic, it's mobile. We have all these different layers. It's visualization and sort of personal intelligence. You look at Yelp or the Foursquare and you say, well, what restaurants are nearby? But increasingly, you can start to see the trend where Siri, it's like find me a Mexican restaurant nearby. You see where we're going. Increasingly, it's just take me there. And the design of systems that are smart enough to do what we want. And I think, again, going back to that Google Autonomous Vehicle, I've been spending a lot of time thinking about that as a metaphor for where we're going. Peter Norvig says, we didn't have better algorithms, we just have more data. So the whole role of data collection there. But also this notion that the car drives itself, that your interface comes, take me to Bob's house, as opposed to show me the route to Bob's house and I'll drive there. And that as a metaphor for where we're going with all of this stuff is really important for anybody involved in business intelligence. The people who are going to be using a lot of those tools are people who are designing algorithms, as I said, not people who will be making decisions. Yeah, I mean, I think, everyone talks about user experience and the application explosion here at Strata is what Dave and I are talking about the year of that application explosion, platform stabilizing. There's no more data model lock-in, so data sets are kind of meshing together, values being created, applications are exploding. But that brings up the next question in the evolution, which is user experience. So, what's your perspective on the evolution of the current user experience with completely connected individuals? You have AI guys talking about this, you've got real-time analytics to provide these kinds of benefits, you have mobile, cloud mobile and social is truly creating a new user experience and expectation. So, any kind of change in your mind and perspective around kind of where it's going, any tweaks, can you share with us your view on it? Kind of looking into the future of user experience. So, by the way, this is just the way I tend to think, is you have a sense of where things are going, it's kind of far out, then you look for signs that it's actually going there. And so, just a good example, Tan Lee from Emotive is here, on the whole Emotive headset. I remember when I first saw that at Google's Light guys a couple of years ago, how amazing it was that you could actually put some electrodes on your head and you could control stuff on the screen just by thinking. I was recently wearing a heads-up display and we've had the rumors of the Google goggles becoming real goggles, we have- Wearable computers. Yeah, wearable computing of all kinds. We have the sort of haptic interfaces that we start to see with the Kinect. So, we're in the threshold of a UI revolution. We're still thinking of mobile and tablets as our interfaces and they're beyond what we had with keyboards and the like, but I think we're gonna find, somebody's gonna have a breakthrough. This is a really good thing to think about. Everybody should go back and look at an early iPod. Everybody should have one in their house because it looks so clunky today. And yet, I remember the magical experience of that little scroll wheel and how it was so awesome. And somebody will just come up with a little metaphor that will kind of break. And that was before touch screens, but it was really the first sort of little sense of, oh, we're gonna have some new kind of touch-based interface and we're gonna have these things right now that just seem a little odd, and maybe they seem cool. And some years from now, we'll go, oh yeah, that really was the beginning. The original Mac, we've seen all these images now, the original Mac with Steve Jobs is passing. It's just amazing. Oh yeah, actually it was fantastic. I was just recently in Hawaii and I went to the Pearl Harbor Memorial and they've got there the battleship Missouri, which was retired in 1991. And so in all this of the wardrooms, you'll see the computers of the day and it's this little time capsule of, oh, that's what they were actually using on a battleship in 1991. And it was actually, it was an old Mac I saw there, but like computers from Olivetti and people like that. It was really kind of like, whoa, we've come a long way, haven't we? Jim O'Reilly, great insight, signal from the noise right there. A lot of noise being extracted from Tim right now, sharing with us. Post-Ted, I'm sure you're the intellectual candy for the brain. Ted is a great conference for that. Yeah, but what do we say about Strata? Strata is Ted for real people. Yeah, yeah, and then I also said it's a muffin. I'm like, I don't know, I wouldn't call Strata a muffin. Now, actually, I have to say there's so many wonderful places where people are sharing their experience and their vision. And it's a wonderful time in history when we're able to share so much with each other so easily. And hopefully we will take all of those connections that we make and start applying them to solving the world's great problems, which are bearing down on us faster than we appreciate. Well, and you're doing it, you're thinking about it. And I love when Tim comes on, John, because we go back to the 70s, talk about seminal papers in the 70s and apply them today. We talk about creating more value than you capture as a self-serving concept. We love that, right? And we try to create more value than we capture as well, so it's music to our ears. So where do you, one last question is Strata. I mean, we're here at the Humble Beginnings, we're here last year. Where do you see it, where do you see it going? What's that? Well, it's pretty clear that, you know, I say data is the currency of this whole new economy. And I'm hoping that this becomes, you know, the gathering place for all the people who are inventing the future of the data world. It's well on its way to being that event. I think we're going to see it. You know, we saw it double in size from last year, this year. I think we'll see it, you know, three or four times the size next year, you know. And we'll see more and more areas being touched by data, more and more people demonstrating how they're getting breakthroughs through data analytics and data science. And I think we're in a really exciting time. Well, thanks for having us here. Appreciate it. Thanks for all your collaboration