>> Announcer: Live, from Las Vegas, It's theCUBE, covering IBM Think 2018. Brought to you by IBM. >> We're back at IBM Think 2018 from Mandalay Bay in Las Vegas. My name is Dave Vellante. I'm here with Peter Burris, my co-host. You're watching theCUBE, the leader in live tech coverage. Scott Hebner's here as the Vice President of Marketing for IBM Analytics. Scott, welcome back, good to see you. >> Thank you, glad to be back again. >> So you heard Jenny this morning, a very inspiring speech. I love her talks. She's really good in front of an audience and one-on-one. What were your takeaways, specifically as it relates to your group? >> Well I think the theme of this whole conference is a lot of these technologies over the years that have been purchased separately and are thought of separate, quote-unquote, segments, are really all starting to fuse together. They're becoming different facets of the same challenge that a large majority of our clients have. And that is really this evolution towards a more AI based set of business models, right? There's a stack of things that need to be done to make that successful. You've got to move to the cloud for the agility of it, the economics of it. You got to get more value out of your data, and make your data ready for AI. Then you can start to more effectively train your AI models and allow them to continue to learn and everything. So it all really comes together, and I thought that's what she was framing, of what IBM's trying to do uniquely. >> Yeah, and I think it came across that way. Obviously, this conference is about bringing together all the separate... And your organization is evolving. I mean, when you think about IBM... Go back, Peter, to even the Gerstner days, and he said, "No, we're not going to split up "into a million companies. "We're going to have one face to the customer." And then, obviously, IBM was very successful there. You now had some major changes in the marketplace and you're responding to those. >> Yeah, and I think that's exactly right. We're being very customer-driven. One of the great advantages of IBM is that we have so many customers, right? A mix of new ones, a mix of ones we've had for a long time. We have so many people that engage. If you think about the size of IBM and how many are engaged with customers every single day at all levels, from the very most technical to the people that manage relationships, we learn a lot collectively. With all the new technologies, particularly around digital, net promoter score, all these things, we learn a lot about what they're trying to do. And that's what's driving us to fuse these strategies together into a more wholistic one. And that's what you heard this morning from Jenny. >> So, I also really enjoyed what I heard this morning from Jenny. It takes me reminded me, though, of one of those television shows where people bring in their old family artifacts, and then people price them. I imagine enterprises today literally looking at their data, the 80% that nobody has visibility to, and finding Grandpa's letter from Abraham Lincoln. >> Yeah. >> And using and discovering that this is a source of value that they've never envisioned before. Is that kind of the mentality, the conversation, that we're having today? >> No, that's exactly right. A large, large majority of CEOs have declared their data to be a strategic asset, but only about 10% of them believe their company treats it that way. And it leads to the statistic that you just referenced, which is 80% of data is either unanalyzed, untrusted, or inaccessible. So they're sitting on a gold mine of data, right? It's not just empirical customer records, but it's increasingly IOT and sensor data. It's behavioral data. There's a gold mine there. Step one is how do you take advantage of that and get more value out of it, right? Just in today's world, right? And then it really becomes fundamental to being successful with artificial intelligence. You have to have an information architecture. We kind of say if there's no IA, there's no AI. You have to have that information architecture to be successful, and that's really where we're focused on at this conference today, is getting that data ready for AI. >> So getting the data ready for AI, there's a lot that goes into that. But when you consider the notion of data as an asset, and what we heard from Jenny this morning, it seems as so, in many respects, there's kind of two models happening in the industry. You can see if I got this right. Companies that make money off of your data and companies that aren't going to make money off of your data. >> Right. >> Would you agree... I mean, is that kind of how the split is starting to happen in the industry right now? >> Yeah, no, I think that's right. I mean, I think a large majority of our clients are using their data within their firewall to operate their businesses better, better understand their customers. >> No, I learned something different. Yeah, sorry, I apologize. Companies that are going to make money off their customers' data-- >> Yes. >> And companies that are not going to make money off their customers' data. >> Yeah. >> Right? >> Yeah. What I'm saying is... No, I get the question. Different companies have different business models with what they're going to do with their data. Some see it as an asset to run their business more effectively. Others see it at as a direct asset that they sell and resell and resell, right? What I'm saying is the majority of the customers we deal with are looking at their data as an asset to run their business better. >> And that's the basis for the argument that the incumbency, that we're entering back into the area of the incumbency because of all these rich assets that aren't currently being utilized. Is that right? >> That's right. >> Great. >> It all starts with the fact that the data is fragmented everywhere. Business partner networks across different databases. Step one is to make that data simple and accessible. But once you do that, that's not the end of it because you need to make sure that the data that people are using is trusted. You have to have that trusted analytics foundation. So you got to integrate it, replicate it, catalog it, cleanse it, manage its lifecycle. You need to have one version of the truth, right, that everyone works off of, which is a major problem, by the way. It's the whole notion of governance and that falls into other categories like privacy and all the compliance challenges that customers have. Then from there, you have that foundation where you can start to drive more insights out of it through things like machine learning and pattern recognition. As you start to build those skills around data science, it starts to get you really ready for that next step on that ladder to AI. That's where a lot of these customers are figuring out how do I get on this roadmap to AI. And 85% or so say they're going to get there in the next five years. There's a great study from MIT Sloan that came out last year of 3,000 customers and was very clear. The difference between the pioneers that are having success, and those that aren't, is the pioneers have figured out how to make their data ready for AI. It all really starts there. That's really what we're focused on here at the show. >> Let's talk about that incumbent theme. It was part of Jenny's talk this morning. >> Scott: Yup. >> And you're right, the incumbents, their data exists in silos, even though they're maybe data companies, like a bank. >> Scott: Yeah. >> They're organized, perhaps, around their products. Or a manufacturer might be organized around the bottling plant, as you say. Whereas those companies that are AI driven have data at their core. So it's a challenge for the incumbent. >> Huge. >> How are you helping them close that gap, that AI gap, if you will? >> Right, and that's exactly what I was just saying before, is that the data is incredibly dynamic and growing at exponential rates. Not only through what you just mentioned, but there's acquisitions. There's different business partners that evolve through your networks, your client data, things of that nature. >> Dave: And data sources, yeah. >> Data sources are changing. And then you get into the technical layer of all different types of data, from images to empirical data. And then you get into different databases. It becomes a very heterogenous mess. Step one is to make it simple and accessible. And doing that though big data and being able to view through a single layer all the data as it changes, right? Because if you don't have access to your data, then what are you going to be training your AI algorithms on? And again, from there, you've got to govern it in a way that it's trusted data. This is a huge challenge for customers, because they get different versions of data that tell them different things. Which is the single version of the truth? It's kind of like if you've ever been on a... When you get on a treadmill, your watch says this many steps, your phone says another number of steps, the treadmill says the third number of steps. You're like, how many steps did I really take? They have that challenge every day. When you get that foundation and information architecture together, then you're ready for AI. What this MIT Sloan study showed was that bad data is paralyzing to AI. No matter how sophisticated your algorithmic AI capabilities are, bad data is simply paralyzing. So that's really where it needs to start. To circle back to your point about 80% of data, untrusted, unanalyzed, and inaccessible, that's got to be step one on that ladder to AI. >> So how are we going to use ML, machine learning AI, to help us get our data ready for machine learning AI? >> Well, that's exactly what we're doing in the IBM portfolio of data and analytics products, is we have this theme called Machine Learning Everywhere. So it actually is in almost every part of our platform. Hybrid data management uses machine learning to help do a much quicker assessment of how you bring data together and analyze it and things of that nature. We use it in the governance. In fact, we have a technology prototype that we've been working with some customers on, that will do the work for GDPR, the European Compliance Guidelines, in probably a few days to a week versus months and months and months. 'Cause we will go in and do all the entity associations for all your data. Help you organize it in a way that you can actually manage what to do with the compliance. And then, obviously, machine language is fundamental to just business analytics in general, right, pattern recognition. The traditional analytics tools will help you understand the data as it's presented, based on what you are trying to get out of it. Often, you don't know what you're trying to get out of it. Machine learning gives that data science method of actually uncovering patterns, which you can't really see. >> Peter: Creating models. >> Yeah, creating models and then you add the neuro-networks to it in deep learning. It's really literally a ladder that you're building that when you get to AI, you're going to be a lot more successful because you've built that trusted foundation underneath it. And I think Jenny was touching on that to some degree this morning. That's what we're majoring on, is that that data is really the key element of AI. >> Scott, who are the roles that you see developing this information architecture, getting ready for AI? CDO, CIO, Chief Digital Officer, where do they all fit? >> Yeah, I think it leads under the CDO. And actually both CDOs, the chief digital officer and the chief data officer, and their collection of data engineers, data stewards, things of that nature. 'Cause, again, you got to start by getting that information architecture in place. It also involves sort of a new generation of data developers that are building cloud-based data intensive applications, particularly of event-space data, which is a little bit different that customer data from sensors and all that, where you need that massive ingest speeds. It's those data-driven applications from the cloud that are really starting to incorporate machine learning. So they become really key. Then from there, if you think of it as a collaborative lifecycle, you get into the data scientists that are applying analytics. They're applying a more sophisticated version of mathematical programming and data science. Then there's a new, sort of subset of them, which are the AI developers. It's really from the data engineer right through business analysts. There's a lifecycle of people that are part of that team. They all have to work off a common platform, a common set of trusted data, to be successful. 'Cause you can no longer segment it. >> Is your strategy to build tooling that allows all of those roles to collaborate, maybe not the chief digital and chief data officer, but the data engineer, the data quality engineer, the application developer, the data scientist, right. Is that correct? >> That is absolutely correct and the CDOs. Actually, what we're announcing at the show is a new offer called IBM Cloud Private For Data. >> Dave: Right. >> So if you're familiar with IBM Cloud Private, it's our private, behind the firewall, cloud platform. We're coming out with a new offering that plugs into it. It's based on Coubanettis, so it runs on IBM Cloud Private For Data, and will run on other Coubanettis-based platforms. It is a fully integrated data and analytics platform, where no assembly is required. It will provision in minutes a pre-assembled, customized experience for you, based on what your role is. So if you're the CDO and you're the data scientist, and I'm the data engineer, we're all going to have a different set of requirements of what we want to get out of the data and what we're looking to do. It will pre-provision that for you very, very quickly. And you're all working off a common platform. It's collaborative in nature, with dynamic dashboards so you can see what's going on. It's really taking the building blocks that you need to move up that ladder and integrating to microservices in to a cloud platform that is just lightning fast in terms of, not only its ingest speeds of data but, more importantly, the ability to provision new users. So it's a major step forward in making it so much easier, so much more simple to get more out of your data and to get your data ready for AI. >> So, last question. You have this giant portfolio. We just finished our Big Data report. You guys, IBM, came up number one. Well, that was services, but still, you got a lot of software in there as well. >> Scott: Yes, we do. >> You've been working hard to pull those pieces together so the clients, it's simplify data. >> Scott: Yup. >> Okay, here's where are are, 2018, where do you want to take this thing? >> Well, I think, again, I think step one is this unified experiences. Because, again, we were kind of majoring on this conversation about the desegmentation of how people work in a business, what technology, what data they use. 'Cause with AI, it really does need to come together, right? So we're trying to do the same thing for the users, which is provision-based, almost on-demand, what you need based on what you're looking to do. And I think what's going to change as we go through time is it becomes more and more machine learning based, pattern recognition. It's more automated and customized and personalized, based on what you're trying to do. That's going to allow businesses to move at a much more rapid pace. And, again, I think the overriding theme when you look over a five year horizon is, is your data ready for AI? And that's where we're moving this whole thing. It's about the data. It's about the people and their skills. And it's the ability to move quickly. That's where the linkage with cloud comes in. >> Getting to pervasive AI, but you got to get your data house in order first. >> You got it. >> Scott Hebner, thanks very much for coming on theCUBE. >> Thank you. >> Great to see you again. >> Great meeting you. >> All right, keep right there everybody. We'll be back with our next guest. You're watching theCUBE at IBM Think 2018.

(energetic electronic music) >> Narrator: Live from Nassau in the Bahamas, it's theCUBE! Covering POLYCON18, brought to you by Polymath. >> Hey, welcome back everyone. This is exclusive live CUBE coverage here in the Bahamas for POLYCON18, it's a crypto event. Just talking economics. It's all the players in the space really discussing the future. I'm John Furrier with my co-host Dave Vellante. Our next guest, Bill Tai, friend, Facebook friend, industry legend, venture capitalist, kite surfer. His Twitter handle is @kitevc. Follow him. He's also involved in Bitfury and a lot of Bitcoin-related activities. Been a mentor to others. Great to have you, Bill. >> Thank you, John. I really appreciate you having me on the show. >> You tweeted in 2010, "This Bitcoin thing is interesting. "Check out this white paper." Can? >> Yeah, that was a >> Seminal moment. >> You know, back then I didn't know it would be, maybe a seminal moment. I was just lonely. (laughing) So, and the back story there, a very good friend of mine is Philip Rosedale, and he had approached me when he was starting a site called Second Life, where you basically create a digital avatar, maybe of yourself, maybe not, and you have this kind of, you know, world where you have people in an unstructured environment. And in the very early days of Second Life, when people were kind of just milling about, I said to Philip, I said, "Hey, Philip. "You know, maybe we should create a currency." I said, you know like, "If you think about it. "Think about what is Las Vegas? "Las Vegas is this pile of sand "but there is this metropolis on it. "How did that happen?" I said, "You know, if you took ten people, "sat them in a circle, and you put one poker chip "in the system, and said 'Pass it to the right,' "and everybody did that a million times a year. "Everybody would have a million dollars of income. "And then you could take chunks off "and build a casino, and build a resort, "and you'd have Las Vegas." So I said, "Let's do that." And so the Linden dollar was born. And so, soon, there was this thriving economy in Second Life that just, it was quite amazing to see. And so, when Bitcoin came out in 2009, as soon as I heard about it, I wanted to see what it was. So I went to the site and I read the paper, and it just seemed really cool. And so I started to play with it a little bit, and by 2010, I just thought it was really cool, but no one else had seen it. >> Yeah. >> So I took to Twitter to say, (laughing) "Is anyone out there "using this P to P digital currency?" You know, and >> It's funny. Our first web, You know, I started SiliconANGLE in 2009. David and I partnered in 2010. Our first website, the developer didn't want PayPal. He wanted Bitcoin. It was 22 cents, I think, at the time and we used the site for about half a year, and then we changed it and went back paid fiat. But if you think about where these come from, you brought up Second Life. Okay, online virtual world, really ahead of its time, but really set the stage for what we're seeing now. Gaming people who know virtual currencies, thrive on crypto. >> Yeah. Yes. >> So I'd like to get your perspective. Because, I know you've done a lot of investing in mobile and gaming, and what not. Where does that cross over? Because there's been a lot of virtual currencies going on in games. >> Yes. >> For a long, long time. >> Yes. >> How is that influencing and impacting this industry? >> Well, you know it's, I guess you have to ask, when you ask, you know, where does the real and where does the digital, like do they cross? And what are they? What is currency? Is the U.S. dollar real, right? And actually, let me pause for a second and reach down to my phone, because did you see a tweet today from Sheila Bair? I have to read this. Okay, so I just saw a tweet from @zerohedge earlier today. Sheila Bair, on Bitcoin, Quote, "I don't think we should ban it. "The green bills in your pocket don't have "an intrinsic value either." >> Well, look, the government wants to get rid of paper money. The people want to get rid of paper money. Why not? >> What is it really? Right? I mean so >> Backed by the U.S. military maybe, I don't know, I mean what >> What is it? >> What is it? Right. >> That's a good question. >> So I don't really see a difference. You know, they're kind of the same thing. You know, it's just something that people believe in, as the embodiment of value exchange. Whatever it is. So if it's a green piece of paper, or it's not. If it's shell, if it's a pebble. There is a fascinating book that you can read called The Ascent of Money by Niall Ferguson. He's at Stanford now at the Hoover Institute, but he got widely known after the great financial crisis unfolded. He basically wrote a book called The Ascent of Money which tracks the history of value exchange across civilized communities, for thousands of years, from pebbles to shells, to feathers, to credit, to default swaps. And coined the term "Cimerica," which is sort of the interdependence of the cash flow. And what became apparent to me when I read that, was that the world of ICOs is actually no different than anything we've experienced in civilized humanity. You know, if you think about, even in the United States, in the 1800s, at one time there were over 200 currencies circulating at the same time. If you think about the formation of the United States as colonies, a bunch of guys get off the boats. They draw lines around the forest. Here's Connecticut, here's Vermont, here's New York, here's Virginia. Let's do an ICO. They all did an ICO. If you think about it, they created their own unit of currency per their community and geography, no different than what's happening today. >> When Lincoln was shot, there was a five dollar confederate bill in his wallet, right? I mean, the confederates had their own money. >> Yeah, and also you brought a point up in the conference you were in in Dubai, which I thought was really intriguing, and provocative, but also kind of real. The Oil Dollar Association post-World War II, >> Yeah >> Essentially wasn't actually securitizing oil That was an ICO. >> It was the tokenization of oil, right. Yeah, so, you know, the modern currency system that we have today, that is commonly known as the Petrodollar, so it's actually a relatively recent phenomenon. So if you think about, of course, the quote "U.S. dollar" was around a little bit longer than 1944, but it was really at Brett Woods that the dollar had its sort of birth to become the world's standard currency. And, you know, this is maybe a little bit of an over-simplification, but think about the picture after World War II. So, you basically have every major productive economy have war, destroy themselves. The U.S. enters late, finishes it all off completely, and you basically have 100 million people milling about. A little bit like Second Life, right? So, what do you do? Got to make them productive. Create a currency, set of currencies. So for every community of interest, like every token community of interest, you say, "Well, here's a lira, here's a franc, "Here's a pound, here's a mark. "Let's take gold, "reference the dollar to gold, and reference "every one of these currencies against the dollar. "Gentlemen, start your engines." Right? >> There you go. >> So how is that different than an ICO? Okay, so that was fixed to gold for a long time until people started to game it. And when the French accumulated a lot of dollars and they realized, whoa, there's more dollars than there is gold, I'm just going to go cash all this in. So they literally came over to take all the gold, and then the president took it off the gold standard. >> Dave Vellante: That's right. >> So it had to couple with something. So what it the utility token that that became? That became referenced to petroleum because the U.S. had basically forced everybody in the Middle East to accept dollars as payment and what that did was it created the dollar as a storage of energy. So you could basically take a token of oil and, as a separate nation, you could store that through your trade, if you had sort of a surplus, and you provided yourself energy security. >> Well, most currencies, right, historically have had a pretty short shelf life. Presumably the same will be true in the Blockchain world. >> Don't know. >> The crypto world. >> Yeah, it's, if you look at the history of humans over six million years, and it's arguable it's at four or six, or whatever it is, you're right. Like there have always been multiple currencies all the time. And very rarely have they ever become sort of like super-dominating currencies. That is also a very recent phenomena. I think, driven by the industrial revolution, and a combination of the Petrodollar and scale economics and manufacturing. So, so that >> Yeah, and overwhelmingly here, at this event, people feel like security tokens, as an asset class, are going to vastly overtake utility tokens. >> You know, actually, securities are a whole, I mean regular securities, (laughing) that's an interesting subject altogether. Right, okay, so there was a time, in my lifetime, when I was a securities analyst at Alex Brown in the '80s, and in that period of time, everything traded at ten times earnings, right? So you had a barometer for, a stock should be valued at this, because is should have a PE of actual real earnings. >> Dave Vellante: Independent of its growth or anything else, right? >> Yes, and if it grew, you had a PEG ratio, so you'd have a little bit higher growth, and so a little higher PE, but what's happened to securities over time, of that ilk, okay, you had to get these companies profitable to get them public in that era, and then over time the sort of like network effects have come in, and communities of interest have formed around companies. So, and the structure of securities has moved from give me something with earnings multiply it by a number to get the value, to give me a share of something that has no voting rights and no earnings. Does that sound like a token? That's Snapchat, right? (laughing) >> So you literally have, you know, Google, Facebook, all these companies now issue shares that don't have the characteristics of equity shares. They don't vote. What are they now, right? So tokenization is sort of a natural extension of that. >> Dave Vellante: Do you see that as a >> They don't have dividends either >> You see that as a fundamental shift in the value equation, the perceived value equation? Both? Is it sustainable? >> I think it's basically, so, you know, I go back and forth on this, because is it a trend line or is it a return in the past? Right? So what is a confederate dollar that was in Abraham Lincoln's pocket? It's a belief. So what is a share of Snapchat? It's a belief. It doesn't have earnings >> John Furrier: And a token is a belief. >> Right. >> But the trend is securing something, right? So the trend we're seeing is, obviously the ruling, first of all the ruling in Switzerland was interesting. You now have a trading so an asset, so security, asset, and then trading. So they kind of went a little bit deeper, which I think is helpful. >> Yeah. >> For the community. But what are they securing? So the trend, as we see, is percentage of revenue, non dilutive and equity in the classic sense, so kind of a token. And then some sort of either buyback options, people are doing things like that. Do you see patterns like that? What are you seeing for? >> Well. >> I mean a security token makes sense. It's all credited. The paperwork's known. >> Yeah, so, you know, it feels like, so some people refer to sort of Bitcoin as digital gold, you know, and in that sense, like gold is a commodity but is the root of securities, you know, whether it's gold ETF's or something, because you perceive a limited supply, and you perceive a storage of value, so that is where I think Bitcoin sits. But then I think this whole other category of utility tokens, that may be considered security tokens by definition of law, that resembles the petrodollar. And as we were talking about earlier, you know gold used to represent or a dollar used to represent a share of gold, but it didn't anymore. So what was underpinning it? It was basically, in my opinion, the ability for that token to have utility as an instrument to purchase oil for your energy security. And so, I think that's kind of where the utility tokens are today. >> You're a leader in the industry, and you're well-known. Communities need to thrive. And factions form, curriencies form, and can be very productive, and also can be counterproductive. >> Yeah. >> So what is the unwritten rules that you guys are putting forth. Are people meeting? Are you talking? And sometimes, as people make money, which a lot of people are making a lot of money right now. I mean, for some people, it's the first time. Didn't have money, make money. You know, egos kind of come in. So all of these are normal things. But again, this is a societal community dynamic, >> Yes. >> But super important. Institutional investors are coming in. >> Right. >> Big money. This isn't Burning Man. This isn't. Burning Man's cool, but you can't model this industry after Burning Man. Maybe you could. I don't know. What is your take? >> Well, you know, it's, I think that the guiding principle really needs to be looking out for the greater good, because I think that is the issue that everyone is trying to solve for. And it's not just endemic to Bitcoin and Blockchain. It's a societal issue that's been with us since the creation of civilization. And I don't know how to solve for that, but I think you need people to stand up and just make sure that people are thinking about that all the time. You know, and I think, over my career, I think I started as kind of like a geek hacker, sitting in the back of the room, working on little microchips and building stuff, and I still do that on weekends sometimes, but, you know, for whatever reason, I've been thrust into this role now where I do have a set of communities of interest that started actually around kiteboarding, but it became sort of a larger community around entrepreneurship. And we've actually, I have a 501(c)(3) that supports ocean causes and entrepreneurial things, and it's called ACTAI Global, and we have a couple value statements. We actually, we're codifying it, so we actually have a little pin, you know the ACTAI stands for Athletes, Conservationists, Technologists, Artists and Innovators, and all of us collectively, we combine our energy to work on causes. Some of the things that we support are around ocean conservation and the preservation of ecosystems, but we also work on a lot of other entrepreneurial efforts to help each other. But the thing that I've realized with our group is we've been very productive as a community, and you see a lot of companies that are born in our community, funded in our community, like, you know, whether it's Canva or Zoom, or any number of projects that turn into community-based companies because the group of people, they think and they stand for something greater than themselves. So that's kind of one principle. It's sort of like, how do you, how do you place your values as something to support the greater community, and that's something that I think, if everybody would just think about that a little bit, and stand for something greater than themselves, the world would be a better place. And on that note, the second ethos that we operate to is that we strive to leave every person or place we touch better than before we touched it. So when you see us like kiting at a beach, you'll see us picking up garbage, too. You know? We don't go someplace without trying to improve it a little bit. And I think we help each other on the companies, too. And I think the last thing that people really should try to do, everybody in this world of technology, has a little bit of a superpower, whatever that is. You know, they wouldn't be doing the things that they're doing if they weren't totally insanely focused on a piece of technology. They know something that other people don't. And if everybody would just try a little bit to use the powers the universe has granted them, to empower others, to unlock other people, the world would be a better place. So I think, you know, I think all of these factions, if we could just get people to stand for something greater than themselves, work to make people and places better off than before they touched them, and empower other people, I think we'll have some great outcomes. >> You know, empathy, empathy is a wonderful thing. And also you mentioned, know your neighbor. You know, that's a big thing. We're doing our part here in theCUBE, bringing our mission content. Bill, been great to have you on. And we'll get that clip out on the network about your mission. Great stuff. >> Thank you, thanks. >> And great to see you >> It's an awesome philosophy. >> be successful, you're a great leader. People look up to you, and certainly we're glad to have you on theCUBE. Thanks for joining us. Hey, more live coverage after this short break here on theCUBE in the Bahamas for crypto currency, token economics, POLYCON18. We'll be back with more after this short break.