>> Live from Las Vegas it's The Cube covering NAB 2017. Brought to you by HGST. >> Welcome back to The Cube. We are live at NAB 2017. I'm Lisa Martin. Very, very excited, kind of geeking out right now to be joined by our next two guests. Sam Blackman, the co-founder and CEO of AWS Elemental, welcome to The Cube. >> Sam: Thank you so much. >> And we have NASA astronaut, Tracy Caldwell Dyson. Both of you, welcome to The Cube. >> Thank you. >> Today has been a very historic day for technology and space. This was the first ever live 4k video stream that happened between you on Earth, Sam, and Doctor Peggy Whitson, aboard the International Space Station. >> Sam: Yes. >> Wow. Tell us about that. >> It was truly amazing to be part of history and the amount of technology that came into play to make this possible. You know, sitting in the conference room in NAB in the middle of Las Vegas, seeing astronauts 250 miles ahead, going around the Earth, 17,000 miles an hour and a seamless, beautiful 4k picture. It was mind blowing. Hard to believe it's happened still. >> I can't even imagine. I'm getting goosebumps for you. Tell us some of the things that Dr. Whitson shared about her experiences. What was the interaction like? >> Well, Commander Whitson and Colonel Fisher was also in the interview and that guy is hilarious, by the way. >> Yeah, he is. >> He is hilarious. They talked about how advanced imaging technology really helps NASA perform experiments and bring experiments that are happening on the space station down to Earth for researchers to use that data and discover how the world works inside the universe. Some of the really interesting examples revolved around some experiments they showed. With thin film technology they had a very small, metallic structure that they could pull water out of and then corral that water, convert it into a spherical shape and in the 4k resolution, you could just see every element of that thin film in a way that looked like it was right next to us. I mean, it was transformative. >> Tracy: Yeah. >> I bet it was. Well, speaking of transformative, this was, I mentioned, a really historic event for a number of reasons. Obviously, for those of us on the ground, for AWS Elemental. But, Tracy, from your perspective, you've been in space for 188... I had it here somewhere, hours. >> Yeah, days. >> You've been on STS118, you've been on the Soyuz to the station on expeditions 23 and 24. What does this capability now mean in the life of an astronaut? >> I think what it does is it helps us bring the experience to everybody here on Earth. It is so hard to capture what we are not just seeing, but experiencing. The richness, the detail, the vividness of the colors and how they're changing are all a part of looking at our beautiful planet. And just from that alone, being able to bring that to the American people, the world, really, is, I think to me a great relief. Because it grieves me to think about how in the world I would describe this beautiful, magnificent view to everybody back home. >> I can imagine. You've done extra-vehicular space walks. >> Tracy: Yes. >> And I can imagine it's indescribable. >> It is. And from the fact you're looking at our planet from 250 miles above, you see the curvature of the Earth, you see it moving at a super high speed, you don't feel the wind in your face, but there's no doubt you're traveling very fast. Just the fact that you are out in the vacuum of space. If you could bring parts of that experience to people back home ... I'm excited to think about how that would transform just the way people think, not to mention the way that they act towards our planet. >> I also think inspiration ... We were talking before we went on that you were about 14 when the Challenger incident happened, we all kind of remember exactly where we were, and that really, a teacher being in space was so inspirational to you. Can you imagine shifting the conversation and what this technology is able to do inspiring the next generation of people that want to be the next Tracy Caldwell Dyson? >> Well, I think what the technology does today, especially in imaging capabilities, is it provides so much more detail than I could even describe. That a young person today watching that, and our generation today is so visual, that they're going to pick up on things that I wouldn't even think to describe to them. And it's going to capture their imagination in ways that are astounding. Compared to I, who, just the sheer knowledge of knowing there was a teacher that was going into space, propelled me to work really hard. I can only imagine what this generation's going to be capable of because of the images that we're bringing to them. >> It's so exciting. Sam, this is really kind of the tip of the iceberg. From AWS Elemental's perspective, first of all, you just had a rebrand. But what does this mean for the future of the video ecosystem? >> Well, I think it really shows you how the technology components came come together to create unbelievable pictures no matter where you are on the planet or in space. We had a live 4k encoder on the space station itself sending down signals to Johnson Space Center, then Johnson Space Center sending redundant links to Las Vegas, here, and the convention center. And then processing the video, the interview with Tracy, here in the space center-- or, here in NAB and then using the cloud to distribute that all over the world. So these 4k images, which take a significant amount of bandwidth, can be created in space, delivered here, produced and delivered anywhere in the world using the power of the cloud and advanced networking technology. And that's pretty amazing, when you think about it. >> Lisa: It really is. I don't think the three of us are smiling big enough. >> I know. It hurts! >> There's so much relief in this face. >> Lisa: I can imagine >> I bet. >> I absolutely can imagine, I think. One of the cool things about-- This is our first time at NAB with The Cube, but we're here: Media, entertainment, Hollywood. What this shows is this transcendence of technology to space. And there's so much interest in space. In fact, Tracy, you were an advisor to Jessica Chastain on "The Martian," which is probably pretty exciting. >> Oh, absolutely. It is. >> But just the transcendence of that and how this technology can be used to power things that everybody can understand, movies and things. But also the future of space exploration, which I can imagine, right now in the era of the space shuttle being retired now, depending on Soyuz rockets to get to the space station as the next vehicle is delivered, this must be quite inspirational for you as an astronaut, as not only is the next vehicle in development, but also, the exploration of Mars. In fact, you were just last month with President Trump. >> Tracy: Yes. >> As they signed a bill. What are your thoughts about that and how do you see imaging technology being an instrumental part of Mars exploration? >> In so many ways, but at the top is the momentum. Like you said, with Hollywood has captured space in some real endearing ways. And the images from NASA, from the human space flight program to Hubble to deep space, it is propelling ... it's momentum. And I think we need that momentum, especially with our young folks because they're going to be the ones, let's face it, who are going to be in the best condition to be on the planet of Mars. So, if we can continue to feed them the images as lifelike as we can, so that they feel they're there, I think we are heading in the right direction to actually being there. >> Wow, fantastic! Congratulations to both of you. Thank you both so much for joining us on The Cube. We can't wait to see what's next. >> Sam: Thank you so much. >> Tracy: Thank you. Thank you. >> Well, for Tracy and Sam, I'm Lisa Martin. You've been watching The Cube live from NAB 2017. Stick around, we'll be right back. (funky music)

>> from Boston, Massachusetts. It's the queue covering active eo 2019. Data driven you by activity. >> Welcome back to Boston. Everybody watching the Cube, the leader and on the ground tech coverage money was David wanted here with my co host. A student of John for is also in the house. This is active FiOS data driven 19 conference. They're second year, John. Her stick is here is the co founder and CEO of on shape John. Thanks for coming in the Cube. Great to have you great to be here. So love the cofounder. I always ask your father. Why did you start the company? Well, we found it on shape because >> we saw an opportunity to improve how every product on Earth gets developed. Let people who develop products do it faster, B'more, innovative, and do it through a new generation software platform based in the cloud. That's our vision for on shape, That's why. Okay, >> so that's great. You start with the widened. The what is just new generation software capabilities to build the great products visualized actually create >> way took the power of cloud web and mobile and used it to re implement a lot of the classic tools for product development. Three d cad Data management Workflow Bill of Materials. He's may not mean anything to you, but they mean a lot to product developers, and we believe by by moving in the cloud by rethinking them for the cloud we can give people capabilities they've never had before. >> John, bring us in tight a little bit. So you know, I think I've heard a lot the last few years. It's like, Well, I could just do everything a simulation computer simulation. We can have all these models. They could make their three D printings changing the way I build prototypes. So what's kind of state of the state and in your fields? So >> the state of the Art R field is to model product in three dimensions in the computer before you build it for lots of reasons. For simulation for three D printing, you have to have a CAD model to do it, to see how it'll look, how parts fit together, how much it will cost. Really, every product today is built twice. First, it's built in the computer in three dimensions, is a digital model, then it's built in the real world, and what we're trying to do is make those three D modeling and data management collaboration tools to take them to a whole nother level to turbo charge it, if you will, so that teams can can work together even if they're distribute around the world. They work faster. They don't have to pay a tax to install and Karen feed for these systems. You're very complicated, a whole bunch of other benefits. So we talk about the cloud model >> you're talking about a sass model, a subscription model of different customer experience, all of the above, all of the above. Yeah, it's definitely a sass model we do on Ly SAS Way >> hosted and, uh, Amazon. Eight of us were all in with Amazon. It's a it's a subscription model, and we provide a much better, much more modern, better, more productive experience for the user CIA disrupting the traditional >> cad business. Is that Is that right? I mean more than cat cat Plus because there's no such thing as a cad company anymore. We're essentially disrupting the systems that we built because I've been in this business 30 38 years now. I've been doing this. I feel like I'm about half done. Really, really talking about >> your career. Way to start out. Well, I grew up in Chicago. I went to M I t and majored in mechanical engineering and knew howto program computers. And I go to get an internship in 1981 and they say computers, mechanical injury. You need to work on CAD. And I haven't stopped since, you know, because Because we're not done, you know, still still working here. You would >> have me, right? You can't let your weight go dynamic way before we get off on the M I t. Thing you were part of, you know, quite well known group. And Emmet tell us a little bit >> about what you're talking about. The American society of Mechanical Engineer >> has may I was actually an officer and and as any I know your great great events, but the number 21 comes to >> mind you're talking about the MIT blackjack team? Yes, I was, ah, player on the MIT blackjack team, and it's the team featured in movies, TV shows and all that. Yeah, very exciting thing to be doing while I was working at the cath lab is a grad student, you know, doing pursuing my legitimate career. There is also also, uh, playing blackjack. Okay, so you got to add some color to that. So where is the goal of the M I T. Blackjack team? What did you guys do? The goal of the M I t blackjack team was honestly, to make money using legal means of skill to Teo obtain an edge playing blackjack. And that's what we did using. Guess what? The theme of data which ties into this data driven conference and what active Eo is doing. I wish we had some of the data tools of today. I wish we had those 30 years ago. We could have We could have done even more, but it really was to win money through skill. Okay, so So you you weren't wired. Is that right? I mean, it was all sort of No, at the time, you could not use a computer in the casino. Legally, it was illegal to use a computer, so we didn't use it. We use the computer to train ourselves to analyze data. To give a systems is very common. But in the casino itself, we were just operating with good old, you know, good. This computer. Okay. And this computer would what you would you would you would count cards you would try to predict using your yeah, count cards and predict in card. Very good observation there. Card counting is really essentially prediction. In a sense, it's knowing when the remaining cards to be dealt are favorable to the player. That's the goal card counting and other systems we used. We had some proprietary systems to that were very, very not very well known. But it was all about knowing when you had an edge and when you did betting a lot of money and when you didn't betting less double doubling down on high probability situations, so on, So did that proceed Or did that catalyze like, you know, four decks, eight decks, 12 12 decks or if they were already multiple decks. So I don't think we drove them to have more decks. But we did our team. Really. Some of the systems are team Pioneer did drive some changes in the game, which are somewhat subtle. I could get into it, you know, I don't know how much time we have that they were minor changes that our team drove. The multiple decks were already are already well established. By the time my team came up, how did you guys do you know it was your record? I like to say we won millions of dollars during the time I was associated with the team and pretty pretty consistently won. We didn't win every day or every weekend, but we'd run a project for, say, six months at a time. We called it a bank kind of like a fund, if you will, into no six months periods we never lost. We always won something, sometimes quite a bit, where it was part of your data model understanding of certain casinos where there's certain casinos that were more friendly to your methodology. Yes, certain casinos have either differences in rules or, more commonly, differences in what I just call conditions like, for instance, obviously there's a lot of people betting a lot of money. It's easier to blend in, and that's a good thing for us. It could be there there. Their aggressiveness about trying to find card counters right would vary from casino to casino, those kinds of factors and occasionally minor rule variations to help us out. So you're very welcome at because he knows is that well, I once that welcome, I've actually been been Bardet many facilities tell us about that. Well, you get, you get barred, you get usually quite politely asked toe leave by some big guy, sometimes a big person, but sometimes just just honestly, people who like you will just come over and say, Hey, John, we'd rather you not play blackjack here, you know that. You know, we only played in very upstanding professional kind of facilities, but still, the message was clear. You know, you're not welcome here in Las Vegas. They're allowed to bar you from the premises with no reason given in Las Vegas. It's just the law there in Atlantic City. That was not the law. But in Vegas they could bar you and just say you're not welcome. If you come back, we'll arrest you for trespassing. Yeah, And you really think you said everything you did was legal? You know, we kind of gaming the system, I guess through, you know, displaying well probabilities and playing well. But this interesting soothe casinos. Khun, rig the system, right? They could never lose, but the >> players has ever get a bet against the House. >> How did >> you did you at all apply that experience? Your affinity to data to you know, Let's fast forward to where you are now, so I think I learned a lot of lessons playing blackjack that apply to my career and design software tools. It's solid works my old company and now death. So System, who acquired solid words and nowt on shape I learned about data and rigor, could be very powerful tools to win. I learned that even when everyone you know will tell you you can't win, you still can win. You know that a lot of people told me Black Jack would never work. A lot of people told me solid works. We never worked. A lot of people told me on shape would be impossible to build. And you know, you learn that you can win even when other people tell you, Can't you learn that in the long run is a long time? People usually think of what you know, Black Jack. You have to play thousands of hands to really see the edge come out. So I've learned that in business sometimes. You know, sometimes you'll see something happened. You just say, Just stay the course. Everything's gonna work out, right? I've seen that happen. >> Well, they say in business oftentimes, if people tell you it's impossible, you're probably looking at a >> good thing to work on. Yeah. So what's made it? What? What? What was made it ostensibly impossible. How did you overcome that challenge? You mean, >> uh, on >> shape? Come on, Shake. A lot of people thought that that using cloud based tools to build all the product development tools people need would be impossible. Our software tools in product development were modeling three D objects to the precision of the real world. You know that a laptop computer, a wristwatch, a chair, it has to be perfect. It's an incredibly hard problem. We work with large amounts of data. We work with really complex mathematics, huge computing loads, huge graphic loads, interactive response times. All these things add up to people feeling Oh, well, that would never be possible in the cloud. But we believe the opposite is true. We believe we're going to show the world. And in the future, people say, you know We don't understand how you do it without the cloud because there's so much computing require. >> Yeah, right. It seems you know where we're heavy in the cloud space. And if you were talking about this 10 years ago, I could understand some skepticism in 10 2019. All of those things that you mentioned, if I could spin it up, I could do it faster. I can get the resources I need when I needed a good economics. But that's what the clouds built for, as opposed to having to build out. You know, all of these resource is yourself. So what >> was the what was the big technical challenge? Was it was it? Was it latent? See, was it was tooling. So performance is one of the big technical challenges, As you'd imagine, You know, we deliver with on shape we deliver a full set of tools, including CAD formal release management with work flow. If that makes sense to you. Building materials, configurations, industrial grade used by professional companies, thousands of companies around the world. We do that all in a Web browser on any Mac Windows machine. Chromebook Lennox's computer iPad. I look atyou. I mean, we're using. We run on all these devices where the on ly tools in our industry that will run on all these devices and we do that kind of magic. There's nothing install. I could go and run on shape right here in your browser. You don't need a 40 pound laptop, so no, you don't need a 40 pound laptop you don't need. You don't need to install anything. It runs like the way we took our inspiration from tools like I Work Day and Sales Force and Zen Desk and Nets. Sweet. It's just we have to do three D graphics and heavy duty released management. All these complexities that they didn't necessarily have to do. The other thing that was hard was not only a technical challenge like that, but way had to rethink how workflow would happen, how the tools could be better. We didn't just take the old tools and throw him up in a cloud window, we said, How could we make a better way of doing workflow, release management and collaboration than it's ever been done before? So we had to rethink the user experience in the paradigms of the systems. Well, you know, a lot of talk about the edge and if it's relevant for your business. But there's a lot of concerns about the cloud being able to support the edge. But just listening to you, John, it's It's like, Well, everybody says it's impossible. Maybe it's not impossible, but maybe you can solve the speed of light problem. Any thoughts on that? Well, I think all cloud solutions use edge to some degree. Like if you look at any of the systems. I just mentioned sales for us workday, Google Maps. They're using these devices. I mean, it's it's important that you have a good client device. You have better experience. They don't just do everything in the cloud. They say There, there. To me, they're like a carefully orchestrated symphony that says We'll do these things in the core of the cloud, these things near the engineer, the user, and then these things will do right in the client device. So when you're moving around your Google map or when you're looking this big report and sales force you're using the client to this is what are we have some amazing people on her team, like R. We have the fellow who was CTO of Blade Logic. Robbie Ready. And he explains these concepts to make John Russo from Hey came to us from Verizon. These are people who know about big systems, and they helped me understand how we would distribute these workloads. So there's there's no such thing is something that runs completely in the cloud. It has to send something down. So, uh, talk aboutthe company where you're at, you guys have done several raises. You've got thousands of customers. You maybe want to add a couple of zeros to that over time is what's the aspirations? Yeah, correct. We have 1000. The good news is we have thousands of customer cos designing everything you could imagine. Some things never would everything from drones two. We have a company doing nuclear counter terrorism equipment. Amazing stuff. Way have people doing special purpose electric vehicles. We have toys way, have furniture, everything you'd imagined. So that's very gratifying. You us. But thousands of companies is still a small part of the world. This is a $10,000,000,000 a year market with $100,000,000,000 in market cap and literally millions of users. So we have great aspirations to grow our number of users and to grow our tool set capability. So let's talk to him for a second. So $10,000,000,000 current tam are there. Jason sees emerging with all these things, like three D printing and machine intelligence, that that actually could significantly increase the tam when you break out your binoculars or even your telescope. Yes, there are. Jason sees their increasing the tam through. Like you say, new areas drive us So So obviously someone is doing more additive manufacturing. More generative design. They're goingto have more use for tools like ours. Cos the other thing that I observed, if I can add one, it's my own observations. I think design is becoming a greater component of GDP, if you will, like if you look at how much goods in the world are driven by design value versus a decade or two or when I was a child, you know, I just see this is incredible amount, like products are distinguished by design more and more, and so I think that we'll see growth also through through the growth in design as an element of GDP on >> Jonah. I love that observation actually felt like, you know, my tradition. Engineering education. Yeah, didn't get much. A lot of design thing. It wasn't until I was in industry for years. That had a lot of exposure to that. And it's something that we've seen huge explosion last 10 years. And if you talk about automation versus people, it's like the people that designed that creativity is what's going to drive into the >> absolutely, You know, we just surveyed almost 1000 professionals product development leaders. Honestly, I think we haven't published our results yet, So you're getting it. We're about to publish it online, and we found that top of mind is designed process improvements over any particular technology. Be a machine learning, You know, the machine learning is a school for the product development. How did it manufacturers a tool to develop new products, but ultimately they have to have a great process to be competitive in today's very competitive markets. Well, you've seen the effect of the impact that Apple has had on DH sort of awakening people to know the value of grace. Desire absolutely have to go back to the Sony Walkman. You know what happened when I first saw one, right? That's very interesting design. And then, you know, Dark Ages compared to today, you know, I hate to say it. Not a shot at Sony with Sony Wass was the apple? Yeah, era. And what happened? Did they drop the ball on manufacturing? Was it cost to shoot? No. They lost the design leadership poll position. They lost that ability to create a world in pox. Now it's apple. And it's not just apple. You've got Tesla who has lit up the world with exciting design. You've got Dyson. You know, you've got a lot of companies that air saying, you know, it's all about designing those cos it's not that they're cheaper products, certainly rethinking things, pushing. Yeah, the way you feel when you use these products, the senses. So >> that's what the brand experience is becoming. All right. All right, John, thanks >> so much for coming on. The Cuban sharing your experiences with our audience. Well, thank you for having me. It's been a pleasure, really? Our pleasure. All right, Keep right. Everybody stupid demand. A volonte, John Furry. We've been back active, eo active data driven 19 from Boston. You're watching the Cube. Thanks

>> Announcer: Live from Las Vegas, it's theCUBE, covering IBM Think 2018, brought to you by IBM. >> Welcome back to theCUBE. We are live on Day One of our three days of coverage of IBM Think, the inaugural single event from IBM. I'm Lisa Martin with Dave Vellante. We're at the Mandalay Bay in beautiful sunny Las Vegas, and we're excited to welcome to theCUBE for the first time, Steve Hill, the Global Head of Innovation at KPMG. Welcome. >> Thanks for having me here. >> So you are giving a talk Wednesday, you said, at the event. >> Yes. >> I want to get a little bit into your role at KPMG, as well as your session. So talk to us a little bit about what your role as the Global Head of Innovation. >> So Innovation is an overused word. I don't particular like the word innovation, but in the context of my role, it really is taking a look at our business and our clients, and saying what it is that our clients need for their futures. What's going to create relevance for our clients as we go forward, and how does our portfolio of services relate to that relevance? And if we have gaps where we see our services not serving them best, or not going to serve them best in the future, my job responsibility is to help for strategy purposes and for investment purposes, bring those points to bear, and to get either investment into those areas, right, or changes in the business as appropriate to make KPMG more relevant to our clients, and to their relevance to their clients, right, that's the whole idea. >> So, Lisa and I talk to a lot of people in theCUBE, and we talk lots about invention, startups inventing something or new technology that gets invented, but innovation to us, and I think KPMG is at the heart of this is taking an invention and actually applying it to effect change, getting it adopted, >> That's right. >> and changing a business, a societal change potentially, is that-- >> That's right, I mean, our short phrase for it is idea to cash for our clients, right. I mean at the end of the day, and I think this is profound in certainly corporate governance evolution, right. We've seen the advent of lots of escrow changes of how companies have been managed, enterprise has been managed, right. The Dutch started with the East Indian Trading Company, one of the first large global enterprises, and since that time we've seen the maturation, the new roles. The CIO role didn't exist much prior to 1950, right. Today we're starting to see innovation to be a very important skill and capability for all corporations, all enterprises, including government, right. And I think we're starting to see a maturation of corporate capability, I would say, in the innovation space, because the pace of change is so fast today, the political, economic, technological, social trends are so complex that you've got to get something in your muscle memory that helps you change your business as much as operate it effectively. >> I'd love to know who you're talking to within organizations. You mentioned CIO role, the CISO role, chief data officer. >> Steve: Right. >> Who are the minds that you're helping to bring together so that an enterprise that needs to digitalize to be competitive will survive, right, really survive these days? How do you help them really embrace a culture of innovation as really there's no other choice? How do you get these minds collectively agreeing, yes, this is the direction we need to go in? >> Yeah, I think, I mean first of all, this is a C-suite conversation and a board conversation in many cases, but the reality is when you start to look at the lack of innovation in an organization, right, and when the environment changes, competitors start to change, and the more complex it is, it's harder and harder for companies to pivot and to reinvent themselves. And we're seeing a lot of unbundling of businesses in today's environment, whether it's a company that moves packages, right, or a professional services firm, or a company that used to distribute videos, right. I mean things change and some of the irony is that sometimes the innovation in companies like Kodak, Steve Sasson invented digital camera, it took eight minutes to go from a snap to a picture, but they invented digital technology from cameras, and that the distribution of digital videos is that it actually would help to, further the demise of that organization. So that notion of how do you take change going on in the environment that you're working at, and more importantly your customers and clients, how does that convert into your business, that's a C-suite conversation, and I think innovation can be embodied in a person to help build process, meaning how do you take an idea, how do you look at the marketplace and get sensory input, convert that to ideas for strategy and for investment, and the investments have to be deployed to the field to the business, and that relationship, that whole lifecycle of innovation requires a lot of people from the enterprise to be involved in it. And I would argue the culture has to evolve because until recently most people, in fact, I would say, including current times, most people in organizations are rewarded for doing what they do well, not breaking what they do, not rethinking what they do. And the more you get into that operational mindset, that I want to wring all the efficiencies out of this process that I can. Right, the more you're wed to the status quo, the more somebody comes in from the side and takes you out. >> So I love this conversation 'cause Steve you're able to take the long view and then I want to sort of shorten it up, and then maybe put it into a longer term context. So over our, your guys 20-plus-year careers, mine a little longer, most of this industry has marched to the cadence of Moore's Law, that's where innovation came from. >> Yes. >> How do you take advantage of Moore's Law? How do you go to client server software, whatever it was, the innovation equation is changing now. It seems to be a function of, these guys have been hearing me say this all day but data that's not siloed, but data that you have access to, applying machine intelligence-- >> Yep. >> And then getting cloud, scale, economics and network effects, and then applying it to your business. >> Bingo. >> So talk about how you see the new wave of innovation in this world of digital or however you phrase it. >> Well, it's interesting, I mean, I don't hear a lot of people phrase it the way you do which I think is spot on which is, and my words are, ubiquitous access to technology which is cloud, data, and that's a huge question mark and a big C-suite conversation. Having a lot of data isn't the key, having the right lot of data is the key. Right so Dyson is moving into auto-making today, right. They have a lot of data and it's very different from what the incumbents have. Is it better or worse? We're going to see, right. And then of course smart computers which is the machine intelligence, right. Those three elements, I think they're fundamentally changing labor productivity. And what I would say is to your question is that innovation is really important here because if all you do is take those three elements and you just digitize a status quo process, you might get marginal benefits, you might get some labor productivity enhancement, you may get some marginal improvement, you may change an outsourcing agreement to an onshore RPA deal, but if that's all you do, you're setting yourself up for a disappointment because what's really going to happen with thinkers, i.e., those that have innovations, they're going to rethink the process. Most of our analog systems are created around people checking people, so you may have nine steps, I'm making it up, in a process, that in a digital world only requires one or two or zero when launching in some cases. And so if you can rethink that process to go from a nine-step to a zero-step process or a one-step that's a nano second long, that changes the dynamic of the process. In fact that's not even nirvana, right, the real nirvana is can you change your business model, right? And I would use IBM, since we're here, as an example of going from a big box with a lot of people running around it, called IBM of the past, Watson, to an API engine that David Kenny has helped to build that says, we're going to have a platform business model leveraging network effects, and I want to have a supply and a demand curve that are much faster growing than my sort of organic ways of growing a network could be, right, through people point clicking. That's innovation. >> IBM is an interesting company because it is a company with a lot of legacy, but I think gets, as you just described it, but you look at the top five companies by market value today, they're six, 700-billion dollar market companies, they are data companies not just with a lot of data, but they've put data at the core, so it's Amazon, it's Apple, it's Facebook, it's Google, et cetera. They've put data at the core whereas most organizations, I'm sure many that you deal with, they have human expertise built around other assets that aren't data. It might be factories, it might be the bottling plants, et cetera. So there's a gap, I don't know, machine, AI gap between sort of those that are innovating today, now granted the stock market can change and, >> Sure. >> Who knows, maybe the oil companies will be back involved, not to drop but how do you deal, how do you advice your clients on how to close that gap? That seems like a huge challenge. >> Well it is a huge challenge, and I think, going back to the three elements, it would be very easy for you to dive bomb into a transformation effort and say, I'm going to go and get some smart computers and hire a bunch of people that know machine intelligence and natural language process, and all that stuff, and put them in a room, and go create some applications, the bottom line is, that's not unimportant. You got to get your hand on the mountain and start climbing, but the data piece, I mean, if you don't understand how data is going to be relevant to your business and to your clients and their clients, right, in the future, you lose. And the reason why those five that you talked about earlier are so successful is they think a couple of steps ahead on the data strategy, right, and they're not thinking about, most organizations by the way, they'll say we want a data strategy and then they'll relegate the strategy thinking part to their businesses which are bifurcated, and they look at the world in silos. And they're doing exactly what they should do which is take care of those businesses, but when you step back into those five companies you've talked about, they step back from those silos and say, what is the enterprise implications, and how do I create new businesses with correlations of data that I didn't have before? I think that requires a whole different level of strategy. It's C-suite and board that has to guide those kinds of decisions. You don't see a lot of people really getting their hands dirty around intense forward-thinking data strategies at the enterprise level like we're talking about here. >> You believe we are entering or going to enter shortly a productivity renaissance. >> I agree, yes. >> That's sort of I'm talking about our off-camera conversation. Explain why you think that, compare it to sort of the Industrial Revolution. Take us through your scenario. >> Sure. So, I mean, when you think about labor, I mean, what are the things that I think those three elements will give us as a society, as a global community, is a pretty big S curve jump in labor productivity. In fact we have at KPMG some efforts to quantify what that might be, looking at what we call frontier firms, and applying those practices back to incumbents. 90% of most industry players is saying what are those differences that we can model. The fact of the matter is when you go back to the Mechanical Revolution, the Industrial Revolution, people did everything by hand prior, right. Equipment helped them do things whether it was, even the printing press saw changes in society and labor, but when you start to getting into heavy manufacture in the Industrial Revolution, productivity was enhanced dramatically, and instead of putting all of these people who were doing things by hand out of business and out of work, it actually created more jobs, a lot more jobs, and a lot more wealth for society. I think we're heading for a similar S-curve change with smart computers, cloud, and with data. And that the roboticism of people is going to be automated, and people are going to be allowed to practice and use what's between their ears a lot more. That's going to create value, insight, new questions to be asked. I mean, how many times have you ever heard this? Every time you answer a question on something that's very important, you want to understand there's two more questions to be asked. Medicine is that way for sure. But you're going to start to see massive advancement in areas where people have had to use a lot of cognitive skills, right. It's severely under-leveraged because they were doing so much roboticism and doing things that computers can start to do now. So I think you're going to start to see a renaissance, if you will, of people using their nogers in ways we haven't seen before, and that's going to change the dynamics of productivity and labor in a way that's going to create wealth for everyone. >> And it's going to change industry. So, okay, so I got a bunch of questions for you then. >> Steve: Yep. >> Here we go. And I asked this earlier but I didn't really get an answer. Will machines? >> Steve: From me or from somebody else? >> No, from somebody else. >> Steve: Okay. >> Will machines make better diagnoses than doctors and when? >> I mean, what's the regression line? I mean, the samples said, I think today you'll find machines giving better diagnoses than doctors in some cases. >> Dave: Okay. >> I don't know where the regression line sits today, but if you look at the productivity of doctors going a hundredfold, and the morals scattering around lung cancer, it's impressive. >> Dave: Yeah. >> And do you want a doctor involved? Yes, you do, because part of it is in an orthodoxy of trust which by the way ten years ago, you wouldn't put your credit card online to buy anything, right. It's the same kind of orthodoxy. But I do think that machines can read so much more data, interpolate so many more correlations than people that when you add that to an oncologist for example and cancer, you have a super oncologist capabilities which is really what you're looking for. We're not looking to replace the oncologist per se, what we're looking to do is get the productivity of the oncologist from two to 200. >> I was talking about diagnoses. So you would say yes, okay. >> Yep. >> Will large retail stores mostly disappear in your opinion? >> No, I think they'll change. I think that the customer experience is still, we're still people, we need physical space, and we need physical things to touch, smell, and feel. I think those things will change, but we'll still need experiences. >> I'm going to keep going 'cause Steve's playing along. Will driving and owning your own car become an exception? >> Yes. >> Okay. >> I can elaborate if you want. >> Please, yeah, go ahead. >> So, I mean, the first, I mean, we actually did at KPMG a study called islands of autonomy which modeled LA and San Diego, Atlanta and Chicago, and we modeled how do people move. And we did this for a reason because autonomous vehicles are often times amalgamated as one thing. Oh well autonomous vehicle is coming so you better sell your sports cars and your SUVs, not so fast. The reality is mobility is very different based on where you are. If you're in the middle of Kansas or something, you're going to need a truck to run around in your farm, but if you're in LA or Atlanta or Chicago, you're going to move with autonomy, with autonomous vehicles, and then you're going to really enable mobility as a service very clearly, but differently. The way people move in these cities is different, and if the US auto industry understands those differences, and extrapolates those to a global marketplace, they're going to be very advantaged as mobility as a service becomes real, but the first car that goes, I hate all of the viewers that love this category, but sedan is the first cars to go. I would say sports cars, I race cars, so I love sports cars. People still ride horses today but they don't need them for transportation. And SUVs, right, specialty vehicles that you may, it may not, the economies may not be there, but as we know transportation and car ownership, it's going to change fundamentally, and that's going to have a massive effect on FS, right, insurance companies, banks that are doing loans today. It's going to have a big effect on healthcare. Mobility as a service is going to transcend to healthcare, mobile healthcare in ways that we can't see. >> You got great perspective. I got one more for you, maybe a couple more. Do you think traditional banks will lose control over payment systems? >> Well, a lot of them are already nervous about that, wouldn't you think? >> Yeah, but it hasn't happened yet though. >> I understand, the bottom line is no 'cause I think the traditional banks are getting smarter and they're leveraging their own innovation horsepower to understand things like Blockchain, and how to incorporate those things into their business models. So the answer is I think the way they do, look, banks exist because of one reason, trust. They have trusted brands, right. As long as they can stay current enough to be relevant to your banking needs, you're going to stay with that trusted brand. I think the trick for banks is how do they move fast enough, leverage the technologies that make your life easier, and not waiting three or four days for bank clearing of a check, for example. >> That's they say if you're-- >> And get to that trust in a new way. >> Unless you're a Bitcoin millionaire or a billionaire. >> You still need a bank. >> Maybe somewhere down the line. >> Yeah. >> Okay, last one, I promise. Will robots and maybe even RPA reverse offshore manufacturing advantages? >> Yes. >> Can you elaborate and give us a sense of-- >> I think, first of all, if you really look at what RPA is doing in many ways, is disintermediating the value of geographic location in many ways, right. So where I may have had, again this is important that you understand, so I can still go offshore today and get labor arbitrage and get margin, but I'm not rethinking the business. What I really want to do is own, I want to have more control and I want to have more flexibility and growth in that back office function. So it would behoove when you think about our RPA, and bring in our RPA technology so I have it one onshore, two, leverage the data more securely potentially, and then leverage that data as part of my lake to say how do I use that data to correlate to get to what I really need which is customer relevance at the front office, right. So, look, I think that this whole notion of you're in a different country, and therefore the labor pools are different, and therefore their arbitrage will get benefits from that, those days are over. I mean, it's just a question of when does it die. >> Dave: The data value offsets that arbitrage advantage. >> Well, forget that. The arbitrage is dead itself because the machines, >> Yeah, yeah, right. >> You're talking about orders that have made it to a cheaper per unit cost for an RPA, for a bot to do something than it is for a person that has to eat, sleep, take vacation, and get sick, and all that stuff. And so no matter where they are in the world. So what I would say is that notion is dead. It's just not buried. And overtime we're going to migrate again to machines doing all that robotic stuff. But, again, those people, they're going to do different things. It's not like we're going to see hordes, hundreds of thousands and millions of people not be able to work, I think they're going to be doing different things using their heads in different ways. >> Lisa: I like that answer. >> That's a plan. >> Dave: It's good. >> There's a price somewhere? >> I'm absolutely wrong, I just don't know how wrong, right. >> Well, it's fun to think about, and you provided some context. It was very useful. So, thank you. >> And I imagine folks that are attending your session at IBM Think on Wednesday are going to hear a little bit more into that. So thanks for sharing. >> We going to see some specifics, yeah. >> Thanks for sharing your insights, Steve, and for joining us on theCUBE. You guys, the innovation equation is changing, and I thank you for letting me sit between a very innovative and informative conversation. >> Thank you both. It was fun. >> Thanks Steve. >> For Dave Vellante, I am Lisa Martin. You're watching theCUBE live on Day One of IBM Think 2018. Head over to thecube.net to watch all of our videos with our guests, and siliconanglemedia.com for all the written articles about that. Also check out Wikibon, find out what our analysts are saying about all things digital transformation, Blockchain, AI, ML, et cetera. Dave and I are going to be right back after a short break with our next guest. We'll see you then. (upbeat music)

>> Announcer: Live, from Las Vegas, it's the Cube. Covering I.B.M. Think 2018. Brought to you by I.B.M. >> Welcome back to the Cube. We are live at I.B.M. Think 2018, our inaugural event. I'm Lisa Martin with Dave Vellante. We're joined by another Vegas veteran, as we all are. First time guest to the Cube, Bret Greenstein, the V.P. of Watson I.o.T. Offerings. Bret, welcome to the Cube. >> Thank you very much, exciting to be here. >> This is the inaugural Think 2018 event. >> Yes. >> 40,000 plus attendees, expected over 10 keynotes, lots of cool stuff. Speaking of cool stuff, I.o.T. What is happening in I.o.T. this year? >> Yeah, so we've been here in Vegas several times over the last several years talking about the Internet of Things, but what's really pivoted, what's really changed, is people talking about applied I.o.T. How are they using it to get business outcomes. Something different happening. And I think when we all started with the Internet of Things we talked a lot about, connecting stuff and devices. But really, it was always about the data and the effect that data had on changing business, changing user engagement, changing outcomes. And so here, on stage, you're going to see people talking about how their businesses have been changed, how their customers are changing as a result of I.o.T. >> Yeah so, I've always felt like I.o.T. is the intersection of devices, data, and machine intelligence. >> Bret: Yeah. >> How are those sort of three things coming together and what's the data model look like? >> Data model is every type of data. I think what people really didn't expect was it wasn't just machine data coming off sensors, temperatures, vibrations. It's all this unstructured data coming in from connected things that are everywhere in our lives. So sensors with cameras for example, being able to see. It's not just recorded images, but it's information. Tons of information that you need A.I. systems and other systems to interpret. So we're able to take all that data, structured data, numeric stuff coming off of devices and sensors, but images and sound and vibration. Even emotional content in people's dialogue. All of that is relevant to the Internet of Things. >> What's the conversation like with customers? For example, when we say, what physical assets do we have that we can instrument. >> Bret: Right. >> Parking meters or whatever, okay. >> Bret: Right. >> What physical assets don't we have that we should have? How can we leverage our existing data? What's the conversation like in terms of transformations that are going on? >> I think the conversations have shifted a lot. Over the couple years people were talking about we want to connect our thing, whatever the thing is, whether it's an elevator or car or whatever. We want to connect it, what does that mean? And that's shifted very quickly to customers who are coming in talking about information data and insights and they want to know, what should I do to get more of those insights? So I'm seeing customers now with Chief Data Officers or heads of digital transformation. Totally new roles that didn't exist before. And they're coming in with a data centric view. They're saying, we're going to be a digital business. We need to understand all of these live data about our customers and our things and our business process. Help us do that. And so that's much more than just instrumenting the individual devices now. And I find that conversation is really, really focused on the value of the data. >> What about the industry impact in this context? Do you see, does I.B.M.'s perspective, is I.o.T., it's certainly transformative. >> Bret: Right. >> But is it disruptive or it is sort of the guys with infrastructure are going to evolve to it? Is it more evolutionary, is it more disruptive? How do you see it? >> I think there's room for both. Obviously traditional players are going to instrument their business process. They're bringing in connected cars and all that. But you could also look at those same industries and say there's new players emerging who are coming in with software defined products that are digital by design. And they can come in and suddenly become leaders in their field. I don't think people would've expected companies like Tesla to be so disruptive in automotive, but coming in as electric changes the game without having to build on a hundred years of mechanical design. You're building on some new principles. And now we see some new players coming in to automotive who've never built cars at all before. Like Dyson for example, that recently announced they were working on electric cars. So I think a digital platform, a digital way of thinking, also creates opportunities for new entrance in every market. >> I think automobiles is a great example because it's an industry that hasn't been largely disrupted. But then you use an example of Tesla which is extremely innovative, you could actually pretend disruptions coming out. And you see whole ecosystems form around that. >> Right, right. And I think what was so powerful about the effect they had was it's a software defined product. The software in it is upgraded constantly. Sometimes you buy the car, the next day you get a new feature you didn't even expect. And this is the way we've come to appreciate, experience through mobile and everything else. Software that continues to improve products that get more valuable over time. Not less valuable over time. >> So let's talk about Watson and I.o.T. I'd also love to maybe take a slice on how I.B.M. is helping customers that maybe have been around maybe the flip side of a Tesla. They've been around a long time. How are they leveraging Watson and I.o.T. to transform their businesses? So kind of start with, what's new with Watson and I.o.T. >> Sure, so I mentioned before that there's a whole part of many data types now that previously were very hard to interpret through traditional analytics. But A.I. and machine learning give you the ability to absorb and consume some of that data. Unstructured sound, images, video, vibration, all of that stuff is now able to become part of a business process. So even traditional companies that have been around a long time can start to look at the data coming off of cameras, visual inspection in manufacturing, sound and voice for example. We work with Jefferson Hospital where they brought Watson into patients rooms so you could ask questions like visiting hours, or set the temperature. Put the patients in control of their experience in a hospital. That takes a traditional experience, like a hospital recovery room, and turns it into something A.I. driven, I.o.T. powered and puts the patient at the center. So very big changes can occur when you do that. >> How far do you see us being able to take A.I. in this whole world of I.o.T.? How far should we take it? >> I think we have to start become more appreciative of the power of machine learning to drive outcomes that are not as easily prescribed with code. So all of us, all of our business processes, all of our businesses will be enhanced with A.I. And we shouldn't look at that in any other way as a better tool to understand data in a way that's different than the way you interpret data. And so it wasn't long ago when big data just meant writing an algorithm across large volumes of data. And now we literally have algorithms whose job is to find patterns. Whose job is to understand data from training. And deliver an outcome that you couldn't have prescribed before. And so those type of problems, it just opens up a class of problems we can all solve now that we couldn't before. >> You're seeing a whole set of digital services emerge. The lingua franca is changing. It's sense, hear, see, respond. >> Bret: Right. >> Optimize. >> Right. >> Fix. (chuckles) >> And all that comes from comprehending. So having a system that can look. For example, I have a camera outside the window of my house and every once in a while I feed the images into Watson to see what it sees. When I first did it, it would say truck. But later, as we make Watson better, now it says FedEx truck or U.P.S. truck. It can read the writing, it can see the patterns. Every camera should know what it sees. Whether it's in a car or a home or somewhere else. Because it's much more valuable than just taking a picture and letting a human being interpret it later. So cameras should know what they see. Machines should know what they hear. Machines should tell us when they're about to break based on vibration or sound. And so this is possible with machine learning. >> So you're saying machines actually take on a whole new set of human-like activities. Digital twins is an example. >> Bret: Okay. >> What's your perspective on, let's start there, digital twins? >> Digital twins, for me, represents sort of the evolution of I.o.T. and that it's digitalizing things. And so, a thing that has no connectivity and very few sensors, is just a thing, it's just a box, it's a block. But as you start to put sensors on it and start to understand it's behavior, it's motion, it's vibration, it's location. Any of the mechanisms, the angels, all this stuff. Then you add a virtual representation of that thing. And if you can do that with all the things in your business, you can start to look for patterns. You can start to assess what's working and what's not working. So I think it just represents a true digitization of a business, of a class of objects in your business. >> Does I.o.T. make security a do-over in your opinion? >> No, but it certainly raises the bar. And so, when we all started connecting our computers to the internet, I remember everyone being panicked. It you put a disc in your machine, you might get a virus. Then we connected them to the internet, we all panicked, but the tools evolved and we start to get things that can help detect zero day problems. In the case of I.o.T. we've got these software defined products that are connected. That are inherently vulnerable cause they're in the real world. They can be touched by other things. So it raises the bar in the expectation of monitoring normal behavior for things. Monitoring all kinds of different threats and stuff, So companies like I.B.M. they focus so much on security and security services, we build that right into our platform so we can keep an eye on that. And also, when things occur, be able to push out new software that is protected. So for more updates, keeping the products live and current is a huge security protection. >> Bret, how would you describe the ecosystem. I.B.M.'s point of view on the ecosystem that you've got to form and catalog in order to succeed in I.o.T.? What does that look like? >> Yeah so, there are so many things for people to do in the world of I.o.T. That I.B.M. doesn't prescribe to do all of them, at all. There's certain things that we're really, really good at. We're certainly good at our cloud infrastructure and analytics and the platforms that enable this and deep industry knowledge. But the ability to apply that in businesses, to take on machine learning algorithms and make it work on the thousands of classes of machines in manufacturing, requires a huge partner ecosystem. So we work very openly on contributions to standards and open source. We certainly work with partners to build a lot of value around our stuff. So for example, on stage this week, we have several partners who are going to be up there. One of them is Harmen, who builds all kinds of things that's including info-tainment units in cars and the professional equipment that goes into hotels and buildings. So we work with them to build great innovative value together and they do things that they're experts in and we do what we're experts in. >> So, from an I.o.T. perspective, what are some of the cool things that are here at I.B.M. Think 2018, that those that are attending are going to get to see and feel and touch and smell? >> Well there are some things I can talk about, things that I can't. Tomorrow we have some very exciting announcements coming up. Going to talk a lot more about Watson and I.o.T. coming together, that's all I can say about that. You'll also see physical representations of things. There's a Jaguar Land Rover out here on the floor. To look at where we have contributed significantly to the engineering and the software development inside these kinds of products like J.L.R. So they're going to be up on stage talking about some of the things we're doing together. You'll hear A.B.B. here talking about some of the work we're doing around manufacturing techniques and helping manage wind turbines. So all kinds of really cool, industrial use cases. It's really exciting and I think working in I.o.T. is great because not only do you get to talk about the technology and the analytics and the data, but you actually get to see things. So it makes all of this feel very real when you walk up to and see a thing that's infused with I.o.T. and made better because of I.B.M. >> What inning are we in? >> What's that? >> What inning are we in? >> Oh it's still early, still early. Third inning still, mostly because so much of the market is still working to figure out how to take advantage of the data and the insights about this to transform their business. I think if you thought of the dot com era and how long it took for companies to emerge to be truly digital e-businesses, on demand businesses. The I.o.T. businesses, the A.I. driven businesses of the future, still very early. Some of them, you probably don't even know their names yet. But they're going to be the leaders that's coming. >> Do you think it'll happen faster because there is an internet? Or not so much because of the physical infrastructure that has to get built out? >> The infrastructure is actually not the gate at all. >> Dave: Okay. >> The real gate is the cultural difference of having people who are data driven, data thinkers. Having a leadership role in our clients. If you can think about it, mechanical things have dominated for a hundred years. Software engineers are still not even the most senior people in most of the companies that build physical things. But to have the data scientists, have the data leaders have a strong enough role to define business process. It's really the readiness and maturity of those data leaders. >> Yeah so the culture of a mechanical engineering culture that says "don't touch my things," >> Right. >> I'm not going to let a software engineer come in and mess with it because it works, it's secure, I trust it. >> Right. >> So that's the cultural one of the cultural dimensions. >> It's to look at what the data might mean. Just understand how your users use your things or if you want to understand what they're doing with those things somewhere else. Or even with the value of your insights of your users are and building entirely new ecosystems of the data of I.o.T. >> Alright, so we're in the third inning. We'll say the top of the third. >> Okay. >> But one of the things that you shared with us is that you're excited about is this is about applied I.o.T. To get business outcomes. >> Yes. >> Shared some examples that attendees of the event are going to hear from A.B.B., you mentioned, you mentioned the >> Bret: J.L.R. >> Land Rover that's here. Harman as well. And maybe some best practices for how to advise companies to get through some of those cultural hurdles, we'll say, to start embracing the opportunities that are within the I.o.T. space. >> I think the best thing people could do is to start to really, I'm going to say it again, put value on data science. It doesn't mean everyone has to be a data geek. But it does mean you have to have a certain value on the skills and the insights that come from a data driven business. What does it mean to make decisions in real time based on your customers? For a hundred years when companies shipped a washing machine it went into someone's house and sat for 10 years and they never heard from the person ever again until they bought another one 10 years later. But now when you ship a washing machine, you want people to connect it to the wi-fi. You want to know the features that are used. Suddenly as a manufacturer of things, you have to respect the data coming off those things because they inform you on how to design better. How to deliver better service and value. Which means those engineers who were the experts in washing machines, now have to be the experts in the data of washing machines and the data of their users. So, I would say, focus on the education, the recruitment, the enablement, the empowerment of people who are data centric by nature and who are looking for the transformation of a digital business from a physical business. >> Awesome, Bret thank you so much for stopping by the Cube and sharing your insights. >> You're very welcome. >> Good luck tomorrow with your presentations and we are going to be waiting on the edge of our seats for those lots of I.o.T. announcements. >> Very exciting. >> Very exciting. >> Okay. >> Alright you heard it here. >> Thank you so much. >> You can watch all of our good stuff on thecube.net live, of course, as we are now as well as the interviews that we've already done and those that we'll be doing for the next two days as our coverage continues of I.B.M. Think 2018. Also check out siliconangle.com our media site for all of your real time coverage of this event and others. For Dave Vellante and Bret, two Vegas Veterans, I'm Lisa Martin. Stick around, Dave and I are going to be right back after a short break. (upbeat music)

>> Voiceover: Live from Las Vegas, it's theCUBE! Covering NAB 2017, brought to you by HGST. >> Hey, welcome back, everybody. Jeff Frick here with Lisa Martin. We are wrapping up three days of wall-to-wall coverage here at NAB 2017, theCUBE's first trip to NAB. What a great three days it's been. Lisa, I really enjoyed working with you over the last couple days. And what a show! >> Oh, what a show. Frick and Martin together again. This is the biggest show I've ever been to and seen and experienced. The breadth of solutions here for just the... I don't want to say amateur photographer or filmmaker to the six major film studios. That is so shocking, to actually see all of it in person. >> Jeff: It's a little overwhelming. I took a little walk around at lunchtime and out in between the convention center they've got the satellite trucks, and the satellite dishes, Steadicams, and drones flying around... >> Lisa: Yes. >> There's a Crazydrone on the back of a jet ski. Really, a bunch of exciting stuff. 360 cameras all over, virtual reality cameras all over. It's overwhelming, the creative tools that can be put in most people's hands today are virtually unlimited. But it just makes me wonder, is it too much? I guess it's always great to have more tools to work with from a creative point of view, to just have alternate ways to realize your vision, and bring your vision to life. >> Yeah. I would agree on the comment of 'overwhelming'. There's so much to see and do here. When I walked out to lunch, I felt like I was on a treadmill that wasn't going anywhere. Like, where's the exit? But you know, the whole theme of the event, the M.E.T. effects, I think being here you're feeling the convergence of media, entertainment, technology. One of the great quotes that I read before we came here from Shira Lazar, who's the official M.E.T. evangelist here is, "If content is king, then technology is queen." And I think we really saw that underscored in all of the different guests that we had on the program the last couple of days. From security experts to those that are enabling large-scale rendering in the cloud for movies like Deadpool 2. Talking to Adobe who's enabling the next aspiring YouTube star, to be able to have access to what they need to do to be creative and really let their creativity flow. >> Right. And in the comfort zone you see the same things that we see all the time. You see democratization of data, access to the data, we see more data-based decision-making. Especially, what I found really interesting is the conversation around audience development and audience knowledge. You know, the great advantage that Netflix had over the original cinemas or HBO is they actually knew who was watching. They had profiles on how long did they watch? When did they change channels? What were their similar likes? It's all the same things: the amazing amount of power that can be delivered via cloud to any individual or small company to really be a game-changer in terms of capabilities where before, they would have to make these tremendous investments. Same things we hear over and over and over at all the other events that we do. >> Exactly. I would say I would agree with you on that. There was a lot of transcendence, the things that we saw here. Obviously, at a media and entertainment show, but things that are very applicable in retail, in sports and sporting events, from the filmmaker studio down to the individual guy or gal. Even to healthcare, we talk about this massive volume of data. Today, incredible opportunity. A historic event, really, that happened with NASA The first-ever live 4K stream conversation from 250 miles above the Earth down to Las Vegas, of all places, where that wasn't possible too long ago. And you think of how massive data sets are. Not just in video, but also in music production. We even look at things that are transcendent to healthcare, but might not be videos. It might be the massive file sizes for all the imaging. There's a lot of cross-pollination with a lot of the other shows that we go to. I agree with you on the audience front. Being a cord-cutter... we're all cord-cutters these days, right? Something that was interesting to me was, like you said, the streaming providers know so much about the audience. And you think, well, traditional film, they don't know as much, it's been more qualitative. And actually, when we had Joan Wrabetz on from HGST, she was actually saying there's benefits on both sides. That the streaming providers actually can't change content, whereas the filmmakers can, so there's really a lot of collaboration and learning that both can do from each other even though they are, obviously, competing for mind share. >> But Lisa, you're trying to be way too professional. Let's just call a spade a spade. You got to ball with an astronaut. >> I did! >> She said there's only 40 astronauts left in the US space program. >> You're right. >> We've had two of them on theCUBE. Both women in the last six months. >> That's right. I can't even say it was a dream come true, because it's never something I dreamt was even possible. But having started my professional career with NASA aims in the Bay Area, I recognized Tracy Caldwell Dyson from her photo I saw many years ago. What a great ambassador, and very inspiring. She was talking about what inspired her to want to be an astronaut back when she was 14. The Challenger accident, which had a teacher. And we were asking her, with real-time video capabilities, what does that mean for NASA? And she was saying, think of the next generation of astronauts and the next generation that will be going to Mars. How much more inspired that they're going to be because, with this technology that they even shared today, it makes space exploration so much more tangible because now there's these incredible videos and images that can be transmitted down to Earth in real time. So that was probably one of the highlights of my life, I would say. So thank you for handing over the keys for that one. >> It's just great. When they arrived on the set after the broadcast from space, the whole area lit up. They're such, as you say, ambassadors. Astronauts as ambassadors are super smart. They're super friendly. They totally have their stuff together. To get an opportunity to have her on was really cool. That was a really great moment, and so fun. You had the background to appreciate it even more than most of us did, so that was a kick. It just goes to show you, it is really about the future. There is a very bright future ahead. We're going to keep covering it. We'll still keep going out to these events, and hopefully be back at NAB next year. >> Lisa: I hope so. >> All right. So with Lisa Martin, I'm Jeff Frick. You're watching theCUBE. Thanks for watching us from NAB 2017. Keep an eye out. The busy season is just getting started here in May. We're going to be all over the airwaves for all the rest of the summer. So keep an eye on siliconangle.tv, youtube.com/siliconangle and siliconangle.com. Thanks for watching. [Upbeat Music]