>> Announcer: Live from Silicon Valley, it's theCUBE, covering Mobile World Congress 2017. Brought to you by Intel. >> Welcome back, everyone. We're here live in Palo Alto for SiliconANGLE Media's theCUBE's new studio, 4500 square feet in Palo Alto. Just moved in less than a month ago, and we're bringing you all the in-studio coverage of what's going on in Barcelona, Spain at Mobile World Congress. This is day two of two days of coverage. Here in the studio we're bringing people in that's in Silicon Valley into the studio, experts, entrepreneurs, venture capitalist investors, angel investors, and of course, analysts here from our own team, and we have Peter Burris with me here. And we're covering all the action. Of course, we have reporters and analysts and friends on the ground doing call-ins in Barcelona, bringing you all the action, and really, bringing the big story that's not being told, which is AI, IOT, and cloud-ready, cloud-native action is happening. This is the disruptor, the calm before the storm as we were saying earlier yesterday. Peter Burris, great to see you. We were talking yesterday morning on the kickoff, let's take that to the next level. Cloud-native, IOT, really the big story that's not being told at Mobile World Congress this year, mainly because it's just in everyone's face right now, and people are making sense of it. Your thoughts on this as you are looking at the research, looking at the marketplace, this is reality. The IOT is real. >> Oh, it's very much real, John. Let's start with why cloud and mobile are so important together. In many respects, the thing that made the cloud real is mobility because the minute that you don't know where your device is going to connect, where the termination point's going to be, then you don't want to have to control and own that network. And so in many respects, the whole concept of mobility catalyzed the need for the cloud because you didn't want to have to utilize a, you didn't want to have to build your own network to support people as they moved around. So the cloud as a front end, or as a set of capabilities that supports mobility is really crucial to this whole concept, and it's somewhat surprising that it's not more closely tied together at Mobile World Congress. But the most important thing that we could talk about obviously is that IOT is going to have a major impact on all kinds of different factors. It's going to have a major impact on the devices that are manufactured, it's going to have a major impact on what the scale efficiencies that you have in manufacturing, the nature of the sensors, the nature of microprocessors, how much memory gets put on stuff, how much flash memory is going to be manufactured over the next decade. All these things are going to have a significant impact on the concept of mobility and what it means and the networks it provided over the course of the next 10 years. >> Peter, I want to bring up something that you brought up yesterday, and I think this is important, that's why I wanted to do a real drill down on what seems to be a major paradigm shift and inflection point. We've been talking about autonomous vehicles, media entertainment, smart cities, smart homes. Those are all the sexy demos at Mobile World Congress. But the real change, as pointed out by Val Bercovici who just came in as CTO is that the sea change underneath it, and you pointed out yesterday the convergence between enterprise and consumers coming together is that this internet of things and people, IOTP, or IOTNP, 'cause things can be sensors and devices, are changing it, and what's obvious to us and now coming out of Mobile World Congress as it's just starting to be seen by the mainstream press and media and community is that the TelCos aren't used to dealing with rapidly provisioning things. They're used to a subscriber who buys a phone, dials up a service, gets provisioned and connected, and they have a number, and then they try to connect to the base station and get on the internet. That's simple, and those connections we all know fail, but now imagine that multiplied by millions and millions of devices that are going to be turned on and connected. This is a scale problem, this is a network problem, this is a physics problem. >> Well, it's a physics problem-- >> Explain your theory on this. >> Yeah, it's a physics problem at a very, very base level. Just talking about the TelCos for a second. You're absolutely right, John. We're talking about, when we talk about the scale problem in the TelCos, it's not that they don't know what to do with their networks, it's not that they don't know how to connect devices to the networks. They just don't know how to provide it at a service level. It's going to be demanded by the scale of the devices moving into and out of networks as we think about IOT and P, the TelCos have historically thought about, they've thought about the assets that they have in place, the rates that they charge for those assets, the returns they generate, the tariff rules they work with with governments around the globe. They tend to focus on, good or bad, 10, 20-year time horizons. >> And their P is phone, not people. >> That's right, their P is absolutely. Their P is phone, and I can, and you were probably around. I can remember when you could not buy a phone that didn't have, on a particular company's network, you still can't buy a phone on a network today. You buying a mobile phone and it goes, it's associated with-- >> You're buying a carrier. >> That's right, that's exactly right. And that's how TelCos want to work. Now, they're hoping that eventually they're going to find themselves in the position to be able to spin up devices very quickly, but the reality is that's not how provisioning works in the real world. It's one of the reasons why TelCos continue to get their lunches eaten by companies that are building out their own networks and doing a much better job of rapid provisioning. >> You and I were talking last night off-camera about this notion of IOT and P, and of course, we all believe in and we're passionate about it, but you made a comment that was interesting. It was that we're going to look back at this time in history as a moment where before and after kind of, before Christ, after Christ, however you want to look at it. I mean, there's always that AD, BC kind of thing going on where before, I always call it before Steve Jobs and iPhone. Now it's going to a whole other level with the societal changes from little things, like we had a guest on talking about waste disposal efficiency. Traffic light management, healthcare, every single digital service. NTT Docomo's investor was on yesterday. She was talking about investing in services and bringing AI as a service, not network services, lifestyle services. What do you mean by that, that this is going to be something that we're going to look back 50 years from now and say this was the moment? Can you expand your? >> Yeah, absolutely, John, and it's really actually pretty simple. If you take a look at how executives are starting to think, what's happening is for the first time, we're really starting to look at data as an asset. That's a big question, but let me try to break it down and be a little bit more concise about what I mean by that. When we think about IOT and P, we're thinking about the idea that we can distribute enormous, billions of devices that are going to be sources of data. They're going to be going into the analog world, put into the analog world, and they're going to take analog signals and turn them into, and transduce them into digital signals. Once those signals become digital, then they hit big data, they hit AI, they hit machine learning. That's what's catalyzing a lot of the social concerns about, well, what does it mean for machines to be more autonomous, to take more responsibility? What's going to happen with business accountability when business are increasingly relying on machines that quote, "think." When we think about these big societal changes, we're talking about the ability that IOT's providing, IOT and P is providing, that for the first time how we're going to capture enormous net-new data, how we're going to process that enormous net-new data, and then ultimately, what we call systems of enaction, how we're going to enact specific events back in the real world as a consequence of what machines say is the right thing to do. That is a demarcation point. It moves from a machine being regarded as a tool, and almost exclusively as a tool, something that performs work better but having that work be very well described and very well articulated and the concept clear to something that might actually introduce new work or do work differently. Take responsibility for how it performs work. That's a major sea change. And so when we say that it's going to be, we'll look back and say, "It was before this time "and after this time," it's because we are now in the position to economically be able to gather these streams of data, process them in ways that are unprecedented, and then have the results of that processing enact in unpredictable ways, and that's a major change. >> I don't know if we can talk about some of your research that's coming out, I dunno, can we touch on some of the points? This has yet to be released research from the Wikibon team headed up by Peter with SiliconANGLE Media. I want to just point out, 'cause I find this interesting, you say that there's a architectural decision point within IOTP, a new phrase, hashtag IOTP if you're interested in working with us, just hit us up at Twitter. But there's really four points you point, physics, the law, legal, of course, everything's legal. Physics, legal, economical, economics, and then, authority. >> Right. >> What do you mean by those four? Can you just take us through conceptually these are dimensions, they interplay, are they dependencies, are they interdependent, are they all intertwined? What's the rationale behind these architectural forces? >> When people think about information systems historically, they've been relatively well circumscribed. So, I have an employee that I'm going to provide a service to from a network that I control that has latency requirements and aren't that big a problem because at the end of the day a human being doesn't operate at nanosecond kind of levels, and I got a machine that's mine, and I own running an application that I've licensed. That is a very, very tightly bound unit. When we start introducing IOTP and some of these other things, now we're talking about emergent behaviors that might be far away that we don't control, we're working with partners, et cetera, and the basic architectural challenge of thinking about what do we have to do to get a handle on the requirements of the processing, 'cause at the end of the day these things are still computers, and they still have operational characteristics that have to be accommodated. We think that there's going to be four factors that are going to influence how what we call the edge zone expands or compresses based on the work that needs to be conducted. One is physics. You're not going to go faster than the speed of light, and in fact, generally speaking, if you look at the distance that you have to travel, you're going to be outside the automation zone. You're going to be outside the automation zone if light has to travel, at best, you're going to be about a 10th of the speed of light, so if your automation zone, if you want your automation zone to be about 100 miles, then it means that from there and back with the speed of light you're not going to be able to automate anything that takes longer than that, just for example. Physics is one. >> Physics and wireless is a great example of physics. >> Wireless is, yeah. >> And moving packets around. >> None of this stuff works without physics, right. The second one is legal, that the reality is is that while the laws of physics are relatively immutable as far as we know, there are also government regulations that are what they are, and that could include privacy, it can include requirements for disclosing things, and so, those also, borders are going to have an impact on this notion of automation zones, or edge zones as we call them. Economics is another one. It costs money to move data from point A to point B, and the question is how much data's going to move. A lot of people think that everything's going to go up to the cloud, it's going to be processed up there, and then some instruction's going to come down for automation. That's probably not the way it's going to work. Our findings are suggesting-- >> Not only is it the cost of data, I would argue that also the product design criteria will be impacted economically on that decision point. >> Absolutely. But that's based on how much does it cost to move the data around. The operational characteristics of a product or service are fundamentally, a digital product or service, are fundamentally tied to the cost of moving data. We think that 95-plus percent of the data's actually going to stay in the edge. And the last one is authority, and we kind of touched upon this a second ago in that we're now suggesting that machines are going to take actions without human intervention. Not just actions, but they're actually going to change the scope and nature of the actions that are going to be taken. What does that mean? What does it mean for a machine to act on behalf of a brand? Or on behalf of a person? People use a simple explanation, "Does the autonomous car take out the old lady "or the cub scouts if you got a problem? "Or does it do something else?" It's those kinds of things that we don't know the answer to. A lot of the questions of authority and how we distribute authority and how we codify authority and how we track authority is going to have a major impact on what limits to behavior we put on these things. >> There's also the security angle alone is another one, too, just like basic stuff. These are interesting. And you see these architectural forces. Are you calling them forces, factors, variables? >> Just factors simply because the concept of factor, or you can call it constraints, is the idea that your decision has to factor these things, so we're just calling 'em factors right now. >> Alright, so let's step back now, and look at some of the commentary from this week in Mobile World Congress and our interviews here in theCUBE as well as the remotes. Certainly the hallway conversation is the business model of the TelCos. Saar Gillia who was on yesterday brought up a point of, hey, where's the use cases? Show me the use case, and then I'll say yes. And it's this too complicated, he was not seeing the use cases, and he was saying, "I'd prefer more battery life than "more one gigabit wireless right now" given that's his current situation. The balancing of where to get started seems to be the number one theme. What do I do next, what's the first step? Will the bridge collapse that I'm trying to cross to this future? Or I can't see the other side? Is the world flat or round? These are kind of more personal feelings that people have around taking that leap of faith into this new world? How do you advise and package that together and assimilate that? I mean, do you, how should people look at that? >> I think it's a great question, and I wasn't part of the conversation yesterday, but let's look at that for example. Today, if you're using your phone, you effectively have a relatively simple number of sensors in your phone, relatively simple number of transducers, right. You have a chip that turns your analog voice into a digital signal, so there's that in there. You have some neat stuff that presents the screens, so there's that in there. You have a microphone, et cetera, that kind of stuff, but when we start thinking about 5G and what networking could become, as we talked about yesterday, it's not so much the absolute bandwidth speeds, and it certainly is not going to have any impact on latency for the most part. It really is the number of devices that you can support at one time. It allows for greater density of sources. Now, without looking at 5G, we can talk about a phone being able to support not just a few generators, or a few sources of data on that phone, but maybe dozens, so maybe things that, you know, the whole concept of wearables. Again, do I want to get involved in the use case? No, you and I are sitting here being analysts, and that's not our business. But are there going to be use cases for more wearable technology? Well, if you're sick, if you have a chronic disease, just for example, yeah, that's a use case. I could see people actually living much higher quality lives because they can support more sensors as a result of 5G, with greater security. Again, we go to the autonomous car. There's going to be a lot of sensors in an autonomous car. Most of them are going to operate locally, but having said that, it might be nice if we could actually have a very, very fast low-cost network with inside the car itself to handle a lot of that work. I think we've, human beings, developers, have always found new use cases when given more compute, more memory, and more networking. I don't think that's going to change. I think we're going to see more of that. >> Peter, what's your thoughts, if you had to summarize and encapsulate it into a narrative, Mobile World Congress 2017, now looking back at day two kind of coming to a close, seeing what's out there, how do you look at that? How would you tell someone here is the story of Mobile World Congress? Tell that story. >> To me, John, having looked at the stuff come over the transom and you know, a lot of new devices being talked about and generating a little bit of excitement, a lot of new this and a little bit of excitement, I think that the question for me is are we moving into a period where integration's going to matter again? And I think in many respects that's going to be kind of the subtext of what's coming out of Mobile World Congress. Is it good enough to have the best of breed device and this and that, with a software stack that's doing this and that? Or is there going to be more value to the enterprise and ultimately to the consumer by taking more of an end-to-end perspective? Apple from a consumer and an experience standpoint has done that and has, what is it? They're worth $150 billion more than any other company on the planet right now or something crazy like that? Don't quote me on that, but I think that's what somebody told me. >> Trillions of dollars in cash overseas, for sure. >> Yeah, so it's that notion of are we moving back into a world where integration is going to matter because we're going through a period of significant discontinuity. >> Integration is a great point, 'cause I see that, I do see that as a thing, and bring the Apple example. Apple, the way they develop might be different than say, what we see in an open source, for instance. If you look at what Intel's doing, and I look at Intel as a bellwether, and this is from my perspective, because they have such a huge long game in play, they have been the leader in my opinion in the tech industry playing the long game, and they have to because they make chips. And they're looking at the 5G as an ecosystem play, and they're admitting and saying it's not one vendor. They don't say take village, but they're basically saying it takes a village to rise all the tide or float all the boats, if you will. If you look at what Intel's doing, they're essentially saying that it's an integration game through their own moves, which is ecosystem, playing well together. Now, you could fight for best of breed on point solutions, whether it's a Snapdragon Qualcom, or Intel processor on the device. At the end of the day, it's, as we were saying, network function virtualization to make those dynamic networks work seem to be the key. To play in that, if as a society globally, to your four factors, it has to be an integration game. No one company can do those factors. >> You're absolutely right. Here's how I would say it to put a slightly different twist on it. The tech industry has moved from a product orientation to a service orientation, or is moving from a product orientation to a service orientation, from an orientation where we focus on what's the intrinsic value of what we're buying to what's the utility of what we're using. From a "Hey, let's a put a spend a lot of money upfront "and maybe we'll get to some point of time in the future "where it's valuable" to a, "Let's only pay for what we got." It's difficult to imagine the tech industry moving successfully into that service orientation without taking more of an integration approach to it. Certainly that's what Amazon's trying to do or AWS is trying to do, that's what Google is trying to do, that's what all the companies that are trying to move infrastructure into the cloud are trying to do, so I think that this is a general issue. If we're moving to a service orientation, we have to start taking the integration view on things. >> Awesome, great, Peter. You're watching theCUBE. This is SiliconANGLE Media, Inc., and SiliconANGLE Media, Inc. comprises of siliconangle.com, led by Rob Hof, that's our publishing journalism, wikibon.com led by Peter Burris and research, and theCUBE, our internet TV led by Jeff Frick, and of course CrowdChat is the data brand and the data science, and we love bringing you this great content. Pete, I'll give you quick plug because I know that you've been doing a ton of work building out the research team at Wikibon and expanding the work behind the firewall, it's a paid subscription. Some premium that we see on siliconangle.com for the most part. A great body of work on the research. I want to congratulate you, but give you an opportunity to share with the folks who are watching what's going on with research and some of the things that you're working on and why they should potentially reach out to Wikibon. >> Yeah, so we're focused on a couple of relatively simple things. We're not a huge team, so we tend to focus less on products, again, the idea of let's take a look at the intrinsic value of products, and we focus more on the impacts. What does it mean to get utility out of things? How do you get utility out of whatever you buy? The other thing we focus on is disruption, and we talked a lot about what are the disrupting factors. IOT, big data, and what we call the systems of enaction, all supported by significant changing infrastructure and new digital business models. So, it's kind of a combination of those five things that we are focusing our time and attention on. Ultimately, we want to be in a position to help our clients make decisions that improve the value of their business by better utilizing data through these digital models, digital business models that require these technology changes to go. >> Great, and it also helped show Mobile World Congress is about cloud-ready. You had a great report on Amazon we posted on siliconangle.com. What was the summary, bottom line that big body of work you did about Amazon that the headline was, "How big can Amazon be?" What was the key findings from your big assembled report on Amazon Web Service? >> The big finding is Amazon's going to get big, but the cloud's also going to get big, and we think that Amazon, the simple finding is, we think Amazon's going to hold share. That may not sound like much, but for the most part, most of the value's going to go into SaaS, most of the value's going to go into the use cases associated with stuff. That's where a lot of the money's going to go. Amazon holding share, given that they're one of the, in many respects, they created this whole thing, is actually a pretty stunning statement. And it all started, John, because when we went and we looked at our semi-annual update to what's going on in the cloud marketplace, the question that kept coming to us was, okay, so we think it's going to go this fast. Well, what's Amazon going to do with that? What's it going to mean to Amazon? How is Amazon's growth going to affect these things? And so, we started with that answer. We built our models and talked to a lot of users, built our scenarios, so we think that Amazon's going to continue to grow very fast, we think it's going to be a $40 billion company, $40 billion-plus company >> John: In revenue. >> In revenue, AWS. >> John: Not Amazon. >> Not Amazon, Amazon's a totally different beast. We'll see what Amazon does. But AWS will be about a $40-plus billion company in four or five years, and still have about eight-plus percent market share in the entire-- >> And Microsoft has changed their game, they're coming right after Amazon. >> Microsoft, Oracle, IBM, Google, and when you start talk internationally, Ali Baba, there's going to be a dozen companies that create enormous businesses. >> And there are companies that don't have a cloud that are late to the game and might not have a seat when the music stops in the old musical chair analogy, so certainly we know who they are. >> You know, what's going to happen to the TelCos? Good question. >> The world, we live in very exciting times as the saying goes. Peter Burris, great to have you, great commentary. Love what you're doing, I think the research around IOT and the edge is a fundamental architectural shift. You've got the four forces laid out. Congratulations, looking forward to doing more where there's totally going to be a game-changer. This will impact everything that we live, and it'll make the autonomous vehicles and the drones and the AI and smart cities a reality. Thanks for the commentary. More Mobile World Congress coverage here in Palo Alto, breaking it all down. We've got a couple late night call-ins, so stay with us. Hopefully, folks will be sauced up a bit, and maybe share some of the news and breaking stories from the hallway. More from theCUBE after this short break. Thanks for watching. (upbeat electronic music)

(techno music) >> Announcer: Live, from Silicon Valley, it's "the Cube," covering Mobile World Congress 2017. Brought to you by Mintel. >> Okay, welcome back everyone. We're here live in Palo Alto, California, covering Mobile World Congress, which is later in Spain right now, in Barcelona, it's gettin' close to bedtime, or, if you're a night owl, you're out hittin' the town, because Barcelona stays out very late, or just finishing your dinner. Of course, we'll bring in all theCube coverage here. News analysis, commentary, and of course, reaction to all the big mega-trends. And our next two guests is Guy Churchward who is the President and CEO of Data Torrent, formerly of EMC. You probably recognize him from theCube, from the EMC world, the many times he's been on. Cube alumni. And Phu Hoang, who's the co-founder and Chief Strategy Officer of Data Torrent. Co-founder, one of the founders. Also one of the early, early Yahoo engineers. I think he was the fourth engineer at Yahoo. Going way back on the 90s. Built that to a large scale. And Yahoo is credited for the invention of Hadoop, and many other great big data things. And we all know Yahoo was data-full. Guys, welcome to theCube's special coverage. Great to see you. >> Thank you so much. So I'm psyched that you guys came in, because, two things. I want to talk about the new opportunity at Data Torrent, and get some stories around the large scales experience that you guys have dealing with data. 'Cause you're in the middle of where this is intersecting with Mobile World Congress. Right now, Mobile World Congress is on the collision course between cloud-ready, classic enterprise network architectures with consumer, all happening at the same time. And data, with internet of things, is that going to be at the center of all the action? So, (laughing) these are not devices. So, that's the core theme. So, Guy, I want to get your take on, what attracted you to Data Torrent? What was the appeal for the opportunity? >> You mean, why am I here, why have I just arrived? >> I've always data-obsessed. You know this. From the days of running the storage business on their data protection, before that I was doing data analytics and security forensics. And if you look at, as you said, whether it's big data, or cloud, and the immersion of IOT, one thing's for sure, for me. It was never about big data, as in a big blob of stuff. It was all about small data sprawl. And the world's just getting more diverse by the second, and you can see that by Mobile World, right? The challenge then you have is, companies, they need to analyze their business. In other words, data analytics. About 30 years ago, when I was working for BA Systems, I remember meeting a general of the army. And he said the next war will be one in the data center, not on the battlegrounds. And so you really understand-- >> He's right about that. >> Yeah. And you have to be very, very close. So in other words, companies have started to obsess about what I call the do loop. And that really means, when data is created, and then ingesting the data, and getting insight from the data, and then actioning on that. And it's that do loop. And what you want to do, is you want to squeeze that down into a sub-second. And if you can run your analytics at the pace of your business, then you're in good shape. If you can't, you lose. And that means from a security perspective, or you're not going to win the bids. In any shape or form. That's not a business-- >> John: So speed is critical. >> Yeah, and people say, speed and accuracy. Because what you don't want to do is to run really really fast and fall off a cliff. So you really need to make sure that speed is there and accuracy is there. In the good old days, when I was running security forensics, you could either do complex end processing, which was a very small amount of information coming in and then querying it like crazy, or things like log management, where you would store data at rest, and then look at it afterwards. But now with the paradigm of all the technology catching up, so whether that's the disk space that you get, and the storage and the processing, and things like Hadoop with the clustering, you now break that paradigm. Where you can collect all the information from a business and process it before you land the data, and then get the insight out of it, and then action. So that was my thing, of looking and saying, look, this whole thing's going to happen. In last year -- >> And at large scale, too. I mean, what you're talking about in the theoretical side makes a lot of sense, but also putting that into large scale, is even more challenging. >> Yeah, we had, when I was going through the processes, dating, you know, to see whether was a company that made sense, I chatted one of our investors. And they're also a customer. And I said, why did you choose Data Torrent? And they said, "We tested everything in production, we tested all the competitive products out there, and we broke everything except Data Torrent. And actually, we tested you in production up to a billion events per second, and you didn't break. And we believe that that quantity is something that you need as a stepping stone to move forward." >> And what use cases does that fit for? Just give me some anecdotal (snaps fingers) billion transactions. At that speed, what's some use cases that really take advantage of that? >> They were mastering in, what I would call, industrialization of IT. So in other words, once you get into things like turbines, wind generation, train parts. We're going to be very very soon, looking out of a window and seeing -- >> John: So is it flow data? Is it the speed of the flow? Is it the feed of all the calculations, or both? >> It's a bit of both. And what I'll do, is I'll give Phu a chance, otherwise, we'll end up chatting about it. >> John: Phu, come on, you're the star. (laughing) When you founded this company, you had a background at Yahoo, which you built from scratch, but that was a first-mover opportunity, Web 1.0, as they say. That evolved up and then, everyone used Yahoo Finance. Everyone used Yahoo Search as a directory early on. And then everything just got bigger and bigger and bigger, and then you had to build your own stuff with Hadoop. >> Yeah. >> So you lived it. The telcos don't have the same problem. They actually got backed into the data, from being in the voice business, and then the data business. The data came after the voice. So what's the motivation behind Data Torrent? Tell us a little bit more. >> It's exactly what you say, actually. Going through the 12 years at Yahoo, and really, we learned big data the hard way. Making mistakes month after month, about how to do this thing right. We didn't have the money, and then we found out that, actually, proprietary systems of the shelf system that we thought were available, really couldn't do their jobs. So we had to invent our own technology, to deal with the kind of data processing that we had. At some point, Yahoo had a billion users using Yahoo at any given point in time, right? And the amount of impressions, the amount of clicks, the amount of activity, that a billion users have, onto the system. And all of the log files that you have to process to understand what's going on. On the other side of that, we need to be able to understand all of those activities in order to sell to our advertisers. Slice and dice behaviors and users, and so on. We didn't have the technology to do that. The only thing we knew how to do was, to have these cheap racks of cheap servers, that we were using to serve webpages. And we turned to that to say, this is what we're going to need to do, to solve these big data problems. And so, the idea of, okay we need to take this big problem and divide it into smaller pieces, so that we can run on these cheap servers, sort of became the core tenant of how we do distributor processing that became Hadoop, at the end of the day, right? >> You had big data come in because you were, big data-full, as we say. You weren't building software to solve someone else's problem. You had your own problem, you had a lot of data. You were full with data. >> Exactly. >> Had to go on a data diet, to your point. (crosstalk) >> And no one to turn to. >> And no one to turn to. >> All right. So let's spin this around or Mobile World Congress. 'Cause the big theme is, obviously, we all know what device is. In fact, we just released here on theCube early this morning Peter Burris pre-announced our new research initiative called IOTP. Which stands for Internet Of Things And People. And so now you add the complexity of people devices, whether that's going to be some sort of watch, phones, anything around them. That adds to the industrial aspect of turbines and what not. Internet of Things is a new edge architecture. So the data tsunami coming, besides the challenges of telcos to provision these devices, are going to be very challenging. So the question I want to ask you guys is, how do you see this evolving, because you have certainly connectivity. Yeah, you know, low latency, small little data coming from the windmills or whatever. Versus big high-dense bandwidth, mobility. And then you got network core issues, right. So how does this going to look like? Where does the data piece fit in? Because all aspects of this have data. What's your thoughts on this, and architecture. Tell us about your impressions, and the conversations you've had. >> First of all, I think data will exist everywhere. On the fringe, in the middle, at the center. And there's going to be data analytics and processing in every path of that. The challenge will be to kind of figure out what part of processing do you put on the fringe, what part do you put at the center. And I think that's a fluid thing that is going to be constantly changing. Going back to the telcos. We've had numbers of conversationw with telcos. And, yes we're helping them right now with their current set of issues around capacity management and billing, all those things. But they are also looking to the next step in their business. They're making all this money from provisioning, but they know they sit on top of this massive amount of really valuable data, from their customers. Every cellphone is sending them all of this data. And so there's a huge opportunity for them to monetize, or really produce value, back to their customers. And that could come in form of offers, to customers. But now you're talking about massive analytics targeting. That is also real-time, because if you're sending an offer to someone at a particular location, if you do that slowly, or in batch, and you give them an offer 10 minutes later, they're no longer where they are. They're 10 minutes away, right? >> Well, first two questions to follow up on that. One, do they know they have a data advantage opportunity here? Do they know that data is potentially a competitive advantage? >> From our conversation, they absolutely do. They're just trying to figure out, so what do we do here? It's new to them. >> I want to get both your perspectives. Guy, I want you to weigh in on this one, 'cause this is another theme that's coming out of the reporting and analysis from Mobile World Congress. This has come also from the cloud side as well. Integration now, is more important than ever, because, for instance, they might have an Oracle there, there might be Oracle databases outside their network. That they might want to tap into. So tapping other people's data. Not just what they can get, the telcos. It's going to be important. So how do you guys see the integration aspect, how we, top of the first inning, national anthem going on. I mean, where are we in this integration? There's a pregame, or, what inning are we in on this? >> Yeah, we're definitely not on the home run on it. I think our friend, and your friend Steve Manly, I sat down with him, and I gave him a brief, you know, what we were doing, and he was blown away by the technology and the opportunity, but he was certainly saying, but the challenge is the diversity of the data types. And then where they're going to be. Autonomic cars. You know each manufacturer will tell the car behind it, what it just experienced, but the question is, when will a Tesla tell a Range Rover, or tell a BMW? So you have actually -- >> They're different platforms, just different stats, it's a nightmare. >> Right. So in other words, >> And trackability. And whether it's going to be open APIs, whether it's technologies like Kafka. But the integration of that, and making sure that you can do transformation and then normalize it and drive it forward. It's kind of interesting, you know. You mentioned the telco space, and do they understand it. In some respects, what Phu went through with Yahoo, in other words, you go to a webpage, you pull it up, it knows you because of a cookie and it figures out, and then sells advertising to you on that page. Now think about you as a location, and you're walking past a Starbucks, and they want to sell you a coffee for ten cents less than they would normally do. They need to know you're there then. And this is the thing, and this is why real-time is going to be so critical. And similarly, like you said, you look out the window and you see DHL, or UPS, or FedEx drones out the window. You not only have an insight issue. You also have a security issue, you have a compliance issue, you have a locational issue. >> I think you're onto something. And I think I actually had this talk today with Steve Manly EMC World last year, around time series data. So this is interesting. Everyone wants to store everything, but it actually might not be worth anything anymore. If the drone is delivering your package, or whatever realtime data is in realtime, it's really important right there in realtime, or near realtime. It might not be worth anything after. But yet a purchase at a store, at a time, might be worth knowing that as a record to pull in. You get what I'm saying? So there's a notion of data that's interesting. >> And I think, and again, Phu's the expert. I'm still running up onto it. It's just a pet hobby, an obsession of mine. But the market has this term ETL. In other words, Extract, Transform, Land. Or load. But in essence, it's always talked about in that (mumbles) batch. In other words, I get the data, transform it, drop it, and then I have a look at it. We're going upside-down. So the idea now is to actually extract, transform, insight, action, then landing. So in other words, get the value at the fresh data, before it's the data late. Because if you set the data late, by default, it's actually stale. And actually, then there's the fascination of saying, if you're delivering realtime data to a person, you can't think fast enough to actually make a live decision. So therefore, you've almost got any information that comes to you, has to tier out. So it comes to a process. You get that fresh use of it, and then it drops into a data lake. And so I think there's using both, but I think what will you see in the market, and, again, you've experienced the disk flash momentum that happened last year. You're going to see that from a data source from at-rest, advanced, to real-time data streams on our applications next year. So I think the issue is, the formative year, and back to your, you know, get it right, get the integration, but make sure your APIs are there, talking to the right technologies. I think everything's going to be exciting this year and new and fresh and people really want to do it. Next year is going to be the year where you're going to see an absolute changing of the guards. >> And then also the SLA requirements, they'll start to get into this when you start looking at integration. >> You're absolutely right. Actually, the SLA part is actually very very important here. Because, as you move analytics from this back world, where it has, you do it once a day, and if it dies, it's okay, you just do it again. To where it is now continuous, 24 by 7, giving you insight continuously about your business, your people, your services, and so on. Then all of a sudden, it has to have the same characteristics as your business. Which is, it's 24 by 7, it can never go down, it can never lose data. So, all of a sudden you're putting tremendous requirements on an analytics system, which has, all the way from the beginning of history 'til now, been a very relaxed batch thing, to all of a sudden being something that is enterprise-grade, 24 by 7. And I think that that's actually where it's going to be the toughest nut to crack. >> So tell about some of the things that you've learned. And pretend for a second, let's pretend that you, as a co-founder at Data Torrent, and Guy, and you are teamed up. You guys run this telco. Let's just make one up, Verizon. Or AT&T, or pick one. And you sit there saying, okay, you've got the keys to the kingdom. And you can do whatever you want (laughing). You can be Donald Trump, or you can be whoever you want. You can fire everybody, or you can pick it over and run it. What would you do? You know you've got IOT. So this is business model innovation opportunities. I want you to put the technical hat on, plus knowing what you know around the business model opportunities. What do you do? You know IOT's an opportunity. Amazon is going after that heavily. Do you bolt a cloud together? Do you go after Amazon? Do you co-op with Amazon? Do you co-integrate? Do you grab the IOT? Do you use the data? I mean, given where we are today, what's the best move if we were consulting with this. >> You know, I will be the last person to be talking about giving advice to a telco. But since we are, we own our own telco here, and then we're pretending, I would say the following. IOT is going to happen, right? Earlier, when I say a billion people, that's just human beings. Once you now talk about censoring, you can program how many times they can send you data per second, then the growth in volume is immense, right? I think there's a huge opportunity, as a telco, in terms of the data that they have available and the insight that they could have about what's going on. That is not easy. I don't think that, as a telco, in the current DNA of a telco, I can go ahead and do all that analytics and really open up my business to the data insight layer. I would partner, and find a way-- >> Well, we're consulting, we're going to sit around and say hey, what do we have? We have relationship with the consumer, big marketing budgets. We can talk to them directly, we have access to their device. >> But you'll bifurcate the business. We're in the boardroom here, this is nothing more than that. But I would look at it and say look, you've got a consumer business, the same as in IOT. There's really, for me, there's three parts of IOT. There is the bit that I love which, you can geek out, which is basically the consumer market, which, there's no money in for a large-scale tenant, right, enterprise. And then you have the industrialization of IOT, which is I've got a leaky pipe, and I want a hardened device, ruggedized, which is wifi, so, now as a telco, I could create a IOT cloud, that allows me to put these devices out there, and in fact, I use Arlo, the little cameras. And they've got one now, where I can basically float it with its own cellular signal. So it's its own cellphone. That's a great use of IOT for that. And then you step to the consumer side of, I've got a cellphone, and then what I'll do is literally, in essence, riff off what Yahoo did in the early days and say, I'm now the new browser. The person's the browser. So in other words, follow the location, follow where he is, and then basically do locational-based advertising. >> By the way, you have to license the patent from our earlier guest, he'll say will he leak, 'cause he's got th6e patent on personal firewall for personal server. He's built a mobile personal server. >> Yeah. >> But this is the opportunity around wireless. Why I love the confusion, but the opportunity around wireless right now is, you can get bandwidth at high capacity. You have millimeter wave four, that doesn't go through walls, but you have other diverse frequencies and spectrum for instance, you can blend it all together to have that little drip signal, if you will, going into the cloud from the leaky pipe. Or if you need turbine, full-fat pipe, you maybe go somewhere. So, I think this is an interesting opportunity. >> And they're going to end up watching the data centers as well. There's still the gamut of saying our customer is going to continue to support their own data centers, or are there going to be one to a hundred data centers out there? And then how does selling a manufacturer or a telco play into that, and do they want to be that guy or not? >> Guy, Phu, thanks for coming in. I want to give you guys a chance to put a plug in for Data Torrent. Thanks for sharing some great commentary on the industry. So, what's up with you guys? Give us the update. Are you hiring? You growing? What are you guys doing? Customers? What's the update? Technology, innovations? >> So we've got a release coming out tomorrow which is a momentum release. I can't talk too much about the numbers, but in essence, from a fact base, we have a thing called a patchy apex. So it's open sourced, so you can use our product for free. But that's growing like gangbusters. From a top-level project, that's actually the fastest-growing one, and it's only been out for seven months. We just broke through 50,000 users on it. From our product, we're doing very well on the back of it. So we actually have subscription for the production side. >> So revenue is a subscription model. >> Yeah, and we meet both sides. So in other words, for the engineer who writes it, you've got the open source. And then when you put it into production, from the operations side, you can then license our products to enable you to manage an easy-- >> So when it gets commercialized, you pay as you go, when you use it. >> And you don't have to, if you don't want to. You've got all the tools to do it. But, we focus for our products group of, time to value, total cost of ownership. We're trying to bring Hadoop and real scale, realtime streaming to the masses. So what's the technology innovation? What's the disruptive enabler for you guys? >> I think we talked about it, right? You've got two really competing trends going on here. On one side, data is getting more and more and more massive. So it's going to take longer and longer to process it. Yet at the other side, business wants to be able to get data, have insight, and take action sub-second. So how do you get both at the same time? That's really the magic of the technology. >> Thanks for coming in. Great to meet you, Phu. I'd love to talk about the old Yahoo days, a total throwback, Web 1.0, a great time in history, pre-bubble bursting. Greatness happening in the valley and all around the world, and I remember those days clearly. Guy, great to see you. Congratulations on your new CEO committee. And great to have you on theCube. This is theCube bringing the coverage, and commentary, and reaction of Mobile World Congress here, in California. As everyone goes to bed in Barcelona, we're just gettin' down to the end of our day here in the afternoon in California. Be right back with more after this short break. (techno music)

>> Narrator: Live from Silicon Valley, it's theCUBE. Covering mobile world congress 2017. Brought to you by Intel. >> Okay, welcome back everyone, we're here live in Palo Alto for day two of two days of Mobile World Congress special coverage here in Palo Alto, where we're bringing all the folks in Silicon Valley here in the studio to analyze all the news and commentary of which we've been watching heavily on the ground in Barcelona. We have reporters, we have analysts, and we have friends there, of course, Intel is there as well as SAP, and a variety of other companies we've been talking to on the phone and all those interviews are on YouTube.com/siliconANGLE. And we're here with Chuck Tato, who's the marketing director of the data center of communications with Intel around the FPGA, which is the programmable chips, formerly with the Alterra Group, now a part of Intel, welcome to theCUBE, and thanks for coming on. >> Thank you for having me. So, actually all the rage Mobile World Congress Intel, big splash, and you guys have been, I mean, Intel has always bene the bellweather. I was saying this earlier, Intel plays the long game. You have to in the chips games. You got to build the factories, build fabs. Most of all, have been the heartbeat of the industry, but now doing more of less chips, Most of all, making them smaller, faster, cheaper, or less expensive and just more power. The cloud does that. So you're in the cloud data center group. Take a second to talk about what you guys do within Intel, and why that's important for folks to understand. >> Sure. I'm part of the programmable solutions group. So the programmable solutions group primarily focuses on field programmable gate array technology that was acquired through the Alterra acquisition at Intel. So our focus in my particular group is around data center and Coms infrastructure. So there, what we're doing is we're taking the FPGAs and we're applying them to the data center as well as carrier infrastructure to accelerate things, make them faster, make them more repeatable, or more terministic in nature. >> And so, that how it works, as you were explaining beforehand, kind of, you can set stream of bits at it and it changes the functionality of the chip. >> Yes. So essentially, an FPGA, think of it as a malleable set of resources. When I say that, you know, you can create, it's basically a fabric with many resources in an array. So through the use of a bit stream, you can actually program that fabric to interconnect the different elements of the chip to create any function that you would like, for the most part. So think of it as you can create a switch, you can create a classification engine, and things like that. >> Any why would someone want that functionality versus just a purpose-built chip. >> Perfect question. So if you look at, there's two areas. So in the data center, as well as in carrier infrastructure, the workloads are changing constantly. And there's two problems. Number one you could create infrastructure that becomes stranded. You know, you think you're going to have so much traffic of a certain type and you don't. So you end up buying a lot of purpose-built equipment that's just wrong for what you need going forward. So by building infrastructure that is common, so it kind of COTS, you know, on servers, but adding FPGAs to the mix allows you to reconfigure the networking within the cloud, to allow you to address workloads that you care about at any given time. >> Adaptability seems to be the key thing. You know kind of trends based upon certain things, and certainly the first time you see things, you've got to figure it out. But this gives a lot of flexibility, it sounds like. >> Exactly. Adaptability is the key, as well as bandwidth, and determinism, right? So when you get a high bandwidth coming into the network, and you want to something very rapidly and consistently to provide a certain service level agreement you need to have circuits that are actually very, very deterministic in nature. >> Chuck, I want to get your thoughts on one of the key things. I talked with Sandra Reddy, Sandra Rivera, sorry, she was, I interviewed her this morning, as well as Dan Rodriguez, and Caroline Chan, Lyn Comp as well. Lot of different perspectives. I see 5G as big on one hand, have the devices out there announcing on Sunday. But what was missing, and I think Fortune was the really, the only one I saw pick up on this besides SiliconANGLE, on terms of the coverage was, there's a real end-to-end discussion here around not just the 5G as the connectivity piece that the carriers care about, but there's the under-the-hood work that's changing in the Data Center. And the car's a data center now, right? >> Yeah. >> So you have all these new things happening, IOT, people with sensors on them, and devices, and then you've got the cloud-ready compute available, right? And we love what's happening with cloud. Infinite compute is there and makes data work much better. How does the end-to-end story with Intel, and the group that you're in, impact that and what are some of the use cases that seem to be popping up in that area. >> Okay, so that's a great question, and I guess some of the examples that I could give of where we're creating end-to-end solutions would be in wireless infrastructure, as you just mentioned. As you move on to 5G infrastructure, the goal is to increase the bandwidth by 100X and reduce the latency by orders of magnitude. It's a very, very significant challenge. To do that is quite difficult, to do it just in software. FPGA is a perfect complement to a software-based solution to achieve these goals. For example, virtual switching. It's a significant load on the processors. By offloading virtual switching in an FPGA, you an create the virtual switch that you need for the particular workload that you need. Workloads change, depending on what type of services you're offering in a given area. So you can tailor it to exactly what you need. You may or may not need6 high levels of security, so things like IPsec, yo6u know, at full line rate, are the kind of things that FPGAs allow you to add ad hoc. You can add them where you need them, when you need them, and change them as the services change. >> It sounds like, I'd never thought about that, but it sounds like this is a real architectural advantage, because I'd never thought about offloading the processor, and we all know we all open up or build our PCs know that the heat syncs only get bigger and bigger, so that people want that horsepower for very processor-intensive things. >> Absolutely. So we do two things. One is we do create this flexible infrastructure, the second thing is we offload the processor for things that you know, free up cores to do more value-added things. >> Like gaming for, my kids love to see that gaming. >> Yes. There's gaming, virtual reality, augmented virtual reality, all of those things are very CPU intensive, but there's also a compute-intensive aspect. >> Okay, so I've got to get your take on this. This is kind of a cool conversation because that's, the virtual reality and augmented reality really are relevant. That is a key part of Mobile World Congress, beside the IOT, which I think is the biggest story this year, is IOT, and all the security aspects of it around, and all that good stuff. And that's really where the meat is, but the real sex appeal is the virtual reality and augmented reality. That's an example of the new things that have popped out of the woodwork, so the question for you is for all these new-use cases that I have found that emerge, there will be new things that pop out of the woodwork. "Oh, my God, I don't have to write software for that, There's an app for that now." So the new apps are going to start coming in, whether it's something new and cool on a car, Something new and cool on a sensor, something new and cool in the data center. How adaptive are you guys and how do you guys kind of fit into that kind of preparing for this unknown future. >> Well, that's a great question, too. I like to think about new services coming forward as being a unique blend of storage, compute, and networking, and depending on the application and the moment in that application, you may have to change that mix in a very flexible way. So again, the FPGA provides you the ability to change all of those to match the application needs. I'm surprised as we dig into applications, you know, how many different sets of needs there are. So each time you do that, you can envision, reprogramming your FPGA. So just like a processor, it's completely reprogrammable. You're not going to reprogram it in the same instantaneous way that you do in software, but you can reprogram it on the fly, whatever you would like. >> So, I'm kind of a neophyte here, so I want to ask some dumb questions, probably be dumb to you, but common to me, but would be like, okay, who writes bits? Is it the coders or is it someone on the firmware side, I'm trying to understand where the line is between that hardened top of kind of Intel goodness that goes on algorithmically or automatically, or what programmers do. So think full-stack developer, or a composer, a more artisan type who's maybe writing an app. Are there both access points to the coding, or is it, where's the coding come from? >> So there's multiple ways that this is happening. The traditional way of programming FPGA is the same way that you would design any ASIC in the industry, right? Somebody sits down and they write RTL, they're very specialized programmers However, going forward, there's multiple ways you an access it. For one, we're creating libraries of solutions that you can access through APIs that are built into DPDK, for example on Xeon. So you can very easily access accelerated applications and inline applications that are being developed by ourselves as well as third parties. So there's a rich eco system. >> So you guys are writing hooks that go beyond being the ASIC special type, specialist programming. >> Absolutely. So this makes it very accessible to programmers. The acceleration that's there from a library and purpose-built. >> Give me an example, if you can. >> Sure, virtual switch. So in our platform for NFE, we're building in a virtual switch solution, and you can program that just like you know, totally in software through DPDK. >> One of the things that coming up with NFE that's interesting, I don't know if this y6our wheelhouse or not, but I want to throw it out there because it's come up in multiple interviews and in the industry. You're seeing very cool ideas and solutions roll out, and I'll give, you know, I'll make one up off the top of my head, Openstack. Openstack is a great, great vision, but it's a lot of fumbling in the execution of it and the cost of ownership goes through the roof because there's a lot of operation, I'm overgeneralizing certain use-case, not all Openstack, but in generally speaking, I do have the same problem with big data where, great solution-- >> Uh-huh. >> But when you lay out the architect and then deploy it there's a lot of cost of ownership overhead in terms of resources. So is this kind of an area that you guys can help simplify, 'cause that seems to be a sticking point for people who want to stand up some infrastructure and do dev ops and then get into this API-like framework. >> Yes, from a hardware perspective, we're actually creating a platform, which includes a lot of software to tie into Openstack. So that's all preintegrated for you, if you will. So at least from a hardware interface perspective, I can say that that part of the equation gets neutralized. In terms of the rest of the ownership part, I'm not really qualified to answer that question. >> That's good media training, right there. Chuck just came back from Intel media training, which is good. We got you fresh. Network transformation, and at the, also points to some really cool exciting areas that are going on that are really important. The network layer you see, EDFE, and SDN, for instance, that's really important areas that people are innovating on, and they're super important because, again, this is where the action is. You have virtualization, you have new capabilities, you've got some security things going down lower in the stack. What's the impact there from an Intel perspective, helping this end-to-end architecture be seamless? >> Sure. So what we are doing right now is creating a layer on top of our FPGA-based SmartNIC solutions, which ties together all of that into a single platform, and it cuts across multiple Intel products. We have, you know, Xeon processors integrated with FPGAs, we have discreet FPGAs built onto cards that we are in the process of developing. So from a SmartNIC through to a fully-integrated FPGA plus Xeon processor is one common framework. One common way of programming the FPGA, so IP can move from one to the other. So there's a lot of very neat end-to-end and seamless capabilities. >> So the final question is the customer environment. I would say you guys have a lot of customers out there. The edge computing is a huge thing right now. We're seeing that as a big part of this, kind of, the clarity coming out of Mobile World Congress, at least from the telco standpoints, it's kind of not new in the data center area. The edge now is redefined. Certainly with IOT-- >> Yes. >> And IOTP, which we're calling IOTP app for people having devices. What are the customer challenges right now, that you are addressing. Specifically, what's the pain points and what's the current state-of-the-art relative to the customer's expectations now, that they're focused on that you guys are solving. >> Yeah, that's a great question, too. We have a lot of customers now that are taking transmission equipment, for example, mobile backhaul types of equipment, and they want to add mobile edge computing and NFE-type capabilities to that equipment. The beauty of what we're doing is that the same solution that we have for the cloud works just as well in that same piece of equipment. FPGAs come in all different sizes, so you can fit within your power envelope or processors come in all different sizes. So you can tailor your solution-- >> That's super important on the telco side. I mean, power is huge. >> Yes, yes, and FPGAs allow you to tailor the power equation as much as possible. >> So the question, I think is the next question is, does this make it cloud-ready, because that's term that we've been hearing a lot of. Cloud-ready. Cause that sounds like what you're offering is the ability to kind of tie into the same stuff that the cloud has, or the data center. >> Yes, exactly. In fact, you know, there's been very high profile press around the use of FPGAs in cloud infrastructure. So we're seeing a huge uptick there. So it is getting cloud-ready. I wouldn't say it's perfectly there, but we're getting very close. >> Well the thing that's exciting to me, I think, is the cloud native movement really talks about again, you know, these abstractions with micro services, and you mentioned the APIs, really fits well into some of the agilenesss that needs to happen at the network layer, to be more dynamic. I mean, just think about the provisioning of IOT. >> Chuck: Yeah. >> I mean, I'm a telco, I got to provision a phone, that's get a phone number, connect on the network, and then have sessions go to the base station, and then back to the cloud. Imagine having to provision up and down zillions of times those devices that may get provision once and go away in an hour. >> Right. >> That's still challenging, give you the network fabric. >> Yes. It is going to be a challenge, but I think as common as we can make the physical infrastructure, the better and the easier that's going to be, and as we create more common-- >> Chuck, final question, what's your take from Mobile World Congress? What are you hearing, what's your analysis, commentary, any kind of input you've heard? Obviously, Intel's got a big presence there, your thoughts on what's happening at Mobile World Congress. >> Well, see I'm not at Mobile World Congress, I'm here in Silicon Valley right now, but-- >> John: What have you heard? >> Things are very exciting. I'm mostly focused on the NFE world myself, and there's been just lots and lots of-- >> It's been high profile. >> Yes, and there's been lots of activity, and you know, we've been doing demos and really cool stuff in that area. We haven't announced much of that on the FPGA side, but I think you'll be seeing more-- >> But you're involved, so what's the coolest thing in NFE that you're seeing, because it seems to be crunch time for NFE right now. This is a catalyst point where at least, from my covering NFE, and looking at it, the iterations of it, it's primetime right now for NFE, true? >> Yeah, it's perfect timing, and it's actually perfect timing for FPGA. I'm not trying to just give it a plug. When you look at it, trials have gone on, very significant, lots of learnings from those trials. What we've done is we've identified the bottlenecks, and my group has been working very hard to resolve those bottlenecks, so we can scale and roll out in the next couple of years, and be ready for 5G when it comes. >> Software definer, Chuck Tato, here from Intel, inside theCUBE, breaking down the coverage from Mobile World Congress, as we wind down our day in California, the folks in Spain are just going out. It should be like at 12:00 o'clock at night there, and are going to bed, depending on how beat they are. Again, it's in Barcelona, Spain, it's where it's at. We're covering from here and also talking to folks in Barcelona. We'll have more commentary here in Silicon Valley on the Mobile World Congress after this short break. (techno music)