>> live from Boston, Massachusetts. It's the Cube covering A W s reinforce 2019. Brought to you by Amazon Web service is and its ecosystem partners. >> Hey, welcome back and run cubes. Live coverage of A W S Amazon Webster's reinforced their inaugural conference around security here in Boston. Messages. I'm John for a day. Volante Day we've been talking about Blockchain has been part of security, but no mention of it here. Amazon announced a Blockchain intention, but was more of a service model. Less of a pure play infrastructure or kind of a new game changes. So we thought we would get our friends to come on, the Cuban tell. Tell us about it. Val Birch, Avicii CEO and founder. A pencil day that Cube alumni formerly of NetApp, among other great companies, and Ed You, founder and CEO of Strong Salt. Welcome to the Q. Tell us why aren't we taught him a Blockchain at a security conference on cloud computing, where they always resource is different. Paradigm is decentralized. What's your take? >> So maybe having been in this world for about 18 24 months now, Enterprise lodging reinvents about six months ago and jazz he mentioned that he finally understood US enterprise an opportunity, and it was the integrity value, finest complex, even announced a specific product announced database available, >> maybe bythe on cryptographic verifiability of transactions minus the complexity of smart contract wallets. Wait, you party with Amazon way too. Versions right? One for distributed use cases. When I call, everyone rises. Never like you need to know what >> the Amazon wants to be that hard on top like complexity. But the reality is, they're they're They're world is targeting a new generation star 14 show is the new generation of developing >> a >> new generation of David. They were. Some of those are in trouble, and I'm hard core on this because it's just so obvious. >> I just can't get him behind myself if you don't >> see this out quicker. The new developers are younger and older systems people. There's a range of ages doing it. They're they're seeing the agility, and it's a cultural shift, not just the age thing. Head this. They're not here right now. This is the missing picture of this show, and my criticism of reinforces big, gaping hole around crypto and blocks, >> and I actually know that people I don't see anything here because it is difficult to currency. >> Blocking is very important that people understand way. Launch strong allows you to see the launching. I don't think that works. Basically, Just like Well, well said everything you do, you always have a single source. I think that's something that people doing this thing here. You want to get your thoughts on this because you made a comment >> about security native being the team here and security native implying that Dev ops what they did for configuration hardening the infrastructures code. You have to consider this token economic business model side of it with the apple cases, a decision application is still an application. Okay. Blockchain is still in infrastructure dynamic their software involved. I mean, we're talking about the same thing is they're lost in translation. In your opinion? >> Well, yeah, I think that you know, to your point, Val, if you can abstract that complexity away, But the fundamentals of of cryptography and software engineering and game theory coming together is what always has fascinated me about this space. And so you're right. I think certainly enterprise customers don't wanna you know, they hear crypto, though no, although it's interesting it was just a conference IBM yesterday. They talk a lot about Blockchain. Don't talk about crypto to me. They go together. Of course, IBM. They don't like to talk a lot about job loss and automation, but But the reality is it's there and it's it's it's has a lot of momentum, which is why you started the company. >> Yeah, we're actually seeing it all over right now. And again, our thing is around reducing, If not eliminating the friction towards adopting Blockchain so less is more. In our case, we're explicitly choosing not to do crypto wallets or currency transactions. It's that Andy Jassy observation the integrity value, the core integrity, value for financial reconciliation, for detecting supply chain counterfeiting for tracking assets and inventory across to your distribution. Unifying multiple source systems of record into a shared state. Those are the kinds of applications received >> culture, and there's so many different use cases, obviously, so >> an Amazon likes to use that word. Words raised the bar, which is more functionality, but on the other, phrases undifferentiated, heavy lifting. There's a lot of details involved in some of those complexity exactly what you're talking about that can be automated away. That's goodness. But you still have a security problem of mutability, which is a beautiful thing with Blockchain. >> Actually, a lot of times people actually forgot to mention one thing that blotchy and all you do that's actually different before was Actually privacy is actually not just security is also privacy, which actually is getting bigger and bigger. As we know, it's something that people feel very strongly about because it's something they feel personal about. And that's something that, in fact, took economics encourages a lot of things that enables privacy that was not able to do before. >> Well, look at Facebook. What do you think about >> face? I'm wonder that you know, I'm a public face book critic. I think they've been atrocious job on the privacy front so far in protecting our data. On the other hand, if you know it's kind of like the mullahs report, if you actually read Facebook's white paper, it's a it's not a launch. It's an announcement. That's a technical announcement. It's so well written, designed so far, and it's Facebook doesn't completely control it. They do have a vision for program ability. They're evolving it from being a permissions toe, ultimately a permission less system. So on paper, I like what I read. And I think it will start to, you know, popularizing democratize the notion of crypto amongst the broader population. I'm going to take a much more weight see approach. Just you know, >> I always love Facebook. I think the den atrocious job. But I'm addicted. I have all my stuff on there, um, centralized. They're bringing up, they bring in an education. Bitcoin is up for a reason. They're bringing the masses. They're showing that this is real market. This is kind of like when the web was still viewed as Kitty Playground for technologists say, Oh, well, it's so slow. And that was for dummies. And you had the Web World Wide Web. So when that hit, that same arguments went down right this minute, crypto things for years. But with Facebook coming, it really legitimizes that well, you bring 2,000,000,000 people to the party. Exactly a lot of good. Now the critics of Facebook is copied pass craft kind of model and there's no way they're gonna get it through because the world's not gonna let Facebook running run commerce and currents. It's like it's like and they don't do it well anyway. So I think it's gonna be a game changing market making move. I think they'll have a play in there, but I don't think that's not gonna have a global force. Says a >> lot that you get 100 companies to put up 10 >> 1,000,000 Starship is already the first accomplice. >> They don't need any more money. We have my dear to us, but >> still the power but the power of that ecosystem to me. I was a big fan of this because I think it gives credibility. So many companies get get interested in it, and I'm not sure exactly what's gonna come out of it. It's interesting that, you know, Bitcoins up. They said, Oh, cell, you're becoming like No, no, no, this is This is a very mature >> Well, I I think open is gonna always win. If you look at you know, the Web's kind of one example of kind of maturity argument. I think the rial analog for me, at least my generation value probably relate to this. David, you as well, you know, I've been born yet you are But, you know, T c p I p came after S n a which IBM on the deck net was the largest network at that time to >> not serious. Says >> mammal. Novell was land all three proprietary network operating systems. So proprietary Narcisse decimated by T c p i p. So to me, I think even their Facebook does go in there. They will recognize that unless they stay open, I think open will always win. I think I think this is the beginning of the death of the closed platform. >> Yeah, they're forced her. I think they have to open it up because if you didn't open up, people won't trust them, and people will use them. And if a Blockchain if you don't have a community behind it, there will be nothing. >> Well, so the thing about the crypto spraying everywhere with crypto winter, But but to your point d c p i p h t t p d >> N s SMTP >> Those were government funded or academic funded protocols. People stop spending money on him, and then the big Internet companies just co opted. No, no, that's what G mails built on. >> Well, I've always said >> so But when you finish the thought, is all this crypto money that came in drove innovation? Yeah, So you're seeing, you know, this new Internet emerge, and I think it's it's really think people, you know, sort of overlooked a lot of the innovation that's >> coming. I have always said, Dave, that Facebook is what the Web would look like if Tim Berners Lee took venture financing. Okay, because what they had at the time was a browser and the way that stand up websites for self service information. They kept it open and it drives. Facebook became basically the Web's version of a, well, lengthen does the same Twitter has opened. They have no developer community. So yeah, I think it is the only company in my opinion, actually does a good job opening up their data. Now they charge you for that. It brings up way still haven't encrypt those. The only community that's entire ethos is based on openness and community you mentioned. And that is a key word >> in traditional media. Of course, focus on the bad stuff that happens, but you know those of us in the business who will pay attention to it, see There's a lot of goodness to is a lot of mission driven, a lot of openness, and it's a model for innovation. What do you guys think about the narrative now to break up big tech? You know you're hearing Facebook, Amazon, Google coming under fire. What are your thoughts on that? >> So I wrote a block, maybe was ahead of its time about 18 months ago. Is coincided with Ginny Rometty, a Davos and 2018 2019 talking about data responsibility. Reason we're having this conversation is at the tech industry. By and large and especially the fang stocks or whatever we're calling them now have been irresponsible with our data. The backlash is palpable in Europe. It's law in Europe. Backlash we knew was going to start at the state level here. There's already ahead of my personal schedule. Federal discussions, FTC DOJ is in a couple weeks ago, so it's inevitable that this sort of tech reckoning is coming in. Maur responsibility is gonna have to be demonstrated by all the custodians of our data, and that's why we're positioning. Check it as a chain of custody is a service to demonstrate to the regulators your customers, your partners, suppliers, you know, transparency, irrefutable transparency, using Blockchain for how you're handling data. You know, if you don't have that, transparency can prove it. Or back to the same old discussions were back Thio Uninformed old legislators making you know Internet, his tubes type regulations. So here, here >> and DOJ, you could argue that they may be too slow to respond to Microsoft back in the nineties. I'm not sure breaking up big tech is the right thing, because I think it's almost like a t. The little Tex will become big checks again, but they should not be breaking the law. >> I think there's a reason why is there's actually a limitation off. What is possible in technology because they understand and also Facebook understands well, is that it's actually very, very hard to have data that's owned by your customers. But you are the one who's keeping track over everything, and you are the one using the data right. It's like a no win, because if you think about encryption cryptography, yes, you can make the data encrypted. That way, the customer has the key. They control it, but then Facebook can offer the service is. So now you have a Congress thinking, Well, if there's no technological way of doing this, what can you do in a legal perspective on a, you know, on the law perspective, toddy make it so that the customer actually owned the data. We actually think that is a perfect reason why you have to actually fix the book. Actually, technical should be built on our platform because we actually allow them to have a day that's encrypted and stupid able to operations holiday tha if the customer give them the permission to do so. And I think that's the perfect word way to go forward. And I think Blockchain is the fundamental thing that brings everybody together, you know, way that actually benefits everyone knows >> and take him into explain strong salt your project. What's it about? What's the mission? Where you >> so so we see strong saw as actually privacy. First, we literally are beauty, a platform where developers including Facebook linked and salesforce can't you build on top of platform, right? So what happens when you do this is that they actually give the data governess to the customers, customers Mashona data. But because our cryptography they actually can offer service is to the customers. When a customer allowed them to do so, for example, we have something. All search of encryption allows you to encrypt the data and still give the search. Aubrey on the data without decrypting the data. First, by giving the power to developers and also the community there, you can have our abstract you currently use. But they're not hard to use that frictionless and still offer the same service that Frank Facebook or sell stolen offer the favor. >> You could do some discovery on it. >> You can't do things >> some program ability around >> exactly, even though the data is encrypted. But custom owns the day. So the customer has to give them permission to do so Right this way. Actually, in fact, launched the first app that I told you it's called strong vote. You can Donald ios or Andrew it And you can't you see the Blockchain play little You can see the rocking your fingerprint. I think a fingertip to see what happens to a data. You see everything that happens when Sheriff I or you open a fire or something, I guess. >> Congratulations, Val. Give a quick plug for your project chain kid into the new branding. They're like it. Pencil data. Where are you on your project? >> So after nine months of hard selling, we're finding out what customers actually paying for right now. In our case, it's hardening their APS, their data and their logs and wrapping the chain of custody around those things. And the use case of the security conference like this is actually quite existential When you think about it, One of the things that the industry doesn't talk enough about is that every attack we read about in the headlines was three privilege escalation. So the attackers somehow hacked. Your Web server managed to get administrative credentials and network or domain administrative credentials. And here's what professional attackers do once they have godlike authority on your network. They identify all the installed security solutions, and they make themselves invisible because they can. After that, they operate with impunity. Our technology, the security use case that we're seeing a lot of traction is, is we can detect that we're applying Blockchain. We're agnostic, so bring your own Blockchain in our case. But we're able >> chain kit a product. Is it a development environment >> globally. Available service Jose on AWS rest ful AP eyes and fundamentally were enabling developers to harden their app stuff to wrap a chain of custody around key data or logs in their laps so that when the attacker's attempt a leverage at administrative authority and tamper with locks tamper >> with service, not a software, >> it's a apply. It's a developer oriented service, but >> this is one of the biggest problems and challenges security today. You see the stat after you get infiltrated. It takes 250 or 300 days to even detect, and I have not heard that number shrink. I've heard people aspire number streaking this. >> We can get it down to realize a crime tip of the spear. That's what we're excited to be here. We're excited to talk about One of the dirty secrets of the security industry is that it shouldn't take a year to detect in advance attack. >> Guys, Thanks for coming on. Cuban sharing your insight. Concussions in your head. Well, great to see you. >> Likewise. And thank you, j for having us on here, and we're looking forward to coming back and weigh. Appreciate. Absolutely >> thankful. Spj Thanks for you. >> It was always paying it forward. Of course, really the most important conversation, that security is gonna be a Blockchain type of implementation. This is a reality that's coming very soon, but we're here. They do is reinforce. I'm talking about the first conference with Amazon Web sources dedicated to sightsee. So's Cee Io's around security jumper. Develop the stables for more coverage. After this short break, >> my name is David.

(light adventurous music) >> Hello everyone, welcome to theCUBE Studios here in Palo Alto. I'm John Furrier, the co-host of theCUBE, co-founder of SiliconANGLE Media. This is our CUBE Conversation Thought Leader Thursday and I'm here with Val Bercovici, who's the founder and CEO of a new startup called PencilDATA. Val, CUBE alumni, been on many times with NetApp and then a variety of other great startups, but now you're doing your own thing around cryptocurrency, blockchain, enterprise-like technical infrastructure. You've been a CTO, now entrepreneur, founder and CEO of PencilDATA. Congratulations, you're on the crypto wave, this wave is coming. >> I believe it's here. >> It's here. >> Timing couldn't be better. >> So, I interviewed Dr. Jian Wang who's the chairman of Alibaba's technology steering committee, also the founder of Alibaba Cloud, just recently in China. Presented by Intel, plug for Intel there, thanks Intel for supporting theCUBE. He said to me, and I put the clip out on Twitter, natively on the video clip, which was, I asked him about blockchain, you know China, they blocked the ICOs, he said, "Blockchain is fundamental, part of the Internet. "It's as fundamental as TCP/IP was." This is the nuance that is attracting a lot of tier one entrepreneurs. Obviously the money side is hyped up beyond all recognition right now. As Don Klein on our team was saying, "It's melting up in terms of hype." But this really speaks to the transformation of the web, and the Internet now, the web is the Internet, from distributed and decentralized. This is a big sea change. Kind of building on the fundamentals of the internet, formerly called the information superhighway, before the web came along, but the web was designed to withstand nuclear disaster, be resilient, be decentralized. >> It reminds me of Back to the Future in many, many ways, because if you're as old as we are, you remember those DARPA origins of the Internet and exactly that decentralized nature, and we've gone away from that, right? As Tim Berners-Lee brought on the HTTP protocol, we've had web protocols, and as major, the FANG vendors have really dominated their usage of that existing layer of technology we've gone away, we've gone to a very, very centralized approach, which as we're seeing with the tech hearings this week, carries all sorts of risks, it's not just business and legal and political. >> And you're referring to the senate hearings, where Facebook, Google, or Alphabet, and Twitter were in front of the senate committee, you're going to tell them about the Russians, the Russian political thing, but they're bringing up the issue of the role of these mega platforms that have all this data and the problem is that this is not what the users bargained for. I mean, I use Facebook as a free app, I love Facebook, Facebook, we love you, WhatsApp here and there, and Instagram, but you know, my bargain was simple. I'll use your free app and I'll let you use some of my data but now you're making billions, $10 billion quarter, fake news has infiltrated the country, I have a poor user experience every day, it's getting worse and worse, a lot of hate and division. This is not what I bargained for. >> Val: Exactly. >> So the world's kind of revolting against these mega-siloed platforms. >> That's the risk of having such centralized control of the technology. If you remember in the old days when Microsoft's dominance was rising, all you had to do was target Windows as a virus platform and you're able to impact thousands of businesses, even in the early Internet days, within hours. And it's the same thing happening right now, there's a weaponization of these social media platforms and Google's search engine technology and so forth. It's the same side effect now, the centralization of that control is the problem. One of the reasons I love the blockstack technology, and blockchain in general is the ability to decentralize these things right now, and the most passionate thing I care about nowadays is being driven out of Europe, where they have a lot more maturity in terms of handling these new scenarios. >> You mean the tech being driven out of Europe. >> The laws. >> The laws, okay. >> Being driven out of Europe. >> Be specific, we'd like an example. >> The major deadline that's coming up in May 25th of 2018 is GDPR, General Data Protection Regulation, where European citizens now in any company, American or otherwise, catering to European citizens, has to respond to things like the right to be forgotten request. You've got 24 hours, as a global corporation with European operations, to respond to European citizens', EU citizens', right to be forgotten request, where all the personally identifiable information, the PII, has to be removed and an audit trail, proving it's been removed, has to be gone from two, three hundred internal systems within 24 hours. And this has teeth by the way, it's not like the $2.7 billion fine that Google just flipped away casually, this has up to 4% of your global profits per incident where you don't meet that requirement. >> Well you bring up a good point, the GDPR is a good one, it has teeth and it's kind of in the weeds with the folks who might not know that regulation, but really it's about the privacy and the rights of the individual. But coming back to Facebook, to connect another dot is, what we're seeing with Facebook, Twitter, and Alphabet with the senate hearings is, and this is why the industry and the media is crumbling, publications are dying, the newspapers, the media's changing, is because knowing your customer is a really important thing. The people who want to be served need to have a closed loop with the publication, and these platforms are bogarting all the data, and so the right of the customer, the users are suffering, and that's what people are generally talking about. You know, personally, a guy can rent a truck and go mow people down in Manhattan, we should know who these people are, like the neighbors, so I think there's going to be a trend towards knowing who your neighbor is, knowing who the customers are, at a level that's not scary privacy violation, but we're going to know who the crazies are, we're going to know what's going on and then that's kind of out there, that's kind of my general feeling. But now, getting back to the impact. GDPR, these big mega platforms where the users are at the center of the value proposition, really comes down to the shift in user expectations around a decentralized Internet. That means agile goes to a whole other level. If I'm a user and I say, "Hey Facebook, "delete my digital exhaust or digital footprints "from Facebook over the past 10 years." I mean, that's hard to do. >> That's hard for them. >> That's not, technically is a really serious problem. >> And it's actually not just a technology challenge, I always love to go back to Conway's Law in these discussions, the org chart, you know, how information, infrastructure is budgeted for, and managed through various different departments within any large enterprise, data-savvy or not, is a challenge, as is coordinating these efforts, actually going beyond the talking phase, towards implementing a master data model. Those are the main challenges right now, and it's a movement that I believe now has political strength to actually migrate across the pond. Over here as well there's a groundswell movement called Digital Sovereignty as a response to GDPR in Europe, where people are realizing that they have the right to be sovereign over their data, their digital exhaust, their digital footprints online and that's a two-way street. You want and demand control over your data, but on the other hand your identity, which you control, has to be authentic as opposed to a fake identity, and your reputation has to be out there as well. >> These signals and these trends you were just referring to, to me are just like little tremors of the tectonic plates that are going to be changing, because if you look at the major shift in technology, let's take blockchain for instance, and look at the impact of a decentralized internet, now global, immutability with the ability now for more agile capability and not just permanent, "I want to erase things" that you're talking about, but three, the younger generation, if we look at what the young kids are doing, I have four kids, my oldest is 22, it's a gaming culture, right? It's a gaming culture, they're online all the time. They're not old like us, my son's like, "Dad, Google Search is for old people." I mean, that's a general sentiment, over-categorizing, but a combination of the new user experience, this younger generation, entrepreneurs and users, and these tremors we're seeing in the marketplace, signaling that, "hey Facebook, you might be too big for your britches," or, "hey Twitter, you got a bot problem, "hey all you gamers using Twitch," this is now a signal, where is it leading to? And where does blockchain in particular impact it? Because this is kind of where everything's converging to. >> So what I'd like to say right now is, you've got Marc Andreessen's premise that software is eating the world. If you extend that, data is feeding it, blockchain is valuing it, and it's AI that's automating it. So in my mind, particularly in my experience earlier this year in the AI industry, you realize that AI today really boils down to machine learning, which in itself boils down to deep learning, which boils down to data, your access to data. Professor Andrew Wang did this at the recent O'Reilly conference up in the city, he got up and lectured as the keynote instead of sharing slides and his number one, two, and three advice to everyone in the audience was, get the right datasets to train your model. If you don't have that you don't have a differentiated business, and that's what inspired PencilDATA, is my encountering of the cold start AI problem where the IP's in a public domain, public datasets are ubiquitous which is fantastic for academics, but as a business you can't differentiate unless you have access to the right datasets to train your models more specifically. >> Okay, as the founder and CEO of PencilDATA, that's your new startup, let's get into some of the reasons why you're starting it. What problem are you attacking? Obviously a pencil, I can see pencil and you erase things, it's got data... >> The internet is no longer written in ink, that's the premise. Now with Pencil you can erase some data. >> Well blockchain is immutable, so this is conflicting in my mind. Help me kind of rationalize this. The benefit of blockchain is everything's permanent, if you're on-chain as they say. >> Exactly. >> If you're off-chain, you could do some things. Is that kind of what we're getting at? >> We're mixing the best of both. So our premise is that again, whether you're an organization or an individual, you need to have, to survive in a new digital economy, control over your data. The blockchain part of it is the visibility side. If you don't know who's doing what to your data, you're far less likely to share it. And once you know who's doing what to your data, in an immutable blockchain, with a detailed audit trail, with strong authentication, of literally who's doing what to your data, gives you that visibility. Then you do what modern asset managers do. You can't really value an asset until you fully control it. And our premise is, you can't control something until you can take it back. So the notion of PencilDATA is the ability to go on-chain for the visibility and off-chain for managing data in encrypted containers, and if a data owner or publisher doesn't like how the subscriber's consuming their data, they have the power to revoke all downloaded copies. >> So is this kind of like a shadow blockchain model? I'm trying to find a mental model because I remember the old days back, I was breaking into the industry in the late '80s, early '90s, WORM drives, write once, read many. And you write it once, it's a laser, it was optical drives at the time. Also, demilitarized zones in networking was an area where there was a safe harbor kind of thing, where people could play around. What metaphor, what mental model can people take away from some of the things that you're trying to solve? Is it like a DMZ, is it like a-- >> The implementation's a lot like a DMZ and the business challenge and opportunity is that there's a lot of tension between protecting data, because we have an epidemic of data breaches right now, I think you're foolish if you're assuming that you haven't been breached yet but you might be, because everyone has been breached, personally and organizationally, so we have to deal with the rising need to protect data more and more. But at the same time, you can't stay in business if you don't optimize the monetization of the data you have. And so PencilDATA walks that fine line between letting you do both, letting you not just protect infrastructure, that's a whole other industry that we're not involved in, but literally protect data at the data level. If you look up terms like crypto anchor you'll see some of the technologies we're taking advantage of there. But being able to monetize data by unlocking all that latent value of data hidden behind firewalls. If you use a physics analogy of potential and kinetic energy, applied to data behind firewalls, there's hundreds of billions of dollars of value in latent data basically, potential data hiding behind firewalls, and when you can safely share it, give the owners control they've never had before, then you expose the value of that data for the first time. >> Alright, so let's take us through where you're at. Obviously super exciting, you're leveraging the blockchain and you've got an ICO, initial coin offering coming up but you're not just doing that for the sake of doing, there's a lot of scams out there, you're taking a little bit more of a pragmatic approach. Give us the status because you're the founder and CEO, what's the makeup of the team, how big are you guys, what are you guys looking for, obviously you're looking for team members most likely. >> We're looking for developers obviously. >> Where in the process are you? >> We are a two-month-old company. We're at the seed stage. And we've actually assembled a world-class team. You hear that a lot, but I'm really, really proud of the team members we have right now. >> World-class, are they from around the world and then they have class? Define world-class. >> They're worldly, like myself, I travel a lot. (laughter) An example, my chief privacy officer is Sheila Fitzpatrick, she's a worldwide recognized leader in data privacy, she's on many, many privacy boards in the US and EU and so forth, and she now is traveling nonstop lecturing on GDPR, itself specifically. She's one of those recognized-- >> Should you see yourself as a solution for GDPR, because that's, again, it does have teeth, I'll just say that we've been reporting on this through Wikibon, our research team as well as theCUBE, it comes up all the time and there's heavy fines associated with it, so it's not like- >> GDPR is the perfect use case because on the one hand, we have that audit trail that proves what you're doing with data. On the other hand we have a kill switch, that revocable use clause for data where you can literally comply with GDPR in minutes or seconds, as opposed to take a full 24 hours to scour database and delete selected records. >> Alright, so what about the product? Give us an example of the product. Will you be, first of all that's right around the corner, it's next year. >> Val: Yeah. >> I think it was a March or April's timeframe, I don't have the exact date but it's pretty soon. >> Public beta before the end of this year, version 1.0 first of second quarter next year. >> For you guys, PencilDATA. >> Yes. >> Clients, are you working with anyone right now, you have a handful? >> So we've actually got really interesting distribution partnerships that we're not in a position to announce right now but the top-tier brand name enterprise cloud vendors, both on the SaaS and infrastructure and database side, they're lining up to work with us. Because we're enabling amazing use cases in healthcare and life sciences, the ability to selectively share patient data with insurers, with healthcare providers, clinical trials now to share more information through differential privacy and collectively have more data to be processed and analyzed. Use cases are just off the charts. >> Well you know we go to all the big data shows, we're horizontally scaled on the event site circuit, but this is the number one thing that comes up, I want to move from batch marketing, batch process, batch business to real-time business, speed is essential, but it's always been a conflict between, how do I enable data to move really fast and be available for applications but protecting the privacy. >> Yeah. >> Do you solve that problem, is that something that you see yourselves solving? >> We aren't necessarily innovating on speed, of data movement, it's going to be a SaaS service. >> So it's availability model. >> It's availability of data that's really never been shared before and I think that's the key here, is we know there's a lot of value locked up behind corporate firewalls. The irony is, we don't even have to sell this outside firewalls initially, when you go to any medium-to-large size enterprise that has more than one site or more than one department, Sales doesn't trust Marketing and vice versa, Engineering doesn't trust Customer Support, neither of the four of them trust each other, so we're actually going to enable more data shared within an enterprise at first. >> So that's a starting point for you guys. >> That's a starting point, that's the easiest low-hanging fruit sale we have. >> Well PencilDATA, it's great stuff, Val, congratulations on that startup. I mean, you've got a world-class management team, and this kind of brings up a point that I've been banging on theCUBE pretty much every time I go out I'll talk about blockchain and ICO because you know, theCUBE is a very decentralized audience and that's a value that we're looking at as well with blockchain. I've got to ask you the personal question, from your own personal perspective, experience, executive and CTO, why is blockchain attracting so many A players? Because you're seeing a lot of what I call A players, entrepreneurs, technical geeks, really jumping into this because they can see it, they can smell the opportunity, and also, it also attracts the scammers as well, but specifically, why are these A players coming in? Is it, what are you hearing, what's the general vibe, what's the anecdotal reason? >> So as you said earlier on, it's a fundamental evolution of the core internet as a technology, as fundamental as HTTP and web was on top of TCP/IP back 20 years ago, but it's got that rare combination of not only being a technical innovation that empowers new use cases on the web, on the internet, it's also got immediate, amazing business applications as a store of value initially, as an actual valuation of various business processes, or datasets in my case, as an ability to exchange that value so transparently, so, in such a friction-less liquid manner, those are some of the amazing innovations it brings to the table and I think the most important thing is not to think of this as being able to do digital transformation or faster analog, it's about completely reimagining the exchange of value, measurement of value, and new kinds of businesses that just weren't possible before. >> And at all points of the stack, not the low levels and at the application level, the business logic, and to the geek side, right? >> Absolutely. >> You agree. I mean, that's great and as you know, theCUBE is looking at a blockchain ICO on down the horizon so keep an eye out for that, CUBEcoins could be in everyone's future, so we're super excited like you. >> I'm looking forward to your presale, just like I'm looking forward to mine. (laughing) >> Well, we'll see. But the bottom line is that this is what the reality is, you know, reimagining the applications is what people are thinking and I think people should beware of the scams out there, and then final question I want to ask you is, obviously we're both in the community together, with our teams. Share your perspective on the ecosystem, because obviously decentralization will change the nature of traditional ecosystems. >> Very much so. >> What's your vision on how the ecosystem will evolve, and how big is it now relative to these early markets? >> We're actually starting to enter the middle innings of the cloud game, if you will, we're seeing a very good maturity, a good diversification of profitable earnings and outcomes for the major cloud players, so I think we've gone well down the cloud path so far. But the decentralized world is in its infancy. It's embryonic right now. And I've always been a proponent of the multi-cloud environment and a multi-cloud world, and decentralization fundamentally is based on and depends on a multi-cloud, not just multi-region, but multi-data-center-in-a-closet scenario as well, to be able to actually have a democratic model for determining where the value is, where the value isn't, blockchain node style. And that is incredibly exciting to me, because that really cements this rebalancing of the pendulum between core and edge in terms of where processing and value happens. >> Yeah, and value exchange obviously now, markup links are becoming the du jour way to exchange value, users are in control, infrastructure equilibrium is interesting. Great stuff. And I'll say, perfect storm for innovation. The waves are coming. (laughing) >> You know, one thing I've learned over the years is, the innovation, change never stops. There's always an opportunity to innovate, and that's what I love about this movement. >> Blockchain, ICO, PencilDATA, check 'em out, Val Bercovici, founder and CEO, great friend of theCUBE, also really strong CTO, check these guys out. This wave of innovation around blockchain ICOs and infrastructure, reimagining, the future is here upon us at theCUBE, be right back with more, thanks for watching. (electronic music)

>> Narrator: Live from San Francisco. It's theCUBE, covering DevNet Create 2017, brought to you by Cisco. >> Welcome back, everyone. We're live in San Francisco for CUBE's special coverage, exclusive coverage, of Cisco Systems DevNet Create. It's an inaugural event for DevNet, a new extension to their developer program. DevNet, which is their classic developer program for the Cisco ecosystem, network guys, so on and so forth, moving packets around, hardware guys. DevNet Create is about developers and dev ops and cloud-native, all the goodness of application developers. Where apps meets infrastructure, certainly with the Cisco acquisition of AppDynamics, a new world order is coming down the pipe. Cisco's moving up the stack. I'm John Furrier, Peter Burris is my co-host, our next guest is Val Bercovici, CUBE alumni and also guest analyst in our studio in Palo Alto, also the cofounder of Peritus.ai, and now you can talk about it. Welcome to theCUBE. >> Thanks, John. We get to talk about it, finally. >> So before we get into your company, and I want to drill into it because the first public CUBE interview, drilling down on what you're working on. What's your take on Cisco's event here, because, I've known Cisco since I moved to Silicon Valley, 18 years, and even before then, and they scaled all the internet connecting networks. There's always been a discussion internally inside Cisco about moving up the stack. And it's always been kind of like a Civil War. Half the company wants to move up the stack, half doesn't, and now, you've been in NetApp, you know this world and its infrastructure, its hardware, its gear, its boxes, network packets. This is a seminal moment for Cisco. They've tried some open source before, but this seems like an all-in bet. Your thoughts? >> It is, and I was just telling Yodi Rahm, before we went live on stage that I think this is like Goldilocks event, right? It's my first. Apparently, it's the first one of its kind here at Cisco, and for me it's not too big. It's not too small. I find it really just the right size, and I find it very well-targeted, in terms of the fellow speakers, panelists that I was on with today in terms of, I see the right amount of laptops, the right amount of code, basically, amongst the attendees on the floor here. So my first impression, 'cause that's all I have so far, is it's a very well-targeted show, and it's not unique anymore. You'll notice Intel kind of pulled back from having one large event, one large annual event, and smaller more targeted events for developers, for operators, for other ISVs, and so forth. >> You're talking about the IDF Intel Developer Forum. >> The IDF, yeah, it's no longer a big, monolithic event. They split it up into more- >> And IBM has also collapsed their shows into one monster show. So little micro-events seem to be the norm. >> Yeah, I wouldn't even call it quite even a micro-event. It's a bit bigger than that, but it's not a VMworld . >> It's not a Dreamforce. >> It's not a COMDEX to VR sales. >> Interesting, I like they did their homework on the panels. So in terms of subject matter, the agenda looks great, but I do agree with you. I like how principals are here. It's not just staff here. It's both people in the trenches at Cisco, and the execs are here. Susie Wee and some other folks, they run Cisco a lot. They're all here. >> And their CTO, this morning, I caught the opening keynote livestream on the way over here. She did a fantastic job describing the role of the infrastructure developer, which is something that is a bit nebulous to nail down, at least it has been in the past, and I'm really glad that Cisco is echoing that, because I think it helps their entire ecosystem, their partner ecosystem, particularly former employers like NetApp of mine. >> I'm usually critical of big companies trying to put their toe in the water with some event that looks like a little cloud washing or you know, here or there, but I think Cisco's got a legit opportunity with programmable infrastructure. And I think, just in general, straight up, they do, because their infrastructure, and Peter and I talked about that. But I think IoT is really the big driver. They could really, that's a network connection. It's at the edge. It requires intelligence. That's a good angle for them. >> It's a great angle. The only beef I have, the gripe I have, is they still call it IoE, I think. If it's going to be Internet of Everything, and it's Internet of nothing, right? I really wish they'd kind of stick to the agreed term, and what they are doing of course is giving- >> But they were first with IoE. They were, you got to give Cisco, when they ran those commercials, what 10 years ago? >> Yeah. >> You know. >> It's a personal in for me. The commercials are fantastic. It's just the term bothers me. >> They got dogma with IoE, come on, get rid of it. Okay, tell me about your company? >> So Peritus.ai, we've realized now there's a chance to go beyond traditional digital disruption of existing industries to cognitive disruption. Let me explain what I mean by that. We're seeing a lot of increasing pace of change in data centers. The conference here, and all the technologies spoken about here, are very foreign to more traditional data center operators, and so the new environments, microservice architectures, or cloud-native apps or so forth. It's a pace of change that we haven't seen before. Agile business and agile software developer models can push code out realistically on a daily basis, whereas the waterfall model and the iCode models in most IT service practitioners practice, that's a manual or quarterly update cycle, with formal change managed practices. >> John: A more settled, structured. >> Yeah, yeah. >> Slow. >> Familiar. >> John: Reliable. >> You know, but it's the past, and the pace of change now is creating stress within IT organizations and stress within the product support organizations of the vendors that they choose to deploy. You couple that with increasing complexity of the environments we have here. We have a lot going on, the ethos of CNCF, which is container packaged, dynamically orchestrated, and micro services architected apps, cloud-native apps. The abstraction layers are masking a lot of complexity there, but the complexity is still there. And you have very good availability if you're able to write to cloud-native principles as a developer, but nevertheless, you still got that .001% of your outages so forth. And the last line of defense towards business continuity is still a human. You still got escalation engineers and support organizations that go through pretty contrived and complicated workflows to triage and diagnose problems, perhaps a case manager to assign a case or subject manager expert, get that back and forth information with the customer and finally resolve the case, and this is what we term cognitive disruption. The maturity of the AI platforms now have reached a point where you can take these complicated workflows that require nuance and inference, and actually apply true machine learning and deep learning to them. And if not entirely automate the resolution of these complex cases, better prepare a scarce resource, an escalation engineer with lots of experience, with more context up front when they encounter the case, so they can close it more quickly, and this has- >> So you're targeting, so if I understand this correctly, you're targeting the personnel in the data center. >> Val: The supportability space. >> Escalation engineers, the human labor, the last mile, if you will, or whatever, first mile, how you look at it. >> Correct. We see APM vendors in this space, we see ITSM vendors in the space. They're partners and even platforms for us. No one really is focused on supportability and automating those workflows using cognitive techniques. >> John: Give an example, give an example. >> The best example I can give actually is firsthand. I'll try and be as generic as I can to protect the innocent, but if you take a look- >> John: NetApp. >> (laughs) It's not even specifically a NetApp case. >> John: Okay, all right. >> If you look at the supply chain upstream, let's talk about electronic supply chain. If a particular manufacturer defect occurs upstream, that defect gets shipped in bundles, purchased by an equipment supplier vendor in bundles, and deployed by customers in bundles. So it's not like one of these one node outage situations is the best case scenario, traditional triple replication, you know. >> John: It's a bad batch basically. >> A bad batch. >> A lot of bad product. >> That can take out not just a node, it can take out a rack. It can take out multiple racks of storage gear, switching gear, server hosts, and so forth. In that case, again, your last line of defense is a human. You basically got to triage and diagnose the problem, could be hardware problem, could be a driver-software problem, could be an upstream OS or database problem. And it's a very stressful environment, a very stressful situation. You can take a look at prior case notes. You can take a look at machine logs and data. You can take a look at product documentation and bill of materials from suppliers, and you can pre-analyze a lot of that, and factor that into your diagnosis, effectively having it almost ready before the case is even opened, so that when the escalation engineer is assigned the case, they don't start from ground zero. They start from third base and almost they're rounding their way to home, and they're able to apply all the prior knowledge, algorithms never sleep. All the prior knowledge in terms of all the cases that have actually been dealt with that match that to a degree. They're never perfect matches, because that's just business process automation. There's a degree of inference required, and using AI techniques, we're able to guess that you know what? I've seen this before. It's very obscure, but it's actually going to be this resolution. >> So AI's technology that you're using in machine learning and data, what problem are you solving specifically? Saving them time, getting them faster resolutions? >> So we're improving the efficiency of support operations. There's always margin pressures within customer support operations. We're fundamentally solving complex system problems. We've reached a point now where business process automation can solve trivial support cases. >> John: Wait a minute, wait a minute, hold on. Expert system's supposed to do this. >> And they did in the past, and now we're evolving beyond the expert. >> Not really. Remember those expert system stays? >> Yeah, I remember LISP and all those early days, so yeah. >> So this kind of sounds like a modern version of an expert system to aid the support engineers to either have a predetermined understanding of options and time to solution. >> So we're able to do so much more than that, right? We're able to create what we call otologies. We're able to categorize all the cases that you've seen in the past, find out whether this new one fits an existing category, if so, if it matches other criteria, if not, defining a category. We're able to orchestrate. Resolution is not just a one-shot deal. Resolution is diagnose the problem, find out if you have some subject matter experts available to resolve the issue, assign it to them, track their progress, close the case, follow up on customer satisfaction. All those things are pretty elaborate workflows that can be highly automated today with cognitive approach-- >> Congratulations on launching. Thanks for spending the time to lay that out. What's next? You've got some seed funding? >> Val: We've got some seed funding. >> You got some in an incubator at the Hive in Palo Alto, which we know quite well. Rob is great, Rob is a great friend. He's done great, he's done great. How many people do have, what are you guys looking to do? What are some of the priorities? >> We are hiring. We're definitely looking to get more data scientists on staff, more full-stack engineers particularly with log experience. We're still looking for a CTO and leadership team. So there's a lot of hiring coming in place. >> John: How many in there now? >> We have about, less than 10 people working right now. >> It's a great opportunity for a classic early-stage opportunity. >> Yeah, early stage opportunity. We're addressing a hot space, and what I love is I personally shifted from being a provider of cloud-native solutions in this market to being a consumer. So I'm seeing exactly how a perfect storm is coming together of machine and deep learning algorithms, running on, orchestrated-- >> John: Both sides of the table. You should talk to Mark Sister. >> Yeah. He's been on both sides. What's it like to be on the other side now? >> It's everything I actually thought it would be, because at the end of the day, I always say, developers are the ultimate pragmatists. So it's not so much about brand loyalty at any particular vendors. What solution, whether it's an open source library, whether it's a commercial library, whether it's a propietary cloud service or something in between. What solution can solve my task, this next task? And composite applications are a very real thing right now. >> So we had a question I posted into the crowd chat, from this social net. I'm going to ask you the same questions. So Burt's watching and maybe you'll find that thread, and I'll add to it later. Here's the question. What challenges still remain as part of implementing DevOps, in your opinion? How did you see the landscape, and how are people addressing them? In your expert opinion, what's the answer to that question? What's your opinion? >> It's a two-faceted answer, at least. The first one, it's not a cliche. It's still a cultural challenge. If you want to actually want to map, it's not even a cultural challenge specifically, it's Conway's Law. Any product output, software output, is a function of your organizational structure that created it. So I find that whether you want to call it culture, whether you want to call it org structure, the org structure's rarely in place to incentivize entire teams to collaborate together throughout a full CICD pipeline process. You've still got incentive structures and org structures in place for people to develop code, unit test it, perhaps even integration test it, but I see more often than I'd like to, isolated or fenced off operations teams that take that and try to make it something real. They might call themselves SREs, and outside recovery engineers, but they're not integrated enough into the development process, in my mind. >> So you're saying the organization structures are also foreclosing their ability be agile, even though they're trying hard, that the incentives are too grounded in there. >> So I still see a lot of skunkworks projects as DevOps projects, and it shouldn't be that way anymore, right? There should be, where there's a legitimate business reason for more agile businesses, there should be a much more formal DevOps structure, as opposed to skunkworks DevOps structure. So that's one challenge, and it's not new, but it's also not resolved. And the other one really is this blind spot for the autonomous data center vision, this blind spot for operations being 100% automated and really just never having to deal with the problem. The blind spot is everything breaks. New technology just happens to break in new ways, but it does fundamentally break, and if your last line of defense is a human or a group of humans, you can expect a very, very different sort of responsiveness and agility as opposed to having something automated. >> Peter and I have been talking all morning the Ford firing of Mark Fields, which was announced yesterday. He quote retired by the Twitter handle of Ford, which is just code words for he got pushed aside. One, we're big fans of Mark Fields, before we covered Ford there in Palo Alto, doing some innovative centers over there, and also a Cloud Foundry customer. So I was actually, took notice of that. We were commenting on not so much the tech, but the guy got fired in less than three years into his journey as chief executive. >> Val: Yeah. >> Now the stock's down 39% so the hammer's coming down from either the family, Ford family, or Wall Street, Peter thinks Wall Street. But this brings up the question, how are you going to be a transformational leader, if you don't have the runway? Back to your org structure. This is, this is-- >> I'm like a broken record. I was thinking that yesterday as I was watching CNBC, and just thinking in my mind, processing what they were announcing. I'm realizing in my head, I bet why, because I don't know, but I bet why, I speculate why he got fired, because he wasn't able to put the org structure and incentives in place to run faster, and that's what the board asked his successor is run faster, and if his successor doesn't put the org structure and the incentives in place to be an agile business. That's the definition of insanity. It's banging your head against the wall. >> If I had to add one more thing to that comment, which by the way I agree with you. If you could configure an asset in a company besides the organizational structure, so you did that, what would your next asset be? More cloud, more data-centric, what would be? >> It might be cliche, but it's totally true, I would have a cloud-first approach to everything. So we don't remember this guy called Obama anymore, but really he did a pretty revolutionary thing, when he brought in a CIO eight, nine years ago, and he made every federal government department defend a capital purchase. And they basically have to go through a multi-hundred page document to defend a capital IT acquisition, but to actually go cloud first or cloud native, didn't require almost any pre-approval at all to get funding. >> So we made it easier incentives to go cloud. >> Created incentives, and I'm a big believer that cloud is not a panacea. >> That helped Amazon, not IBM, as the CIA case now. >> I'm a big believer in life cycles, so it's not like cloud is the rubber stamp solution for every problem, but the beginning innovation phase of every new product line or revenue stream really should be in the cloud right now. The amazing services, forget about IS and all that. Look at the machine language and APIs, IoT APIs, the entire CICD pipelines that are automated and simplistic, the innovation phase for everyone should be in the crowd. Then you got to take a step back, look at that bill, get over your sticker shock, and figure out whether you can afford to stay in a cloud using maybe some of those higher-level proprietary high-margin services and whether you want to re-factor. And that's where professional services kick in, and I think that might be the next great disruption for AI, is re-factoring apps. >> I think one of the things, final question I want to get your thoughts on. Pretend that we're at Cisco and we go back to the ranch, and someone says, "Hey, what's that DevNet Create?" What's our advice to our peers, if we had an opinion that people valued inside Cisco, doubled down on DevNet Create, continue, merge it DevNet? What would your advice be? >> I'm a long time James Governor fan. Developers are the new kingmakers. Actually I think we're in this situation that's not very well understood by business leaders right now, where developers are influencing all the technology infrastructure decisions we're making, but they don't necessarily write the checks. But if you want to run an agile business, a digital business today, you can't do it without happy developers and a good developer experience, so you have to cater to their needs and their biases and so forth, and at shows like this I think, bring Cisco's large ecosystem to bear, where we can figure out how Cisco can maximize the developer experience, how partners, and I'm soon to be a Cisco partner myself at Peritus.ai can maximize their developer experience and just drive more modern business. >> Bring the developer community in with the networking, get those margins connected. Val Bercovici, cofounder of Peritus.ai, this is theCUBE with exclusive coverage of the inaugural event of Cisco's DevNet Create. I'm John Furrier, Peter Burris, returning after this short break. (electric music) >> Hi, I'm April Mitchell, and I'm the senior director.

>> Announcer: Live, from Silicon Valley, it's the Cube. Covering Google Cloud Next 17. (ambient music) >> Okay, welcome back everyone. We are here live in Palo Alto for a special two days of coverage of Google Next 2017 events in San Francisco. Sold out, 10,000 plus people. Yeah, really, an amazing turn of events. Amazon Web Services Reinvent had 36,000, Google's nipping at their heels, although different, we're going to break down the differences with Google versus Amazon because they're really two different things and again, this is Cube coverage here in Palo Alto studio, getting reaction. Sponsored by Intel, thanks, Intel, for allowing us to continue the wall-to-wall coverage of the key events in the tech industry. Our next guest is Val Bercovici who's the boardmember of the Cloud Native Compute Foundation, boardmember. >> That's right. >> Welcome back, you were here last week from Mobile World Congress, great to see you. Silicon contributor, what your reaction to the Google keynote, Google news? Not a lot of news, we saw the SAP, that was the biggest news and the rest were showcasing customers, most of the customers were G Suite customers. >> Yeah, exactly. So, I would say my first reaction is bit of a rough keynote, you know, there's definitely not as quit as much polish as Microsoft had in their heyday and of course, Amazon nowadays in the Cloud era. But what's interesting to me is there's the whole battle around empathy right now. So, the next gen developers and the Clouderati talk about user empathy and that means understanding the workflow of the user and getting the user to consume more of your stuff, you know, Snapchat gets user empathy for the millennial generation but anybody else. Facebook as well. So, you see Google, we emphasize, even the Google Twitter account, it emphasizes developer productivity and they have pretty strong developer empathy. But what AWS has, Amazon with AWS is enterprise empathy, right, they really understand how to package themselves and make themselves more consumable right now for a lot of mainstream enterprises, they've been doing this for three, four years at their Reinvent events now. Whereas Google is just catching up. They've got great developer empathy but they're just catching up on enterprise empathy. Those are the main differences I see. >> Yeah, I think that's an important point, Val, great, great point, I think Amazon certainly has, and I wrote this in my blog post this morning, getting a lot of reaction from that, actually, and some things I want to drill down on the network and security side. Some Google folks DMing me we're going to do that. But really, Amazon's lead is way out front on this. But the rest, you know, call 'em IBM, not in any particular, IBM, Oracle, Google, SAP, others, put Salesforces, we're talking Sass and Adobe, they're all in this kind of pack. It's like a NASCAR, you know, pack and you don't know who's going to slimshot around and get out there. But they all have their own unique use cases, they're using their own products to differentiate. We're hearing Google and again, this is a red flag for me because it kind of smells like they're hiding the ball. G Suite, I get the workplace productivity is a Cloud app, but that's not pure Cloud conversations, if you look at the Gartner, Gartner's recent, last report which I had a chance to get a peek at, there's no mention of Sassifications, Google G Suite's not in there, so the way Cloud is strictly defined doesn't even include Sass. >> Yeah. >> If you're going to include Sass, then you got to include Salesforce in that conversation or Adobe or others. >> Exactly. >> So, this is kind of an optical illusion in my mind. And I think that's something that points to Google's lack of traction on customers in the enterprise. >> This is where behind the scenes, Kubernetes, is so important and why I'm involved with the the CNCF. If anything, the first wave of Clouded option particularly by enterprise was centered around the VM model. And you know, infrastructure's a service based on VMs, Amazon, AWS is the king of that. What we're seeing right now is developers in particular that are developing the next generation of apps, most of them are already on our phones and our tablets and our houses and stuff, which is, you know, all these Echo-style devices. That is a container-based architecture that these next gen applications are based on. And so, Kubernetes, in my mind, is really nothing more than Google's attempt to create as much of a container-based ecosystem at scale so that the natural home for container-based apps will be GCP as opposed to AWS. That's the real long term play in why Google's investing so heavily in Kubernetes. >> Is that counterintuitive? Is that a good thing? I mean, it sounds like they're trying to change the goalpost, if you will, to change the game because we had Joe Arnold on, the founder of Swiftstack and you know, ultimately, you know, Clouds are Clouds and inter-Clouding and multi-Cloud is important. Does Kubernete actually help the industry? Or is that more Google specific in your mind? >> I think it will help the industry but the industry itself is moving so rapidly, we're seeing server-less right now and functions of service, and so, I think the landscape is shifting away from what we would think of as either VM or container-based infrastructure service towards having the right abstractions. What I'm seeing is that, really, even the most innovative enterprises today don't really care about their per minute or per hour cost for a cycle of computer, a byte of, you know, network transferred or stored. They care about big table, big quarry, the natural language processing, visual search, and a whole category of these AI based applications that they want to base their own new revenue-generating products and services based on. So, it's abstraction now as a new battlefield. AWS brings that cult of modularity to it, they're delivering a lot of cool services that are very high level Lambda centered based on really cool modularity, whereas Google's doing it, which is very, very elegant abstraction. It's at the developer level, at the technical level, that's what the landscape is at right now. >> Are you happy with Google's approach because I think Google actually doesn't want to be compared to AWS in a way. I mean, from what I can see from the keynote... >> Only by revenue. (laughs) >> Well, certainly, they're going to win that by throwing G Suite on it but, I mean, this is, again, a philosophy game, right? I mean, Andy Jassy is very customer focused, but they don't have their own Sass app, except for Amazon which they don't count on the Cloud. So, their success is all about customers, building on Amazon. Google actually has its own customer and they actually include that in, as does Microsoft with Office 365. >> Yeah, that's the irony, is if we go back to enterprise empathy I think it's Microsoft has that legacy of understanding the enterprise better than all the others. And they're beginning to leverage that, we're definitely seeing, as you're sliding comfortably to a number two position behind AWS, but it really does come back to, you know, are you going to lead with a propeller head lead in technology which Google clearly has, they've got some of the most superior technology, we were rattling off some the speeds and feeds that one of their product managers shared with you this morning. They've had amazing technology, that's unquestioned. But they do have also is this reputation of almost flying in rarefied air when it comes to enterprises. >> What do you mean by that? >> What I mean by that is that most enterprise IT organizations, even the progressive ones, have a hard time relating to Google technology. It's too far out there, it's too advanced, in some cases, they just can't understand it. They've never been trained in college courses on it or even post-grad courses on it. MBA is older than three years old, don't even reference the Cloud. So, there's a lot of training, a lot of knowledge that has to be, you know, conducted on the enterprise side. AWS is packaged, that technology there is the modularity in such a way that's more consumable. Not perfect, but more consumable than any other Cloud render and that's why, with an early head start, they've got the biggest enterprise traction today. >> Yeah, I mean, and I'm really bullish on Google, I love the company, I've been following them since '98, a lot of friends here at Palo Alto, a lot of Googlers living in my neighborhood, they're all around us. Larry Page, seen him around town. Great, great company and very, always been kind of like an academic, speed of academic. Very strong, technically, and that is, clearly, they're playing that card, "We have the technology." So, I would just say that, to counter that argument would be if Google, I'm Google, I'm on the team, the guy in green and you know, lookit, what I want to do is, we want to be the intel for the Cloud. So, the hard and top is we don't really care if people are trained, should be so easy to use, training doesn't matter. So, I mean, that's really more of an arrogant approach, but I don't think Google's being arrogant in the Cloud. I think that ship has sailed, I think Google has kind of been humbled in the sense, in recognizing that the enterprise is hard, they're checking the boxes. They have a partner program. >> Yeah, you're right, I mean, if you take a look at their customers today, you've got Spotify, and Snap, and Evernote, and you know, Pokemon Go and Niantic, all of the leading edge technology companies that have gone mainstream that are, you know, startup oriented Snap, of course. They're on Google Cloud. But that's not enough, you know, the enterprise, I did a seminar just last week promoting Container World with Jim Forge from ADP. The enterprise is not homogeneous, the enterprise is complicated. The L word legacy is all over, what they have to budget and plan for. So, the enterprise is just a lot more complicated than Google will acknowledge right now. And I believe if they were to humanize some of their advanced technology and package it and price it in such a way that AWS, you know, where they're seeing success, they'll accelerate their inevitable sort of leap to being one of those top three contenders. >> So, I'm just reading some of my, I'm putting together because for the Google folks, I'm going to interview them, just prepping for this, but just networking alone, isolating Cloud resources. That's hard, right? So, you know, virtual network in the Cloud, Google's got the virtual network. You get multiple IP addresses, for instance, ability to move network interfaces and IPs between instances, and AS networking support. Network traffic logging, virtual network peering, manage NAT gateways, subnet level filtering, IP V stick support, use any CIDR including RC 1918. Multiple network interface instances, I mean, this is complicated! (laughs) It's not easy so, you know, I think the strategy's going to be interesting to see how, does Google go into the point to point solution set, or they just say, "This is what we got, take it or leave it," and try to change the game? >> That's where they've been up until now and I don't think it's working because they have very formidable competitors that are not standing still. So, I think they're going to have to keep upping their game, again, not in terms of better technology but in terms of better packaging, better accessibility to their technology. Better trust, if you will, overseas. Cloud is a global game, it's not US only. And trust is so critical, there's a lot of skepticism in Europe today with the latest Wikileaks announcements, or Asia Today around. Any American based Cloud provider truly being able to isolate and protect my citizen's data, you know, within my borders. >> I think Google Cloud has one fatal flaw that I, looking at all the data, is that and the analysis that we've been looking at with Bookie Bontine and our research is that there's one thing that jumps out at me. I mean, the rest are all, I look at as, you know, Google's got such great technologies, they can move up fast, they can scale up to code. But the one thing that's interesting is their architecture, the way they handle their architecture is they can't let customers dictate data where data's stored. That is a huge issue for them. And if, to your point, if a user in Germany is using an app and it's got to stay in Germany. >> This is back to the empathy disconnect, right? As an abstraction layer for a developer, what I want is exactly what Google offers. I don't want to care as a developer where the bits and bytes are stored, I want this consistent, uniform API, I want to do cool stuff with the data. The operation side, particularly within legal parameters, regulatory parameters, you know, all sorts of other costs and quality assurance parameters, they really care about where that data is stored, and that's where having more enterprise empathy, and their thinking, and their offerings, and their pricing, and their packaging will leapfrog Google to where they want to be today. >> Val Bercovici, great analysis, I mean, I would totally agree just to lock that in, their developer empathy is so strong. And their operational one needs to be, they got a blind spot there where they got to work on that. And this is interesting because people who don't know Google are very strong operations, it's not like they don't have any ops chops. (Val laughs) They're absolutely in the five nines, they are awesome operations. But they've been operations for themselves. >> Exactly. >> So, that's the distinction you're getting at, right? >> Absolutely. >> Okay, so the next question I got to ask you is back to the developer empathy, 'cause I think it's a really big opportunity for Google. So, pointing out the fatal flaw in my opinions in the data locality thing. But I think the opportunity for Google to change the game, using the developer community opportunity because you mentioned the Kubernetes. There is a huge, open source, I don't want to say transformation but an evolution to the next generation, you're starting to see machine learning and AI start to tease out the leverage of not just data now. Data's become so massive now, you have data sets. That can be addressable and be treated like software programs. So, data as code becomes a new dynamic with AI. So, with AI, with open source, you're seeing a lot of activity, CNCF, the Cloud Native Compute Foundation, folks should check that out, that's an amazing group, analytics foundation. This is an awesome opportunity for Google to use Kubernetes as saying, "Hey, we will make orchestration of application workloads." >> Absolutely. >> This is something, Amazon's been great with open source, but they don't get a lot of love... >> Amazon has a blind spot on containers, let's not, you know, let's not call, you know, let's call it the speed of speed, let's not, you know, beat around the bush, they do have a blind spot around containers. It is something they strategically have to get a hold of, they've got some really interesting proprietary offerings. But it's not a natural home for a Docker workflow, it's not a natural home for a Kubernetes workflow yet. And it's something they have to work on and AI as a use case could not be more pertinent to business today because it's that quote, you know, "The future is here "but unevenly distributed." That's exactly where AI is today, the businesses that are figuring it out are really leaping ahead of their competitors. >> We're getting some great tweets, my phone's blowing up. Val, you've got great commentary. I want to bring up, so, I've been kind of over the top with the comment that I've been making. It's maybe mischaracterized but I'll say it again. There seems to be a Cold War going on inside the communities between, as Kubernetes have done, we've seen doc, or we've seen Docker Containers be so successful in this service list, server list vision, which is absolutely where Cloud Native needs to be in that notion of, you know, separating out fiscal gear and addressability, making it completely transparent, full dev ops, if you will. To who's going to own the orchestration and where does it sit on the stack? And with Kubernetes, to me, is interesting is that it tugs at some sacred cows in the container world. >> Yes. >> And it opens up the notion of multi-Cloud. I mean, assume latency can be solved at some point, but... >> It's actually core religion, what impressed me about he whole Kubernetes community, and community is its greatest strength, by the way, is the fact that they had a religion on multi-Cloud from day one. It wasn't about, "We'll add it later "'cause we know it's important," it's about portability and you know, even Docker lent that to the community. Portability is just a number one priority and now portability, at scale, across multiple Clouds, dynamically orchestrated, not through, you know, potential for human error, human interventions we saw last week. That the secret sauce there to stay. >> I think not only is, a Cold War is a negative connotation, but I think it's an opportunity to be sitting in the sun, if you will, on the beach with a pina colada because if you take the Kubernetes trend that's got developer empathy with portability, that speaks to what developers want, I want to have the ability to write code, ship it up to the network, and have it integrate in nicely and seamlessly so, you know, things can self-work and do all that. And AI can help in all those things. Connecting with operational challenges. So, what is, in your mind, that intersection? Because let's just say that Kubernetes is going to develop a nice trajectory which it has now and continues to be a nice way to galvanize a community around orchestration, portability, etc. Where does that intersect with some of the challenges and needs for operational effectiveness and efficiency? >> So, the dirtiest secret in that world is data gravity, rigtht? It's all well and fine to have workload portability across, you know, multiple instances and a cluster across multiple Clouds, so to speak. But data has weight, data has mass and gravity, and it's very hard to move particularly at scale. Kubernetes only in the last few releases with a furious pace in evolution, one four, one five, has a notion of provisioning persistent volumes, this thing they affectionately called pet sets that are not a stateful sets, I love that name. >> Cattle. >> Exactly. (laughs) So, Google is waking up and Kubernetes, I should say, in particular is waking up to the whole notion of managing data is really that last mile problem of Cloud portability and operational maturity. And planning around data gravity and overcoming where you can data gravity through meta-operational procedures is where this thing is going to really take off. >> I think that's where Google, I like Google's messaging, I like their posture on machine learning AI, I think that's key. But Amazon has been doing AI, they've got machine learning as a service, they've had Kineses for a while. In fact, Redshift and Kineses were their fastest growing services before Aurora became the big thing that they had. So, I think, you know, they're interested in the jets, with the trucks, and the snowmobile stuff. So I think certainly, Amazon's been doing that data and then rolling in as some sort of AI. >> And they've been humanizing it better, right? I can relate to some of Amazon's offering and sometimes I have it in the house. You know, so, the packaging and just the consumerability of these Amazon services today is ahead of where Google is and Google arguably has the superior technology. >> Yeah, and I think, you know, I was laying out my analysis of Google versus Amazon but I think it's not fair to try to compare them too much because Google is just making their opening moves on the chessboard. Because they had Diane Green, got to give her credit, she's really starting behind. And that's been talked about but they are serious, they're going to get there. The question is what does an enterprise need to do? So, your advice to enterprise would be what? Stick with the use cases that are either Google specific apps or Cloud Native, where do you go, how do you...? >> I would say to remember the lock-in days of the Linux vendors and even Microsoft in their heyday and definitely think multi-Cloud, you know, Cloud first is fine. But think, we need data first in a Cloud before I think a particular Cloud first. Always keep your options open, seek the highest levels of abstraction, particularly as you're innovating early on and fast failing in the Cloud. Don't go low right away, go low later on when you're operationalizing and scaled and looking to squeeze efficiencies out of a new product or service. >> Don't go low, you mean don't go low in the stack? >> Don't go low in the stack, exactly. Start very high in the stack. >> What would be an example? >> Lambda, you know, taking advantage of, if we bring in Kineses, IOT workflows, all sorts of sensor data coming in from the Edge. Don't code that for efficiency day one and switch to Kafka or something else that's more sophisticated, but keep it really high level as events triggering off, whether it's the IOTICK in the sensor inputs or whether it's S3 events, Dynamo, DB events. Write your functions that are very, very high level. >> Yeah. >> Get the workflows right. Pay a bit more money up front, pay premium for the fast... >> Well, there's also Bootstraps and the Training Channel Digimation, so, with Google, pick some things that are known out there. But you mentioned IOT and one of the things I was kind of disappointed in the keynote today, there wasn't much talk about IOT. You're not seeing IOT in the Google story. >> That may come up in tomorrow's keynote, it may come up tomorrow in a more technical context. But you're right, it's an area both Agar and AWS have a monster of a lead right now, as they've had really good SDKs out there to be able to create workflows without even being an expert in some of the devices that you know, you might own and maintain. >> Google's got some differentiation, they've got something, I'll highlight one that I like that I think is really compelling. Tensor flow. Tensor flow as got a lot of great traction and then Intel is writing chips with their Skylake product that actually runs much faster silicon... >> What was that, Nvidia? You know, it's a GPU game as much as a CPU game when it comes to machine learning. And it's just... >> What does that mean for you? I mean, that's exciting, you smile on that, I get geeked out on that because if you think about that, if you can have a relationship between the silicon and software, what does it mean from an impact standpoint? Do you think that's going to be a good accelerant for the game? >> Massive accelerant, you know, and this is where we get into sort of more rarefied air with Elon Musk's quote around the fact we'll need universal income for society. There a lot of static tasks that are automated today. There's more and more dynamic tasks now that these AI algorithms, through machine learning, can be trained to conduct in a very intelligent manner. So, more and more task based work all over the world, including in a robotic context but also call centers, stock brokerage, for example, it's been demonstrated that AI ML algorithms are superior to humans nine times out of ten in terms of recommending stocks. So, there's a lot of white collars, while it's blue collared work that just going to be augmented and then eliminated with these technologies and the fact that you have major players, economies at scales such as Intel and Nvidia and so forth accelerating that, making it affordable, fast, low power in certain edge context. That's, you know, really good for the industry. >> So, day one of two days of coverage here with Google, just thoughts real quick on what Google needs to do to really conquer the enterprise and really be credible, viable, successful, number two, or leader in the enterprise? >> I'm a big fan, you know, I've had personal experiences with fast following as opposed to leading and innovating sometimes in terms of getting market traction. I think they should unabashedly, unashamedly examine what Microsoft or what Amazon are doing right in the Cloud. Because you know, simple things like conducting a bit more of a smooth keynote, Google doesn't seem to have mastered it yet, right now in the Cloud space. And it's not rocket science, but shamelessly copying what works, shamelessly copying the packaging and the humanization that some of the advanced technologies that Amazon and Microsoft have done in particular. And then applying their technical superiority, you know, their uptime availability advantages, their faster networks, their strong consistency which is a big deal for developers across their regions. Emphasizing their strengths after they package and make their technology more consumable. As opposed to leading where the tech specs. >> And you have a lot of experience in the enterprise, table stakes out there that are pretty obvious that they need to check the boxes on, and would be what? >> A very good question, I would say, first and foremost, you really have to focus on more, you know, transparent pricing. Think something that is a whole black art in terms of optimizing your AWS usage in this industry that's formed around that. I think Google has and they enact blogs advertising a lot of advantages they have in the granularity, in the efficiency of their auto scaling up and down. But businesses don't really map that, they don't think of that first even though it can save them millions of dollars as they do move to Cloud first approaches. >> Yeah and I think Google got to shake that academic arrogance, in a way, that they've had a reputation for. Not that that's a bad thing, I'll give you an example, I love the fact that Google leads a lot of price performance on many levels in the Cloud, yet their SLAs are kind of wonky here and there. So, it's like, okay, enterprises like SLAs. You got to nail that. And then maybe keep their price a little high here, it can make more money, but... So, you were saying, is that enterprise might not get the fact that it's such a good deal. >> It's like enterprise sales 101, you talk about, you know, the operational benefits but you also talk about financial benefits and business benefits. Catching into those three contexts in terms of their technical superiority would do them a world of good as they seek more and more enterprise opportunities. >> Alright, Val Bercovici, CTO, also CTO, and also on the board of the Cloud Native Compute Foundation known as CNCF, a newly formed organization, part of the Linux Foundation. Really looking at the orchestration, looking at the containers, looking at Kubernetes, looking at a whole new world of app enablement. Val, thanks for the company, great to see you. Turning out to be guest contributor here on the Cube studio, appreciate his time. This is the Cube, two days of live coverage. Hope to have someone from Google on the security and network side coming in and calling in, we're going to try to set that up, a lot of conversations happening around that. Lot of great stuff happening at Google Next, we've got all the wall-to-wall coverage, reporters on the ground in San Francisco as well as analysts. And of course, in studio reaction here in Palo Alto. We'll be right back. (ambient music)

>> Announcer: Live from Silicon Valley. It's The Cube. Covering Mobile World Congress 2017. Brought to you by Intel. >> Okay welcome back everyone. We're here live in Palo Alto for The Cube's special broadcast presentation and coverage of Mobile World Congress. Which is happening in Barcelona, Spain. I'm John Furrier here with The Cube. And of course we're covering it here in Palo Alto. Bringing in experts and friends who have been following all the action. As well as have commentary and opinion on what's happening. We're going to roll up the news. It's the end of the day in Barcelona. We're just getting our sea legs here for day two of 8AM to 6PM coverage inside The Cube. And of course we want to break down the content. Our next guest is Val Bercovici who is the CTO at Solify also a governing board member of the CNCA the Cloud Native Compute Foundation, CNCF. Which was CubeCom which is now part of the Linux Foundation. Which if you know The Cube you know we've been covering that like a blanket. All these shows, The Cube has been there. This is in the world of Dockercon et cetera et cetera. Val, a CTO, 19-year veteran at NetApp of course knows the stories business, knows the converge infrastructure, know the Cloud. Val great to see you thanks for coming in. >> Thanks for having me back on after all these years. >> Yeah I mean it's great to have you on. We see each other at some of the parties, at Georgianna's place in particular. Georgianna brings all the storage and Cloud together but you and I had conversations a few years ago about where Cloud was going. And you can almost kind of connect the dots. Not to pat ourselves on the back, but I think we were right that the cloud was what we thought it would be. And probably more. For me I think I underestimated certainly the Amazon impact. >> Me too. >> But you look at what's happening in Mobile World Congress. You have a bi-polar show. You have a device show. Rah-rah look at the fancy devices. And the other show you have a Telco show that's trying to figure out their future. And that's interesting because the Telco's power the big networks that everyone's using the devices for. So you have a consumer market. But the real conversation is 5G IoT. You have a collision course of enterprise issues, enterprise data center, enterprise technology, colliding with a Telco infrastructure, AKA mobile. Head on. So it's not just more wireless. 5G's certainly the story we talked to folks like Intel and others around that but you have essentially all these core problems that are going to scale up this next generation use cases, are enterprise-like. This is your wheelhouse. So are you looking at this saying hm I've seen this movie before. What's your thoughts? >> I actually haven't. And that's what's so exciting right. As you said, there's so much innovation happening. For me probably the big story is what's not in the headlines at Mobile World Congress. Which is the back office work to support a 5G rollout. And I've had a lot of experience particularly on the side most recently. Speaking with all the big Telecos globally, and the implementations. Now what's interesting is they're all going through a gen two, or a re-architecture right now. A lot of first-generation MFE was done based on tradition or legacy now clad architecture which very VM based. And all of them are now architecting and implementing microservices based implementations. And a driver for that is just the explosion that 5G will enable in terms of connectivity between devices. So the least interesting stat to me is how fast I can download a movie off of 5G. The most interesting is how many hundreds of thousands or millions of devices within my domain are going to be communicating with each other on 5G. >> We had Saar Gillai who's going to come back today. He's also a guest, former HPer. He built their communications group while at NFE. I'd like it if he was commenting on the same thing, he made a point I want to bring up which is I don't really need more gigabit data, I want more battery life. So he's kind of being a pedestrian but that really is kind of the consumer issue. You're pointing about things that are going to be harder to do. In NFE you mention one of them. Can you explain the NFE's current situation? Also we've been doing a lot of the open stag all the open shows since it started. That has become kind of a Telco, NFE storage show as well. >> Val: Absolutely. >> So what is the real issue with NFE and why is it important and relevant to the service providers right now? >> So if you take a look at all the services we depend on on our phones nowadays. There's obviously the basic connectivity. There's additional services around location mapping for GPS, related services on top of that in terms of the collaborative apps that we use and depend on every day. Sometimes on S3 which is not always available as we're reporting right now. There's a lot of layers there. And from an NFV perspective from a back end data center perspective. Everything amounts to a session. So even though it's packet switch it's still a logical session you have to set up. So for every session, and imagine this happening millions of times at every tower, and more than millions of times at every regional or central data center. You got to have a session set up where you got to authenticate actually Who the user or the device is, make sure they have permission to be on the network and accessing certain things. You've got to authorize them to do certain things. You've got to log what's happening. Then you've got to slap some firewall or security around them. Then you've got to layer in access to all the other resources you're trying to combine into a service back to the end user. There's a lot of things going on. And we have to set up these sessions for every connection. And if you try to set up a VM, for every connection, you would have to fund a multi-billion dollar data center Google can't even afford. So this is where microservices are becoming essential right now. And a 5G hyper-connected world is where you have to have much more efficiency, in the speed with which you set up these sessions, the efficiency of number of sessions per server. And the cost, the processing of these transactions. >> This is interesting. I want to just kind of translate a little bit for the folks that aren't CTO's out there. Essentially when you think about mobile we've all been, you know, since the iPhone in 2007, we've seen this just accelerate. You know with data and whatnot. You've been at a concert, you've been in a stadium, you've got signal but you can't connect. >> Right. >> That is essentially the base station saying I can't get a session. Now as a user you have a phone, so you've been provisioned by the Telco, so they know who you are. So you have a phone, you have a device, you just can't connect a session to the radio connector and then get to the internet. That's a known problem. Now when you think about IoT, internet of things and now people, your watches, your wearables, sensors on the airplanes, industrial equipment to traffic lights. Those are devices that are going to be provisioned and turned off and on. So it's like a new phone every time. So you've got the complication of not knowing the devices that are coming on, and then trying to establish the connections. And figuring all this out. This is kind of a really hard problem. >> It is. >> This is a really really hard problem of scale at many levels. So to me what we're hearing at Mobile World Congress is you need a dynamic network. >> Val: Absolutely. >> What are some of the tech involved? What's the real enabler. You mentioned microservices, we know about containers. Linux Foundation's opening up their kernel for a lot of variety of new configurations. You got solid state memory and you got new memory architectures. What are some of the key things from a technical perspective that are going to change that complexity to be seamless for users? >> Probably the most fascinating trend to me and we're just beginning to see some stories emerge around this is the rise of edge computing. I kind of hark back to when I started my career, I'm dating myself now but the client server era that succeeded from mainframes, we've seen a huge pendulum shift towards Cloud computing. And centralizing a lot of processing. Well back to 5G, back to millions if not billions of connected devices right now. There is no way Einstein introduced his problem for the speed of light. There is no way to process the exponential amount of data we're dealing with right now at the core. And still provide useful feedback at the edge. So the rise of edge computing has a bit of a counterbalance to Cloud computing. And having more powerful, more intelligent processing at the edge, filtering a lot of data 'cause we can't possibly store the exit bytes and yadabytes of data. >> This is a paradigm shift. What you're talking about is a new paradigm shift. Because it used to be a centralized computer, and then a master slave or connected device terminal then you had smart terminals, business clients, and then PCs and then smart phones, so what you're bringing up is an interesting architecture that is an enterprise data center thing. And we were talking yesterday, and then I was telling the Intel folks, I pressed them on this 'cause they're obviously in the data center business, that a car that's fully instrumented like a Tesla or a future autonomous car is essentially a moving data center. So it changes the notion of data. >> Yes. >> This is a paradigm shift. You agree with that. >> Moreover. IoT is maybe the first technology buzzword that takes a lot of this digital world that we've been talking about. It's really been largely abstract and virtual for the common person. And it makes it physical and real. So the impact of IoT is an actuator changing your traffic light. You know, it's whether you're getting water, you're getting electricity at your house. Whether you're finding your way to your location via GPS. That's especially impacting your physical world it's no longer just a virtual thing. So that's where IoT's going to become really really significant in our lives. >> And the software program that needs to be created. This is an opportunity for entrepreneurs certainly. Peter Burris and I were talking yesterday morning about the edge computing. He's got a slew of research on this. He goes by IoT and p, IoT, things and people. And we were also talking yesterday about the relationship of the people to technology. So for instance in Telco's they view the phone as the relationship that's coupled to the carrier. And the premise we put out yesterday was that that's going to be an uncoupling. It's going to be a person's relationship to multiple carriers if you will. So the question is how does business extract value out of this? And this is something again that Peter Burris was digging into. Which is the business value of technology. In the paradigm we just talked about which seems pretty obvious, how we get there not so obvious, but people are working on that. How should companies think about getting value out of this massive shift? A lot of moving parts. >> The examples are already there. Let's talk about one of the most talked-about companies around here. Uber. And not because of the reasons they're attracting right now, but some of the classical disruption they enabled. Take a look at the fundamentals of what they do technically. It's interesting. It's somewhat impressive, but it's not revolutionary. What made them revolutionary is digitizing the transportation relationship you and I have with our transportation providers. And when they tapped into that they realized the potential for that is limitless right now. 'Cause we're all physical beings, we still have to move ourselves and our food, our packages around. But digitizing transportation is really you know a great example of any industry. Whether it's a 100-year-old industry or a brand new industry when you digitize the distribution, and when you actually add digital efficiencies in the back end, you end up with that 100 x effect, more than a 10 x effect. And truly earned the term disruptor. >> Give us more examples that you've seen. I know you talk a lot of Telco's but what other use cases. Because the whole notion of 5G and this new architecture is really coming down to use cases. And certainly the sexy ones. The car, the smart cities, I mean there's a lot of policy, societal impact issues that need to be thought through. But just generally, what's the low-hanging fruit right now? >> You know instead of low-hanging fruit let me give you the most pedestrian example I can think of. Which is when I meet with some of the waste management companies years ago I took them for granted. There was no innovation here. It's going to be an old enterprise discussion with some conservative tech leaders. I'm not even going to, I'm not trying to phone this is. I show up to meet with them, and they were truly innovating because they realized the whole customer experience of putting out your trash bin, your recycle bin, your organics bin, and so forth, your compost bin, can actually be improved. And the efficiencies added when you put GPS trackers on all the trucks. When you figure out when they have to go to the dump because there's an inordinately high amount of garbage put out early in the route one morning. And the ability for you to know when your bins are picked up. So you can actually go and pick up those bins. Put them out minutes before instead of the night before. Bring them back minutes after. Just reinventing that very pedestrian mundane experience tells me that there are opportunities for innovation everywhere in our lives. >> So really pick a spot to make efficient. Is probably easiest. Great, great feedback. Thoughts on developers. 'Cause it's something that we didn't, and we'd love to bring you back for more time on this but the CNC the Cloud Native Compute Foundation which is now part of the Linux Foundation, you mentioned microservices, orchestrations, there's a lot of software around composability, whether that's an artisan light developer, or the hardcore developers down lower on the stack. How does autonomous vehicles and this new future use case whether it's programming drones or writing cool software, to what's going on in the developer community? Can you share any color on trends around what's being done in traditional classic developing? >> Autonomous vehicles is already a perfect example because CNCF fundamentally is about what we call Cloud native technologies and applications. In a typical Cloud native architecture is container packaged not VM packaged. And it's dynamically orchestrated. So we say it's basically declarative as opposed to opinionated to use back end speak technical developer speak. But what does that mean? Autonomous cars are not interesting if one car is autonomous. Autonomous cars are interesting when dozens, hundreds, perhaps thousands of cars along your route those are autonomous. The interaction between them, and making sure they don't all try to occupy the same space at the same time. That's pretty essential. But also keeping traffic flowing smoothly and preventing unnecessary traffic jams. So it's the coordination of multiple processes, multiple things. That's what really make Cloud native computing happen at scale. So CNCF actually is five projects right now. Most people know it as the Kubernetes project and it is very much that. I think a year ago no one knew how hot Kubernetes would be but certainly it's taken off right now. Thanks a lot in part to Google. We've got new technologies around monitoring. So you've got a monitor your app obviously in the Cloud world to see what are the efficiencies performances for the end user. Around logging, distributed logging and monitoring. We've got new projects around actually debugging at scale. So debugging one process is simple as any developer knows. Debugging multiple concurrent threads or processes, that's still a black art. And so we've got open tracing technologies around that, and there's a new style of project, something known as link or d. But it's around now and the IoT context the most important thing to me discovery of context. What other devices, what other sensors are out there. >> It sounds like an operating system to me. You got linkers, you got loaders, you got all this orchestration. This is a global operating environment. >> It's a great insight. It's not an operating system. >> Not in like a classic sense. But there's some systems... >> It is a new operating environment. In the Cloud native world, operating system still connotates one PC, one device or one host on a data center. It really is a coordination of services. New modern high-end services. >> And declarative thing with containers is essentially assembly based, you can manage things component-wise, those kinds of concepts. And you see that as a key part of enabling these new use cases. >> There's actually no economies of scale if you don't go Cloud native nowadays. As 5G networks become more prevalent, as IoT becomes more mainstream, it doesn't play without microservice. >> And the trade-offs for not being Cloud native is what? >> Being disrupted. It's literally you know there's some great recent blogs. You've heard this title before, the coming SaaSpocalypse. So the disruption of the legacy SaaS vendors. The economics of them force you to basically have fixed subscription models with your customers. And whether you're using you know your CRM map once a day or 100 times a day. It costs you the same. These new Cloud native architectures are going to enable disruption in an industry because they only consume resources as a sessions for an app and the licensing and business model can now be that much more efficient. People are actually willing to be charged per use as opposed to per subscription. >> Now you know, I've gotten to know you over the years, and a great guest to have on The Cube. Thanks for sharing that insight. But it is an exciting time. You had a great run at NetApp. I mean you look at what NetApp's been doing, I mean they were the darling of Silicon Valley. Classic success story. Multiple reinventions, great founding team, great investors, just a classic run that they've had. As you look back now going forward, looking back and now looking forward, what are some of the things that get you jazzed up right now in terms of things that are that next wave that's coming. What do you see that's exciting and what would you share for folks for insight? >> I'd say the most exciting thing to me at a high level is the opportunity that 5G IoT enables. I think there's a whole new market segment. Some people might call it the real evolution of HCI. Which is edge computing, and all these really fast workloads. That are not going to be necessarily virtual desktops in terms of running or operating your business. But entirely new revenue streams, entirely new services, and all sorts of companies, digital or analog can offer. That excites me. And of course we've talked about the back end of the shift towards away from fast storage. Fast storage toward persistent memory. That in itself is going to open up a whole new category of apps that we've yet to see. >> Yeah we got to get that Linux rewritten and opened up. All kinds of new stuff. Great great commentary Val. Thanks for coming on The Cube to share. We certainly want to have you back. And really unpack and drill down and double down on what Cloud native impact means, and certainly edge and IoT computing. Really is going to be a fascinating run I think. I think that's going to open up a huge can of worms and an opportunity for really changing the game and creating great value and risk too. I mean Amazon S3's down as we speak. We're joking but you know we see insecurity problems out there and we'll stay on top of it. Of course The Cube has got you covered. And that's the hot themes really that's not being reported about Mobile World Congress that we're reporting. Which is the surge in IoT relevance. But that gives a mental model. This is the story of Mobile World Congress. 5G as a fabric connecting in with hard enterprise data center-like technologies. End to end for dynamic experiences. This is the challenge for Telcos. And someone will get it done. Let's see who it will be. Of course we'll be watching it. This is The Cube with more coverage of Mobile World Congress after this short break.

>> Announcer: Live from San Francisco, it's theCube. Covering DevNet Create 2017, brought to you by Cisco. >> Hey welcome back everyone. Live here in San Francisco, exclusive coverage with theCube at Cisco's inaugural DevNet Create event. I'm John Furrier with my co-host Peter Burris. We're breaking down the new foray into the open source world with a big presence. Cisco expanding their DevNet core developer classic program and creating an open source model with collaboration, 90% of that activity is non-Cisco, really a good formula. And to help us this down is Krish Subramanian, Principal Analyst at Rishidot Research, formerly of Red Hat, formerly of a start up that was recently sold. Can't talk about it because it's not released yet. Friend of theCube, Cube alumni, part of the Clouderati, going way back. Krish, we've seen a lot of the waves of how cloud has evolved from the early days. I remember when EngineYard was a startup, Haruku was a couple guys, we were having our meetups. >> And the AWS was still like people who weren't able to make money. >> They were poo-pooing the hell out of it. It was EC2 and S3 with a couple different, I mean RightScale did everything back then, so think about the changes. And now Cisco here with the formula, they have the right formula, I got to give them props for that, doing it right. They're not trying to come in and do a land grab and sort of, "Ahh, we're Cisco", throwing their elbows around. Really doing it right, your thoughts? >> Yeah, definitely, come back to what some other legacy companies tried to do. Cisco didn't try to jump in and say, "Hey, we are going to run public cloud, compete with Amazon", and sort of take them down. They sort of waited for right moment, they initially started with the InterCloud, which will go much further, but when IoT came into picture, they were there right for that and they were there taking advantage of that. And with the increasing focus on developers, they are going right to capture the minds of developers. Especially for IoT, that is critical for Cisco to go-- >> Well, I'm really glad you're on with Peter. We have two analysts here who know the industry up and down, from every dimension. Of course, I'll add my color, but I want to ask both of you guys a couple questions. One, do you think Cisco's making the right moves by coming out and really focusing on their core competency, which is the network? They also bought AppDynamics, so that is a big purchase. So, you got apps meets infrastructure, programmable infrastructure, which means infrastructure as code. You really can't have infrastructure as code unless Cisco gets behind it, they're the leader. So, with IoT looming, this seems like a good move for Cisco. What do you think? >> Yeah, definitely, they are going in the right direction, so it's really like IoT's still in the early stages and we have to wait and see how it is going to evolve, but Cisco is very persistent. Especially I like the AppDynamics acquisition because they are clearly telling the world that we understand that applications are the future and developers need the right tools if they are to develop their apps on Cisco infrastructure. And with the emphasis on programmability, Cisco is taking right steps towards capturing developer attention and I hope with successful events like this, they will be able to get there. >> Peter, I want to go to you for a second because we just found out, in talking to Suzy, I did not know this, but in your previous life, when you ran research at META Group, folks may not know what that was, it was a big research firm at the time, you did some really similar work around the infrastructure developer. >> Yeah >> Okay, and our comment was, "What is old is now new". I got a degree in operating systems and computer science and that seems to be the model. What is this notion of an infrastructure developer? It was mentioned in the keynote today. Does that exist in this new scenario? Do you see it being viable? It seems like the messaging is tight. What is your reaction to this notion? You've done a lot of work on that. >> Well, as a way of answering the question John, and I'll play off of something you just said, when we talk about the degree with which this is relevant to Cisco, here's what I say. Everybody's always looking for what is it that's different from today, relative to yesterday? And there's a lot of things that are different. One of the most important ones is that yesterday's computing industry emphasized a priority set of models about how you do things. So, if you thought about the network, the network had a modeled structure. You sat there and you designed a network to be as relevant to as many things as possible. Same with the database. You sat there and you designed the database to be as relevant to whatever notion of applications. When we start talking about the new world, now what we're discovering is the data is going to force a reconfiguration. That's what big data is. In many respects, it's non-structured, non-modeled data, but we still want to do analytics. Same thing with the network. We want the network to evolve and emerge, have emerging characteristics that allow us to do things that we never really anticipated when we first put this stuff down. And so, the thing that an infrastructure developer, at least as we conceived it, and we were way ahead and probably wrong for that reason, but the way we conceive it is someone has to take some degree of responsibility for starting to characterize, fill that gap, characterize the services in the infrastructure that need to be made available to application developers in a way that makes coherent and consistent sense so that an application written to an infrastructure, in fact, may become a service to another application at some point in time in the future, because they make consistent assumptions about where they operate within that margin between the application and the infrastructure. >> John: Does that environment exist today, in your opinion? >> It does in certain places. It does in certain places. I think the whole notion of containers is making, in Kubernetes for example, is making some very powerful presumptions about how applications are going to interact with each other in the future. Now, we had SOA, but we also talked about Conway's law, it just never happened because the structure of the organizations that were using SOA just guaranteed you end up with monolithic, crap applications anyway. >> Explain Conway's law real quick for people who didn't-- >> Yeah, Conway's law is, it's been mentioned in theCube a couple times, basically, it's a suggestion that the structure of the application is a reflection of the structure of the organization that created it. And so, if you have a silo-based application development organization that's looking at the application for the finance group, or the marketing group, you are going to get a structured, siloed-oriented application, no matter what underlying technology you use. And that's been that way forever. >> And so, Krish, I want to get your thoughts because let's take that to the next level. So, one of the benefits of cloud was horizontally scalable model. That really kind of, to me, was the big ah-ha moment around software. And with DevOps, which is now called cloud native, which is the same thing, infrastructures code was, hey, I'm not not an infrastructure person. I just want it to be available for me and help me configure it out and programmable, as Suzy was saying. Okay, so if you take what Peter's saying about data, you've lived through the infrastructure as a service, platform as a service, SAS wars or evolution, however you want to look at it. And, now you see that kind of coalescing into SAS and infrastructure and PAS kind of folding away and kind of becoming less of a contentious conversation. But, now that same thing's happening with data, we believe. I mean I think, maybe he may disagree, but now data's now the new data layer. What's your thoughts on that? Because now, if you inject data into what was the old cloud stack, new things are really possible. >> Yeah, the thing is, data brings in a new dimensionality to what we are seeing right now. Everything from infrastructure to application, everything requires a mindset change in terms of seeing them as services. So, even if it is a physical hardware you are dealing with, you have to make it more service-like by putting an API in front of it. So, it's changing the way how we consume these services. But, data is the one that is bringing business value to customers. When you make data easily, sort of like, inter operate with the services, let's say call it, for lack of a better term, a services ocean kind of IT model you have in your enterprise. So, when you offer to bring data into it, it offers you a lot of opportunities which didn't exist in the past. It opens up new avenues in which you could manipulate data, make sense out of it and probably get more value than what you were getting in the past. >> What's interesting, if you bring micro services, if you think about Docker and Kubernetes, as you were saying, and you bring data now into the equation and the notion of microservices, you can apply all that microservices knowledge to data. That's what you were saying, from what I hear. Or concepts of-- >> Sort of like you will bring data close to take, earlier as Peter pointed out, data was in silos, representative of the organizational structure. So, by taking a more services approach and spreading the services across these siloed, PAS, siloed organization, you are bringing the entire organization into one single umbrella, sharing the data and thereby benefiting much more than what they were getting in the past. >> So John, in the opening, one of the things we talked about, and I'll repeat it here because he's probably going to see it and I'd love to hear your comments on it, is that we went to hardware-defined networking. And then we went to software-defined networking. And, Wikibon's working on a proposition and I'm sure we'll find reasons why it's not going to play out, but again, I'd like to hear your position, is what I'll call data-defined infrastructure. So, we were on theCube last week at Informatica and we heard a lot about the role that metadata's going to play in discovery of data resources and whatnot. I can imagine adding metadata when we start talking about dependencies and time and location and things that are relevant to how a network or how an infrastructure might configure itself to serve the data, becoming a feature of the programmability of the underlying infrastructure so that we end up, in five years, we do talk about data-defined infrastructure. Just as today, we're talking about software-defined infrastructure, where the infrastructure, literally, responds to the needs of the data because that, ultimately, is the most flexible way of think about this. What do you think? >> Yeah, I fully agree with you. In fact, data brings in a new dimensionality to the equation where applications, it's a morph based on what is there in the data. So, on-the-fly, the infrastructure needs to be modified. So, data sort of brings in a new way of doing infrastructure from what we have done in the past. I fully agree with the role of data in that and how, through the application, that influences how we deal with infrastructure. It does change completely. >> All right, so I got to ask you guys a question. Journeys, is journey to DevOps, journey to digital transformation, certainly has a lot of cloud, has a lot of open source involved with it. We're seeing the Ford CEO get fired, he hasn't been on the job for four years, right? So, you guys both work with end users and advise them, so what's your advise to CXOs where, hey the clock now is, I thought four years was short. It really should be seven to 10 on the transformation scale, but people are getting axed in their third year, so they got to show results. How does an executive make all this stuff happen in such a short time? Or should they just reset expectations? >> When the executive comes in, he, or she, not only should look at their core business, they should also think that they are a technology business and change the mindset completely. That mindset change needs a push from the top that's going to accelerate the change down the lane and I think the executive should think that they are becoming a CEO, or CXO, of a technology company, rather than a manufacturing company or a automobile company kind of thing. >> I think that's true, but look, we haven't studied what happened at Ford in detail because I'm sure there's some subtleties in there that we just don't fully understand, but on the surface, it sounds like he might have gotten a little bit of a raw deal, just from the pure standpoint of-- >> Well the stock was down 39%, so my guess is total Wall Street hatchet job, but -- >> Peter: Exactly. >> We don't know a lot of the politics, but Val Bercovici, who was on earlier, who has a lot of experience in organizations that net app since 97, or late 90s, brought an interesting point, you were saying earlier. Tesla creates a car that's a service. And so, to me, I hate to use the cliche, "Everything as a service", but essentially, that's what software's going to. So, where you make up a day, that's why I'm kind of poking at the data thing because I think you're on to som-- >> But it's the end of the day, Tesla still has to have a shop that bends metal, there's still some car manufacturing things that have to happen. And, in many respects, whether the old CEO is saying, well the value proposition is, someday this autonomous vehicle is going to happen, but right now, we still got to build cars that can compete in the world market. There's a lot of subtleties here. There are-- >> Yeah, but Tesla does upgrade with software over the network. >> For an 80 to $100,000 price point and there's about four billion people that are going to buy cars in the next five years that may, or may not, be able to buy a 80,000 to $100,000 car. So anyway, coming back to your core point, I think what it really means is that if you're in a situation where you don't have visibility in a how, some of these new, digital approaches are going to create value for your business, you're doomed. So, I think the first thing you got to do is you got to be very explicit. This is how digital technology's going to create value for my business, that's number one. And, be able to articulate that to, virtually, anybody that's capable of understanding it, including Wall Street. But, to do that, you have to step back and say, and what is it about that digital technology that's going to create value for my business. And the thing that's going to do it, or not, is the data. >> And the asset configuration around, the work around the assets. >> Especially the asset configuration, as it's defined by the data. And, increasingly, there's an economics terms, what we're going to see happen over the next 10 years is the asset specificities are going to go down dramatically. In other words, the ability to which, or the degree to which an asset can only be configured to a specific purpose. Software's going to change that dynamic dramatically. And that, in many respects, is one of the fundamental, underlying things that's going on here. But, at the end of the day, you have to say, what role is data going to play in my business? How am I going to articulate that role by saying that I'm going to incorporate digital in this way? And then, put in place a plan that demonstrates that you're competent about some of these things. And, if your shareholders don't like it, they're not going to like it from anybody, not just you. >> Krish, I want to get your thoughts on the Cloud Native Compute Foundation. Why it's so successful. Why, in your opinion, do you think, there just booming with vendors, a lot of cash infusion, a lot of activity, projects went from one, three, 10. We had Dan on earlier, a lot of growth in the cloud native. And then, also, Kubernetes as a, kind of as an emerging, really interesting dynamic, vis-a-vis multicloud. So why cloud native is so popular and the impact of Kubernetes. >> Cloud native is popular because of late, developers are understanding that the role we are building applications is not going to work in cloud. When containers came into picture, that really made it easy for developers to develop cloud native apps. It got them to take advantage of the more distributed nature of the underlying infrastructure. So, the containers are the main reason why cloud native has become the household term, even in the enterprises. That could be one of the reason why Cloud Native Foundation is popular. Because they came at the right time to host all these development projects and evangelize with the developers and take steps in that. As far as Kubernetes is concerned, it worked at Google's CE. If it can work at Google's CE and then solve Google's problem, it should be able to help-- >> If it's good for Google, it's good for me. That's their strategy. >> And also, people are slowly realizing that as more and more enterprises go to cloud, they are realizing that going with a single cloud provider may not solve all their problems because different cloud providers have different set of services. So, they want to take advantage of all that. But, they want a single pane of glass to manage everything. Kubernetes is this general to be that at the cloud-- >> Krish, thanks for coming on. Peter, thanks for the comments, I'll just wrap up the analyst segment by saying, in my opinion, I think Cisco's making a good move here because, to your point about Google and Kubernetes is, and that's one of many examples of great software being contributed to open source. And open source, for all the times I've been involved with it since I was in college, is this more great software coming to the table now than ever before and that's creating great innovation. So, combined with the cloud and cloud native and Kubernetes, a perfect storm of innovation is coming. And it's coming, not from vendors, it's coming from open source. And, so the smart vendors are putting their toe in the water and really figuring it out. And again, the-- >> Peter: It is coming from vendor support though. >> Well the vendors are smart by putting their people in open source as a proxy for contribution. That's the open source model. That, to me, is the new R&D. It's a new innovation strategy, coupled with some proprietary R&D. Not saying they should be going all open source. >> I agree with it completely. In fact, I would even go one step further and say open source is completely disrupting the traditional enterprise software in modern business. Think about someone like Capital One putting critical software as open source and disrupting all the vendors in the space, so it's-- >> Well, let's continue the conversation in studio or tomorrow. Again, open source is horizontally scaling as well. Great stuff, great projects. More exclusive coverage from the inaugural event for Cisco's DevNet Create after this short break. (up-tempo music) >> Hi, I'm April Mitchell and I'm the senior director of strategy--

>> They are disruptive technologies. And if you think about the disruption that's happening in business, with IoT, with OT, and with big data, you can't get anything more disruptive to the whole of the business chain as this particular area. It's an area that I focused on myself, asking the question, should everything go to the cloud? Is that the new future? Is 90% of the computing going to go to the cloud with just little mobile devices right on the edge? Felt wrong when I did the math on it, I did some examples of real-world environments, wind farms, et cetera, it clearly was not the right answer, things need to be near the edge. And I think one of the areas to me that solidified it was when you looked at an area like video. Huge amounts of data, real important decisions being made on the content of that video, for example, recognizing a face, a white hat or a black hat. If you look at the technology, sending that data somewhere to do that recognition just does not make sense. Where is it going? It's going actually into the camera itself, right next to the data, because that's where you have the raw data, that's where you have the maximum granularity of data, that's where you need to do the processing of which faces are which, right close to the edge itself, and then you can send the other data back up to the cloud, for example, to improve those algorithms within that camera, to do all that sort of work on the batch basis over time, that's what I was looking at, and looking at the cost justification for doing that sort of work. So today, we've got a set people here on the panel, and we want to talk about coming down one level to where IoT and IT are going to have to connect together. So on the panel I've got, I'm going to get these names really wrong, Sanjeev Kumar? >> Yes, that's right. >> From FogHorn, could you introduce yourself and what you're doing where the data is meeting the people and the machines? >> Sure, sure, so my name is Sanjeev Kumar, I actually run engineering for a company called FogHorn Systems, we are actually bringing analytics and machine learning to the edge, and, so our goal and motto is to take computing to where the data is, than the other way around. So it's a two-year-old company that started, was incubated in the hive, and we are in the process of getting our second release of the product out shortly. >> Excellent, so let me start at the other end, Rohan, can you talk about your company and what contribution you're focusing on? >> Sure, I'm head product marketing for Maana, Maana is a startup, about three years old, what we're doing is we're offering an enterprise platform for large enterprises, we're helping the likes of Shell and Maersk and Chevron digitally transform, and that simply means putting the focus on subject matter experts, putting the focus on the people, and data's definitely an important part of it, but allowing them to bring their expertise into the decision flows, so that ultimately the key decisions that are driving the revenue for these behemoths, are made at a higher quality and faster. >> Excellent. Well, two software companies, we have a practitioner here who is actually doing fog computing, doing it for real, has been doing it for some time, so could you like, Janet George from Western Digital, can you introduce yourself, and say something from the trenches, of what's really going on? >> Okay, very good, thank you. I actually build infrastructure for the edge to deal with fog computing, and so for Western Digital, we're very lucky, because we are the largest storage manufacture, and we have what we call Internet of Things, and Internet of Test Equipment, and I process petabytes of data that comes out of the Internet of Things, which is basically our factories, and then I take these petabytes of data, I process them both on the cloud and then on the edge, but primarily, to be able to consume that data. And the way we consume that data is by building very high-profile models through artificial intelligence and machine learning, and I'll talk a lot more about that, but at the end of the day, it's all about consuming the data that you collect from anywhere, Internet of Things, computer equipment, data that's being produced through products, you have to figure out a way to compute that, and the cloud has many advantages and many trade-offs, and so we're going to talk about the trade-offs, that's where the gap for computing comes into play. >> Excellent, thanks very much. And last but not least, we have Val, and I can never pronounce your surname. >> Bercovici. >> Thank you. (chuckling) You are in the midst of a transition yourself, so talk about where you have been and where you're going. >> For the better part of this century, I've been with NetApp, working at various functions, obviously enterprise storage, and around 2008, my developer instinct kind of fired up, and this thing called cloud became very interesting to me. So I became a self-anointed cloud czar at NetApp, and I ended up initiating a lot of our projects which we know today as the NetApp Data Fabric, that culminated about 18 months ago, in acquisition of SolidFire, and I'm now the acting CTO of SolidFire, but I plan to retire from the storage industry at the end of our fiscal year, at the end of April, and I'm spending a lot of time with particularly the Cloud Native Compute Foundation, that is, the opensource home of Google's Kubernetes Technology and about seven other related projects, we keep adding some almost every month, and I'm starting to lose track, and spending a lot of time on the data gravity challenge. It's a challenge in the cloud, it's a particularly new and interesting challenge at the edge, and I look forward to talking about that. >> Okay, and data gravity is absolutely key, isn't it, it's extremely expensive and extremely heavy to move around. >> And the best analogy is workloads are like electricity, they move fairly easily and lightly, data's like water, it's really hard to move, particularly large bodies around. >> Great. I want to start with one question though, just in the problem, the core problem, particularly in established industries, of how do we get change to work? In an IT shop, we have enough problems dealing with operations and development. In the industrial world, we have the IT and the OT, who look at each other with less than pleasure, and mainly disdain. How do we solve the people problem in trying to put together solutions? You must be right in the middle of it, would you like to start with that question? >> Absolutely, so we are 26 years old, probably more than that, but we have very old and new mix of manufacturing equipment, it's a storage industry, and in our storage industry, we are used to doing things a certain way. We have existing data, we have historical data, we have trend data, you can't get rid of what you already have. The goal is to make connectors such that you can move from where you're at to where you're going, and so you have to be able to take care of the shift that is happening in the market, so at the end of the day, if you look at five years from now, it's all going to be machine learning and AI, right? Agent technology's already here, it's proven, we can see, Siri is out here, we can see Alexa, we can see these agent technologies out there, so machine learning is a getting a lot of momentum, deep learning and neural networks, things like that. So we got to be able to look at that data and tap into our data, near realistically, very different, and the way to do that is really making these connections happen, tapping into old versus new. Like for example, if you look at storage, you have file storage, you have block storage, and then you have object storage, right? We've not really tapped into the field of object storage, and the reason is because if you are going to process one trillion objects like Amazon is doing right now with S3, you can't do it with the file system level storage or with the blog system level storage, you have to go to objects. Think Internet of Things. How many trillions of objects are going to come out of these Internet of Things? So one, you have to be positioned from an infrastructure standpoint. Two, you have to be positioned from a use case prototyping perspective, and three, you got to be able to scale that very rapidly, very quickly, and that's how change happens, change does not happen because you ask somebody to change their behavior, change happens when you show value, and people are so eager to get that value out of what you've shown them in real life, that they are so quick to adapt. >> That's an excellent-- >> If I could comment on that as well, which is, we just got through training a bunch of OT guys on our software, and two analogies that actually work very well, one is sort of, the operational people are very familiar with circuit diagrams, and so, and sort of, flow of things through essentially black boxes, you can think of these as something that has a bunch of inputs and has a bunch of outputs. So that's one thing that worked very well. The second thing that works very well is the PLC model, and there are direct analogies between PLC's and analytics, which people on the floor can actually relate to. So if you have software that's basically based on data streams and time, as a first-class citizen, the PLC model again works very well in terms of explaining the new software to the OT people. >> Excellent, okay, would you want to come in on that as well? >> Sure, I think a couple of points to add to what Janet said, I couldn't agree more in terms of the result, I think Maana did a few projects, a few pilots to convince customers of their value, and we typically focus very heavily on operationalizing the output, so we are very focused on making sure that there is some measurable value that comes out of it, and it's not until the end user started seeing that value that they were willing and open to adopt the newer methodologies. A second point to that is, a lot of the more recent techniques available to solve certain challenges, there are deep learning neural nets there's all sorts of sophisticated AI and machine learning algorithms that are out there, a lot of these are very sophisticated in their ability to deliver results, but not necessarily in the transparency of how you got that, and I think that's another thing that Maana's learning, is yes, we have this arsenal of fantastic algorithms to throw at problems, but we try to start with the simplest approach first, we don't unnecessarily try to brute force, because I think an enterprise, they are more than willing to have that transparency in how they're solving something, so if they're able to see how they were able to get to us, how the software was able to get to a certain conclusion, then they are a lot happier with that approach. >> Could you maybe just give one example, a real-world example, make it a little bit real? >> Right, absolutely, so we did a project for a very large organization for collections, they have a lot of outstanding capital locked up and customers not paying, it's a standard problem, you're going to find it in pretty much any industry, and so for that outstanding invoice, what we did was we went ahead and we worked with the subject matter experts, we looked at all the historical accounts receivable data, we took data from a lot of other sources, and we were able to come up with models to predict when certain customers are likely to pay, and when they should be contacted. Ultimately, what we wanted to give the collection agent were a list of customers to call. It was fairly straightforward, of course, the solution was not very, very easy, but at least on a holistic level, it made a lot of sense to us. When we went to the collection agents, many of them actually refused to use that approach, and this is part of change management in some sense, they were so used to doing things their way, they were so used to trying to target the customers with the largest outstanding invoice, or the ones that hadn't paid for the longest amount of time, that it actually took us a while, because initially, what the feedback we got was that your approach is not working, we're not seeing the results. And when we dug into it, it was because it wasn't being used, so that would be one example. >> So again, proof points that you will actually get results from this. >> Absolutely, and the transparency, I think we actually sent some of our engineers to work with the collections agents to help them understand what approach is it that we're taking, and we showed them that this is not magic, we're actually, instead of looking at the final dollar value, we're looking, we're calculating time value lost, so we are coming up with a metric that allows us to incorporate not just the outstanding amount, or the time that they haven't paid for, but a lot of other factors as well. >> Excellent, Val. >> When you asked that question, I immediately went to more of a nontechnical business side of my brain to answer it, so my experience over the years has been particularly during major industry transitions, I'm old enough to remember the mainframe to client server transition, and now client server to virtualization and cloud, and really, sales reps have that well-earned reputation of being coin-operated, though it's remarkable how much you can adjust compensation plans for pretty much anyone, in a capitalist environment, and the IT/OT divide, if you will, is pretty easy to solve from a business perspective when you take someone with an IT supporting the business mentality, and you compensate them on new revenue streams, new business, all of a sudden, the world perspective changes sometimes overnight, or certainly when that contract is signed. That's probably the number one thing you can do from a people perspective, is incent them and motivate them to focus on these new things, the technology is, particularly nowadays is evolving to support them for these new initiatives, but nothing motivates like the right compensation plan. >> Excellent, a great series of different viewpoints. So the second question I have again coming down a bit to this level, is how do we architect a solution? We heard you got to architect it, and you've got less, like this, it seems to me that that's pretty difficult to do ahead of where you're going, that in general, you take smaller steps, one step at a time, you solve one problem, you go on to the next. Am I right in that? If I am, how would you suggest the people go about this decision-making of putting architectures together, and if you think I'm wrong and you have a great new way of doing it, I'd love to hear about it. >> I can take a shorter route. So we have a number of customers that are trying to adopt, are going through a phased way of adopting our technology and products, and so it begins with first gathering of the data, and replaying it back, to build the first level of confidence, in the sense that the product is actually doing what you're expecting it to do. So that's more from monitoring administration standpoint. The second stage is you should begin to capture analytical logic into the project, where it can start doing prediction for you, so you go into, so from operational, you go into a predictive maintenance, predictive maintenance, predictive models standpoint. The third part is prescriptive, where you actually help create a machine learning model, now, it's still in flux in terms of where the model gets created, whether it's on the cloud, in a central fashion, or some sort of a, the right place, the right context in a multi-level hierarchical fog layer, and then, you sort of operationalize that as close to the data again as possible, so you go through this operational to predictive to prescriptive adoption of the technology, and that's how people actually build confidence in terms of adopting something new into, let's say, a manufacturing environment, or things that are pretty expensive, so I give you another example where you have the case of capacitors being built on a assembly line, manufacturing, and so how do you, can you look at data across different stations and manufacturing on a assembly line? And can you predict on the second station that it's going to fail on the eighth one? By that, what you're doing is you are actually reducing the scrap that's coming off of the assembly line. So, that's the kind of usage that you're going to in the second and third stage. >> Host: Excellent. Janet, do you want to go on? >> Yeah, I agree and I have a slightly different point of view also. I think architecture's very difficult, it's like Thomas Edison, he spent a lot of time creating negative knowledge to get to that positive knowledge, and so that's kind of the way it is in the trenches, we spend a lot of time trying to think through, the keyword that comes to mind is abstraction layers, because where we came from, everything was tightly coupled, and tightly coupled, computer and storage are tightly coupled, structured and unstructured data are tightly coupled, they're tightly coupled with the database, schema is tightly coupled, so now we are going into this world of everything being decoupled. In that, multiple things, multiple operating systems should be able to use your storage. Multiple models should be able to use your data. You cannot structure your data in any kind of way that is customized to one particular model. Many models have to run on that data on the fly, retrain itself, and then run again, so when you think about that, you think about what suits best to stay in the cloud, maybe large amounts of training data, schema that's already processed can stay on the cloud. Schema that is very dynamic, schema that is on the fly, that you need to read, and data that's coming at you from the Internet of Things that's changing, I call it heteroscedastic data, which is very statistical in nature, and highly variable in nature, you don't have time to sit there and create rows and columns and structure this data and put it into some sort of a structured set, you need to have a data lake, you need to have a stack on top of that data lake that can then adapt, create metadata, process that data and make it available for your models, so, and then over time, like I totally believe that now we're running into near realtime compute bottleneck, processing all this pattern processing for the different models and training sets, so we need a stack that we can quickly replace with GPUs, which is where the future is going, with pattern processing and machine learning, so your architecture has to be extremely flexible, high layers of abstraction, ability to train and grow and iterate. >> Excellent. Do you want to go next? >> So I'll be a broken record, back to data gravity, I think in an edge context, you really got to look at the cost of processing data is orders of magnitude less than moving it or even storing it, and so I think that the real urgency, I don't know, there's 90% that think of data at the edge is kind of wasted, you can filter through it and find that signal through the noise, so processing data to make sure that you're dealing with really good data at the edge first, figuring out what's worth retaining for future steps, I love the manufacturing example, I have lots of customer examples ourselves where, for quality control in a high-moving assembly line, you want to take thousands of not millions of images and compare frame and frame exactly according to the schematics where the device is compared to where it should be, or where the components, and the device compared to where they should be, processing all of that data locally and making sure you extract the maximum value before you move data to a central data lake to correlate it against other anomalies or other similarities, that's really key, so really focus on that cost of moving and storing data, yeah. >> Yes, do you want the last word? >> Sure, Maana takes an interesting approach, I'm going to up-level a little bit. Whenever we are faced with a customer or a particular problem for a customer, we try to go over the question-answer approach, so we start with taking a very specific business question, we don't look at what data sources are available, we don't ask them whether they have a data lake, or we literally get their business leaders, their subject matter experts, we literally lock them up in a room and we say, "You have to define "a very specific problem statement "from which we start working backwards," each problem statement can be then broken down into questions, and what we believe is any question can be answered by a series of models, you talked about models, we go beyond just data models, we believe anything in the real world, in the case of, let's say, manufacturing, since we're talking about it, any smallest component of a machine should be represented in the form of a concept, relationships between people operating that machinery should be represented in the form of models, and even physics equations that are going into predicting behavior should be able to represent in the form of a model, so ultimately, what that allows us is that granularity, that abstraction that you were talking about, that it shouldn't matter what the data source is, any model should be able to plug into any data source, or any more sophisticated bigger model, I'll give you an example of that, we started solving a problem of predictive maintenance for a very large customer, and while we were solving that predictive maintenance problem, we came up with a number of models to go ahead and solve that problem. We soon realized that within that enterprise, there are several related problems, for example, replacement of part inventory management, so now that you figured out which machine is going to fail at roughly what instance of time from now, we can also figure out what parts are likely to fail, so now you don't have to go ahead and order a ton of replacement parts, because you know what parts are going to likely fail, and then you can take that a step further by figuring out which equipment engineer has the skillset to go ahead and solve that particular issue. Now, all of that, in today's world, is somewhat happening in some companies, but it is actually a series of point solutions that are not talking to each other, that's where our pattern technology graph is coming into play where each and every model is actually a note on the graph including computational models, so once you build 10 models to solve that first problem, you can reuse some of them to solve the second and third, so it's a time-to-value advantage. >> Well, you've been a fantastic panel, I think these guys would like to get to a drink at the bar, and there's an opportunity to talk to you people, I think this conversation could go on for a long, long time, there's so much to learn and so much to share in this particular information. So with that, over to you! >> I'll just wrap it up real quick, thanks everyone, give the panel a hand, great job. Thanks for coming out, we have drinks for the next hour or two here, so feel free to network and mingle, great questions to ask them privately one-on-one, or just have a great conversation, and thanks for coming, we really appreciate it, for our Big Data SV Event livestreamed out, it'll be on demand on YouTube.com/siliconangle, all the video, if you want to go back, look at the presentations, go to YouTube.com/siliconangle, and of course, siliconangle.com, and Wikibond.com for the research and content coverage, so thanks for coming, one more time, big round of applause for the panel, enjoy your evening, thanks so much.

>> Narrator: Live from Silicon Valley, it's theCUBE, covering Google Cloud, Next 17. >> Hey, welcome back everyone. We're here live in the Palo Alto Studios, SiliconANGLE Media, is theCUBE's new 4400 square foot studio, here in our studio, this is our sports center. I'm here with Stu Miniman, analyst at Wikibon on the team. I was at the event all day today, drove down to Palo Alto to give us the latest in-person updates, as well as, for the past two days, Stu has been at the Analyst Summit, which is Google's first analyst summit, Google Cloud. And Stu, we're going to break down day one in the books. Certainly, people starting to get onto there. After-meetups, parties, dinners, and festivities. 10,000 people came to the Google Annual Cloud Next Conference. A lot of customer conversations, not a lot of technology announcements, Stu. But we got another day tomorrow. >> John, first of all, congrats on the studio here. I mean, it's really exciting. I remember the first time I met you in Palo Alto, there was the corner in ColoSpace-- >> Cloud Air. >> A couple towards down for fries, at the (mumbles) And look at this space. Gorgeous studio. Excited to be here. Happy to do a couple videos. And I'll be in here all day tomorrow, helping to break down. >> Well, Stu, first allows us to, one, do a lot more coverage. Obviously, Google Next, you saw, was literally a blockbuster, as Diane Greene said. People were around the block, lines to get in, mass hysteria, chaos. They really couldn't scale the event, which is Google's scale, they nailed the scale software, but scaling event, no room for theCUBE. But we're pumping out videos. We did, what? 13 today. We'll do a lot more tomorrow, and get more now. So you're going to be coming in as well. But also, we had on-the-ground, cause we had phone call-ins from Akash Agarwal from SAP. We had an exclusive video with Sam Yen, who was breaking down the SAP strategic announcement with Google Cloud. And of course, we have a post going on siliconangle.com. A lot of videos up on youtube.com/siliconangle. Great commentary. And really the goal was to continue our coverage, at SiliconANGLE, theCUBE, Wikibon, in the Cloud. Obviously, we've been covering the Cloud since it's really been around. I've been covering Google since it was founded. So we have a lot history, a lot of inside baseball, certainly here in Palo Alto, where Larry Page lives in the neighborhood, friends at Google Earth. So the utmost respect for Google. But really, I mean, come on. The story, you can't put lipstick on a pig. Amazon is crushing them. And there's just no debate about that. And people trying to put that out there, wrote a post this morning, to actually try to illustrate that point. You really can't compare Google Cloud to AWS, because it's just two different animals, Stu. And my point was, "Okay, you want to compare them? "Let's compare them." And we're well briefed on the Cloud players, and you guys have the studies coming out of Wikibon. So there it is. And my post pretty much sums up the truth, which is, Google's really serious about the enterprise. Their making steps, there's some holes, there's some potential fatal flaws in how they allow customers to park their data. They have some architectural differences. But Stu, it's really a different animal. I mean, it's apples and oranges in the Cloud. I don't think it's worthy complaining, because certainly Amazon has the lead. But you have Microsoft, you have Google, you have Oracle, IBM, SAP, they're all kind of in the cluster of this, I call "NASCAR Formation", where they're all kind of jocking around, some go ahead. And it really is a race to get the table stake features done. And really, truly be serious contender for the enterprise. So you can be serious about the enterprise, and say, "Hey, I'm serious about the enterprise." But to be serious winner and leader, are two different ball games. >> And a lot to kind of break down here, John. Because first of all, some of the (mumbles) challenges, absolutely, they scaled that event really big. And kudos to them, 10,000 people, a lot of these things came together last minute. They treated the press and analysts really well. We got to sit up front. They had some good sessions. You just tweeted out, Diane Greene, in the analyst session, and in the Q&A after, absolutely nailed it. I mean, she is an icon in the industry. She's brilliant, really impressive. And she's been pulling together a great team of people that understand the enterprise. But who is Google going after, and how do they compete against so of the other guys, is really interesting to parse. Because some people were saying in the keynote, "We heard more about G Suite "than we heard about some of the Cloud features." Some of that is because they're going to do the announcements tomorrow. And you keep hearing all this G Suite stuff, and it makes me think of Microsoft, not Amazon. It makes me think of Office 365. And we've been hearing out of Amazon recently, they're trying to go after some of those business productivity applications. They're trying to go there where Microsoft is embedded. We know everybody wants to go after companies like IBM and Oracle, and their applications. Because Google has some applications, but really, their strength is been on the data. The machine the AI stuff was really interesting. Dr. Fei-Fei Li from Stanford, really good piece in the keynote there, when they hired her not that long ago. The community really perked up, and is really interesting. And everybody seems to think that this could be the secret weapon for Google. I actually asked them like, in some of the one-on-ones, "Is this the entry point? "Are most people coming for this piece, "when it's around these data challenges in the analytics, "and coming to Google." And they're like, "Well, it's part of it. "But no, we have broad play." Everything from devices through G Suite. And last year, when they did the show, it was all the Cloud. And this year, it's kind of the full enterprise suite, that they're pulling in. So there's some of that sorting out the messaging, and how do you pull all of these pieces together? As you know, when you've got a portfolio, it's like, "Oh well, I got to have a customer for G Suite." And then when the customer's up there talking about G Suite for a while, it's like, "Wait, it's--" >> Wait a minute. Is this a software? >> "What's going on?" >> Is this a sash show? Is this a workplace productivity show? Or is this a Cloud show? Again, this is what my issue is. First of all, the insight is very clear. When you start seeing G Suite, that means that they've got something else that they are either hiding or waiting to announce. But the key though, that is the head customers. That was one important thing. I pointed out in my blog post. To me, when I'm looking for it's competitive wins, and I want to parse out the G Suite, because it's easy just to lay that on, Microsoft does it with 365 of Office, Oracle does it with their stuff. And it does kind of make the numbers fuzzy a little bit. But ultimately, where's the beef on infrastructure as a service, and platform as a service? >> And John, good customers out there, Disney, Colgate, SAP as a partner, HSBC, eBay, Home Depot, which was a big announcement with Pivotal, last year, and Verizon were there. So these are companies, we all know them. Dan Greene was joking, "Disney is going to bring their magic onto our magic. "And make that work." So real enterprise use cases. They seem to have some good push-around developers. They just acquired Kaggle, which is working in some of that space. >> Apogee. >> Yeah, Apogee-- >> I think Apogee's an API company, come on. What does that relate to? It has nothing to do with the enterprise. It's an API management solution. Okay, yes. I guess it fits the stack for Cloud-Native, and for developers. I get that. But this show has to nail the enterprise, Stu. >> And John, you remember back four years ago, when we went to the re:Invent show for the first time, and it was like, they're talking to all the developers, and they haven't gotten to the enterprise. And then they over-pivoted to enterprise. And I listen to the customers that were talking and keynote today, and I said, "You know, they're talking digital transformation, "but it's not like GE and Nike getting up on stage, "being like, "'We're going to be a software company, "'and we're hiring lots--'" >> John: Moving our data center over. >> They were pulling all of over stuff, and it's like, "Oh yeah, Google's a good partner. "And we're using them--" >> But to be fair, Stu. Let's be fair, for a second. First of all, let's break down the keynotes. And then we'll get to some of the things about being fair. And I think, one, people should be fair to Diane Greene, because I think that the press and the coverage of it, looking at the media coverage, is weak. And I'll tell you why it's weak. Cause everyone has the same story as, "Oh, Google's finally serious about Cloud. "That's old news. "Diane Greene from day one says "we're serious with the Cloud." That's not the story. The story is, can they be a serious contender? That's number one. On the keynote, one, customer traction, I saw that, the slide up there. Yeah, the G Suite in there, but at least they're talking customers. Number two, the SAP news was strategic for Google. SAP now has Google Cloud platform, I mean, Google Cloud support for HANA, and also the SAP Cloud platform. And three, the Chief Data Science from AIG pointed. To me, those were the three highlights of the keynote. Each one, thematically, represents at least a positive direction for Google, big time, which is, one, customer adoption, the customer focus. Two, partnerships with SAP, and they had Disney up there. And then three, the real game changer, which is, can they change the AI machine learning, TensorFlow has a ton of traction. Intel Xeon chips now are optimized with TensorFlow. This is Google. >> TensorFlow, Kubernetes, it's really interesting. And it's interesting, John, I think if the media listened to Eric Schmidt at the end, he was talking straight to them. He's like, "Look, bullet one. "17 years ago, I told Google that "this is where we need to go. "Bullet two, 30 billion dollars "I'm investing in infrastructure. "And yes, it's real, "cause I had to sign off on all of this money. And we've been all saying for a while, "Is this another beta from Google. "Is it serious? "There's no ad revenue, what is this?" And Diane Greene, in the Q&A afterwards, somebody talked about, "Perpetual beta seems to be Google." And she's like, "Look, I want to differentiate. "We are not the consumer business. "The consumer business might kill something. "They might change something. "We're positioning, "this a Cloud that the enterprise can build on. "We will not deprecate something. "We'll support today. "We'll support the old version. "We will support you going forward." Big push for channel, go-to-market service and support, because they understand that that-- >> Yeah, but that's weak. >> For those of us that used Google for years, understand that-- >> There's no support. >> "Where do I call for Google?" Come on, no. >> Yeah, but they're very weak on that. And we broke that down with Tom Kemp earlier, from Centrify, where Google's play is very weak on the sales and marketing side. Yeah, I get the service piece. But go to Diane Greene for a second, she is an incredible, savvy enterprise executive. She knows Cloud. She moved from server to virtualization. And now she can move virtualization to Cloud. That is her playbook. And I think she's well suited to do that. And I think anyone who rushes to judgment on her keynote, given the fail of the teleprompter, I think is a little bit overstepping their bounds on that. I think it's fair to say that, she knows what she's doing. But she can only go as fast as they can go. And that is, you can't like hope that you're further along. The reality is, it takes time. Security and data are the key points. On your point you just mentioned, that's interesting. Because now the war goes on. Okay, Kubernetes, the microservices, some of the things going on in the applications side, as trends like Serverless come on, Stu, where you're looking at the containerization trend that's now gone to Kubernetes. This is the battleground. This is the ground that we've been at Dockercon, we've been at Linux, CNCF has got huge traction, the Cloud Native Compute Foundation. This is key. Now, that being said. The marketplace never panned out, Stu. And I wanted to get your analysis on this, cause you cover this. Few years ago, the world was like, "Oh, I want to be like Facebook." We've heard, "the Uber of this, and the Airbnb of that." Here's the thing. Name one company that is the Facebook of their company. It's not happening. There is no other Facebook, and there is no other Google. So run like Google, is just a good idea in principle, horizontally scalable, having all the software. But no one is like Google. No one is like Facebook, in the enterprise. So I think that Google's got to downclock their messaging. I won't say dumb down, maybe I'll just say, slow it down a little bit for the enterprise, because they care about different things. They care more about SLA than pricing. They care more about data sovereignty than the most epic architecture for data. What's your analysis? >> John, some really good points there. So there's a lot of technology, where like, "This is really cool." And Google is the biggest of it. Remember that software-defined networking we spent years talking about? Well, the first big company we heard about was Google, and they got up of stage, "We're the largest SDN deployer in the world on that." And it's like, "Great. "So if you're the enterprise, "don't deploy SDN, go to somebody else "that can deliver it for you. "If that's Google, that's great." Dockercon, the first year they had, 2014, Google got up there, talked about how they were using containers, and containers, and they spin up and spin down. Two billion containers in a week. Now, nobody else needs to spin up two billion containers a week, and do that down. But they learned from that. They build Kubernetes-- >> Well, I think that's a good leadership position. But it's leadership position to show that you got the mojo, which again, this is again, what I like about Google's strategy is, they're going to play the technology card. I think that's a good card to play. But there are some just table stakes they got to nail. One is the certifications, the security, the data. But also, the sales motions. Going into the enterprise takes time. And our advice to Diane Greene was, "Don't screw the gold Google culture. "Keep that technology leadership. "And buy somebody, "buy a company that's got a full blown sales force." >> But John, one of the critiques of Google has always been, everything they create, they create like for Google, and it's too Googley. I talked to a couple of friends, that know about AWS for a while, and when they're trying to do Google, they're like, "Boy, this is a lot tougher. "It's not as easy as what we're doing." Google says that they want to do a lot of simplicity. You touched on pricing, it's like, "Oh, we're going to make pricing "so much easier than what Amazon's doing." Amazon Reserved Instances is something that I hear a lot of negative feedback in the community on, and Google's like, "It's much simpler." But when I've talked to some people that have been using it, it's like, "Well, generally it should be cheaper, "and it should be easier. "But it's not as predictable. "And therefore, it's not speaking to what "the CFO needs to have. "I can't be getting a rebate sometime down the road. "Based on some advanced math, "I need to know what I'm going to be getting, "and how I'm going to be using it." >> And that's a good point, Stu. And this comes down to the consumability of the Cloud. I think what Amazon has done well, and this came out of many interviews today, but it was highlighted by Val Bercovici, who pointed out that, Amazon has made their service consumable by the enterprise. I think that's important. Google needs to start thinking about how enterprises want to consume Cloud, and hit those points. The other thing that Val and I teased at, was kind of some new ground, and he coined the term, or used the term, maybe he coined it, I'm not sure, empathy. Enterprise empathy. Google has developer empathy, they understand the developer community. They're rock solid on open source. Obviously, their mojo's phenomenal on technology, AI, et cetera, TensorFlow, all that stuff's great. Empathy for the enterprise, not there. And I think that's something that they're going to have to work on. And again, that's just evolution. You mentioned Amazon, our first event, developer, developer, developer. Me and Pat Gelsinger once called it the developer Cloud. Now they're truly the enterprise Cloud. It took three years for Amazon to do that. So you just can't jump to a trajectory. There's a huge amount of diseconomies of scale, Stu, to try and just be an enterprise player overnight, because, "We're Google." That's just not going to fly. And whether it's sales motions, pricing and support, security, this is hard. >> And sorting out that go-to-market, is going to take years. You see a lot of the big SIs are there. PwC, everywhere at the show. Accenture, big push at the show. We saw that a year or two ago, at the Amazon show. I talked to some friends in the channel, and they're like, "Yeah, Google's still got work to do. "They're not there." Look, Amazon has work to do on the go-to-market, and Google is still a couple-- >> I mean, Amazon's not spring chicken here. They're quietly, slowly, ramming up. But they're not in a good position with their sales force, needs to be where they want to be. Let's talk about technology now. So tomorrow we're expecting to see a bunch of stuff. And one area that I'm super excited about with Google, is if they can have their identity identified, and solidified with the mind of the enterprise, make their product consumable, change or adjust or buy a sales force, that could go out and actually sell to the enterprise, that's going to be key. But you're going to hear some cool trends that I like. And if you look at the TensorFlow, and the relationship, Intel, we're going to see Intel on stage tomorrow, coming out during one of the keynotes. And you're going to start to see the Xeon chip come out. And now you're starting to see now, the silicon piece. And this has been a data center nuisance, Stu. As we talked about with James Hamilton at Amazon, which having a hardware being optimized for software, really is the key. And what Intel's doing with Xeon, and we talked to some other people today about it, is that the Cloud is like an operating system, it's a global computer, if you want look at that. It's a mainframe, the software mainframe, as it's been called. You want a diversity of chipsets, from two cores Atom to 72 cores Xeon. And have them being used in certain cases, whether it's programmable silicon, or whether it's GPUs, having these things in use case scenarios, where the chips can accelerate the software evolution, to me is going to be the key, state of the art innovation. I think if Intel continues to get that right, companies like Google are going to crush it. Now, Amazon, they do their own. So this is going to another interesting dynamic. >> Yeah, it was actually one of the differentiating points Google's saying, is like, "Hey, you can get the Intel Skylake chip, "on Google Cloud, "probably six months before you're going to be able to "just call up your favorite OEM of choice, "and get that in there." And it's an interesting move. Because we've been covering for years, John, Google does a ton of servers. And they don't just do Intel, they've been heavily involved in the openPOWER movement, they're looking at alternatives, they're looking at low power, they're looking at from their device standpoint. They understand how to develop to all these pieces. They actually gave to the influencers, the press, the analysts, just like at Amazon, we all walked home with Echo Dot, everybody's walking home with the Google Homes. >> John: Did you get one? >> I did get one, disclaimer. Yeah, I got one. I'll be playing with it home. I figured I could have Alexa and Google talking to each other. >> Is it an evaluation unit? You have to give it back, or do you get to keep? >> No, I'm pretty sure they just let us keep that. >> John: Tainted. >> But what I'm interested to see, John, is we talk like Serverless, so I saw a ton of companies that were playing with Alexa at re:Invent, and they've been creating tons of skills. Lambda currently has the leadership out there. Google leverages Serverless in a lot of their architecture, it's what drives a lot of their analytics on the inside. Coming into the show, Google Cloud Functions is alpha. So we expect them to move that forward, but we will see with the announcements come tomorrow. But you would think if they're, try to stay that leadership though there, I actually got a statement from one of the guys that work on the Serverless, and Google believes that for functions, that whole Serverless, to really go where it needs to be, it needs to be open. Google isn't open sourcing anything this week, as far as I know. But they want to be able to move forward-- >> And they're doing great at open source. And I think one of the things, that not to rush to judgment on Google, and no one should, by the way. I mean, certainly, we put out our analysis, and we stick by that, because we know the enterprise pretty well, very well actually. So the thing that I like is that there are new use cases coming out. And we had someone who came on theCUBE here, Tarun Thakur, who's with Datos, datos.io. They're reimagining data backup and recovery in the Cloud. And when you factor in IoT, this is a paradigm shift. So I think we're going to see use cases, and this is a Google opportunity, where they can actually move the goal post a bit on the market, by enabling these no-use cases, whether it's something as, what might seem pedestrian, like backup and recovery, reimagining that is huge. That's going to take impact as the data domains of the world, and what not, that (mumbles). These new uses cases are going to evolve. And so I'm excited by that. But the key thing that came out of this, Stu, and this is where I want to get your reaction on is, Multicloud. Clearly the messaging in the industry, over the course of events that we've been covering, and highlighted today on Google Next is, Multicloud is the world we are living in. Now, you can argue that we're all in Amazon's world, but as we start developing, you're starting to see the emergence of Cloud services providers. Cloud services providers are going to have some tiering, certainly the big ones, and then you're going to have secondary partner like service providers. And Google putting G Suite in the mix, and Office 365 from Microsoft, and Oracle put in their apps in their Clouds stuff, highlights that the SaaS market is going to be very relevant. If that's the case, then why aren't we putting Salesforce in there, Adobe? They all got Clouds too. So if you believe that there's going to be specialism around Clouds, that opens up the notion that there'll be a series of Multicloud architectures. So, Stu-- >> Stu: Yeah so, I mean, John, first of all-- >> BS? Real? I mean what's going on? >> Cloud is this big broad term. From Wikibon's research standpoint, SaaS, today, is two-thirds of the public Cloud market. We spend a lot of time talking-- >> In revenue? >> In revenue. Revenue standpoint. So, absolutely, Salesforce, Oracle, Infor, Microsoft, all up there, big dollars. If we look at the much smaller part of the world, that infrastructures a service, that's where we're spending a lot of time-- >> And platforms a service, which Gartner kind of bundles in, that's how Gartner looks at it. >> It's interesting. This year, we're saying PaaS as a category goes away. It's either SaaS plus, I'm sorry, it's SaaS minus, or infrastructure plus. So look at what Salesforce did with Heroku. Look at what company service now are doing. Yes, there are solutions-- >> Why is PaaS going away? What's the thesis? What's the premise of that for Wikibon research? >> If we look at what PaaS, the idea was it tied to languages, things like portability. There are other tools and solutions that are going to be able to help there. Look at, Docker came out of a PaaS company, DockCloud. There's a really good article from one of the Docker guys talking about the history of this, and you and I are going to be at Dockercon. John, from what I hear, we're going to spending a lot of time talking about Kubernetes, at Dockercon. OpenStack Summit is going to be talking a lot about-- >> By the way, Kubernetes originated at Google. Another cool thing from Google. >> All right, so the PaaS as a market, even if you talk to the Cloud Foundry people, the OpenShift people. The term we got, had a year ago was PaaS is Passe, the nice piffy line. So it really feeds into, because, just some of these categorizations are what we, as industry watchers have a put in there, when you talk to Google, it's like, "Well, why are they talking about G Suite, "and Google Cloud, and even some of their pieces?" They're like, "Well, this is our bundle "that we put together." When you talk to Microsoft, and talk about Cloud, it's like, "Oh, well." They're including Skype in that. They're including Office 365. I'm like, "Well, that's our productivity. "That's a part of our overall solutions." Amazon, even when you talk to Amazon, it's not like that there are two separate companies. There's not AWS and Amazon, it's one company-- >> Are we living in a world of alternative facts, Stu? I mean, Larry Ellison coined the term "Fake Cloud", talking about Salesforce. I'm not going to say Google's a fake Cloud, cause certainly it's not. But when you start blending in these numbers, it's kind of shifting the narrative to having alternative facts, certainly skewing the revenue numbers. To your point, if PaaS goes away because the SaaS minuses that lower down the stack. Cause if you have microservices and orchestration, it kind of thins that out. So one, is that the case? And then I saw your tweet with Sam Ramji, he formally ran Cloud Foundry, he's now at Google, knows his stuff, ex-Microsoft guy, very strong dude. What's he take? What's his take on this? Did you get a chance to chat with Sam at all? >> Yeah, I mean, it was interesting, because Sam, right, coming from Cloud Foundry said, what Cloud Foundry was one of the things they were trying to do, was to really standardize across the clouds. And of course, little bias that he works at Google now. But he's like, "We couldn't do that with Google, "cause Google had really cool features. And of course, when you put an abstraction layer on, can I actually do all the stuff? And he's like, "We couldn't do that." Sure, if you talked to Amazon, they'll be like, "Come on. "Thousand features we announced last year, "look at all the things we have. "It's not like you can just take all of our pieces, "and use it there." Yes, at the VM, or container, or application microservices layer, we can sit on a lot of different Clouds, public or private. But as we said today, the Cloud is not a utility. John, you've been in this discussion for years. So we've talked about, "Oh, I'm just going "to have a Cloud broker, "and go out in a service." It's like, this is not, I'm not buying from Domino's and Pizza Hut, and it's pepperoni pizza's a pepperoni pizza. >> Well, Multicloud, and moving workloads across Clouds, is a different challenge. Certainly, I might have to some stuff here, maybe put some data and edge my bets on leveraging other services. But this brings up the total cost of ownership problem. If you look at the trajectory, say OpenStack, just as a random example. OpenStack, at one point, had a great promise. Now it's kind of niched down into infrastructural service. I know you're going to be covering that summit in Boston. And it's going to be interesting to see how that is. But the word in the community is, that OpenStack is struggling because of the employment challenges involved with it. So to me, Google has an opportunity to avoid that OpenStack kind of concept. Because, talking about Sam Ramji, open source is the wildcard in all of this. So if you look at a open source, and you believe that that PaaS layer's thinning down, to infrastructure and SaaS, then you got to look at the open source community, and that's going to be a key area, that we're certainly watching, and we've identified, and we've mentioned it before. But here's my point. If you look at the total cost of ownership. If I'm a customer, Stu, I'm like, "Okay, if I'm just going to move to the Cloud, "I need to rely and lean on my partner, "my vendor, my supplier, "Amazon, or Google, or Microsoft, whoever, "to provide really excellent manageability. "Really excellent security. "Because if I don't, I have to build it myself." So it's becoming the shark fin, the tip of the iceberg, that you don't see the hidden cost, because I would much rather have more confidence in manageability that I can control. But I don't want to have to spend resources building manageability software, if the stuff doesn't work. So there's the issue about Multicloud that I'm watching. Your thoughts? Or is that too nuance? >> No, no. First of all, one of the things is that if I look at what I was doing on premises, before versus public Cloud, yes, there are some hidden costs, but in general I think we understand them a little bit better in public Cloud. And public Cloud gives us a chance to do a do-over for this like security, which most of us understand that security is good in public Cloud. Now, security overall, lots of work to do, challenges, not security isn't the same across all of them. We've talked to plenty of companies that are helping to give security across Clouds. But this Multicloud discussion is still something that is sorting out. Portability is not simple, but it's where we're going. Today, most companies, if I'm not really small, have some on-prem pieces. And they're leveraging at least one Cloud. They're usually using many SaaS providers. And there's this whole giant ecosystem, John, around the Cloud management platforms. Because managing across lots of environment, is definitely a challenge. There's so many companies that are trying to solve them. And there's just dozens and dozens of these companies, attacking everything from licensing, to the data management, to everything else. So there's a lot of challenges there, especially the larger you get as a company, the more things you need to worry about. >> So Stu, just to wrap up our segment. Great day. Wanted to just get some color on the day. And highlighting some parody from the web is always great. Just got a tweet from fake Andy Jassy, which we know really isn't Andy Jassy. But Cloud Opinion was very active to the hashtag, that Twitter handle Cloud Opinion. But he had a medium post, and he said, "Eric Schmidt was boring. "Diane Greene was horrible. "Unfortunately, day one keynote were missed opportunity, "that left several gaps, "failed to portray Google's vision for Google Cloud. "They could've done the following, A, "explain the vision for the Cloud, "where do they see Google Cloud going. "Identify customer use cases that show samples "and customer adoption." They kind of did that. So discount that. My favorite line is this one, "Differentiate from other Cloud providers. "'We're Google damn it,' isn't working so well. "Neither is indirect shots as S3 downtime, "didn't work either as well as either. "Where is the customer's journey going? "And what's the most compelling thing for customers?" This phrase, "We're Google damn it," has kind of speaks to the arrogance of Google. And we've seen this before, and always say, Google doesn't have a bad arrogance. I like the Google mojo. I think the technology, they run hard. But they can sometimes, like, "Customer support, self-service." You can't really get someone on the phone. It's hard to replies from Google. >> "Check out YouTube video. "We own that too, don't you know that?" >> So this is a perception of Google. This could fly in the face, and that arrogance might blow up in the enterprise, cause the enterprises aren't that sophisticated to kind of recognize the mojo from Google. And they, "Hey, I want support. "I want SLAs. "I want security. "I want data flexibility." What's your thoughts? >> So Cloud Opinion wrote, I thought a really thoughtful piece leading up to it, that I didn't think was satire. Some of what he's putting in there, is definitely satire-- >> John: Some of it's kind of true though. >> From the keynote. So I did not get a sense in the meetings I've been in, or watching the keynote, that they were arrogant. They're growing. They're learning. They're working with the community. They're reaching out. They're doing all the things we think they need to do. They're listening really well. So, yes, I think the keynote was a missed opportunity overall. >> John: But we've got to give, point out that was a teleprompter fail. >> That was a piece of it. But even, we felt with a little bit of polish, some of the interactions would've been a little bit smoother. I thought Eric Schmidt's piece was really good at end. As I said before, the AI discussion was enlightening, and really solid. So I don't give it a glowing rating, but I'm not ready to trash it. And tomorrow is when they're going to have the announcements. And overall, there's good buzz going at the show. There's lots going on. >> Give 'em a letter. Letter grade. >> For the keynote? Or the show in general? >> So far, your experience as an analyst, cause you had the, again, to give them credit, I agree with you. First analyst conference. They are listening. And the slideshow, you see what they're doing. They're being humble. They didn't take any real direct shots at its competitors. They were really humble. >> And that is something that I think they could've helped to focus one something that differentiated a little bit. Something we had to pry out of them in some of the one-on-ones, is like, "Come on, what are you doing?" And they're like, "We're winning 50, 60% of our competitive deals." And I'm like, "Explain to us why. "Because we're not hearing it. "You're not articulating it as well." It's not like we expect them, it's like, "Oh wait, they told us we're arrogant. "Maybe we should be super humble now." It's kind of-- >> I don't think they're thinking that way. I think my impression of Google, knowing the companies history, and the people involved there, and Diane Greene in particular, as you know from the Vmware days. She's kind of humble, but she's not. She's tough. And she's good. And she's smart. >> And she's bringing in really good people. And by the way, John, I want to give them kudos, really supported International Women's Day, I love the, Fei-Fei got up, and she talked about her, one of her compatriots, another badass woman up there, that got like one of the big moments of the keynote there. >> John: Did they have a woman in tech panel? >> Not at this event. Because Diane was there, Fei-Fei was there. They had some women just participating in it. I know they had some other events going on throughout the show. >> I agree, and I think it's awesome. I think one of the things that I like about Google, and again, I'll reiterate, is that apples and oranges relative to the other Cloud guys. But remember, just because Amazon's lead is so far ahead, that you still have this jocking of position between the other players. And they're all taking the same pattern. Again, this is the same thing we talked about at our other analysis, is that, certainly at re:Invent, we talked about the same thing. Microsoft, Oracle, IBM, and now Google, are differentiating with their apps. And I think that's smart. I don't think that's a bad move at all. It does telegraph a little bit, that maybe they got, they could add more to show, we'll see tomorrow. But I don't think that's a bad thing. Again, it does make the numbers a little messy, in terms of what's what. But I think it's totally cool for a company to differentiate on their offering. >> Yeah, definitely. And John, as you said, Google is playing their game. They're not trying to play Amazon's game. They're not, Oracle's thing was what? You kind of get a little bit of the lead, and kind of just make sure how you attack and stay ahead of what they're doing, going to the boating analogy there. But Google knows where they're going, moving themselves forward. That they've made some really good progress. The amount of people, the amount of news they have. Are they moving fast enough to really try to close a little bit on the Amazon's world, is something I want to come out of the show with. Where are customers going? >> And it's a turbulent time too. As Peter Burris, our own Peter Buriss at Wikibon, would say, is a turbulent time. And it's going to really put everyone on notice. There's a lot to cover, if you're an analyst. I mean, you have compute, network storage, services. I mean, there's a slew of stuff that's being rolled out, either in table stakes for existing enterprises, plus new stuff. I mean, I didn't hear a lot of IoT today. Did you hear much IoT? Is there IoT coming to you at the briefing? >> Come on. I'm sure there's some service coming out from Google, that'll help us be able to process all this stuff much faster. They'll just replace this with-- >> So you're in the analyst meeting. I know you're under NDA, but is there IoT coming tomorrow? >> IoT was a term that I heard this week, yes. >> So all right, that's a good confirmation. Stu cannot confirm or deny that IoT will be there tomorrow. Okay, well, that's going to end day one of coverage, here in our studio. As you know, we got a new studio. We have folks on the ground. You're going to start to see a new CUBE formula, where we have in-studio coverage, and out in the field, like our normal CUBE, our "game day", as we say. Getting all the signal, extracting it from that noise out there, for you. Again, in-studio allows us to get more content. We bring our friends in. We want to get the content. We're going to get the summaries, and share that with you. I'm John Furrier, Stu Miniman, day one coverage. We'll see you tomorrow for another full day of special coverage, sponsored by Intel, two days of coverage. I want to thank Intel for supporting our editorial mission. We love the enterprise, we love Cloud, we love big data, love Smart Cities, autonomous vehicles, and the changing landscape in tech. We'll be back tomorrow, thanks for watching.

>> 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)

>> Announcer: Live from Silicon Valley, it's theCUBE, covering Mobile World Congress 2017. Brought to you by Intel. >> Okay, welcome back, everyone. We're live here in Palo Alto, California for SiliconANGLE Media's theCUBE special two-day coverage of Mobile World Congress in Barcelona, Spain. As people starting to get ready to take that nap to go out all night in Barcelona after they've had their tapas and wine we're here in California breaking it all down. Two days of coverage, this is end of day two in Spain. We're in the middle of it here, and breaking down the analysis, covering all the news, commentary, identifying the trends and talking to the folks here in the Bay Area that can add value to the conversation, and our next guest is Bob Stefanski, who's the managing director of eLab, located in Palo Alto, a venture capitalist making investments and really a key player bridging Silicon Valley with Michigan Motor City here bringing the two worlds together as the autonomous vehicles and the automotive industry's under massive disruption and change, and the car companies know about it and they're not afraid of it. Ford's here, GM's here, they're all here, and now we have Bob Stefanski here in theCUBE. Bob, good to see ya, thanks for coming in. >> John, thanks for having me on. It's good to be here. >> I love this story, and I think this is not really well documented, but this is the beginning of what's been happening for a while, kind of as an outpost to Michigan and Motor City, you have some satellite offices in Palo Alto or Silicon Valley. They're close to Stanford, close to Cal, close to a lot of the research, but now it's a change where you're starting to see Ford, GM, all the car companies, BMW, big venture fund as well, all here in Silicon Valley because the software defined blank is everything, so software-defined radios in 5G, big story at Mobile World Congress, software-defined networks, the world is software-driven, so they're here. You're bridging the investments, trying to identify the key trends. >> Bob: You bet. >> To help identify this new game-changing technology that's going to bring a whole new world together, and certainly Intel and others are changing the networks, creating an end-to-end architecture digitally to bring autonomous vehicles, media entertainment, smart cities, the smart home, and we're seeing Alexa, Google's got their device, and you're seeing smart cities. What's the big bridge being built around? I mean, obviously, the cars themselves are changing. What is this bridge between Silicon Valley and Michigan Motor City? Obviously, that's a big part of Uber and whatnot. >> Absolutely, John, you know, I grew up in Michigan, I grew up in the days before there was a single chip, I think, in cars. I worked for General Motors when I was a summer intern in the early '80s in the engineering group there. There was a very distinct automotive culture. I then fast forward 20 years, and I'm in Silicon Valley. I've spent the majority of my career here in Silicon Valley doing Silicon Valley things, so software, enterprise software was where I spent most of my career with TIBCO software. We are now bridging these two things. We're bridging, the automotive industry is, I think we all know, anyone who's paying attention, the car now has a lot of chips in it, and it's about to have a lot more, the car is becoming a data center on wheels. It's becoming another mobile device, a very big mobile device, and the really neat thing is with, we're the only venture fund with offices and partners located in both places. We have fairly deep networks and connections into the whole Michigan ecosystem back there in automotive, and of course, we're out here in Silicon Valley as well. It's been fascinating to see after spending, after having that early childhood experience, young adult experience as I was growing up in the auto industry, and really kind of the heyday of the auto industry, maybe the beginning of the decline in the '70s and early '80s, and then having sort of spent the career working on the latest, greatest, newest technologies as they've come along out here in Silicon Valley. This is a fascinating time to see these two now finally merging together with autonomous vehicles. >> One of the things that we're seeing in Intel, obviously the bellwether, and they always have the long game going and make the big bets, and autonomous vehicles and virtual reality is that showcase, but what I find interesting and I want to get your thoughts on and reaction to is that I shared on my Facebook feed a post by autoblog.com that says, "Race for autonomous cars is over in Silicon Valley." And they were kind of pointing to the obvious things that people are seeing today, which is myopic and narrow in my opinion, but obviously Apple kind of tapped out of building a car, and I think a lot of people thought, "Oh, Apple should build a car. "They built a watch, why not build a car?" Obviously, they forgot about Teslas here, so I'm not sure what they're thinking, but I think they missed the point that it's bigger than the actual car. Could you share some color commentary around the mindset of Detroit? Because we're seeing that certainly Ford's not lookin' the other way, they have their finger on the pulse. Others do as well. What is the general mindset for the folks in both ecosystems and how are they working together right now? >> Sure, that's a great question, John. And you said it right at the outset, look, all the autos are here, and they're here in our backyard in Palo Alto. They've really sort of migrated here over the last five, seven years probably. GM is here, Ford is here in a big way, BMW's here, Mercedes' here. So they all obviously recognize that the car's becoming all about technology, and they need to be, if they're going to be a key part of that in the future, they need to be out here, and they need to be understanding that, on the other hand, making cars is hard. Making cars is not a simple thing, and this is where 70% of auto research in the U.S. is still happening in Michigan in the Detroit area. Michigan has a very high density of automotive engineers, and integration engineers and integrating IT with the autos and so forth. There's a lot of talent there, there's a lot of experience there. I think, you know, frankly probably the biggest and most interesting thing in this bridge is going to be to watch the cultures either integrate or not, and there's a lot of talk about who wins and the autos can't move fast enough, and that may be the case, but we'll find out. I'm not so sure. They know how to compete and there's a lot of smart people. >> There's no way that Detroit's going away. >> Bob: Not at all. >> My view is they're very solid, and I think they got good self-awareness, and I think if you look at the signals, I would say that I'm pretty confident it's just a matter of how they get reconfigured in this new value-creation model around 5G and whatnot. But I want to get your thoughts on another point, which is if you look at what the iPhone did, that created a new class of app developer and that, I would call them, on one hand artisan developers, people who are composing much more design-centric, obviously, and then, you still had the hardcore developers, and that was lower in the stack, but also other harder problems. But when you talk about automotive, there are some serious technology challenges that require, I won't say old-school engineering, but really hardcore engineering. You're talking about wireless, which is a physics issue, you have all kinds of policy challenges, but really hardcore engineering and software development. I'm not discounting what the app guys are doing, but certainly there will be plenty of apps like all that more the finishing touches in, say, cars for instance. What are some of those technologies because that's really where you need to see the classic double-E, computer science, physics gurus, the real PhD kind of guys. What's your thoughts and what trends do you see in that hardcore area? >> Absolutely, you know, I mean, look, we all know that cars are no longer about just axles and engines, and those hard things. But I think when we make this transition to highly automated, to fully autonomous vehicles, the technologies that are driving that, the fundamental technologies and the really hard stuff are around sensors, right. We're constantly developing newer, faster, better, further range, more precise sensors, so we're talking about Lidar, we're talking about of course, Mobileye and what's happening with the camera and vision processing. We're talking about even radar, a 1940s technology that actually is changing very fast. There's a lot of interesting things happening. >> AI's an old technology coming back now and getting rebooted with cloud computing and whatnot. >> Yeah, absolutely, and then, connecting all that to the cloud, right. I think the hardest, and I think we talked about this before, probably still the single hardest piece and the point of this fear on this is artificial intelligence at the end of the day. It's the same stuff that's driving virtual reality, it's the same stuff that's driving a lot of different things right now, but it's also true in self-driving cars. These things, when you make a car, first of all, it's got to be safe. It has got to be safe. The Department of Transportation, the government regulatory interest is in safety. To make a car safe, they have to be tested, tested, tested, tested, what's that about? Well, when autonomous takes over, it's no long John Furrier driving that car, it's the AI driving the car, right? How do you make it AI smart? >> The crash test dummy's inside AI. >> Right, this is fundamental deep learning. This is fundamental deep learning that the guys at Google know as much as anybody in the world and Facebook and all, you know, that we all know about the arms race in artificial intelligence, but that's at the core of what's happening in self-driving vehicles, and most of that talent, the talent is spread out, it's all over the world, but there's a lot of it out here. And they know they need to have those engineers here. >> What's interesting about your background, you mentioned when we started this segment, you have an enterprise software background in Silicon Valley and you've been very successful, it's interesting, we were talking yesterday and we kind of validated this morning on our opening segment around Mobile World Congress, it's a two-show game right now. It's kind of a bipolar show. You got devices, the new phones, the glam and the sizzle, Samsung and so on, so forth, LG. >> Bob: Can't wait. >> And then you got the TelCo show, which is, TelCo's trying to figure things out, but what's interesting is what we noticed is that there's really a trend between enterprise computing concepts, network data center with consumer clash, so there's a direct collision course between the TelCos which serve as consumers, but the infrastructure challenges are all enterprise. >> Bob: Right, right. >> And the number one thing that's key there is integration and ecosystems. So, you kind of have the right background for this, so we want to get your thoughts on ecosystem integration concepts where a lot of boats in the harbor, so rising tide will float all boats, we see that as a trend, but also integrating. You mentioned the testing, so it's not one company's going to do all this. >> It's not one company that's going to do all this, and in fact, it's going to one of the more complex integrations we've ever undertaken because we're going to have to have those automotive engineers, we're going to have to have those, the software developers, we're going to have to have the AI guys, we're going to have to have the sensor guys, and it's all going to the cloud ultimately. And don't forget GPS, you got GPS. You got a lot. >> Connectivity challenges. Mobility. >> Connectivity challenges, and of course, 5G when 5G comes down the line is going to be a critical part of this as well. You're also going to have smart cities, you're going to have infrastructure embedded in the environment, and in particular, the highly dense areas is where it'll happen first. It's not going to, rural America and so forth, they're going to be probably driving their cars without the embedded sensor for a while, but there are a lot of different components to integrate. >> We had a CTO on earlier before, Val Bercovici, he was talking about the cloud native architecture really plays well in this market because it's not so much about the one car, it's about the one cars in relations to thousands of other cars that are self-driving. It's a multi-touch data equation. Alright, Bob, final question I want to get to you is what are you investing in? What are some of the things that you're looking at? Can you share? I know some of the stuff is pretty stealthy on your end, 'cause it's pretty high end, but can you share any, show a little leg on investments you've made? >> You bet, you bet. Yeah, John, we're, some of the, probably the coolest stuff I can't talk about right now, you're right. Hint hint, it's in some of the things I've already talked about. We're certainly in artificial intelligence. We have a portfolio company in that. We're looking at others. In better sensors, some of the sensor areas I talked about, we are in the process of looking at companies. We have investments in the connected space, not autonomous, but connected space, which is also going to be a very big and important part of this. Company called Aperia right up here that is, at the end of the day, they're tire inflation, but it's all about data. They do automated tire inflation, connected, they'll be connecting every fleet in America. And so we're-- >> It's those boring little efficiency areas that really yield a lot of cash. We just talked about a guest about waste optimize, waste disposal industries. >> Absolutely. >> Little things that are luring billion dollar innovations. >> Little things, very big problems, right, and it's where you can marry things like tire inflation on commercial fleets with data, with lots of data that we never had before. And then apply artificial intelligence to that to learn what's happening and map an entire fleet or multiple fleets nationwide, worldwide, collect all that data and start to correlate and understand what. Those are the problems that are, where a lot of value can be added actually with these technologies. >> It's super interesting, and I think you got a great opportunity, congratulations. Great to see the bridge between Silicon Valley and Michigan Motor City, and I think that's anecdotally means automotive, but there's probably other bridges your connecting, too. Bob, thanks for coming in and sharing. Final question for you while we got you, got a little bit more time. What premises would you, are you betting on? I mean, everyone has a premise, and you mentioned before you came on-camera that one of your premises is that automotive won't miss mobility. What other premises are you investing, what thesises are you building around? >> Well, look, for the, are you talking about autonomous vehicles or much--? >> For the bridge fund and how you're looking at the future of autonomous driving in the connected ecosystem, what are the premise, what's on the premise? >> The premise there is that we're in for what I think is going to be the biggest change in the biggest thing to happen in transportation ever, but it's not just transportation, so we're looking at areas that are not autonomous per se, but that are going to be fundamentally impacted, so services. We're talking about things like insurance, we're talking about all the shared services that are going to come out of this. Medicine is going to probably change, and there's some interesting plays there. And so all of this sort of periphery that is going to be disrupted, we're trying to look five years, 10 years ahead and look at how life is going to change, people's individual experiences are going to change, and how new services, in particular shared services, are going to be enabled by autonomy. >> Bob Stefanski here inside theCUBE, breaking down his commentary and direction of his investments bridging Silicon Valley with Michigan Motor City, or really looking at the autonomous future of vehicles and transportation. This is theCUBE, I'm John Furrier. We'll be back with more coverage and analysis of Mobile World Congress 2017 after this short break. (upbeat electronic music)