(upbeat music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBE Conversation. >> Welcome everyone to this special CUBE Conversation Around the CUBE segment, Unpacking AI, number two, sponsored by Juniper Networks. We've got a great lineup here to go around the CUBE and unpack AI. We have Ken Jennings, all-time Jeopardy champion with us. Celebrity, great story there, we'll dig into that. John Hinson, director of AI at Evotek and Charna Parkey, who's the applied scientist at Textio. Thanks for joining us here for Around the CUBE Unpacking AI, appreciate it. First question I want to get to, Ken, you're notable for being beaten by a machine on Jeopardy. Everyone knows that story, but it really brings out the question of AI and the role AI is playing in society around obsolescence. We've been hearing gloom and doom around AI replacing people's jobs, and it's not really that way. What's your take on AI and replacing people's jobs? >> You know, I'm not an economist, so I can't speak to how easy it's going to be to retrain and re-skill tens of millions of people once these clerical and food prep and driving and whatever jobs go away, but I can definitely speak to the personal feeling of being in that situation, kind of watching the machine take your job on the assembly line and realizing that the thing you thought made you special no longer exists. If IBM throws enough money at it, your skill essentially is now obsolete. And it was kind of a disconcerting feeling. I think that what people need is to feel like they matter, and that went away for me very quickly when I realized that a black rectangle can now beat me at a game show. >> Okay John, what's your take on AI replacing jobs? What's your view on this? >> I think, look, we're all going to have to adapt. There's a lot of changes coming. There's changes coming socially, economically, politically. I think it's a disservice to us all to get to too indulgent around the idea that these things are going to change. We have to absorb these things, we have to be really smart about how we approach them. We have to be very open-minded about how these things are going to actually change us all. But ultimately, I think it's going to be positive at the end of the day. It's definitely going to be a little rough for a couple of years as we make all these adjustments, but I think what AI brings to the table is heads above kind of where we are today. >> Charna, your take around this, because the role of humans versus machines are pretty significant, they help each other. But is AI going to dominate over humans? >> Yeah, absolutely. I think there's a thing that we see over and over again in every bubble and collapse where, you know, in the automotive industry we certainly saw a bunch of jobs were lost, but a bunch of jobs were gained. And so we're just now actually getting into the phase where people are realizing that AI isn't just replacement, it has to be augmentation, right? We can't simply use images to replace recognition of people, we can't just use black box to give our FICO credit scores, it has to be inspectable. So there's a new field coming up now called explainable AI that actually is where we're moving towards and it's actually going to help society and create jobs. >> All right so let's stay on that next point for the next round, explainable AI. This points to a golden age. There's a debate around are we in a bubble or a golden age. A lot of people are negative right now on tech. You can see all the tech backlash. Amazon, the big tech companies like Apple and Facebook, there's a huge backlash around this so-called tech for society. Is this an indicator of a golden age coming? >> I think so, absolutely. We can take two examples of this. One would be where, you remember when Amazon built a hiring algorithm based upon their own resume data and they found that it was discriminating against women because they had only had men apply for it. Now with Textio we're building augmented writing across the audience and not from a single company and so companies like Johnson and Johnson are increasing the pipeline by more than nine percent which converts to 90,000 more women applying for their jobs. And so part of the difference there is one is explainable, one isn't, and one is using the right data set representing the audience that is consuming it and not a single company's hiring. So I think we're absolutely headed into more of a golden age, and I think these are some of the signs that people are starting to use it in the right way. >> John, what's your take? Obviously golden age doesn't look that to us right now. You see Facebook approving lies as ads, Twitter banning political ads. AI was supposed to solve all these problems. Is there light at the end of this dark tunnel we're on? >> Yeah, golden age for sure. I'm definitely a big believer in that. I think there's a new era amongst us on how we handle data in general. I think the most important thing we have here though is education around what this stuff is, how it works, how it's affecting our lives individually and at the corporate level. This is a new era of informing and augmenting literally everything we do. I see nothing but positives coming out of this. We have to be obviously very careful with our approaching all the biases that already exist today that are only going to be magnified with these types of algorithms at mass scale. But ultimately if we can get over that hurdle, which I believe collectively we all need to do together, I think we'd live in much better, less wasteful world just by approaching the data that's already at hand. >> Ken, what's your take on this? It's like a daily double question. Is it going to be a golden age? >> Laughs >> It's going to come sooner or later. We have to have catastrophe before, we have to have reality hit us in the face before we realize that tech is good, and shaping it? It's pretty ugly right now in some of the situations out there, especially in the political scene with the election in the US. You're seeing some negative things happening. What's your take on this? >> I'm much more skeptical than John and Charna. I feel like that kind of just blinkered, it's going to be great, is something you have to actually be in the tech industry and hearing all day to actually believe. I remember seeing kind of lay-person's exposure to Watson when Watson was on Jeopardy and hearing the questions reporters would ask and seeing the memes that would appear, and everyone's immediate reaction just to something as innocuous as a AI algorithm playing on a game show was to ask, is this Skynet from Terminator 2? Is this the computer from The Matrix? Is this HAL pushing us out of the airlock? Everybody immediately first goes to the tech is going to kill us. That's like everybody's first reaction, and it's weird. I don't know, you might say it's just because Hollywood has trained us to expect that plot development, but I almost think it's the other way around. Like that's a story we tell because we're deeply worried about our own meaning and obsolescence when we see how little these skills might be valued in 10, 20, 30 years. >> I can't tell you how much, by the way, Star Trek, Star Wars and Terminators probably affected the nomenclature of the technology. Everyone references Skynet. Oh my God, we're going to be taken over and killed by aliens and machines. This is a real fear. I thinks it's an initial reaction. You felt that Ken, so I've got to ask you, where do you think the crossover point is for people to internalize the benefits of say, AI for instance? Because people will say hey, look back at life before the iPhone, look at life before these tools were out there. Some will say society's gotten better, but yet there's this surveillance culture, things... And on and on. So what do you guys think the crossover point is for the reaction to change from oh my God, it's Skynet, gloom and doom to this actually could be good? >> It's incredibly tricky because as we've seen, the perception of AI both in and out of the industry changes as AI advances. As soon as machine learning can actually do a task, there's a tendency to say there's this no true Scotsman problem where we say well, that clearly can't be AI because I see how the trick worked. And yeah, humans lose at chess now. So when these small advances happen, the reaction is often oh, that's not really AI. And by the same token, it's not a game-changer when your email client can start to auto-complete your emails. That's a minor convenience to you. But you don't think oh, maybe Skynet is good. I really do think it's going to have to be, maybe the inflection point is when it starts to become so disruptive that actually public policy has to change. So we get serious about >> And public policy has started changing. >> whatever their reactions are. >> Charna, your thoughts. >> The public policy has started changing though. We just saw, I think it was in September, where California banned the use of AI in the body cameras, both real-time and after the fact. So I think that's part of the pivot point that we're actually seeing is that public policy is changing.` The state of Washington currently has a task force for AI who's making a set of recommendations for policy starting in December. But I think part of what we're missing is that we don't have enough digital natives in office to even attempt to, to your point Ken, predict what we're even going to be able to do with it, right? There is this fear because of misunderstanding, but we also don't have a respect of our political climate right now by a lot of our digital natives, and they need to be there to be making this policy. >> John, weigh in on this because you're director of AI, you're seeing positive, you have to deal with the uncertainty as well, the growth of machine learning. And just this week Google announced more TensorFlow for everybody. You're seeing Open Source. So there's a tech push, almost a democratization, going on with AI. So I think this crossover point might be sooner in front of us than people think. What's your thoughts? >> Yeah it's here right now. All these things can be essentially put into an environment. You can see these into products, or making business decisions or political decisions. These are all available right now. They're available today and its within 10 to 15 lines of code. It's all about the data sets, so you have to be really good stewards of the data that you're using to train your models. But I think the most important thing, back to the Skynet and all this science-fiction side, we have to collectively start telling the right stories. We need better stories than just this robots are going to take us over and destroy all of our jobs. I think more interesting stories really revolve around, what about public defenders who can have this informant augmentation algorithm that's going to help them get their job done? What about tailor-made medicine that's going to tell me exactly what the conditions are based off of a particular treatment plan instead of guessing? What about tailored education that's going to look at all of my strengths and weaknesses and present a plan for me? These are things that AI can do. Charna's exactly right, where if we don't get this into the right political atmosphere that's helping balance the capitalist side with the social side, we're going to be in trouble. So that's got to be embedded in every layer of enterprise as well as society in general. It's here, it's now, and it's real. >> Ken, before we move on to the ethics question, I want to get your thoughts on this because we have an Alexa at home. We had an Alexa at home; my wife made me get rid of it. We had an Apple device, what they're called... the Home pods, that's gone. I bought a Portal from Facebook because I always buy the earliest stuff, that's gone. We don't want listening devices in our house because in order to get that AI, you have to give up listening, and this has been an issue. What do you have to give to get? This has been a big question. What's your thoughts on all this? >> I was at an Amazon event where they were trumpeting how no technology had ever caught on faster than these personal digital assistants, and yet every time I'm in a use case, a household that's trying to use them, something goes terribly wrong. My friend had to rename his because the neighbor kids kept telling Alexa to do awful things. He renamed it computer, and now every time we use the word computer, the wall tells us something we don't want to know. >> (laughs) >> This is just anecdata, but maybe it speaks to something deeper, the fact that we don't necessarily like the feeling of being surveilled. IBM was always trying to push Watson as the star Trek computer that helpfully tells you exactly what you need to know in the right moment, but that's got downsides too. I feel like we're going to, if nothing else, we may start to value individual learning and knowledge less when we feel like a voice from the ceiling can deliver unto us the fact that we need. I think decision-making might suffer in that kind of a world. >> All right, this brings up ethics because I bring up the Amazon and the voice stuff because this is the new interface people want to have with machines. I didn't mention phones, Androids and Apple, they need to listen in order to make decisions. This brings up the ethics question around who sets the laws, what society should do about this, because we want the benefits of AI. John, you point out some of them. You got to give to get. Where are we on ethics? What's the opinion, what's the current view on this? John, we'll start with you on your ethics view on what needs to change now to move the ball faster. >> Data is gold. Data is gold at an exponential rate when you're talking about AI. There should be no situation where these companies get to collect data at no cost or no benefit to the end consumer. So ultimately we should have the option to opt out of any of these products and any of this type of surveillance wherever we can. Public safety is a little bit different situation, but on the commercial side, there is a lot of more expensive and even more difficult ways to train these models with a data set that isn't just basically grabbing everything our of your personal lives. I think that should be an option for consumers and that's one of those ethical check-marks. Again, ethics in general, the way that data's trained, the way that data's handled, the way models actually work, it has to be a primary reason for and approach of how you actually go about developing and delivering AI. That said, we cannot get over-indulgent in the fact that we can't do it because we're so fearful of the ethical outcomes. We have to find some middle ground and we have to find it quickly and collectively. >> Charna, what's your take on this? Ethics is super important to set the agenda for society to take advantage of all this. >> Yeah. I think we've got three ethical components here. We certainly have, as John mentioned, the data sets. However, it's also what behavior we're trying to change. So I believe the industry could benefit from a lot more behavioral science, so that we can understand whether or not the algorithms that we're building are changing behaviors that we actually want to change, right? And if we aren't, that's unethical. There is an entire field of ethics that needs to start getting put into our companies. We need an ethics board internally. A few companies are doing this already actually. I know a lot of the military companies do. I used to be in the defense industry, and so they've got a board of ethics before you can do things. The challenge is also though that as we're democratizing the algorithms themselves, people don't understand that you can't just get a set of data that represents the population. So this is true of image processing, where if we only used 100 images of a black woman, and we used 1,000 images of a white man because that was the distribution in our population, and then the algorithm could not detect the difference between skin tones for people of color, then we end up with situations where we end up in a police state where you put in an image of one black woman and it looks like ten of them and you can't distinguish between them. And yet, the confidence rate for the humans are actually higher, because they now have a machine backing their decision. And so they stop questioning, to your point, Ken, about what is the decision I'm making, they're like I'm so confident, this data told me so. And so there's a little bit of you need some expert in the loop and you also can't just have experts, because then you end up with Cambridge Analytica and all of the political things that happened there, not just in the US, but across 200 different elections and 30 different countries. And we are upset because it happened in the US, but this has been happening for years. So its just this ethical challenge of behavior change. It's not even AI and we do it all the time. Its why the cigarette industry is regulated (laughs). >> So Ken, what's your take on this? Obviously because society needs to have ethics. Who runs that? Companies? The law-makers? Someone's got to be responsible. >> I'm honestly a little pessimistic the general public will even demand this the way we're maybe hoping that they will. When I think about an example like Facebook, people just being able to, being willing to give away insane amounts of data through social media companies for the smallest of benefits: keeping in touch with people from high school they don't like. I mean, it really shows how little we value not being a product in this kind of situation. But I would like to see this kind of ethical decisions being made at the company-level. I feel like Google kind of surreptitiously moved away from it's little don't be evil mantra with the subtext that eh, maybe we'll be a little evil now. It just reminds me of Manhattan Project era thinking, where you could've gone to any of these nuclear scientists and said you're working on a real interesting puzzle here, it might advance the field, but like 200,000 civilians might die this summer. And I feel like they would've just looked at you and thought that's not really my bailiwick. I'm just trying to solve the fission problem. I would like to see these 10 companies actually having that kind of thinking internally. Not being so busy thinking if they can do something that they don't wonder if they should. >> That's a great point. This brings up the point of who is responsible. Almost as if who is less evil than the other person? Google, they don't do evil, but they're less evil than Amazon and Facebook and others. Who is responsible? The companies or the law-makers? Because if you look up some of the hearings in Washington, D.C., some of the law-makers we see up there, they don't know how the internet works, and it's pretty obvious that this is a problem. >> Yeah, well that's why Jack Dorsey of Twitter posted yesterday that he banned not just political ads, but also issue ads. This isn't something that they're making him do, but he understands that when you're using AI to target people, that it's not okay. At some point, while Mark is sitting on (laughs) this committee and giving his testimony, he's essentially asking to be regulated because he can't regulate himself. He's like well, everyone's doing it, so I'm going to do it too. That's not an okay excuse. We see this in the labor market though actually, where there's existing laws that prevent discrimination. It's actually the company's responsibility to make sure that the products that they purchase from any vendor isn't introducing discrimination into that process. So its not even the vendor that's held responsible, it's the company and their use of it. We saw in the NYPD actually that one of those image recognition systems came up and someone said well, he looked like, I forget the name of what the actor was, but some actor's name is what the perpetrator looked like and so they used an image of the actor to try and find the person who actually assaulted someone else. And that's, it's also the user problem that I'm super concerned about. >> So John, what's your take on this? Because these are companies are in business to make money, for profit, they're not the government. And who's the role, what should the government do? AI has to move forward. >> Yeah, we're all responsible. The companies are responsible. The companies that we work with, I have yet to interact with customers, or with our customers here, that have some insidious goal, that they're trying to outsmart their customers. They're not. Everyone's looking to do the best and deliver the most relevant products in the marketplace. The government, they absolutely... The political structure we have, it has to be really intelligent and it's got to get up-skilled in this space and it needs to do it quickly, both at the economy level, as well as for our defense. But the individuals, all of us as individuals, we are already subjected to this type of artificial intelligence in our everyday lives. Look at streaming, streaming media. Right now every single one of us goes out through a streaming source, and we're getting recommendations on what we should watch next. And we're already adapting to these things, I am. I'm like stop showing me all the stuff you know I want to watch, that's not interesting to me. I want to find something I don't know I want to watch, right? So we all have to get educated, we're all responsible for these things. And again, I see a much more positive side of this. I'm not trying to get into the fear-mongering side of all the things that could go wrong, I want to focus on the good stories, the positive stories. If I'm in a courtroom and I lose a court case because I couldn't afford the best attorney and I have the bias of a judge, I would certainly like artificial intelligence to make a determination that allows me to drive an appeal, as one example. Things like that are really creative in the world that we need to do. Tampering down this wild speculation we have on the markets. I mean, we are all victims of really bad data decisions right now, almost the worst data decisions. For me, I see this as a way to actually improve all those things. Fraud fees will be reduced. That helps everybody, right? Less speculation and these wild swings, these are all helpful things. >> Well Ken, John and Charna, thank- (audio feedback) >> Go ahead, finish. Get that word in. >> Sorry. I think that point you were making though John, is we are still a capitalist society, but we're no longer a shareholder capitalist society, we are a stakeholder capitalist society and the stakeholder is the society itself. It is us, it what we want to see. And so yes, I still want money. Obviously there are things that I want to buy, but I also care about well-being. I think it's that little shift that we're seeing that is actually you and I holding our own teams accountable for what they do. >> Yeah, culture first is a whole new shift going on in these companies that's a for-profit, mission-based. Ken, John, Charna, thanks for coming on Around the CUBE, Unpacking AI. Let's go around the CUBE Ken, John and Charna in that order, and just real quickly, unpacking AI, what's your final word? >> (laughs) I really... I'm interested in John's take that there's a democratization coming provided these tools will be available to everyone. I would certainly love to believe that. It seems like in the past, we've seen no, that access to these kind of powerful, paradigm-changing tools tend to be concentrated among a very small group of people and the benefits accrue to a very small group of people. But I hope that doesn't happen here. You know, I'm optimistic as well. I like the utopian side where we all have this amazing access to information and so many new problems can get solved with amazing amounts of data that we never could've touched before. Though you know, I think about that. I try to let that help me sleep at night, and not the fact that, you know... every public figure I see on TV is kind of out of touch about technology and only one candidate suggests the universal basic income, and it's kind of a crackpot idea. Those are the kind of things that keep me up at night. >> All right, John, final word. >> I think it's beautiful, AI's beautiful. We're on the cusp of a whole new world, it's nothing but positivity I see. We have to be careful. We're all nervous about it. None of us know how to approach these things, but as human beings, we've been here before. We're here all the time. And I believe that we can all collectively get a better lives for ourselves, for the environment, for everything that's out there. It's here, it's now, it's definitely real. I encourage everyone to hurry up on their own education. Every company, every layer of government to start really embracing these things and start paying attention. It's catching us all a little bit by surprise, but once you see it in production, you see it real, you'll be impressed. >> Okay, Charna, final word. >> I think one thing I want to leave people with is what we incentivize is what we end up optimizing for. This is the same for human behavior. You're training a new employee, you put incentives on the way that they sell, and that's, they game the system. AI's specifically find the optimum route, that is their job. So if we don't understand more complex cost functions, more complex representative ways of training, we're going to end up in a space, before we know it, that we can't get out of. And especially if we're using uninspectable AI. We really need to move towards augmentation. There are some companies that are implementing this now that you may not even know. Zillow, for example, is using AI to give you a cost for your home just by the photos and the words that you describe it, but they're also purchasing houses without a human in the loop in certain markets, based upon an inspection later by a human. And so there are these big bets that we're making within these massive corporations, but if you're going to do it as an individual, take a Coursera class on AI and take a Coursera class on ethics so that you can understand what the pitfalls are going to be, because that cost function is incredibly important. >> Okay, that's a wrap. Looks like we have a winner here. Charna, you got 18, John 16. Ken came in with 12, beaten again! (both laugh) Okay, Ken, seriously, great to have you guys on, a pleasure to meet everyone. Thanks for sharing on Around the CUBE Unpacking AI, panel number two. Thank you. >> Thanks a lot. >> Thank you. >> Thanks. I've been defeated by artificial intelligence again! (all laugh) (upbeat music)

>> Live from Mountain View, California, it's the Cube! Covering Devnet Create 2019. Brought to you by Cisco. >> Welcome back to the Cube's coverage, day one, Cisco Devnet Create 2019 at the Computer History Museum in Mountain View, California. Lisa Martin with John Furrier, pleased to welcome to the Cube for the first time, Mathieu Gerard, the co-founder and CTO of Mapwize. Mathieu, it's lovely to have you on the program. >> Thank you. >> So Mapwize and Cisco are partners, but first, give our audience an idea of Mapwize. What you are, what you deliver, where you're located. >> Yeah, Mapwize is a startup company, we are based in France. And so we want to bring digital services inside buildings. We feel that a lot of our life has been digitalized, but that there are still a lot of services that can be brought inside those buildings. And one of the key elements, when you speak about digital services in buildings, is to have a map. A map where you can show all the different details about the buildings, the live data that is generating from all the sensors that's in the building. That's where the partnership with Cisco actually comes in to bring all those infrastructure sensors that you get, bring that to be displayed on the map as well and bring services to the user. >> So one of the hot announcements is the Wi-Fi 6. I'm jazzed about. It was 802.11 something A or B, I forget what it was. But you're now calling it Wi-Fi 6, thank God. Although even numbers, I'm skeptical of that. You know, odds tend to be better, bug-free, going back to our old days as you know. But Wi-Fi 6 changes the game at many levels. What are some of the things that will help you guys? Because we've all been in the buildings where, concrete, bounces RF, you can't get through certain things, we've all been in stadiums where it's kind of like a nightmare with bandwidth. Wi-Fi's like, you know, part of Maslow's hierarchy of needs now. We want our Wi-Fi. Businesses want Wi-Fi, so new things are happening. What's your take on Wi-Fi 6? >> So our take is that we really want to bring all those services. Of course bandwidth is something, but for us it's not necessarilly the critical part. For us it's really the kind of data that you can get from the Wi-Fi. Making sure that all the IOT devices can be deployed in more and more of those buildings. Everybody now wants to know if a meeting room is available or not. So what's the best way of doing that, and just having a small sensor that detects presence, and can be broadcasted back to the cloud and then displayed on the map. So there are so many sensors, that's one of them. But in terms of pollution of temperature, if you have those in the building, can bring new services around all those mapping. >> So bandwidth is not an issue, obviously this is like gig ethernet now, just helps with the signaling. What about range and coverage area, antenna chains? These are the kind of things we're hearing about, some of the benefits. Does that help you guys at all? Does that help the maps and get more range? >> Yeah, and at the same time the challenge we are facing when we look at the Wi-Fi is to be able to use it to locate people and to know where I am so that I can be provided services around me. And so that usually came with a need for more density of access points because the more density you have the better you can access the location of a user. And so what we see is a lot of evolution in the Wi-Fi in the kind of capabilities that they have in positioning people. So we hope to see that as well in Wi-Fi 6. >> What's your vision on location services inside an enterprise? Because we saw that movie play out on the consumer side with mobile, iPhones and Androids now everywhere. We've all seen it, we know when art was showing up, all the things that were happening on the maps, map mashups back in the old web 2.0 days. What's the new sets of things that will come out that you see? What's your vision? >> What we see is that, as you were mentioning, mapping and wave finding is something we are using everyday. And nobody would even imagine how it was back in the time when we had paper maps. And so we believe that that is also coming into all the office and industry environments. For example the possibility of seeing live, what's available, what's going on in my building, what's available as services where are the people that I need to interact with, where are the assets I need to actually go grab? That's something that today, seems like complicated to do, and I'm pretty convinced that in a few years from now, it's going to be natural, like waze is natural everyday for everybody. >> And this is the opportunity for Mapwize and with Cisco as well, to convert existing structures into these smart buildings. Are you seeing that as well as with the development of new buildings that are kind of built natively smart? >> Yeah, of course the new buildings are built more smart. And with new infrastructure, that allows a lot more. But the new buildings are still a very small percentage of the buildings that are out there. And so the great thing is that all the infrastructure that already exists is already capable of a lot. And so even with the updates that are being done there, there is a lot of data that today are totally not used, that we believe still can bring a lot of new services and a lot of potential. >> Is there any industries in particular where you and Cisco are working together where this is a really, they're right for this type of transformation. I can think of hospitals as one thing that comes to mind with being able to identify where everything is, censor services. Especially in life and death situations. >> Yeah, so what we see is that everybody that works in a hospital has the same reaction. It's like, where is everything? It's the kind of campuses where it's really easy to get lost. And so, whenever you get there, you need to get to your appointment, and if you don't find it, what're you going to do is to ask the medical staff. So you ask people that are actually saving life, how to get to your next appointment, which we feel is kind of a waste. >> Huge efficiencies. Not just asset tracking, which is low-hanging fruit. IOT devices in terms of instrumentation, but just supply chain services. It's a tsunami of new things. Limited by a lot of old school, either technical limitations on connectivity at the edge or just software. >> You know that in health care, there is a lot of time where a surgery room is ready with all the surgeons and the staff and the patient is not there because the person who is supposed to go get him in his room and bring to the surgery is actually late. And so we think that that's such a waste of time and money. >> Absolutely. >> Could be much better utilized. >> You could bring surge pricing in to the surgery room. (laughing) We're backed up, or hey I got low pricing, I got a price line ... But all joking aside, this is really important. This is like real value. High priced resources, idle in a hospital. There's probably a zillion examples of those. Okay, what's the low-hanging fruit that you guys see? When you start rolling out Mapwize. Is it just getting a physical footprint of it? Is it just a graphic rendering? Is the mashup piece? Is it visualization? What are some of the key things that you guys are doing, or have done to remove the blockers for adoption and create more movement towards that value? >> So what we see is really the first step is bring some wave finding, helping people navigate around the buildings. And so basically taking the old stock of technical floor plans that everybody has, that usually just a few architects use in a company. And being able to drag and drop that into a web platform. And from one day to another, making it available to a hundred percent of the people that actually live in that building on a daily basis. So that's really the first step we see. And then together with Cisco, being able to bring the location of the users. So that I have the same experience outside of the GPS as I have inside the building with the Wi-Fi infrastructure. >> It'd be great to know too, there's a lot of people streaming video around one access point. Might want to add another one. These kinds of things just are natural ideas that people would do. >> Yeah and where the bandwidth is the best, where the noise is the lowest, where potentially is the temperature higher, lower. Today in the flex office, people can choose to sit wherever they want. So what are the key reasons to choose one spot or the other? And I think there are a lot more value that we can bring to those as occupants. >> So you have here at Devnet Create 2019, you have a breakout, or had today a breakout and a workshop. Tell us about the workshop first in terms of the title, the conversations and some of the interesting conversations that you had with some of the participants. >> The workshop was about how to bring the link between the map and the more key infrastructure that you have. So potentially, even before anyone connects to a Wi-Fi, we're actually already showing him usually a portal, a captive portal where he can look in. And how we can add in that captive portal, already services. Like showing him, where is, on a map, how to get to any destination, potentially services that are around him. So that was the goal of the workshop. And it was great because everybody was saying directly in his industry. I had somebody from a university say this is exactly what we need as well for our campus. So I think it's something we can bring to much more industries. >> There's much more of a horizontal opportunity like you said, across industries. And you also had a breakout session. What did that dive into? >> The breakout session was specifically around location analytics. So it's completely different world, but it's about them using the location of the crow of every single device in the building and see how people move. Where do they go. And to understand the behavior of the people that are there. Just to give you an example, if you look at an event like this one, maybe the organizers would like to understand how much time people spend looking at the talk, looking at the workshop, getting around. So basically using all the data that's collected by the Wi-Fi, we can get a lot of analytics and numbers to better assess if the spaces are well organized. >> Making sure people are at their desks doing their job. (laughing) >> Oh no, no. No big brother. >> That's potentially the downside around it. It's something we need to be careful about. >> Innovation versus creepiness. It's always a trade off, privacy. >> It is a trade off and I think we need to be aware of when we allow it. When there is somebody working alone in a building, you actually do want to know where he is, because it's good for his safety. >> It's all over. We all have privacy problems. The GPS knows everything I'm doing here. Get over it, people. >> I think it's good to know which cases and to have opt-in. Like sometimes I want people to know where I am exactly, because that can actually help me. And I've other cases where I do not want it. So I think it's important that any developer who is building application with that data, is aware of that privacy issue and can know when to anonymize data, when not. >> Great stuff. >> Mathieu, thank you so much for joining John and me talking about Mapwize, what you're doing with Cisco. Really, really interesting technology. Maybe next year at Devnet Create you can tell us all of the analytic from this year. >> Yeah, absolutely. >> All right, we appreciate your time. >> Thank you so much. >> Thank you. >> For John Furrier, I'm Lisa Martin, live on the Cube from Cisco Devnet Create 2019. Thanks for watching.

>> Narrator: From San Francisco, it's theCUBE. Covering Samsung Developer Conference 2017. Brought to you by Samsung. (cheerful music) >> Welcome back everyone, live here from San Fransisco, Moscone West, at the Samsung Developer Conference, 2017 #SDC2017. I'm John Furrier, cohost of theCUBE, co-founder of Silicon Angle Media. My next guest, Hilary Karls, Senior Software Engineer at Uber. Great to have you on, welcome to theCUBE. >> Thank you for having me. >> Great to have a female engineer for Uber, pun intended. In all seriousness, thanks for coming out, appreciate it. >> Oh, my pleasure. >> Love talking tech here; Samsung obviously is huge with Android, that's what you do. What do you do with Uber? Let's get that out on the table. What's your role at Uber as an engineer? >> I'm an Android engineer, I work on UberEATS, which is our food delivery product. I've been at Uber for about three years now. So I've gotten to see UberEATS grow from just a tiny operations experiment, in LA, all the way up to being in over 120 cities and having its own app. >> Uber's got that great culture; trying new things. Love the iteration and our family uses the competitor, DoorDash, and I can't wait for UberEATS to come to Palo Alto. Is it in Palo Alto yet? >> Yeah, it is. >> I better try it out. Bring me a discount, can you send me a little discount code? >> Yeah, I can definitely send you a discount code. >> Okay good, got that out of the way. Got my free phone here from Samsung, as well. Thank you Samsung for the free phone. So let's talk about Samsung, obviously this is a developer's conference, you're on the front line, building the app on the Android side. >> Yeah >> Google was on stage yesterday so there it is, it's all out there, Samsung innovating with the handset. Great reviews on the new 8, great screen. This is an Apple-esque going on here. They're there, they got an iOT strategy, so they're bringing together lifestyle. >> Yeah. >> Okay, this is the new user experience. Okay, so has Android gone up? They got Bixby. >> They got Bixby, yeah. >> What's your experience with Android and developing in the environment? >> Well I've been developing on Android for about four or five years now, and it's wonderful. It's open, it enables you to actually go and build. Using more of the APIs and having more ability to connect into the phone itself. To be honest, I love it. It's one of those where you actually get to take your ideas and ship it out to a much broader range of people. >> Build things that are still very very beautiful and very usable to people. >> I was talking with Sam Ramji, who's heading up Cloud product management at Google, as well as, developer programs across Google. We were talking at VM World, and I know their conference is more Cloud oriented. >> Hmm Hmm >> Talking about the user experience and Google is hyper-focused on building open-sourced libraries. >> Hmm Hmm >> So Google is going to be contributing all this goodness, you got the tensor flow, you got all this innovations going on at Google, that's translating to the edge of the network, we're seeing that with Samsung. House devices are great, you got TVs that are known for that, but connecting the smart things is really their strategy. As a developer, how do you look at that landscape, because you're looking at now tons of open source goodness coming in, from Google and then the communities, Android leveling up on capability. >> Hmm hmm >> And with the open APIs, where do you try to navigate, how do you extract the signal from the noise in the community? >> Well basically, you look for whatever libraries are actually used very heavily by people that have latest commands. If it comes from something like from Google, or from other really strong reputed open source players, like Square, you'll end up seeing adoption of that a lot more. When you then go into internet of things, it becomes also like how you see community - the chicken and egg thing. Is this the best opportunity to go for right now? Is the community there, can I monetize this? How do you integrate it? >> Yeah, that's the big question, what's the integration? So let me ask you a question on the Android. In your opinion, Android, Apple IOS, leveled up, in terms of capability? >> Pretty much, yeah. >> What's the difference between IOS and the Android, if you could explain to someone that's knocking on the door of both developer communities. >> Well basically, I would go for who you were trying to go for first. Are you trying to target the U.S, and trying to target that higher end of consumer? Or are you trying to have a mass appeal? For a lot of small start-ups, I'd actually say go IOS first, it makes sense. But when you want to bring it to the global market that's when you really, really, really need Android. When you want to bring it to places around the world where there are more Androids than IOS, that's definitely something that just needs that core experience. >> Is there anything that Android has, because it seems to me that Android has a lot more unique opportunities to customize. >> Yes. >> I think that seems to appeal to developers. When I look at our data, we look at our audience, I'll see the general purpose, I call general purpose Apple because Apple is like fine jewelry. Everyone wants to have the high-end suits, and the high-end code, whatever. But, you don't have the flexibility because it's kind of a walled garden from Java's standpoint. You have the open garden with the Android, that community, their playing more in open source, you're seeing block chain, you're seeing all these kinds of cool communities. What are some of the things that Android offers in this open approach that you like? Is there things that jump out at you? >> Well a lot of it's the ability to get customized, to have better security controls, to have widgets on your home screen. From a developer's standpoint, to have more flexibility about when you ask for permissions vs. when you don't. Also, the richness of the notifications, we've had that for a while on Android. It's like you can do actions and have things animate and keep things like progress bars on there for quite some time and IOS is finally catching up to that. >> And you're happy with Android? >> Oh, very much so. >> Alright, so what's your take on this show at Samsung? What's your vibe on the show, feeling, they got some good stuff? When do they need to work on things? >> Ummm. >> Give me the positive review and then give me the critical what they can do better? >> Yeah, I think actually bringing everything together in a connected cloud makes a lot of sense. Developers don't really like fragmented APIs. If you have to actually go talk to five or six different services to get something done, that's a lot more effort and a lot more overhead of understanding of how to connect to each one. So bringing it all together in one place, especially if that can have the overhead of, handle the overhead, making it secure, and doing data storage, and all that stuff, makes a lot of sense. >> Awesome. Hilary, final question for ya, personal question, put you on the spot here. What's the coolest thing you've built this past couple of years? That you coded, could be anything. >> Ohhh. >> What's the coolest thing that you feel >> Personally? >> Yeah. >> Alright, so I guess it was a year and a half now, there was a team of four of us that build the new Android Eats app. Built it from scratch in about three and a half months It was a team that was magical and never happens in Silicon Valley. It was three women and a latino dude, and we shipped it. >> No way. >> Yeah. >> Three months? >> Yeah, three and a half months. Starting in September, shipping early. >> We're talking, on the drawing board, on the design, >> Yeah. Literally, start to end. First line of code in early September, end of code writing, like wrapping and shipping it up right before Christmas. >> That's the new format, three women and a latino dude. (laughing) Congratulations, anything you'd like to share with the audience about the development scene here, what you're thinking about, what you're passionate about? >> I really really loved the piece of using technology to build more human connection, better humanity. I thought that was amazing; that piece was really inspiring to me. >> This is the new lifestyle tech is coming. The consumerization, blending analog, and digital together. This is the new normal from fashion tech, to UberEats. Congratulations, thanks for coming on theCUBE, Hilary Karls, Senior Software Engineer at Uber. This is theCUBE's live coverage of Samsung Developer Conference 2017, in San Francisco. I'm John Furrier, we'll be back with more after this short break. (cheerful music)

(upbeat music) >> Announcer: Live from Los Angeles, it's theCUBE covering Open Source Summit, North America 2017, brought to you by the Linux Foundation, and the Red Hat. >> Okay, welcome back everyone. Live here in Los Angeles, is theCUBE's exclusive coverage of the Open Source Summit, North America. I'm John Furrier, your host, with my cohost, Stu Miniman with Wikibon. Our next guest is Ross Turk, Director of Evangelism at Red Hat. Welcome to theCUBE, good to see you again. >> Good to see you. >> So, evangelizing is now going to be super more important as Open Source Summit, formerly called The Linux Con, Linux kernel. So, Linux is really now the foundation. So, now all these new products are emerging, hence the new name Open Source Summit. You guys are in the middle of it. >> Ross: Mm-hmm. >> What's the themes that you guys are pumping out there right now from an evangelist standpoint? Give me the order of operations in terms of priorities. >> Well, gosh, we're trying to tell stories about how people operate infrastructure in today's modern world, right, which is a lot about making sure that, you know, dealing with ephemeral infrastructure, dealing with containerized applications, and that sort of thing. It gives a lot more flexibility to people who are doing modern operations. It's about applications that spill over across multiple machines and doing so in a way that doesn't require a lot of heavy lifting or wiring things up by hand. So, there's this whole modern operations experience thing we talk about, but we also talk about a modern developer experience. What does it mean to build applications today? And, of course, you combine those together it turns into Dev Ops, right. But, the large companies still work in these two separate worlds. But, people are building technology differently than they ever did in the past, and they're deploying it differently than they did in the past. So, there's lots of stories that can come out of that. >> Well, let's start with the story that we love. Stu and I were talking about the server list at the beginning because you have the Dev Ops movement certainly is going mainstream. You're seeing a lot of enterprises looking at that as viable. Now, they're operationalizing it, and they need to have that industrial strength Red Hat, Linux. But, now Kubernetes and Servalist, the younger developers, they just want an infrastructure as code. >> That seems to be a very hot story here, and Kubernetes server list is kind of in the hallway conversations. How do you guys bring that to bear? >> Well, I think that what Red Hat does is we give an operating environment that can sit underneath all of it with Rail and everything else we build that is stable and secure and reliable. And, you need that in order to have all of this chaos happening above it with developers deploying microservices and moving things around, and demands changing and all these other things, you need to have something really stable and reliable underneath that, something that you know can be if the applications and virtual machines and containers aren't long running, what sits underneath of them is long running, and it still needs to be stable and reliable. So, a lot of the work we've been doing for the past 20 years around Linux Engineering, I think, contributes to making this stable environment for a modern developer. >> Yeah, Ross, one of the challenges in scaling is usually I've got to worry things like storage. You know, state is there, you know data gravity is something we need to be concerned about. It's great to say ephemeral and I want everything anywhere, and, I can put it in this cloud or use it in that application, but at the end of the day it's tough to build some of these pieces. How's Red Hat helping there as containerization and scale, how does that fit into kind of this storage discussion moving on? >> It's a real struggle right, because you can talk to people and they say oh, every single one of the microservices held over and they scale out, and all this, and they talk about this really elaborate infrastructure like well, where is all your data being stored? Oh, it's sitting in Oracle, you know, so you find this sort of like dissonance between how data is managed and how applications are managed. At Red Hat, we believe that storage should be another microservice alongside all the other microservices make up and application. So, that's why we put a lot of engineering effort into making things like Ceph and Red Hat Gluster Storage work well alongside Open Shift so that a developer can provision storage as needed without having to go to an ops person, and that when that storage gets provisioned it's in containers alongside other containers that are providing the other things that your application needs. >> Software defined storage was the answer, it's the Holy Grail. We've heard software defined data center. We've been covering this also in the VM world, heard an awful lot about that. But, that still is a key part of the software, and now you have hardware stacks, so IOT and Cloud are opening up these new use cases for enterprises where whoa, we actually kind of didn't test that hardware with that software, so it's kind of interesting dynamic because software defined is still super important. What's your view on software defined storage, in particular, is that an answer, is it stable, what's your thoughts? >> Well, I think it's an answer, but it depends on what the question is, just to be kind of-- >> What is software defined storage? Let's start with that one. >> Well, so, what is software defined storage? Software defined storage is, okay, so I'll say it in more like what it isn't. >> The traditional storage, traditional storage solutions get deployed as appliances, which are vertically integrated hardware and software solutions that are built to do one thing, and to do that one thing well. And, that one thing is to store data. They're kind of like big refrigerator-sized things that you bring into your data center with a forklift and it's a big oepration, and then they provide storage for any number of applications. What software defined storage does is it implements those same services and those same capabilities, but it does it entirely in software. So, instead of being this vertically integrated software, hardware solution, you end up with software that lets you build it on any hardware, and that hardware can be physical hardware so you can build a storage cluster made up of 1,000 bare metal servers, or you could build that same cluster on a thousand VMs inside of a public cloud. So, in making storage no longer a hardware problem, like it used to be, I mean fundamentally it's a hardware problem, you get down bits are stored somewhere, but, the management of storage is no longer a hardware concern, it's a software concern, now, and that means it's a little bit more flexible. You can containerize it. You can deploy it in the public cloud. You can deploy it in VMs. You can deploy it on bare metal. So, that's what software defined storage is doing is it's changing things around, but it requires different skills. >> Come on Ross, I want a storageless environment, can we get on that? >> A storageless environment? Sure, I guess. Storage has become somebody else's problem at that point. >> Absolutely, how about, how is containers changing that whole discussion? You know, it took us like a decade to kind of get storage working in a virtualized environment, networking seems to be really tackling the container piece, storage seems a little further behind, you know, what're you seeing some of the big challenges there and how are we looking to solve that? >> Well, here there's when you look at containers and storage, there are really two things to consider. The first is how do you make storage such that a containerized environment can consume it easily, right. This is what at Red Hat we call container ready. So, we call a storage solution container ready, what it means that your container platform knows how to consume it. Most storage is container ready, all it takes is a Kubernetes volume driver to be container ready, and that's one half of it, and that's really, really important. It's the same kind of thing we had to do with virtualization, making sure every hypervisor could talk to every storage system. Now, we're making sure every container platform can talk to every storage system. That's important, but it's only half the puzzle, 'cause the other half is now that you have storage as a software thing, a distributed software thing, you can actually deploy that storage inside the same containers that you're using, that are driving the demand for that storage. So, it's this kind of weird, you know, snake eating it's own tail thing where you as a developer, let's say I'm deploying an application, I need a database, I need a web server, blah, blah, and a bunch of other things, and I need a scale out storage system, I can deploy that in containers just alongside everything else, and it uses the local storage of each of the container hosts to build that shared storage that then is used to provide services to other containerized applications. So, it's the ability to have storage in containers Which is really strange. We call that container native storage. >> It's interesting the markets going pretty crazy, so if you kind of take the Dev Ops and say assume for a minute infrastructure is programmable. >> Mm-hmm. >> But, then you look at the developer action right now on the App side, we've seen all kinds of new stuff Apple has their announcement today with the new iPhone 8. We've been covering that on siliconangle.com. Forbes has got great stories as well. New AR kit, so augmented reality is a huge deal, virtual reality obviously still hyped up, is still promised, those are going to require new chips. That's going to require consumer behavior change, so, the developers are staring at a different market than worrying about provisioning storage, right. So, but, these are now new pressures. New hardware, new opportunities, as a developer, advocate, and evangelist, and an industry participant, and user, how do you look at that, and how is that impacting the developer market because Androids got good stuff coming down, too, not just Apple, Samsung? >> Ross: Yeah. >> It's all multimedia, I mean. >> Well, what's interesting about AR kit is that if you go just back five years that same capability required a very, very particular type of phone, you know, like the project Tango stuff required all these depth cameras and like connect style stuff to do the AR kit, and Apple was able to solve a lot of that in software just using two cameras, right, and in software. And, I think that's really-- >> John: On a phone? >> On a phone, on a phone no less, and I think what's amazing about that is all of the capabilities that we walk around with in our pocket now were really hard to get a long time ago. >> Well, this is interesting, your point, let's stay on this because this really illustrates the point. AR kit, for example is proving that the iPhone now is smart enough and with software, enough horsepower to do that kind of thing, but that's replicable across all devices now as an IOT device. The Internet of Things is going to be a freight train coming down the tracks, security, endpoint security, whether it's, I mean all kinds of coolness, but yet threats are there. So, software has to do all this, right. So, how's that going to impact the cloud game, your business, you guys you have to move faster on hardening things, be more organic on the innovation side, not business-wise, but technical strategy. >> Well, I think a lot of it is enabling developers to work more quickly and build features more quickly, also, educating developers on the security and privacy ramifications of the things that they build because it's really easy to just go out in front and advance and innovate and forget about all of that stuff. So, it's about changing developer culture so that you consider security and privacy first, as opposed to later. And, also, maybe you want to consider storage as well if you're talking about machine learning or IOT and all of these types of things, you're -- >> Videos, I mean this is video, software rendering. That's a storage nightmare. >> It's all got to live somewhere, and once you put it in that place where it lives, it's really hard to move it. So, this is a thing you want to plan from the very beginning. >> And, I think that's what's cool about AI, too, and self-driving cars it's a consumer, you know, flashy, coolness that can say hey, this is happening. I mean how fast is happening, but the developer is now bringing it to the businesses and say, okay, we don't have an AR virtual reality strategy for our retail, for instance, you potentially could be out of business. So, these are the kind of thoughts that are going at the C-level that now are going into what used to be IT, but all of IT, how do you handle this? This is an architectural question, so your thoughts on that, because that seems to be a conversation we see a lot. Architectural that's going to solve problems today, not foreclose future opportunities. >> Well, it's cultural, too, inside of the company, like everywhere inside of a company there used to be Internet teams in companies, remember. We used to be like oh, go talk to the Internet team because something's wrong with the Web or whatever, now, there's no Internet team, everybody's the Internet team, Every single team in an organization is thinking about how to leverage the Internet to make their job more effective. The same is going to be true for everything that we're talking about, you know. Security, interestingly enough, so many people always thought security was somebody else's problem. but just this week, we were reminded that it's everybody's problem, hundreds of millions of people's problem, security. So, I think that as these things kind of advance-- >> John: Security first, and privacy first is critical. >> It is absolutely critical, and there used to be, I mean, I think at some point maybe there won't be a security team inside of a company because everybody's going to be the security team, but it's like everybody's the Internet team now, and I always felt the same way about open source communities. I thought there would never, you know, always everybody-- >> Well, people are ruling their own security now. You have these LifeLock or whatever they call them, these services for a password protection because you can't trust even all these databases that are out there. You have block chain with immutability, yeah, certainly the wallets are not yet, but I mean certainly this is where it might be a future scenario. >> Yeah, and I think for all of these things agility is going to be key. The ability to go down a path a certain distance and realize whoa I've run into a privacy problem, back up a little bit, continue down another path. I think that the faster we can make the development process, I think the less risky we make going into all these new frontiers. >> Yeah, Ross, one of the things we've really liked watching the last kind of five years or so is storage turning into a discussion of data and how can we leverage that data, real-time data, you know, decisions at the edge, analytics, what's exciting you the most about kind of the storage world these days? >> Oh boy. Well, you know, I just spent about five years in the storage infrastructure world, so a lot of what kind of kept me going day and night was saving people money, making things faster, making things easier, but also, giving storage platforms that were elastic enough to handle all of this really interesting stuff that happens on top of them. So, there's all kinds of new big data stacks that I find particularly interesting, a lot of the real time analysis stuff like Apache Spark and things like that. There's so much going into visualization right now, as well, how you handle large amounts of time series data and that sort of thing. There's been a lot of advancements in exactly that. Personally, I'm really excited lately in all the data of this stuff, all the ways you can extract meaning from all this data, you know, the ways that you can give it a business context that allows you to make better decisions with it. >> Not a lot of data conversations here at this conference as is open source software, but I mean data I mean I've said and I wrote a blog post in 2008 Dave always, Dave Olantho always jokes with me because I always reference it, I said data is the new development kit, meaning data is going to be part of the software development model, and it actually is with big data, but, you're not hearing a lot of it here because most people are talking about their communities, their projects, but the role of data is fundamental at the edge. >> Ross: Absolutely. >> And, so, how is that going to change some of these conversations and can data be developed on, and is data now part of the software development life cycle that's coming to fruition in the new way. >> Interesting, I think that's an interesting observation that as we see sort of Dev and Ops coming together, right, the world of the operator and the world of the developer coming together, I think we'll probably, at some point, see the world of the developer come together with the world of the data scientist because as I kind of wrack my brain I'm thinking okay, what type of future developer wouldn't have to be dealing with large amounts of data wouldn't have to have that kind of skill to be able to deal with it. So, I think we're going to start to see more software developers getting more involved in big data, machine learning, data analytics, and things like that for sure. >> Well, either way, this open source growth that's coming is going to be exponential. Data is already there. I mean we have a joke in our office software is eating the world as Mark Andreasen would say years ago, but, data is eating software. So, in terms of how you look at it someone's eating somebody, but, this becomes interesting for the IOT developer, or the industrial developer. Those systems were never connected to IT in the past. It was like they ran their own stuff from their own terminals. >> And, there's this idea that everybody's heard that data has gravity, right. And, I actually was talking to somebody about this and they said, well, actually the data has inertia, and I'm like, no, that's not really it 'cause once it's moving it's not hard to stop it. The idea that data has gravity means that let's say I'm putting together this new IOT application, or whatever, I'm gathering data from a bunch of sensors or whatever, and I've got the data in that place. Now, having all that data in that place is more meaningful to me than most of the software that I wrote. You know, it's like that is the value, the kernel of the data is there, and data having gravity means that it's hard to move once it's in a certain place, but, it also means that it attracts workloads to it, right. So, it used to be that software was king, and software created data and managed data, and now data is king, and it brings software to it, I think. >> I totally agree with you, and I think they might even call this the open data summit soon, but it's beyond open source. Now, this is going to be great. They work hand in hand. Software and data are going to be great. Stu what's your thoughts on the role that data's not being talked much here? >> Yeah, John at Amazon weighed in last year. When we talked to Andy Jassy it was the customers were the flywheel, and I think data's going to be that next flywheel of really feeding into that data gravity discussion that you were having, Ross. You know, when Hadoop came out it was like oh, we're going to bring the code to the data. Well, we know if I'm going to have more data I'm going to have my data sources, I'm going to have third party data sources that I want to be able to work and interact with those, so, data absolutely huge opportunities there, and the companies that can leverage that and get more value out of it is going to be a-- >> Well, we already see it's a competitive advantage, no doubt, but it's the privacy issue still the big debate like we know in our immediate businesses. Look at Facebook, I've got a free App I get to see all my friends' photos, their vacations, everyone's living a great life on Facebook, but, then all of a sudden I give my data away for free for the privilege to use that App, but all the sudden they start injecting fake news at me. I don't want that anymore, and you're still making money off of my data, so that's interesting. Facebook makes money off of my data. >> Yeah, that's-- >> That's my contract with them. >> Yeah, If you ask what their asset is, one person might think it's traffic, you know, or eyeballs, but, I think it's data. >> So, they're using data, I might not like it, so that might be an opportunity for somebody else so your point Stu, so if you start thinking about it differently, data decisions are going to be an architectural challenge. >> Yeah, absolutely. I think enterprise architecture thinking, even today, you're seeing enterprise architects thinking more and more and more about data than they have in the past. >> Ross, what do you think about the show, final word in the segment, what's going on Open Source Summit, share with the folks that are watching? >> The vibe here, it's now a new name, but it's still the same game, multiple events come together. >> Yeah, multiple events together. I like Open Source Summit as a name. I think it's a good name. It's properly named for what's going on here. It's been an interesting experience for me because I've been in this community for a really long time. So, I come here and I run into all kinds of old friends, the hallway track's always a good track for me. The content is fantastic, but the hallway track is always really good, and I can't think of anywhere else where you can go and get this selection of people, right. You have people who're working on all layers of the problem, and they can all come together and talk. So, I don't know-- >> It's really a cross-fertilization, cross-pollination, whatever word you want to use. I think this event's going to be in the 30,000 pretty quickly. I mean this is going to be. Well, if you look at the growth, the numbers, you know, presented on stage, Jim Zemlon, was pointing out the growth, by 2026, 400 million libraries. I mean people still think that's underestimated. >> Yeah. >> So, that's a lot of growth. >> I think it could get there, and I think these folks organize great shows, so I look forward to seeing them scale up to 30,000. >> Ross, thanks for your commentary, appreciate the perspective, and the insight here on theCUBE. >> Thank you. >> Thanks for joining us. This is theCUBE live coverage from Open Source Summit, North America. I'm John, for Stu Miniman, back with more after this short break. (upbeat music)