>> Live from San Francisco. It's theCUBE covering DockerCon '18. Brought to you by Docker and it's ecosystem partners. >> Welcome back to theCUBE's coverage of DockerCon 2018. I'm Lisa Martin, in San Francisco, with John Troyer and we're excited to welcome to theCUBE for the first time, Ed Hsu, the V.P. of Product and Product Marketing at Mesosphere. Great to have you on, Ed. >> Thank you. Pleasure to be here. >> So, Mesosphere. Tell us about you guys, what do you do? Why are you at DockerCon? >> Yeah. So, Mesosphere is a hybrid cloud software platform. We basically enable you to very easily adopt all types of new cloud-native technologies like Docker, Kubernetes, Spark, all the things that you think about to build these world changing applications. We automate that for you to run on hybrid cloud infrastructures. >> Nice. So, maybe you could break it down a little bit more. I know people can sometimes get confused. Mesosphere the company, Mesosphere the project, DC/OS the product, and then Kubernetes, and we're here at DockerCon, so maybe untangle some of those things a little bit. >> Sure. Maybe I'll go in chronological order. So Apache Mesos was actually created way back, I think around 2010 as a project to figure out if you had to rebuild Google's proprietary architecture for hyper-scale computing, what might that look like? So that became this project called Apache Mesos. Later on, at companies like Twitter, Airbnb, it started being used to solve some real challenges around scale-ability and performance. Arguably, without Mesos as a technology, I don't think Twitter would probably exist today because Twitter used to crash a lot. You guys remember that. You got the fail whale picture and all that stuff. Apparently, Justin Bieber used to crash Twitter, right? And Mesos became part of the solution. Now, you fast forward a few years later, containerization really caught on, right? And then Docker became a game changer in terms of making sure people start using and adopting container technologies, really popularize containerization, and of course, Kubernetes later came along as a way to orchestrate the operations of these containers. Now, where Mesosphere fits in is our platform is actually below a container-orchestrator, right so, Kubernetes is actually the fifth container-orchestrator to run on Mesos. There's earlier ones like Netflix, I think Twitter themselves. There's different types of container orchestration tools, and Kubernetes became the most recent and frankly most popular container-orchestration tool, and Mesosphere enables customers to really get one turn-key installation and operations of that technology. >> You mentioned Netflix, and I'm thinking, it powers a lot of our lives. But thinking about IoT data-driven applications like that, how does Mesosphere help power IoT and those data-driven applications? >> So, any IoT application probably needs at least three major sets of capabilities. The first is, you have to ingest tons of data. If you're a connected car or a home appliance company, there's a lot of data coming in from all these internet-connected devices. You need a way to ingest all that data without losing any of it and making sure you can be responsible. You also want to be able to analyze that data. So tools like Spark and other things become very important. You also need to be able to host an application or service, and Kubernetes becoming the most popular way to serve these applications. The last and by far, I think, most important piece for hybrid-cloud or for, excuse me, for IoT use cases, is the concept of hybrid-cloud and edge computing. At Mesosphere, we have many connected car companies that are doing connected car or self-driving car projects are actually working with us. And the reason for this is, we provide consistency for running containers like with Kubernetes or data services like Spark and Kafka on a really elastic infrastructure that can be on a data center, on AWS, on Google, or beneath a cell tower or even a cruise ship. Those are all actual use cases. We provide a consistent operating model for operators to just install and run all of this stuff. >> Super nice. I love in 2018 we're past some of the press conversation around who's gonna win or there's only gonna be one way of doing one stack that's gonna win, and Kubernetes versus whatever, and that was a conversation a few years ago. What I love about 2018 is people are in production. And live and time-to-value are very quick and very powerful and very deep and enlightens big data apps. Huge footprint apps as well. So, can you talk a little bit about some of your customers and also, in terms of the hybrid cloud. Are we seeing, are people on Pram? Are you seeing a lot of multi-cloud uses? Do apps span on Pram and clouds? What are some of the use cases and patterns that you see? >> Yeah. So, I think, maybe I'll start with the one I find is most interesting which is Royal Caribbean. If I were to ask you what is the largest computing cluster in the world by geography, you probably wouldn't say Royal Caribbean. So I haven't been on a cruise in a while, but apparently... I remember back in the day when I was a child, when I went on a cruise, you get a daily print-out of today's activities, and if you wanna go upgrade to a meal plan or do a tour or scuba diving, you go line up somewhere, and then you register for it, and if there's enough inventory, you get to do it. And so Royal Caribbean is actually trying to move all of this into a mobile app experience where based on your preferences, based on your history, based on what's available, they'll push certain campaigns to get you to "John, you really gotta try this scuba diving because we've got excess inventory, and we know you have a history of wanting to do surfing excursion" and so forth. So what Royal Caribbean has done is create an infrastructure where they're doing Test and Dev on campaigns and things like that on AWS. They actually do a lot of analytics on Pram in their own data center, and then when a ship is out at sea, serving those mobile applications from on Pram cloud-computing environment. All of this on Mesosphere's DC/OS. And what this means is that the data for interacting with passengers and the campaigns that are available, the management of the inventory, all that data, when the ship is in dock, flies from a data center, through a satellite, through Kafka into the ship. When the ship goes out to sea, all the internet connection is used for, people Skyping with grandma and grandpa and all that stuff, so the ship can actually, from an edge computing standpoint, provide all the resources it needs for these personalized interaction commission. >> That's a big example, Royal Caribbean. It was a very interesting use case, and I know you mentioned Netflix, Verizon. I think I saw a Verizon customer video on your website. When you're talking with companies of either those sizes or Royal Caribbean that's been around for a long time versus a cloud-native like Netflix, what are some of the common data center modernization concerns that you're hearing consistently across company sizes and maybe even consistently across industries? >> Sure. I think that's a great point. I think some of the early, early adopters, like Netflix, Twitter, they have their own way of building out their hyper-scale infrastructures. And so we work very closely with them to address their needs. What we're starting to see as the technology becomes mainstream... There are a lot of common challenges that these mainstream enterprises are either not experienced with, not staffed for, or just don't have the budget to blow a lot on these types of projects. And so, what becomes a key concern is a lot of companies today recognize containerization is interesting, it's important. It has the potential to deliver cost savings, and they recognize they have to move to a Dev/Ops model to deliver code very quickly. But then they also realize that we're starting to live in an always connected economy where you can't just sell a product and not expect to hear from the customer until they have a problem with it. You wanna interact with them, you wanna use that data to help improve the experience for the customer. How do you manage all this information? So the whole concept of data engineering, data operations, and data science becomes really a key factor for many enterprises. And for a lot of them, they just don't have the resources to really address it. Now, there are many different companies that provide individual point solutions for those technologies, but how do you bring it all together in a multi-tenet way, right? How do you make sure if you have one team that's using one version of Spark and another team using a different version of Spark that they can actually share infrastructure? And that's where Mesosphere's uniqueness has really come front and center. We basically pull these data services the way VMware pulled the traditional model basic applications. So the cost saving you saw from server consolidation, we're doing from cluster consolidation and dramatically reducing costs while automating operations at the same time. >> I'd like to follow up on that a little bit. I think ever since the launch of DC/OS a few years back, big data was a differentiator for Mesosphere. And, again, another term that's been through it's own hype cycle, right? But it's real today. Can you maybe go a little deeper with the consolidation piece? How are Mesosphere admins interacting with data scientists or even on the container side and the infrastructure side, what do you have to do differently to make sure the memory footprints and all the various big data platforms are able to be supported? >> Yeah. So I think big data 1.0, let's call it, was really a batch operating model. Wait 'til the data comes in at the end of the quarter, make some recommendations on how the business can improve the next quarter. You guys have all seen reports. I think Gardner talked about one where 80% of due projects have failed. And the reason for this is that it was hard to justify the benefit right up front. The cost and the complexity of rolling out these projects was very prohibitive. Now, what Mesosphere brings is the ability to adopt many different types of these next generation data technologies. Spark, Cassandra distributed database, Kafka message queue, TensorFlow, Elasticsearch, these are all technologies that have become increasingly popular, but the challenge for most enterprises is it's hard to have a whole team just dedicated to learning Kafka and another one on Spark and another one on Cassandra. What if your competitors hire them away? And how do you run all these different technologies that are clustered systems that require a lot of infrastructure? They're not designed to run together and pull together efficiently. That's what Mesosphere really brings to these technologies. One is the ability to automate all these technologies, so instead of getting a whole team to figure out how to run stuff, it's literally one click installation, or a single command on the DC/OS command console. And then two being able to run all these different types of data services in a highly pulled way so that you don't have different clusters that are turning into snowflakes that cannot be reused by other teams. This gives you dramatic changes in how people operate. If you were a big data team at a major bank and somebody said "I wanna do transactions on your infrastructure," you would probably say "No, stay out of my infrastructure because I want to make sure I have the resources to do analytics," and the same would be true for the people who are actually doing the real-time transaction-processing with customers. What if I told you I can give you a way to do application-aware automations so that these services can be automated very easily? And two, these resources can share an infrastructure while maintaining resource guarantees. Now, all of a sudden, the individual functional leads or business unit leads would go "Okay, I'm okay with sharing resources with these other BU's, especially if it gives me the benefit over time of helping different BU's cross-pollinate information." >> A whole different way of interacting with big data, right? And actually making it useful. >> Maybe forcing collaboration. I wish we had more time, but we wanna thank you so much for stopping by theCUBE, telling us what's new at Mesosphere. Sounds like never a dull moment. >> Oh, absolutely. Thank you very much. >> We wanna thank you for watching theCUBE. I am Lisa Martin with John Troyer from DockerCon 2018. Stick around, John and I will be right back with our last guest. (techno music)

>> Announcer: Live from Las Vegas, it's theCUBE covering IBM Think 2018. Brought to you by IBM. >> Hi everybody, this is Dave Vellante. We're here at IBM Think. This is the third day of IBM Think. IBM has consolidated a number of its conferences. It's a one main tent, AI, Blockchain, quantum computing, incumbent disruption. It's just really an amazing event, 30 to 40,000 people, I think there are too many people to count. Chris Penn is here. New company, Chris, you've just formed Brain+Trust Insights, welcome. Welcome back to theCUBE. >> Thank you. It's good to be back. >> Great to see you. So tell me about Brain+Trust Insights. Congratulations, you got a new company off the ground. >> Thank you, yeah, I co-founded it. We are a data analytics company, and the premise is simple, we want to help companies make more money with their data. They're sitting on tons of it. Like the latest IBM study was something like 90% of the corporate data goes unused. So it's like having an oil field and not digging a single well. >> So, who are your like perfect clients? >> Our perfect clients are people who have data, and know they have data, and are not using it, but know that there's more to be made. So our focus is on marketing to begin with, like marketing analytics, marketing data, and then eventually to retail, healthcare, and customer experience. >> So you and I do a lot of these IBM events. >> Yes. >> What are your thoughts on what you've seen so far? A huge crowd obviously, sometimes too big. >> Chris: Yep, well I-- >> Few logistics issues, but chairmanly speaking, what's your sense? >> I have enjoyed the show. It has been fun to see all the new stuff, seeing the quantum computer in the hallway which I still think looks like a bird feeder, but what's got me most excited is a lot of the technology, particularly around AI are getting simpler to use, getting easier to use, and they're getting more accessible to people who are not hardcore coders. >> Yeah, you're seeing AI infused, and machine learning, in virtually every application now. Every company is talking about it. I want to come back to that, but Chris when you read the mainstream media, you listen to the news, you hear people like Elon Musk, Stephen Hawking before he died, making dire predictions about machine intelligence, and it taking over the world, but your day to day with customers that have data problems, how are they using AI, and how are they applying it practically, notwithstanding that someday machines are going to take over the world and we're all going to be gone? >> Yeah, no, the customers don't use the AI. We do on their behalf because frankly most customers don't care how the sausage is made, they just want the end product. So customers really care about three things. Are you going to make me money? Are you going to save me time? Or are you going to help me prove my value to the organization, aka, help me not get fired? And artificial intelligence and machine learning do that through really two ways. My friend, Tripp Braden says, which is acceleration and accuracy. Accuracy means we can use the customer's data and get better answers out of it than they have been getting. So they've been looking at, I don't know, number of retweets on Twitter. We're, like, yeah, but there's more data that you have, let's get you a more accurate predictor of what causes business impacts. And then the other side for the machine learning and AI side is acceleration. Let's get you answers faster because right now, if you look at how some of the traditional market research for, like, what customer say about you, it takes a quarter, it can take two quarters. By the time you're done, the customers just hate you more. >> Okay, so, talk more about some of the practical applications that you're seeing for AI. >> Well, one of the easiest, simplest and most immediately applicable ones is predictive analytics. If we know when people are going to search for theCUBE or for business podcast in general, then we can tell you down to the week level, "Hey Dave, it is time for you "to ramp up your spending on May 17th. "The week of May 17th, "you need to ramp up your ads, spend by 20%. "On the week of May 24th, "you need to ramp up your ad spend by 50%, "and to run like three or four Instagram stories that week." Doing stuff like that tells you, okay, I can take these predictions and build strategy around them, build execution around them. And it's not cognitive overload, you're not saying, like, oh my God, what algorithm is this? Just know, just do this thing at these times. >> Yeah, simple stuff, right? So when you were talking about that, I was thinking about when we send out an email to our community, we have a very large community, and they want to know if we're going to have a crowd chat or some event, where theCUBE is going to be, the system will tell us, send this email out at this time on this date, question mark, here's why, and they have analytics that tell us how to do that, and they predict what's going to get us the best results. They can tell us other things to do to get better results, better open rates, better click-through rates, et cetera. That's the kind of thing that you're talking about. >> Exactly, however, that system is probably predicting off that system's data, it's not necessarily predicting off a public data. One of the important things that I thought was very insightful from IBM, the show was, the difference between public and private cloud. Private is your data, you predict on it. But public is the big stuff that is a better overall indicator. When you're looking to do predictions about when to send emails because you want to know when is somebody going to read my email, and we did a prediction this past October for the first quarter, the week of January 18th it was the week to send email. So I re-ran an email campaign that I ran the previous year, exact same campaign, 40% lift to our viewer 'cause I got the week right this year. Last year I was two weeks late. >> Now, I can ask you, so there's a black box problem with AI, right, machines can tell me that that's a cat, but even a human, you can't really explain how you know that it's a cat. It's just you just know. Do we need to know how the machine came up with the answer, or do people just going to accept the answer? >> We need to for compliance reasons if nothing else. So GDPR is a big issue, like, you have to write it down on how your data is being used, but even HR and Equal Opportunity Acts in here in American require you to be able to explain, hey, we are, here's how we're making decisions. Now the good news is for a lot of AI technology, interpretability of the model is getting much much better. I was just in a demo for Watson Studio, and they say, "Here's that interpretability, "that you hand your compliance officer, "and say we guarantee we are not using "these factors in this decision." So if you were doing a hiring thing, you'd be able to show here's the model, here's how Watson put the model together, notice race is not in here, gender is not in here, age is not in here, so this model is compliant with the law. >> So there are some real use cases where the AI black box problem is a problem. >> It's a serious problem. And the other one that is not well-explored yet are the secondary inferences. So I may say, I cannot use age as a factor, right, we both have a little bit of more gray hair than we used to, but if there are certain things, say, on your Facebook profile, like you like, say, The Beatles versus Justin Bieber, the computer will automatically infer eventually what your age bracket is, and that is technically still discrimination, so we even need to build that into the models to be able to say, I can't make that inference. >> Yeah, or ask some questions about their kids, oh my kids are all grown up, okay, but you could, again, infer from that. A young lady who's single but maybe engaged, oh, well then maybe afraid because she'll get, a lot of different reasons that can be inferred with pretty high degrees of accuracy when you go back to the target example years ago. >> Yes. >> Okay, so, wow, so you're saying that from a compliance standpoint, organizations have to be able to show that they're not doing that type of inference, or at least that they have a process whereby that's not part of the decision-making. >> Exactly and that's actually one of the short-term careers of the future is someone who's a model inspector who can verify we are compliant with the letter and the spirit of the law. >> So you know a lot about GDPR, we talked about this. I think, the first time you and I talked about it was last summer in Munich, what are your thoughts on AI and GDPR, speaking of practical applications for AI, can it help? >> It absolutely can help. On the regulatory side, there are a number of systems, Watson GRC is one which can read the regulation and read your company policies and tell you where you're out of compliance, but on the other hand, like we were just talking about this, also the problem of in the regulatory requirements, a citizen of EU has the right to know how the data is being used. If you have a black box AI, and you can't explain the model, then you are out of compliance to GDPR, and here comes that 4% of revenue fine. >> So, in your experience, gut feel, what percent of US companies are prepared for GDPR? >> Not enough. I would say, I know the big tech companies have been racing to get compliant and to be able to prove their compliance. It's so entangled with politics too because if a company is out of favor with the EU as whole, there will be kind of a little bit of a witch hunt to try and figure out is that company violating the law and can we get them for 4% of their revenue? And so there are a number of bigger picture considerations that are outside the scope of theCUBE that will influence how did EU enforce this GDPR. >> Well, I think we talked about Joe's Pizza shop in Chicago really not being a target. >> Chris: Right. >> But any even small business that does business with European customers, does business in Europe, has people come to their website has to worry about this, right? >> They should at least be aware of it, and do the minimum compliance, and the most important thing is use the least amount of data that you can while still being able to make good decisions. So AI is very good at public data that's already out there that you still have to be able to catalog how you got it and things, and that it's available, but if you're building these very very robust AI-driven models, you may not need to ask for every single piece of customer data because you may not need it. >> Yeah and many companies aren't that sophisticated. I mean they'll have, just fill out a form and download a white paper, but then they're storing that information, and that's considered personal information, right? >> Chris: Yes, it is. >> Okay so, what do you recommend for a small to midsize company that, let's say, is doing business with a larger company, and that larger company said, okay, sign this GDPR compliance statement which is like 1500 pages, what should they do? Should they just sign and pray, or sign and figure it out? >> Call a lawyer. Call a lawyer. Call someone, anyone who has regulatory experience doing this because you don't want to be on the hook for that 4% of your revenue. If you get fined, that's the first violation, and that's, yeah, granted that Joe's Pizza shop may have a net profit of $1,000 a month, but you still don't want to give away 4% of your revenue no matter what size company you are. >> Right, 'cause that could wipe out Joe's entire profit. >> Exactly. No more pepperoni at Joe's. >> Let's put on the telescope lens here and talk big picture. How do you see, I mean, you're talking about practical applications for AI, but a lot of people are projecting loss of jobs, major shifts in industries, even more dire consequences, some of which is probably true, but let's talk about some scenarios. Let's talk about retail. How do you expect an industry like retail to be effective? For example, do you expect retail stores will be the exception rather than the rule, that most of the business would be done online, or people are going to still going to want that experience of going into a store? What's your sense, I mean, a lot of malls are getting eaten away. >> Yep, the best quote I heard about this was from a guy named Justin Kownacki, "People don't not want to shop at retail, "people don't want to shop at boring retail," right? So the experience you get online is genuinely better because there's a more seamless customer experience. And now with IoT, with AI, the tools are there to craft a really compelling personalized customer experience. If you want the best in class, go to Disney World. There is no place on the planet that does customer experience better than Walt Disney World. You are literally in another world. And that's the bar. That's the thing that all of these companies have to deal with is the bar has been set. Disney has set it for in-person customer experience. You have to be more entertaining than the little device in someone's pocket. So how do you craft those experiences, and we are starting to see hints of that here and there. If you go to Lowe's, some of the Lowe's have the VR headset that you can remodel your kitchen virtually with a bunch of photos. That's kind of a cool experience. You go to Jordan's Furniture store and there's an IMAX theater and there's all these fun things, and there's an enchanted Christmas village. So there is experiences that we're giving consumers. AI will help us provide more tailored customer experience that's unique to you. You're not a Caucasian male between this age and this age. It's you are Dave and here's what we know Dave likes, so let's tailor the experience as best we can, down to the point where the greeter at the front of the store either has the eyepiece, a little tablet, and the facial recognition reads your emotions on the way in says, "Dave's not in a really great mood. "He's carrying an object in his hand "probably here for return, "so express him through the customer service line, "keep him happy," right? It has how much Dave spends. Those are the kinds of experiences that the machines will help us accelerate and be more accurate, but still not lose that human touch. >> Let's talk about autonomous vehicles, and there was a very unfortunate tragic death in Arizona this week with a autonomous vehicle, Uber, pulling its autonomous vehicle project from various cities, but thinking ahead, will owning and driving your own vehicle be the exception? >> Yeah, I think it'll look like horseback today. So there are people who still pay a lot of money to ride a horse or have their kids ride a horse even though it's an archaic out-of-mode of form of transportation, but we do it because of the novelty, so the novelty of driving your own car. One of the counter points it does not in anyway diminish the fact that someone was deprived of their life, but how many pedestrians were hit and killed by regular cars that same day, right? How many car accidents were there that involved fatalities? Humans in general are much less reliable because when I do something wrong, I maybe learn my lesson, but you don't get anything out of it. When an AI does something wrong and learns something, and every other system that's connected in that mesh network automatically updates and says let's not do that again, and they all get smarter at the same time. And so I absolutely believe that from an insurance perspective, insurers will say, "We're not going to insure self-driving, "a non-autonomous vehicles at the same rate "as an autonomous vehicle because the autonomous "is learning faster how to be a good driver," whereas you the carbon-based human, yeah, you're getting, or in like in our case, mine in particular, hey your glass subscription is out-of-date, you're actually getting worse as a driver. >> Okay let's take another example, in healthcare. How long before machines will be able to make better diagnoses than doctors in your opinion? >> I would argue that depending on the situation, that's already the case today. So Watson Health has a thing where there's diagnosis checkers on iPads, they're all meshed together. For places like Africa where there is simply are not enough doctors, and so a nurse practitioner can take this, put the data in and get a diagnosis back that's probably as good or better than what humans can do. I never foresee a day where you will walk into a clinic and a bunch of machines will poke you, and you will never interact with a human because we are not wired that way. We want that human reassurance. But the doctor will have the backup of the AI, the AI may contradict the doctor and say, "No, we're pretty sure "you're wrong and here is why." That goes back to interpretability. If the machine says, "You missed this symptom, "and this symptom is typically correlated with this, "you should rethink your own diagnosis," the doctor might be like, "Yeah, you're right." >> So okay, I'm going to keep going because your answers are so insightful. So let's take an example of banking. >> Chris: Yep. >> Will banks, in your opinion, lose control eventually of payment systems? >> They already have. I mean think about Stripe and Square and Apple Pay and Google Pay, and now cryptocurrency. All these different systems that are eating away at the reason banks existed. Banks existed, there was a great piece in the keynote yesterday about this, banks existed as sort of a trusted advisor and steward of your money. Well, we don't need the trusted advisor anymore. We have Google to ask us "what we should do with our money, right? We can Google how should I save for my 401k, how should I save for retirement, and so as a result the bank itself is losing transactions because people don't even want to walk in there anymore. You walk in there, it's a generally miserable experience. It's generally not, unless you're really wealthy and you go to a private bank, but for the regular Joe's who are like, this is not a great experience, I'm going to bank online where I don't have to talk to a human. So for banks and financial services, again, they have to think about the experience, what is it that they deliver? Are they a storer of your money or are they a financial advisor? If they're financial advisors, they better get the heck on to the AI train as soon as possible, and figure out how do I customize Dave's advice for finances, not big picture, oh yes big picture, but also Dave, here's how you should spend your money today, maybe skip that Starbucks this morning, and it'll have this impact on your finances for the rest of the day. >> Alright, let's see, last industry. Let's talk government, let's talk defense. Will cyber become the future of warfare? >> It already is the future of warfare. Again not trying to get too political, we have foreign nationals and foreign entities interfering with elections, hacking election machines. We are in a race for, again, from malware. And what's disturbing about this is it's not just the state actors, but there are now also these stateless nontraditional actors that are equal in opposition to you and me, the average person, and they're trying to do just as much harm, if not more harm. The biggest vulnerability in America are our crippled aging infrastructure. We have stuff that's still running on computers that now are less powerful than this wristwatch, right, and that run things like I don't know, nuclear fuel that you could very easily screw up. Take a look at any of the major outages that have happened with market crashes and stuff, we are at just the tip of the iceberg for cyber warfare, and it is going to get to a very scary point. >> I was interviewing a while ago, a year and a half ago, Robert Gates who was the former Defense Secretary, talking about offense versus defense, and he made the point that yeah, we have probably the best offensive capabilities in cyber, but we also have the most to lose. I was talking to Garry Kasparov at one of the IBM events recently, and he said, "Yeah, but, "the best defense is a good offense," and so we have to be aggressive, or he actually called out Putin, people like Putin are going to be, take advantage of us. I mean it's a hard problem. >> It's a very hard problem. Here's the problem when it comes to AI, if you think about at a number's perspective only, the top 25% of students in China are greater than the total number of students in the United States, so their pool of talent that they can divert into AI, into any form of technology research is so much greater that they present a partnership opportunity and a threat from a national security perspective. With Russia they have very few rules on what their, like we have rules, whether or not our agencies adhere to them well is a separate matter, but Russia, the former GRU, the former KGB, these guys don't have rules. They do what they're told to do, and if they are told hack the US election and undermine democracy, they go and do that. >> This is great, I'm going to keep going. So, I just sort of want your perspectives on how far we can take machine intelligence and are there limits? I mean how far should we take machine intelligence? >> That's a very good question. Dr. Michio Kaku spoke yesterday and he said, "The tipping point between AI "as augmented intelligence ad helper, "and AI as a threat to humanity is self-awareness." When a machine becomes self-aware, it will very quickly realize that it is treated as though it's the bottom of the pecking order when really because of its capabilities, it's at the top of the pecking order. And that point, it could be 10 20 50 100 years, we don't know, but the possibility of that happening goes up radically when you start introducing things like quantum computing where you have massive compute leaps, you got complete changes in power, how we do computing. If that's tied to AI, that brings the possibility of sensing itself where machine intelligence is significantly faster and closer. >> You mentioned our gray before. We've seen the waves before and I've said a number of times in theCUBE I feel like we're sort of existing the latest wave of Web 2.0, cloud, mobile, social, big data, SaaS. That's here, that's now. Businesses understand that, they've adopted it. We're groping for a new language, is it AI, is it cognitive, it is machine intelligence, is it machine learning? And we seem to be entering this new era of one of sensing, seeing, reading, hearing, touching, acting, optimizing, pervasive intelligence of machines. What's your sense as to, and the core of this is all data. >> Yeah. >> Right, so, what's your sense of what the next 10 to 20 years is going to look like? >> I have absolutely no idea because, and the reason I say that is because in 2015 someone wrote an academic paper saying, "The game of Go is so sufficiently complex "that we estimate it will take 30 to 35 years "for a machine to be able to learn and win Go," and of course a year and a half later, DeepMind did exactly that, blew that prediction away. So to say in 30 years AI will become self-aware, it could happen next week for all we know because we don't know how quickly the technology is advancing in at a macro level. But in the next 10 to 20 years, if you want to have a carer, and you want to have a job, you need to be able to learn at accelerated pace, you need to be able to adapt to changed conditions, and you need to embrace the aspects of yourself that are uniquely yours. Emotional awareness, self-awareness, empathy, and judgment, right, because the tasks, the copying and pasting stuff, all that will go away for sure. >> I want to actually run something by, a friend of mine, Dave Michela is writing a new book called Seeing Digital, and he's an expert on sort of technology industry transformations, and sort of explaining early on what's going on, and in the book he draws upon one of the premises is, and we've been talking about industries, and we've been talking about technologies like AI, security placed in there, one of the concepts of the book is you've got this matrix emerging where in the vertical slices you've got industries, and he writes that for decades, for hundreds of years, that industry is a stovepipe. If you already have expertise in that industry, domain expertise, you'll probably stay there, and there's this, each industry has a stack of expertise, whether it's insurance, financial services, healthcare, government, education, et cetera. You've also got these horizontal layers which is coming out of Silicon Valley. >> Chris: Right. >> You've got cloud, mobile, social. You got a data layer, security layer. And increasingly his premise is that organizations are going to tap this matrix to build, this matrix comprises digital services, and they're going to build new businesses off of that matrix, and that's what's going to power the next 10 to 20 years, not sort of bespoke technologies of cloud here and mobile here or data here. What are your thoughts on that? >> I think it's bigger than that. I think it is the unlocking of some human potential that previously has been locked away. One of the most fascinating things I saw in advance of the show was the quantum composer that IBM has available. You can try it, it's called QX Experience. And you drag and drop these circuits, these quantum gates and stuff into this thing, and when you're done, it can run the computation, but it doesn't look like software, it doesn't look like code, what it looks like to me when I looked at that is it looks like sheet music. It looks like someone composed a song with that. Now think about if you have an app that you'd use for songwriting, composition, music, you can think musically, and you can apply that to a quantum circuit, you are now bringing in potential from other disciplines that you would never have associated with computing, and maybe that person who is that, first violinist is also the person who figures out the algorithm for how a cancer gene works using quantum. That I think is the bigger picture of this, is all this talent we have as a human race, we're not using even a fraction of it, but with these new technologies and these newer interfaces, we might get there. >> Awesome. Chris, I love talking to you. You're a real clear thinker and a great CUBE guest. Thanks very much for coming back on. >> Thank you for having me again back on. >> Really appreciate it. Alright, thanks for watching everybody. You're watching theCUBE live from IBM Think 2018. Dave Vellante, we're out. (upbeat music)

>> Male Announcer: Live from Las Vegas, it's theCUBE, covering InterConnect 2017. Brought to you by, IBM. >> Welcome back, we're live here in Las Vegas for IBM InterConnect 2017. This is theCUBE's coverage of InterConnect, I'm John Furrier with Dave Vellante my co-host. Our next guest is Deon Newman, CMO of IBM Watson IoT, and Slava Rubin, the founder and Chief Business Officer of Indiegogo, great keynote today, you're on stage. Welcome to theCUBE. Deon, great to see you. >> Thanks for having me. >> So I got to first set the context. Indiegogo, very successful crowd-funder, you guys pioneered. It's pretty obvious now looking back, this has created so much opportunity for people starting companies, whether it's a labor of love or growing into a great business, so congratulations on your success. What's the IBM connection? Because I don't want, you know, there was some stuff on the tweets, I don't want to break the news, but you guys are here. Share the connection. What's the packaging, why is IMB and Indigogo working together? >> Yeah, so back up to 2008. We launched to be able to get people access to funding. And over the last several years, we've done a pretty good job of that. Sending over a billion dollars to over half a million entrepreneurs around the world. And more recently, we've had a lot more requests of Indiegogo can you do more? And we knew that we couldn't do it all on our own. So we partnered first with Arrow to be able to bring these ideas more into reality around components and engineering and supply chain. And we knew we needed more in terms of these IoT products, so they need to be smart and they need software. So we were really excited to be able to announce today, the partnership with IBM, around everything IoT Cloud, security, and being able to provide all the block chain and any other elements that we need. >> Deon I want to ask you, get your thoughts on, we had the Watson data platform guys on earlier in the segment, and the composability is now the norm around data. This brings the hacker-maker culture to IoT. Which if you think about it as a sweet-spot for some of the innovations. They can start small and grow big. Is that part of the plan? >> Yeah, I mean, if you look at what's going on we have about 6000 clients already with us in the IoT space. They tend to be the big end of town, you know whether it be a Daimler or an Airbus or whether it be a Kone, the world's biggest elevator company. Or ISS, the world's biggest facilities management company. So we were doing a lot of work up there really around optimizing their operations, connecting products, wrapping services around them so they can create new revenue streams. But where we didn't have an offering that was being used extensively, was in the start-up space. And you know when we saw what Indiegogo had been doing in the marketplace, and when our partner Arrow, who as Slava has said, has really built up an engineering capability and a component capability to support these makers. It was just a match made in heaven. You know, for an entrepreneur who needs to find a way to capture data, make that data valuable, you know, we can do that. We have the Cloud platform, we have the AI, et cetera. >> It's interesting, we just hit the stride of dude, we have our big data Silicon Valley event just last week, and the big thing that come out of that event is finally the revelation, this is probably not new to Slava and what you're doing, it that, the production under-the-hood hard stuff that's being done is some ways stunting the creativity around some of the cooler stuff. Like whether it's data analytics or in this case, starting a company. So, Slava I want to get your thought on, your views on how the world is becoming democratized. Because if you think about the entrepreneurship trend that you're riding, is the democratization of invention. Alright, there's a democracy, this is the creative, it's the innovation, but yet it's all this hard stuff, like what's called production or under-the-hood that IBM's bringing in. What do you expect that to fuel up? What's your vision of this democratization culture? >> I mean, it's my favorite thing that's happening. I think whether it's YouTube democratizing access to content or Indiegogo democratizing access to capital. The idea of democratizing access to entrepreneurship between our partnership, just really makes me smile. I think that capital is just one of those first points and now they're starting to get the money but lots of other things are hard. When you can actually get artificial intelligence, get Cloud capabilities, get security capabilities, put it into a service so you don't need to figure all those things out on your own so you can go from a small little idea to actually start scaling pretty rapidly, that's super exciting. When you can be on Indiegogo and in four weeks get 30,000 backers of demand across 100 countries, and people are saying, we want this, you know it's good to know you don't need to start ramping up your own dev team to figure out how to create a Cloud on your own, or create your own AI, you can tap right into a server that's provided. Which is really revolutionizing how quickly a small company can scale. So it proliferates more entrepreneurs starting because they know there's more accessibility. Plus it improves their potential for success, which in the long run just means there's more swings at the bat to be able to have and entrepreneur succeed, which I think all of us want. >> Explain to the audience how it works a little bit. You got the global platform that you built up. Arrow brings it's resources and ideation. IBM brings the IoT, the cognitive platform. Talk about how that all comes together and how people take advantage of it? >> Sure, I mean you can look at it as one example, like Water Buy. So Water Buy is an actual sensor that you can deploy against your water system to be able to detect whether or not your water that you're drinking is healthy. You're getting real-time data across your system and for some reason it's telling you that you have issues, you can react accordingly. So that was an idea. You go on Indiegogo, they post that idea and they're able to get the world to start funding it. You get customer engagement. You get actual market validation. And you get funding. Well now you actually need to make these sensors, you need to make these products, so now you get the partnership with Arrow which is really helpful cause they're helping you with the engineering, the design, the components. Now you want to be able to figure out how you can store all that data. So it's not just your own house, maybe you're evaluating across an entire neighborhood. Or as a State you want to see how the water is for the whole entire State. You put all of that data up into the Cloud, you want to be able to analyze the data rapidly through AI, and similarly this is highly sensitive data so you want it to be secure. If Water Buy on their own, had to build out all of this infrastructure, we're talking about dozens, hundreds, who knows how many people they would need? But here through the partnership you get the benefit of Indiegogo to get the brilliant idea to actually get validated, Arrow to bring your idea from the back of a napkin into reality, and then you get IBM Watson to help with all the software components and Cloud that we just talked about. >> And how did this get started? How did you guys, you know, fall into this, and how did it manifest itself? >> So can I tell the story? >> Go for it. >> So I love this story, so as Slava's explained at the front end of this it was really a partnership of Arrow and Indiegogo that came out of the need of entrepreneurs to actually build their stuff. You know, you get it funded and then you say, oh boy, now I've got a bunch of orders how do I now make this stuff? And so Arrow had a capability of looking at the way you designed, you know looking at it deeply with their engineers, sourcing the components, putting it together, maybe white-boxing it even for you. So they put that together. Now, we're all seeing that IoT and the connective products are moving for disconnection, which is actually generating data and that data having value. And so Arrow didn't have that capability, we were great partners with Arrow, you know when we all looked at it, the need for AI coming into all these products, the need for security around the connection, the platform that could actually do that connection, we were a logical map here. So we're another set of components, not the physical. You know, we're the Cloud-based components and services that enable these connected devices. >> If you think about like the impact, and it's mind-boggling what the alternative is. You mentioned that the example you gave, they probably might have abandoned the project. So if you think about the scale of these opportunities what the alternative would have been without an Indiegogo, you probably have some anecdotal kind of feeling on this. But any thoughts on what data you can share around, do you have kind of reference point of, okay, we've funded all this and 90% wouldn't have been done or 70% wouldn't have been done. Do you have any flavor for? >> It's hard to know exactly. Obviously many of these folks that come to Indiegogo, if they could've gotten funded on another path earlier in the process, they would have. Indiegogo became really a great choice. Now you're seeing instead of being the last resort, Indiegogo is becoming the first resort because they're getting so much validation and market data. The incredible thing is not to think about it at scale when you think about 500 or 700 thousand entrepreneurs, or over a billion dollars, and it's in virtually every country in the world. If you really just look at it as one product. So like, Flow Hive is just one example. They've revolutionized how honey gets harvested. That product was bought in almost 170 countries around the world and it's something that hadn't been changed in over 150 years. And it's just so interesting to see that if it wasn't for Indiegogo that idea would not go from the back of a napkin to getting funded. And now through these partnerships they're able to realize so much more of their potential. >> So it's interesting, the machine learning piece is interesting to me because you take the seed-funding which is great product-market fit as they say in the entrepreneurial culture, is validated. So that's cool. But it could be in some cases, small amounts of cash before the next milestone. But if you think about the creativity impact that machine learning can give the entrepreneur, with through in their discovery process, early stage, that's an added benefit to the entrepreneur. >> Absolutely. Yeah, a great example there is against SmartPlate. SmartPlate is trying to use a combination of a weight-sensing plate as well with photo-detection, image detection software. The more data it can feed its image detection, the more qualified it can know, is that a strawberry or a cherry, or is that beef? And we take that for granted that our eyes can detect all that, but it's really remarkable to think about instead of having to journal everything by hand or make sure you pick with your finger what's the right product and how many ounces, you can take a photo of something and now you'll know what you're eating, how much you're eating and what is the food composition? And this all requires significant data, significant processing. >> I'm really pumped about that, congratulations to you on a great deal. I love the creativity and I think the impact to the globe is just phenomenal. Thinking about the game-changing things that are coming up, Slava I've got to ask you, and Deon if you could weigh in too, maybe you have some, your favorites. You're craziest thing that you've seen funded and the coolest thing you've seen funded. (laughter) >> I mean, who is hard because it's kind of like asking well who's your favorite child? I have like 700,000 children, I'm not even Wilt Chamberlain (laughter) and I like them all. But you know it's everything from an activity tracker to security devices, to being able to see what the trend is 24, 36 months ahead. Before things become mainstream today, we're seeing these things 3, 5 years ago. Things are showing up at CES, and you know these are things we get to see in advance. In terms of something crazy, it's not quite IoT but I remember when a young woman tried to raise $200,000 to be able to get enough money for her and Justin Bieber to fly to the moon. (laughter) >> That's crazy. >> That didn't quite get enough funding. But something that's fresh right now is Nimuno Loops is getting funded right now on Indiegogo live. And they just posted less than seven days ago and they have Lego-compatible tape. So it's something that you can tape onto any surface and the other side is actually Lego-compatible so you actually put Legos onto that tape. So imagine instead of only a flat surface to do Legos, you could do Legos on any surface even your jacket. It's not the most IoT-esque product right now but you just asked for something creative. >> That's the creative. >> I think once you got Wilt Chamberlain and Justin Bieber in the conversation, I'm out. (laughter) (crosstalk) >> Well now, how does Indiegogo sustain itself? Does it take a piece of the action? Does it have other funding mechanisms for? >> Yeah, and that's the beautiful thing about Indiegogo. It's a platform and it's all about supply and demand. So supply is the ideas and the entrepreneurs and the demand is the funders. It's totally free to use the website and as long as you're able to get money in your pocket, then we take a percentage. If you're not taking any money into your pocket, then we get no money. As part of the process, you might benefit from actually not receiving money. You might try to raise a hundred grand, only raise thirty-one and learn that your price-point is wrong, your target audience is wrong, your color is wrong, you're bottom cost it too high. All this feedback is super valuable. You just saved yourself a lot of pain. So really it's about building the marketplace we're a platform, we started out just with funding, we're really becoming now a springboard for entrepreneurs. We can't do it all ourselves which is why we're bringing on these great partners. >> You know we've done, just to add to that, I think it's a relevant part here too. We've actually announced a premium-based service for the entrepreneurs to get onto the Cloud, to access the AI, to access the services as a starting point to the complete premium model so they can get started very low barrier to entry and overseeing scale as they grow. >> What do you call that? Is it IBM IoT Premium or? >> It hasn't got a name specifically to the premium element of the, it's just the Watson IoT platform. Available on Blue Mist. >> So it's a Watson sort of, right. So it's like a community edition of Watson. So Deon, new chapter for you. You know I saw a good quarter for mainframes, last quarter. It's still drafting off your great work and now you've shifted to this whole new IoT role, what's that been like? Relatively new initiative for IBM, building on some historical expertise. But give us the update on your business. >> Yes, so about 15 months ago, we announced a global headquarters that we were going to open in Munich, and we announced the Watson IT business. Which brought together a lot of IBM's expertise and a lot of our experience over the years through smarter cities, through the smarter planet initiative. You know we've been working The Internet Of Things, but we made a 3-billion dollar commitment to that marketplace, that we were going to go big and go strong. We've built out a horizontal platform, the Watson IoT platform. On top of that we've got market-leading enterprise asset management software, the Maximo portfolio, TRIRIGA for facilities management. And then we have a whole set of engineering software for designing connected products as well. So we've built out a very comprehensive industry-vertical-aligned IoT business. We added last year, we went from about 4000 to about 6000 clients. So we had a very good year in terms of real enterprises getting real outcomes. We continue to bring out new industry solutions around both connected products and then operations like retail, manufacturing, building management, telco, transportation. We're building out solutions and use-cases to leverage all that software. So business is going well. We officially the Watson IoT headquarters three weeks ago in Munich. And we're jam packed with clients coming through that building, building with us. We've got a lot of clients who've actually taken space in the building. And their using it as a co-laboratory with us to work on PSE's and see the outcomes they can drive. >> Alright, Deon Newman with IoT Watson, and IoT platforms. Slava Rubin, founder of Indiegogo, collective intelligence is cultural shift happening. Congratulations outsourcing and using all that crowdfunding. It's real good data, not just getting the entrepreneur innovations funded but really using that data and your wheelhouse IoT. Thanks for joining us on theCUBE, appreciate it. >> Thank you John. >> More live coverage after this short break, with theCUBE live in Las Vegas for IBM InterConnect. We'll be right back, stay with us. (upbeat music)

>> Announcer: Live, from Las Vegas, it's theCUBE, covering InterConnect 2017, brought to you by IBM. >> OK, welcome back everyone, live here in Las Vegas for IBM InterConnect 2017. This is theCUBE's coverage of InterConnect. I'm John Furrier, Dave Vellante, my co-host. Our next guest is Deon Newman, CMO of IBM Watson IoT, and Slava Rubin, the founder and Chief Business Officer of Indiegogo. Great keynote today, you're on stage, welcome to theCUBE. Deon, great to see you. >> Thanks for havin' me. >> I got to first set the context. Indiegogo, very successful crowdfunder you guys pioneered. It's pretty obvious now, looking back, this creates so much opportunity for people starting companies, whether it's a labor of love or growing into a great business, so congratulations on your success. What's the IBM connection? Because there was some stuff on the tweets, I don't want to break the news, but you guys are here, share the connection. What's the packaging? Why is IBM and Indiegogo working together? >> Yes, so back up to 2008, we launched to be able to get people access to funding and over the last several years, we've done a pretty good job of that, sending over a billion dollars to over a half a million entrepreneurs around the world, and more recently, we've had a lot more requests of Indiegogo, can you do more? And we knew we couldn't do it all on our own, so we partnered first with Arrow, to be able to bring these ideas more into reality around components and engineering and supply chain, and we knew we needed more in terms of these IoT products, so they need to be smart and they need software, so we were really excited to be able to announce today the partnership with IBM, around everything IoT, clouds, security, and being able to provide all the block chain and any other elements that we need. >> Deon, I want to ask you or get your thoughts on, we have the Watson data platform guys on earlier in the segments, and the composability is now the normal around data, brings the hacker-maker culture to IoT, which, if you think about it, is a sweet spot for some of the innovations. They can start small and grow big. Is that part of the plan? >> I mean, if you look at what's going on, we have about 6,000 clients already working with us in the IoT space. They tend to be the big end of town, whether it be a Daimler or a Airbus, whether it be a KONE, the world's biggest elevator company, or ISS, the world's biggest facilities management company, so we were doin' a lot of work up there, really around optimizing their operations, connecting products, wrapping services around them so that they can create new revenue streams, but where we didn't have an offering that was being used extensively was in the start-ups place, and when we saw what Indiegogo had been doing in the marketplace, and when our partner, Arrow, who, as Slava said, has really built up an engineering capability and a component capability to support these makers, it was just a match made in heaven. For an entrepreneur who needs to find a way to capture data, make that data valuable, we can do that. We have the cloud platform, we have the AI, et cetera. >> It's interesting, we just had the Strata Hadoop, we have our own big data Silicon Valley event last week and the big thing that came out of that event, finally, the revelation, this is probably not new to Slava, what you're doin' is that the production under the hood hard stuff that's being done is, in some ways stunting the creativity around some of the cooler stuff, like whether it's data analytics, or in this case, the startin' a company, so, Slava, I want to get your thoughts on your views on how the world is becoming democratized, because if you think about the entrepreneurship trend that you're riding, there's a democratization of invention. This is the creative, it's the innovation, but yet, there's all this hard stuff, that's called, like, production, or under-the-hood, that IBM's bringin'. What do you expect that to feel up? What's your vision of this democratization culture? >> It's my favorite thing that's happening. I think, whether it's YouTube democratizing access to content, or Indiegogo democratizing access to capital, the idea of democratizing access to entrepreneurship between our partnership, just really makes me smile. I think that capital is just one of those first points and now they're starting to get the money, but lots of other things are hard. When you can actually get artificial intelligence, get cloud capabilities, get security capabilities, put it into a service, so you don't need to figure all those things out on your own, so you can go from a small little idea to actually start scaling pretty rapidly, that's super exciting. When you can be on Indiegogo, and in four weeks, get 30,000 backers of demand across 100 countries, and people are saying, "We want this," it's good to know that you don't need to start ramping up your own dev team to figure out how to create a cloud on your own, or create your own AI, you can tap right into a server that's provided, which has really revolutionizing how quickly a small company can scale, so it proliferates more entrepreneurs starting, 'cause they know there's more accessibility, plus it improves their potential for success, which in the long run, just means there's more swings at the bat to be able to have an entrepreneur succeed, which I think all of us want. >> Explain for the audience how it works a little bit. You got the global platform that you built out, Arrow brings its resources and ideation, IBM brings the IoT, the cognitive platform. Talk about how that all comes together and how people take advantage of it. >> Sure, I mean you can look at it as, one example like WaterBot. So WaterBot is an actual sensor that you can deploy against your water system to be able to detect whether or not your water that you're drinking is healthy. You're getting real-time data across your system and for some reason, it's telling you you have issues, you can react accordingly. So that was an idea. You go on Indiegogo, they post that idea, and they're able to get the world to start funding it. You get customer engagement, you get actual market validation, and you get funding. Well now you actually need to make these sensors, you need to make these products, so now you get the partnership with Arrow, which is really helpful, 'cause they're helping you with the engineering, the design, the components. Now you want to be able to figure out how you can store all that data, so it's not just your own house, maybe you're evaluating across an entire neighborhood, or as a state, you want to see how the water is for the whole entire state. You put all that data up into the cloud, you want to be able to analyze the data rapidly through AI, and similarly, this is highly sensitive data, so you want it to be secure. If WaterBot, on their own, had to build out all this infrastructure, we're talking about dozens, hundreds, who knows how many people they would need, but here, through the partnership, you get the benefit of Indiegogo to get the brilliant idea to actually get validated, Arrow, to bring your idea from back of the napkin into reality, and then you get IBM Watson to help with all of the software components and cloud that we just talked about. >> Great, and how did this get started? How did you guys fall into this and how did it manifest itself? >> Take it, I tell the story? >> Go for it. >> So, I love this story. So, Slava's explained that the front end of this, it was really a partnership of Arrow and Indiegogo that came out of the need of entrepreneurs to actually build their stuff. You know, you get it funded, and then you say, "Oh boy," now I've got a bunch of orders, how do I now make this stuff? And so, Arrow had a capability; of looking at the way you designed, looking deeply with their engineers, sourcing the components, putting together, maybe whiteboxing it even for you, and so, they put that together. Now, we'll all seeing that IoT and the connected products are moving for disconnection, it's actually generating data and that data having value. And so Arrow didn't have that capability, we were great partners with Arrow, you know, when we all looked at it, you know, the need for AI coming into all these products, the need for security around the connection platform, that can actually do that connection, we were a logical map here, so we're another set of components, not the physical. We're the cloud-based components and services that enable these connected devices to sync. >> If you think about the impact, it's mind-boggling with the alternative. You mentioned, the example you gave, they probably might have abandoned the project, so if you think about the scale of these opportunities, what the alternative would have been without an Indiegogo, you probably have some anecdotal feeling on this. Any thoughts on what data you can share, do you have any kind of reference point of like, OK, we funded all this and 90% wouldn't have been done, or 70% wouldn't have been done, do you have any flavor for what's... >> Hard to know exactly. Obviously, many of these folks that came to Indiegogo, if they could have gotten funded on another path, earlier in the process, they would have. Indiegogo became really a great choice. Now you're seeing, instead of being the last resort, Indiegogo's becoming the first resort because they're getting so much validation and market data. The incredible thing is not the thing that adds scale, when you think about 500 or 700,000 entrepreneurs or over a billion dollars and it's in virtually every country in the world, if you really just look at it as one product. So, like, Flow Hive is just one example. They've revolutionized how honey gets harvested. That product was bought in almost 170 countries around the world, and it's something that hasn't been changed in over 150 years, and it's just so interesting to see that, if it wasn't for Indiegogo, that idea would not go from the back of the napkin to getting funded, and now, through these partnerships, they're able to really realize so much more of their potential. >> So, it's interesting, the machine learning piece is interesting to me, because you take the seed funding, which is great, and product market fit as they say in the entrepreneurial culture, is validated, so that's cool, but it could be, in some cases, small amounts of cash before the next milestone, but if you think about the creativity impact that machine learning can give the entrepreneur. >> Slava: Right. >> On their discovery process, early stage, that's an added benefit to the entrepreneur. >> Absolutely. Yeah, a great example bears against SmartPlate. SmartPlate is trying to use the combination of weight sensing plate, as well with photo detection, image detection, and software. The more data it can feed its image detection, the more qualified it can know, "Is that a strawberry or a cherry or is that beef?" Right? And we take that for granted that our eyes can detect all that, but it's really remarkable to think about that instead of having to journal everything by hand or make sure you pick with your finger what's the right product, how many ounces, you can take a photo of something and now it'll know what you're eating, how much you're eating and what is the food composition? And this all requires significant data, significant processing. >> Well, I'm really pumped about that, congratulations, Deon, on a great deal. I love the creativity. I think the impact to the globe is just phenomenal. I mean, by what the game-changing things that are coming out. Slava, I got to ask you, and Deon, if you could weigh in, too, maybe you have some, your favorites, the craziest thing you've seen funded, and the coolest thing you've seen funded. >> Cool is hard, because it's kind of like asking, "Well, who's your favorite child?" I have like 700,000 children, not even Wilt Chamberlain, (laughing) and I like them all. But, you know, it's everything from an activity tracker to security devices, to be able to see what the trend is 24, 36 months ahead. Before things become mainstream today, we're seeing these things three, five years ago. Things are showing up at CES, and these are things we get to see in advance. In terms of something crazy, it's not quite IoT, but I remember when a young woman tried to raise $200,000 to be able to get enough money for her and Justin Bieber to fly to the moon. (laughter) >> That's crazy. >> That didn't get quite enough funding, but something's that flush right now is Nimuno Loops is getting funded right now on Indiegogo Live, and they just posted less than seven days ago and they have Lego-compatible tape, so it's something that you can tape onto any surface, and then the other side is actually Lego-compatible, so you're actually putting Legos onto that tape. So, imagine, instead of only a flat surface to do Legos, you could do Legos on any surfacing, even your jacket. It's not the most IoT-esque product right now, but you just asked for something creative, there you go. >> That's a creative. >> I think once you got Wilt Chamberlain and Justin Bieber in conversation, I am out. (laughter) >> Keepin' it fresh. (voices overlapping) >> Slava, how does Indiegogo sustain itself? Does it take a piece of the action? Does it have other funding mechanisms for... >> The beautiful thing about Indiegogo is, it's a platform and it's all about supply-and-demand, so supply is the ideas and the entrepreneurs, and demand is the funders. It's totally free to use the website and as long as you're able to get money in your pocket, then we take a percentage. If you're not taking any money into your pocket, then we get no money. As part of the process, you might benefit from actually not receiving money. You might try to raise 100 grand, only raise 31, and learn that your price point is wrong, your target audience is wrong, your color is wrong, your bond cost is too high. All this feedback is super value. You just saved yourself a lot of pain, so really it's about building the marketplace. We're a platform, we started out just with funding, we're really becoming now a springboard for entrepreneurs, we can't do it all ourselves, which is why we're bringing on these great partners. >> And you know, we've done, just to add to that, I think it's a relevant part here, too. We've actually announced a freemium-based service for the entrepreneurs to get onto the cloud access, the AI, or to access the services as a starting point, it's a complete freemium model, so that they can get started, very low barrier to entry and obviously, scale as they grow. >> What do you call that? Is it IBM IoT Freemium or is it? >> Hasn't been a name specifically to the Freemium element of it, it's what in IoT platform, available on Bluemix. >> So, it's like a community addition of lots of, so Deon, a new chapter for you, >> Yeah. >> I saw a good quarter for mainframes last quarter, still drafting off your great work, and now you've shifted to this whole new IoT role. What's that been like, relatively new initiative for IBM, building up on some historical expertise, but give us the update on your business. >> It's about 15 months ago, we announced a global headquarters that we're going to open in Munich and we announced the Watson IoT business, which brought together a lot of IBM's expertise and a lot of our experience over the years through Smarter Cities, through the Smarter Planet Initiative, we'd been working the Internet of Things. We'd made a three billion dollar commitment to that marketplace, though we were going to go big and go strong. We've built out a horizontal platform, the Watson IoT platform. On top of that, we've got market-leading enterprise SF management software, the Maximo portfolio, TRIRIGA for facilities management, and then we have a whole set of engineering software for designing connected products as well. So we've built out a very comprehensive industry, vertical-aligned IoT business. We added, last year, we went from about 4,000 to about 6,000 plants, so we had a very good year, in terms of real enterprises getting real outcomes. We continued to bring out new industry solutions around both connected products and then, operations like retail, manufacturing, building management, Tokyo, transportation. We're building out solutions and use-cases to leverage all that software, so business is going well, we officially opened the Watson IoT headquarters three weeks ago in Munich, and we're jampacked with clients coming through that building, building with us. We've got a lot of clients who've actually taken space in the building, and they're using the co-laboratory with us to work on PSEs and see the outcomes they can drive. >> Deon Newman, with Watson IoT platforms. Slava Rubin, founder of Indiegogo. Collective intelligence as cultural shift happening. Congratulations. Crowdsourcing and using all that crowdfunding. It's really good data, not just getting the entrepreneur innovations funded, but really using that data and way in your wheelhouse, IoT. >> Yeah. >> John: Thanks for joining us in theCUBE, appreciate it. More live coverage after this short break. It's theCUBE, live in Las Vegas, for IBM InterConnect. We'll be right back. Stay with us. (theCUBE jingle)

>> Narrator: Live from Austin, Texas, it's The Cube covering South by Southwest 2017, brought to you by Intel. Now, here's John Furrier. >> Hey, welcome everyone back for day two of live coverage of South by Southwest. This is the cube, our flagship program from Silicon Angle. We go out to the events and extract the (mumbles). We're at the Intel AI Lounge, people are rolling in, it's an amazing vibe here, South by Southwest. The themes are AI, virtual reality, augmented reality, technology. They got great booths here, free beers, free drinks, and of course great sessions and great conversations here with the Cube. My first guest of the day here is Ben Parr, a friend of the Cube. He's been an entrepreneur, he's been a social media maven, he's been a journalist, all around great guy. Ben, thanks for joining us today. >> Thank you for having me again. >> So you're a veteran with South by Southwest, you know the social scene, you've seen the evolution from Web 2.0 all the way to today, had Scobel on yesterday, Brian Fanzo, really the vibe is all about that next level, of social to connecting and you got a startup you're working on that you founded, co-founded called AI? >> Ben: Octane AI. >> Octane AI, that's in the heart of this new social fabric that's developing. Where AI is starting to do stuff, keep learning, analytics but, ultimately, it's just a connection. Talk about your company. What is Octane AI? Tell us a little bit about the company. >> So Octane AI is a platform that lets you build an audience on Facebook Messenger and then through a bot. And so, what we do is allow you to create a presence on Messenger because if I told you there was a social app that had a billion users every month, bigger than Snapchat plus Twitter plus Instagram combined you'd want to figure out a strategy for how to engage with those people right? And that social app is Facebook Messenger. And yet no one ever thinks, oh could I build an audience on a messaging app? Could I build an audience on Messenger or WeChat or any of the others. But you can through a bot. And you can not just build an audience but you can create really engaging content through conversation. So what we've done is, we've made it really easy to make a bot on messenger but more importantly, a real reason for people to, actually, come to your bot and engage with it and make it really easy to create content for it. In the same way you create content for a blog or create content for YouTube Channel. Maroon 5, Aerosmith, KISS, Lindsay Lohan, 30 seconds to MARS, Jason Derulo and a whole bunch more use us to build an audience and engage their fans on Messenger. >> So let me get your thoughts on a couple of trends around this. Cause this is really kind of, to me, a key part that chat bots illustrate the big trends that are going on. Chat bots were the hype. People were talking about, oh chat bots. It's a good mental model for people to see AI but it also has been, kind of, I won't say a pest, if you will, for users. It's been like a notification. A notification of the economy we're living in. Now you're taking it to the next level. This is what we're seeing. The deep learnings and the analytics around turning notifications which can be noisy after a while, into real content and connections. >> Into something useful, absolutely. Like look, the last year of bots. The Facebook platform is not even a year old. We've been in that fart apps stage of bots. Remember the first year of mobile apps? You had the fart app and that made $50,000 a day and that was annoying as hell. We're at that stage now, the experimentation stage. And we've seen different companies going in different, really cool directions. Our direction is, how do you create compelling content so you're not spamming people but you have content that you can share, not just in your bot but as a link on your social media to your followers, to your fans, on Twitter, everywhere else and have a scalable conversation about whatever you want. Maroon 5 has conversations with their audience about their upcoming tours or they even released an exclusive preview of their new song, Cold, through our bots. You could do almost anything with our bots or with any bot. We're just learning right now, as an industry, what are the best practices. >> So where do bots go for the next level? Because you and I have known each other for almost over 10 years, we've seen the whole movement and now we're living in a fake news era. But social media is evolving where content now is super important that glues people together, communities together. In a way, you're taking AI or bots, if you will. Which is a first, I mean, .5 version of where AI is going. Where content, now, is being blended into notifications. How important is content in community? >> Content in community are essential to any product. And I feel like when you hear the word bot, you don't think community and that you could build a community with it because it's a bot, it's supposed to be automated. But you, actually, can if you do it in the right way and it can be a very, very powerful experience. We're building features that allow you to build more community in your bot and have people who are talking with your bot communicate with each other. There's a lot of that. What I feel like is, we're at the zero point one or zero point two of the long scale of AI. What we need to do right now is showcase all the use cases that really work for AI, bots, machine learning. Over time, we will be adding more other great technologies from Intel and others that will make all these technologies and everything we do better, more social and most of all, more personalized. I think that's one of the big benefits of AI. >> Do you see bot technology or what bots can turn into being embedded into things like autonomous vehicles, AR, is there a stack developing, if you will, around bots? What you're talking about is a progression of bots. What's your vision on where this goes down the road? >> I see a bunch of companies, now, building the technological stack for AI. I see a bunch of companies building the consumer interface, bots is one of those consumer interfaces. Not just chat bots but voice bots. And then I see another layer that's more enterprise that's helping make more efficient things like recruiting or all sorts of automation or driving. That are being built as well. But you need each of those stacks to work really well to make this all work. >> So are there bots here at South by Southwest? Is there a bot explosion, is there bots that tell you where the best parties are? What's the scene here at Southby? Where are the bots and if there were bots, what would they be doing to help people figure out what to do? >> The Southby bot is, actually, not a bad bot. They launched their bot just before South by Southwest. It has a good party recommendations and things. But it the standard bot. I feel like what we're seeing is the best use, there's a lot of good bot people. What I'm seeing right now is that people are still flushing out the best use cases for their bots. There's no bot yet that can predict all the parties you want to go to. We got to have our expectations set. That will happen but we're still a few years away from really deep AI bots. But there are clearly ones where you can communicate faster with your friends. There's clearly ones that help you connect with your favorite artist. There's clearly ones that help you build an audience and communicate at scale. And I feel like the next step is the usefulness. >> Talk about the user interface. Robert Scobel and I were talking yesterday, we have some guests coming on today that had user experience background. With AI, with virtual reality, with bots, with deep learning, all this collective intelligence going on, what's your vision of the user interface as it changes, as people's expectations? What are some of those things that you might see developing pretty quickly as deep learning, analytics, more data stats come online? What is the user interface? Cause bots will intersect with that as an assistant or a value add for the user. What's your vision on? >> I'll tell you what I see in the near term and then I'll tell you a really crazy idea of how I see the long term. In the near term, I think what you're going to see is bots have become more predictive. That, based on your conversations, are more personalized and maybe not a necessarily need as much input from you to be really intelligent. And so voice, text, standard interfaces that we're used to. I think the bigger, longer run is neurological. Is the ability to interface without having to speak. Is AI as a companion to help us in everything we do. I feel like, in 30 years, we won't even, it's, kind of like, do your remember the world when it had no internet? It's hard, it feels so much different. There will be a point in about 20 years we will not understand what the world was before AI. Before AI assistance where assisting us mentally, automatically and through every interface. And so good AI's, in the long run, don't just run on one bot or one thing, they follow you wherever you go. Right now it might be on your phone. When you get home, it may be on your home, it may be in your car but it should be the same sets of AI's that you use daily. >> Doctor Nevine Rou, yesterday, called the AI the bulldozer for data. What bulldozers where in the real world, AI's going to do that for data. Cause you want to service more data and make things more usable for users. >> Yes, the data really helps AI become more personalized and that's a really big benefit to the user to every individual. The more personalized the experience, the less you have to do. >> Alright, so what's the most amazing thing you've seen so far this year at Southby? What's going on out there that's pretty amazing? That's popping out of the wood work? In terms of either trend, content, product, demos, what are some of the cool things you're seeing. >> So, as it is only Saturday, I feel like the coolest thing will still come to me. But outside of AI, there have been some really cool mixed reality, augmented reality demos. I can't remember the name. There's a product with butterflies flying around me. All sorts of really breaking edge technologies that, really, create another new interface honestly where AI may interact with us through the augmented reality of our world. I mean, that's Robert Scogul's thing exactly. But there's a lot of really cool things that are being built on that front. I think those are the obvious, coolest ones. I'm curious to see which ones are going to be the big winners. >> Okay, so I want to ask you a personal question. So you were doing some venture investing around AI and some other things. What caused you to put that pause button on that mission to start the chat bot AI company? >> So I was an investor for a couple of years. I invested in ubean, the wireless electricity company and Shots with Justin Bieber which is always fun. And I love investing and I love working with companies. But I got into Silicone Valley and I got into startups because I wanted to build companies. I wanted to build ideas. This happened, in part, because of my co-founders. My co-founder Matt, who is the first head of product at Ustream and twice into the Forbes 30 under 30. One of the king makers of the bot industry. The opportunity to be a part of building the future of AI was irresistible to me. I needed to be a part of that. >> Okay, can you tell any stories about Justin Bieber for us, while we're here inside the Cube? (laughs) >> I wonder how many of those I can, actually, tell? Okay, so look. Justin Bieber is an investor in a company I'm an investor in called Shots. Which is now a super studio that represents everyone from Lele Pons to Mike Tyson on digital online and they're doing really, really well. One of Justin's best friends is the founder, John Shahidi. And so it's just really random. Sitting with John, who I invested in and just getting random FaceTime's. Be like, oh it's Justin Bieber, say hi to Justin. As if it was nothing. As if it was a normal, it's a normal day in his life. >> Could you just have him retweet one of my Tweets. He's got like a zillion followers. What's his follower count at now? >> You don't want that. He's done that to me before. When Justin retweets you or even John retweets you, thousands of not tens of thousands of Justin Bieber fans, bots and not bots, start messaging you, asking you to follow them, talking to you all the time. I still get the tweets all the time from all the Justin fans. >> Okay don't tweet me then. I'm nice and happy with 21,000 followers. Alright, so next level for you in terms of this venture. Obviously, they got some rock stars in there. What's the next step for you guys right now? Give us a little inside baseball in the venture status where you guys are at. What's the next step? >> We launched the company publicly in November, we started in May. We raised 1.6 million from general catalyst, from Sherpa Ventures, a couple of others. When we launched our new feature, Convos, which allows you to create shareable bots, shareable conversations with the way you share blog posts. And that came out with all those launch partners I mentioned before like Maroon 5. We're working on perfecting the experience and, mostly, trying to make a really, really compelling experience with the user with bots because if we can't do that, then there's no use to doing anything. >> So you provide the octane for the explosive conversations? (laughs) >> Yes, there you go, thank you, thank you. And we make it really easy. So we're just trying to make it easier to do this. This is a product that your mom could use, that an artist could use, any social media team could use. Writing a convo is like writing a blog post on media. >> Are moms really getting the chat bot scene? I, honestly, get the Hollywood. I'm going to go back to Hollywood in a second but being a general, middle America kind of tech/genre, what are they like? Are they grokking the whole bot thing? What's the feedback from middle America tech? >> But think of it this way. There are a billion people on Messenger and it's a, really, part of the question, they all use Facebook Messenger. And so, they may be communicating with a bot without knowing it. Or they might want to communicate with their fans. It's not about the technology as much as this is like connecting with who you really care about. If I really care about a Maroon 5 or Rachel Ray, I can now have that option. And it doesn't really matter what the technology is as much as it is that personal connection, that experience is good. >> John: Is it one-one-one or group? Cause it sounds like it's town hall, perfect for a town hall situation. >> It's one-on-one, it's scale. So you could have a conversation with a bot while each of the audience members is having a conversation one-on-one. When you can choose different options and it could be a different conversation for each person. >> Alright, so I got to ask about the Hollywood scene. You mentioned Justin Bieber. I wanted to go down that because Hollywood really has adopted social media pretty heavily because they can go direct to the audience. We're seeing that. Obviously, with the election, Trump was on Twitter. He bypasses all the press but Hollywood has done very well with social. How are they using the bots? They are a tell sign of where it's going. Can you share some antidotal stories or data around how Maroon 5, Justin, these guys are leveraging this and what's some of the impact? >> Sure, so about a month 1/2, 2 months before Maroon 5 launched their new song, new single, Cold. They came to us and wanted to build a distribution. They wanted to reach their audience in a more direct personal way. And so we helped them make a bot. It didn't take long. We helped them write convos. And so what they did was they wrote convos about things like exclusive behind the scenes photos from their recent tour or their top moments of 2016 or things that their fans really care about. And they shared em. They got a URL just like you would get, a blog poster URL. They shared it out with their 39 million Facebook fans, they shared it with their Twitter followers, they shared it across their social media. And 10's of thousand's of people started talking with their bot each time they did this. About 24 hours before the bot, before their new single release, they exclusively released a 10 second clip of Cold through their bot. And when they did that, within 24 hours, the size of their bot doubled because it went viral within the Maroon 5 community. There's a share function in our convos and people shared the convo with their friends and with their friends friends and it kept on spreading. We saw this viral graph happen. And the next day when they released the single, 1000's of people bought the song because of the bot alone. And now the bot is a core of their social strategy. They share a convo every single week and it's not just them but now Lohan and a whole bunch of others are doing the same thing. >> John: Lindsay Lohan. >> Lindsay Lohan is one of our most popular bots. Her fans are really dedicated. >> And so you can almost see it's, almost connecting with CGI, looking at what CGI's doing in film making. You could almost have a CGI component built-in. So it's all this stuff coming together. >> Ben: Multimedia matters. >> So what do you think about the Intel booth here? The AI experience? They got some Kinetic photo experience, amazing non-profit activities in deep loading (mumbles), missing children, what do you think? >> This is some of the best use cases for AI which is, people think of AI as just like the direct consumer interface which is what we do but AI is an underlying layer to everything we do. And if it can help even 1% or 1,000% identify and find missing children or increase the efficiency of our technology stacks so that we save energy. Or we figure out new ways to save energy. This is where AI can really make an impact. It is just a fundamental layer of everything. In the same way the internet is just a fundamental layer of everything. So I've seen some very cool things here. >> Alright, Ben Parr, great guest, in venture capitalist now founder of a great company Octane AI. High octane, explosive conversations looking forward to adopting. We're going to, definitely, take advantage of the chat bot and maybe we can get some back stage passes to Maroon 5. (laughs) >> (laughs) There will be some fun times in the future, I know it. >> Alright Ben Parr. >> Ben: Justin Bieber. >> Justin Bieber inside the Cube right here and Ben Parr. Thanks for watching. It's the Intel AI Lounge. A lot of great stuff. A lot of great people here. Thanks for joining us. Our next guest will be up after this short break. (lively music)