>>Live from Denver, Colorado. It's the cube covering comm vault. Go 2019 brought to you by Combolt. >>Hey, you welcome back to the cubes coverage of combo go 19. We're in Colorado this year. Lisa Martin with Stu Miniman and we have a couple of gents joining us alumni of the cube. We're gonna have a really spirited conversation. Please welcome Avinash locks from the CEO of Hedvig, one of our alumni and Don Foxer, the VP of storage solutions from combo and Ann Campbell. Oh gee, Dawn, you can say that, right? Yes, yes. So guys, just a little bit of news coming out with combo and Hedvig in the last month or so, you guys announced combo, announced they were acquiring Hedvig. We last had you on the cube of an Asha DockerCon 18 talking about had veg. And here we are, the announcement comes in September. Acquisitions already closed, lots of buzz, lots of excitement. I'll finish. Let's start with you. Why Convolt >>good question. Uh, first of all, thanks for having me. Uh, C, the way I look at it, I believe the enterprises are gravitating towards complete solutions. If you look at, uh, data management and backup Conwell's clearly the leader in that space, I don't have to say it, I think the analysts have all attested to it. We bring in a very complimentary set of tools that I think coupled together could be a complete solution for a large variety of workloads in the modern data center. And hence it makes it a ideal fit. And also the cultures from an engineering perspective, being Hedwig being a small company in Cornwall is also a small company. But you know, definitely big when compared to what we are at. Um, the cultures were more or less aligned in terms of the engineering culture, so to speak. And that makes it, uh, it made it a very natural choice. Do you know, feel comfortable going into a bigger company. So it worked out really well. >>So Don way we've seen the slides given in the keynote, they talked about the two halves of the brain, the storage management and the data management. Talked to us a little bit about of Hedwig plus con vault and how that goes together. Yeah, for sure. I mean, if you start to look at the, I mean, I guess you look at the marketplace today and you can tell that, uh, kind of the, the lines of delineation of what vendor a versus vendor B versus vendor seat is doing is completely blurred, right? And you'll see that with the attachment of secondary storage, you see that with way backup companies and are driving more towards sort of, you know, uh, the app dev space. And we really start to look at where, what Combolt's doing and, and, and I always say when we talked about the acquisition of Hedvig, it's accelerating the vision that we've had on be able to provide a really super scalable backend for where you can land information that Combalt protects, but the really interesting and cool part, but as you start to realize the tool set that it has within it, it also keeps us very relevant for the future, for where it, in the shifts with applications are going. >>Then it gives us a chance to really give that complete solution from giving the storage, taking the information as it's being created and storing it in a compliance form, storing it off to the cloud, maybe re-purposing it, reusing it into the future. So that's how this really starts to come together. You have the index in control and management, the understanding of what Combolt provides the data management and you have all the flexibility and control that the Hedvig platform provides and Miriam together just gives you that much more agility for how you can use that information, that data. I want to understand what being part of Convolt will be different for Hedvig. I think back to, I've been talking to you since the company came out of stealth. We're huge proponents of the learnings that the hyperscalers had. You came from Amazon and Facebook. Bringing that to the enterprise is great, but building something that is highly scalable versus frigging something that has repeatability and scalability through thousands of deployment, like convoluted have are two separate issues. So, you know, we'll, we'll being part of Convolt, how will that impact your business and your group? >>I think the latter is what is going to make it really exciting for us. I think we added a point where the product that we are bringing into the market or we are brought into the market, it's pretty mature and most of the customers would deploy it and use it. They've been extremely happy with the way it performs and the way it has performed over time. And I think with the combo, they have a larger footprint in the enterprise, large channel infrastructure already in place makes it a lot more easy to push the product out there into the market. And uh, we will be given and VR given complete autonomy plus you what it would it is at Viva doing. And obviously, you know, when you go into any other organization that has got to be some cross-pollination, which is also something that we will be pursuing. But these two things I think, uh, make it very exciting times for us. >>Didn't you? You mentioned the word acceleration a few minutes ago. I'm just wondering from your perspective being called on as long as you have, do you and maybe customers and partners see the Hedvig acquisition as? Sanjay was saying something that's trending on Twitter today is the hashtag new comm dolls. Yep. So it's actually interesting. At first when the acquisition was announced, there were some partners that were like, Hmm, okay, I need to think about this a little bit. And then as we kind of went through the talk track and sort of explain some of the power with the head of the platform delivers, there were a number of, there was suddenly aha. Like you could just tell the light bulb went off. I get where this is going. And then you see what we're doing from Convolt metallic as well, right? The the SAS offering. And you see how we're continuing to drive all of the innovation in that core product. I don't know if you want to call it a combo to Datto, but I do think we've entered a new era of what we're delivering back to our customers from a solutions perspective. And it's really exciting because you can talk to a customer about backup and give them the best solution in the world, but we can also start to expand and get a whole heck of a lot more strategic and help be thought leaders and some of these new spaces, >>well, some of the commentary that I was reading about the acquisition from analysts say, Hey, this is a potentially, this is going to give Combalt opened the door for a bigger presence in the surge defined space, a big market. Also elevate comm vault from a Tam perspective. Talk to us about those perspectives. As some of the analysts said, when Sanjay came onboard nine months ago, Hey combo, you really got to expand your market share and get a kick out of just cultivating the large enterprises. How do you see that? >>Yeah, sure. I mean that's the easiest place to point to the secondary storage market place, right? So the secondary to storage marketplace, it's double digits in billions of market share. And that can be anything from things like object storage. It could just be scale-out, NAS. It could be, um, it could be, you know, companies like Cohesity and others that have a platform that build out secondary storage is a whole slew of people that play in that space. Uh, it also goes back to like appliances in a whole form of other storage types that are purpose built. So the secondary storage is a fairly broad sort of brush that people paint. You know, something is not running production workloads. But the interesting thing is, and this is kind of something that when the we've talked about we see those lines of private production or primary, secondary, tertiary, that's starting to really blur out. >>Um, so that market share that is in secondary storage, that market share that attaches also to object for where your, where we're going from a even a scale out backup perspective. You know, those are I going to be target areas that we can start to give customers solutions into in a really integrated and complete way. Uh, one of the customer areas that I've heard from Convolt that I'm curious if it might be applicable for your, for your team of an option is the service providers, you know, they've sold and you talk about how many end users actually leverage Convolt technology. It's like almost an order of magnitude more when you go through the service providers and when you talk about scalability and the requirements that that seems to be like it could be a fit for a. >>Yeah, you could even think of someone who is running a private cloud in their own on premise data center as being a service provider for their own internal consumption. Grateful folks working in tunnel. I guess going to an MSB or even do a larger service providers is an extrapolation of the same thing. So it'll obviously make it a very natural fit because you know, everyone understands the cap X game. Operational efficiency is the harder problem to actually crack. And with systems like this you can actually address that very simplistically. And it also allows them to kind of scale with their growth in a very effortless fashion. So it makes an agile mix a lot of natural sense. >>And that's an interesting point cause that aligns well too with the way the Combalt software themselves also attack attaches, right? We do a much better job of running that value back to the larger enterprise or those that are seeing more of that operational efficiency challenge. So it's another reason why this is a great intersection or you know, great, great marriage of the two technologies, um, what want to speak with, I think we talked about Sanjay about he of being at puppet worked a lot with dev ops in that environment. I heard from Convolt COO that five of the 45 developers that are here doing whiteboard session come from Hedvig. So speak a little bit of that, that customer base, the developer community microservices, you know, that kind of modern >>I think we have a, a demo session. I don't know what time, but we're going to give you a comprehensive overview of how, uh, you know, kind of Kubernetes orchestrated containers works with Hedwig. I think if people are here, they're hearing me, they should definitely check it out. And, uh, if you look at some of our larger customers, they deploy us in environments where they want to have practically zero touch provisioning capability, right? Which means that you got your infrastructure ought to be completely programmable, which bitches, what the DevOps movement is all about. And uh, the comprehensive set of APIs that be exposed for control and data plane, it actually makes that pipe dream a reality. >>Let's talk a little bit about the integrations. I mentioned a minute ago. The announcement was in September, the acquisitions close and you guys have already really started to buckle down into the integration between the technologies. Can you talk to us about that? And then I'd love to get your perspective on existing had big customers, you know, what door does this open for them? >>So for an existing customers, they are very happy because they now are convinced that we have a larger footprint and we have a lot more people to help to help support them as they grow and they don't have this field anymore as to how perhaps a small startup would be able to support them. So that fear factor goes away. So they're all very relieved on that front. Second, from an integration perspective, uh, there's a lot of things that we are working on from a technological perspective that is getting deep into the roadmap. I dunno if he can talk much about it at this point, but a non-technology we're all well integrated in, we are all Commonwealth employees now Gunwale badges come while emails so well integrated at this point. >>I guess maybe from a high level perspective, what we probably can say is probably number one, we want to make sure the experiences across both products are merged. So it truly views as you know, one one true company vault and providing that experience. And that's everything from installation to support to how we communicate and manage the, the ongoing relationship with the customer. So that's one there's always work to do there. Right? And the next core piece is just how we can make the two technologies basically make, you know, the had big platform, a part of the combo data platform and make sure those two integrations are as tight as possible. And that will be a longterm path, right? Because as that becomes more integrated, there's going to be new ideas, new innovations, and she's gonna come up with a whole lot of new things that we could potentially do that will meet the needs for the customer. And I think the third piece that ties back into the dev ops conversation is we've got two really solid API stacks. So bringing those together is going to be important in the future as well. So that it really is a crisp and clean sort of programmable infrastructure for customers from how the storage is delivered all the way to how it's managed and potentially even deleted out the back end. >>Well, with how quickly we're seeing Convolt move in the last nine months, I mean this year there's so much innovation from leadership changes in sales and marketing, new GTM routes, et cetera. What can, what can combo customers expect in terms of, I know you can't divulge too much on the roadmap, but you know with faster, shorter cycles of development. >>So I'll go first. I mean I think as you look at the sort of sort of where maybe the easiest way to answers is we're staying in front of where the market is heading and we're making sure we're providing solutions that can get customers to solve those challenges when they hit them. We don't want them to have to hit those challenges, have to then struggle, fight, figure out what it is they can do while everyone in their market moves past them. We want to be there with a solution that answers some of those challenges that day. They hit them more preemptive, preemptive, absolutely more preempted to react. That's a perfect way to put it. Thank you. So that's part of what they can expect from us and we do a lot of research and working with our customers and understanding where their future needs are, where they're going. We spend a lot of time with industry experts and analysts too for what they're seeing across the globe. Obviously we can only go so far and travel and talk to so many people. So we leveraged the collective of the industry to also kind of have a pretty good gauge and I'll say we've got leaders like Amash and Sanjay that are also awesome at just kind of having a really good pulse on where the industry is going and what we should be doing as a company. >>I'm just getting pickled in so too early for me to answer how that roadmap may Michio or how customers may perceive. But I think, uh, what should be very encouraging is that we bring so many, so much more capabilities. The enterprise has always been in this mindset of procuring things with a single throat to choke and this makes it very easy for them. >>What's the question of done for you is some of the things that Sue and I have talked about with guests today is from a partner perspective, there's been a lot of positive feedback in Navarro community we talked with and think we're talking with Rick de Blasio tomorrow. Want to understand, you know, some of the new partner programs, how are his Convolt traditional channel, your VARs, but also all the way up to your. Their reaction to all of the changes and the acceleration that Cohmad is driving is particularly with respect to head veg. >>For the most part it's been incredibly positive and even though the technology partner side, it's, it's fairly positive and also it forces us to have a much closer conversation on. All right, let's continue to talk about how we're successful together in the marketplace because we understand that our customers will need more than one vendor, more than two vendors to be successful as they kind of tackle the challenges that are in front of them. So you know, we're not going to stop our innovation and partnering and technology ecosystem development because that's so important to allow the customer to have the choice. We know that we're only one of many players and so we want to give them the choice to use whatever they need. We just want to help them control and manage the data >>and help them maybe simplify their operations. And especially as you know, we don't, we don't go to any event without talking about multi-cloud. It's the world that most businesses are living in. And, and I'll say, if you're not you Willy, how can what combat is doing now, not just with Hedvig but also just with some of the structural changes and directions that you guys have made it help customers embrace multicloud actually be able to protect, recover that data and >>you know, shift, sift insights from it. Yeah, sure. Please. All right, so multi-cloud, so first it starts off in tying in the ecosystems of the different cloud players offer, right? You need to be able to sort the support their platforms. You need to be able to continue to abstract out the information, the data itself that may be tied to an application or tied to a platform and give that level of portability. It's actually something that Hedvig does a fantastic job on as well and when you start to have that level of portability, well then it becomes a heck of a lot easier to either use other platforms within that cloud or a separate cloud or something you might homegrown build yourself as. That's part of the big value prop. We're doing all of these things not to have the best infrastructure but to make it easier for customers to use that data. So that means integrating and being strong partners to cloud players. It means continuing to be a really technological leader in how you can support all the platforms and services they offer and really allow the data to rise to the top as far as the value perspective goes and that's really where we continue to drive our innovation, at least on the on the data management side. >>That's a good Commonwealth perspective. The Hedvig perspective comes from a different angle. We always look at data portability, be it multicloud or even be at hybrid via met a lot of customers who went down the hybrid pot and then had to pull back. And when you pull back, you don't want to be in a situation where you're rewriting your entire application because your data is persisted in a very different way. But providing that data portability with an abstraction that sits between the application and the underlying physical infrastructure, I think is going to be a very important solution to take. You know, view often in this mix and hence together it becomes a comprehensive solution. >>Well guys, we thank you so much for stopping by joining soon and be on the program telling us a little bit more about this exciting new venture that you guys are going in together and we look forward to hearing more about it as it unfolds and maybe getting some customers on the cube next year. Absolutely. All right. Thank you. Thanks for Sumeta, man. I am Lisa Martin. You're watching the cube from convo. Go 19.

>> 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)