 Live from Copenhagen, Denmark, it's theCUBE. Covering Nutanix.next 2019, brought to you by Nutanix. Welcome back everyone to theCUBE's live coverage of Nutanix.next. We are at the Bella Center in Copenhagen, Denmark. I'm your host, Rebecca Knight, alongside of Stu Miniman, of course. We are joined by a good friend of theCUBE, Ray Wong, principal analyst and CEO of Constellation Research. Thank you so much for returning to theCUBE. Hey, how you doing? Good morning. Good morning. Good morning. Good morning. I don't know, I got all my accents wrong out here. So you got a shout out on the main stage this morning from Monica Kumar. Congratulations on that. She talked about you and your research on the infinite role of computing. You also do a lot with the future of work. I know that that is really, really right in your wheelhouse right now. What are you hearing? What are you seeing? What kinds of conversations are you having that are interesting you? Yeah, so this infinite computing option, it's one of the things that we're talking about, the fact that we can scale out forever, right? And the problem that's holding us back has been technical debt, right? So all that legacy that everyone's got to figure out, that's like, you know, my connections, my server, my disk recovery, my disaster recovery, backup, everything, you know, just, it's a pain in the butt, right? And I'm still trying to get onto the cloud, right? So on that end, we're like, okay, all this stuff is holding us back. How do we get there, right? Now, the future of work is a little bit different. We're seeing a very, very different set of work, right? People have talked about where we are in the gig economy, but that's just one aspect of it. Everything is being decomposed into microservices. So large processes are becoming smaller and smaller microservices, they're being reusable, where work and tasks are falling the same way, right? So we're getting smaller and smaller tasks, some are more repetitive, some are going to be automated, and it's really about where we actually find the difference between augmentation of humanity and full automation, and that's where the next battle's going to be. You know, Ray, some of the discussions we've been having this week is, you know, how do we really simplify the environment? You know, the balance I hear from customers, on the one hand, they're always like, I don't have enough money, I don't have enough personnel. On the other hand, oh my gosh, that full automation sounds like you're going to put me out on a job. We know, you know, we're not putting everybody out of work, you know, in the next couple of years. There are challenges, we worry about the hollowing out of the center of the economy. But, you know, here, what Nutanix is trying to do, of course, is I don't want to have to thrive in that complexity anymore. I want to be able to drive innovation, keep up with that, take advantage of that unlimited resources out there. So where do you see, you know, you've been here at the show, what are you hearing from the customers here? Anything different in Europe versus, you know, back in North America that you'd share about kind of that journey onto the changing roles? Oh, it's a great point, right? It's about simplifying everything where you can. It's about areas of automation where they make sense. Here in Europe, it's slightly different because a lot of the focus in Europe has been about cost and efficiency, right? Followed by, of course, regulatory. Those have been the two drivers and they've been battling that in order to be even able to look at some level of innovation. We're in the U.S., people are head on doing innovation, you know, regulatory and operational efficiency at the same time. So that creates a very, very different environment. But what we have noticed are some patterns, right? Especially when we look at automation and AI, there are four areas out of seven where we see a lot more automation that's happening, right? The first one is massively repetitive tasks. Those are things, yeah, you got to get that out of the way. We don't do this very, very well. The second one is really thinking about massive nodes of interaction. When you're connected to multiple places, multiple organizations, multiple instances, that's something where we start to get overwhelmed. And then of course, there is lots of volume. If you've got lots of volume requests that are coming through, you can't possibly handle that and that's a place where we see a lot of machine scale. And the last piece is really when you have to scale, humans don't scale very well. However, it's actually not a hauling out of the middle. It's actually a resume, it's a hauling out of the ends when a very, very real end because really, really simple tasks go away, super complex tests go away and the middle actually remains. And the middle is things that are complex that cannot be recreated by math. There are also areas that require a lot of creativity. Humans make the rules, we break the rules. And then the last part is really find motor skills and presence, the machines still aren't as good. So we still have some hope. So the middle stays, but it's the hauling out of the ends, the high-end jobs and the low-end jobs are the ones we're going to see a lot of risk. So what does that mean? So we have, we, leaving the middle there, I mean, and as you said, the high-end jobs and the low-end jobs go away, but what does that mean in terms of the skills, in terms of what employers are looking for, in terms of what they need in their perspective, applicants and hires? It's a great point. Soft skills are important. It's the qualitative skills that become even more important. It's also being able how to manage and orchestrate the hard skills, right? Because you don't necessarily have to know how to do the calculation. You have to just know which algorithm to apply. Okay, and then also the soft skills of managing people, I'm assuming too, because computers are not so good at that either. Yes, soft skills are managing people, but also manage the human and machine equation that's going to happen. Because we have to train the machines. The machines aren't going to know that level of intuition and there's a large amount of training that's going to happen over time. All right, so one of the things Nutanix is doing is as they've been transforming to not only subscription, software has always been at their core, but they're starting to do not just infrastructure software, but application software. I know you live in that world quite a lot, so when you hear Nutanix talking about building databases, delivering these services, it's something that I look at, like Amazon does some of that, but for the most part, they're infrastructure and build on top of us. How do you think, how is Nutanix doing? What are some of the challenges for them, going up against some of the bellwethers out there in tech and all the open source projects that are out there? So the challenge is always going to be, there is a one dominant player in every market. And what they're providing is an alternative to allow the orchestration of not having that, not only that dominant player, but a choice. And so in every single market, they're focused on giving users choice and giving them the ability to aggregate and bring everything into one single plane. That is tough to do. And the fact that they see that as their big harry audacious goal, that's impressive. If you said they were going to do this three years ago, I wouldn't have believed them. Well, yeah, I think back to remember almost 10 years ago, VMware tried to get an application. They bought Zimbra, they brought a few others. Cisco did like 26 adjacencies, they were going to take over video and do all those things. And we've seen lots of failures over the years. They re-focused on their core, was a big thing that I heard that the user seemed to be excited about. Are there areas that you find especially interesting as to where Nutanix is poking? So I would say that Nutanix three years ago was a little bit sleepy, right? They got comfortable, they did the stuff that they did really well. And it feels like maybe about 12 months ago, Duraj had a different vision. Like something snapped, something hit. He said, this isn't working, we're going to change things. And we've seen a whole bunch of new talent come into place. We've also seen a huge expansion of what they're trying to do. And a cleanup of all those side projects that were all going on before. So I think they've actually honed in on, okay, if we can simplify this piece, this is a money winning business for some time. And they're talking about 80% margins last quarter. I mean, that's huge, right? And that's just trying to save customers money and make their lives simpler. Do you think that they have the messaging, right? Because I mean, they're going to this Theruvian, Emersonian idea of simplify, simplify, simplify. And it does resonate, of course. What customer doesn't want a simpler computing experience? But do you think that they are reaching the right people and they have obviously very passionate customers, but are they getting into new businesses? I think they're getting into the businesses that their customers are asking them to. Those adjacencies are huge. I think when you think about cleaning up technical debt, all that legacy debt that you actually have to fix. I mean, this is where you begin. It's so hard to make that cloud journey to begin with. It's even harder to carry all that legacy with you. And we're going to see a lot more of this going forward. All right. So, Ray, talk a little bit about, I loved an event you did last year, the People-Centered Digital Future. Help explain to our audience what this is about and where you're taking it again this year. So that event was a one-time event. We were celebrating the 70th anniversary of the United Nations founding. We were celebrating almost 50 years of the internet and 50% of the world being connected to the internet. And part of the reason that was an important event was we really felt that there was a need to get back to the roots of where the internet had begun. And more importantly, talk about where we are today in the world, the privacy. One of the biggest challenges we have in a digital world is that your personal data, your genomics, all this information about you is being brokered for free. And what we have to do is take that back. And by taking that back, what I mean is we've got to make all these rights property right. If we can make that a property right, we can leverage the existing rules and legislation that's there, and we can actually start paying people for that data through consent and giving people that ability on consent to data could create lots of things from universal basic income to a brand new set of data accounting that equalizes the playing fields while keeping the large tech giants. Yeah, there's some of those big journeys that we went on. You talk about the internet. This year's 50th anniversary of the first walking on the moon. And you look at how entire countries rallied together, so much technology that's gone off of what they've done there. We need some rallying cries in today's day and age to solve some of these big day and age. Is that AI, is that, where are some of the big areas that you see tech needing to drive forward in the next decade? I think the big area is going to be around decentralization, giving individuals more empowerment. We've got large big tech companies that are, I'd say, imbalanced. We start companies right away, building monopolies on day one, and we don't open up those markets. And the question is how do we create a level playing field for the individual to be able to compete, to bring a new idea, and to innovate, if that's continuously stifled by big technology companies without an opportunity, we're in trouble. And so that starts by making data a property right to the personal data. It starts by also creating marketplaces for that data. And those marketplaces have to have regulations similar to capital market flows. The way we treat exchanges, we treat marketplaces, we need to do the same thing with the way we do data. And the third piece, there has to be some level of attacks that goes to all these data economies so that they can fund the infrastructure and the watchdogs that are there. Now this is coming from a free market. I'm a free market capitalist, okay? Like, I can't stand regulation, but I also realize it's so important that we have a fair market. But do you, so many, we know so much about how Americans are so much more cavalier about their privacy than even Europeans. What will it take to galvanize Americans to care about those little crumbs that they're leaving on the internet that is the data that you say should be a property right that we should be paid for? I think it's going to start with companies actually take and do the right thing where they actually give them that opportunity to monetize that information. Do they do that? I think the new set of startups are starting to do that. Because they're looking at the risk that's being posed at Facebook and Google and Amazon on the antitrust, DOJ, FCC, they're all coming in at the same time, FTC, they're all wondering, do we break these companies up or not? The short answer is I don't think they're going to. Because we are competing with China. And when you're looking at that scale data where Amazon's transactions are only one-tenth of Alibaba's, that's huge. So the consolidation has to happen, but we need to create a layer that actually democratizes and creates a fair trading play. And those startups you think can compete with established players? I think once we set the rules and the ground rules, I think people are going to be able to do that. But once you free that data, what are we competing on now? You have to pay for my consent. You have to earn my business. You can't trade it for free. Or just say, hey, look, you are the product. That changes everything. Yeah, it's a good point. All right, Ray, I know you spend a lot of time talking to and giving advice to some of the leaders in technology. You're welcome to get into some specifics about Nutanix or some of the cloud players, but what are some of the key themes? What are people getting right and what are they still doing wrong? Okay, so theme number one, this is going to be a multi-cloud hybrid world for a long time. Anybody that's bucking the multi-cloud trend, they've missed the point, right? Because we want portability and data. There's only two or three players in every single market. If I can't move my data and my workloads and my IO in and out, then you've actually created vendor lock-in from hell. And I think customers are going to protest against that. So the second one, and you guys are probably following this trend a lot, is really about AI ethics and design principles for AI. So what is ethical AI? We've got five things that are important. The first one is make sure it's transparent, right? See the algorithms, see what they're right. Second one, make sure it's explainable. Hey, bias is not a bad thing. So if I'm discriminating against red heads with left-handed and that happen to like, I don't know, Oracle, fine. But if that was unintended and you're discriminating against that, then we have to get rid of that, right? And so we have to figure out how to reduce that kind of bias if it's unwanted bias, right? If you discover that you're discriminating and not being inclusive, you've got to make sure that you address that. So then the next part is it's got to be reversible. And once you have that reversibility, we also make sure that we can train these systems over time. And then the last piece is must could be right. Must could be right. The machines might take over, but if you insert a human at the beginning of the process and at the end of the process, you won't get taken over. I want to hear about what the future of work looks like for Ray Wong. You are on the road constantly. You are moving your data from one place to another. You are everywhere all the time. So what do you have on next? What's exciting you about your professional life? I think the challenge is that we are living in a world where there's too much information, too much content. And you guys say this all the time, separating the signal from the noise. And people are willing to pay for that signal, but that is a very, very tough job. It's about the analysis, the insights. And when you have that, people don't want to read through your reports. They don't want to watch through the videos. They just want to call you up and say, hey, what's going on and get the short version of it? And that's what's making it very interesting because you'd expect this would be in a chatbot, it'd be in a robo-advisor. Doesn't work that way. People still want the human connection, especially given all that data out there. They want the analysis and insights that you guys provide. That's very, very important. But even more important right now, it's really about getting back to those relationships. I think people are very careful about the relationships they're keeping. They're also curating those relationships and coming back to spending more time. And so we're seeing a lot more of in-person meetings, in-person events, very, very small, curated conversations. And I think that's coming back. I mean, that's why we do our conference every year as well. I mean, that's, we try to keep two to 300 people intimately together. Those human connections. Human connections. Not going away. Nope, not going away in an automated AI digital world. This is our post-digital future. Excellent. Well, Ray, thank you so much for coming on theCUBE. It's always so much fun to talk to you. Hey, thanks a lot. My energy guy. My energy. I'm Rebecca Knight for Stu Miniman. We will have more from the Bella Center at Nutanix.next coming up in just a little bit.