(upbeat music) >> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Everyone, welcome to this CUBE conversation. I'm John Furrier with theCUBE, host of theCUBE here in our Palo Alto office for remote interviews during this time of COVID-19. We're here with the quarantine crew here in our studio. We've got a great guest here from Google, Will Grannis, managing director, head of the office of the CTO with Google Cloud. Thanks for coming on, Will. Appreciate you spending some time with me. >> Oh, John, it's great to be with you. And as you said, in these times, more important than ever to stay connected. >> Yeah, and I'm really glad you came on because a couple of things. One, congratulations to Google Cloud for the success you guys had. Saw a lot of big wins under your belt, both on the momentum side, on the business side, but also on the technical side. Meet is available now for folks. Anthos is doing very, very well. Partner ecosystem's developing. Got some nice use cases in vertical markets, so I want to get in and unpack with you. But really, the bigger story here is that the world has seen the future before it was ready for it. And that is the at-scale challenge that the COVID-19 has shown everyone. We're seeing the future has been pulled forward. We're living in a virtualized environment. It's funny to say that, virtualization (laughs). Server virtualization is a tech term, but that enabled a lot of things. We're living in a virtualized world now 'cause we have to, but this is going to set in motion a series of new realities that you guys have been experiencing and supporting for many, many years. But now as a provider of Google Cloud, you guys have to operate at scale, you have. And now the whole world realizes that scale is a big deal. And so you guys have had some successes. I want to get your thoughts on the this at scale problem that the world now realizes. I mean, everyone's at home. That's a disruption that was unforecasted. Whether it's under-provisioning VPNs in IT to a surface area for security, to just work and play. And activities are now confined, so people aren't convening anymore and it's a huge issue. What's your take on all this? >> Well, I mean, to your point just now, the fact that we can have this conversation and we can have it fluidly from our respective remote locations just goes to show you the power of information technology that underlies so many of the things that we do today. And for Google Cloud, this is not a new thing. And for Google, this is not a new thing. For Google Cloud, we had a mission of trying to help companies accelerate their transformation and enable them in these new digital environments. And so many companies that we've been working with, they've already been on the path to operating in environments that are digital, that are fluid. And when you think about the cloud, that's one of the great benefits of cloud, is that scalability in common with the business demand. And it also helps the scale situation without having to do the typical, "Oh wait, "you need to find the procurement people. "We need to find the server vendors. "We need to get the storage lined up." It really allows a much more fluid response to unexpected and unforecasted situations. Whether that's customer demand or in this case a global pandemic. >> Yeah, one of the things I want to get in with you on, you have explained what your job is there 'cause obviously Google's got a new CEO now for over a year. Thomas Kurian came from Oracle, knows the enterprise up and down. You had Diane Greene before that. Again, another enterprise leader. Google Cloud has essentially rebuilt itself from the original Google Cloud to be very enterprise centric. You guys have great momentum, and this is a world where cloud-native is going to be required. I mean, everyone now sees it. The tide has been pulled out, everything's exposed, all the gaps in business from a tech standpoint is kind of exposed. And so the smart managers and companies are looking at things and saying, "Double down on that. "Let's kill that. "We don't want to pay that supplier. "They're not core to our business." This is going to be a very rapid acceleration of what I call a vetting of the new set of players that are going to emerge because the folks who don't adapt to this new cloud-native reality, whether it's app workloads for banking to whatever are going to have to reinvent themselves now and reset and tweak to come out of this crisis. So it's going to be very cloud-native. This is a big deal. Can you share your reaction to that? >> Absolutely. And so as you pointed out, there are kind of two worlds that exist right now. Companies that are moving to become more digital and transform, and you mentioned the momentum in Google Cloud just over the last year, greater than 50% revenue growth. And in a greater than $10 billion run rate business and adding customers at a really quick clip, including just yesterday, Splunk, and along the way, Telecom Italia, Major League Baseball, Vodafone, Lowe's, Wayfair, Activision Blizzard. This transformation and this digitization is not just for a few or just for any one industry. It's happening across the board. And then you add that to the implementations that have been happening across Shopify and the Spotify and HSBC, which was a early customer of ours in the cloud and it already has a little bit of a headstart into this transformation. So you see these new companies coming in and seeing the value of digital transformation. And then these other companies that have kind of lit the path for others to consider. And Shopify is a really good example of how seeing drastic uptick in demand, they're able to respond and keep roughly half a million shops up and running during a period of time where many retailers are trying to figure out how to stay online or even get online. >> Well, what is your role at Google? Obviously, you're the managing director. Title is managing director, head of the office of the CTO. We've seen these roles before, head of the CTO, obviously a technical role. Is it partnering with the CEO on strategy? Is it you're tire kicking new things? Are you overseeing any strategic initiatives? What is your role? >> So a little bit of all of those things combined into one. So I spent the first couple of decades of my career on the other side of the fence in the non-tech community, both in the enterprise. But we were still building technology and we were still digitally minded. But not the way that people view technology in Silicon Valley. And so spending a couple of decades in that environment really gave me insights into how to take technology and apply them to a specific problem. And when I came to Google five years ago, selfishly, it was because I knew the potential of Google's technology having been on the other side. And I was really interested in forming a better bridge between Google's technology and people like me who were CTOs of public companies and really wanted to leverage that technology for problems that I was solving. Whether it was aerospace, public sector, manufacturing, what have you. And so it's been great. It's the role of a lifetime. I've been able to build the team that I wanted as an enterprise technologist for decades and the entire span of technologies at our disposal. And we do two things. One is we help our most strategic customers accelerate their path to cloud. And two, we create these signals by working with the top companies moving to the cloud and digitally transforming. We learned so much, John, about what we need to build as an organization. So it also helps balance out the Google driven innovation with our customer driven innovation. >> Yeah, and I can attest. I've been watching you guys from day one. Hired a lot of great enterprise people that I personally know. So you get in the enterprise chops and stuff and you've seen some progress. I have to ask you though, because first of all, big fan of Google at scale from knowing them from when they were just a little search engine to what they are now. There was an expression a few years ago I heard from enterprise customers. It goes along the lines like this. "I want to be like Google," because you guys had a great network, you had large scale. You had all these things that were like awesome. And then they realized, "Well, we can't be like Google. "We don't have SREs. "We don't have large scale data centers." So there was a little bit of a translation, and I want to say a little bit of a overplay of the Google hand, and you guys had since realized that it wasn't just people are going to bang at your doorstep and be adopting Google Cloud because there was a little bit of a cultural disconnect from wanting to be like Google, then leveraging Google in their business as they transform. So as you guys have moved from that, what's changed? They still want to be like Google in the sense you have great security, got a great network, and you've got that scale. Enterprises are a little bit slower to adopt that, which you're focused on now. What is the story there? Because I think that's kind of the theme that I'm hearing. Okay, Google now understands me. They know I'm not as fast as Google. They got super great people (laughs). We are training our people. We're retraining them. This is the transformation that they're going through. So you might be a little bit ahead of them certainly, but now they need to level up. How do you respond to that? >> Well, a lot of this is the transformation that Thomas has been enacting over the last year plus. And it comes in kind of three very operational or tactical pillars that I think of. First, we expanded our customer and we continue to expand our customer facing teams. Three times what they were before because we need to be there. We need to be in those situations. We need to hear from the customer. We need to learn more about the problems they're trying to solve. So we don't just take a theoretical principle and try to overlay it onto a problem. We actually get very visceral understanding of what they're trying to solve. But you have to be there to gain that empathy and that understanding. And so one is showing up, and that has been mobilizing a much larger engine of customer facing personnel from Google. Second, it's also been really important that we evolve our own. Just as Google brought SRE principles and principles of distributed systems and software design out to the world, we also had a little bit to learn about transitioning from typical customer support and moving to more customer experience. So you've seen that evolution under Thomas as well with cloud changing... Moving from talking about support to talking about customer experience, that white glove experience that our customers get and our partners get from the beginning of their journey with us all the way through. And then finally making sure that our product roadmap has the solutions that are relevant across key priority industries for us. Again, that only comes from being present from having a focus in those industries and then developing the solutions that progress those companies. This isn't about taking a principle and trying to apply it blindly. This is about adding that connection, that really deep connection to our customers and our partners and letting that connection manifest the things that we have to do as a product company to best support them over a long period of time. I mean, look at some of these deals we've been announcing. These are 10-year, five-year, multi-year strategic partnerships that go across the canvas of all of Google. And those are the really exciting scaled partnerships. But to your point, you can't just take SRE from Google and apply it to company X, but you can things like error budgets or how we think about the principles of SRE, and you can apply them over the course of developing technology, collaborating, innovating together. >> Yeah, and I think cloud-native is going to be a key thing. It's just my opinion, but I think one of those situations where the better mouse trap will win. If you're cloud-native and you have APIs and you have the kind of services, people will beat it to your doorstep. So I got to ask you, with Thomas Kurian on board, obviously, we've been following his career as well at Oracle. He knows what he's doing. Comes into Google, it's being built out. It's like a rocket ship at this point. What bet is he making and what bet are you guys making on behalf of your customers? If you had to boil it down to Google Cloud's big bet, what is the bet on the technology side? And what's the bet on the business side? >> Sure. Well, I've already mentioned... I've already hinted at the big strategy that Thomas has brought in. And that's, again, those three pillars. Making sure that we show up and that we're present by having a scaled customer facing organization. Again, making sure that we transition from a typical support mindset into more of a customer experience mindset and then making sure that those solutions are tailored and available for our priority industries. If I was to add more color to that, I think one of the most important changes that Thomas has personally been driving is he's been converting us to a partner-led business and a partner-led organization. And this means a lot of investments in large global systems integrators like Accenture and Deloitte. But this also means that... Like the Splunk announcement from yesterday, that isn't just a sell to. This is a partnership that goes deep across go-to market product and sell to. And then we also bring in very specific partners like Temenos in Europe for financial services or a CETA or a Rackspace for migrations. And as a result, already, we're seeing really incredible lifts. So for example, nearly 200% year over year increase in partner influenced revenue in Google Cloud and almost like a 13X year over year increase in new customers won by partners. That's the kind of engine that builds a real hyper-scale business. >> Interesting you mentioned Splunk. I want to get to that in a second, but I also noticed there was a deal with TELUS Group on eSIM subscriptions, which kind of leads me into the edge piece. There's a real edge component here with Google Cloud, and I think I had a conversation with Jennifer Lynn a few years ago, really digging into the built-in security and the value of the Google network. I mean, a lot of the scuttlebutt around the Valley and the industry is Google's got an amazing network. Software-defined networking is going to be a hot programmable area. So you got programmable networking and you got edge and edge security. These are killer areas that need innovation. Could you comment on what you guys are doing there and do you agree? Obviously, you have a killer network and you're leveraging it. Can you just give some insight into what's going on in those two areas? Network and then the edge. >> Yeah, I think what you're seeing is the manifestation of the progression of cloud generally. And what do I mean by that? It started out as like get everything to the data center. We kind of had this thought that maybe we could take all the workloads and we could get them to these centralized hubs and that we could redistribute out the results and drive the latency down over time so we can expand the portfolio of applications and services that would become relevant over time. And what we've seen over the last decade really in cloud is an evolution to more of a layered architecture. And that layered architecture includes kind of core data centers. It includes CDN capacity, points of presence, it includes edge. And just in that list of customers over the last year I mentioned, there were at least three or four telcos in there. And you've also probably heard and seen quite a bit of telco momentum coming from us in recent announcements. I think that's an indication that a lot of us are thinking about, how can we take technology like Anthos, for example, and how could we orchestrate workloads, create a common control plane, manage services across those three shells, if you will, of the architecture? And that's a very strategic and important area for us. And I think generally for the cloud industry, is expanding beyond the data center as the place where everything happens. And you can look at Google Fi, you can look at Stadia. You can look at examples within Google that go well beyond cloud as to how we think about new ways to leverage that kind of criteria. >> All right, so we saw some earnings come out on Amazon side as Google, both groups and Microsoft as well, all three clouds are crushing it on the cloud side. That's a tailwind, I get that. But as it continues, we're expecting post-COVID some redistribution of development dollars in projects. Whether it's IT going cloud-native or whatever new workloads. We are predicting a Cambrian explosion of new things from core to edge. And this is going to create some lifts. So I want to get your thoughts on you guys' strategy with go-to market, as well as your customers as they now have the ability to build workloads and apps with AI and data. There seems to be a trend towards the verticalization of whether it's sales and go-to market and/or specialism because you have horizontal scalability with cloud and you now have data that has distinct (chuckles) value in these verticals. So it's really seems to be... I won't say ratification, but in a way, that seems to be the norm. Whether you come into a market and you have specialization, but the data is there so apps can be more agile. Are you guys seeing that? And is that something that you guys are considering from an organization standpoint? And how do customers think about targeting vertical industries and their customers? >> Yeah, I bring this to... And where you started going there at the end of the question is exactly the way that we think about it as well. Which is we've moved from, "Here are storage offers for everybody, "and here's basic infrastructure for everybody." And now we've said, "How can we make sure "that we have solutions that are tailored "to the very specific problems that customers "are trying to solve?" And we're getting to the point now where performance and variety of technologies are available to be able to impose very specific solutions. And if you think about the substrate that has to be there, we mentioned you have to have some really great partners, and you have to have a roadmap that is focused on priority solution. So for example, at Google Cloud, we're very focused on six priority vertical areas. So retail, financial services, healthcare, manufacturing and industrials, healthcare life sciences, public sector. And as a result of being very focused in those areas, we can make more targeted investments and also align our entire go-to market system and our entire partner ecosystem... Excuse me, ecosystem around those bare specific priority areas. So for example, we work with CETA and HDA Healthcare very recently to develop and maintain a national response portal for COVID-19. And that's to help better inform communities and hospitals. We can use Looker to help with like a Commonwealth Care Alliance nonprofit and that helps monitor patient symptoms and risk factors. So we're using a very specific focus in healthcare and a partner ecosystem to develop very tailored solutions. You can also look at... I mentioned Shopify earlier. That's another great example of how in retail, they can use something like Google Meet, inherent reliability, scalability, security, to connect their employees during these interesting times. But then they can also use GCP, Google Cloud Platform to scale out. And as they come up with new apps and experiences for their shoppers, for their shops, they can rapidly deploy, to your point. And those solutions and how the database performs and how those tiers perform, that's a very tight-knit feedback loop with our engineering teams. >> Yeah, one of the things I'm seeing obviously with the virtualization of the COVID is that when the world gets back to normal, it'll be a hybrid. And it'll be a hybrid between reality, not physical and a hundred percent virtual, hybrid. And that's going to impact events too, media, to everything. Every vertical will be impacted. And I want to point out the Splunk deal and bring that back in because I want you to comment on the relevance of the Splunk deal in context to Splunk has a cloud. And they've got a great slogan, "Data for everywhere." "Data to everywhere," I think it is. But theCUBE, we have a cloud. Every company will have a cloud scale. At some level, we'll progress to having some sort of cloud because they have data. How are you guys powering those clouds? Because I think the Splunk deal is interesting. Their partner, their stock price was up out on the news of the deal. Nice bump there for Splunk, shout out to those guys. But they're a data company and now they're cross-platform. But they're not Google, but they have a cloud. So you know what I'm saying? So they need to play in all the clouds, but they need infrastructure (laughs), they need support. So how do you guys talk to that customer that says, "Hey, the next pandemic that comes, "the next crisis that's going to cause some "either social disruption or workflow disruption "or supply chain disruption. "I need to be agile. "I need to have full cloud scale. "And so I need to talk to Google." What do you say to them? What's the pitch? And does the Splunk deal mirror some of those capabilities? Or tie that together for us, the Splunk deal and how it relates to how to proof themselves for the future. Sorry. >> For example, with the Splunk cloud deal, if you take a look at what Google is already really good at, data processing at scale, log analytics, and you take a look at what Splunk is doing with their events and security incident monitoring and the rest, it's a really great mashup because they see by platforming on Google Cloud, not only do they get highly performing infrastructure. But they also get the opportunity to leverage data tools, data analytics tools, machine learning and AI that can help them provide enhanced services. So not just about capacity going up and down through periods of demand, but also enhancing services and continuing to offer more value to their customers. And we see that as a really big trend. And this gets at something, John, a little bit bigger, which is kind of the two views of the world. And we talked about very tailored, focused solutions. Splunk is an example of taking a very methodical approach to a partnership, building a solution specifically with partners. And in this case, Splunk on the security event management side. But we're always going to provide our data processing platform, our infrastructure for companies across many different industries. And I think that addresses one part of the topic, which is, how do we make sure that in periods of demand rapidly changing, and this goes back to the foundational elements of infrastructure as a service and elasticity. We're going to provide a platform and infrastructure that can help companies move through periods of... It's hard to forecast, and/or demand may rise and fall in very interesting ways. But then there's going to be times where we... Because we're not necessarily a focused use case where it may just be generalized platform versus a focused solution. So for example, in the oil and gas industry, we don't develop custom AI, ML solutions that facilitate upstream extraction, for example. But what we do do is work with renewable energy companies to figure out how they might be able to leverage some of our AI machine learning algorithms from our own data centers to make their operations more efficient and to help those renewable energy companies learn from what we've learned building out what I consider to be a world leading renewable energy strategy and infrastructure. >> It's a classic enablement model where you're enabling your platform for your customers. Okay, so I've got to ask the question. I asked this to the Microsoft guys as well because Amazon has their own SaaS stuff. But really more of end to end. The better product's usually on the ecosystem side. You guys have some killer SaaS. G Suite, we're a customer. We use the G Suite really deeply. We also use some Bigtable as well. I want to build a cloud, we have a cloud, CUBE cloud. But you guys have Meet. So I want to build my product on Google Cloud. How do I know you're not going to compete with me? Do you guys have those conversations around the trade-off between the pure Google services, which provide great value for the areas where the ecosystem needs to develop those new areas that are going to be great markets, potentially huge markets that are out there. >> Well, this is the power of partnership. I mentioned earlier that one of the really big moves that Thomas has made has been developing a sense of partners. And it kind of blurs the line between traditional, what you would call a customer and what you would call a partner. And so having a really strong sense of which industries we're in, which we prioritize, plus having a really strong sense of where we want to add value and where our customers and partners want to add that value. That's the foundational, that's the beginning of that conversation that you just mentioned. And it's important that we have an ability to engage not just in a, "Here's the cloud infrastructure piece of the puzzle." But one of the things Thomas has also done and a key strategy of his has been to make sure that the Google Cloud relationship is also a way to access all amazing innovation happening across all of Google. And also help bring a strategic conversation in that includes multiple properties from across Google so that an HSBC and Google and have a conversation about how to move forward together that is comprehensive rather than having to wonder and have that uncertainty sit behind the projects that we're trying to get out and have high velocity on because they offer so much to retail bank, for example. >> Well, I've got a couple more questions and then I'll let you go. I know you got some other things going on. I really appreciate you taking the time, sharing this great insight and updates. As a builder, you've been on the other side of the table. Now you're at Google heading up the CTO. Also working with Thomas, understanding the go-to market across the board and the product mix. As you talk to customers and they're thinking... The good customers are thinking, "Hey, "I want to come out of this COVID on an upward trajectory "and I want to use this opportunity "to reset and realign for the future." What advice do you have for those enterprises? They could be small, medium-sized enterprises to the full large big guys. And obviously, cloud-native, we've talked some of that already, but what advice would you have for them as they start to really prioritize, as some things are now exposed? The collaboration, the tooling, the scale, all these things are out there. What have you seen and what advice would you give a CXO or CSO or a leader in the industry to think about and how they should come out of this thing, how they should plan, execute, and move forward? >> Well, I appreciate the question because this is the crux of most of my day job, which is interacting with the C-suite and boards of companies and partners around the world. And they're obviously very interested to learn or get a data point from someone at Google. And the advice generally goes in a couple of different directions. One, collaboration is part of the secret sauce that makes Google what it is. And I think you're seeing this right now across every industry, and whether you're a small, medium-sized business or you're a large company, the ability to connect people with each other to collaborate in very meaningful ways, to share information rapidly, to do it securely with high reliability, that's the foundation that enables all of the projects that you might choose to... Applications to build, services to enable, to actually succeed in production and over the long haul. Is that culture of innovation and collaboration. So absolutely number one is having a really strong sense of what they want to achieve from a cultural perspective and collaboration perspective and the people because that's the thing that fuels everything else. Second piece of advice, especially in these times where there's so much uncertainty, is where can you buy down uncertainty with...? You can learn without a high penalty. This is why cloud I think is really, really finding super scale. It was already on the rise, but what you're seeing now as you've laid back to me during this conversation, we're seeing the same thing, which is a high increase in demand of, "Let's get this implemented now. "How can we do this more? "This is clearly one way to move through uncertainty." And so look for those opportunities. I'll give you a really good example. Mainframes, (chuckles) one of the classic workloads of the on-premise enterprise. There are all sorts of potential magic solves for getting mainframes to the cloud and getting out of mainframes. But a practical consideration might be maybe you just front-end it with some Java. Or maybe you just get closer to other data centers within a certain amount of milliseconds that's required to have a performant workload. Maybe you start chunking at art and treat the workload a little bit differently rather than just one thing. But there are a lot of years and investments in our workload that might run on a mainframe. And that's a perfect example of how biting off too much might be a little bit dangerous, but there is a path to... So for example, we brought in a company called Cornerstone to help with those migrations. But we also have partnerships with data center providers and others globally plus our own built infrastructure to allow even a smaller step per se for more close proximity location of the workload. >> It's great. Everything kind of has a technical metaphor connection these days when you have a internet, digitally connected world. We're living in the notion of a digital business, was a research buzzword that's been kicked around for years. But I think now COVID-19, you're seeing the virtual or digital, it's really digital, but virtual reality, augmented reality is going to come fast too. Really get people to go, "Wow. "Virtualization of my business." So we've been kind of kicking around this term business virtualization just almost as a joke, but it's really more about, okay, this is about a new world, new opportunity to think about when we come out of this, we're going to still go back to our physical world. Now, the hybrid now kicks in. This kind of connects all aspects of business in every vertical. It's not like, "Hey, I'm targeting this industry." So there might be unique solutions in those industries, but now the world is virtualized. It's connected, it's a digital environment. These are huge concepts that I think has kind of been a lunatic fringe idea, but now it's brought mainstream. This is going to be a huge tailwind for you guys as well as developers and entrepreneurs and application software. This is going to be, we think, a big thing. What's your reaction to that? Based on your experience, what do you see happening? Do you agree with it? And do you have anything you might want to add to that? >> Maybe one kind of philosophical statement and then one more... I bruised my shins a lot in this world and maybe share some of the black and blue coloration. First from a philosophical standpoint, the greater the crisis, the more open-minded people become and the more creative people get. And so I'm really excited about the creativity that I'm seeing with all of the customers that I work with directly, plus our partners, Googlers. Everybody is rallying together to think about this world differently. So to your point, a shift in mindset, there are very few moments where you get this pronounced change and everyone is going through it all at the same time. So that creates an opportunity, a scenario where you're bold thinking new strategies, creativity. Bringing people in in new ways, collaborating in new ways and offer a lot of benefits. More practically speaking and from my experience, building technology for a couple decades, it has an interesting parallel to building tightly coupled, really large maybe monoliths versus microservices and the debate around, "Do we build small things "that can be reconfigured and built out by others "or built upon by others more easily? "Or do we create a golden path and a more understood development environment?" And I'm not here to answer the question of which one's better because that's still a raging debate. But I can tell you that the process of going through and taking a service or an application or a thing that we want to deliver to a customer, that one of our customers wants to deliver to their customer. And thinking about it so comprehensively that you're able to think about it in, what are its core functions? And then thinking methodically about how to enable those core functions. That's a real opportunity, and I think technology to your point is getting to the place where if you want to run across multiple clouds, this is the Anthos conversation were recently GA'ed. Global scale platform, multicloud platform, that's a pretty big moment in technology. And that opens up the aperture to think differently about architectures and that process of taking an application service and making it real. >> Well, I think you're right on the money. I think philosophically, it's a flashpoints opportunity. I think that's going to prove to be accelerating and to see people win faster and lose faster. You're going to to see that quickly happen. But to your point about the monolith versus service or decoupled based systems, I think we now live in a world where it's a systems view now. You can have a monolith combined with decoupled systems. That's distributed computing. I think this is the trend, it's a system. It's not one thing or the other. So I think the debate will continue just like VI versus Emacs (chuckles). We don't know, right? People are going to have the debate, but if you think about it as a system, the use case defines your architecture. That's the beautiful thing about the cloud. So great insight, I really appreciate it. And how's everything going over there at Google Cloud? You've got Meet that's available. How's your staff? What's it like inside the Googleplex and the Google Cloud team? Tell us what's going on over there. People still working, working remote? How's everyone doing? >> Well, as you can tell from my scenario here, my backdrop, yes, still part at work. And we take this as a huge responsibility. These moments as a huge responsibility because there are educators, loved ones, medical professionals, critical life services that run on services that Google provides. And so I can tell you we're humbled by the opportunity to provide the backbone and the platform and the people and the curiosity and the sincere desire to help. And I mentioned a couple of ways already just in this conversation where we've been able to leverage some of our investments technology to help form people that really gets at the root of who we are. So while we just like any other humans are going through a process of understanding our new reality, what really fires us up and what really charges us up is because this is a moment where what we do really well is very, very important for the world in every geo, in every vertical, in every use case, in every solution type. We're taking that responsibility very seriously. And at the same time, we're trying to make sure that all of our teams as well as all of the teams that we work with and our customers and partners are making it through the human moment, not just the technology moment. >> Well, congratulations and thanks for spending the time. Great insight, Will. Appreciate, Will Grannis, managing director, head of technology office of the CTO at Google Cloud. This certainly brings to the mainstream what we've been in the industry been into for a long time, which is DevOps, large scale, role of data and technology. Now we think it's going to be even more acute around societal benefits. And thank God we have all those services for the frontline workers. So thank you so much for all that effort and thanks for spending the time here in theCUBE Conversation. Appreciate it. >> Thanks for having me, John. >> Okay, I'm John Furrier here in Palo Alto studios for remote CUBE Conversation with Google Cloud, getting the update. Really looking at the future as it unfolds. We are going to see this moment in time as an opportunity to move to the next level, cloud-native and change not only the tech industry but society. I'm John Furrier, thanks for watching. (upbeat 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)