>> Welcome back to the cubes, ongoing coverage of VMworld 2021 the second year in a row. We've done this virtually. My name is Dave Volante and long time VMware technologist and new CTO kit Colbert is here. Kit welcome good to see you again. >> Thanks Dave, super excited to be here. >> So let's talk about your new role, you've been at VMware. You've touched all the bases, so to speak and, you know, love the career evolution, you're ready for this job. So tell us about that role. >> Well, I hope so. I don't know. It's definitely a big step up been here at VMware for 18 years now, which if you're not Silicon valley, you know, that's a long time. It's probably like four or five normal Silicon valley lifetime in terms of stints at a company. But I love it. I love the company, I love the culture. I love the technology and I'm super passionate, super excited about it. And so, you know, the, the new role previously, I was CTO for one of our business groups and focused on a specific set of our products and services. But now as the corporate CTO, I really am overseeing all of VMware, R and D. In the sense of really trying to drive a whole bunch of core engineering transformations, right? Where we've talked a lot about our shift toward becoming a SAS company. So, you know, a cloud services company. And so there's a lot of changes. We got to make internally, technologies, platform services we need to build out, you know, the, the sort of culture aspects of it again. And so, you know, I'm kind of sitting at the center of that and it's, I'll be honest, it's big, there's a lot of stuff to go and do, but I am just super excited about it. Wake up every day, really excited to meet a whole bunch of new people across the organization and to learn all the cool things we're doing, it's just, well, you know, I'll say it again, like the level of innovation happening inside of VMware is just insane. And it's really cool now that I get kind of more of a front and center road to see everything that's happening. >> Well and when I was preparing for the interview with Ragu, I was thinking about, you know, I've been following VMware for a long time, and I sort of noted that it's like the fourth wave of executive management and sort of went back and said, okay, yes, we know it started with, you know, workstation. Okay, fine. But then really quickly went into really changing the way in which we think about servers, server utilization and driving. I remember the first time I ever saw a demo, I said, wow, this is going to be completely game changing. And really, and then, and then thought about the era of the software defined data center, fine tuning the cloud strategy. And then this explosion of innovation, whether it was the sort of NSX piece, the acquisitions you've made around security, again, more cloud expansion. And now you're laying out sort of this Switzerland from multi-cloud combined with this as you're pointing out this as a service model. So when you think about the technical vision of the company transforming into a cloud and subscription model, what does that mean from a sort of architectural standpoint or a mindset perspective? >> Oh yeah. Both great questions, both sort of key focus areas for me. And by the way, it's something I've been thinking about for quite a while, right? Yeah so you're right. Like we are on our third or fourth lap of the track depending on, on how you count. But I also think that this one that this notion of getting into multicloud of becoming a real cloud services company is going to be probably the biggest one for us. And the biggest transformation that we're going to have to make. You know, we, we did extend from core compute virtualization to network and storage, but the software defined data center. But now these things I think are a bit more fundamental. So, you know, how are we thinking about it? But we're thinking about it in a few different ways. I do think, as you mentioned, the mindset is definitely the most important thing. This notion that, you know, we no longer really have product teams purely. They should be thinking of themselves as service teams and the idea being that they are operating and accountable for the availability of their cloud service. And so this means we really need to step up our game. We have in terms of the types of tooling that we built, but really it's about getting these developers engaged with that, to know that, hey, like what matters most of all right now is that service availability. In addition to things like security compliance, et cetera, but we have monitoring systems to tell you, hey, there's a problem. And that you need to go jump on those things immediately. This is not like, you know, a normal bug that comes in, oh, I'll get to it tomorrow or whatever. It's like, no, no, no, you got to step up and really get there immediately. And so there is that big mindset shift. That's something we've been driving the past few years, but we need to continue to push there. And as part of that, you know, the other thing we're doing is that what we've seen is that a lot of our individual teams have gone out and build like really great cloud services. But what we really want to build to enable us to accelerate that is a platform, a true SaaS platform and leveraging all these great capabilities that we have to help all of our teams go faster. So it gets to things like standardization and really raising the bar across the board to allow all these teams to focus on what makes their products or services unique and differentiated rather than, you know, just doing the basic blocking and tackling. So those are a couple of things I'm really focused on both driving the mindset shift. You know, I think when I, you know, as I was taking on this role, I did a lot of reading on other CTOs and, you know, how do they view their roles within their companies? And one of the things I did hear there was that the CTO is kind of the I dunno, the keeper is the right word, but the keeper of the engineering culture, right. That you want to really be a steward for that to help take it forward in the right sort of directions that align with the strategic direction of the business. And so that's a big aspect for what I'm thinking about. And the second one, the SAS platform, one of the really interesting things about this reorg that we've done internally is that traditionally CTO has kind of focused, you know, outbound, maybe a little bit inbound, but typically don't have large engineering organizations, but here what we want to do, because this, this SAS platform is so important to us. We did centralize it within the office of the CTO. And so now, you know, my customers from an engineering standpoint are all the internal business units. So a lot of really big changes inside VMware, but I think this is the sort of stuff we need to do to help us really accelerate toward the multi-cloud vision that we're painting. >> Well, VMware has always had a super strong engineering culture. And I like the way you phrase that the steward of the engineering culture, when you think about a product mindset, when, of course correct me, if I'm off here, but when you're building a product and you're making that thing rock solid, you want more rich to talk about the hardened top, and so it seems to me that the services mindset expands the mind a little bit in terms of what other services can I integrate to make my service better. Whether that's a machine intelligence service or a security service, or, you know, the dozens of other services that you guys are now building the combination of that innovation is, has like a step function and a lever on top of the sort of traditional product mindset. >> Yeah, there is, I think you're absolutely right. There's a ton of like really fundamental mental mindset shifts, right? That are a part of that. And the integration piece, you mentioned super critical, but I also think it's, it's actually taking a step back and looking at the life cycle more holistically when you're thinking about a product you're thinking about, okay, I get the bits together, I'm going to ship it out, but then it's really up to the customer to go deploy that, to operate it and, you know, deal with problems and bugs that come up. And when you're delivering a cloud service, those are all problems that you, as the application creator have to deal with. And so you got to be on top of all those things. And, you know, if you design something in such a way that it becomes kind of hard to bug it runtime, well, that's going to directly impact your availability that might have, you know, contractual obligations with an SLA impact to a customer. So there's some really big implications there that I think traditionally product teams didn't always fully think through, but now that they sort of have to with a cloud service. The other point, I think that's really important, there is the notion of simplicity and ease of use experience is always important, right? Customer experience, user experience, but it gets even more magnified in a SaaS type of environment because the idea is that you shouldn't have to talk to anybody view, you as a user, should be able to go and call an API and start using this thing right and swipe a credit card and you're good to go. And so, you know, that sort of maniacal focus on how you just remove roadblocks, remove any unnecessary things between that customer and getting the value that they're looking for. So in general, the thing that I really love about SaaS and cloud services is that they really align incentives very well. What you want to do as an application builder, as a solution builder really aligns well with what customers are looking for. And you can get that feedback very, very rapidly, which allows for much quicker evolution of the underlying product and application. >> So one of the other things I learned from my interview with Ragu and I couldn't go deep into it. I did a little bit with summit, but I want to get your perspectives as well as I always talk about this obstruction layer across clouds, hybrid, multicloud edge extract, extracting, the complexity of the, you know, the underlying complexity, and Ragu was sort of it's nuance, but he said, okay, but the thing is, we're not trying to limit access to the primitives. We want to allow developers to go there to the extent they want to and my takeaway was okay, but the, the abstraction is you want to be that single management layer with access to the deep primitives and APIs of the respective clouds. But simplify to your point across those estates at the management layer, and maybe you could add some color to that. >> Yeah you know, it's a really interesting question. And but let me tell you about how we think about it because you're right. And that the, you know, the abstractions can sometimes find the underlying primitives and capabilities. And so Ragu is getting at, hey, like we don't necessarily force you one way or the other. And here's the way to think about it is that it's really about delivering optionality. And we do that through offering these abstractions at different layers. So to your point, Dave, like we have a management capabilities that can enable you to manage consistently across all types of clouds, public, private, edge, et cetera, irrespective of what that underlying infrastructure is. And so you look at things that are like our V realize suite of products or cloud health or tons, and tons of mission control is really focused on that one as well. But then we also have our infrastructure layer. That's what we're doing with VMware cloud and this notion of delivering consistent infrastructure. Now, even though, the core sort of IS layer is more consistent, you still get great flexibility in terms of the higher level services. If you want to use a database from one of the public clouds or messaging system or streaming services, you know, AI, whatever it is, you still got that sort of optionality as well. And so the reason that we offer these different things is because customers are just in different places. As a matter of fact, a single customer may have all of those different use cases, right? They may have some apps where they're moving from on-prem and the cloud, they want to do that very quickly. So, boom, we can just do it really fast with VMware cloud consistent infrastructure, we can vMotion that thing up in the cloud. Great. But for other ones, maybe a modern app they're building and maybe a team has chosen to use native AWS for that, but they want to leverage Kubernetes. So there you could put in a ton of mission control to give them that, you know, consistent management across sites or leverage cloud health to understand costs and to really enable the application teams to manage costs on their own. So I think, you know, I always go back to that concept of optionality, like we offer sort of these different levels of abstraction. And it really depends on what the use case is because the reality is especially for a complex enterprise, they're likely going to have all those use cases. >> You know. I want to stay on optionality for a moment because you're essentially becoming a cloud company. I'm expanding the definition of cloud and that's, which I think is appropriate because the cloud is expanding. It's going on, prem, it's going out to the edge hybrid connections across clouds, et cetera. And when you look at the public cloud players there, they all are deep into what I'll call data management. I'm not even sure what that term means anymore sometimes, but certainly they all own own databases, but they also offer databases from folks. You I go back to something Moritz said with the software mainframe that we want to be able to run any workload, you know, anywhere and, and have high reliability recovery, you know, lowest costs, et cetera. It doesn't seem as though you're going to run those, those workloads project Monterey is about supporting new workloads, but it doesn't seem like you have aspirations to, own sort of the database layer, for example, what's your philosophy around that? >> Not generally I mean, we do have some solutions like Greenplum, for instance, that play in that space, more of a data warehouse solution. But generally speaking, you're absolutely right. You know, VMware success was built through tight partnerships. We have a very, very broad partner network. And of course we see hyperscalers as great partners as well. And so, you know, I think if we get back to like, what's the core of VMware, it really is providing those powerful abstractions in the right places, at the infrastructure level, at the management level and so forth. But yeah, we're not trying to necessarily compete with everyone reinvent the world, what we're trying to do is, and by the way, if I just take a step back when we talk to customers, what really drives them toward multi clouds toward using multiple clouds is the fact that they want to get after these, what we call best of breed cloud services, that many of the different public clouds offer databases and AI and ML systems. And for each app team, the exact one that perfectly meets their needs, maybe different, right? Maybe on one cloud versus another cloud. And so that is really the optionality that we want to optimize for when we talk to those customers that they want the easiest way of getting that app onto that cloud. So we can take advantage of that cloud service, but what they worry about is the lack of consistency there. And that goes across the board. You know, if something fails at two AM, you have to wake up and go fix it. Do you have like the right sort of tooling in place, if it's fails on one cloud versus another, do you have to like, you know, scramble to figure out which tools to go use, how to go, you know, which dashboard to look at? I was like, no, they want kind of a consistent one. When you think about, from a security perspective, how do you drive a secure software supply chain? How do you prevent the types of attacks that we've seen in the past few years where people insert malicious code into your supply chain, and now you're running with hack code out there. And if you have different teams doing different things across different clouds, well, that's going to just open up sort of a can of worm, of different possibilities there for hackers to get in. So that's why this consistency is so important. And so, you know, if, I guess if we refine, the optionality a little bit, that point it's about getting optionality around cloud services and that those, like, those are the things that really differentiate. And so that, you know, we're not trying to compete with that. We're saying, hey, like we want to bring customers to those and give them the best experience that they can irrespective of whether that's in the public cloud or on prem or even at the edge. >> That's a huge technical challenge and amazing value for customers, I want to ask you, there's a lot of talk about ESG today. How does that fit into the CTO mindset? Is it a bolt-on, is it as it is fundamental component? >> Yeah the idea there is that if we look at the core values for VMware, this is something that's hugely important and something that we've actually been focused on for quite a while. We now have a whole team focused on this really being a force multiplier to help keep us honest across VMware, to help ensure equity and in many different ways that we have an air continue to increase. For instance, the amount of female representation within our organization or underrepresented minorities or communities ensuring that, you know, pay is equal across the company. You know, these different sorts of things, but also around sustainability. They actually have a number of folks working very closely with our teams to drive sustainability into our products. You know, vSphere is great because it reduces the amount of physical servers you need. So by definition reduces the carbon footprint there, but now, you know, I'm taking a step further. We have cloud partners that we're working with to ensure that they have net zero carbon emissions, you know, using a hundred percent renewables by 2030. And in fact, that's something that we ourselves have signed up for. As you know, today we are carbon neutral, but what we want to get to is to be net carbon zero by 2030, which is an absolutely huge lift. And that's, by the way, not just for VMware, our operations, our offices, but also for our supply chain as well. And so, you know, when you look across this, you know, as well as efforts around diversity and inclusion, this is something that is very core to what we do as a company, but it's also a personal passion of mine. The ESG office actually lives within my organization. And it does that because what I view the office of the CTO as being as really a force multiplier, as I said before, like, yes, the team is located here, but their purview is across all of engineering. And in fact, all of VMware. So I think, you know, when we look at this, it's about getting the best talent we have, very diverse talent increasing our ability to deliver innovative products, but also doing so in a way that's good for the planet that is sustainable and that is giving back to the community. But I think, you know, I'm looking at measuring success in a few different ways. First of all, as I said before, the ESG component and in diversity equity inclusion in particular, in terms of our workforce, extraordinarily important to me and something we're going to be really pushing hard on, you know, as we all know, you know, women, underrepresented minorities, not very well represented in general in Silicon valley. So something that we all need to step up on. And so we're going to be putting a lot of effort in there and that will actually help drive as I said before, all of these innovations, this fundamental shift in mindset, I mean that requires diverse perspectives. It requires pushing us out of our comfort zone, but the net result of that is, so what you're going to see is a much faster cadence of releases of innovation coming from VMware. So there's some just insanely exciting things that are happening in the labs right now that we're cooking up. But, you know, as we start making this shift, we're going to be delivering those faster and faster to our customers and our partners. >> You know, I'm interested to hear that it's a passion of yours. There was an article, I think it was last week in the wall street journal was this, it was an insert section on, on women in the workforce. And there was a stat in there, which I thought was pretty interesting. I'll run it by you see what you think it said that, you know, it's talking about COVID and post COVID and the stresses. And it's interesting to me because a lot of executives are, and you know, I'm, I'm with them is, hey, work from home. This is some beautiful thing. It's good for business too, because you know, everybody's more productive, but then you have this perpetual workday now it's like we never sleep. And then it goes bleeds in the weekends. And the stat from Qualtrics, which was published in the journal, said that, I think it said 30% of working women said that they, their mental health has declined since COVID. And that number was only 15% for working men, still notable but half. And so, you know, one has to question maybe that perpetual work week, and, you know, maybe there's a benefit from business productivity, but then there's the other side of that as well. And a lot of women have left the workforce, a lot of working previously working moms. And so there's a, there's an untapped labor pool there, and there's this huge labor shortage. And so these are important issues, but they're not easy ones to solve, are they? >> No, no, no. It's something we've been putting a lot of thought into at VMware. So we do have a flexible program that we're rolling out in terms of work. People can come into the office if they want to, of course, you know, where we have offices, where it's safe to do so where the government is allowed that our people can and people can have an actual desk there, or sometimes they can say, hey, I only want to come in once or twice a week. And then we say, okay, we'll have some floating desks that you can take. And others are saying, I want to be fully remote. So we give people a pretty broad range in terms of how they want to address that. But I do think to your point though, and this is something I've been really trying to do already is to create a more inclusive environment by doing a number of different things. And so it's being thoughtful around when you're sending emails 'cause like I do like the, my sort of schedule as I do tend to like fire off a lot of emails late at night after the kids are in bed and get a little quiet time, some thinking time, but I make it very clear that I'm not expecting an immediate response don't worry about it. I'm just, this is my work time. Doesn't have to be your work time. And so really setting those, I guess, boundaries very well explicitly and kind of the, the expectations name is a better term setting that explicitly trying to schedule meetings, not at times where you're going to have to drop the kids off at school or pick them to take over your life. And so we really try to emphasize boundaries and, and really studying those things appropriately. But honestly, it's something that we're still working on and I'm still learning and so I'd love to get feedback from folks, but those are some of the early thinkings. But I would say that we at VMware are taking it very, very seriously and really supporting our employees in terms of navigating that work-life balance. >> Well, okay. Congratulations on the new role and it's great to see you again I hope I hope next year we could be face-to-face always a pleasure to have you on the cube. >> Thanks, Dave. Appreciate it being here. >> Alright and thank you for watching the cubes continuous coverage of VMworld 2021, the virtual edition. Keep it right there for more right after this.

>>live from Las Vegas. It's the Cube covering. Inform Attica World 2018 Not you. Buy. Inform Attica. >>Welcome back and run. Live here in Las Vegas at the Venetian Cubes coverage of In From Attica, World 2018. I'm John for the coast to queue with by host the next two days. Peter Barrister, head of research for Wicked Bonds with an Angle and the Cube. Our next two guests from Deloitte. Leo Cabrera, who's senior manager. And Rajeev Krishna, who's the specialist leader on the engineering side. CDO side guys, Thanks for joining us. Thank you, John. Thank you, Lloyd. The leader in a lot of areas, absolutely doing a lot of cutting edge stuff from c'mon, the Blockchain crypto side tax side also in the I t side. You guys have been in a great top customers here in data in from Atticus, leading the charge, looking good with the trends. But the cloud is here. Cloud scale ecosystems developing. How do you guys see in from Attica? Evolving. Going forward, Mostly great messaging. But they still got customers out there that have sold stuff. They want to bring in cloud native new data. What's what's the prospects were in from Attica. >>Foreign Formica, Saudi lawyer. We have this nuanced article data advantage and basically would consider the inflection point between what we call in just 3.0, industry for point. And it's basically now we want to get value out of the data and our data advantage strategy Focus on three pillars. They have engineering wilderness and enable men for as Informatica Isa great component and a great supporter in each of these areas. Right, So, through these study we offer video service is we offer data governance. Studio chief did offer sheet state all of it. Yeah, on. And we partner with Informatica to profile the data to understand what will be the points in which we can find value over the data on off course with the new enterprise catalog to tool to do better governance for our clients. >>I want to get under the hood. I see the catalog is getting a lot of great reviews. Some people think that this is the next big wave in data management, similar to what we've seen in other ways like well, what? Relational databases and every way that comes on cap this catalogue New kind of catalogs emerging. What's your view on this? Is it away? Visit like recycled catalog, is it? >>So get a cataloguing and data. Curation has bean going on for decades, right? But it's never gained traction on, and it's never given Klein's the value because it was so manual takes tons of effort to get it right, right. So what inform Attica is done, which is absolute breakthrough? This embed a i into their enterprise data can log into which kind of accelerates the whole data. Cataloging on basically gives them gives climbs. The value in terms of cutting down on there are packed in terms of how many people, how many data students you need to put together >>So they modernize that. Basically, they exactly all the manual stuff put automation around and put some software to find around at machine learning. Is that kind of the secret to their success? >>Absolutely. And Down Delight has been partnering with Informatica for quite a while. In fact, we are one of the few companies that have a seat on the product advice report s o what we see from the marketplace we cannot feed into in from Attica to say, Hey, here's what you need to build into your products, right? So we be doing that with their MDM solution. For example, we have what we have. Articles indium, elevate. So we build machine learning into their MP and platform and offer. That's a solution similarly, and for America has built the clear platform into their E. D. C s. Oh, that's absolutely driving Valley for clients. And we have a lot of clients that are already leveraging >>a lot of risk and platforms tools, right? I see a lot of data stuff out there that's like like a feature, not a platform, that these guys got a platform, right? So But now the world's changing the cloud. How do you guys take that data advantage program or go to a CDO and saying, Look, you gotta think differently around the data, protect you explain your view on that. >>For us, data is now the center of everything, right? So any business who want to remain competitive in the future needs to get into entire end twin management of the data, getting the value of off data and also understanding what is the data coming from and what is the day they're going to write off course is studded with all the regulations. And now GDP are coming on Friday. It is a big, you know, pusher for companies to realize that over. If >>you have a big party on Friday, a big party or is this what you Katie was a big part. Nothing happened. So you're never mean GDP. Are you guys have a lot going on there? I mean, this is the center of the conversation. >>Yeah. I mean, we do have a lot of clients who need to be compliant on GDP are on informatica is one of the tools that have already pre established the policies, so you can quickly determine where is the data that GPR is gonna be monitoring and looking for compliance on So rather than doing it from a scratch, right? So it takes a lot of it >>for Let's build on this a little bit. So when we talk about different as John was saying, different generations of data management technology, we're coming out of a generation was focused on extract, transform and load where every single application or every single new analytics application wasn't you identify the source is uniquely you build extractions unique. You'd build transformations, you build load scripts. Uniquely all that stuff was done uniquely. Now what we're saying is catalog allows us to think to move into a re use world. We've been reusing code fragments and gets and all these other things for years. In many respects, what we're talking about is the ability to bring a reuse orientation inside the enterprise to data. Have I got that right? You got it >>right. Two minutes. But the most important parties how to get value out of that, right? Because they did >>manage to get value out of using >>it more exactly And understanding, You know, how can improve your operations or you know, the bottom line, or reduce the risk that you have in your data, which is basically CPR is about, >>and one other Salin point is on very scene for America bringing values their completeness of mission. Right. So when you talk about gdp are you need different aspects, right? You need your data integration. Whether it be through cloud around. Promise you need get a governor on top of what you're cataloging, right? You need security data security. Right? So it all comes together in the hole in dramatic solutions. And I think that's very see value is supposed to like pocket pockets >>of guys. I gotta ask you a question. We've seen many ways. I think it's a big way this whole date away. But you guys, you have a term called industry four point. Oh, is what is industry but the Deloitte term. But what is that? What is industry four point? Oh, me. Can you define that? >>You wanna take that door? >>Yeah, sure. So we've seen, you know, revolutions in terms off technology and data on. We've seen people going from kind of the industrial revolution to the dark. Amira, What? Three terms in the street? Four point off where data is annoying, right? So data is an acid that needs to be completely leverage. Not just you look a reactively and retrospectively like How did we do? Right? And not even just for predictive analytics. We've seen that for a few years now. It's also about using data to drive. This is value, right? So are there new ways to monetize data? Are there new ways to leverage data and grow your business? Right? So that's what Industry four. No, no is about. >>That's awesome. Well, we got a lot of things going on here. Thanks for coming on. The Cube had a couple of questions. Got a lot of dishes going on. That preparing for the big opening of the Solutions Expo Hall. We're in the middle of all the action. You're out in the open, accused. What we do. We go out in the open final question, eyes around the CDO. Who should the chief date officer report to the C I O board? What >>do you >>guys seeing? Because the CDO now picking a strategic role if Davis the new oil. That data is the fourth wave of innovation that we've seen over centuries. What does that mean? For the chief Data Officer? More power? Why'd you report to the C i o? Why is the CEO reported the Chief Data officer? What's your take? >>Traditionally our clients in the past, where the mandate for the studios were more in the data governess, right? As of today, it is going more into enablement the data, right? So more than Analytics case. Still, service is so well seen clients going from the studio moving from under the CEO in tow, the CEO and into the CMO in some cases, more about marketing. However, at the lawyer, our proposition is that companies should do a big shift and funded the new data function as a totally new vertical next to H. R next to finance right, which have his own funding and the CDO being the leader of that function, reporting directly to the CEO or >>enablement side CEO handling much of three things engineering, governance and enablement correct. So the CEO will handle Engineering Dept. Which not just its engineering, full stack developers, possibly our cloud native developers. Governance could come into policy, normal stuff. We've seen enablement more tooling, democratization of things. >>Yeah, yeah, >>yeah. I mean, what we've been seeing right in the real world, Liss, you have, for example, finance transformation that CIA full heads, right? So there's a lot of traction at that point to kind of bring the company together. But then that soon fizzles out. Sometimes you have, ah, the CMO bringing on and marketing campaign and, you know, analytics initiative, right? There's a lot of traction. Then it fizzes out. So you need somebody at the chief data officer of the C suite level to maintain that traction that moment, Um, in order freed value. >>But it seems the key issue is someone who is focused on data as an asset generating competitive returns on data as an asset because and the reason why it could be the CEO, it could be somebody else. Historically, an i t. The asset was the hardware on the argument here is that the asset is no longer the hardware now the data data. So whoever whatever you call it, someone and a group who's focused on generating returns out of data, >>Yes. But it has to have that executive level and that new talent mortal that we're proposing right where everybody knows a little bit of data in a sense. >>And the other thing is that I mean, think about this role that's dedicated to creating value of data, right? So you can understand you know how you create value in one function. Take it to the other function and tell them Hey, here's have helped finance right, get more value and then use the same thing marketing our sales. So it's also the cross pollination of ideas across different functions in an organization. S O n roll like that is helpful in terms of >>just to say, the data could very well become the next shared service's organization. That's because you don't want your salespeople to be great with data and your marketing people to be lousy with data. >>Correct. You're totally right on that. That's what we're proposing, right? So data being another vertical in entire business, >>the Lloyd bring all the action here on the Q. With all the data they're sharing here to you. It's the Cuban John for With Peter Burst, more live cover. Stay with us. We're here in Las Vegas. Live for in from Attica, World 2018 day. One of two days of wall to wall comes here out in the open. Bringing you all the data is Thank you. Stay with us.

>> Announcer: Live from the Computer History Museum, in Mountain View, California, it's theCUBE! Covering DevNet Create 2018, brought to you by Cisco. >> Hello and welcome back to theCUBE's exclusive live coverage here in Mountain View, California, the heart of Silicon Valley at the Computer History Museum for Cisco's DevNet Create. I'm here with Lauren Cooney, the analyst, for the Wikibon team and our next guest is I'm proud to have Guy Kawasaki here on theCUBE. Guy is, goes without mentioning, a legend in the industry. Currently, the chief evangelist for Canva author of Art of the Start, a real pioneer in entrepreneurship, tech entrepreneurship, tech evangelism. Guy, great to see you, thanks for joining us. >> Thank you. >> Among other things, you've done a lot of amazing things. Thanks for joining us. >> What better place to be. >> The tech culture now is so mainstream. You're seeing Facebook CEO draw in more audience than a Supreme Court justice. >> More people watched the Senate hearings yesterday-- >> He probably has more impact than a Supreme Court justice. >> He's running the world. The tech culture has really grown to be a mainstream...in the early days the computer industry when it was really the beginning of the revolution, the PC revolution, Macintosh and the PC, you were there. So much has happened. I mean, as you look back, I mean looked out at the young guns coming up, what's your view, what's your reaction to all this? You have these (mumbles) moments. >> What's your take on all this? >> I suppose many people would say, we never thought it would get to this point. It's turned destructive and negative and all that. But it's a short snapshot of time and, first of all, can we put the genie back in the bottle? No, so it doesn't really matter. But, all things considered, the democratization of computing, everybody has a computer, whether it's a phone or a computer. The democratization of the transfer of information, obviously some information may be faint, may be not what you like. But would we go back to a time where we send things by fax machines? Not at all, I mean all things considered, >> it's a great time to be alive. >> Democratization goes through these waves, democratization with the PC, democratization with the internet, democratization of web 2.0 and social media. The beginning of social media, about 15 years, maybe 10, whatever way you might want to mark it. And now democratization with data and AI is interesting. So you're having these waves of democratization. It's going to take some time to sort out. I mean, as you look at the tech trends, how do you make sense of it, or what do you get excited about? How do you surf that wave? (chuckling) If you're going to surf the wave, the big wave coming, which some say is block chain and cryptocurrency and decentralization. What's the wave that you're on, that's the question? >> To use a surfing analogy, if we're going to go down that rat hole, a good, experienced surfer knows where to sit, can look out and say, I'll take the fourth wave. And I'll sit in the right place, turn around at the right time, paddle at the right time, you know, all that. And then there's people like me. We sit in the same place, and every 15 minutes, the right wave comes along and catches us. Those are the two theories. >> I think if only predicting tech trends were as easy as predicting surfing. >> Interviewer: Timing's everything. >> Timing is everything, luck is a lot to do with it. We only learn about the Apples and the Googles and the Ciscos and the Facebooks and the Pinterests and the Instagrams. I think you think, well, there are these really smart people and they can predict the trend or cause a trend. I think it's more the game of big numbers where if you have enough surfers in the water, somebody's going to catch a wave. (chuckling) And then you can say, yeah, I knew he was the best surfer. >> But really, right place, right time. >> And you got to know what a wave looks like. >> Guy: Well, yeah. >> You got to be, like, okay, am I in a tide pool >> or am I on a boogie board. >> And to your point, you've got to be in the water. [John] Yeah, yeah. >> You can't be standing on the shore, saying I'm going to catch a wave. You have to be in the water, and if you're in the water, >> nine times out of ten you're going to get crushed. (chuckling) >> If you're not out in front of that next wave, you're driftwood. In surfing, people will jump and try to take your wave, this sounds like the tactic of the whole industry. >> Guy: Exactly, right, right. >> What waves do you see that are coming, in your mind. You've seen a lot of waves in your day. I mean, right now, what wave is exciting you right now. >> If you look at the waves, what's out there? >> What I learn about that is, you can only declare your intelligence and victory after the fact, right. I can tell you the internet of things is big. I can tell you that social media is big. I can tell you that computing is big. Problem is I could tell you that because I know it's big now. Can I tell you what's in the future, no. If I could...first of all I wouldn't tell you. (chuckling) So I think in a rare moment of humility it's the law of big numbers. Infinite monkeys typing at keyboards, somebody's going to come up with Beethoven. >> I want to ask you a question because I get asked this question a lot, Hey, John, you've been around a while. I want to catch that next big wave, I want to be in the next Google, I want to be rich on stock options. (Guy chuckling) I said, a lot of times the best companies where you take the most advantage of is when no one else wants to work there or no one yet knows it. We really can't say, Oh, I'm going to get rich on that company because by that time it's either too late and people are chasing the wrong thing. >> Guy: Absolutely. >> How do you give that same advice to someone? >> Listen, you're talking to a guy who quit Apple twice and turned down Steve once. So how smart could I be? (John chuckling) Now we can say Apple is the most valuable company in the world, you should have stayed there. Well, thank you very much, thanks for tell me now. I think it's really... I don't want to be too dramatic, but I could almost build a case that you should invest in or work for the most dumb-ass idea you heard of. Because at any given point-- >> Airbnb, we're going to rent out mattresses >> and give out cereal. >> Very good example, Airbnb. Let's face it, if somebody told you Airbnb, before there was Airbnb, you would say, So you're telling me that I'm going to rent a room from somebody I met on the internet, and I'm going to sleep in that person's house, hoping he's not a murderer or pedophile. On the flip side, you're saying, I'm going to rent out my room to someone who I hope is not a pedophile or an ax murderer. Or ebay...I'm going to buy this printer from 3000 miles away and I'm going to assume it works. Or I'm going to sell my good printer to someone 3000 miles away and assume that he's not going to say he never got it or that it didn't work and he wants a refund. So if you go down the line of all these ideas, you'd have to say at the time, nobody. Even take an extreme: Zappos. If you told me that women would buy shoes without trying them on, seeing them, smelling them, and touching them, I would tell you you're crazy. You'd buy a book that way. You'd buy a CD that way, you'd buy a DVD. Would you buy shoes, would you buy shoes without trying them on. >> I totally would. (laughing) Now I can say that. >> To Zappos's credit, some of the way it made that work is it offered shipping back for free. So there was really no risk. But I would have been a skeptic about Zappos. >> Well, it was one of those things for me, Zappos, where they shipped in one day so I could get them immediately, try them on and if they didn't work, I could ship them back and get a different size. It was no big deal, it was very low overhead. So that's one of the reasons that that worked. But I think when you mention all of these great things like Ebay and Airbnb, it's really part of the sharing economy with people really wanting to share the goodness of their goods with other people that need them. >> It's just really connecting those folks. >> Places like Oakland and San Francisco, where there are certain streets where you line up and you just get in the next car with a stranger, and you go to San Francisco with them. >> Lauren: Yeah. >> And it's not computerized or anything. It's just trust. >> I did that once and it was frightening. (laughs) You never know who the driver is going to be or how they're going to drive. >> But you did it. >> I did it. >> People do it every day. >> I know. >> I'm amazed. >> I did it once, but... (laughing) >> Let's ask you a question. What's the craziest idea that you've seen that worked and the craziest idea that didn't work. >> Let's start with the easy one. I had a company called garage.com, and we were a venture capitalist investment bank, so we got pitched all the time. One day, a guy comes in and says, I'm going to build... A dirigible hotel over San Francisco. So you stay in the dirigible. Another person said, We're going to build a geodesic dome over Los Angeles. And I can't remember if it was to keep the air pollution in or out. I'll just tell you one really great one. These people were from Seagate so they had Cray, they worked for Seagate. And they say, We have this patent-pending, curb-jumping, patent-pending whatever technology so that if you drop your laptop with your hard disk, the head won't crash into the hard disk and ruin the hard disk. And at the time, this was 15 years ago, that was a great idea, right. It wasn't solid state. Heads crashing into hard disks. >> Moving parts. >> Seagate, so this is a great idea. Every hard disk in every laptop should be like it. So we get in the car, we go to their office, and the receptionist says, Oh, they're running late because they're on the phone with IBM. IBM is really interested in using this technology for the IBM PC laptop. Keep us waiting, keep us waiting. And they get out, and, Yeah, IBM was really, they're so excited, they're ready to move. And I, like, we're really excited. And finally I said, Give me the jist, what is your technology, is it like some special chip that detects gravitational fall, it's too fast, it's got to be hitting the ground so it parks the head because it recognizes motion or whatever. And I swear to God, I swear to God, he brings out this piece of foam and he says this is military spec foam. So we take your hard disk, we put this foam thing around it, and we put it in the laptop. And I swear to God, I was having an out of body experience. >> You're telling me-- >> I drove all the way here-- >> That your proprietary technology is putting foam around the hard disk, and IBM is excited by this foam. So welcome to my life. >> So what are you up to now. Talk about your evangelism. I know you're a (mumbles) Mercedes. You have a bunch of things going on. You've been very prolific in social media. You were on the suggested user list from day one on Twitter. >> No, I wasn't. >> Oh, no, you weren't, that's right. But you have a zillion followers. >> That's why I have never forgiven Twitter for that. >> I thought they put you on. >> Guy: No. >> Okay, I stand corrected. >> You had to be an actress. >> Some tech people got on there, I know. >> Guy: Yeah. >> But I was not on. >> There you go. >> Measly 20,000 or so. But you got a million and a half followers active. You've really been prolific in a good way. (laughing) Engaging with communities. >> Yeah. >> What have you learned and how do you view this next generation of social because you're seeing the Facebooks, you're seeing LinkedIn. There's siloed platforms. Is there hope? What's your take on it, is it going to grow? >> I've come to the point where I always believe things are never as good or as bad as they seem. So I don't think it's as bad as people say. If these social media sites are selling my data, they're going to go broke selling my data. (laughs) I don't know how you could look at my data. First of all, I never look at ads, so go ahead, sell my data. I'm not going to look at the ad anyway. It doesn't matter. I think the ability to spread ideas, arguably good or bad, the ability to spread ideas with social media, all things considered, is better. It's going to be abused and all that. My father was a state senator in Honolulu, and we were into banner ads way before anybody else. Banner was literally a piece of cloth with his name on it that you staple to the side of a building, saying Vote for Duke Kawasaki. That was the nature of banner advertisement back then. Do I think that social media targeting and all that for sales is a good thing? Yes, I do. If you're a real estate broker, and you wanted to reach people who live in Silicon Valley, age 50 to 70, female or male or whatever, in such-and-such an income bracket, how else can you do it but Facebook? >> It's good and bad. >> That's why Facebook is so successful. >> The metadata is all about the clan and the culture, and I think putting ideas out there is a way to send your ideas into the ether, make it happen. So, that's key. Now, we're here at a developer conference, so one of the things that's also a big part of this community is the notion of how open source has become a tier one citizen, and it's really running the world. Which is also grounded in community as well. You have this ethos of community, ethos of software open. >> I believe in open source. I believe that the more intelligent people pounding on your stuff, the better it is. I'm an author, and what I do is, speaking in the sense of open source. So right now I'm about 80% done with my book. I put out a post on social media saying anybody that wants to review my book, test my book, send me your information. So I do this, I cut it off at about 280 people. I send them the Word document, the entire Word document of my book. Does that mean they can take it and publish it in China tomorrow, yes. But, from that, I get hundreds and hundreds of comments. >> John: Wisdom of the crowds, self-editing. >> Yeah, and they point out stuff that I never would have noticed because I'm too close to at this point. So is there a downside, yes. Is there piracy, yes. Arguably, would those pirates have bought the book anyway? No. >> Our content's all free. We're really big in China because they actually take it and translate it in the native language. >> Guy: Which you would never have done. >> With all the jargon, you can't hire a-- >> Guy: You would never have done that. >> Yeah, exactly. >> Guy, great to catch up with you. Thanks for coming on. What are you working on now, you mentioned the book, what's the book about? >> The book is called Wise Guy, and it's a compilation of the stories that have influenced my life. So it's not an auto-biography. It is not a memoir. Have you ever heard of the book Chicken Soup for the Soul? >> John: Yeah, yeah. >> You know, it's inspirational stories. This is miso soup for the soul. (laughing) So I'm working on that, TV evangelism with Canva is just going gangbusters. Brand ambassadors for Mercedes Benz. I'm on the board of directors of a company called Cheeze with a zee. It's an anti-social photo-sharing and vidoo-sharing app. And that's it. >> You've been an inspiration to many, great job of the year has been a big fan of your work. Thanks for coming on theCUBE. Really appreciate it. >> Thank you. >> Guy Kawasaki here inside theCUBE. We're at Devnet Create. This is Cisco's cloud developer conference. Different from their core Devnet Cisco Networking developer, and this is all about dev ops open source. And this is theCUBE bringing you all the action here in Mountain View, California. We'll be right back with more after this short break.

>> Announcer: Live, from the Moscone Center it's theCUBE. Covering AWS Summit San Francisco, 2018. Brought to you by, Amazon Web Services. >> Welcome back I'm Stu Miniman and this theCUBE's live coverage from AWS Summit San Francisco. Happy to have two industry analysts here. Also, they are founding partners of Kaleido Insights Jeremiah Owyang and Jessica Groopman. Join me and help me extract the signal from the noise that is our industry today. Thanks so much for joining us. >> Great to be here. >> Jessica it's actually the first time I've met you. Why don't you give our audience a little bit about your background and what led to the finding of Kaleido Insights. >> Of course, so I have been covering Internet of things, IOT for many years, and also in the last couple of years have gone very deep in both AI and blockchain. So, have this sort of umbrella category, which we call automation at Kaleido, that I cover and basically we formed the firm because what we saw was companies pursuing single technologies. What's your AI strategy, what's your IOG strategy what's your AR strategy? When in reality, all of these things are impacting each other. so we take a kaleidoscopic sort of converged lens. >> I love that, so Jeremiah, I can't believe it's your first time on our program, John Furrier's taking photos. You're one of the first people I followed on Twitter when I got on, I've known you for many years, so thanks. You've watched so many of these waves. Give us your take as to how you fit into the Kaleidoscope of what's happening. >> Yeah thanks a lot, so I've been in Silicon Valley for over 20 years, and I've seen threewaves.com, social media, collaborative, and now autonomous is the fourth wave that we're seeing right now. And, it's just amazing to see. I see the frequency of technologies is happening at a faster pace, and the impacts they're having to business models and what companies have to do to keep up, so it is a really exciting time. A few years ago, Uber and Airbnb were really hot and I was focused in on that topic. And now, it seems like that is a lifetime ago. We're focused on autonomous technologies; blockchain, IOT. And the things that Amazon announced today on stage like machine learning and drones and self-driving cars. It's a dizzying pace on what's going on it's like it explodes. >> Just in the last couple of weeks, look what happened to Facebook and Amazon with some of the internal and external pressures on those companies. I like what you say, we get excited by the new shiny. It was like, oh everything that was big data is now kind of AI well, IOT and ML. At WikiBound, on our research side, we say it's data at the center of it, data data data. And we've been talking about this for years. Jeremiah and I worked in the boring old storage industry. Which was never about storing the information, it was, how do I allow it to be shared and leverage it. So it's like it's maturation, you know, what's your take what's at the center over here, what are some of the biggest challenges, what's real what's not, and you know, doing it in under a minute. >> It continues to be the central focus, I mean it's been very interesting watching in the IOT space for the past couple of years where we've been fixated on things, right, the objects. But in reality it's about extracting data either between or about or in aggregate or about individuals sensor data, around those things. So the same is true, now we're seeing this shift into cognitive IOT, where devices themselves can analyze and process at the edge, or send learnings across a whole fleet of vehicles or a whole ray of devices about a given environment. Same story, different technologies continuing the cycle. >> Jeremiah, you know, that pace of change you talked about is so challenging, how do you go from I've got an idea to I'm going to start rolling it out by the time I use it, aren't I out of date? What do you see, how do you help customers look at this holistically and not constantly be tripping over themselves? >> And for the bigger the company the harder it is for them to keep up. The technology paces are coming faster, so one trend that we're seeing is corporations are launching innovation programs. It's an actual team, they have a dotted line to the CEO or the Chief Product Officer, and they're responsible for testing all of these new technologies. Maybe in a secluded area or tying it back to a business unit but their job is to experiment like a startup in the big company. So that's what we're seeing right now, these innovation programs that are merging. >> Why don't you tell us, we're here at the Amazon show. How are they doing, what's good? Where are some of the competitors leading them, you know? What are customers asking for? >> It's fascinating to see how Amazon is effectively taking different strategies at every single part of the stack. I believe this morning Verner said, offering egalitarian access to data storage, to data compute to machine learning algorithms. Effectively, it makes the company's only job to have a great idea and then sort of bringing in Amazon to do the rest. What I also see is that it's shifting the Venn diagrams or the complex diagrams of who's competitive and where. Competitive landscapes are shifting all the time at each of these new announcements. >> It's like the only thing you need from IT is bandwidth, the pipe. And Amazon is promising to do just about all the rest of that. >> Yeah, but the challenges. Remember when cloud computing was supposed to be simple and now it's like, oh okay. I'm going to build a database on Amazon. Well which one of the 15 do you want? All the languages, all the choices. >> 125 products, they listed on stage. >> Yeah, there are over 1,000 releases every year. They have two to three new products almost every day. When they do this Summit and they did a bunch of announcements most of those weren't planned for this it just happened to be what's coming out of the CIDC pipeline, if you will from them. >> Imagine being a salesperson for Amazon just to sell the products. >> Or imagine being a customer trying to figure out just what to use in the architecture. >> Unfortunately we don't have a lot more time to talk. Give us some of the things your firm is looking at what we look to see in this year from you. >> Yeah, so broadly speaking, we're really focused on these different technology convergences. Just published new research on where IOT and blockchain are coming together, that's a space we're following very closely. The next report working on right now is around AI readiness. There's much ado about data pipelines and data preparedness as there should be, but there's a whole realm of people process, governance, leadership preparedness. So we're really focused on how companies can prepare for this new technology. >> I'm also looking at how the new business models from automation will impact different enterprise business units. And our other partners are looking at content and automation in the marketing side, and we just had a report released from Jaime Szymanski on how virtual reality and mixed reality is going to impact enterprise. And there's six used cases for the business and Rebecca is working on the marketing report. >> Jeremiah and Jess, hope we can get back with you soon to discuss all this, you hit a whole bunch of things. You mentioned blockchain, so we'll get 10X of the views of what we would have had otherwise. We'll be back with lots more coverage. Thanks to Kaleido Insights for joining us on this segment. We'll be back with lots more. I'm Stu Miniman, you're watching theCUBE. >> Man: Thank you. (digital music)

>> Announcer: Live from New York City, it's The Cube, covering IBM data science for all. Brought to you by IBM. >> Welcome back to data science for all. This is IBM's event here on the west side of Manhattan, here on The Cube. We're live, we'll be here all day, along with Dave Vallente, I'm John Walls Poor Dave had to put up with all that howling music at this hotel last night, kept him up 'til, all hours. >> Lots of fun here in the city. >> Yeah, yeah. >> All the crazies out last night. >> Yeah, but the headphones, they worked for ya. Glad to hear that. >> People are already dressed for Halloween, you know what I mean? >> John: Yes. >> In New York, you know what I mean? >> John: All year. >> All the time. >> John: All year. >> 365. >> Yeah. We have with us now the head of data science, and the VP at Galvanize, Nir Kaldero, and Nir, good to see you, sir. Thanks for being with us. We appreciate the time. >> Well of course, my pleasure. >> Tell us about Galvanize. I know you're heavily involved in education in terms of the tech community, but you've got corporate clients, you've got academic clients. You cover the waterfront, and I know data science is your baby. >> Nir: Right. >> But tell us a little bit about Galvanize and your mission there. >> Sure, so Galvanize is the learning community for technology. We provide the training in data science, data engineering, and also modern software engineering. We recently built a very large, fast growing enterprise corporate training department, where we basically help companies become digital, become nimble, and also very data driven, so they can actually go through this digital transformation, and survive in this fourth industrial revolution. We do it across all layers of the business, from the executives, to managers, to data scientists, and data analysts, and kind of transform and upscale all current skills to be modern, to be digital, so companies can actually go through this transformation. >> Hit on one of those items you talked about, data driven. >> Nir: Right. >> It seems like a no-brainer, right? That the more information you give me, the more analysis I can apply to it, the more I can put it in my business practice, the more money I make, the more my customers are happy. It's a lay up, right? >> Nir: It is. >> What is a data driven organization, then? Do you have to convince people that this is where they need to be today? >> Sometimes I need to convince them, but (laughs) anyway, so let's back up a little bit. We are in the midst of the fourth industrial revolution, and in order to survive in this fourth industrial revolution, companies need to become nimble, as I said, become agile, but most importantly become data driven, so the organization can actually best respond to all the predictions that are coming from this very sophisticated machine intelligence models. If the organization immediately can best respond to all of that, companies will be able to enhance the user experience, get insight about their customers, enhance performances, and et cetera, and we know that the winners in this revolution, in this era, will be companies who are very digital, that master the skills of becoming a data driven organization, and you know, we can talk more about the transformation, and what it consisted of. Do you want me to? >> John: Sure. >> Can I just ask you a question? This fourth wave, this is what, the cognitive machine wave? Or how would you describe it? >> Some people call it artificial intelligence. I think artificial intelligence is like big data, kind of like a buzz word. I think more appropriately, we should call it machine intelligence industrial revolution. >> Okay. I've got a lot of questions, but carry on. >> So hitting on that, so you see that as being a major era. >> Nir: It's a game changer. >> If you will, not just a chapter, but a major game changer. >> Nir: Yup. >> Why so? >> So, okay, I'll jump in again. Machines have always replaced man, people. >> John: The automation, right. >> Nir: To some extent. >> But certain machines have replaced certain human tasks, let's say that. >> Nir: Correct. >> But for the first time in history, this fourth era, machine's are replacing humans with cognitive tasks, and that scares a lot of people, because you look at the United States, the median income of the U.S. worker has dropped since 1999, from $55,000 to $52,000, and a lot of people believe it's sort of the hollowing out of that factor that we just mentioned. Education many believe is the answer. You know, Galvanize is an organization that plays a critical role in helping deal with that problem, does it not? >> So, as Mark Zuckerberg says, there is a lot of hate love relationship with A.I. People love it on one side, because they're excited about all the opportunities that can come from this utilization of machine intelligence, but many people actually are afraid from it. I read a survey a few weeks ago that says that 36% of the population thinks that A.I. will destroy humanity, and will conquer the world. That's a fact that's what people think. If I think it's going to happen? I don't think so. I highly believe that education is one of the pillars that can address this fear for machine intelligence, and you spoke a lot about jobs I talk about it forever, but just my belief is that machines can actually replace some of our responsibilities, right? Not necessarily take and replace the entire job. Let's talk about lawyers, right? Lawyers currently spend between 40% to 60% of the time writing contracts, or looking at previous cases. The machine can write a contract in two minutes, or look up millions of data points of previous cases in zero time. Why a lawyer today needs to spend 40% to 60% of the time on that? >> Billable hours, that's why. >> It is, so I don't think the machine will replace the job of the lawyer. I think in the future, the machine replaces some of the responsibilities, like auditing, or writing contracts, or looking at previous cases. >> Menial labor, if you will. >> Yes, but you know, for example, the machine is not that great right now with negotiations skills. So maybe in the future, the job of the lawyer will be mostly around negotiation skills, rather than writing contracts, et cetera, but yeah, you're absolutely right. There is a big fear in the market right now among executives, among people in the public. I think we should educate people about what is the true implications of machine intelligence in this fourth industrial revolution and era, and education is definitely one of those. >> Well, one of my favorite stories, when people bring up this topic, is when Gary Kasparov lost to the IBM super computer, Blue Jean, or whatever it's called. >> Nir: Yup. >> Instead of giving up, what he said is he started a competition, where he proved that humans and machines could beat the IBM super computer. So to this day has a competition where the best chess player in the world is a combination between humans and machines, and so it's that creativity. >> Nir: Imagination. >> Imagination, right, combinatorial effects of different technologies that education, hopefully, can help keep those either way. >> Look, I'm a big fan of neuroscience. I wish I did my PhD in neuroscience, but we are very, very far away from understanding how our brain works. Now to try to imitate the brain when we don't know how the brain works? We are very far away from being in a place where a machine can actually replicate, and really best respond like a human. We don't know how our brain works yet. So we need to do a lot of research on that before we actually really write a very strong, powerful machine intelligence model that can actually replace us as humans, and outbid us. We can speak about Jeopardy, and what's on, and we can speak about AlphaGo, it's a Google company that kind of outperformed the world champion. These are very specific tasks, right? Again, like the lawyer, the machines can write beautiful contracts with NLP, machines can look at millions and trillions of data and figure out what's the conclusion there, right? Or summarize text very fast, but not necessarily good in negotiation yet. >> So when you think about a digital business, to us a digital business is a business that uses data to differentiate, and serve customers, and maintain customers. So when you talk about data driven, it strikes me that when everybody's saying digital business, digital transformation, it's about a data transformation, how well they utilize data, and if you look at the bell curve of organizations, most are not. Everybody wants to be data driven, many say they are data driven. >> Right. >> Dave: Would you agree most are not? >> I will agree that most companies say that they are data driven, but actually they're not. I work with a lot of Fortune 500 companies on a daily basis. I meet their executives and functional leaders, and actually see their data, and business problems that they have. Most of them do tend to say that they are data driven, but truly just ask them if they put data and decisions in the same place, every time they have to make a decision, they don't do it. It's a habit that they don't yet have. Companies need to start investing in building what we say healthy data culture in order to enable and become data driven. Part of it is democratization of data, right? Currently what I see if lots of organizations actually open the data just for the analyst, or the marketers, people who kind of make decisions, that need to make decisions with data, but not throughout the entire organization. I know I always say that everyone in the organization makes decisions on a daily basis, from the barista, to the CEO, right? And the entirety of becoming data driven is that data can actually help us make better decisions on a daily basis, so how about democratizing the data to everyone? So everyone, from the barista, to the CEO, can actually make better decisions on a daily basis, and companies don't excel yet in doing it. Not every company is as digital as Amazon. Amazon, I think, is actually one of the most digital companies in the world, if you look at the digital index. Not everyone is Google or Facebook. Most companies want to be there, most companies understand that they will not be able to survive in this era if they will not become data driven, so it's a big problem. We try at Galvanize to address this problem from executive type of education, where we actually meet with the C-level executives in companies, and actually guide them through how to write their data strategy, how to think about prioritizing data investment, to actual implementation of that, and so far we are highly successful. We were able to make a big transformation in very large, important organizations. So I'm actually very proud of it. >> How long are these eras? Is it a century, or more? >> This fourth industrial? >> Yeah. >> Well it's hard to predict that, and I'm not a machine, or what's on it. (laughs) >> But certainly more than 50 years, would you say? Or maybe not, I don't know. >> I actually don't think so. I think it's going to be fast, and we're going to move to the next one pretty soon that will be even more, with more intelligence, with more data. >> So the reason I ask, is there was an article I saw and linked, and I haven't had time to read it, but it talked about the Four Horsemen, Amazon, Google, Facebook, and Apple, and it said they will all be out of business in 50 years. Now, I don't know, I think Apple probably has 50 years of cash flow in the bank, but then they said, the one, the author said, if I had to predict one that would survive, it would be Amazon, to your point, because they are so data driven. The premise, again I didn't read the whole thing, was that some new data driven, digital upstart will disrupt them. >> Yeah, and you know, companies like Amazon, and Alibaba lately, that try kind of like in a competition with Amazon about who is becoming more data driven, utilizing more machine intelligence, are the ones that invested in these capabilities many, many years ago. It's no that they started investing in it last year, or five years ago. We speak about 15 and 20 years ago. So companies who were really a pioneer, and invested very early on, will predict actually to survive in the future, and you know, very much align. >> Yeah, I'm going to touch on something. It might be a bridge too far, I don't know, but you talk about, Dave brought it up, about replacing human capital, right? Because of artificial intelligence. >> Nir: Yup. >> Is there a reluctance, perhaps, on behalf of executives to embrace that, because they are concerned about their own price? >> Nir: You should be in the room with me. (laughing) >> You provide data, but you also provide that capability to analyze, and make the best informed decision, and therefore, eliminate the human element of a C-suite executive that maybe they're not as necessary today, or tomorrow, as they were two years ago. >> So it is absolutely true, and there is a lot of fear in the room, especially when I show them robots, they freak out typically, (John and Dave laugh) but the fact is well known. Leaders who will not embrace these skills, and understanding, and will help the organization to become agile, nimble, and data driven, will not survive. They will be replaced. So on the one hand, they're afraid from it. On the other side, they see that if they will not actually do something, and take an action today, they might be replaced in the future. >> Where should organizations start? Hey, I want to be data driven. Where do I start? >> That's a good question. So data science, machine learning, is a top down initiative. It requires a lot of funding. It requires a change in culture and habits. So it has to start from the top. The journey has to start from executive, from educating and executive about what is data science, what is machine learning, how to prioritize investments in this field, how to build data driven culture, right? When we spoke about data driven, we mainly speaks about the culture aspect here, not specifically about the technical side of it. So it has to come from the top, leaders have to incorporate it in the organization, the have to give authority and power for people, they have to put the funding at first, and then, this is how it's beautiful, that you actually see it trickles down to the organization when they have a very powerful CEO that makes a decision, and moves the organization quickly to become data driven, make executives look at data every time they make a decision, get them into the habit. When people look up to executives, they try to do the same, and if my boss is an example for me, someone who is looking at data every time he is making a decision, ask the right questions, know how to prioritize, set the right goals for me, this helps me, and helps the organization better perform. >> Follow the leader, right? >> Yup. >> Follow the leader. >> Yup, follow the leader. >> Thanks for being with us. >> Nir: Of course, it's my pleasure. >> Pinned this interesting love hate thing that we have going on. >> We should address that. >> Right, right. That's the next segment, how about that? >> Nir Kaldero from Galvanize joining us here live on The Cube. Back with more from New York in just a bit.