Upbeat music plays >> Voice Over: TheCUBE presents Ignite 22, brought to you by Palo Alto Networks. >> Good morning everyone. Welcome to theCUBE. Lisa Martin here with Dave Vellante. We are live at Palo Alto Networks Ignite. This is the 10th annual Ignite. There's about 3,000 people here, excited to really see where this powerhouse organization is taking security. Dave, it's great to be here. Our first time covering Ignite. People are ready to be back. They.. and security is top. It's a board level conversation. >> It is the other Ignite, I like to call it cuz of course there's another big company has a conference name Ignite, so I'm really excited to be here. Palo Alto Networks, a company we've covered for a number of years, as we just wrote in our recent breaking analysis, we've called them the gold standard but it's not just our opinion, we've backed it up with data. The company's on track. We think to do close to 7 billion in revenue by 2023. That's double it's 2020 revenue. You can measure it with execution, market cap M and A prowess. I'm super excited to have the CEO here. >> We have the CEO here, Nikesh Arora joins us from Palo Alto Networks. Nikesh, great to have you on theCube. Thank you for joining us. >> Well thank you very much for having me Lisa and Dave >> Lisa: It was great to see your keynote this morning. You said that, you know fundamentally security is a data problem. Well these days every company has to be a data company. Grocery stores, gas stations, car dealers. How is Palo Alto networks making customers, these data companies, more secure? >> Well Lisa, you know, (coughs) I've only done cybersecurity for about four, four and a half years so when I came to the industry I was amazed to see how security is so reactive as opposed to proactive. We should be able to stop bad threats, right? as they're happening. But I think a lot of threats get through because we don't have the right infrastructure and the right tooling and right products in there. So I think we've been working hard for the last four and a half years to turn it around so we can have consistent data flow across an enterprise and then mine that data for threats and anomalous behavior and try and protect our customers. >> You know the problem, I wrote this, this weekend, the problem in cybersecurity is well understood, you put up that Optiv graph and it's like 8,000 companies >> Yes >> and I think you mentioned your keynote on average, you know 30 to 40 tools, maybe 50, at least 20, >> Yes. >> from the folks that I talked to. So, okay, great, but actually solving that problem is not trivial. To be a consolidator, I mean, everybody wants to consolidate tools. So in your three to four years and security as you well know, it's, you can't fake security. It's a really, really challenging topic. So when you joined Palo Alto Networks and you heard that strategy, I know you guys have been thinking about this for some time, what did you see as the challenges to actually executing on that and how is it that you've been able to sort of get through that knot hole. >> So Dave, you know, it's interesting if you look at the history of cybersecurity, I call them the flavor of the decade, a flare, you know a new threat vector gets created, very large market gets created, a solution comes through, people flock, you get four or five companies will chase that opportunity, and then they become leaders in that space whether it's firewalls or endpoints or identity. And then people stick to their swim lane. The problem is that's a very product centric approach to security. It's not a customer-centric approach. The customer wants a more secure enterprise. They don't want to solve 20 different solutions.. problems with 20 different point solutions. But that's kind of how the industry's grown up, and it's been impossible for a large security company in one category, to actually have a substantive presence in the next category. Now what we've been able to do in the last four and a half years is, you know, from our firewall base we had resources, we had intellectual capability from a security perspective and we had cash. So we used that to pay off our technical debt. We acquired a bunch of companies, we created capability. In the last three years, four years we've created three incremental businesses which are all on track to hit a billion dollars the next 12 to 18 months. >> Yeah, so it's interesting on Twitter last night we had a little conversation about acquirers and who was a good, who was not so good. It was, there was Oracle, they came up actually very high, they'd done pretty, pretty good Job, VMware was on the list, IBM, Cisco, ServiceNow. And if you look at IBM and Cisco's strategy, they tend to be very services heavy, >> Mm >> right? How is it that you have been able to, you mentioned get rid of your technical debt, you invested in that. I wonder if you could, was it the, the Cloud, even though a lot of the Cloud was your own Cloud, was that a difference in terms of your ability to integrate? Because so many companies have tried it in the past. Oracle I think has done a good job, but it took 'em 10 to 12 years, you know, to, to get there. What was the sort of secret sauce? Is it culture, is it just great engineering? >> Dave it's a.. thank you for that. I think, look, it's, it's a mix of everything. First and foremost, you know, there are certain categories we didn't play in so there was nothing to integrate. We built a capability in a category in automation. We didn't have a product, we acquired a company. It's a net new capability in instant response. We didn't have a capability. It was net new capability. So there was, there was, other than integrating culturally and into the organization into our core to market processes there was no technical integration needed. Most of our technical integration was needed in our Cloud platform, which we bought five or six companies, we integrated then we just bought one recently called cyber security as well, which is going to get integrated in the Cloud platform. >> Dave: Yeah. >> And the thing is like, the Cloud platform is net new in the industry. We.. nobody's created a Cloud security platform yet, so we're working hard to create it because we don't want to replicate the mistakes of the past, that were made in enterprise security, in Cloud security. So it's a combination of cultural integration it's a combination of technical integration. The two things we do differently I think, than most people in the industry is look, we have no pride of, you know of innovations. Like, if somebody else has done it, we respect it and we'll acquire it, but we always want to acquire number one or number two in their category. I don't want number three or four. There's three or four for a reason and there still leaves one or two out there to compete with. So we've always acquired one or two, one. And the second thing, which is as important is most of these companies are in the early stage of development. So it's very important for the founding team to be around. So we spend a lot of time making sure they stick around. We actually make our people work for them. My principle is, listen, if they beat us in the open market with all our resources and our people, then they deserve to run this as opposed to us. So most of our new product categories are run by founders of companies required. >> So a little bit of Jack Welch, a little bit of Franks Lubens is a, you know always deference to the founders. But go ahead Lisa. >> Speaking of cultural transformation, you were mentioning your keynote this morning, there's been a significant workforce transformation at Palo Alto Networks. >> Yeah >> Talk a little bit about that, cause that's a big challenge, for many organizations to achieve. Sounds like you've done it pretty well. >> Well you know, my old boss, Eric Schmidt, used to say, 'revenue solves all known problems'. Which kind of, you know, it is a part joking, part true, but you know as Dave mentioned, we've doubled or two and a half time the revenues in the last four and a half years. That allows you to grow, that allows you to increase headcount. So we've gone from four and a half thousand people to 14,000 people. Good news is that's 9,500 people are net new to the company. So you can hire a whole new set of people who have new skills, new capabilities and there's some attrition four and a half thousand, some part of that turns over in four and a half years, so we effectively have 80% net new people, and the people we have, who are there from before, are amazing because they've built a phenomenal firewall business. So it's kind of been right sized across the board. It's very hard to do this if you're not growing. So you got to focus on growing. >> Dave: It's like winning in sports. So speaking of firewalls, I got to ask you does self-driving cars need brakes? So if I got a shout out to my friend Zeus Cararvela so like that's his line about why you need firewalls, right? >> Nikesh: Yes. >> I mean you mentioned it in your keynote today. You said it's the number one question that you get. >> and I don't get it why P industry observers don't go back and say that's, this is ridiculous. The network traffic is doubling or tripling. (clears throat) In fact, I gave an interesting example. We shut down our data centers, as I said, we are all on Google Cloud and Amazon Cloud and then, you know our internal team comes in, we'd want a bigger firewall. I'm like, why do you want a bigger firewall? We shut down our data centers as well. The traffic coming in and out of our campus is doubled. We need a bigger firewall. So you still need a firewall even if you're in the Cloud. >> So I'm going to come back to >> Nikesh: (coughs) >> the M and A strategy. My question is, can you be both best of breed and develop a comprehensive suite number.. part one and part one A of that is do you even have to, because generally sweets win out over best of breed. But what, how do you, how do you respond? >> Well, you know, this is this age old debate and people get trapped in that, I think in my mind, and let me try and expand the analogy which I tried to do up in my keynote. You know, let's assume that Oracle, Microsoft, Dynamics and Salesforce did not exist, okay? And you were running a large company of 50,000 people and your job was to manage the customer process which easier to understand than security. And I said, okay, guess what? I have a quoting system and a lead system but the lead system doesn't talk to my coding system. So I get leads, but I don't know who those customers. And I write codes for a whole new set of customers and I have a customer database. Then when they come as purchase orders, I have a new database with all the customers who've bought something from me, and then when I go get them licensing I have a new database and when I go have customer support, I have a fifth database and there are customers in all five databases. You'll say Nikesh you're crazy, you should have one customer database, otherwise you're never going to be able to make this work. But security is the same problem. >> Dave: Mm I should.. I need consistency in data from suit to nuts. If it's in Cloud, if you're writing code, I need to understand the security flaws before they go into deployment, before they go into production. We for somehow ridiculously have bought security like IT. Now the difference between IT and security is, IT is required to talk to each other, so a Dell server and HP server work very similarly but a Palo Alto firewall and a Checkpoint firewall Fortnight firewall work formally differently. And then how that transitions into endpoints is a whole different ball game. So you need consistency in data, as Lisa was saying earlier, it's a data problem. You need consistency as you traverse to the enterprise. And that's why that's the number one need. Now, when you say best of breed, (coughs) best of breed, if it's fine, if it's a specific problem that you're trying to solve. But if you're trying to make sure that's the data flow that happens, you need both best of breed, you know, technology that stops things and need integration on data. So what we are trying to do is we're trying to give people best to breed solutions in the categories they want because otherwise they won't buy us. But we're also trying to make sure we stitch the data. >> But that definition of best of breed is a little bit of nuance than different in security is what I'm hearing because that consistency >> Nikesh: (coughs) Yes, >> across products. What about across Cloud? You mentioned Google and Amazon. >> Yeah so that's great question. >> Dave: Are you building the security super Cloud, I call it, above the Cloud? >> It's, it's not, it's, less so a super Cloud, It's more like Switzerland and I used to work at Google for 10 years, not a secret. And we used to sell advertising and we decided to go into pub into display ads or publishing, right. Now we had no publishing platform so we had to be good at everybody else's publishing platform >> Dave: Mm >> but we never were able to search ads for everybody else because we only focus on our own platform. So part of it is when the Cloud guys they're busy solving security for their Cloud. Google is not doing anything about Amazon Cloud or Microsoft Cloud, Microsoft's Azure, right? AWS is not doing anything about Google Cloud or Azure. So what we do is we don't have a Cloud. Our job in providing Cloud securities, be Switzerland make sure it works consistently across every Cloud. Now if you try to replicate what we offer Prisma Cloud, by using AWS, Azure and GCP, you'd have to first of all, have three panes of glass for all three of them. But even within them they have four panes of glass for the capabilities we offer. So you could end up with 12 different interfaces to manage a development process, we give you one. Now you tell me which is better. >> Dave: Sounds like a super Cloud to me Lisa (laughing) >> He's big on super Cloud >> Uber Cloud, there you >> Hey I like that, Uber Cloud. Well, so I want to understand Nikesh, what's realistic. You mentioned in your keynote Dave, brought it up that the average organization has 30 to 50 tools, security tools. >> Nikesh: Yes, yes >> On their network. What is realistic for from a consolidation perspective where Palo Alto can come in and say, let me make this consistent and simple for you. >> Well, I'll give you your own example, right? (clears throat) We're probably sub 10 substantively, right? There may be small things here and there we do. But on a substantive protecting the enterprise perspective you be should be down to eight or 10 vendors, and that is not perfect but it's a lot better than 50, >> Lisa: Right? >> because don't forget 50 tools means you have to have capability to understand what those 50 tools are doing. You have to have the capability to upgrade them on a constant basis, learn about their new capabilities. And I just can't imagine why customers have two sets of firewalls right. Now you got to learn both the files on how to deploy both them. That's silly because that's why we need 7 million more people. You need people to understand, so all these tools, who work for companies. If you had less tools, we need less people. >> Do you think, you know I wrote about this as well, that the security industry is anomalous and that the leader has, you know, single digit, low single digit >> Yes >> market shares. Do you think that you can change that? >> Well, you know, when I started that was exactly the observation I had Dave, which you highlighted in your article. We were the largest by revenue, by small margin. And we were one and half percent of the industry. Now we're closer to three, three to four percent and we're still at, you know, like you said, going to be around $7 billion. So I see a path for us to double from here and then double from there, and hopefully as we keep doubling and some point in time, you know, I'd like to get to double digits to start with. >> One of the things that I think has to happen is this has to grow dramatically, the ecosystem. I wonder if you could talk about the ecosystem and your strategy there. >> Well, you know, it's a matter of perspective. I think we have to get more penetrated in our largest customers. So we have, you know, 1800 of the top 2000 customers in the world are Palo Alto customers. But we're not fully penetrated with all our capabilities and the same customers set, so yes the ecosystem needs to grow, but the pandemic has taught us the ecosystem can grow wherever they are without having to come to Vegas. Which I don't think is a bad thing to be honest. So the ecosystem is growing. You are seeing new players come to the ecosystem. Five years ago you didn't see a lot of systems integrators and security. You didn't see security offshoots of telecom companies. You didn't see the Optivs, the WWTs, the (indistinct) of the world (coughs) make a concerted shift towards consolidation or services and all that is happening >> Dave: Mm >> as we speak today in the audience you will find people from Google, Amazon Microsoft are sitting in the audience. People from telecom companies are sitting in the audience. These people weren't there five years ago. So you are seeing >> Dave: Mm >> the ecosystem's adapting. They're, they want to be front and center of solving the customer's problem around security and they want to consolidate capability, they need. They don't want to go work with a hundred vendors because you know, it's like, it's hard. >> And the global system integrators are key. I always say they like to eat at the trough and there's a lot of money in security. >> Yes. >> Dave: (laughs) >> Well speaking of the ecosystem, you had Thomas Curry and Google Cloud CEO in your fireside chat in the keynote. Talk a little bit about how Google Cloud plus Palo Alto Networks, the Zero Trust Partnership and what it's enable customers to achieve. >> Lisa, that's a great question. (clears his throat) Thank you for bringing it up. Look, you know the, one of the most fundamental shifts that is happening is obviously the shift to the Cloud. Now when that shift fully, sort of, takes shape you will realize if your network has changed and you're delivering everything to the Cloud you need to go figure out how to bring the traffic to the Cloud. You don't have to bring it back to your data center you can bring it straight to the Cloud. So in that context, you know we use Google Cloud and Amazon Cloud, to be able to carry our traffic. We're going from a product company to a services company in addition, right? Cuz when we go from firewalls to SASE we're not carrying your traffic. When we carry our traffic, we need to make sure we have underlying capability which is world class. We think GCP and AWS and Azure run some of the biggest and best networks in the world. So our partnership with Google is such that we use their public Cloud, we sit on top of their Cloud, they give us increased enhanced functionality so that our customers SASE traffic gets delivered in priority anywhere in the world. They give us tooling to make sure that there's high reliability. So you know, we partner, they have Beyond Corp which is their version of Zero Trust which allows you to take unmanaged devices with browsers. We have SASE, which allows you to have managed devices. So the combination gives our collective customers the ability for Zero Trust. >> Do you feel like there has to be more collaboration within the ecosystem, the security, you know, landscape even amongst competitors? I mean I think about Google acquires Mandiant. You guys have Unit 42. Should and will, like, Wendy Whitmore and maybe they already are, Kevin Mandia talk more and share more data. If security's a data problem is all this data >> Nikesh: Yeah look I think the industry shares threat data, both in private organizations as well as public and private context, so that's not a problem. You know the challenge with too much collaboration in security is you never know. Like you know, the moment you start sharing your stuff at third parties, you go out of Secure Zone. >> Lisa: Mm >> Our biggest challenge is, you know, I can't trust a third party competitor partner product. I have to treat it with as much suspicion as anything else out there because the only way I can deliver Zero Trust is to not trust anything. So collaboration in Zero Trust are a bit of odds with each other. >> Sounds like another problem you can solve >> (laughs) >> Nikesh last question for you. >> Yes >> Favorite customer or example that you think really articulates the value of what Palo Alto was delivering? >> Look you know, it's a great question, Lisa. I had this seminal conversation with a customer and I explained all those things we were talking about and the customer said to me, great, okay so what do I need to do? I said, fun, you got to trust me because you know, we are on a journey, because in the past, customers have had to take the onus on themselves of integrating everything because they weren't sure a small startup will be independent, be bought by another cybersecurity company or a large cybersecurity company won't get gobbled up and split into pieces by private equity because every one of the cybersecurity companies have had a shelf life. So you know, our aspiration is to be the evergreen cybersecurity company. We will always be around and we will always tackle innovation and be on the front line. So the customer understood what we're doing. Over the last three years we've been working on a transformation journey with them. We're trying to bring them, or we have brought them along the path of Zero Trust and we're trying to work with them to deliver this notion of reducing their meantime to remediate from days to minutes. Now that's an outcome based approach that's a partnership based approach and we'd like, love to have more and more customers of that kind. I think we weren't ready to be honest as a company four and a half years ago, but I think today we're ready. Hence my keynote was called The Perfect Storm. I think we're at the right time in the industry with the right capabilities and the right ecosystem to be able to deliver what the industry needs. >> The perfect storm, partners, customers, investors, employees. Nikesh, it's been such a pleasure having you on theCUBE. Thank you for coming to talk to Dave and me right after your keynote. We appreciate that and we look forward to two days of great coverage from your executives, your customers, and your partners. Thank you. >> Well, thank you for having me, Lisa and Dave and thank you >> Dave: Pleasure >> for what you guys do for our industry. >> Our pleasure. For Nikesh Arora and Dave Vellante, I'm Lisa Martin, you're watching theCUBE live at MGM Grand Hotel in Las Vegas, Palo Alto Ignite 22. Stick around Dave and I will be joined by our next guest in just a minute. (cheerful music plays out)

(upbeat music) >> Every company needs great salespeople, it's one of the most lucrative professions out there. And there's plenty of wisdom and knowledge that's been gathered over the years about selling. We've heard it all, famous quotes from the greatest salespeople of our time, like Zig Ziglar and Jeffrey Gitomer, and Dale Carnegie and Jack Welch, and many others. Things like, "Each of us has only 24 hours in a day, "it's all about how we use our time." And, "You don't have to be great to start, "but you have to start to be great." And then I love this one, "People hate to be sold, but they love to buy." "There are no traffic jams on the extra mile, "make change before you have to." And the all time classic, "Put that coffee down. "Coffee is for closers." Thousands of pieces of sales advice are readily available in books, videos, on blogs and in podcasts, and many of these are free of charge. So why would entrepreneurs start a company to train salespeople? And how is it that sharp investors are pouring millions of dollars into this space? Hello everyone, and welcome to this Cube Video Exclusive, my name is Dave Vellante, and today we welcome Paul Fifield who's the co-founder and CEO of Sales Impact Academy who's going to answer these questions and share some exciting news on the startups. Paul, welcome to "The Cube" good to see you again. >> Yeah, good to see you again, Dave, great to be here. >> Hey, so before we get into the hard news, tell us a little bit about the Sales Impact Academy, why'd you start the company, maybe some of the fundamentals of this market, your total available market, who you're targeting, you know, what's the premise behind the company? >> Yeah sure. So I mean, I started the company, it was actually pretty organic in the way it began. I had a 10 year career as a CRO and it was, you know, had a couple of great hits with two companies, but it was a real struggle to basically, you know, operate as a CRO and learn your craft at the same time. And so when I left my last company, I kind of got out there, I wanted to kind of give back a little bit and I started doing some voluntary teaching in and around London, and I actually, one of the companies I started was in New York so I got schooled very much on a sort of US approach to how you build a modern you know, go to market and sales operation. Started going out there, doing some teaching, realized that so many people just didn't have a clue about how to build a scalable and predictable revenue function, and I kind of felt sorry for them. So I literally started doing some, you know, online classes myself, got my co-founder Alex to put curriculum together as well and we literally started just doing online classes, very live, very organic, just a Google Drive and some decks, and it really just blew up from there. >> That's amazing. I mean, so you've my, you know, tongue and cheek up front, but people might wonder, why do you need a platform 'cause there's so much free information out there? Is it to organize, is it a discipline thing? Explain that. >> Well, I think the way I sort of see this is that is that the lack of structured learning and education is actually one of the greatest educational travesties, I think, of the last 50 years, okay. Now sales and go to market is a huge global profession, right? Half the world's companies are B2B, so roughly that's a proxy for half the world's GDP, right? Which is $40 trillion of GDP. Now that 40 trillion rests on kind of the success of the growth and the sales functions of all those companies. Yet in its infinite wisdom, the global education system literally just ignored sales and go to market as a profession. Some universities are kind of catching up, but it's really too little too late. So what I sort of say to people, you imagine this Dave, right. You imagine if the way that law worked as a profession let's say, is that there's no law school, there's no law training, there's no even in work professional continuous professional development in law. The way that it works is you leave university, join a company, start practicing law and just use like YouTube just to maybe like, you know, where you're struggling, just use YouTube to like work out what's going on. The legal profession would be in absolute chaos. And that's what's happened in the sales and go to market profession, okay. What this profession desperately desperately needs is structured learning, good pedagogy, good well designed course and curriculum. And here's the other thing, right? Is the sort of paradox of infinite information is that just because all the information is out there, right, doesn't mean it's actually a good learning experience. Like, where do you find it? What's good? What's not good? And also the other thing I'd point out is that there is this kind of myth that all the information is out there on the internet. But actually what we do, and we'll come into it in a second is, the people teaching on our platform are the elite people from the industry. They haven't got time to do blog posts and just explain to people how they operate. They're going from company to company working at like, you know, working at these kind of elite companies. And they're the people that teach, and that information is not readily available and freely out there on the internet. >> Yeah, real opportunity, you made some great points there. I think business schools are finally starting to teach a little bit about public speaking and presenting, but nobody's teaching us how to sell. As Earl Nightingale says, "To some degree we're all salespeople, "selling our family on living the good life" or whatever. What movie we want to see tonight. But okay, let's get to the hard news. You got fresh funding of 22 million, tell us about that, congratulations. You know, the investors, what else can you share with us? >> Sure. Well, I mean, obviously, you know, immensely proud. We started from very sort of humble beginnings, as I said, we've now scaled very rapidly, we're a subscription business, we're a SaaS business. We'll come onto some of the growth metrics shortly, but just in a couple of years, you know, the last year which ended January, we grew 500% from year one, we're now well over 125 people, and I'm very, very, very honored, flattered, humbled that MIT, obviously one of those prestigious universities in the world, has taken a direct investment by their endowment fund, HubSpot Ventures. Another Boston great has also taken a direct investment as well. They actually began as a customer and loved what we were doing so much that they then decided to make an investment. Stage 2 Capital who invested in our seed round pretty much tripled down, played a huge role in helping us assemble MIT and HubSpot ventures as investors, and they continue to be an incredible VC giving us amazing, amazing support that their LP network of go to market leaders is second to none. And then Emerge Education, who is our pre-seed investor, they're actually based in London, also joined this round as well. >> Great, well actually, let's jump ahead. Let's talk about the metrics. I mean, if Stage Two is involved, they're hardcore. What can you share with us about, you know, everybody's chasing AR and NR and the like, what can you share with us? >> They are both pretty important. Well, I think from a headcount perspective, so as I mentioned our fiscal ends at the end of January, each year. We've gone from 25 to over 125 employees in that time. We've gone from 82 to 260 customers also in that time. And customers now include HubSpot, Gong, Klaviyo, GitHub, GT, Six Cents, so some really sort of major SaaS companies in the space. Our revenue's grown significantly with 5X. So 500% increase in revenue year over year, which is pretty fast, very proud of that. Our learning community has gone from over 3000 people to almost 15,000 professionals, and that makes us comfortably, the largest go to market learning community in the world. >> How did you decide when to scale? What were the sort of signals that said to you, "Okay, we're ready, "we have product market fit, "we can now scale the go to market." What were the signals there, Paul? >> Yeah. Well, I mean, I think for a very small team to achieve that level of growth in customers, to be kind of honest with you, like it's the pull that we're getting from the market. And I think the thing that has surprised me the most, perhaps in the last 12 months, is the pull we're getting from the enterprise. We're you know, I can't really announce, we've actually got a huge pilot with one of the largest companies actually in the world which is going fantastically well, our pipeline for enterprise customers is absolutely huge. But as you can imagine, if you've got distributed teams all over the world, we're living and working in this kind of hybrid world, how on earth do you kind of upscale all those people, right, that are, like I say, that are so distributed. It's impossible. Like in work, in the office delivery of training is pretty much dead, right? And so we sort of fill this really big pain, we solved this really, really big pain of how to effectively upskill people through this kind of live curriculum and this live teaching approach that we have. So I think for me, it's the pull that we're getting from the market really meant that you know, we have to double down. There is such a massive TAM, it is absolutely ridiculous. I mean, I think there are 20 million people just in sales and go to market in tech alone, right. And I mentioned to you earlier, half the world's companies effectively, you know, are B2B and therefore represent, you know, at its largest scope, our TAM. >> Excellent, thank you for that. Tell us more about the product and the platform. How's it work if I'm a customer, what type of investment do I have to make both financially? And what's my time commitment? How do you structure that? >> So the model is basically on a seat model. So roughly speaking, every seat's about a thousand dollars per year per rep. The lift is light. So we've got a very low onboarding, it's not a highly complex technical product, right? We've got a vast curriculum of learning that covers learning for, you know, SDRs, and the AEs, and CS reps, and leadership management training. We're developing curriculum for technical pre-sales, we're developing curriculum for revenue operations. And so it's very, very simple. We basically, it's a seat model, people literally just send us the seats and the details, we get people up and running in the platform, they start then enrolling and we have a customer success team that then plots out learning journeys and learning pathways for all of our customers. And actually what's starting to happen now, which is very, very exciting is that, you know, we're actually a key part of people's career development pathway. So to go from you know, SDR1 let's say to SDR2, you have to complete these three courses with Sales Impact Academy, and let's say, get 75% in your exam and it becomes a very powerful and simple way of developing career pathway. >> Yeah, so really detailed curriculum. So I was going to say, do I as a sales professional, do I pick and choose the things that are most relevant for me? Or are people actually going through a journey in career progression, or maybe both? >> Yeah, it's a mixture of both. We tend to see now, we're sort of starting to standardize, but really we're developing enough curriculum that over, let's say a 15 year period, you could start with us as an SDR and then end as a chief revenue officer, you know, running the entire function. This is the other thing about the crazy world of go to market. Very often, people are put into roles and it's sink or swim. There's no real learning that happens, there's no real development that happens before people take these big steps. And what this platform does so beautifully is is it equips people with the right skills and knowledge before they take that next step in their profession and in their career. And it just dramatically improves their chances of succeeding. >> Who are the trainers? Who's leading the classes, how do you find these guys, how do you structure? What are the content, you know, vectors, where's all that come from? >> Yeah. So the sort of secret source of what we do, beyond just the live instruction, beyond the significant amount of peer to peer learning that goes on, is that we go and source the absolute most elite people in go to market to teach, okay. Now I mentioned to you before, you've got these people that are going from like job to job at the very like the sort of peak of their careers, working for these incredible companies, it's that knowledge that we want to get access to, right. And so Stage 2 Capital is an incredible resource. The interesting thing about Stage 2 Capital as you know Dave, you know, run by Mark Roberge, who was on when we spoke last year and also Jay Po is all the LPs of Stage 2 Capital represent 3 to 400 of the most elite go to market professionals in the world. So, you know, about seven or eight of those are now on an advisory board. And so we have access to this incredible pool of talent. And so we know by consulting these amazing people who are the best people in certain aspects of go to market. We reach out to them and very often they're at a stage in their career where they're really kind of willing to give back, of course there are commercials around it as well, and there's lots of other benefits that we provide our teachers and our faculty, and what we call our coaches. But yeah, we source the very, very best people in the world to teach. >> Now, how does it work as a user of your service? Is it all on demand? Do you do live content or a combination? >> Yeah look, one of the big differentiators is this is a live delivery of learning, okay. Most learning online is typically done on demand, self-directed, and there's a ton of research. There's a great blog post on Andrew's recent site. A short time ago, which is talking about how the completion rates of on demand learning are somewhere between 3 and 6%. That is like, that's awful. >> Terrible. >> I was like why bother? However, we're seeing through that live instruction. So we teach two, one hour classes a week, that's it. We're upskilling very busy people, they're stressed, they've got targets. We have to be very, very cognizant of that. So we teach two, one hour classes a week. Typically, you know, Monday and a Wednesday, or a Tuesday and a Thursday. And that pace of learning is about right, it's kind of how humans learn as well. You know, short bursts of information, and then put that learning and those skills that you've acquired in class literally to work minutes after the class finishes. And so through that, and it sits in your calendar like a meeting, it doesn't feel overwhelming, you're learning together as a team as well. And all that combined, we see completion rates often in excess of 80% for our courses. >> Okay, so they block that time out- >> In the calendar, yeah. >> And they make an investment. Go ahead, please. >> Yeah yeah, exactly, sorry Dave. Yeah, yeah, exactly. So like, you know, we have course lengths. So one of our shorter courses are like four hours long over two weeks. And again, it's just literally in the calendar. We also teach what we call The Magic Learning Hour. And the magic learning hour is this one specific hour in the day that enables teams all over the western hemisphere to join the same class. And that magic learning hour is eight o'clock Pacific 11 o'clock Eastern, >> 4: 00 PM over in the UK, and 5:00 PM in the rest of Europe. And that one time in the day means that these enterprises have got teams all over the western hemisphere joining that class, learning together as a team, plus it's in the calendar and it's that approach is why we're seeing such high engagement and completion. >> That's very cool, the time zone thing. Now who's the target buyer? Are you selling only to sales teams? Can I as an individual purchase your service? >> Yeah, that's a good question. Currently it's a very much like a B2B motion. As I mentioned earlier on, we're getting an enormous pull from the enterprise, which is very exciting. You know, we have an enterprise segment, we have sort of more of a startup earlier stage segment, and then we have a mid-market segment that we call our sort of strategic, and that's typically and most of like venture backed, fast growth tech companies. So very much at the moment a B2B motion. We're launching our own technology platform in the early summer, and then later on this year we're going to be adding what's called PLG or a product led growth, so individuals can actually sign up to SIA. >> Yeah, I mean, I think you said $1,000 per year per rep, is that right? I mean, that's- >> Yeah. >> That's a small investment for an individual that wants to be part of, you know, this community and grow his or her career. So that's the growth plan? You go down market I would imagine, you talked about the western hemisphere, there's international opportunities maybe, local language. What's the growth plan? >> Yeah, I mean look, we've identified the magic learning hour for the middle east and APAC, which is eight o'clock in the morning in Istanbul, right. Is 5:00 PM in Auckland, it's quite fun trying to work out like what this optimum magic learning hour is. What's incredible is we teach in that time and that opens up the whole of the middle east and the whole of APAC, right, right down to Australia. And so once we're teaching the curriculum in those two slots, that means literally you can have teams in any country in the world, I think apart from Hawaii, you can actually access our live learning products in work time and that's incredibly powerful. So we have so many like axis of growth, we've got single users as I mentioned, but really Dave that's single users we'll be winning from the enterprise and that will represent pipeline that we could then potentially convert as well. And look, you make a very good point. You know, we've seen students are now leaving university with over $100,000 dollars in debt. We've got a massive, massive debt problem here in the US with student debt. You could absolutely sign up to our platform at let's say a hundred bucks a month, right. And probably within six months, gain enough knowledge and skill to walk into a $60,000 a year based salary job as an SDR, that's a huge entry level salary. And you could do that without even going to university. So there could be a time here where we become a really viable alternative to actually even going to university. >> I love it. The cost education going through the roof, it's out of reach for so many people. Paul, congratulations on the progress, the fresh funding. Great to have you back in "The Cube." We'd love to have you back and follow your ascendancy. I think great things ahead for you guys. >> Thank you very much, Dave. >> All right, and thank you for watching. This is Dave Vellante for "The Cube, we'll see you next time. (upbeat music)

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle, everybody to Cuban cloud. My name is Dave Volonte, and I'll be here throughout the day with my co host, John Ferrier, who was quarantined in an undisclosed location in California. He's all good. Don't worry. Just precautionary. John, how are you doing? >>Hey, great to see you. John. Quarantine. My youngest daughter had covitz, so contact tracing. I was negative in quarantine at a friend's location. All good. >>Well, we wish you the best. Yeah, well, right. I mean, you know what's it like, John? I mean, you're away from your family. Your basically shut in, right? I mean, you go out for a walk, but you're really not in any contact with anybody. >>Correct? Yeah. I mean, basically just isolation, Um, pretty much what everyone's been kind of living on, kind of suffering through, but hopefully the vaccines are being distributed. You know, one of the things we talked about it reinvent the Amazon's cloud conference. Was the vaccine on, but just the whole workflow around that it's gonna get better. It's kind of really sucky. Here in the California area, they haven't done a good job, a lot of criticism around, how that's rolling out. And, you know, Amazon is now offering to help now that there's a new regime in the U. S. Government S o. You know, something to talk about, But certainly this has been a terrible time for Cove it and everyone in the deaths involved. But it's it's essentially pulled back the covers, if you will, on technology and you're seeing everything. Society. In fact, um, well, that's big tech MIT disinformation campaigns. All these vulnerabilities and cyber, um, accelerated digital transformation. We'll talk about a lot today, but yeah, it's totally changed the world. And I think we're in a new generation. I think this is a real inflection point, Dave. You know, modern society and the geo political impact of this is significant. You know, one of the benefits of being quarantined you'd be hanging out on these clubhouse APS, uh, late at night, listening to experts talk about what's going on, and it's interesting what's happening with with things like water and, you know, the island of Taiwan and China and U. S. Sovereignty, data, sovereignty, misinformation. So much going on to talk about. And, uh, meanwhile, companies like Mark injuries in BC firm starting a media company. What's going on? Hell freezing over. So >>we're gonna be talking about a lot of that stuff today. I mean, Cuba on cloud. It's our very first virtual editorial event we're trying to do is bring together our community. It's a it's an open forum and we're we're running the day on our 3 65 software platform. So we got a great lineup. We got CEO Seo's data Practitioners. We got a hard core technologies coming in, cloud experts, investors. We got some analysts coming in and we're creating this day long Siri's. And we've got a number of sessions that we've developed and we're gonna unpack. The future of Cloud computing in the coming decade is, John said, we're gonna talk about some of the public policy new administration. What does that mean for tech and for big tech in General? John, what can you add to that? >>Well, I think one of the things that we talked about Cove in this personal impact to me but other people as well. One of the things that people are craving right now is information factual information, truth texture that we call it. But hear this event for us, Davis, our first inaugural editorial event. Robbo, Kristen, Nicole, the entire Cube team Silicon angle, really trying to put together Morva cadence we're gonna doom or of these events where we can put out feature the best people in our community that have great fresh voices. You know, we do interview the big names Andy Jassy, Michael Dell, the billionaires with people making things happen. But it's often the people under there that are the rial newsmakers amid savory, for instance, that Google one of the most impressive technical people, he's gotta talk. He's gonna present democratization of software development in many Mawr riel people making things happen. And I think there's a communal element. We're going to do more of these. Obviously, we have, uh, no events to go to with the Cube. So we have the cube virtual software that we have been building and over years and now perfecting and we're gonna introduce that we're gonna put it to work, their dog footing it. We're gonna put that software toe work. We're gonna do a lot mawr virtual events like this Cuban cloud Cuban startup Cuban raising money. Cuban healthcare, Cuban venture capital. Always think we could do anything. Question is, what's the right story? What's the most important stories? Who's telling it and increase the aperture of the lens of the industry that we have and and expose that and fastest possible. That's what this software, you'll see more of it. So it's super exciting. We're gonna add new features like pulling people up on stage, Um, kind of bring on the clubhouse vibe and more of a community interaction with people to meet each other, and we'll roll those out. But the goal here is to just showcase it's cloud story in a way from people that are living it and providing value. So enjoy the day is gonna be chock full of presentations. We're gonna have moderated chat in these sessions, so it's an all day event so people can come in, drop out, and also that's everything's on demand immediately after the time slot. But you >>want to >>participate, come into the time slot into the cube room or breakout session. Whatever you wanna call it, it's a cube room, and the people in there chatting and having a watch party. So >>when you're in that home page when you're watching, there's a hero video there. Beneath that, there's a calendar, and you'll see that red line is that red horizontal line of vertical line is rather, it's a linear clock that will show you where we are in the day. If you click on any one of those sessions that will take you into the chat, we'll take you through those in a moment and share with you some of the guests that we have upcoming and and take you through the day what I wanted to do. John is trying to set the stage for the conversations that folks are gonna here today. And to do that, I wanna ask the guys to bring up a graphic. And I want to talk to you, John, about the progression of cloud over time and maybe go back to the beginning and review the evolution of cloud and then really talk a little bit about where we think it Z headed. So, guys, if you bring up that graphic when a W S announced s three, it was March of 2000 and six. And as you recall, John you know, nobody really. In the vendor and user community. They didn't really pay too much attention to that. And then later that year, in August, it announced E C two people really started. They started to think about a new model of computing, but they were largely, you know, chicken tires. And it was kind of bleeding edge developers that really leaned in. Um what? What were you thinking at the time? When when you saw, uh, s three e c to this retail company coming into the tech world? >>I mean, I thought it was totally crap. I'm like, this is terrible. But then at that time, I was thinking working on I was in between kind of start ups and I didn't have a lot of seed funding. And then I realized the C two was freaking awesome. But I'm like, Holy shit, this is really great because I don't need to pay a lot of cash, the Provisional Data center, or get a server. Or, you know, at that time, state of the art startup move was to buy a super micro box or some sort of power server. Um, it was well past the whole proprietary thing. But you have to assemble probably anyone with 5 to 8 grand box and go in, and we'll put a couple ghetto rack, which is basically, uh, you know, you put it into some coasting location. It's like with everybody else in the tech ghetto of hosting, still paying monthly fees and then maintaining it and provisioning that's just to get started. And then Amazon was just really easy. And then from there you just It was just awesome. I just knew Amazon would be great. They had a lot of things that they had to fix. You know, custom domains and user interface Council got better and better, but it was awesome. >>Well, what we really saw the cloud take hold from my perspective anyway, was the financial crisis in, you know, 709 It put cloud on the radar of a number of CFOs and, of course, shadow I T departments. They wanted to get stuff done and and take I t in in in, ah, pecs, bite sized chunks. So it really was. There's cloud awakening and we came out of that financial crisis, and this we're now in this 10 year plus boom um, you know, notwithstanding obviously the economic crisis with cove it. But much of it was powered by the cloud in the decade. I would say it was really about I t transformation. And it kind of ironic, if you will, because the pandemic it hits at the beginning of this decade, >>and it >>creates this mandate to go digital. So you've you've said a lot. John has pulled forward. It's accelerated this industry transformation. Everybody talks about that, but and we've highlighted it here in this graphic. It probably would have taken several more years to mature. But overnight you had this forced march to digital. And if you weren't a digital business, you were kind of out of business. And and so it's sort of here to stay. How do you see >>You >>know what this evolution and what we can expect in the coming decades? E think it's safe to say the last 10 years defined by you know, I t transformation. That's not gonna be the same in the coming years. How do you see it? >>It's interesting. I think the big tech companies are on, but I think this past election, the United States shows um, the power that technology has. And if you look at some of the main trends in the enterprise specifically around what clouds accelerating, I call the second wave of innovations coming where, um, it's different. It's not what people expect. Its edge edge computing, for instance, has talked about a lot. But industrial i o t. Is really where we've had a lot of problems lately in terms of hacks and malware and just just overall vulnerabilities, whether it's supply chain vulnerabilities, toe actual disinformation, you know, you know, vulnerabilities inside these networks s I think this network effects, it's gonna be a huge thing. I think the impact that tech will have on society and global society geopolitical things gonna be also another one. Um, I think the modern application development of how applications were written with data, you know, we always been saying this day from the beginning of the Cube data is his integral part of the development process. And I think more than ever, when you think about cloud and edge and this distributed computing paradigm, that cloud is now going next level with is the software and how it's written will be different. You gotta handle things like, where's the compute component? Is it gonna be at the edge with all the server chips, innovations that Amazon apple intel of doing, you're gonna have compute right at the edge, industrial and kind of human edge. How does that work? What's Leighton see to that? It's it really is an edge game. So to me, software has to be written holistically in a system's impact on the way. Now that's not necessarily nude in the computer science and in the tech field, it's just gonna be deployed differently. So that's a complete rewrite, in my opinion of the software applications. Which is why you're seeing Amazon Google VM Ware really pushing Cooper Netease and these service messes in the micro Services because super critical of this technology become smarter, automated, autonomous. And that's completely different paradigm in the old full stack developer, you know, kind of model. You know, the full stack developer, his ancient. There's no such thing as a full stack developer anymore, in my opinion, because it's a half a stack because the cloud takes up the other half. But no one wants to be called the half stack developer because it doesn't sound as good as Full Stack, but really Cloud has eliminated the technology complexity of what a full stack developer used to dio. Now you can manage it and do things with it, so you know, there's some work to done, but the heavy lifting but taking care of it's the top of the stack that I think is gonna be a really critical component. >>Yeah, and that that sort of automation and machine intelligence layer is really at the top of the stack. This this thing becomes ubiquitous, and we now start to build businesses and new processes on top of it. I wanna I wanna take a look at the Big Three and guys, Can we bring up the other The next graphic, which is an estimate of what the revenue looks like for the for the Big three. And John, this is I asked and past spend for the Big Three Cloud players. And it's It's an estimate that we're gonna update after earning seasons, and I wanna point a couple things out here. First is if you look at the combined revenue production of the Big Three last year, it's almost 80 billion in infrastructure spend. I mean, think about that. That Z was that incremental spend? No. It really has caused a lot of consolidation in the on Prem data center business for guys like Dell. And, you know, um, see, now, part of the LHP split up IBM Oracle. I mean, it's etcetera. They've all felt this sea change, and they had to respond to it. I think the second thing is you can see on this data. Um, it's true that azure and G C P they seem to be growing faster than a W s. We don't know the exact numbers >>because >>A W S is the only company that really provides a clean view of i s and pass. Whereas Microsoft and Google, they kind of hide the ball in their numbers. I mean, I don't blame them because they're behind, but they do leave breadcrumbs and clues about growth rates and so forth. And so we have other means of estimating, but it's it's undeniable that azure is catching up. I mean, it's still quite distance the third thing, and before I want to get your input here, John is this is nuanced. But despite the fact that Azure and Google the growing faster than a W s. You can see those growth rates. A W s I'll call this out is the only company by our estimates that grew its business sequentially last quarter. Now, in and of itself, that's not significant. But what is significant is because AWS is so large there $45 billion last year, even if the slower growth rates it's able to grow mawr and absolute terms than its competitors, who are basically flat to down sequentially by our estimates. Eso So that's something that I think is important to point out. Everybody focuses on the growth rates, but it's you gotta look at also the absolute dollars and, well, nonetheless, Microsoft in particular, they're they're closing the gap steadily, and and we should talk more about the competitive dynamics. But I'd love to get your take on on all this, John. >>Well, I mean, the clouds are gonna win right now. Big time with the one the political climate is gonna be favoring Big check. But more importantly, with just talking about covert impact and celebrating the digital transformation is gonna create a massive rising tide. It's already happening. It's happening it's happening. And again, this shift in programming, uh, models are gonna really kinda accelerating, create new great growth. So there's no doubt in my mind of all three you're gonna win big, uh, in the future, they're just different, You know, the way they're going to market position themselves, they have to be. Google has to be a little bit different than Amazon because they're smaller and they also have different capabilities, then trying to catch up. So if you're Google or Microsoft, you have to have a competitive strategy to decide. How do I wanna ride the tide If you will put the rising tide? Well, if I'm Amazon, I mean, if I'm Microsoft and Google, I'm not going to try to go frontal and try to copy Amazon because Amazon is just pounding lead of features and scale and they're different. They were, I would say, take advantage of the first mover of pure public cloud. They really awesome. It passed and I, as they've integrated in Gardner, now reports and integrated I as and passed components. So Gardner finally got their act together and said, Hey, this is really one thing. SAS is completely different animal now Microsoft Super Smart because they I think they played the right card. They have a huge installed base converted to keep office 3 65 and move sequel server and all their core jewels into the cloud as fast as possible, clarified while filling in the gaps on the product side to be cloud. So you know, as you're doing trends job, they're just it's just pedal as fast as you can. But Microsoft is really in. The strategy is just go faster trying. Keep pedaling fast, get the features, feature velocity and try to make it high quality. Google is a little bit different. They have a little power base in terms of their network of strong, and they have a lot of other big data capabilities, so they have to use those to their advantage. So there is. There is there is competitive strategy game application happening with these companies. It's not like apples, the apples, In my opinion, it never has been, and I think that's funny that people talk about it that way. >>Well, you're bringing up some great points. I want guys bring up the next graphic because a lot of things that John just said are really relevant here. And what we're showing is that's a survey. Data from E. T. R R Data partners, like 1400 plus CEOs and I T buyers and on the vertical axis is this thing called Net score, which is a measure of spending momentum. And the horizontal axis is is what's called market share. It's a measure of the pervasiveness or, you know, number of mentions in the data set. There's a couple of key points I wanna I wanna pick up on relative to what John just said. So you see A W S and Microsoft? They stand alone. I mean, they're the hyper scale er's. They're far ahead of the pack and frankly, they have fall down, toe, lose their lead. They spend a lot on Capex. They got the flywheel effects going. They got both spending velocity and large market shares, and so, but they're taking a different approach. John, you're right there living off of their SAS, the state, their software state, Andi, they're they're building that in to their cloud. So they got their sort of a captive base of Microsoft customers. So they've got that advantage. They also as we'll hear from from Microsoft today. They they're building mawr abstraction layers. Andy Jassy has said We don't wanna be in that abstraction layer business. We wanna have access to those, you know, fine grain primitives and eso at an AP level. So so we can move fast with the market. But but But so those air sort of different philosophies, John? >>Yeah. I mean, you know, people who know me know that I love Amazon. I think their product is superior at many levels on in its way that that has advantages again. They have a great sass and ecosystem. They don't really have their own SAS play, although they're trying to add some stuff on. I've been kind of critical of Microsoft in the past, but one thing I'm not critical of Microsoft, and people can get this wrong in the marketplace. Actually, in the journalism world and also in just some other analysts, Microsoft has always had large scale eso to say that Microsoft never had scale on that Amazon owned the monopoly on our franchise on scales wrong. Microsoft had scale from day one. Their business was always large scale global. They've always had infrastructure with MSN and their search and the distributive how they distribute browsers and multiple countries. Remember they had the lock on the operating system and the browser for until the government stepped in in 1997. And since 1997 Microsoft never ever not invested in infrastructure and scale. So that whole premise that they don't compete well there is wrong. And I think that chart demonstrates that there, in there in the hyper scale leadership category, hands down the question that I have. Is that there not as good and making that scale integrate in because they have that legacy cards. This is the classic innovator's dilemma. Clay Christensen, right? So I think they're doing a good job. I think their strategy sound. They're moving as fast as they can. But then you know they're not gonna come out and say We don't have the best cloud. Um, that's not a marketing strategy. Have to kind of hide in this and get better and then double down on where they're winning, which is. Clients are converting from their legacy at the speed of Microsoft, and they have a huge client base, So that's why they're stopping so high That's why they're so good. >>Well, I'm gonna I'm gonna give you a little preview. I talked to gear up your f Who's gonna come on today and you'll see I I asked him because the criticism of Microsoft is they're, you know, they're just good enough. And so I asked him, Are you better than good enough? You know, those are fighting words if you're inside of Microsoft, but so you'll you'll have to wait to see his answer. Now, if you guys, if you could bring that that graphic back up I wanted to get into the hybrid zone. You know where the field is. Always got >>some questions coming in on chat, Dave. So we'll get to those >>great Awesome. So just just real quick Here you see this hybrid zone, this the field is bunched up, and the other companies who have a large on Prem presence and have been forced to initiate some kind of coherent cloud strategy included. There is Michael Michael, multi Cloud, and Google's there, too, because they're far behind and they got to take a different approach than a W s. But as you can see, so there's some real progress here. VM ware cloud on AWS stands out, as does red hat open shift. You got VM Ware Cloud, which is a VCF Cloud Foundation, even Dell's cloud. And you'd expect HP with Green Lake to be picking up momentum in the future quarters. And you've got IBM and Oracle, which there you go with the innovator's dilemma. But there, at least in the cloud game, and we can talk about that. But so, John, you know, to your point, you've gotta have different strategies. You're you're not going to take out the big too. So you gotta play, connect your print your on Prem to your cloud, your hybrid multi cloud and try to create new opportunities and new value there. >>Yeah, I mean, I think we'll get to the question, but just that point. I think this Zeri Chen's come on the Cube many times. We're trying to get him to come on lunch today with Features startup, but he's always said on the Q B is a V C at Greylock great firm. Jerry's Cloud genius. He's been there, but he made a point many, many years ago. It's not a winner. Take all the winner. Take most, and the Big Three maybe put four or five in there. We'll take most of the markets here. But I think one of the things that people are missing and aren't talking about Dave is that there's going to be a second tier cloud, large scale model. I don't want to say tear to cloud. It's coming to sound like a sub sub cloud, but a new category of cloud on cloud, right? So meaning if you get a snowflake, did I think this is a tale? Sign to what's coming. VM Ware Cloud is a native has had huge success, mainly because Amazon is essentially enabling them to be successful. So I think is going to be a wave of a more of a channel model of indirect cloud build out where companies like the Cube, potentially for media or others, will build clouds on top of the cloud. So if Google, Microsoft and Amazon, whoever is the first one to really enable that okay, we'll do extremely well because that means you can compete with their scale and create differentiation on top. So what snowflake did is all on Amazon now. They kind of should go to azure because it's, you know, politically correct that have multiple clouds and distribution and business model shifts. But to get that kind of performance they just wrote on Amazon. So there's nothing wrong with that. Because you're getting paid is variable. It's cap ex op X nice categorization. So I think that's the way that we're watching. I think it's super valuable, I think will create some surprises in terms of who might come out of the woodwork on be a leader in a category. Well, >>your timing is perfect, John and we do have some questions in the chat. But before we get to that, I want to bring in Sargi Joe Hall, who's a contributor to to our community. Sargi. Can you hear us? All right, so we got, uh, while >>bringing in Sarpy. Let's go down from the questions. So the first question, Um, we'll still we'll get the student second. The first question. But Ronald ask, Can a vendor in 2021 exist without a hybrid cloud story? Well, story and capabilities. Yes, they could live with. They have to have a story. >>Well, And if they don't own a public cloud? No. No, they absolutely cannot. Uh hey, Sergey. How you doing, man? Good to see you. So, folks, let me let me bring in Sergeant Kohala. He's a He's a cloud architect. He's a practitioner, He's worked in as a technologist. And there's a frequent guest on on the Cube. Good to see you, my friend. Thanks for taking the time with us. >>And good to see you guys to >>us. So we were kind of riffing on the competitive landscape we got. We got so much to talk about this, like, it's a number of questions coming in. Um, but Sargi we wanna talk about you know, what's happening here in Cloud Land? Let's get right into it. I mean, what do you guys see? I mean, we got yesterday. New regime, new inaug inauguration. Do you do you expect public policy? You'll start with you Sargi to have What kind of effect do you think public policy will have on, you know, cloud generally specifically, the big tech companies, the tech lash. Is it gonna be more of the same? Or do you see a big difference coming? >>I think that there will be some changing narrative. I believe on that. is mainly, um, from the regulators side. A lot has happened in one month, right? So people, I think are losing faith in high tech in a certain way. I mean, it doesn't, uh, e think it matters with camp. You belong to left or right kind of thing. Right? But parlor getting booted out from Italy s. I think that was huge. Um, like, how do you know that if a cloud provider will not boot you out? Um, like, what is that line where you draw the line? What are the rules? I think that discussion has to take place. Another thing which has happened in the last 23 months is is the solar winds hack, right? So not us not sort acknowledging that I was Russia and then wish you watching it now, new administration might have a different sort of Boston on that. I think that's huge. I think public public private partnership in security arena will emerge this year. We have to address that. Yeah, I think it's not changing. Uh, >>economics economy >>will change gradually. You know, we're coming out off pandemic. The money is still cheap on debt will not be cheap. for long. I think m and a activity really will pick up. So those are my sort of high level, Uh, >>thank you. I wanna come back to them. And because there's a question that chat about him in a But, John, how do you see it? Do you think Amazon and Google on a slippery slope booting parlor off? I mean, how do they adjudicate between? Well, what's happening in parlor? Uh, anything could happen on clubhouse. Who knows? I mean, can you use a I to find that stuff? >>Well, that's I mean, the Amazons, right? Hiding right there bunkered in right now from that bad, bad situation. Because again, like people we said Amazon, these all three cloud players win in the current environment. Okay, Who wins with the U. S. With the way we are China, Russia, cloud players. Okay, let's face it, that's the reality. So if I wanted to reset the world stage, you know what better way than the, you know, change over the United States economy, put people out of work, make people scared, and then reset the entire global landscape and control all with cash? That's, you know, conspiracy theory. >>So you see the riches, you see the riches, get the rich, get richer. >>Yeah, well, that's well, that's that. That's kind of what's happening, right? So if you start getting into this idea that you can't actually have an app on site because the reason now I'm not gonna I don't know the particular parlor, but apparently there was a reason. But this is dangerous, right? So what? What that's gonna do is and whether it's right or wrong or not, whether political opinion is it means that they were essentially taken offline by people that weren't voted for that. Weren't that when people didn't vote for So that's not a democracy, right? So that's that's a different kind of regime. What it's also going to do is you also have this groundswell of decentralized thinking, right. So you have a whole wave of crypto and decentralized, um, cyber punks out there who want to decentralize it. So all of this stuff in January has created a huge counterculture, and I had predicted this so many times in the Cube. David counterculture is coming and and you already have this kind of counterculture between centralized and decentralized thinking and so I think the Amazon's move is dangerous at a fundamental level. Because if you can't get it, if you can't get buy domain names and you're completely blackballed by by organized players, that's a Mafia, in my opinion. So, uh, and that and it's also fuels the decentralized move because people say, Hey, if that could be done to them, it could be done to me. Just the fact that it could be done will promote a swing in the other direction. I >>mean, independent of of, you know, again, somebody said your political views. I mean Parlor would say, Hey, we're trying to clean this stuff up now. Maybe they didn't do it fast enough, but you think about how new parlor is. You think about the early days of Twitter and Facebook, so they were sort of at a disadvantage. Trying to >>have it was it was partly was what it was. It was a right wing stand up job of standing up something quick. Their security was terrible. If you look at me and Cory Quinn on be great to have him, and he did a great analysis on this, because if you look the lawsuit was just terrible. Security was just a half, asshole. >>Well, and the experience was horrible. I mean, it's not It was not a great app, but But, like you said, it was a quick stew. Hand up, you know, for an agenda. But nonetheless, you know, to start, get to your point earlier. It's like, you know, Are they gonna, you know, shut me down? If I say something that's, you know, out of line, or how do I control that? >>Yeah, I remember, like, 2019, we involved closing sort of remarks. I was there. I was saying that these companies are gonna be too big to fail. And also, they're too big for other nations to do business with. In a way, I think MNCs are running the show worldwide. They're running the government's. They are way. Have seen the proof of that in us this year. Late last year and this year, um, Twitter last night blocked Chinese Ambassador E in us. Um, from there, you know, platform last night and I was like, What? What's going on? So, like, we used to we used to say, like the Chinese company, tech companies are in bed with the Chinese government. Right. Remember that? And now and now, Actually, I think Chinese people can say the same thing about us companies. Uh, it's not a good thing. >>Well, let's >>get some question. >>Let's get some questions from the chat. Yeah. Thank you. One is on M and a subject you mentioned them in a Who do you see is possible emanate targets. I mean, I could throw a couple out there. Um, you know, some of the cdn players, maybe aka my You know, I like I like Hashi Corp. I think they're doing some really interesting things. What do you see? >>Nothing. Hashi Corp. And anybody who's doing things in the periphery is a candidate for many by the big guys, you know, by the hyper scholars and number two tier two or five hyper scholars. Right. Uh, that's why sales forces of the world and stuff like that. Um, some some companies, which I thought there will be a target, Sort of. I mean, they target they're getting too big, because off their evaluations, I think how she Corpuz one, um, >>and >>their bunch in the networking space. Uh, well, Tara, if I say the right that was acquired by at five this week, this week or last week, Actually, last week for $500 million. Um, I know they're founder. So, like I found that, Yeah, there's a lot going on on the on the network side on the anything to do with data. Uh, that those air too hard areas in the cloud arena >>data, data protection, John, any any anything you could adhere. >>And I think I mean, I think ej ej is gonna be where the gaps are. And I think m and a activity is gonna be where again, the bigger too big to fail would agree with you on that one. But we're gonna look at white Spaces and say a white space for Amazon is like a monster space for a start up. Right? So you're gonna have these huge white spaces opportunities, and I think it's gonna be an M and a opportunity big time start ups to get bought in. Given the speed on, I think you're gonna see it around databases and around some of these new service meshes and micro services. I mean, >>they there's a There's a question here, somebody's that dons asking why is Google who has the most pervasive tech infrastructure on the planet. Not at the same level of other to hyper scale is I'll give you my two cents is because it took him a long time to get their heads out of their ads. I wrote a piece of around that a while ago on they just they figured out how to learn the enterprise. I mean, John, you've made this point a number of times, but they just and I got a late start. >>Yeah, they're adding a lot of people. If you look at their who their hiring on the Google Cloud, they're adding a lot of enterprise chops in there. They realized this years ago, and we've talked to many of the top leaders, although Curry and hasn't yet sit down with us. Um, don't know what he's hiding or waiting for, but they're clearly not geared up to chicken Pete. You can see it with some some of the things that they're doing, but I mean competed the level of Amazon, but they have strength and they're playing their strength, but they definitely recognize that they didn't have the enterprise motions and people in the DNA and that David takes time people in the enterprise. It's not for the faint of heart. It's unique details that are different. You can't just, you know, swing the Google playbook and saying We're gonna home The enterprises are text grade. They knew that years ago. So I think you're going to see a good year for Google. I think you'll see a lot of change. Um, they got great people in there. On the product marketing side is Dev Solution Architects, and then the SRE model that they have perfected has been strong. And I think security is an area that they could really had a lot of value it. So, um always been a big fan of their huge network and all the intelligence they have that they could bring to bear on security. >>Yeah, I think Google's problem main problem that to actually there many, but one is that they don't They don't have the boots on the ground as compared to um, Microsoft, especially an Amazon actually had a similar problem, but they had a wide breath off their product portfolio. I always talk about feature proximity in cloud context, like if you're doing one thing. You wanna do another thing? And how do you go get that feature? Do you go to another cloud writer or it's right there where you are. So I think Amazon has the feature proximity and they also have, uh, aske Compared to Google, there's skills gravity. Larger people are trained on AWS. I think Google is trying there. So second problem Google is having is that that they're they're more focused on, I believe, um, on the data science part on their sort of skipping the cool components sort of off the cloud, if you will. The where the workloads needs, you know, basic stuff, right? That's like your compute storage and network. And that has to be well, talk through e think e think they will do good. >>Well, so later today, Paul Dillon sits down with Mids Avery of Google used to be in Oracle. He's with Google now, and he's gonna push him on on the numbers. You know, you're a distant third. Does that matter? And of course, you know, you're just a preview of it's gonna say, Well, no, we don't really pay attention to that stuff. But, John, you said something earlier that. I think Jerry Chen made this comment that, you know, Is it a winner? Take all? No, but it's a winner. Take a lot. You know the number two is going to get a big chunk of the pie. It appears that the markets big enough for three. But do you? Does Google have to really dramatically close the gap on be a much, much closer, you know, to the to the leaders in orderto to compete in this race? Or can they just kind of continue to bump along, siphon off the ad revenue? Put it out there? I mean, I >>definitely can compete. I think that's like Google's in it. Then it they're not. They're not caving, right? >>So But But I wrote I wrote recently that I thought they should even even put mawr oven emphasis on the cloud. I mean, maybe maybe they're already, you know, doubling down triple down. I just I think that is a multi trillion dollar, you know, future for the industry. And, you know, I think Google, believe it or not, could even do more. Now. Maybe there's just so much you could dio. >>There's a lot of challenges with these company, especially Google. They're in Silicon Valley. We have a big Social Justice warrior mentality. Um, there's a big debate going on the in the back channels of the tech scene here, and that is that if you want to be successful in cloud, you have to have a good edge strategy, and that involves surveillance, use of data and pushing the privacy limits. Right? So you know, Google has people within the country that will protest contract because AI is being used for war. Yet we have the most unstable geopolitical seen that I've ever witnessed in my lifetime going on right now. So, um, don't >>you think that's what happened with parlor? I mean, Rob Hope said, Hey, bar is pretty high to kick somebody off your platform. The parlor went over the line, but I would also think that a lot of the employees, whether it's Google AWS as well, said, Hey, why are we supporting you know this and so to your point about social justice, I mean, that's not something. That >>parlor was not just social justice. They were trying to throw the government. That's Rob e. I think they were in there to get selfies and being protesters. But apparently there was evidence from what I heard in some of these clubhouse, uh, private chats. Waas. There was overwhelming evidence on parlor. >>Yeah, but my point is that the employee backlash was also a factor. That's that's all I'm saying. >>Well, we have Google is your Google and you have employees to say we will boycott and walk out if you bid on that jet I contract for instance, right, But Microsoft one from maybe >>so. I mean, that's well, >>I think I think Tom Poole's making a really good point here, which is a Google is an alternative. Thio aws. The last Google cloud next that we were asked at they had is all virtual issue. But I saw a lot of I T practitioners in the audience looking around for an alternative to a W s just seeing, though, we could talk about Mano Cloud or Multi Cloud, and Andy Jassy has his his narrative around, and he's true when somebody goes multiple clouds, they put you know most of their eggs in one basket. Nonetheless, I think you know, Google's got a lot of people interested in, particularly in the analytic side, um, in in an alternative, hedging their bets eso and particularly use cases, so they should be able to do so. I guess my the bottom line here is the markets big enough to have Really? You don't have to be the Jack Welch. I gotta be number one and number two in the market. Is that the conclusion here? >>I think so. But the data gravity and the skills gravity are playing against them. Another problem, which I didn't want a couple of earlier was Google Eyes is that they have to boot out AWS wherever they go. Right? That is a huge challenge. Um, most off the most off the Fortune 2000 companies are already using AWS in one way or another. Right? So they are the multi cloud kind of player. Another one, you know, and just pure purely somebody going 200% Google Cloud. Uh, those cases are kind of pure, if you will. >>I think it's gonna be absolutely multi cloud. I think it's gonna be a time where you looked at the marketplace and you're gonna think in terms of disaster recovery, model of cloud or just fault tolerant capabilities or, you know, look at the parlor, the next parlor. Or what if Amazon wakes up one day and said, Hey, I don't like the cubes commentary on their virtual events, so shut them down. We should have a fail over to Google Cloud should Microsoft and Option. And one of people in Microsoft ecosystem wants to buy services from us. We have toe kind of co locate there. So these are all open questions that are gonna be the that will become certain pretty quickly, which is, you know, can a company diversify their computing An i t. In a way that works. And I think the momentum around Cooper Netease you're seeing as a great connective tissue between, you know, having applications work between clouds. Right? Well, directionally correct, in my opinion, because if I'm a company, why wouldn't I wanna have choice? So >>let's talk about this. The data is mixed on that. I'll share some data, meaty our data with you. About half the companies will say Yeah, we're spreading the wealth around to multiple clouds. Okay, That's one thing will come back to that. About the other half were saying, Yeah, we're predominantly mono cloud we didn't have. The resource is. But what I think going forward is that that what multi cloud really becomes. And I think John, you mentioned Snowflake before. I think that's an indicator of what what true multi cloud is going to look like. And what Snowflake is doing is they're building abstraction, layer across clouds. Ed Walsh would say, I'm standing on the shoulders of Giants, so they're basically following points of presence around the globe and building their own cloud. They call it a data cloud with a global mesh. We'll hear more about that later today, but you sign on to that cloud. So they're saying, Hey, we're gonna build value because so many of Amazon's not gonna build that abstraction layer across multi clouds, at least not in the near term. So that's a really opportunity for >>people. I mean, I don't want to sound like I'm dating myself, but you know the date ourselves, David. I remember back in the eighties, when you had open systems movement, right? The part of the whole Revolution OS I open systems interconnect model. At that time, the networking stacks for S N A. For IBM, decadent for deck we all know that was a proprietary stack and then incomes TCP I p Now os I never really happened on all seven layers, but the bottom layers standardized. Okay, that was huge. So I think if you look at a W s or some of the comments in the chat AWS is could be the s n a. Depends how you're looking at it, right? And you could say they're open. But in a way, they want more Amazon. So Amazon's not out there saying we love multi cloud. Why would they promote multi cloud? They are a one of the clouds they want. >>That's interesting, John. And then subject is a cloud architect. I mean, it's it is not trivial to make You're a data cloud. If you're snowflake, work on AWS work on Google. Work on Azure. Be seamless. I mean, certainly the marketing says that, but technically, that's not trivial. You know, there are latent see issues. Uh, you know, So that's gonna take a while to develop. What? Do your thoughts there? >>I think that multi cloud for for same workload and multi cloud for different workloads are two different things. Like we usually put multiple er in one bucket, right? So I think you're right. If you're trying to do multi cloud for the same workload, that's it. That's Ah, complex, uh, problem to solve architecturally, right. You have to have a common ap ice and common, you know, control playing, if you will. And we don't have that yet, and then we will not have that for a for at least one other couple of years. So, uh, if you if you want to do that, then you have to go to the lower, lowest common denominator in technical sort of stock, if you will. And then you're not leveraging the best of the breed technology off their from different vendors, right? I believe that's a hard problem to solve. And in another thing, is that that that I always say this? I'm always on the death side, you know, developer side, I think, uh, two deaths. Public cloud is a proxy for innovative culture. Right. So there's a catch phrase I have come up with today during shower eso. I think that is true. And then people who are companies who use the best of the breed technologies, they can attract the these developers and developers are the Mazen's off This digital sort of empires, amazingly, is happening there. Right there they are the Mazen's right. They head on the bricks. I think if you don't appeal to developers, if you don't but extensive for, like, force behind educating the market, you can't you can't >>put off. It's the same game Stepping story was seeing some check comments. Uh, guard. She's, uh, linked in friend of mine. She said, Microsoft, If you go back and look at the Microsoft early days to the developer Point they were, they made their phones with developers. They were a software company s Oh, hey, >>forget developers, developers, developers. >>You were if you were in the developer ecosystem, you were treated his gold. You were part of the family. If you were outside that world, you were competitors, and that was ruthless times back then. But they again they had. That was where it was today. Look at where the software defined businesses and starve it, saying it's all about being developer lead in this new way to program, right? So the cloud next Gen Cloud is going to look a lot like next Gen Developer and all the different tools and techniques they're gonna change. So I think, yes, this kind of developer ecosystem will be harnessed, and that's the power source. It's just gonna look different. So, >>Justin, Justin in the chat has a comment. I just want to answer the question about elastic thoughts on elastic. Um, I tell you, elastic has momentum uh, doing doing very well in the market place. Thea Elk Stack is a great alternative that people are looking thio relative to Splunk. Who people complain about the pricing. Of course it's plunks got the easy button, but it is getting increasingly expensive. The problem with elk stack is you know, it's open source. It gets complicated. You got a shard, the databases you gotta manage. It s Oh, that's what Ed Walsh's company chaos searches is all about. But elastic has some riel mo mentum in the marketplace right now. >>Yeah, you know, other things that coming on the chat understands what I was saying about the open systems is kubernetes. I always felt was that is a bad metaphor. But they're with me. That was the TCP I peep In this modern era, C t c p I p created that that the disruptor to the S N A s and the network protocols that were proprietary. So what KUBERNETES is doing is creating a connective tissue between clouds and letting the open source community fill in the gaps in the middle, where kind of way kind of probably a bad analogy. But that's where the disruption is. And if you look at what's happened since Kubernetes was put out there, what it's become kind of de facto and standard in the sense that everyone's rallying around it. Same exact thing happened with TCP was people were trashing it. It is terrible, you know it's not. Of course they were trashed because it was open. So I find that to be very interesting. >>Yeah, that's a good >>analogy. E. Thinks the R C a cable. I used the R C. A cable analogy like the VCRs. When they started, they, every VC had had their own cable, and they will work on Lee with that sort of plan of TV and the R C. A cable came and then now you can put any TV with any VCR, and the VCR industry took off. There's so many examples out there around, uh, standards And how standards can, you know, flair that fire, if you will, on dio for an industry to go sort of wild. And another trend guys I'm seeing is that from the consumer side. And let's talk a little bit on the consuming side. Um, is that the The difference wouldn't be to B and B to C is blood blurred because even the physical products are connected to the end user Like my door lock, the August door lock I didn't just put got get the door lock and forget about that. Like I I value the expedience it gives me or problems that gives me on daily basis. So I'm close to that vendor, right? So So the middle men, uh, middle people are getting removed from from the producer off the technology or the product to the consumer. Even even the sort of big grocery players they have their APs now, uh, how do you buy stuff and how it's delivered and all that stuff that experience matters in that context, I think, um, having, uh, to be able to sell to thes enterprises from the Cloud writer Breuder's. They have to have these case studies or all these sample sort off reference architectures and stuff like that. I think whoever has that mawr pushed that way, they are doing better like that. Amazon is Amazon. Because of that reason, I think they have lot off sort off use cases about on top of them. And they themselves do retail like crazy. Right? So and other things at all s. So I think that's a big trend. >>Great. Great points are being one of things. There's a question in there about from, uh, Yaden. Who says, uh, I like the developer Lead cloud movement, But what is the criticality of the executive audience when educating the marketplace? Um, this comes up a lot in some of my conversations around automation. So automation has been a big wave to automate this automate everything. And then everything is a service has become kind of kind of the the executive suite. Kind of like conversation we need to make everything is a service in our business. You seeing people move to that cloud model. Okay, so the executives think everything is a services business strategy, which it is on some level, but then, when they say Take that hill, do it. Developers. It's not that easy. And this is where a lot of our cube conversations over the past few months have been, especially during the cova with cute virtual. This has come up a lot, Dave this idea, and start being around. It's easy to say everything is a service but will implement it. It's really hard, and I think that's where the developer lead Connection is where the executive have to understand that in order to just say it and do it are two different things. That digital transformation. That's a big part of it. So I think that you're gonna see a lot of education this year around what it means to actually do that and how to implement it. >>I'd like to comment on the as a service and subject. Get your take on it. I mean, I think you're seeing, for instance, with HP Green Lake, Dell's come out with Apex. You know IBM as its utility model. These companies were basically taking a page out of what I what I would call a flawed SAS model. If you look at the SAS players, whether it's salesforce or workday, service now s a P oracle. These models are They're really They're not cloud pricing models. They're they're basically you got to commit to a term one year, two year, three year. We'll give you a discount if you commit to the longer term. But you're locked in on you. You probably pay upfront. Or maybe you pay quarterly. That's not a cloud pricing model. And that's why I mean, they're flawed. You're seeing companies like Data Dog, for example. Snowflake is another one, and they're beginning to price on a consumption basis. And that is, I think, one of the big changes that we're going to see this decade is that true cloud? You know, pay by the drink pricing model and to your point, john toe, actually implement. That is, you're gonna need a whole new layer across your company on it is quite complicated it not even to mention how you compensate salespeople, etcetera. The a p. I s of your product. I mean, it is that, but that is a big sea change that I see coming. Subject your >>thoughts. Yeah, I think like you couldn't see it. And like some things for this big tech exacts are hidden in the plain >>sight, right? >>They don't see it. They they have blind spots, like Look at that. Look at Amazon. They went from Melissa and 200 millisecond building on several s, Right, Right. And then here you are, like you're saying, pay us for the whole year. If you don't use the cloud, you lose it or will pay by month. Poor user and all that stuff like that that those a role models, I think these players will be forced to use that term pricing like poor minute or for a second, poor user. That way, I think the Salesforce moral is hybrid. They're struggling in a way. I think they're trying to bring the platform by doing, you know, acquisition after acquisition to be a platform for other people to build on top off. But they're having a little trouble there because because off there, such pricing and little closeness, if you will. And, uh, again, I'm coming, going, going back to developers like, if you are not appealing to developers who are writing the latest and greatest code and it is open enough, by the way open and open source are two different things that we all know that. So if your platform is not open enough, you will have you know, some problems in closing the deals. >>E. I want to just bring up a question on chat around from Justin didn't fitness. Who says can you touch on the vertical clouds? Has your offering this and great question Great CP announcing Retail cloud inventions IBM Athena Okay, I'm a huge on this point because I think this I'm not saying this for years. Cloud computing is about horizontal scalability and vertical specialization, and that's absolutely clear, and you see all the clouds doing it. The vertical rollouts is where the high fidelity data is, and with machine learning and AI efforts coming out, that's accelerated benefits. There you have tow, have the vertical focus. I think it's super smart that clouds will have some sort of vertical engine, if you will in the clouds and build on top of a control playing. Whether that's data or whatever, this is clearly the winning formula. If you look at all the successful kind of ai implementations, the ones that have access to the most data will get the most value. So, um if you're gonna have a data driven cloud you have tow, have this vertical feeling, Um, in terms of verticals, the data on DSO I think that's super important again, just generally is a strategy. I think Google doing a retail about a super smart because their whole pitches were not Amazon on. Some people say we're not Google, depending on where you look at. So every of these big players, they have dominance in the areas, and that's scarce. Companies and some companies will never go to Amazon for that reason. Or some people never go to Google for other reasons. I know people who are in the ad tech. This is a black and we're not. We're not going to Google. So again, it is what it is. But this idea of vertical specialization relevant in super >>forts, I want to bring to point out to sessions that are going on today on great points. I'm glad you asked that question. One is Alan. As he kicks off at 1 p.m. Eastern time in the transformation track, he's gonna talk a lot about the coming power of ecosystems and and we've talked about this a lot. That that that to compete with Amazon, Google Azure, you've gotta have some kind of specialization and vertical specialization is a good one. But of course, you see in the big Big three also get into that. But so he's talking at one o'clock and then it at 3 36 PM You know this times are strange, but e can explain that later Hillary Hunter is talking about she's the CTO IBM I B M's ah Financial Cloud, which is another really good example of specifying vertical requirements and serving. You know, an audience subject. I think you have some thoughts on this. >>Actually, I lost my thought. E >>think the other piece of that is data. I mean, to the extent that you could build an ecosystem coming back to Alan Nancy's premise around data that >>billions of dollars in >>their day there's billions of dollars and that's the title of the session. But we did the trillion dollar baby post with Jazzy and said Cloud is gonna be a trillion dollars right? >>And and the point of Alan Answer session is he's thinking from an individual firm. Forget the millions that you're gonna save shifting to the cloud on cost. There's billions in ecosystems and operating models. That's >>absolutely the business value. Now going back to my half stack full stack developer, is the business value. I've been talking about this on the clubhouses a lot this past month is for the entrepreneurs out there the the activity in the business value. That's the new the new intellectual property is the business logic, right? So if you could see innovations in how work streams and workflow is gonna be a configured differently, you have now large scale cloud specialization with data, you can move quickly and take territory. That's much different scenario than a decade ago, >>at the point I was trying to make earlier was which I know I remember, is that that having the horizontal sort of features is very important, as compared to having vertical focus. You know, you're you're more healthcare focused like you. You have that sort of needs, if you will, and you and our auto or financials and stuff like that. What Google is trying to do, I think that's it. That's a good thing. Do cook up the reference architectures, but it's a bad thing in a way that you drive drive away some developers who are most of the developers at 80 plus percent, developers are horizontal like you. Look at the look into the psyche of a developer like you move from company to company. And only few developers will say I will stay only in health care, right? So I will only stay in order or something of that, right? So they you have to have these horizontal capabilities which can be applied anywhere on then. On top >>of that, I think that's true. Sorry, but I'll take a little bit different. Take on that. I would say yes, that's true. But remember, remember the old school application developer Someone was just called in Application developer. All they did was develop applications, right? They pick the framework, they did it right? So I think we're going to see more of that is just now mawr of Under the Covers developers. You've got mawr suffer defined networking and software, defined storage servers and cloud kubernetes. And it's kind of like under the hood. But you got your, you know, classic application developer. I think you're gonna see him. A lot of that come back in a way that's like I don't care about anything else. And that's the promise of cloud infrastructure is code. So I think this both. >>Hey, I worked. >>I worked at people solved and and I still today I say into into this context, I say E r P s are the ultimate low code. No code sort of thing is right. And what the problem is, they couldn't evolve. They couldn't make it. Lightweight, right? Eso um I used to write applications with drag and drop, you know, stuff. Right? But But I was miserable as a developer. I didn't Didn't want to be in the applications division off PeopleSoft. I wanted to be on the tools division. There were two divisions in most of these big companies ASAP. Oracle. Uh, like companies that divisions right? One is the cooking up the tools. One is cooking up the applications. The basketball was always gonna go to the tooling. Hey, >>guys, I'm sorry. We're almost out of time. I always wanted to t some of the sections of the day. First of all, we got Holder Mueller coming on at lunch for a power half hour. Um, you'll you'll notice when you go back to the home page. You'll notice that calendar, that linear clock that we talked about that start times are kind of weird like, for instance, an appendix coming on at 1 24. And that's because these air prerecorded assets and rather than having a bunch of dead air, we're just streaming one to the other. So so she's gonna talk about people, process and technology. We got Kathy Southwick, whose uh, Silicon Valley CEO Dan Sheehan was the CEO of Dunkin Brands and and he was actually the c 00 So it's C A CEO connecting the dots to the business. Daniel Dienes is the CEO of you I path. He's coming on a 2:47 p.m. East Coast time one of the hottest companies, probably the fastest growing software company in history. We got a guy from Bain coming on Dave Humphrey, who invested $750 million in Nutanix. He'll explain why and then, ironically, Dheeraj Pandey stew, Minuteman. Our friend interviewed him. That's 3 35. 1 of the sessions are most excited about today is John McD agony at 403 p. M. East Coast time, she's gonna talk about how to fix broken data architectures, really forward thinking stuff. And then that's the So that's the transformation track on the future of cloud track. We start off with the Big Three Milan Thompson Bukovec. At one oclock, she runs a W s storage business. Then I mentioned gig therapy wrath at 1. 30. He runs Azure is analytics. Business is awesome. Paul Dillon then talks about, um, IDs Avery at 1 59. And then our friends to, um, talks about interview Simon Crosby. I think I think that's it. I think we're going on to our next session. All right, so keep it right there. Thanks for watching the Cuban cloud. Uh huh.

>> Announcer: From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a Cube Conversation. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're in our Palo Alto Studios today, having a Cube Conversation, you know, with the COVID situation going on we've had to change our business and go pretty much 100% digital. And as part of that process, we wanted to reach out to our community, and talk to some of the leaders out there, because I think leadership in troubling times is even more amplified in it's importance. So we're excited to be joined today by two leaders in our community. First one being John Chambers, a very familiar face from many, many years at Cisco, who's now the founder and CEO of JC2 Ventures. John, great to see you. >> Jeff, it's a pleasure to be with you again. >> Absolutely. And joining him is Umesh Sachdev, he's the co-founder and CEO of Uniphore. First time on theCUBE, Umesh, great to meet you. >> Jeff, thank you for having me, it's great to be with you. >> You as well, and I had one of your great people on the other day, talking about CX, and I think CX is the whole solution. Why did Uber beat cabs, do you want to stand on a corner and raise your hand in the rain? Or do you want to know when the guy's going to come pick you up, in just a couple minutes? So anyway, welcome. So let's jump into it. John, one of your things, that you talked about last time we talked, I think it was in October, wow how the world has changed. >> Yes. >> Is about having a playbook, and really, you know, kind of thinking about what you want to do before it's time to actually do it, and having some type of a script, and some type of direction, and some type of structure, as to how you respond to situations. Well there's nothing like a disaster to really fire off, you know, the need to shift gears, and go to kind of into a playbook mode. So I wonder if you could share with the viewers, kind of what is your playbook, you've been through a couple of these bumps. Not necessarily like COVID-19, but you've seen a couple bumps over your career. >> So it's my pleasure Jeff. What I'll do is kind of outline how I believe you use an innovation playbook on everything from acquisitions, to digitizing a company, to dealing with crisis. Let's focus on the playbook for crisis. You are right, and I'm not talking about my age, (John laughing) but this is my sixth financial crisis, and been through the late 1990s with the Asian financial crisis, came out of it even stronger at Cisco. Like everybody else we got knocked down in the 2001 tech bubble, came back from it even stronger. Then in 2008, 2009, Great Recession. We came through that one very, very strong, and we saw that one coming. It's my fourth major health crisis. Some of them turned out to be pretty small. I was in Mexico when the bird pandemic hit, with the President of Mexico, when we thought it was going to be terrible. We literally had to cancel the meetings that evening. That's why Cisco built the PLAR Presence. I was in Brazil for the issue with the Zika virus, that never really developed much, and the Olympics went on there, and I only saw one mosquito during the event. It bit me. But what I'm sharing with you is I've seen this movie again and again. And then, with supply chain, which not many people were talking about yet, supply chain crisis, like we saw in Japan with the Tsunami. What's happening this time is you're seeing all three at one time, and they're occurring even faster. So the playbook is pretty simple in crisis management, and then it would be fun to put Umesh on the spot and say how closely did you follow it? Did you agree with issues, or did you disagree, et cetera, on it. Now I won't mention, Umesh, that you've got a review coming up shortly from your board, so that should not affect your answer at all. But the first playbook is being realistic, how much was self-inflicted, how much was market. This one's largely market, but if you had problems before, you got to address them at the same time. The second thing is what are the five to seven things that are material, what you're going to do to lead through this crisis. That's everything from expense management, to cash preservation. It's about how do you interface to your employees, and how do you build on culture. It's about how do you interface to your customers as they change from their top priority being growth and innovation, to a top priority being cost savings, and the ability to really keep their current revenue streams from churning and moving. And it's about literally, how do make your big bets for what you want to look like as you move out of this market. Then it's how do you communicate that to your employees, to your shareholders, to your customers, to your partners. Painting the picture of what you look like as you come out. As basic as that sounds, that's what crisis management is all about. Don't hide, be visible, CEOs should take the role on implementing that playbook. Umesh to you, do you agree? And have fun with it a little bit, I like the give and take. >> I want to see the playbook, do you have it there, just below the camera? (Jeff laughing) >> I have it right here by my side. I will tell you, Jeff, in crisis times and difficult times like these, you count all the things that go right for you, you count your blessings. And one of the blessings that I have, as a CEO, is to have John Chambers as my mentor, by my side, sharing not just the learning that he had through the crisis, but talking through this, with me on a regular basis. I've read John's book more than a few times, I bet more than anybody in the world, I've read it over and over. And that, to me, is preparation going into this mode. One of the things that John has always taught me is when times get difficult, you get calmer than usual. It's one thing that when you're cruising on the freeway and you're asked to put the brakes, but it's quite another when you're in rocket ship, and accelerating, which is what my company situation was in the month of January. We were coming out of a year of 300% growth, we were driving towards another 300% growth, hiring tremendously, at a high pace. Winning customers at a high pace, and then this hit us. And so what I had to do, from a playbook perspective, is, you know, take a deep breath, and just for a couple of days, just slow down, and calmly look at the situation. My first few steps were, I reached out to 15 of our top customers, the CEOs, and give them calls, and said let's just talk about what you're seeing, and what we are observing in our business. We get a sense of where they are in their businesses. We had the benefit, my co-founder works out of Singapore, and runs our Asia business. We had the benefit of picking up the sign probably a month before everyone else did it in the U.S. I was with John in Australia, and I was telling John that "John, something unusual is happening, "a couple of our customers in these countries in Asia "are starting to tell us they would do the deal "a quarter later." And it's one thing when one of them says it, it's another when six of them say it together. And John obviously has seen this movie, he could connect the dots early. He told me to prepare, he told the rest of the portfolio companies that are in his investment group to start preparing. We then went to the playbook that John spoke of, being visible. For me, culture and communication take front seat. We have employees in ten different countries, we have offices, and very quickly, even before the governments mandated, we had all of them work, you know, go work from home, and be remote, because employee safety and health was the number one priority. We did our first virtual all-hands meeting on Zoom. We had about 240 people join in from around the world. And my job as CEO, usually our all-hands meeting were different functional leaders, different people in the group talk to the team about their initiatives. This all-hands was almost entirely run by me, addressing the whole company about what's going to be the situation from my lens, what have we learned. Be very factual. At the same time, communicating to the team that because of the fact that we raised our funding the last year, it was a good amount of money, we still have a lot of that in the bank, so we going to be very secure. At the same time, our customers are probably going to need us more than ever. Call centers are in more demand than ever, people can't walk up to a bank branch, they can't go up to a hospital without taking an appointment. So the first thing everyone is doing is trying to reach call centers. There aren't enough people, and anyways the work force that call centers have around the world, are 50% working from home, so the capacity has dropped. So our responsibility almost, is to step up, and have our AI and automation products available to as many call centers as we can. So as we are planning our own business continuity, and making sure every single employee is safe, the message to my team was we also have to be aggressive and making sure we are more out there, and more available, to our customers, that would also mean business growth for us. But first, and foremost is for us to be responsible citizens, and just make it available where it's needed. As we did that, I quickly went back to my leadership team, and again, the learning from John is usually it's more of a consensus driven approach, we go around the table, talk about a topic for a couple of hours, get the consensus, and move out of the room. My leadership meetings, they have become more frequent, we get together once a week, on video call with my executive leaders, and it's largely these days run by me. I broke down the team into five different war rooms, with different objectives. One of them we called it the preservation, we said one leader, supported by others will take the responsibility of making sure every single employee, their families, and our current customers, are addressed, taken care of. So we made somebody lead that group. Another group was made responsible for growth. Business needs to, you know, in a company that's growing at 300%, and we still have the opportunity, because call centers need us more than ever, we wanted to make sure we are responding to growth, and not just hunkering down, and, you know, ignoring the opportunity. So we had a second war room take care of the growth. And a third war room, lead by the head of finance, to look at all the financial scenarios, do the stress tests, and see if we are going to be ready for any eventuality that's going to come. Because, you know, we have a huge amount of people, who work at Uniphore around the world, and we wanted to make sure their well being is taken care of. So from being over communicative, to the team and customers, and being out there personally, to making sure we break down the teams. We have tremendous talent, and we let different people, set of people, run different set of priorities, and report back to me more frequently. And now, as we have settled into this rhythm, Jeff, you know, as we've been in, at least in the Bay area here, we've been shelter in place for about a month now. As we are in the rhythm, we are beginning to do virtual happy hours, every Thursday evening. Right after this call, I get together with my team with a glass of wine, and we get together, we talk every but work, and every employee, it's not divided by functions, or leadership, and we are getting the rhythm back into the organization. So we've gone and adjusted in the crisis, I would say very well. And the business is just humming along, as we had anticipated, going into this crisis. But I would say, if I didn't have John by my side, if I hadn't read his book, the number of times that I have, every plane ride we've done together, every place we've gone together, John has spoken about war stories. About the 2001, about 2008, and until you face the first one of your own, just like I did right now, you don't appreciate when John says leadership is lonely. But having him by our side makes it easier. >> Well I'm sure he's told you the Jack Welch story, right? That you've quoted before, John, where Jack told you that you're not really a good leader, yet, until you've been tested, right. So you go through some tough stuff, it's not that hard to lead on an upward to the right curve, it's when things get a little challenging that the real leadership shines through. >> Completely agree, and Jack said it the best, we were on our way to becoming the most valuable company in the world, he looked me in the eye and said "John, you have a very good company." And I knew he was about to give me a teaching moment, and I said "What does it take to have a great one?" He said a near death experience. And I thought I did that in '97, and some of the other management, and he said, "No, it's when you went through something "like we went through in 2001, "which many of our peers did die in." And we were knocked down really hard. When we came back from it, you get better. But what you see in Umesh is a very humble, young CEO. I have to remember he's only 34 years old, because his maturity is like he's 50, and he's seen it before. As you tell, he's like a sponge on learning, and he doesn't mind challenging. And what what he didn't say, in his humbleness, is they had the best month in March ever. And again, well over 300% versus the same quarter a year ago. So it shows you, if you're in the right spot, i.e. artificial intelligence, i.e. cost savings, i.e. customer relationship with their customers, how you can grow even during the tough times, and perhaps set a bold vision, based upon facts and a execution plan that very few companies will be able to deliver on today. So off to a great start, and you can see why I'm so honored and proud to be his strategic partner, and his coach. >> Well it's interesting, right, the human toll of this crisis is horrible, and there's a lot of people getting sick, and a lot of people are dying, and all the estimations are a lot more are going to die this month, as hopefully we get over the hump of some of these curves. So that aside, you know, we're here talking kind of more about the, kind of, the business of this thing. And it's really interesting kind of what a catalyst COVID has become, in terms of digital transformation. You know, we've been talking about new ways to work for years, and years, and years, and digital transformation, and all these kind of things. You mentioned the Cisco telepresence was out years, and decades ago. I mean I worked in Mitsubishi, we had a phone camera in 1986, I looked it up today, it was ridiculous, didn't work. But now, it's here, right. Now working from home is here. Umesh mentioned, you know, these huge call centers, now everybody's got to go home. Do they have infrastructure to go home? Do they have a place to work at home? Do they have support to go home? Teachers are now being forced, from K-12, and I know it's a hot topic for you, John, to teach from home. Teach on Zoom, with no time to prep, no time to really think it through. It's just like the kids aren't coming back, we got to learn it. You know I think this is such a transformational moment, and to your point, if this goes on for weeks, and weeks, and months, and months, which I think we all are in agreement that it will. I think you said, John, you know, many, many quarters. As people get new habits, and get into this new flow, I don't think they're going to go back back to the old ways. So I think it's a real, you know, kind of forcing function for digital transformation. And it's, you can't, you can't sit on the sidelines, cause your people can't come to the office anymore. >> So you've raised a number of questions, and I'll let Umesh handle the tough part of it. I will answer the easy part, which is I think this is the new normal. And I think it's here now, and the question is are you ready for it. And as you think about what we're really saying is the video sessions will become such an integral part of our daily lives, that we will not go back to having to do 90% of our work physically. Today alone I've done seven major group meetings, on Zoom, and Google Hangouts, and Cisco Webex. I've done six meetings with individuals, or the key CEOs of my portfolio. So that part is here to stay. Now what's going to be fascinating is does that also lead into digitization of our company, or do the companies make the mistake of saying I'm going to use this piece, because it's so obvious, and I get it, in terms of effectiveness, but I'm not going to change the other things in my normal work, in my normal business. This is why, unfortunately, I think you will see, we originally said, Jeff, you remember, 40% maybe as high as 45% of the Fortune 500 wouldn't exist in a decade. And perhaps 70% of the start-ups wouldn't exist in a decade, that are venture capital backed. I now think, unfortunately, you're going to see 20-35% of the start-ups not exist in 2 years, and I think it's going to shock you with the number of Fortune 500 companies that do not make this transition. So where you're leading this, that I completely agree with, is the ability to take this terrible event, with all of the issues, and again thank our healthcare workers for what they've been able to do to help so many people, and deal with the world the way it is. As my parents who are doctors taught me to do, not the way we wish it was. And then get your facts, prepare for the changes, and get ready for the future. The key would be how many companies do this. On the area Umesh has responsibility for, customer experience, I think you're going to see almost all companies focus on that. So it can be an example of perhaps how large companies learn to use the new technology, not just video capability, but AI, assistance for the agents, and then once they get the feel for it, just like we got the feel for these meetings, change their rhythm entirely. It was a dinner in New York, virtually, when we stopped, six weeks ago, traveling, that was supposed to be a bunch of board meetings, customer meetings, that was easy. But we were supposed to have a dinner with Shake Shack's CEO, and we were supposed to have him come out and show how he does cool innovation. We had a bunch of enterprise companies, and a bunch of media, and subject matter expertise, we ended up canceling it, and then we said why not do it virtually? And to your point, we did it in 24 different locations. Half the people, remember six weeks ago, had never even used Zoom. We had milk shakes, and hamburgers, and french fries delivered to their home. And it was one of the best two hour meetings I've seen. The future is this now. It's going to change dramatically, and Umesh, I think, is going to be at the front edge of how enterprise companies understand how their relationship with their customers is going to completely transform, using AI, conversational AI capability, speech recognition, et cetera. >> Yeah, I mean, Umesh, we haven't even really got into Uniphore, or what you guys are all about. But, you know, you're supporting call centers, you're using natural language technology, both on the inbound and all that, give us the overview, but you're playing on so many kind of innovation spaces, you know, the main interaction now with customers, and a brand, is either through the mobile phone, or through a call center, right. And that's becoming more, and increasingly, digitized. The ability to have a voice interaction, with a machine. Fascinating, and really, I think, revolutionary, and kind of taking, you know, getting us away from these stupid qwerty keyboards, which are supposed to slow us down on purpose. It's still the funniest thing ever, that we're still using these qwerty keyboards. So I wonder if you can share with us a little bit about, you know, kind of your vision of natural language, and how that changes the interaction with people, and machines. I think your TED Talk was really powerful, and I couldn't help but think of, you know, kind of mobile versus land lines, in terms of transformation. Transforming telecommunications in rural, and hard to serve areas, and then actually then adding the AI piece, to not only make it better for the front end person, but actually make it for the person servicing the account. >> Absolutely Jeff, so Uniphore, the company that I founded in 2008. We were talking about it's such a coincidence that I founded the company in 2008, the year of the Great Recession, and here we are again, talking in midst of the impact that we all have because of COVID. Uniphore does artificial intelligence and automation products, for the customer service industry. Call centers, as we know it, have fundamentally, for the last 20, 30 years, not have had a major technology disruption. We've seen a couple of ways of business model disruption, where call centers, you know, started to become offshore, in locations in Asia, India, and Mexico. Where our calls started to get routed around the world internationally, but fundamentally, the core technology in call centers, up until very recently, hadn't seen a major shift. With artificial intelligence, with natural language processings, speech recognition, available in over 100 languages. And, you know, in the last year or so, automation, and RPA, sort of adding to that mix, there's a whole new opportunity to re-think what customer service will mean to us, more in the future. As I think about the next five to seven years, with 5G happening, with 15 billion connected devices, you know, my five year old daughter, she the first thing she does when she enters the house from a playground, she goes to talk to her friend called Alexa. She speaks to Alexa. So, you know, these next generation of users, and technology users will grow up with AI, and voice, and NLP, all around us. And so their expectation of customer service and customer experience is going to be quantum times higher than some of us have, from our brands. I mean, today when a microwave or a TV doesn't work in our homes, our instinct could be to either go to the website of the brand, and try to do a chat with the agent, or do an 800 number phone call, and get them to visit the house to fix the TV. With, like I said with 5G, with TV, and microwave, and refrigerator becoming intelligent devices, you know, I could totally see my daughter telling the microwave "Why aren't you working?" And, you know, that question might still get routed to a remote contact center. Now the whole concept of contact center, the word has center in it, which means, in the past, we used to have these physical, massive locations, where people used to come in and put on their headsets to receive calls. Like John said, more than ever, we will see these centers become dispersed, and virtual. The channels with which these queries will come in would no more be just a phone, it would be the microwave, the car, the fridge. And the receivers of these calls would be anywhere in the world, sitting in their home, or sitting on a holiday in the Himalayas, and answering these situations to us. You know, I was reading, just for everyone to realize how drastic this shift has been, for the customer service industry. There are over 14 million workers, who work in contact centers around the world. Like I said, the word center means something here. All of them, right now, are working remote. This industry was never designed to work remote. Enterprises who fundamentally didn't plan for this. To your point Jeff, who thought digitization or automation, was a project they could have picked next year, or they were sitting on the fence, will now know more have a choice to make this adjustment. There's a report by a top analyst firm that said by 2023, up to 30% of customer service representatives would be remote. Well guess what, we just way blew past that number right away. And most of the CEOs that I talked to recently tell me that now that this shift has happened, about 40% of their workers will probably never return back to the office. They will always remain a permanent virtual workforce. Now when the workforce is remote, you need all the tools and technology, and AI, that A, if on any given day, 7-10% of your workforce calls in sick, you need bots, like the Amazon's Alexa, taking over a full conversation. Uniphore has a product called Akira, which does that in call centers. Most often, when these call center workers are talking, we have the experience of being put on hold, because call center workers have to type in something on their keyboard, and take notes. Well guess what, today AI and automation can assist them in doing that, making the call shorter, allowing the call center workers to take a lot more calls in the same time frame. And I don't know your experience, but, you know, a couple of weekends ago, the modem in my house wasn't working. I had a seven hour wait time to my service provider. Seven hour. I started calling at 8:30, it was somewhere around 3-4:00, finally, after call backs, wait, call back, wait, that it finally got resolved. It was just a small thing, I just couldn't get to the representative. So the enterprises are truly struggling, technology can help. They weren't designed to go remote, think about it, some of the unique challenges that I've heard now, from my customers, is that how do I know that my call center representative, who I've trained over years to be so nice, and empathetic, when they take a pee break, or a bio break, they don't get their 10 year old son to attend a call. How do I know that? Because now I can no more physically check in on them. How do I know that if I'm a bank, there's compliance? There's nothing being said that isn't being, is, you know, supposed to be said, because in a center, in an office, a supervisor can listen in. When everyone's remote, you can't do that. So AI, automation, monitoring, supporting, aiding human beings to take calls much better, and drive automation, as well as AI take over parts of a complete call, by the way of being a bot like Alexa, are sort of the things that Uniphore does, and I just feel that this is a permanent shift that we are seeing. While it's happening because of a terrible reason, the virus, that's affecting human beings, but the shift in business and behavior, is going to be permanent in this industry. >> Yeah, I think so, you know it's funny, I had Marten Mickos on, or excuse me, yeah, Marten Mickos, as part of this series. And I asked him, he's been doing distributed companies since he was doing MySQL, before Sun bought them. And he's, he was funny, it's like actually easier to fake it in an office, than when you're at home, because at home all you have to show is your deliverables. You can't look busy, you can't be going to meetings, you can't be doing things at your computer. All you have to show is your output. He said it's actually much more efficient, and it drives people, you know, to manage to the output, manage to what you want. But I want to shift gears a little bit, before we let you go, and really talk a little bit about the role of government. And John, I know you've been very involved with the Indian government, and the French government, trying to help them, in their kind of entrepreneurial pursuits, and Uniphore, I think, was founded in India, right, before you moved over here. You know we've got this huge stimulus package coming from the U.S. government, to try to help, as people, you know, can't pay their mortgage, a lot of people aren't so fortunate to be in digital businesses. It's two trillion dollars, so as kind of a thought experiment, I'm like well how much is two trillion dollars? And I did the cash balance of the FAANG companies. Facebook, Apple, Amazon, Netflix, and Alphabet, just looking at Yahoo Finance, the latest one that was there. It's 333 billion, compared to two trillion. Even when you add Microsoft's 133 billion on top, it's still shy, it's still shy of 500 billion. You know, and really, the federal government is really the only people in a position to make kind of sweeping, these types of investments. But should we be scared? Should we be worried about, you know, kind of this big shift in control? And should, do you think these companies with these big balance sheets, as you said John, priorities change a little bit. Should it be, keep that money to pay the people, so that they can stay employed and pay their mortgage, and go buy groceries, and maybe get take out from their favorite restaurant, versus, you know, kind of what we've seen in the past, where there's a lot more, you know, stock buy backs, and kind of other uses of these cash. As you said, if it's a crisis, and you got to cut to survive, you got to do that. But clearly some of these other companies are not in that position. >> So you, let me break it into two pieces, Jeff, if I may. The first is for the first time in my lifetime I have seen the federal government and federal agencies move very rapidly. And if you would have told me government could move with the speed we've seen over the last three months, I would have said probably not. The fed was ahead of both the initial interest rate cuts, and the fed was ahead in terms of the slowing down, i.e. your 2 trillion discussion, by central banks here, and around the world. But right behind it was the Treasury, which put on 4 trillion on top of that. And only governments can move in this way, but the coordination with government and businesses, and the citizens, has been remarkable. And the citizens being willing to shelter in place. To your question about India, Prime Minister Modi spent the last five years digitizing his country. And he put in place the most bandwidth of any country in the world, and literally did transformation of the currency to a virtual currency, so that people could get paid online, et cetera, within it. He then looked at start-ups and job creation, and he positioned this when an opportunity or problem came along, to be able to perhaps navigate through it in a way that other countries might struggle. I would argue President Macron in France is doing a remarkable job with his innovation economy, but also saying how do you preserve jobs. So you suddenly see government doing something that no business can do, with the scale, and the speed, and a equal approach. But at the same time, may of these companies, and being very candid, that some people might have associated with tech for good, or with tech for challenges, have been unbelievably generous in giving both from the CEOs pockets perspective, and number two and three founders perspective, as well as a company giving to the CDC, and giving to people to help create jobs. So I actually like this opportunity for tech to regain its image of being good for everybody in the world, and leadership within the world. And I think it's a unique opportunity. For my start-ups, I've been so proud, Jeff. I didn't have to tell them to go do the right thing with their employees, I didn't have to tell them that you got to treat people, human lives first, the economy second, but we can do both in parallel. And you saw companies like Sprinklr suddenly say how can I help the World Health Organization anticipate through social media, where the next spread of the virus is going to be? A company, like Bloom Energy, with what KR did there, rebuilding all of the ventilators that were broken here in California, of which about 40% were, out of the stock that they got, because it had been in storage for so long, and doing it for all of California in their manufacturing plant, at cost. A company like Aspire Foods, a cricket company down in Texas, who does 3D capabilities, taking part of their production in 3D, and saying how many thousand masks can I generate, per week, using 3D printers. You watch what Umesh has done, and how he literally is changing peoples lives, and making that experience, instead of being a negative from working at home, perhaps to a positive, and increasing the customer loyalty in the process, as opposed to when you got a seven hour wait time on a line. Not only are you probably not going to order anything else from that company, you're probably going to change it. So what is fascinating to me is I believe companies owe an obligation to be successful, to their employees, and to their shareholders, but also to give back to society. And it's one of the things I'm most proud about the portfolio companies that I'm a part of, and why I'm so proud of what Umesh is doing, in both a economically successful environment, but really giving back and making a difference. >> Yeah, I mean, there's again, there's all the doctor stuff, and the medical stuff, which I'm not qualified to really talk about. Thankfully we have good professionals that have the data, and the knowledge, and know what to do, and got out ahead of the social distancing, et cetera, but on the backside, it really looks like a big data problem in so many ways, right. And now we have massive amounts of compute at places like Amazon, and Google, and we have all types of machine learning and AI to figure out, you know, there's kind of resource allocation, whether that be hospital beds, or ventilators, or doctors, or nurses, and trying to figure out how to sort that all out. But then all of the, you know, genome work, and you know, kind of all that big heavy lifting data crunching, you know, CPU consuming work, that hopefully is accelerating the vaccine. Because I don't know how we get all the way out of this until, it just seems like kind of race to the vaccine, or massive testing, so we know that it's not going to spike up. So it seems like there is a real opportunity, it's not necessarily Kaiser building ships, or Ford building planes, but there is a role for tech to play in trying to combat this thing, and bring it under control. Umesh, I wonder if you could just kind of contrast being from India, and now being in the States for a couple years. Anything kind of jump out to you, in terms of the differences in what you're hearing back home, in the way this has been handled? >> You know, it's been very interesting, Jeff, I'm sure everyone is concerned that India, for many reasons, so far hasn't become a big hot spot yet. And, you know, we can hope and pray that that remains to be the case. There are many things that the government back home has done, I think India took lessons from what they saw in Europe, and the U.S, and China. They went into a countrywide lockdown pretty early, you know, pretty much when they were lower than a two hundred positive tested cases, the country went into lockdown. And remember this is a 1.5 billion people all together going into lockdown. What I've seen in the U.S. is that, you know, California thankfully reacted fast. We've all been sheltered in place, there's cabin fever for all of us, but you know, I'm sure at the end of the day, we're going to be thankful for the steps that are taken. Both by the administration at the state level, at the federal level, and the medical doctors, who are doing everything they can. But India, on the other hand, has taken the more aggressive stance, in terms of doing a country lockdown. We just last evening went live at a University in the city of Chennai, where Uniphore was born. The government came out with the request, much like the U.S., where they're government departments were getting a surge of traffic about information about COVID, the hospitals that are serving, what beds are available, where is the testing? We stood up a voice bot with AI, in less than a week, in three languages. Which even before the government started to advertise, we started to get thousands of calls. And this is AI answering these questions for the citizens, in doing so. So it goes back to your point of there's a real opportunity of using all the technology that the world has today, to be put to good use. And at the same time, it's really partnering meaningfully with government, in India, in Singapore, in Vietnam, and here in the U.S., to make sure that happens on, you know, John's coaching and nudging, I became a part of the U.S.-India Strategic Partnership Forum, which is truly a premier trade and commerce body between U.S. and India. And I, today, co-chaired the start-up program with, you know, the top start-ups between U.S. and India, being part of that program. And I think we got, again, tremendously fortunate, and lucky with the timeline. We started working on this start-up program between U.S. and India, and getting the start-ups together, two quarters ago, and as this new regulation with the government support, and the news about the two trillion dollar packages coming out, and the support for small businesses, we could quickly get some of the questions answered for the start-ups. Had we not created this body, which had the ability to poll the Treasury Department, and say here are questions, can start-ups do A, B, and C? What do you have by way of regulation? And I think as a response to one of our letters, on Monday the Treasury put out an FAQ on their website, which makes it super clear for start-ups and small businesses, to figure out whether they qualify or they don't qualify. So I think there's ton that both from a individual company, and the technology that each one of us have, but also as a community, how do we, all of us, meaningfully get together, as a community, and just drive benefit, both for our people, for the economy, and for our countries. Wherever we have the businesses, like I said in the U.S., or in India, or parts of Asia. >> Yeah, it's interesting. So, this is a great conversation, I could talk to you guys all night long, but I probably would hear about it later, so we'll wrap it, but I just want to kind of close on the following thought, which is really, as you've talked about before John, and as Umesh as you're now living, you know, when we go through these disruptions, things do get changed, and as you said a lot of people, and companies don't get through it. On the other hand many companies are birthed from it, right, people that are kind of on the new trend, and are in a good position to take advantage, and it's not that you're laughing over the people that didn't make it, but it does stir up the pot, and it sounds like, Umesh, you're in a really good position to take advantage of this new kind of virtual world, this new digital transformation, that's just now waiting anymore. I love your stat, they were going to move X% out of the call center over some period of time, and then it's basically snap your fingers, everybody out, without much planning. So just give you the final word, you know, kind of advice for people, as they're looking forward, and Umesh, we'll get you on another time, because I want to go deep diving in natural language, I think that's just a fascinating topic in the way that people are going to interact with machines and get rid of the stupid qwerty keyboard. But let me get kind of your last thoughts as we wrap this segment. Umesh we'll let you go first. >> Umesh, you want to go first? >> I'll go first. My last thoughts are first for the entrepreneurs, everyone who's sort of going through this together. I think in difficult times is when real heroes are born. I read a quote that when it's a sunny day, you can't overtake too many cars, but when it's raining you have a real opportunity. And the other one that I read was when fishermen can't go out fishing, because of the high tide, they come back, and mend their nets, and be ready for the time that they can go out. So I think there's no easy way to say, this is a difficult time for the economy, health wise, I hope that, you know, we can contain the damage that's being done through the virus, but some of us have the opportunity to really take our products and technology out there, more than usual. Uniphore, particularly, has a unique opportunity, the contact center industry just cannot keep up with the traffic that it's seeing. Around the world, across US, across Asia, across India, and the need for AI and automation would never be pronounced more than it is today. As much as it's a great business opportunity, it's more of a responsibility, as I see it. There can be scale up as fast as the demand is coming, and really come out of this with a much stronger business model. John has always told me in final words you always paint the picture of what you want to be, a year or two out. And I see Uniphore being a much stronger AI plus automation company, in the customer service space, really transforming the face of call centers, and customer service. Which have been forced to rethink their core business value in the last few weeks. And, you know, every fence sitter who would think that digitalization and automation was an option that they could think of in the future years, would be forced to make those decisions now. And I'm just making sure that my team, and my company, and I, am ready to gear to that great responsibility and opportunity that's ahead of us. >> John, give you the final word. >> Say Jeff, I don't know if you can still hear me, we went blank there, maybe for me to follow up. >> We gotcha. >> Shimon Peres taught me a lot about life, and dealing with life the way it is, not the way you wish it was. So did my parents, but he also taught me it always looks darkest just before the tide switches, and you move on to victory. I think the challenges in front of us are huge, I think our nation knows how to deal with that, I do believe the government has moved largely pretty effectively, to give us the impetus to move, and then if we continue to flatten the curve on the issues with the pandemic, if we get some therapeutic drugs that dramatically reduce the risk of death, for people that get the challenges the worst, and over time a vaccine, I think you look to the future, America will rebound, it will be rebounding around start-ups, new job creation, using technology in every business. So not only is there a light at the tunnel, at the end of the tunnel, I think we will emerge from this a stronger nation, a stronger start-up community. But it depends on how well we work together as a group, and I just want to say to Umesh, it's an honor to be your coach, and I learn from you as much as I give back. Jeff, as always, you do a great job. Thank you for your time today. >> Thank you both, and I look forward to our next catch up. Stay safe, wash your hands, and thanks for spending some time with us. >> And I just want to say I hope and pray that all of us can get together in Palo Alto real quick, and in person, and doing fist bumps, not shake hands or probably a namaste. Thank you, it's an honor. >> Thank you very much. All right, that was John and Umesh, you're watching theCUBE from our Palo Alto Studios, thanks for tuning in, stay safe, wash your hands, keep away from people that you're not that familiar with, and we'll see you next time. Thanks for watching. (calm music)

>>From Las Vegas. It's the cube covering Qualis security conference 2019 you buy quality. >>Hey, welcome back. You're ready. Jeff Frick here with the cube. We're in Las Vegas at the Bellagio, at the quality security conference. It's the 19th year they've been doing this. It's our first year here and we're excited to be here and it's great to have a veteran who's been in this space for so long, to give a little bit more of a historical perspective as to what happened in the past and where we are now and what can we look forward to in the future. So coming right off his keynote is Felipe korto, the chairman and CEO of Qualys. Phillip, great to see you. Thank you. Same, same, same for me. Absolutely. So you touched on so many great, um, topics in your conversation about kind of the shifts of, of, of modern computing from the mainframe to the mini. We've heard it over and over and over, but the key message was really about architecture. If you don't have the right architecture, you can't have the right solution. So how has the evolution of architects of architectures impacted your ability to deliver security solutions for your clients? >>So now that's a very good question. And in fact, you know, what happened is that we started in 1999 with a vision that we could use exactly like a salesforce.com this nascent internet technologies and apply that to security. And uh, so, and mod when you have applied that to essentially changing the way CRM was essentially used and deployed in enterprises and with a fantastic success as we know. So for us, the, I can say today that 19 years later the vision was right. It took a significant longer because the security people are not really, uh, warm at the idea of silently, uh, having the data in their view, which was in place that they could not control. And the it people, they didn't really like at all the fact that suddenly they were not in control anymore of the infrastructure. So we had a lot of resistance. >>I, wherever we always, I always believe, absolutely believe that the, the cloud will be the cloud architecture to go back. A lot of people make the confusion. That was part of the confusion that for people it was a cloud, that kind of magical things someplace would you don't know where. And when I were trying to explain, and I've been saying that so many times that well you need to look at the cloud like compute that can architecture which distribute the competing power far more efficiently than the previous one, which was client server, which was distributing the convening power far better than of course the mainframes and the mini computers. And so if you look at their architectures, so the mainframe were essentially big data centers in uh, in Fort Knox, like settings, uh, private lines of communication to a dump terminal. And of course security was not really issue then because it's security was built in by the IBM's and company. >>Same thing with the mini computer, which then was instead of just providing the computing power to the large, very large company, you could afford it. Nelson and the minicomputer through the advanced in semiconductor technology could reduce a foot Frank. And then they'll bring that computing power to the labs and to the departments. And was then the new era of the digital equipment, the prime, the data general, et cetera. Uh, and then kind of server came in. So what client server did, again, if you look at the architecture, different architecture now silently servers, the land or the internal network and the PC, and that was now allowing to distribute the computing power to the people in the company. And so, but then you needed to, so everybody, nobody paid attention to security because then you were inside of the enterprise. So it started inside the walls of the castle if you prefer. >>So nobody paid attention to that. It was more complex because now you have multiple actors. Instead of having one IBM or one digital equipment, et cetera, suddenly you have the people in manufacturing and the servers, the software, the database, the PCs, and on announcer, suddenly there was the complexity, increasing efficiency, but nobody paid attention to security because it wasn't a needed until suddenly we realized that viruses could come in through the front door being installed innocently. You were absolutely, absolutely compromised. And of course that's the era of the antivirus which came in. And then because of the need to communicate more and more now, Senator, you could not stay only in your castle. You needed to go and communicate to your customers, to your suppliers, et cetera, et cetera. And now he was starting to open up your, your castle to the world and hello so now so that the, the bad guy could come in and start to steal your information. >>And that was the new era of the forward. Now you make sure that those who come in, but of course that was a little bit naive because there were so many other doors and windows, uh, that people could come in, you know, create tunnels and create these and all of that trying to ensure your customers because the data was becoming more and more rich and more, more important or more value. So whenever there is a value, of course the bad guys are coming in to try to sell it. And that was that new era of a willing to pay attention to security. The problem has been is because you have so many different actors, there was nothing really central there that was just selling more and more solutions and no, absolutely like 800 vendors bolting on security, right? And boating on anything is short-lived at the end of the day because you put more and more weight and then you also increase the complexity and all these different solutions you need. >>They need to talk together so you have a better context. Uh, but they want the design to talk together. So now you need to put other system where they could communicate that information. So you complicated and complicated and complicated the solution. And that's the problem of today. So now cloud computing comes in and again, if you look at the architecture of cloud computing, it's again data centers, which is not today I've become thanks to the technology having infinite, almost competing power and storage capabilities. And like the previous that I sent her, the are much more fractured because you just one scale and they become essentially a little bit easier to secure. And by the way, it's your fewer vendors now doing that. And then of course the access can be controlled better. Uh, and then of course the second component is not the land and the one, it's now the internet. >>And the internet of course is the web communications extremely cheap and it brings you an every place on the planet and soon in Morris, why not? So and so. Now the issue today is that still the internet needs to be secure. And today, how are we going to secure the internet? Which is very important thing today because you see today that you can spoof your email, you can spoof your website, uh, you can attack the DNS who, yes, there's a lot of things that the bad guys still do. And in fact, they've said that leverage the internet of course, to access everywhere so they take advantage of it. So now this is obviously, you know, I created the, the trustworthy movement many years ago to try to really address that. Unfortunately, the quality's was too small and it was not really our place today. There's all the Google, the Facebook, the big guys, which in fact their business depend on the internet. >>Now need to do that. And I upload or be diabetic, criticized very much so. Google was the first one to essentially have a big initiative, was trying to push SSL, which everybody understand is secret encryption if you prefer. And to everybody. So they did a fantastic job. They really push it. So now today's society is becoming like, okay, as I said, you want to have, as I said it all in your communication, but that's not enough. And now they are pushing and some people criticize them and I absolutely applaud them to say we need to change the internet protocols which were created at a time when security, you were transferring information from universities and so forth. This was the hay days, you know, of everything was fine. There was no bad guys, you know, the, he'd be days, if you like, of the internet. Everybody was free, everybody was up and fantastic. >>Okay. And now of course, today this protocol needs to be upgraded, which is a lot of work. But today I really believe that if you put Google, Amazon, Facebook altogether, and they can fix these internet protocols. So we could forget about the spoofing and who forgot about all these phishing and all these things. But this is their responsibility. So, and then you have now on the other side, you have now very intelligent devices from in a very simple sensors and you know, to sophisticated devices, the phone, that cetera and not more and more and more devices interconnected and for people to understand what is going. So this is the new environment and whether we always believe is that if you adopt an architecture, which is exactly which fits, which is similar, then we could instead of bolting security in, we can now say that the build security in a voting security on, we could build security in. >>And we have been very proud of the work that we've done with Microsoft, which we announced in fact relatively recently, very recently, that in fact our agent technologies now is bundled in Microsoft. So we have built security with Microsoft in. So from a security perspective today, if you go to the Microsoft as your secretly center, you click on the link and now you have the view of your entire Azure environment. Crazier for quality Sagent. You click on a second link and now you have the view of your significant loss posture, crazy of that same quality. Say Sagent and then you click on the third name with us. Nothing to do with quality. It's all Microsoft. You create your playbook and you remediate. So security in this environment has become click, click, click, nothing to install, nothing to update. And the only thing you bring are your policies saying, I don't want to have this kind of measured machine expose on the internet. >>I want, this is what I want. And you can continuously audit in essentially in real time, right? So as you can see, totally different than putting boxes and boxes and so many things and then having to for you. So very big game changer. So the analogy that I want you that I give to people, it's so people don't understand that paradigm shift is already happening in the way we secure our homes. You put sensors everywhere, you have cameras, you have detection for proximity detection. Essentially when somebody tried to enter your home, all that data is continuously pumped up into an incidence restaurant system. And then from your phone, again across the internet, you can change the temperature of your rooms. You can do what you can see the person who knocks on the door. You can see its face, you can open the door, close the door, the garage door, you can do all of that remotely, another medically. >>And then if there's a burglar then in your house to try to raking immediately the incidents or some system called the cops or the far Marsha difficult fire. And that's the new paradigm. So security has to follow that paradigm. And then you have interesting of the problem today that we see with all the current secretly uh, systems, uh, incidents, response system. They have a lot of false positive, false positive and false negative are the enemy really of security. Because if you are forced visited, you cannot automate the response because then you are going to try to respond to something that is not true. So you are, you could create a lot of damage. And the example I give you that today in the, if you leave your dog in your house and if you don't have the ability, the dog will bark, would move. And then the sensors would say intruder alert. >>So that's becomes a false positive. So how do you eliminate that? By having more context, you can eliminate automatically again, this false positives. Like now you take a fingerprint of your dog and of these voice and now the camera and this and the sensors and the voice can pick up and say, Oh, this is my dog. So then of course you eliminate that for solar, right? Right. Now even if another dog managed to enter your home through a window which was open or whatever for soul, you will know her window was up and but you know you cannot necessarily fix it and the dog opens. Then you will know it's a, it's a, it's not sure about, right? So that's what security is evolving such a huge sea of change, which is happening because of all that internet and today companies today, after leveraging new cloud technology, which are coming, there's so much new technology. >>What people understand is where's that technology coming from? How come silently we have, you know, Dockers netics all these solutions today, which are available at almost no cost because it's all open source. So what happened is that, which is unlike the enterprise software, which were more the Oracle et cetera, the manufacturer of that software today is in fact the cloud public cloud vendors, the Amazon, the Google, the Facebook, the Microsoft. We suddenly needed to have to develop new technology so they could scale at the size of the planet. And then very shrewdly realized that effective that technology for me, I'm essentially going to imprison that technology is not going to evolve. And then I need other technologies that are not developing. So they realized that they totally changed that open source movement, which in the early days of opensource was more controlled by people who had more purity. >>If you prefer no commercial interests, it was all for the good of the civilization and humankind. And they say their licensing model was very complex. So they simplified all of that. And then nothing until you had all this technology coming at you extremely fast. And we have leverage that technology, which was not existing in the early days when when socials.com started with the Linux lamp pour called what's called Linux Apache. My SQL and PHP, a little bit limiting, but now suddenly all this technology, that classic search was coming, we today in our backend, 3 trillion data points on elastic search clusters and we return inflammation in a hundred milliseconds. And then onto the calf cabin, which is again something at open source. We, we, we, and now today 5 million messages a day and on and on and on. So the world is changing and of course, if that's what it's called now, the digital transformation. >>So now enterprises to be essentially agile, to reach out to the customers better and more, they need to embrace the cloud as the way they do, retool their entire it infrastructure. And essentially it's a huge sea of change. And that's what we see even the market of security just to finish, uh, now evolving in a totally different ways than the way it has been, which in the past, the market of security was essentially the market for the enterprise. And I'm bringing you my, my board, my board town solutions that you have to go and install and make work, right? And then you had the, the antivirus essentially, uh, for all the consumers and so forth. So today when we see the marketplace, which is fragmenting in four different segments, which is one is the large enterprise which are going to essentially consolidate those stock, move into the digital transformation, leveraging absolutely dev ops, which isn't becoming the new buyer and of course a soak or they could improve, uh, their it for, to reach out to more customers and more effectively than the cloud providers as I mentioned earlier, which are building security in the, no few use them. >>You don't have to worry about infrastructure, about our mini servers. You need, I mean it is, it's all done for you. And same thing about security, right? The third market is going to be an emergence of a new generation of managed security service providers, which are going to take to all these companies. We don't have enough resources. Okay, don't worry, I'm going to help you, you know, do all that digital transformation. And that if you build a security and then there's a totally new market of all these devices, including the phone, et cetera, which connects and that you essentially want to all these like OT and IOT devices that are all now connected, which of course presents security risk. So you need to also secure them, but you also need to be able to also not only check their edits to make sure that, okay, because you cannot send people anymore. >>So you need to automate the same thing on security. If you find that that phone is compromised, you need to make, to be able to make immediate decisions about should I kill that phone, right? Destroyed everything in it. Should I know don't let that phone connect anymore to my networks. What should I do? Should I, by the way detected that they've downloaded the application, which are not allowed? Because what we see is more and more companies now are giving tablets, do the users. And in doing so now today's the company property. So they could say, okay, you use these tablets and uh, you're not allowed to do this app. So you could check all of that and then automatically remote. But that again requires a full visibility on what you are. And that's why just to finish, we make a big decision about a few, three months ago that we have, we build the ability for any company on the planet to automatically build their entire global HSE inventory, which nobody knows what they have in that old networking environment. >>You don't know what connects to have the view of the known and the unknown, totally free of charge, uh, across on premise and pawn cloud containers, uh, uh, uh, whether vacations, uh, OT and IOT devices to come. So now there's the cornerstone of security. So with that totally free. So, and then of course we have all these additional solutions and we're build a very scalable, uh, up in platform where we can take data in, pass out data as well. So we really need to be and want to be good citizen here because security at the end of the day, it's almost like we used to say like the doctors, you have to have that kind of apricot oath that you cannot do no arm. So if you keep, if you try to take the data that you have, keep it with you, that's absolutely not right because it's the data of your customers, right? >>So, and you have to make sure that it's there. So you have to be a good warning of the data, but you have to make sure that the customer can absolutely take that data to whatever he wants with it, whatever he needs to do. So that's the kind of totally new field as a fee. And finally today there is a new Ash culture change, which is, which is happening now in the companies, is that security has become fronted centers, is becoming now because of GDPR, which has a huge of financial could over you challenge an impact on a company. A data breach can have a huge financial impact. Security has become a board level. More and more social security is changing and now it's almost like companies, if they want to be successful in the future, they need to embrace a culture of security. And now what I used to say, and that was the, the conclusion of my talk is that now, today it DevOps, uh, security compliance, people need to unite. Not anymore. The silos. I do that. This is my, my turf, my servers. You do that, you do this. Everybody in the company can work. I have to work together towards that goal. And the vendors need to also start to inter operate as well and working with our customers. So it's a tall, new mindset, which is happening, but the safes are big. That's what I'm very confident that we're now into that. Finally, we thought, I thought it would have happened 10 years ago, quite frankly. And uh, but now today's already happening. >>She touched on a lot, a lot there. And I'll speak for another two hours if we could. We could go for Tara, but I want to, I want to unpack a couple of things. We've had James Hamilton on you to at AWS. Um, CTO, super smart guy and it was, it was at one of his talks where it really was kind of a splash, a wet water in the face when he talked about the amount of resources Amazon could deploy to just networking or the amount of PhD power he could put on, you know, any little tiny sub segment of their infrastructure platform where you just realize that you just can't, you can't compete, you cannot put those kinds of resources as an individual company in any bucket. So the inevitability of the cloud model is just, it's, it's the only way to leverage those resources. But because of that, how has, how has that helped you guys change your market? How nice is it for you to be able to leverage infrastructure partners? Like is your bill for go to market as well as feature sets? And also, you know, because the other piece they didn't talk about is the integration of all these things. Now they all work together. Most apps are collection of API APIs. That's also changed. So when you look at the cloud provider GCP as well, how does that help you deliver value to your customers? >>Yeah, but the, the, the, the club, they, they don't do everything. You know, today what is interesting is that the clubs would start to specialize themselves more and more. So for example, if you look at Amazon, the, the core value of Amazon since the beginning has been elastic computing. Uh, now today we should look at Microsoft. They leverage their position and they really have come up with a more enterprise friendly solution. And now Google is trying to find also their way today. And so then you have Addy Baba, et cetera. So these are the public cloud, but life is not uniform like is by nature. Divers life wants to leave lunch to find better ways. We see that that's what we have so many different species and it just ended up. So I've also the other phenomena of companies also building their own cloud as well. >>So the word is entering into a more hybrid cloud. And the technology is evolving very fast as well. And again, I was selling you all these open source software. There's a bigger phenomenon at play, which I used to say that people don't really understand that much wood, but it's so obvious is if you look at the printing price, that's another example that gives the printing price essentially allowed, as we all know, to distribute the gospel, which has some advantage of, you know, creating more morality, et cetera. But then what people don't know for the most part, it distributed the treaties of the Arabs on technology, the scientif treaties, because the archives, which were very thriving civilization at the time, I'd collected all the, all the, all the information from India, from many other places and from China and from etc. And essentially at the time all of Europe was pretty in the age they really came up and it now certainty that scientific knowledge was distributed and that was in fact the seeds of the industrial revolution, which then you're up cat coats and use that and creating all these different technologies. >>So that confidence of this dimension of electricity and all of that created the industrial revolution seeded by now, today what is happening is that the internet is the new printing press, which now is distributing the knowledge that not to a few millions of people to billions of people. So the rate today of advancing technology is accelerating and it's very difficult. I was mentioning today, we know today that work and working against some quantum computing which are going to totally change things. Of course we don't know exactly how and you have also it's clear that today we could use genetic, uh, the, the, the, if you look at DNA, which stores so much information, so little place that we could have significant more, you know, uh, memory capabilities that lower costs. So we have embarked into absolutely a new world where things are changing. I've got a little girl, which is 12 years old and fundamentally that new generation, especially of girls, not boys, because the boys are still on, you know, at that age. >>Uh, they are very studious. They absorb so much information via YouTube. They are things like a security stream. They are so knowledgeable. And when you look back at history 2000 years plus ago in Greece, you at 95 plus percent of the population slaves. So a few percent could start to think now, today it's totally changed. And the amount of information they can, they learn. And this absolutely amazing. And you know, she, she's, I would tell you the story which has nothing to do with computing, but as a button, the knowledge of, she came to me the few, few weeks ago and she said, Oh daddy, I would like to make my mother more productive. Okay. So I said, Oh, that's her name is Avia, which is the, which is the, the, the either Greece or Zeus weathered here. And so I say, Evie, I, so that's a good idea. >>So how are you going to do it? I mean, our answer, I was flawed, but that is very simple. Just like with, for me, I'm going to ask her to go to YouTube to learn what she needs to learn. Exactly. And she learns, she draws very well. She learns how to draw in YouTube and it's not a gifted, she's a nice, very nice little girl and very small, but all her friends are like that. Right? So we're entering in a word, which thing are changing very, very fast. So the key is adaptation, education and democracy and democratization. Getting more people access to more. Absolutely. It's very, very important. And then kind of this whole dev ops continuous improve that. Not big. That's a very good point that you make because that's exactly today the new buyer today in security and in it is becoming the DevOps shipper. >>Because what? What are these people? There are engineers which suddenly create good code and then they want to of course ship their code and then all these old silos or you need to do these, Oh no, we need to put the new server, we don't have the capacity, et cetera. How is that going to take three months or a month? And then finally they find a way through, again, you know, all the need for scale, which was coming from the Google, from the Facebook and so forth. And by the way, we can shortcut all of that and we can create and we can run out to auto-ship, our code. Guess what are they doing today? They are learning how to secure all of that, right? So again, it's that ability to really learn and move. And today, uh, one of the problem that you alluded to is that, which the Amazon was saying is that their pick there, they have taken a lot of the talent resources in the U S today because of course they pay them extra to me, what? >>Of course they'll attract that talent. And of course there's now people send security. There's not enough people that even in, but guess what? We realized that few years ago in 2007, we'll make a big decision who say, well, never going to be able to attract the right people in the Silicon Valley. And we've started to go to India and we have now 750 people. And Jack Welch used to say, we went to India for the cost and discover the talent. We went to India for the talent and we discover the cost. And there is a huge pool of tenants. So it's like a life wants to continue to leave and now to, there are all these tools to learn, are there, look at the can Academy, which today if you want to go in nuclear physics, you can do that through your phone. So that ability to learn is there. So I think we need just more and more people are coming. So I'm a very optimistic in a way because I think the more we improve our technologies that we look at the progress we're making genetics and so everywhere and that confidence of technology is really creating a new way. >>You know, there's a lot of conversations about a dystopian future and a utopian future with all these technologies and the machines. And you know what? Hollywood has shown us with AI, you're very utopian side, very optimistic on that equation. What gives you, what gives you, you know, kind of that positive feeling insecurity, which traditionally a lot of people would say is just whack a mole. And we're always trying to chase the bad guys. Generally >>speaking, if I'm a topian in in a way. But on the other end, you'd need to realize that unfortunately when you have to technological changes and so forth, it's also create factors. And when you look at this story in Manatee, the same technological advancement that some countries to take to try to take advantage of fathers is not that the word is everything fine and everything peaceful. In fact, Richard Clark was really their kid always saying that, Hey, you know that there is a sinister side to all the internet and so forth. But that's the human evolution. So I believe that we are getting longterm. It's going to. So in the meantime there's a lot of changes and humans don't adapt well to change. And so that's in a way, uh, the big challenge we have. But I think over time we can create a culture of change and that will really help. And I also believe that probably at some point in time we will re-engineer the human race. >>All right, cool. We'll leave it there. That's going to launch a whole nother couple hours. They leave. Congratulations on the event and a great job on your keynote. Thanks for taking a few minutes with us. Alrighty. It's relief. I'm Jeff. You're watching the cube where the Qualice security conference at the Bellagio in Las Vegas. Thanks for watching. We'll see you next time.

>> Boston, Massachusetts. It's the queue covering W T G transformed 2019 Accio by Winslow Technology Group. >> Hi, I'm Stew Minutemen And this is the Cubes. Third year at W. T. G. Transform 2019 which is the Window Technologies Group, Their user conference. Longtime compelling customer, of course. Compelling, bought by Del del Body M. C. So it's now the deli emcee user event and to help me kick off a day of content where we're gonna be talking. Toa some of the W T G executive some of their customers and some of their partners is first time guests on the program. Joe Batista, Who's a Creek and easy chief creative, apologised at Del Technologies. Joe Appreciate you making it all the way in from the suburbs to come here to downtown Boston in the shadow of Fenway. >> It was a long haul this morning with no traffic of 5 30 35 minutes in. >> Yeah, a Zeiss safe for the people. Adele. It's about the distant from Boston Towe where we live as it is to go from Austin to Round Rock. So >> there we go, >> you know, similar types of things. So I have to start create apologised. A song. You know, I did a little bit of reading and, you know, having watched Aquino, it's, you know, sparking that creativity. So I love the idea of it. You've had this title for quite a while since before you Riddell just give us a little bit about background of you know what you do, and you know why you're qualified to do it. >> Well, it was quite a fight. It's a fun brand, but literally. It sits at the nexus of business and technology, and my job's simply is to help it re image the business, because now every company's a technology company. So what does that look like? So I get involved Also, it's a really cool problems, opportunities that customers are facing by re imaging it >> well, it's funny that you say re image, because when I did my history, the oldest thing I found some article from the nineties talking about somebody from Polaroid that that title and I was actually talking to some of the young people in the office there, like everybody's using Polaroids. There's these days, it's cool. It's true. They're doing it. So what's old is new again. You know everything come back together. So luckily, you know our industry. I mean, nothing changes, right? You know, it's the same now as it was 10 years ago, 100 years ago. You know, I'll just go into the factory and pumping things out now. >> Still, you know, I've been a referee a long time, and in the old days we had swim lengths, right? You know, you thought about certain vendors. They were in swim lanes. Now, today, with the influx of cash, as I was talking about, and the level of it of even innovation cycle time and how the industry's become more fragmented with lots of products, the complexity index has increased exponentially, and the velocity around that complexity is even more accelerate. So, no, it hasn't gotten easier. It's gotten more difficult. >> Yeah, fascinating. Actually. I just heard a segment on our national public radio station here in Boston talking about that. One of the biggest changes and how people think over the last few decades is we're better at recognizing patterns. Used to be, we could be an expert on something and do our thing, you know. We know the old trope is well, you know. My grandfather, you know, worked at a company for 30 years and did his same thing today. Things are changing constantly. You know, we didn't have, you know, the power of a supercomputer in our pocket, you know, 10 years ago, you know, let alone even older. So, you know, this is a user conference. So you know what air they did do. I mean, if if I understand, if I'm, you know, making a decision today for my business. And oftentimes that decision is something I need to live with for a while. How do I make sure that I'm making the right decisions That's going to keep me, you know, you know, keeping up with the competition and keeping my business moving forward as things constantly change. >> Yeah. So there is no easy answer to that question. There's a couple of thoughts and hasn't said in the presentation. You gotta look at these vectors that impacted trajectory of the thinking. And I love the Peter Drucker coat. Right. If he using yesterday's logic probably gonna get in trouble, you have to rethink the logic. In the example I gave you was the high jumper and how we did high jumping before and after 1960. So? So the question becomes one of those vectors, and I went through some of those vectors to help people think about, Okay, I do. My analysis on technology, that's all good. And, uh, tell technology you got a huge portfolio of technology. But how do you think about the perimeter? About how those things change over depreciation cycle. So is trying to add a little bit more color in there, thought processes. And I got a lot of post questions afterwards and a lot of engagements. So it seemed to resonate with the field. And I'll tell you what. The thing that they like the most was the business conversation off. They're like, you know, we don't do that enough. >> Yeah, right. I mean, you know, when we look at the successful companies today, it is not, You know, we've been talking for years, you know? Does it matter? Is it just a cost center? And it needs to be if it isn't helping the business drive forward and responding to what the business needs, uh, you know, could be replaced. That's where we got. Shadow it. It's It can't be the nowhere the slow needs to be. When the business says we need to go, you know, get on board and drive. I love one of the analogies you used is, you know, in this world of complexity, there's so many things out there, You know, when I've worked with, you know, enterprises and small cos you look at their environments and it's like, Oh my God, it's this Hedorah genius mess, you know? How do we standardize things? How do we make things easier? You had a fun little analogy talking about space. Maybe, maybe. >> Okay, that was good. I always try to use visuals as much as possible. So high, high, high light with challenges. So the challenge was, Oh, actually have it in my pocket. So they pulled this out and basically what it is. If you look at the international space shuttle, that's the only thing that they need to fix anything on Specialist 7/16 inch socket or the millimeter version of it. I can't read. Excited my glasses on to fix anything. So imagine if I had one tool to fix anything that's Nirvana. That's not reality. I have to fatigue. So I need to get to that simplicity. Its glasses law remember, every 25% increase in function shin is 100% increase in complexity. And that's public enemy number one for us. >> All right, so So you hopped on board the Dell family relatively recently, when most people think, Adele, it's well, you know, Delpy sees, you know, talk to my you know, my parents. They're like they know Dell computers. They've used them forever. You're talking most people, you know, Del servant. Like you talked a lot about your presentation software is eating the world. Give give us how you know where Del fits in that software was eating the world picture. >> Well, what I can tell you, though, is I was absolutely amazed when I did my due diligence about all the innovation that happens in this company. Phenomenal not only about the hardware but the soft. And I think actually, Jeff said it best. I think we have more software engineers now that we have heart hardware engineers. So the pivots there, we're pivoting our talent, the software, but it's the innovation that's in this company. And I think I kind of rattled off a couple of statistics by how much we spend the quantity of I p that we have. And I think customers are amazed at that innovation. But the supercharger on is okay. How does the innovation apply to the business mechanics of the company? And what value do you extract from it? And that's where the whole language and conversation usually happens with us. I will tell you, though, I'm really excited that Del Technologies kind of doubling down on business outcomes. They're really trying to change the culture and helping customers understand what the technology >> means. Yeah, one of things that struck me. I've been to this event now for a couple of years, and, you know, there's a lot of product discussion here, you know, when you get down to the channel, it's like, Okay, great. You know, I'm doing a server refresh. I'm looking to things like hyper convert, you know? What am I doing in my network? You know, when you up level things a little bit, You know, when I went to del World, it's like, you know, we hear about the venture, you know, activity that's happening around and things like coyote coming down the pipe. But How does that trickle down to the customers? That talking event here? It's great to talk about innovation, but, you know, I got to run my business. You know what? You know. Where does Del fit in that picture >> for you? Got it? Well, it's a custom you got to do both, right? So this has got to be a shift, because now I have to think differently, right? I know how to do feature analysis and benefit analysis of a point in time product, but what's the periphery of activities that inspecting, impacting that decision? Does that architectures scale? What are the economics around that? So you need to think about all those things. And I think it's just a journey for not only us as a vendor, but also for customers as well. >> Okay, so you're relatively new in today. L I want to ask you You gave a great quote in your presentation from from Jack Welch. Er said if the rate of change outside the company is greater than inside the company, the end is near. >> I would say the post. >> So, you know, explain to us the pace of change inside of del technologies. >> Well, you know, that's That's a That's a big question. I mean, piece of change varies by organization by business unit I really can't comment on your individual business units, but I will say, though there's a definite desire toe. Understand? We're customers interested. He is there. So what's the customer trying to dio? And then how do we satisfy the customer request? It's a matter of fact. I don't know if you know this and it was amazing because that's what the customer the other day, you know, Stevie Awards. Which a customer satisfaction, which we double down on customer satisfaction. We have a customer chief customer officer was Karen, and we just won 15 Stevie Awards, which is about customer satisfaction. So I think there's a slow shift, but there's a real focus on customer Central City. For us, the velocity will get there. But if you put the customer at the center like we do, that's a winning strategy. >> Yeah, well, yeah, we know Karen Kim does quite well, you know, culture and working with customers. You know, quite dio you talked about the portfolio of companies and l We know Del Bhumi quite well. We've done their event in the team were well, and you know, VM wears no slouch in the industry. I've had one of the pleasures of my careers. You know, I started working with him. Where when they were, like, 100 person company. No, watch them grow and pack. El Singer, I think was just named like the number one number two, you know, CEO work for employees by employees from glass doors. So, you know No, no slouch on the the venture family. So congratulations, toe Dale family on all that. >> Thank you very much are exciting. >> Joe Batista. Thank you so much for joining me here at the W T. G. Transformed 2019. Pleasure to catch up with you. Appreciate the opportunity. All right, so we're here with customers, the executives, and digging into all the industry trends. Of course. Check out the cute dot net for where we will be. And, uh, I think it was always for watching the cube

>> Live from San Francisco. It's the cube covering IBM thing twenty nineteen brought to you by IBM. >> Welcome back to Mosconi North here in San Francisco, California. I'm student of my co host, A Volante. We're in day three of four days live. Walter. Wall coverage here at IBM think happened. Welcome back to the program. Talk about one of our favorite topics. Cube alarm. Steve Hill, who's the global head of innovation. That topic I mentioned from KPMG, Steve, welcome back to the program. >> Seems to have made good to see you. >> All right. So, you know, we know that the the only constant in our industry is change. And, you know, it's one of those things. You know, I look at my career, it's like innovation. Is it a buzz word? You know? Has innovation stalled out of the industry? But you know, you're living it. You you're you're swimming in it. Talkinto a lot of people on it. KPMG has lots of tools, so give us the update from from last year. >> Well, I think you know, we talked about several things last year, but innovation was a key theme. And and when I would share with you, is that I think across all industries, innovation as a capability has become more mature and more accepted, still not widely adopted across all industries and all competitors and all kinds of companies. But the reality is, innovation used to be kind of one person's job off in the closet today. I think a lot of organizations or realizing you have to have corporate muscle that is as engaged as in changing the status quo as the production muscle is in maintaining the status quo has >> become a cultural. >> It's become part of culture, and so I think innovation really is part of the evolution of corporate governance as far as I'm >> concerned. What one thing I worry about a little bit is, you know, I see a company like IBM. They have a long history of research that throws off innovation over the years. You know, I grew up, you know, in the backyard of Bell Labs and think about the innovation a drove today, the culture you know, faster, faster, faster and sometimes innovation. He does sit back. I need to be able to think longer, You know? How does how does an innovation culture fit into the ever changing, fast paced you? No need to deliver ninety day shot clock of reality of today. >> Well, I think innovation has to be smart, meaning you have to be able to feed the engines of growth. So your horizon one, if you will, of investments and your attention and efforts have to pay off the short term. But you also can't be strategically stupid and build yourself into an alleyway or to our corner, because you're just too short term thought through. Right? So you need to have a portfolio of what we call Horizon three blended with Horizon one and Horizon two types investment. So your short term, your middle term and your longer term needs are being met. Of course, if you think about it like a portfolio of investments, you're going tohave. Probably a smaller number of investments that air further out, more experimental and a larger proportion of them going to be helping you grow. You could say, almost tactically or sort of adjacent to where you are today, incrementally. But some of those disruptive things that you work on an H three could actually change your industry. Maybe you think about today where we are. Azan Economy intangibles are starting to creep into this notion of value ways we've never seen before. Today, the top five companies in terms of net worth all fundamentally rely on intangibles for their worth. Five years ago, it was one or two, and I would argue that the notion of intangibles, particularly data we'll drive a lot of very transformative types of investments for organizations going forward. So you've got to be careful not to starve a lot of those longer term investments, >> right? And it's almost become bromide. Large companies can innovate, but those five companies just mentioned well alluded to Amazon. Google, etcetera Facebook of Apple, Microsoft there, innovators, right? So absolutely and large companies innovate. >> Yes, clearly, yeah, but you have to have muscle, but it doesn't happen by accident, and you do put discipline and process and rigor and tools and leadership around innovation. But it's a different kind of discipline than you need in the operation, so I'll make him a ratio that makes sense. Maybe ninety five percent production, five percent innovation in an organization. That innovation engine is always challenging that ninety five percent Are you good enough? Are you relevant enough? Are you fast enough? Are you agile enough? You need that in every corporate organization in terms of governance to stay healthy and relevant overtime. >> So it's interesting. You know, I was in a session that Jack Welch talk wants, and he's like, I hear big companies can innovate is like big companies made up of people. People are the things that can innovate absolute. But, you know, I've worked in large organizations. We understand that the fossilization process and the goto market that you have, you know, will often kill, you know, those new flowers that are blooming, what separates the people that can drive innovation on DH? You know, put those positive place and kind of the also rans that, you know get left behind window disruption. >> Well, there's several. There's a couple things that I would highlight of a longer list, one of them we culture. I mean, I think innovation has been part of a culture. People in the institution have value innovation and want to be part of it. And there is, you know, a role that everyone can play. Just because you're in operations, if you will, doesn't mean you ignore change or you ignore the opportunity to improve the status quo. But you still have you get paid to operate what I find that is related to culture that gets a lot of people, you know, slow down or or roadblock is the disconnect between the operating part of the business and the innovative part of the business. If you try, if you build them to separately, what happens is you have a disconnection. And if you innovate the best idea in the world over here. But you can't scale it with production, you lose. So you have to make sure that, as as a leader overall, the entire enterprise you build those connections, rotations, leadership, You know, How do you engage the production, you know, engine into the innovation engine? It's to be very collaborative. It should be seamless. You know, everyone likes to say that, but that word, but relative seamlessness is, is heavy architecture. You've gotto build that, you know, collaboration into your model of of how you innovate >> and >> don't innovate in the vacuum. >> And it comes back to the cultural aspects we're talking about. Do you mentioned the ninety day shot? Clocks were here in the Bay Area. Silicon Valley. The most innovative place in the world. They've lived along the ninety day shot clock forever, and it seems to have not heard that so called short term thinking. Why is that? >> Well, there's so much start up here. I mean, at the end of the day, there is so much churn of new thinking and start up in V C. And there's so much activity that it's almost a microcosm, right? Not every place in the world smells, feels, looks like Silicon Valley, right? And the reason for it is in part because there's just so much innovation in what happens here. And these things change me. If you think about, uh, these unicorns that we have today. Today there's about three hundred ninety one unicorns. Just five years ago, there were one hundred sixty globally on before that. Hardly people didn't know they were hardly recognized. But that's all coming from pockets of innovation like Silicon Valley. So I'd argue that what you have here is an interesting amalgamation of culture being part of a macro environment region that that really rewards innovation and demonstrates that in in market valuations in capital raises, I mean, today one hundred million dollars capital raise is pretty common, especially for unicorns. Five, ten years ago. You never see me. It was very difficult to get a hundred million dollars capital, right? >> You mean you're seeing billion dollar companies do half a billion dollars raises today? I mean, it's >> all day, right? And some of them don't make a profit. Which is I mean, and that's kind of the irony, Which is, Are those companies? What did they get that the rest of us, you know, there was that live on Wall Street right out of in New York. What do we not see? Is that some secret that downstream there will be some massive inflow? Hard to say. I mean, look at Amazon is an example. They've used an intangible to take industries out that they were never in before they started selling books, and they leverage customer behavior data to move into other spaces. And this is kind of the intangible dynamic. And the infection >> data was the fuel for the digital disruption to travel around the world. You see that folks outside of Silicon Valley are really sort of maybe creating new innovation recipes? >> Yes. I think that what you see here is starting to go viral right on DH way that KPMG likes to share a holistic way to look at this for our clients. What is what we call the twenty first century enterprise. So the things that we used to do in the twentieth century to be successful, hire people, build more machines, right? You know, buy more assets, hard, durable assets. Those things don't necessarily give you the recipe for success in the twenty first century. And if you look at that and you think about the intangibles work that's been well written about there's there's all kinds of press on this today. You'll start to realize that the recipe for success in this new century is different, and you can't look at it in a silo to say, Okay, so I've gotta change my department or I've got a I've got to go change, You know, my widgets. What you've got to think is that your entire enterprise and so are construct called the twenty first Century prize. Looks at four things. Actually, it's five, and the fifth one is the technologies to enable change in the other four. And those technologies we talk about here and I have made him think which are, you know, cloud data, smart computers or a blockchain, etcetera. But those four pillars our first customer. How do you think about your customer experience today? How do you rethink your customer experience tomorrow? I think the customer dynamic, whether it's generational or it's technologically driven, change is happening more rapidly today than ever. And looking at that front office and the customer dementia, it is really important. The second is looking at your acid base. The value of your assets are changing, and intangibles are big category of that change. But do your do your hard assets make the difference today and forward. Or all these intangibles. Companies that don't have a date a strategy today are at peril of falling victim to competitors who will use data to come through a flank. And Amazons done that with groceries, right? The third category is as a service capabilities. So if you're growing contracting going into new markets are opening new channels. How do you build that capability to serve that? Well, there's a phenomenon today that we know is, you know, I think, very practised, but usually in functions called as a service by capability on the drink instead of going out and doing big BPO deals. Think about a pea eye's. Think about other kinds of ways of get access to build and scale very fucks Pierre your capabilities and in the last category, which actually is extremely important for any change you make elsewhere is your workforce. Um, culture is part of that, right? And a lot of organizations air bringing on chief culture officers. We and KPMG did the same thing, but that workforce is changing. It's not just people you hire into your four walls today. You've got contingent workforce. You have gig economy, workforce a lot of organizations. They're leveraging platform business models to bring on employees to either help customers with help. Dex needs or build code for problems that they like to solve for free. So when you talk about productivity, which we talked about last year and you start thinking about what's separating the leaders from a practical standpoint from the laggers from practically standpoint, a lot of those attributes of changing customer value of assets as a service growth and workforce are driving growth and productivity for that subset of our community and many injured. >> So when you look at the firm level you're seeing some real productivity gains versus just paying attention to the macro >> Correct, any macro way think proactive is relatively flat, and that's not untrue. It's because the bottom portion the laggards aren't growing. In fact, productivity is in many ways falling off, but the ones that are the frontier of those top ten percent fifteen hundred global clients we've looked at, uh, you know, you see that CD study show that they're actually driving growth and productivity substantially, and the chasm is getting larger. >> So, Steve, Steve, it's curious what this means for competition. I think about if I'm using external workforces in open source communities, you know, Cloud and I, you know, changes in the environment. A supposed toe I used to kind of have my internal innovation. Now I'm out in these communities s O You know, we're here than IBM show. You know, I think back the word Coop petition. I first heard in context of talking about how IBM works with their ecosystem. So how did those dynamics change of competition and innovation in this? You know, the gig. Economy with open source and cloud. May I? Everywhere. >> Big implications. I mean, I I think you know, and this is the funny point you made is nontraditional competitors, because I think most of our clients and ourselves recognized that we haven't incredible amount of nontraditional competitors entering our space in professional services. We have companies that are not overtly going after our space, but are creating capabilities for our clients to do for themselves what we used to do for them. Data collection, for example, is one of those areas where clients used to spend money for consultants coming in to gather data into aggregate data with tools today that's ah, a very short process, and they do it themselves. So that's a disintermediation or on bundling of our business. But every business has these types of competitive non Trish competitive threats, and what we're seeing is that those same principles that we talked about earlier of the twenty first century surprise applies, right? How are they leveraging there the base and how they leveraging their workforce? Are they? Do they have a data strategy to think through? Okay, what happens if somebody else knows more about my customers than I do? Right? What does that do to make those kinds of questions need to be asked an innovation as a capability I think is a good partner and driving that nothing I would say, is that eco systems and you made you mention that word, and I want to pick up on that. I mean, I think eco systems air becoming a force in competitive protection and competitive potential going forward. If you think about a lot of you know, household names relative Teo data, you know Amazon's one of them. They are involved in the back office in the middle ofthis have so many organizations they're in integrated in those supply chains. Value change, I think services firms, and particularly to be thinking about how do they integrate into the supply chains of their customers so that they transcend the boars of, you know, their four walls, those eco systems and IBM was We consider KPMG considers IBM to be part of our ecosystem, right? Um, as well as other technology. >> So they're one of one of the things we're hearing from IBM. Jenny talked about it yesterday, and her keynote was doubling down on trust. Essentially one. Could you be implying that trust is a barrier to ay? Ay adoption is that. Is that true? Is that what your data show? >> We we we see that very much in spades. In fact, um, you know, I I if you think about it quite frankly, our oppa has driven a lot of people to class to class three. Amalgamation czar opportunities. But what's happening is we're seeing a slowdown because the price of some of these initials were big. But trust, culture and trust are big issues. In fact, we just released recently. Aye, Aye. And control framework, which includes methods and tools assessments to help our clients that were working with the city of Amsterdam today on a system for their citizens that helped them have accountability. Make sure there's no bias in their systems. As a I systems learn and importantly, explain ability. Imagine, you know. Ah, newlywed couple going into a bank to get a house note and having the banker sit back and have his Aye, aye, driven. You know, assessment for mortgage applicability. Come up moored. Recommend air saying no. You Ugh. I can't offer you a mortgage because my data shows you guys going to be divorced, right? We don't want to tell it to a newlywed couple, right? So explain ability about why it's doing what it's doing and put it in terms that relate to customer service. I mean, that's a pretty it's a silly example, but it's a true example of the day. There's a lot of there's a lack of explain ability in terms of how a eyes coming up with some of its conclusions. Lockbox, right? So a trusted A I is a big issue. >> All right, Steve, Framework that you just talked about the twenty first century enterprise. Is there a book or their papers? So I just go to the website, Or do I need to be a client? Read more about, >> you know, absolutely. You can go to our website, kpmg dot com and you can get all the della you want on the twenty first century enterprise. It talks to how we connect our customers front to middle toe back offices. How they think about those those pillars, the technologies we can help them with. Make change happen there, etcetera. So I appreciate it that >> we'll check it out that way. Don't be left in the twentieth century. Come on. >> No, you can't use twentieth century answers to solve twenty first century challenges, right? >> Well, Steve, he'll really appreciate giving us the twenty first century update for day. Volante on student will be back with our next guest here. IBM think twenty nineteen. Thanks for watching you.

Upbeat techno music >> Live, from Barcelona Spain, it's theCUBE! Covering Cisco Live Europe. Brought to you by Cisco and it's ecosystem partners. >> Hey, everyone. Welcome back to The Cube's exclusive coverage, here in Barcelona, Spain, for Cisco Live Europe 2019. I'm John Furrier. With hosts this week: Dave Vellante, Stu Miniman, here all for three days. So, we're wrapping up Cisco Live 2019, here in Europe. Guys, we're breaking it down. We had some great editorial segments, where we unpacked everything here. But, as we look back over the show, I want to get your observations and insights into, kind of what's going on with Cisco, the secret formula around why DevNet- their developer program; which also has Devnet Create, which is cloud native- is growing very rapidly. Huge resonance with the customer base in Cisco. It's created a revitalization of Cisco, as a company. And you can see that permeating throughout the organization with their branding, how the teams are organized, and they're engineering their products. Is this the future model for all infrastructure companies that don't have a cloud? And why is that successful? And then other observations. Guys, we'll start with DevNet. The very successful program, led by Susie Wee, Senior Vice President and CTO, executing flawlessly how to transform a community, without killing the old to bring in the new. Stu. >> Yeah, John, it's been fascinating to watch. We've talked about the ground effort, a lot of hard work by a small team, build a community. Last year, over 500,000. We hear they're at 560,000 people using this tool. Four and a half years ago, you know, Cisco- mostly a hardware company. It really- what I've seen over the last year or two, they were talking about software, but I've really seen deliverables here. You talk about CloudCenter Suite, you talk about the DNA Center platform; if they're a hardware company, there's a disconnect between what's going on in the DevNet zone, and what's happening in the company. But, we've seen rallying around software solutions. I've heard from the partnering system, from the customers: this isn't Cisco of a few years ago. Very fragmented, lots of lines of businesses, lots of different things. I remember back when Chambers announced, like, "oh, we've got, you know, 37 different adjacencies we're going to go into." No. Now it's: solution suites and platforms and, you know, DevNet- it is a unifying force of what they're doing. That's a great term, John. Love it. And see, that transformation of being a software company, that DevNet set some of the groundwork, and we heard the CIO of Cisco saying that, you know, security and the developer activity, are his partners in crime. Helping him, driving change, and... >> And they did a nice clever play on words: Data Centered. And that's kind of a shot across the bough of the classic data center, which shows it is a cloud world. And data is a center part of it. And, I think the API-centric economy's certainly doing it. But, Dave, I want to get your thoughts, because you asked a question to Susie Wee of DevNet- a very important question Other companies couldn't be successful with developer programs. Cisco has been. What's the secret formula? Well, I asked Amanda Whaley, who's her right-hand woman around what's going on, and she said, "well, there's no secret formula..." Guess what. There is a secret formula. They're being humble. But seems to be content- seems to be the unifying force of the community. They understood the need, they saw the future around cloud native and API's, being a very important connection tissue- connective tissue, for this cloud native world, and an upstream path for Cisco. They understood the future, knew the need, and they provided great content. The sessions and the education are open, inclusive, very education oriented. But, conversations with their peers have been key. TheCUBE's been here, talkin' to... They treat everyone the same, not the big pitches. Real authentic and genuine content that allowed people to learn and grow, and connect with others. To me, I think that is kind of- this is one of my observations. Your thoughts, Dave, on that. >> Yeah, so... First of all, there is a secret formula. And, this is the new blueprint, or the blueprint that infrastructure companies should be following. Cisco's clearly leading there. I think it's content and community. And, they're used their programmability, of their infrastructure, and they've socialized that. They've developed the technology. They say big companies can't innovate; DevNet is a real solid innovation. And it's- we witnessed all week, people coming in, training, learning; these are network engineers. They're learning new skills. They're learning how to be developers. And that is, to me, a huge innovation in business model, in technology. It's creating a flywheel for them. So, they've created- they've come up with the idea, that the network is a data platform. And it's now, also, become an application development platform. On which, they're deploying applications all over the place. Edge, we heard applications being deployed in police vehicles! And so, this is a very important trend, and from what I can tell, they're way ahead of other infrastructure companies: HP, I don't see this, they talk that game. Dell EMC; we talked about code. You know, IBM trying to make it happen with Bluemix. Oracle owns Java, and it still sort of struggles to own the development, developer marketplace. >> So, Dave, I love what you say there. I saw Jack Welch speak a number of years ago, and he's like, "eh, people always tell me all the time that big companies can't innovate." He's like, "well, maybe big companies, but what are companies made up of? Companies are made up of people, and people can innovate." And I think that's- you know, the key there is, it was very people-focused. Absolutely, content. When you talk about what were the big sessions here: oh, they're doin' Java, they're doin' kubernetes. It's like, okay, wait: is there a connection to Cisco products? Absolutely. Is it a product pitch in a product training? There's plenty of that going here! People need that. People built their careers out of Cisco. But this new career? A big question question I had coming in, is: it's a multi-cloud world, you know... Infrastructure, developer, and everything. Cisco's a piece of that. You know, how do they make sure that they get- sticking this with them, and helping them to build their career, and move forward. There's going to be some nice activity, there. And, you get a good glow, and you know, Cisco makes themselves relevant in those communities. >> The other observation that I saw, and I want to get your reactions to it, guys, is: that we saw Scale- and we talk about this all the time in theCUBE. Scale is now table stakes, to compete in this global landscape. But, complexity with multi-cloud, and these things, is there. Every major inflection point in the industry- abstraction layers and software, and/or hardware advances- certainly, Moore's Law kicks in and helps that. But, it's been software abstractions that have really moved the needle, because that's where you can have complexity, and still remove it; from an integration standpoint, from a consumption standpoint. This seems to be- Cisco's buying into this, across the companies, Stu- software. Not just hardware. They've coupled it, but they all work together. This is the magic of DevNet, the magic of API's. It's the magic of an internet operating system. Your thoughts. >> Yeah, and look- we talked to a number of the companies that were acquired by Cisco over the last few years, and I think those are helping to drive some of the change. You have, of course, APT is the big one, Duo in security; companies that were born in the cloud, and helping to move that change along the way, and John, as you said, that unifying factor of, "we're rallying," it's not just, the new Chip Stubbs standing up on the- and saying, "you know, okay, we spent millions of dollars in developing this thing, everybody go out and sell that." It's now- there's co-creation, you're seeing that evolution of that partner ecosystem. And, it's a challenging change, but Cisco is, you know, moving in the right direction. >> It starts at the top, too, Stu. And, I wanted to make a point of- we learned, also- and this is learning for me. Chuck Robbins is behind all this, okay. The CEO has identified DevNet, and said, "this is strategic to our company." All new products now, that are introduced at Cisco, will have API support and a DevNet component. This is a radical change from Cisco of the past. This means that every solution, out of the box- literally- and software, will have that in there. So, with API's and DNA Center, those are two areas to me, that I think will really be a tell sign. If Cisco can execute on the DNA Center, and bring in API's and a DevNet- a real supporting community behind every product; I think the programmable network will be a reality. >> So, help me squint through this. You know, we talk to a lot of people, we go to a lot of shows. We're gettin' the Kool-Aid injection from the DevNet crew here- but, there's real substance. We're going to challenge some of the other companies that we work with. Some of the other infrastructure companies. The IT business, it's like the NFL. It's a copycat league. So, HP is going to say, "oh, we got ATI's." EMC, Dell: they're going to say the same thing. But, what's different here... I mean, clearly, you see it in the evidence of being able to cultivate a community of developers. >> Of course. >> Is it because of the network? >> No, it's management. HP has people- I've talked to them on theCUBE- that believe in cloud native. The company just doesn't fund them properly. They've got the smallest booth at the events, they're always, you know, a partner booth. They're part of an adjunct of something else. HP and Tony O'Neary, I don't think is funding open cloud native... Or certainly the marketing people, or product people, are not funding developers. >> Well, certainly not to the degree that Cisco is, obviously. >> There's no physical signs of any kind. We go to all the shows. >> What about Dell? What about Dell EMC? >> I think Dell EMC is kind of keeping it open, but there's no coherent group. I can't, in my mind's eye, point to one group, saying, "wow, they're kickin' ass." >> They got bigger problems now. It's how you consolidate the portfolio... >> What is- Michael Dell's state of goal, is for Dell to be the leading infrastructu&re company out there. There's a big hardware component of that. Absolutely, they participate in open source, they have some developer- API's are great, and they love standards. But, you know, this is a software movement. >> Yeah. >> Infrastructure's code is where they're going. VMWare, you know, they've made some pushes and moves, in this space... >> With developers? >> Not big developers... >> But, where are the developers? They had their operators on the IT side, so- back to Dell for a second. I think Dell Boomi is one signal, I've seen some sign there. But then- and that's still relatively new, but there's no one- there's no DevNet for Dell. On VMWare... >> People Labs is someone that is helping customers learn to code, do that kind of activity. But, you know, broadly across the Dell family, I haven't seen as much. >> I think VMware has a good ecosystem. I think they have good technical people. I don't think they need a developer program, per se. I think they need more of an operator program. I think that's VMWorld. You go to VMWorld and you see a lot of the partners, and how they integrate in. >> So, who are the favorites in the developer world? Obviously, Microsoft, and MUS... >> I mean, to me, it's Amazon- as a kid in a candy store, if you're a developer, you're all over Amazon. They have great stuff, they're always introducing new candy for the kids, all the time. New services; Amazon, number one. Azure, I think- not so much, in my mind. I think it's a lot of legacy, there, with Azure. But, they are- they're puttin' up the numbers on the profit, and you know my stand on Azure. I think Azure's sandbagging the numbers. But, the growth's there, it's going to be a matter of time. I think, Azure, is on the path. And they have the legacy developer program, world class, Microsoft. Microsoft is in the Cisco kind of wheelhouse. If they can transform their existing developer community, to be cloud native, they hit a home run. >> Yeah, but, John, you were talking about IT ops, out there; Microsoft does great in that. They've got a lot of big push there. They absolutely- the DotNet developers are there. You go to the Build conference, they play. We go to CUBECon, and a lot of the developer shows, and Microsoft, strongly there... >> No, let me just clarify my point. Let me clarify my point on Microsoft. Yes, they have a pre-existing, huge, development. They've been successful by the core competancy, no doubt. Cisco had a developer community: all networking. So, I think Microsoft has that legacy win, but they have to transform, and go the next level. The question is, do they have that. So- with Azure, I'm saying... >> What about Google? You guys were at the Google Cloud Show last year, we'll be there again in April. >> Yeah, you got to put Google in the mix. No doubt, I mean, no question. And, what about Red Hat? With IBM, on the developer front? >> Yeah, look, when you talk to the developers, and all the- a lot of the training their doing, if you've got LITIC skill sets, you've got a leg up in a lot of these environments. There are a lot of developers. It's not like people at Red Hat- some, are like, "oh wait, 6here's my first hoodie, and I'm going to learn to start code." They're already there. They're in this ecosystem. Red Hat: huge part- everybody we just talked about, Red Hat has a strong piece in there. That's one of the reasons why IBM bought them, Dave, is to help ride that wave. >> That's expensive, but they got the ingredients now. >> Red Hat's- check, I love those guys. Google has a lot of developers. They contribute heavily in open source. But, in terms of a Google community, that's really the CNCF in my mind. I think they're doing great job stewarting CNCF, but there's not a lot of people- users, in the Google ecosystem, they've got tons of developers. And, that's an opportunity for Google, in my opinion. >> Well, let's bring it back to Cisco. So, are we in agreement that they've got a leg up on the other infrastructure competitors... >> Yeah, I do. >> Specifically, as it relates to developers. >> They have a huge leg up, but I think it's even bigger that that. I think that this company is going to skyrocket, if they crack the code on network programmability. They're at the early stages now, you're talking about intro to Python, they give more advanced classes... Give them 24 months, if they continue momentum on DevNet, that's the tipping point, in my mind. Two years, they could own everything, and just be a whole other level company, if they crack the code. 'Cause the network is the value. Payload, network effect, this is the new normal in today's.. >> It's a big challenger. I mean, it's really not- and, the networking companies, for years, haven't been able... The Aristas, and the Junipers, haven't been able to unseed them, as the leader. They still got 60 percent of the marketplace. >> DMWare- DMWare and Cisco. >> DMWare, alright. >> DMWare and Cisco, 'cause DMWare and Amazon, that's a lethal combination. I think that's what I'm going to watch, the frenemy action between DMWare and Cisco. I think that level of where NSX, and what Cisco's trying to do, within ten paces of that working. >> Well, and Outpost is the hybrid infrastructure. Does that eventually become a multi-cloud play? Maybe it's a few years off, but... >> Yeah, absolutely. Look, we've watched- a year ago, we were saying, "okay, Google's a strong partner to Cisco, how 'about AWO's?" Well, they're integrating with kubernetes, they're starting to do more with AWS. It's always an interesting partnership with Amazon. Cisco's got lots of products in the marketplace, they're growing in that environment, but Amazon's learning from everybody and can potentially be a threat down the road to where Cisco is. And, I'd love to see Cisco doing more in the Microsoft space, too. >> We'll be watching Cisco, over the year. We're going to continue to go deep on Cisco. We got the Cisco Live North America Show on the cal... >> San Diego. >> This year in San Diego. So, we'll see theCUBE there, for multiple days, as well. Of course, we'll be following all the traction of software define everything, as the world goes completely cyber, dark, encrypted; whatever it is, we're going to be covering it. Well, thanks for watching. I want to give a shout out to the crew. Good job, guys. Well done. Thanks for watching theCUBE here, in Barcelona. I'm Jeff Furrier with Dave Vellonte, Stu Miniman. Thanks for watching. (upbeat techno music)

Silicon Valley, it's theCUBE covering People First Network. Brought to you by Mayfield. >> Hello, I'm John Furrier here in Palo Alto for an exclusive conversation, CUBE conversation, part of the People First Network with theCUBE and Mayfield fund. I'm here with John Chambers at his house in Palo Alto. John Chambers is the former CEO/Chairman of Cisco Systems, now running J2C, JC2 Ventures. Great to see you, thanks for spending time! >> It's a pleasure to be together again. >> I'm here for two reasons. One, I wanted a conversation about People First and technology waves, but also, I want to talk about your new book, which is exciting, called Connecting the Dots. And it's not your standard business book, where, you know, hey, rah-rah, you know, like a media post these days on the internet; it's some personal stories weaved in with the lessons you've learned through the interactions you've had with many people over the years, so exciting book and I'm looking forward to talking about that. >> Thank you! >> Again, John Chambers, legend, Cisco, 1991 when you joined the company from Wang before that. 400 employees, one product, 70 million in revenue. And when you retired in 2015, not so much retired, 'cos you've got some--. >> I'm working on my next chapter! >> You've got your next chapter (laughs)! 180 acquisitions, 447 billion in revenue, you made 10,000 people millionaires, you created a lot of value, probably one of the biggest inflection points in computer history, the evolution of inter-networking and tying systems together, it was probably one of the biggest waves somewhat before the wave we're on now. So an amazing journey, now you're running JC2 Ventures and investing in game-changing start-ups. So you're not retired? >> No. It was only my next chapter. I made my decision almost 10 years before I left Cisco first, to make for a very smooth transition because it's my family, and out of the 75,000 people, I hired all but 23 of them! And in terms of what I wanted to do next, I really wanted to both give back, create more jobs, get our start-up engine going again in this country, and it's currently broken, and I want to do that on a global basis, in places like France and India as well. So I'm on to my next chapter, but the fun part in this chapter is that I do the things that I love. >> And you've got a great team behind you, but also, you have a great personal network. And I want to get into that, of your personal stories as well as your social network in business and in the community; but one of the things I want to get up front, because I think this is important for this conversation is, you've been very strong. I've seen you present many times over the years, going way back into the 90's. You're eloquent, you're people-oriented, but you have a knack for finding the waves, seeing transitions, you've been through many waves. >> Yes I have, good and bad. >> Good and bad. But one of the big ones, how do you spot those transitions? And what wave are we in now? I mean, talk about the wave that's happening now, it's unprecedented on many levels, but, different, but it's still a wave. >> It is, and outgoing market transitions and often combined with either economic changes or business model changes with technology. And part of the reason that I've been fortunate to be able to identify many of them is I listen to customers very carefully, but also, you're often a product of your prior experiences. Having experienced West Virginia, one of the top states in the US in terms of the chemical industry, uh, during the 40's and 50's and 60's when I was growing up there, and literally more millionaires in West Virginia than there were in the entire Great Britain. We were on top of the world in the chemical industry, and the coal industry, and yet, because we missed transitions, and we should've seen them coming, the state fell a long way, so now we're trying to correct that with some of the start-up activity we'll talk about later. As you see this, and then I went to Boston, 128, we were talking earlier, Wang Laboratories, the mini-computer era, but I was in IBM first out of the central part of the nation, so I watched IBM and Mainframes, and then I watched them miss on going to the mini-computer, and then miss in terms of the internet. So I was able to see the transitions that occurred in Boston, Route 128, where we were the Silicon Valley of the world, and we knew it, and this unusual area out in California called Silicon Valley, we paid almost no attention to, and we didn't realize we failed to make a transition from the mini-computer era to the pc and the internet era. Then I joined Cisco, and saw the internet era. So part of it is, you're a product of your experiences, and know the tremendous pain that occurs, because Boston 128 is nowhere near what it used to be, so there's no entitlement in this new world out of the thousand high-tech companies that I was associated with, including four or five giants in mini-computers, none of them are really in existence today, so it shows you, if you don't identify the transitions, number one, you're going to have an opportunity to benefit by them, but number two, you sure have an opportunity to get hurt by them. >> And you know, these waves also create a lot of wealth and value; not just personal wealth, but community wealth, and Cisco in particular had a good thing going for them, you know, TCP-IP was a defact-- not even a standard, it was a defacto standard at that time, IBM and these kinds of digital equipment corporations dominated the network protocol. Even today, people are still trying to take out Cisco competitively, and they can't because they connected the world. Now the world's connected with digital, it's connected with mobile, so we're kind of seeing this connected wave globally. How do you think about that, now that you've seen the movie at the plumbing levels at Cisco, you now have been traveling the world, we're all connected. >> We are. And it's important to understand that I'm completely arms-length with Cisco, it's their company to run now, and I'm excited about their future. But I'm focused on the next chapter in my life, and while I think about the people at Cisco everyday, I'm into the start-up world now, so how do I think about it now? I think most of the innovation over the next decade will come from start-ups. The majority of the top engineering students, for example, at a Stanford or an MIT or a Polytechnique in France, which is the top engineering school, I think, in Europe, or at the ITs in India, they are all thinking about going to start-ups, which means this is where innovations going to come from. And if you think about a digital world going from the time you and I, we almost recruited you to Cisco, and then we finally did; there's only a thousand devices connected then when Cisco was founded. Today there are about 20 billion devices connected to the internet; in the future, it's going to be 500 billion in a decade, and so this concept of digitalization combined with artificial intelligence, all of a sudden we'll get the right information at the right time to the right person or machine to make the right decision, sounds complex, and it is. And it's ability to do that, I think start-ups are well-positioned to play a key role in, especially in innovation. So while the first stage of the internet, and before that were all dominated by the very large companies, I think you're going to see, in this next phase of digitalization, you're going to see a number of start-ups really emerge, in terms of the innovation leaders, and that's what I'm trying to do with my 16 investments I've made, but also coaching probably another 50 uh, start-ups around the world on a regular basis. >> And the impact of outside Silicon Valley, globally, how do you see that ecosystem developing with the entrepreneurship models that are now globally connected in with these connection points like Silicon Valley? >> It will partially in parallel, partially, it's a new phenomenon. I sold the movie of Boston 128, as I said earlier, and on top of the world, and there is no entitlement. The same thing's true with Cisco, um, sorry, of Silicon Valley today; there's no entitlement for the future, and just because we've led up until this point in time, doesn't mean we will in 10 years, so you can't take anything for granted. What you are seeing, since almost all job creation will be from start-ups, and small companies getting bigger, the large companies in total will probably not add any head count over this next decade because of artificial intelligence and digitization, and so you're now going to see job growth coming from those smaller companies, if these small companies don't get a forum to all 50 states, if they don't get a chance to grow their head count there, and the economic benefits of that, then we're going to leave whole states behind. So I think it's very important that we look at the next wave of innovation, I think there's a very good probability that it will be more inclusive, both by geography, by gender, and all diversity measures, and I'm optimistic about the future, but there are no guarantees, and we'll see how it plays out. >> Let's talk about your next chapter. I was going to wait, but I want to jump while we're on the topic. JC2 is a global start-up, game-changing start-up focus that you have. What is the thesis? What are you looking for, and talk about your mission? >> Well, our mission is very simple. I had a chance to change the world one time with Cisco, and many people, when I said Cisco's going to change the way the world works, lives, learns, and plays by enabling the internet, everybody said nice marketing, but you're a router company. And yet, I think most people would agree, probably more than any other company, we had the leadership role in changing the internet and the direction going on, and now, a chance to do it again, because I think the next wave of innovation will come from the start-ups, and it doesn't come easy. They need coaches, they need strategic partners, they need mentors as much as they need the venture capitalists, so I would think of as this focusing on disruptive start-ups that get very excited in these new areas of technology, ranging from physical and virtual worlds coming together, to artificial intelligence and automation everywhere, to the major capabilities on cyber security across that to the internet of things, so we're trying to say, how do we help these companies grow in skill? But if I was just after financial returns, I'd stay right here in the Valley. I can channel anybody, VC's here that I trust and they trust me, and it would be a better financial return. But I'm after, how do you do this across a number of states, already in seven states, and how do you do it in France and India as role models? >> It's got a lot of purpose. It's not just a financial purpose. I mean, entrepreneurs want to make money, too, but you've made some good money over the years, but this is a mission for you, this is a purpose. >> It is, but you referred to it in your opening comments. When we were at Cisco, I've always believed that the most successful owe an obligation to give back, and we did. We won almost every corporate social responsibility award there was. We won it from the Democrats and the Republicans, from Condie Rice and George Bush and from Hillary Clinton and President Obama. We also, as you said, made 10,000 Cisco employees millionaires just in the first decade. And we tried to give back to society with training programs like Network Academies and trained seven million students. And I think it's very important for the next generation of leaders here in the Valley to be good at giving back. And it's something that I think they owe an obligation to do, and I think we're in danger now of not doing it as well as we should, and for my start-ups, I try to pick young CEOs that understand, they want to make a financial return, and they want to get a great product out of this, but they also want to be fair and giving back to society and make it a win-win, if you will. >> And I think that's key. Mission-driven companies are attracting the best talent, too, these days, because people are more cognizant of that. I want to get into some of your personal stories. You mentioned giving back. And reading your book, your parents have had a big role in your life--. >> Yes, they have. >> And being in West Virginia has had a big role in your life. You mentioned it having a prosperity environment, and then missing that transition. Talk about the story of West Virginia and the role your parents played, because, they were doctors, so they were in the medical field. The combination of those two things, the culture where you were brought up, and your family impacted your career. >> I'm very proud of being from West Virginia, and very proud of the people in West Virginia, and you see it as you travel around the world. All of us who, whether we're in West Virginia, or came out of it, care about the state a great deal. The people are just plain good people, and I think they care about treating people with respect. If I were ever run off a road at night in the middle of the night, I'd want to be in West Virginia, (both laugh) when I go up to knock on that door. And I think it carries through. And also, the image of our state is one that people tend to identify in terms of a area that you like the people. Now what I'm trying to do in West Virginia, and what we just announced since last week, was to take the same model we did on doing acquisitions, 180 of them, and say here's the playbook, the innovation playbook for doing acquisitions better than anyone else, and take the model that we did on country digitization, which we did in Israel and France and India with the very top leaders, with Netanyahu and Shimon Peres in Israel, with Macron in France and with Modi in India, and drove it through, and then do the same thing in terms of how we take the tremendous prosperity and growth that you see in Silicon Valley, and make it more uniform across the country, especially as traditional business won't be adding head count. And while I'd like to tell you the chemical industry will come back to West Virginia and mining industry will come back in terms of job creation, they probably won't, a lot of that will be automated in the future. And so it is the ability to get a generation of start-ups, and do it in a unique way! And the hub of this has to be the university. They have to set the pace. Gordon Gee, the President there, gets this. He's created a start-up mentality across the university. The Dean of the business school, Javier Reyes is going across all of the university, in terms of how you do start-ups together with business school, with engineering, with computer science, with med school, et cetera. And then how do you attract students who will want to really be a part of this, how do you bring in venture capital, how do you get the Governor and the President and the Senate and the Speaker of the House on board? How do you get our two national senators, Shelly Moore Capito and also Joe Manchin, a Democrat and a Republican working together on common goals? And then how do you say here's what's possible, write the press release, be the model for how a country, or a state, comes from behind and that at one time, then a slow faller, how do we leap frog? And before you say it can't be done, that was exactly what people said first about India, when I said India would be the strongest growing economy in the world, and it is today, probably going to grow another seven to 10%. That means you double the per capita of everyone in India, done right, every seven to 10 years. And France being the innovation engine in Europe to place your new business, you and I would have said John, no way, just five years ago, yet it has become the start-up engine for Europe. >> It's interesting, you mentioned playbook, and I always see people try to replicate Silicon Valley. I moved out here from the East Coast in 1999, and it's almost magical here, it's hard to replicate, but you can reproduce some things. One of the common threads, though, is education. The role of education in the ecosystem of these new environments seems to be a key ingredient. Your thoughts about how education's going to play a role in these ecosystems, because education and grit, and entrepreneurial zeal, are kind of the magic formula. >> Well they are in many ways. It's about leadership, it's about the education foundation, it's about getting the best and brightest into your companies, and then having the ability to dream, and role models you can learn from. We were talking about Hewlett-Packard earlier, a great role model of a company that did the original start-up and Lou Platt, who was the President of HP when I came out here, I called him up and said, you don't know me, Lou, I'm with a company you've probably never heard of, and we have 400 people, but I don't know the Valley, can you teach me? And he did, and he met with me every quarter for three years, and then when I said what can I do to repay you back, because at that time, Cisco was on a roll, he said John, do it for the next generation. And so, that's what I'm trying to do, in terms of, you've got to have role models that you can learn from and can help you through this. The education's a huge part. At the core of almost all great start-up engines is a really world-class university. Not just with really smart students, but also with an entrepreneur skill and the ability to really create start-ups. John Hennessey, Stanford did an amazing thing over the last 17 years on how to create that here at Stanford, the best in the world, probably 40% of the companies, when I was with Cisco, we bought were direct or indirect outgrowth of Stanford. Draw a parallel. Mercury just across the way, and this isn't a Stanford/CAL issue, (both laugh) equally great students, very good focus on interdisciplinary activities, but I didn't buy a single company out of there. You did not see the start-ups grow with anywhere near the speed, and that was four times the number of students. This goes back to the educational institution, it has to have a focus on start-ups, it has to say how they drive it through, this is what MIT did in Boston, and then lost it when 128 lost it's opportunity, and this is what we're trying to do at West Virginia. Make a start-up engine where you've got a President, Gordon Gee, who really wants to drive this through, bring the political leaders in the state, and bring the Mountaineers, the global Mountaineers to bare, and then bring financial resources, and then do it differently. So to your point, people try to mimic Silicon Valley, but they do it in silos. What made Silicon Valley go was an ecosystem, an education system, a environment for risk-taking, role models that you could steal people from--. >> And unwritten rules, too. They had these unwritten rules like pay it forward, your experience with Lou Platt, Steve Jobs talks about his relationship with David Packard, and this goes on and on and on. This is an important part. Because I want to just--. >> Debt for good is a big, big issue. Last comment on education, it's important for this country to know, our K through 12 system is broken. We're non-competitive. People talk about STEM, and that's important, but if I were only educating people in three things, entrepreneurship, how to use technology, and artificial intelligence; I would build that into the curriculum where we lose a lot of our diversity, especially among females in the third, fourth, fifth grade, so you haveta really, I think, get people excited about this at a much earlier age. If we can become an innovation engine again, in this country, we are not today. We're not number one in innovation, we're number 11! Imagine that for America? >> I totally agree with ya! And I don't want to rant and waste a lot of time, but my rants are all on Facebook and Twitter. (both laugh) Education's a problem. It's like linear, it's like a slow linear train wreck, in my opinion, but now you have that skills gaps, you mentioned AI. So AI and community are two hot trends right now. I'm going to stay with community for a minute. You mentioned paying it forward. Open source software, these new forms of operational scale, cloud computing, open source software, that all have this ethos of pay it forward; community. And now, community is more important than ever. Not just from the tech world, but you're talking about in West Virginia, now on a global scale. How does the tech industry, how can the tech industry, in your opinion, nurture community at local, regional, global scale? >> This is a tough one John, and I'd probably answer it more carefully if I was still involved directly with Cisco. But the fun thing is, now I represent myself. >> In your own opinion, not Cisco. There's a cultural thing. This is, Silicon Valley has magic here, and community is part of it. >> Yes, well it's more basic than that. I think, basically, we were known for two decades, not just Cisco, but all of the Valley as tech for good, and we gave back to the communities, and we paid it forward all the time, and I use the example of Cisco winning the awards, but so do many of our peers. We're going to Palestine and helping to rebuild Palestine in terms of creating jobs, et cetera. We went in with the Intels of the world, and the Oracles and the other players and HP together, even though at times we might compete. I think today, it's not a given. I think there is a tug of war going on here, in terms of what is the underlying purpose of the Valley. Is it primarily to have major economic benefits, and a little bit of arm's length from the average citizen from government, or is it do well financially, but also do very well in giving back and making it inclusive. That tug of war is not a given. When you travel throughout the US, today, or around the world, there are almost as many people that view tech for bad as they do tech for good, so I think it's going to be interesting to watch how this plays out. And I do think there are almost competing forces here in the Valley about which way should that go and why. The good news is, I think we'll eventually get it right. The bad news is, it's 50/50 right now. >> Let's talk about the skill gap. A lot of leaders in companies right now are looking at a work force that needs to be leveled up, and as new jobs are coming online that haven't been trained for, these openings they don't have skills for because they haven't been taught. AI is one example, IOT you mentioned a few of those. How do great leaders, proactively and reactively, too, get the skills gaps closed? What strategies can you do, what's the playbook there? >> Well two separate issues. How do they get it closed, in terms of their employees, and second issue, how do we train dramatically better than we've done before? Let's go to the first one. In terms of the companies, I think that your ability to track the millennials, the young people, is based upon your vision of doing more than quote just making a profit, and you want to be an exciting place to work with a great culture, and part of that culture should be giving back. Having said that, however, the majority of the young people today, and I'm talking about the tops out of the key engineering schools, et cetera, they want to go to start-ups. So what you're going to see is, how well established companies work with start-ups, in a unique partnership, is going to be one of the textbook opportunities for the future, because most companies, just like they didn't know how to acquire tech companies and most of all tech acquisitions failed, even through today. We wrote the textbook on how to do it differently. I think how these companies work with start-ups and how they create a strategic relationship with a company they know has at least a 50/50 probability of going out of business. And how do you create that working relationship so that you can tap into these young innovative ideas and partnerships, and so, what you see with the Spark Cognition, 200 people out of Texas, brilliant, brilliant CEO there in terms of what he is focused on, partnering with Boeing in that 50/50 joint venture, 50/50 joint venture to do the next FAA architecture for unmanned aircraft in this country. So you're going to see these companies relate to these start-ups in ways they haven't done before. >> Partnership and collaboration and acquisitions are still rampant on the horizon, certainly as a success for you. Recently in the tech industry we're seeing big acquisitions, Dell, EMC, IBM bought Red Hat, and there's some software ones out there. One was just going public and got bought, just recently, by SAP, how do you do the acqui-- you've done 180 of them? How do you do them successfully without losing the innovation and losing the people before they invest and leave; and this is a key dynamic, how do companies maintain innovation in an era of collaboration, partnerships, and enmity? >> I had that discussion this morning at Techonomy with David Kirkpatrick, and David said how do you do this. And then as I walked out of the room, I had a chance to talk with other people and one of them from one of the very largest technology companies said, John, we've watched you do this again and again; we assumed that when we acquired a company, we'd get them to adjust to our culture and it almost never worked, and we lost the people at a tremendously fast pace, especially after their lock-in of 18 to 24 months came up. We did the reverse. What we did was develop a replicatible innovation playbook, and I talk about it in that book, but we did this for almost everything we did at Cisco, and I would've originally called that, bureaucracy, John. (both laugh) I would've said that's what slow companies do. And actually, if done right, allows you to move with tremendous speed and agility, and so we'd outline what we'd look for in terms of strategy and vision; if our cultures weren't the same, we didn't acquire them. And if we couldn't keep the people, to generate the next generation of product, that was a bad financial decision for us, as well. So our attrition rate averaged probably about 5% or over while I was at Cisco for 20 years. Our voluntary attrition rate of our acquired companies, which normally runs 20% in these companies, we had about four. So we kept the people, we got the next generation product out, and we went in with that attitude in terms of you're acquiring to be able to keep the people and make them a part of your family and culture. And I realize that that might sound corny today, but I disagree. I think to attract people, to get them to stay at your company, it is like a family, it is like how you succeed and occasionally lose together, and how you build that family attitude under every employee, spouse, or their children that was life-threatening, and we were there for them in the ways that others were not. So you're there when your employees have a crisis, or your customer does, and that's how you form trust in relationships. >> And here's the question, what does People First mean to you? >> Well people first is our customer first. It means your action and everything you do puts your customers and your people first, that's what we did at Cisco. Any customer you would talk to, almost every customer I've ever met in my life would do business with us again, or with me again, because your currency in today's world is trust, track record, and relationships, and we built that very deep. Same thing with the employees. I still get many, many notes from people we helped 10 or 15 years ago; here's the picture of my child that you all helped make a difference in, Cisco and John, and you were there for us when we needed you most. And then in customers. It surprises you, when you help them through a crisis, they remember that more than when you helped them be successful, and they're there for you. >> Talk about failure and successes. You talk about this in the book. This is part of entrepreneurship, you can't succeed without failures. Handling failures is just as important as handling successes, your thoughts on people should think about that from a mindset standpoint? >> Well, you know, what's fun is those of you who are parents, or who will be parents in the future, when your child scores a goal in soccer or makes a good grade on a test, you're proud for them, but that isn't what worries you. What worries you is when they have their inevitable setbacks, everybody has that in life. How do you learn to deal with them? How do you understand how much were self-inflicted and how much of it was done by other causes, and how they navigate through that determines who they are. Point back to the West Virginia roots, I'm dyslexic, which means that I read backwards. Some people in early grade school thought I might not even graduate from high school much less go to college. My parents were doctors, they got it, but how I handled that was key. And while I write in the book about our successes, I spend as much time on when disaster strikes, how you handle that determines who you are in the future. Jack Welch told me in the 90's, he said John, you have a very good company, and I said Jack, you're good at teaching me something there, we're about to become the most valuable company in the world, we've won all of the leadership awards and everything else, what does it take to have a great company? He said a near-death experience. At the time I didn't understand it. At the end of 2001 after the dot com bubble, he called me up, he said, you now have a great company, I said Jack, it doesn't feel like it. Our stock price is down dramatically, people are questioning can I even run the company now, many of the people who were so positive turned very tough and--. >> How did you handle that? How did you personally handle that, 'cos--. >> It's a part of leadership. It's easy to be a leader when everything goes well, it's how you handle when things are tough, and leadership is lonely, you're by yourself. No matter how many friends you have around you, it's about leadership, and so you'd lead it through it. So 2001, took a real hard look, we made the mistake of focusing, me, on the numbers, and my numbers in the first week of December were growing at 70% year over year. We'd never had anything negative to speak of, much less below even 30% growth, and by the middle of January, we were -30%. And so you have to be realistic, how much was self-inflicted, how much the market, I felt the majority of it was market-inflicted, I said at the time it's a hundred year flood. I said to the employees, here's how we're going to go forward, we need to bring our head count back in line to a new reality, and we did it in 51 days. And then you paint the picture from the very beginning of what you look like as you recover and in the future and why your employees want to stay here, your customers stay with you and your shareholders. It wiped out most of our competitors. Jack Welch said, John, this is probably your best leadership year ever, and I said Jack, you're the only one that's going to say that. He said probably, and he has been. >> And you've got the scar tissue to prove it. And I love this story. >> But you're a product of your scars. And do you learn how to deal with them? >> Yeah, and how you-- and be proud of them, it's what, who you are. >> I don't know if proud's the right word. >> Well, badge of honor. (both laugh) >> Red badge of honor, they're painful! >> Just don't do it again twice, right? >> We still make the same mistake twice, but at the same time when I teach all these start-ups, I expect you to make mistakes. If you don't make mistakes, you're not taking enough risk. And while people might've, might say John, one of your criticisms is that you spread yourself a little bit too thin in the company at times, and you were too aggressive. After thinking about it, I respectfully disagree. If I had to do it over, I'd be even bolder, and more aggressive, and take more risks, and I would dream bigger dreams. With these start-ups, that's what I'm teaching them, that's what I'm doing myself. >> And you know, this is such a big point, because the risk is key. Managing risk is actually, you want to be as risky as possible, just don't cut an artery, you know, do the right things. But in your book, you mention this about how you identify transitions, but also you made the reference to your parents again. This is, I think, important to bring up, because we have an expression in our company: let's put the patient on the table and let's look at the problem. Solving the problems and not going out of business at that time, but your competitors did, you had to look at this holistically, and in the book, you mentioned that experience your parents taught you, being from West Virginia, that it changed how you do problem solving. Can you share what that, with that in conscience? >> Well, both parents were doctors, and the good news is, you got a lot of help, the bad news is, you didn't get a lot of self 'cos they'd fix you. But they always taught me to focus on the real, underlying issue, to your point. What is the real issue, not what the symptom is, the temperature, or something else. And then you want to determine how much of that was self-inflicted, and how much of it was market, and if your strategy's working before, continue, if your strategy was starting to get long in the tooth, how do you change it, and then you got to have the courage to reinvent yourself again and again. And so they taught me how to deal with that. I start off the book by talking about how I almost drowned at six years of age, and as I got pulled down through the rapids, I could still see my dad in my mind today running down the side of the river yelling hold on to the fishing pole. It was an ugly fishing pole. Might've cost $5. But he was concerned about the fishing pole, so therefore I obviously couldn't be drowning so I focused both hands on the fishing pole and as I poked my head above water, I could still see him running down. He got way down river, swam out, pulled me in, set me on the side, and taught me about how you deal when you find yourself with major setbacks. How do you not panic, how do you not try to swim against the tide or the current, how you be realistic of the situation that you're in, work your way to the side, and then you know what he did? He put me right back in the rapids and let me do it myself. And taught me how to deal with it. Dad taught me the business picture and how you deal with challenges, Mom, uh, who was internal medicine, psychiatry, taught me the emotional IQ side of the house, in terms of how you connect with people, and I believe, this whole chapter, I build relationships for life. And I really mean it. I think your currency is trust, relationships, and track record. >> And having that holistic picture to pull back and understand what to focus on, and this is a challenge for entrepreneurs. You're now dealing with a lot of entrepreneurs and coaching them; a lot of times they get caught in the forest and miss the trees, right? Or have board meetings or have, worry about the wrong metrics, or hey, I got to get financing. How should an entrepreneur, or even a business leader, let's talk about entrepreneur first and then business leader, handle their advisors, their investors, how do they manage that, how do they tap into that? A lot of people say, ah, they don't add much value, I just need money. This is important, because this could save them, this could be the pole for them. >> It could, or it could also be the pole that causes the tent to collapse (both laugh). So I think the first thing when you advise young entrepreneurs, is realize you're an advisor, not a part of management. And I only take young entrepreneurs who want to be coached. And as I advise them, I say all I'm asking is that you listen to my thoughts and then you make the decision, and I'll support you either way you go, once you've listened to the trade-offs. And I think you want to very quickly realize where they are in vision and strategy, and where they are on building the right team and evolving the team and changing the team, where they are in culture, and where they are on their communication skills because communication skills were important to me, they might not have been to Jack Welch, the generation in front of me, but they were extremely important to ours. And today, your communication mismatch on social media could cost your company a billion dollars. If you're not good at listening, if you're not good at communicating with people and painting the picture, you've got a problem. So how do you teach that to the young players? Then most importantly, regardless of whether you're in a big company or a small company, public or private sector, you know what you know and know what you don't. Many people who, especially if they're really good in one area, assume that carries over to others, and assume they'll be equally as good in the others, that's huge mistake; it's like an engineer hiring a good sales lead, very rarely does it happen. They recruit business development people who appeals to an engineer, not the customer. (both laugh) So, know what you know, know what you don't. For those things you don't know, surround yourself with those people in your leadership team and with your advisors to help you navigate through that. And I had, during my career, through three companies, I always had a number of advisors, formal and informal, that I went to and still go to today. Some of them were very notable players, like our President Clinton or President Bush, Shimon Peres, Henry Kissinger, or names that were just really technical leads within companies, or people that really understood PR like Thomas Freedman out of the New York Times, or things of that. >> You always love being in the trenches. I noticed that in Cisco as an observer. But now that you're in start-ups, it's even more trenches deeper (laughs) and you've got to be seeing the playing field, so I got to ask ya a personal question. How do you look back at the tech trends that's happening right now, globally, both political, regulatory technology, what advice would you give your 23-year-old self if you were breaking into the business, you were at Wang and you were going to make your move; in this world today, what's going on, what would you be doing? >> Well the first thing on the tech trend is, don't get too short-term focused. Picture the ones that are longer term, what we refer to as digitization, artificial intelligence, et cetera. If I were 23 years old, or better yet, 19 years old, and were two years through college and thinking what did I want to do in college and then on to MBA school and perhaps beyond that, legal degree if I'd followed the prior path. I would focus on entrepreneurship and really understand it in a lot more detail. I learned it over 40 years in the business. And I learned it from my dad and my mom, but also from the companies I went into before. I would focus on entrepreneurship, I'd focus on technology that enables entrepreneurship, I would probably focus on what artificial intelligence can do for that and that's what we're doing at West Virginia, to your point earlier. And then I would think about security across that. If you want really uh, job security and creativity for the future, if you're a really good entrepreneur, with artificial intelligence capability, and security capability, you're going to be a very desired resource. >> So, we saw you, obviously networking is a big part of it. You got to be networking with other people and in the industry, would you be hosting meet ups? Young John Chambers right now, tech meet ups, would you be at conferences, would you be writing code, would you be doing a start-up? >> Well, if we were talking about me advising them? >> No, you're 23-years-old right now. >> No, I'd just be fooling around. No, I'd be in MBA school and I'd be forming my own company. (both laugh) And I would be listening to customers. I think it's important to meet with your peers, but while I developed strong relationships in the high-tech industry, I spent the majority of time with my customers and with our employees. And so, I think at that age, my advice to people is there was only one Steve Jobs. He just somehow knew what to build and how to build it. And when you think about where they were, it still took him seven years (laughs). I would say, really get close to your customers, don't get too far away; if there's one golden rule that a start-up ought to think about, it's learning and staying close to your customers. There too, understand your differentiation and your strategy. Well John, thanks so much. And the book, Connecting the Dots, great read, it's again, not a business book in the sense of boring, a lot of personal stories, a lot of great lessons and thanks so much for giving the time for our conversation. >> John, it was my pleasure. Great to see you again. >> I'm John Furrier here with the People First interview on theCUBE, co-created content with Mayfield. Thanks for watching! (upbeat electronic music)

>> Live from the MIT campus in Cambridge, Massachusetts, it's theCUBE, covering the 12th Annual MIT Chief Data Officer and Information Quality Symposium. Brought to you by SiliconANGLE Media. >> Welcome back to theCUBE's coverage of MIT CDOIQ here in Cambridge, Massachusetts. I'm your host Rebecca Knight along with my cohost Peter Burris. We have two guests on this segment. We have Cortnie Abercrombie, she is the founder of the nonprofit AI Truth, and Carl Gerber, who is the managing partner at Global Data Analytics Leaders. Thanks so much for coming on theCUBE Cortnie and Carl. >> Thank you. >> Thank you. >> So I want to start by just having you introduce yourselves to our viewers, what you do. So tell us a little bit about AI Truth, Cortnie. >> So this was born out of a passion. As I, the last gig I had at IBM, everybody knows me for chief data officer and what I did with that, but the more recent role that I had was developing custom offerings for Fortune 500 in the AI solutions area, so as I would go meet and see different clients, and talk with them and start to look at different processes for how you implement AI solutions, it became very clear that not everybody is attuned, just because they're the ones funding the project or even initiating the purpose of the project, the business leaders don't necessarily know how these things work or run or what can go wrong with them. And on the flip side of that, we have very ambitious up-and-comer-type data scientists who are just trying to fulfill the mission, you know, the talent at hand, and they get really swept up in it. To the point where you can even see that data's getting bartered back and forth with any real governance over it or policies in place to say, "Hey, is that right? Should we have gotten that kind of information?" Which leads us into things like the creepy factor. Like, you know target (laughs) and some of these cases that are well-known. And so, as I saw some of these mistakes happening that were costing brand reputation, our return on investment, or possibly even creating opportunities for risk for the companies and for the business leaders, I felt like someone's got to take one for the team here and go out and start educating people on how this stuff actually works, what the issues can be and how to prevent those issues, and then also what do you do when things do go wrong, how do you fix it? So that's the mission of AI Truth and I have a book. Yes, power to the people, but you know really my main concern was concerned individuals, because I think we've all been affected when we've sent and email and all of a sudden we get a weird ad, and we're like, "Hey, what, they should not, is somebody reading my email?" You know, and we feel this, just, offense-- >> And the answer is yes. >> Yes, and they are, they are. So I mean, we, but we need to know because the only way we can empower ourselves to do something is to actually know how it works. So, that's what my missions is to try and do. So, for the concerned individuals out there, I am writing a book to kind of encapsulate all the experiences that I had so people know where to look and what they can actually do, because you'll be less fearful if you know, "Hey, I can download DuckDuckGo for my browser, or my search engine I mean, and Epic for my browser, and some private, you know, private offerings instead of the typical free offerings. There's not an answer for Facebook yet though. >> So, (laughs) we'll get there. Carl, tell us a little bit about Global Data Analytics Leaders. >> So, I launched Analytics Leaders and CDO Coach after a long career in corporate America. I started building an executive information system when I was in the military for a four-star commander, and I've really done a lot in data analytics throughout my career. Most recently, starting a CDO function at two large multinational companies in leading global transformation programs. And, what I've experienced is even though the industries may vary a little bit, the challenges are the same and the patterns of behavior are the same, both the good and bad behavior, bad habits around the data. And, through the course of my career, I've developed these frameworks and playbooks and just ways to get a repeatable outcome and bring these new technologies like machine learning to bear to really overcome the challenges that I've seen. And what I've seen is a lot of the current thinking is we're solving these data management problems manually. You know, we all hear the complaints about the people who are analysts and data scientists spending 70, 80% of their time being a data gatherer and not really generating insight from the data itself and making it actionable. Well, that's why we have computer systems, right? But that large-scale technology in automation hasn't really served us well, because we think in silos, right? We fund these projects based on departments and divisions. We acquire companies through mergers and acquisitions. And the CDO role has emerged because we need to think about this, all the data that an enterprise uses, horizontally. And with that, I bring a high degree of automation, things like machine learning, to solve those problems. So, I'm now bottling that and advising my clients. And at the same time, the CDO role is where the CIO role was 20 years ago. We're really in it's infancy, and so you see companies define it differently, have different expectations. People are filling the roles that may have not done this before, and so I provide the coaching services there. It's like a professional golfer who has a swing coach. So I come in and I help the data executives with upping their game. >> Well, it's interesting, I actually said the CIO role 40 years ago. But, here's why. If we look back in the 1970s, hardcore financial systems were made possible by the technology which allowed us to run businesses like a portfolio: Jack Welch, the GE model. That was not possible if you didn't have a common asset management system, if you didn't have a common cached management system, etc. And so, when we started creating those common systems, we needed someone that could describe how that shared asset was going to be used within the organization. And we went from the DP manager in HR, the DP manager within finance, to the CIO. And in many respects, we're doing the same thing, right? We're talking about data in a lot of different places and now the business is saying, "We can bring this data together in new and interesting ways into more a shared asset, and we need someone that can help administer that process, and you know, navigate between different groups and different needs and whatnot." Is that kind of what you guys are seeing? >> Oh yeah. >> Yeah. >> Well you know once I get to talking (laughs). For me, I can going right back to the newer technologies like AI and IOT that are coming from externally into your organization, and then also the fact that we're seeing bartering at an unprec... of data at an unprecedented level before. And yet, what the chief data officer role originally did was look at data internally, and structured data mostly. But now, we're asking them to step out of their comfort zone and start looking at all these unknown, niche data broker firms that may or may not be ethical in how they're... I mean, I... look I tell people, "If you hear the word scrape, you run." No scraping, we don't want scraped data, no, no, no (laugh). But I mean, but that's what we're talking about-- >> Well, what do you mean by scraped data, 'cause that's important? >> Well, this is a well-known data science practice. And it's not that... nobody's being malicious here, nobody's trying to have a malintent, but I think it's just data scientists are just scruffy, they roll up their sleeves and they get data however they can. And so, the practice emerged. Look, they're built off of open-source software and everything's free, right, for them, for the most part? So they just start reading in screens and things that are available that you could see, they can optical character read it in, or they can do it however without having to have a subscription to any of that data, without having to have permission to any of that data. It's, "I can see it, so it's mine." But you know, that doesn't work in candy stores. We can't just go, or jewelry stores in my case, I mean, you can't just say, "I like that diamond earring, or whatever, I'm just going to take it because I can see it." (laughs) So, I mean, yeah we got to... that's scraping though. >> And the implications of that are suddenly now you've got a great new business initiative and somebody finds out that you used their private data in that initiative, and now they've got a claim on that asset. >> Right. And this is where things start to get super hairy, and you just want to make sure that you're being on the up-and-up with your data practices and you data ethics, because, in my opinion, 90% of what's gone wrong in AI or the fear factor of AI is that your privacy's getting violated and then you're labeled with data that you may or may not know even exists half the time. I mean. >> So, what's the answer? I mean as you were talking about these data scientists are scrappy, scruffy, roll-up-your-sleeves kind of people, and they are coming up with new ideas, new innovations that sometimes are good-- >> Oh yes, they are. >> So what, so what is the answer? Is this this code of ethics? Is it a... sort of similar to a Hippocratic Oath? I mean how would you, what do you think? >> So, it's a multidimensional problem. Cortnie and I were talking earlier that you have to have more transparency into the models you're creating, and that means a significant validation process. And that's where the chief data officer partners with folks in risk and other areas and the data science team around getting more transparency and visibility into what's the data that's feeding into it? Is it really the authoritative data of the company? And as Cortnie points out, do we even have the rights to that data that's feeding our models? And so, by bringing that transparency and a little more validation before you actually start making key, bet-the-business decisions on the outcomes of these models, you need to look at how you're vetting them. >> And the vetting process is part technology, part culture, part process, it goes back to that people process technology trying. >> Yeah, absolutely, know where your data came from. Why are you doing this model? What are you doing to do with the outcomes? Are you actually going to do something with it or are you going to ignore it? Under what conditions will you empower a decision-maker to use the information that is the output of the model? A lot of these things, you have to think through when you want to operationalize it. It's not just, "I'm going to go get a bunch of data wherever I can, I put a model together. Here, don't you like the results?" >> But this is Silicon Valley way, right? An MVP for everything and you just let it run until... you can't. >> That's a great point Cortnie (laughs) I've always believed, and I want to test this with you, we talk about people process technology about information, we never talk about people process technology and information of information. There's a manner of respects what we're talking about is making explicit the information about... information, the metadata, and how we manage that and how we treat that, and how we defuse that, and how we turn that, the metadata itself, into models to try to govern and guide utilization of this. That's especially important in AI world, isn't it? >> I start with this. For me, it's simple, I mean, but everything he said was true. But, I try to keep it to this: it's about free will. If I said you can do that with my data, to me it's always my data. I don't care if it's on Facebook, I don't care where it is and I don't care if it's free or not, it's still my data. Even if it's X23andMe, or 23andMe, sorry, and they've taken the swab, or whether it's Facebook or I did a google search, I don't care, it's still my data. So if you ask me if it's okay to do a certain type of thing, then maybe I will consent to that. But I should at least be given an option. And no, be given the transparency. So it's all about free will. So in my mind, as long as you're always providing some sort of free will (laughs), the ability for me to having a decision to say, "Yes, I want to participate in that," or, "Yes, you can label me as whatever label I'm getting, Trump or a pro-Hillary or Obam-whatever, name whatever issue of the day is," then I'm okay with that as long as I get a choice. >> Let's go back to it, I want to build on that if I can, because, and then I want to ask you a question about it Carl, the issue of free will presupposes that both sides know exactly what's going into the data. So for example, if I have a medical procedure, I can sit down on that form and I can say, "Whatever happens is my responsibility." But if bad things happen because of malfeasance, guess what? That piece of paper's worthless and I can sue. Because the doctor and the medical provider is supposed to know more about what's going on than I do. >> Right. >> Does the same thing exist? You talked earlier about governance and some of the culture imperatives and transparency, doesn't that same thing exist? And I'm going to ask you a question: is that part of your nonprofit is to try to raise the bar for everybody? But doesn't that same notion exist, that at the end of the day, you don't... You do have information asymmetries, both sides don't know how the data's being used because of the nature of data? >> Right. That's why you're seeing the emergence of all these data privacy laws. And so what I'm advising executives and the board and my clients is we need to step back and think bigger about this. We need to think about as not just GDPR, the European scope, it's global data privacy. And if we look at the motivation, why are we doing this? Are we doing it just because we have to be regulatory-compliant 'cause there's a law in the books, or should we reframe it and say, "This is really about the user experience, the customer experience." This is a touchpoint that my customers have with my company. How transparent should I be with what data I have about you, how I'm using it, how I'm sharing it, and is there a way that I can turn this into a positive instead of it's just, "I'm doing this because I have to for regulatory-compliance." And so, I believe if you really examine the motivation and look at it from more of the carrot and less of the stick, you're going to find that you're more motivated to do it, you're going to be more transparent with your customers, and you're going to share, and you're ultimately going to protect that data more closely because you want to build that trust with your customers. And then lastly, let's face it, this is the data we want to analyze, right? This is the authenticated data we want to give to the data scientists, so I just flip that whole thing on its head. We do for these reasons and we increase the transparency and trust. >> So Cortnie, let me bring it back to you. >> Okay. >> That presupposes, again, an up-leveling of knowledge about data privacy not just for the executive but also for the consumer. How are you going to do that? >> Personally, I'm going to come back to free will again, and I'm also going to add: harm impacts. We need to start thinking impact assessments instead of governance, quite frankly. We need to start looking at if I, you know, start using a FICO score as a proxy for another piece of information, like a crime record in a certain district of whatever, as a way to understand how responsible you are and whether or not your car is going to get broken into, and now you have to pay more. Well, you're... if you always use a FICO score, for example, as a proxy for responsibility which, let's face it, once a data scientist latches onto something, they share it with everybody 'cause that's how they are, right? They love that and I love that about them, quite frankly. But, what I don't like is it propagates, and then before you know it, the people who are of lesser financial means, it's getting propagated because now they're going to be... Every AI pricing model is going to use FICO score as a-- >> And they're priced out of the market. >> And they're priced out of the market and how is that fair? And there's a whole group, I think you know about the Fairness Accountability Transparency group that, you know, kind of watch dogs this stuff. But I think business leaders as a whole don't really think through to that level like, "If I do this, then this this and this could incur--" >> So what would be the one thing you could say if, corporate America's listening. >> Let's do impact. Let's do impact assessments. If you're going to cost someone their livelihood, or you're going to cost them thousands of dollars, then let's put more scrutiny, let's put more government validation. To your point, let's put some... 'cause not everything needs the nth level. Like, if I present you with a blue sweater instead of a red sweater on google or whatever, (laughs) You know, that's not going to harm you. But it will harm you if I give you a teacher assessment that's based on something that you have no control over, and now you're fired because you've been laid off 'cause your rating was bad. >> This is a great conversation. Let me... Let me add something different, 'cause... Or say it a different way, and tell me if you agree. In many respects, it's: Does this practice increase inclusion or does this practice decrease inclusion? This is not some goofy, social thing, this is: Are you making your market bigger or are you making your market smaller? Because the last thing you want is that the participation by people ends with: You can't play because of some algorithmic response we had. So maybe the question of inclusion becomes a key issue. Would you agree with that? >> I do agree with it, and I still think there's levels even to inclusion. >> Of course. >> Like, you know, being a part of the blue sweater club versus the (laughs) versus, "I don't want to be a convict," you know, suddenly because of some record you found, or association with someone else. And let's just face it, a lot of these algorithmic models do do these kinds of things where they... They use n+1, you know, a lot... you know what I'm saying. And so you're associated naturally with the next person closest to you, and that's not always the right thing to do, right? So, in some ways, and so I'm positing just little bit of a new idea here, you're creating some policies, whether you're being, and we were just talking about this, but whether you're being implicit about them or explicit, more likely you're being implicit because you're just you're summarily deciding. Well, okay, I have just decided in the credit score example, that if you don't have a good credit threshold... But where in your policies and your corporate policy did it ever say that people of lesser financial means should be excluded from being able to have good car insurance for... 'cause now, the same goes with like Facebook. Some people feel like they're going to have to opt of of life, I mean, if they don't-- >> (laughs) Opt out of life. >> I mean like, seriously, when you think about grandparents who are excluded, you know, out in whatever Timbuktu place they live, and all their families are somewhere else, and the only way that they get to see is, you know, on Facebook. >> Go back to the issue you raised earlier about "Somebody read my email," I can tell you, as a person with a couple of more elderly grandparents, they inadvertently shared some information with me on Facebook about a health condition that they had. You know how grotesque the response of Facebook was to that? And, it affected me to because they had my name in it. They didn't know any better. >> Sometimes there's a stigma. Sometimes things become a stigma as well. There's an emotional response. When I put the article out about why I left IBM to start this new AI Truth nonprofit, the responses I got back that were so immediate were emotional responses about how this stuff affects people. That they're scared of what this means. Can people come after my kids or my grandkids? And if you think about how genetic information can get used, you're not just hosing yourself. I mean, breast cancer genes, I believe, aren't they, like... They run through families, so, I-- >> And they're pretty well-understood. >> If someone swabs my, and uses it and swaps it with other data, you know, people, all of a sudden, not just me is affected, but my whole entire lineage, I mean... It's hard to think of that, but... it's true (laughs). >> These are real life and death... these are-- >> Not just today, but for the future. And in many respects, it's that notion of inclusion... Going back to it, now I'm making something up, but not entirely, but going back to some of the stuff that you were talking about, Carl, the decisions we make about data today, we want to ensure that we know that there's value in the options for how we use that data in the future. So, the issue of inclusion is not just about people, but it's also about other activities, or other things that we might be able to do with data because of the nature of data. I think we always have to have an options approach to thinking about... as we make data decisions. Would you agree with that? Yes, because you know, data's not absolute. So, you can measure something and you can look at the data quality, you can look at the inputs to a model, whatever, but you still have to have that human element of, "Are you we doing the right thing?" You know, the data should guide us in our decisions, but I don't think it's ever an absolute. It's a range of options, and we chose this options for this reason. >> Right, so are we doing the right thing and do no harm too? Carl, Cortnie, we could talk all day, this has been a really fun conversation. >> Oh yeah, and we have. (laughter) >> But we're out of time. I'm Rebecca Knight for Peter Burris, we will have more from MIT CDOIQ in just a little bit. (upbeat music)

(upbeat music) >> Welcome to this special CUBEConversation here in the Palo Alto CUBE studio. I'm John Furrier, the co-host, theCUBE co-founder of SiliconANGLE Media. In theCUBE we're here with Alan Cohen, CUBE alumni, joining us today for a special segment on the future of technology and the impact to society. Always good to get Alan's commentary, he's the Chief Commercial Officer for Illumio, industry veteran, has been through many waves of innovation and now more than ever, this next wave of technology and the democratization of the global world is upon us. We're seeing signals out there like cryptocurrency and blockchain and bitcoin to the disruption of industries from media and entertainment, biotech among others. Technology is not just a corner industry, it's now pervasive and it's having some significant impacts and you're seeing that in the news whether it's Facebook trying to figure out who they are from a data standpoint to across the board every company. Alan, great to see you. >> Always great to be here, I always feel like, I can't tell whether I'm at the big desk at ESPN or I've got the desk chair at CNBC, but that's what it's like being on theCUBE. >> Great to have you on extracting the signal noises, a ton of noise out there, but one of things of the most important stories that we're tracking is, that's becoming very obvious, and you're seeing it everywhere from Meed to all aspects of technology. Is the impact of technology to people in society, okay you're seeing the election, we all know what that is, that's now a front and center in the big global conversation, the Russian's role of hacking, the weaponizing of data, Facebook's taking huge brand hits on that, to emerging startups, and the startup game that we're used to in Silicon Valley is changing. Just the dynamics, I mean cryptocurrency raises billions of dollars but yet (laughs) something like 10, 20% of it's been hacked and stolen. It's a really wild west kind of environment. >> Well it's a very different environment. John, you and I have been in the technology industry certainly for a whole bunch of lines under our eyes over the years have gone there. My friend Tom Friedman has this phrase that he says, "Everybody's connected and nobody's in control," so the difference is that, as you just said, the tech industry is not a separate industry. The tech industry is in every product and service. Cryptocurrency is like, the concept of that money is just code. You know, our products and services are just code, it raises a couple of really core issues. Like for us on the security point of view, if I don't trust people with the products they're selling me, that I feel like they're going to be hacked, including my personal data, so your product now includes my personal information, that's a real problem because that could actually melt down commerce in a real way. Obviously the election is if I don't trust the social systems around it, so I think we're all at an, and I'd like to say world is still kind of like iRobot moment, and if you remember iRobot, it's like, people build all these robots to serve humankind and then one day the robots wake up and they go, "We have our own point of view on how things are going to work" and they take over, and I think whether it's the debate about AI, whether cryptocurrency's good or bad, or more importantly, the products and services I use, which are now all digitally connected to me, whether I trust them or not is an issue that I think everyone in our industry has to take a step back because without that trust, a lot of these systems are going to stop growing. >> Chaos is an opportunity, I think that's been quoted many times, a variety-- >> You sound like Jeff Goldblum in like Jurassic Park, yeah. (laughing) >> So chaos is upon us, but this is an opportunity. The winds are shifting, and that's an opportunity for entrepreneurs. The technology industry has to start working for us but we've got to be mindful of these blind spots and the blind spots are technology for good not necessarily just for profits, so that also is a big story right now. We see things like AI for good, Intel has been doing a lot of work on that area, and you see stars dedicated to societal impact, then young millennials, you see the demographic shift where they want to work on stuff that empowers people and changes society so a whole kind of new generation revolution and kind of hippie moment, if you look at the 60s, what the 60s were, right? >> Well there's people out in the street protesting, right? There were a couple of million women out in the street this weekend, so we are in that kind of moment again, people are not happy with things. >> And I believe this is a signal of a renaissance, a change, a sea change at enormous levels, so I want to get your thoughts on this. As technology goes out in mainstream, certainly from a security standpoint, your business Illumio is in that now where there's not a lot of control, just like you were mentioning before we came on that all the spends happening but no one has more than 4% market share. These are dynamics and this is not just within one vertical. What's your take on this, how do you view this sea change that's upon us, this tech revolution? >> Well, you know, think about it. You and I grew up in the era where clients server took over from main frame, right? So remember there was this big company called IBM and they owned a lot of the industry, and then it blew up for client server and then there were thousands of companies and it consolidated its way down, but when those thousands of new companies, like you didn't know what was going to be Apollo and what was going to be Oracle right? Like you didn't know how that was going to work out, there was a lot of change and a lot of uncertainty. I think now we're seeing this on a scale like that's 10x of this that there's so much innovation and there's so much connectedness going on very rapidly, but no one is in control. In the security market, you know, what's happening in our world is like, people said, okay I have to reestablish control over my data, I've lost that control, and I've lost it for good reasons, meaning I've evolved to the cloud, I've evolved to the app economy, I've done all of these things, and I've lost it for bad reasons because like am I, like I'm not really running my data center the way I should. We're in the beginning of a move in of people kind of reasserting that control, but it's very hard to put the genie back in the bottle because the world itself is so much more dynamic and more distributed. >> It's interesting, I've been studying communities and online communities for over a decade in terms of dynamics. You know, from the infrastructural level, how packets move to a human interaction. It's interesting, you mentioned that we're all connected and no one's in control, but you now see a ground swell of organic self-forming networks where communities are starting to work together. You kind of think about the analog world when we grew up without computers and networks, you kind of knew everyone, you knew your neighbor, you knew who the town loony was, you kind of knew things and people watch each other's kids and parents sat from the porch, let the kid play, that's the way that I grew up, but it was still chaotic but yet somewhat controlled by the group. So I got to ask you, when you see things like cryptocurrency, things like KYC, know your customer, anti money laundering, which is, you know these are policy based things, but we're in a world now where, you know, people don't know who their neighbors are. You're starting to see a dynamic where people are-- >> Put the phone down. >> Asserting themselves to know their neighbor, to know their customer, to have a connected tissue with context and so your trust and reputation become super important. >> Well I think people are really, so like every time there is a shift in technology, there's scary stuff. There's the fuddy-duddy moment where people are saying, "Oh we can't use that," or "I don't know that," and you know, clearly we're in this kind of new kam-ree and explosion of this cloud mobile blah blah blah type of computing thing and ... Blah blah blah is always a good intersection when you don't have a term. Then things form around it, and just as you said, so if you think about 25 years ago, right, people created The WELL and there was community writing first bulletin boards and like now we have Facebook and you go through a couple of generations and for a while, things feel out of control and then it reforms. I personally am an optimist. Ultimately I believe in the inherent goodness of people, but inherent goodness leaves you open and then, you know, could be manipulated, and people figure these things out. Whether it's cryptocurrency or AI, they are really exciting technologies that don't have any ground rules, right? What's going to happen I believe is that people are going to reestablish ground rules, they're going to figure out some of the core issues, and some of these things may make it, and some of these things may not make it. Like cryptocurrency, like I don't know whether it makes it or not, but certainly the blockchain as a technology we're going to be incorporating in what we do, and maybe the blockchain replaces VPNs and last generation's way of protecting zeros and ones. If AI is figuring out how to read an MRI in five minutes, it's a good thing, and if the AI is teaching you how to exclude old folks for me finding jobs, it's a bad thing. I think as technology forms, there's always Spectre and 007, right? There's always good and bad sides and you know, I think if you believe-- >> I'm with you on that. I think value shifts and I think ultimately it's like however you want to look at it will shift to something, value activity will be somewhere else. Behind me in the bookshelf is a book called The World is Flat and you're quoted in it a lot as a futurist because you have inherently that kind of view, well that's not what you do for a living, but you're kind of in an opt-- >> Alan: Marketing, futurist, kind of same thing. >> Thomas Friedman, the book, that was a great book and at that time, it was game changing. If you take that premise into today where we are living in a flat world and look at cryptocurrency, and then over with the geo political landscape, I mean I just can't see why the Federal Reserve wouldn't reign in this cryptocurrency because if Japan's going to control a bunch of, or China, it's going to be some interesting conversations. I mean I would be like all over that if I was in the Federal Reserve. >> I think people-- Look, cryptocurrency's really interesting and I think people a little over-rotated. If you look at the amount of GDP that's invested in cryptocurrency, it's like, I don't know, there might've been, you know 20 years ago the same amount involved invested in Beanie Babies, right? I mean things show up for a while and the question is is it sustainable over time? Now I'm trained as an economist, you and I have had this conversation, so I don't know how you have a series of monetary without kind of governmental backing, I just don't understand. But I do understand that people find all kinds of interesting ways to trade, and if it's an exchange, like I mean what's the difference between gold and cryptocurrency? Somebody has ascribed a value to something that really has no efficacy outside of its usage. Yeah I mean you can make a filling or bracelets out of gold but it doesn't really mean anything except people agree to a unit of value. If people do that with cryptocurrency, it does have the ability to become a real currency. >> I want to pick your perspective on this being an economist, this is is the hottest area of cryptocurrency, it's also known as token economics, is a concept. >> Alan: Token economics. >> You know that's an area that theCUBE, with CUBE coins, experimenting with tokens. Tokens technically are used for things in mobile and whatnot but having a token as a utility in a network is kind of the whole concept, so the big trend that we're seeing and no one's really talking about this yet is instead of having a CTO, Chief Technology Officer, they're looking for a CEO, a Chief Economist Officer, because what you're seeing with the MVP economy we're living in and this gamification which became growth hack which didn't really help users, the notion of decentralized applications and token economics can open the door for some innovation around value and it's an economic problem, how you have a fiscal policy of your token, there's a monetary policy, what's it tied to? A product and a technology, so you now have a now a new, twisted, intertwined mechanism. >> Well you have it as part of this explosion, right? We're at a period of time, it feels like there's a great amount of uncertainly because everything's, you know, there's a lot of different forces and not everybody's in control of them, and you know, it's interesting. Google has this architecture, they call it BeyondCorp, where the concept is like networks are not trusted so I will just put my trust in this device, Duo Security's a great example of a company that's built a technology, a security technology around it which is completely antithetical to everything we know about networks and security. They're saying everything's the internet, I'll just protect the device that it's on. It's a kind of perfect architecture for a world like where nobody is in charge, so just isolate those, buy this, what is a device? It's a token too, it's a person, your iPhone's your personal token. Then over time, systems will form around it. I think we just have to, we always have to learn how to function in a different type of economy. I mean democracy was a new economy 250 years ago that kind of screwed around with most of the world, and a lot of people didn't think it would make it, in fact we went through two World War wars that it was a little on the edge whether democracy was going to make it and it seems to have done okay, like it was pretty good IPO to buy into. You know, in 1776. But it's always got risks and struggles with it. I think if, ultimately it comes together, it's whether a large group of people can find a way to function socially, economically, and with their personal safety in these systems. >> You bring up a great point, so I want to go to the next level in this conversation which is around-- >> Alan: You've got the wrong guy if you're going to the next level because I just tapped out. >> No, no, no we'll get you there. It's my job to get you there. The question is that everyone always wants to look at, whether it's someone looking at the industry or actors inside the industries across the board, mainly the tech and we'll talk about tech, is the question of are we innovating? You brought up some interesting nuances that we talk about with token economics. I mean Steve Jobs had the classic presentation where he had street signs, technology meets liberal arts. That's a mental image that people who know Steve Jobs, know Apple, was a key positioning point for Apple at that time which was let's make computers and technology connect with society, liberal arts. But we were just talking about is the business impact of technology, the economics, and that's just not like just some hand waving, making technology integrate with business. You're in the security business, There are some gamification technology, gamification that's business built into the products. So the question is, if we have the integration of business, technology, economics, policy, society rolling into the product definitions of innovation, does that change the lens and the aperture of what innovation is? >> I think it does, right? The IT industry's somewhere between three and four trillion dollars depends on how it counts in. It grows pretty slowly, it grows by a low single digit. That tells me as composite, like is that, that slow growth is a structural signal about how consumers of technology think in a macro sense. On a micro sense, things shift very rapidly, right? New platforms show up, new applications show up, all kinds of things show up. What I don't think we have done yet, to your point, is in this new integrated world, the role of technology is not just technology anymore. I don't think, you know you said you need Chief Economical Officer, what about Chief Political Officer? What about a Chief Social Officer? How many heads of HR make decisions about the insertion of systems into their business? And that's what this kind of iRobot concept is in my mind which is that you know, we are exceeding control of things that used to be done by human beings to systems and when you see control, the social mores, the political mores, the cultural mores, and the human emotional mores have to move with it. We don't tend to think about things like that. We're like, "I win and my competitors lose." Like technology used to be much more of a zero sum, my tech's better than yours. But the question is not just is my tech better than yours, is my customer better off in their industry for the consumption of my technology of inserting it into their offering or their service? You know what, that is probably going to be the next area of study. The other thing that's very important in whether, any of you have read Peter Thiel's book Zero to One, the nature of competition technology used to feel like a flat playing field and now the other thing that's rising is do you have super winners? And then what is the power of the super winners? So you mentioned whether it's Facebook or Google or Amazon or you know, or Microsoft, the FANG companies right? Their roles are so much more significant now than the Four Horsemen of the Nasdaq were in 2000 when you had Intel and Cisco and Oracle and Saht-in it's a different game. >> You're seeing that now. That's a good point, so you're reinforcing kind of this notion that the super players if you will are having an impact, you're mentioning the confluence of these new sectors, you know, government, policy, social are new areas. The question is, this sounds like a strategic imperative for the industry, and we're early so it's not like there's a silver bullet or is there, it doesn't sound like there, so to me that's not really in place yet, I mean. >> Oh no. We're not even in alpha. We have demo code for the new economy and we're trying to get the new model funded. >> John: That's the demo version, not the real version. It's the classic joke. >> Yeah this not the alpha or the beta version that like you're going to go launch it. If people think they're launching it, I think it's a little preliminary and you know, it's not just financial investment, it's like do I buy in? I'll tell you something that's really interesting. I've been visiting a bunch of our customers lately and the biggest change I'd say in the last two years is they now have to prove to their customers they're going to be good custodians of their data. Think about that, like you could go to any digital commerce you do, any website you use and you give them basically the ticket to the Furrier family privacy, you do, but you don't spend a lot of time questioning whether they're really going to protect your data. That has changed. And it's really changing in B2B and in government organizations. >> The role of data to us is regulation, GDPR in Europe, but this is a whole new dynamic. >> It's not just my data because I'm worried about my credit card getting hacked, I'm worried about my identity. Like am I going to show up as a meme in some social media feed that's substituted for the news? I don't want to use the FN word, but you know what I mean? It is a really brave new world. It's like a hyper-democracy and a hyper-risky state at the same time. >> We're living in an area of massive pioneering, new grounds, this is new territory so there's a lot of strategic imperatives that are yet not defined. So now let's take it to how people compete. We were talking before we came on camera, you mentioned the word we're in an MVP economy, minimum viable product concept, and you're seeing that being a standard operating procedure for essentially de-risking this challenge. The old way of you know, build it, ship it, will it work? We're seeing the impact from Hollywood to big tech companies to every industry. >> Well you've got a coffee mug for a company that does both. Amazon does MVP in entertainment, like we'll create one pilot and see if it goes as opposed to ordering a season for 17 million dollars to hey, let's try this feature and put it out on AWS. What's interesting is I don't think we've completely tilted but the question is will buyers of technology, of entertainment products, of any product start to say, "I'll try it." You know like, look, I've done four startups and I always know there's somebody I can go to get and try my early product. There are people that just have an appetite, right? The Jeffrey Moores, early adapter, all the way to the left of the-- >> They'll buy anything new. >> They'll try it, they're interested, they have the time and the resources, or they're just intellectually curious. But it was always a very small group of people in the IT industry. What I think that the MVP economy is starting to do is look, I Kickstarted my wallet. I don't know if I'm the only person who bought that skinny little wallet on Kickstarter, it doesn't matter to me, it had appeal. >> What's the impact of the MVP economy? Is it going to change to the competitive landscape like Peter Thiel was suggesting? Does it change the economics? Does it change the makeup of the team? All of the above? What's your thoughts on how this is going to impact? Certainly the encumbrance will seem to be impacted or not. >> I think two things happen. One, it attacks the structural way markets work. If you go back to classical economics, land, labor, and capital, and people who own those assets, now you add information as a fourth. If those guys were around now they would say that would be the fourth core asset, production, I'm sorry, means of production is the term. The people who can dominate that would dominate a market. Now that that's flattened out, you know, I think it pushes against the traditional structures and it allows new giants to kind of show up overnight. I mean the e-commerce market is rife with companies that have, like look at Stich Fix. A company driven by AI, fashions, tries to figure out what you like, sends it to you every month, just had a monster IPO. We invented, by the way the Spiegal Catalog, except like with a personal assistant and you know, it's changed that in just a short number of years. I think two things happen. One is you'll get new potential giants but certainly new players in the market quickly. Two, it'll force a change in the business model of every company. If you're in a cab in any city in the world, I'm not saying whether the app works there or not, Uber and Lyft has forced every cab company to show you here's the app to call the cab. They haven't quite caught up to the rest of the experience. What I think happens is ultimately, the larger players in an industry have to accommodate that model. For people like me, people who build companies or large technology companies, we may have to start thinking about MVPing of features early on, working with a small group, which is a little what the beta process is but now think about it as a commercial process. Nobody does it, but I bet sure a lot of people will be doing it in five years. >> I want to get your take on that approach because you're talking about really disrupting, re-imagining industry, the Spiegal catalog now becomes digital with technology, so the role of technology in business, we kind of talked about the intertwine of that and its nuance, it's going to get better in my opinion. But specifically the IT, the information technology industry is being disrupted. Used to be like a department, and the IT department will give you your phone on your desk, your PC on your desk or whatever, now that's being shattered and everyone that's participating in that IT industry is evolving. What's your take on the IT industry's disruption? >> Well look, it started 20 years ago when Marc Benioff and Salesforce decided to sell the sales forces instead of IT people, right? They went around to the end buyer. I don't think it's a new trend, I think a lot of technology leaders now figure out how to go to the business buyer directly and make their pitch and interestingly enough, the business buyer, if the IT team doesn't get on board, will do that. >> John: Because of cloud computing and ... >> Because of everything. The modern analog I think in our world is that the developers are increasingly in control. Like my friend Martin Casado up in Andreessen talks about this a lot. The traditional model on our industry is you build a product, you launch it, you launch your company, you work with the traditional analyst firms, you try to get a little bit of halo, you get customer references, those are the things you do and there was a very wall structured, for example, enterprise buying cycle. >> And playbook. >> Playbook, and there's the challenger sale and there's Jeffrey Moore and there's like seeing God. You've got your textbooks on how it's been done. As everything turns into code, the people who work with code for a living increasingly become the front end of your cycle and if you can get to them, that changes. Like I mean think about like, you know, Tom wrote about this actually in The World is Flat, like Linux started as a patchy. It didn't start with the IT department, it started with developers and there was the Linux foundation and now Linux is everything. >> There's a big enemy called the big mini computer, and not operating systems and work stations. >> Wiped out whole parts of Boston and other parts of the world, right? >> Exactly, that's why I moved out here. >> You filed client's server out here. >> I filed a smell of innovation. No but this is interesting because this location of industries is happening, so with that, so they also on the analog, so Martin's at Andreessen, so we'll do a little VC poke there at the VCs because we love them of course, they're being dislocated-- >> I don't (mumbles) my investors. >> Well no, their playbook is being challenged. Here's an example, go big or go home investment thesis seems not to be working. Where if you get too much cash on the front end, with the MVP economy we were just riffing on and with the big super powers, the Amazons and the Googles, you can't just go big or go home, you're going to be going home more than going big. >> I think they know that. I mean Dee-nuh Suss-man who's I think Chief Investment Officer at Nasdaq has a very well known talking line that there are half as many public companies as there were 10 years ago, so the exit scenario for our industry is a little bit different. We now have things like acqui-hires, right we have other models for monetization, but I think what the flip side of it is, we're in the-- >> Adapt or die because the value will shift. Liquidity's changing, which acqui-hires-- >> I think the investment community gets it completely and they spend a lot more time with the developer mindset. In fact I think there's been a doubling down focus on technical founders versus business founders for companies for just that reason because as everything turns to code, you got to hang out with the code community. I think there are actually-- >> You think there'll be more doubling down on technical founders? You do, okay. >> Yeah I think because that is ultimately the shift. There are business model shifts, but it's, you know, I mean like Uber was a business model shift, I mean the technology was the iPhone and GPS and they wrote an app for it, but it was a business model shift, so it can be a business model shift. >> And then scale. >> And then scale and then all of those other things. But I think if you don't think about developers when you're in our, and it's like we built Illumio because a developer could take the product and get started. I mean you can, developers actually can write security policy with our product because there's a class of customers, where as not everyone where that matters. There's other people where the security team is in charge or the infrastructure team is in charge but I think everything is based on zeros and ones and everything is based on code and if you're not sensitive to how code gets bought, consumed, I mean there's a GitHub economy which is I don't even have to write the code, I'll go look at your code and maybe use pieces of it, which has always been around. >> Software disruption is clear. Cloud computing is scale. Agile is fast, and with de-risking capabilities, but the craft is coming back and some will argue, we've talked about on theCUBE before is that, you know, the craftsmanship of software is moving to up the stack in every industry, so-- >> I think it's more like a sports league. I love the NBA, right? In the old days, your professional team, you'd scout people in college. Now they used to scout them in high school, now they're scouting kids in middle school. >> (laughs) That's sad. >> Well what it says is that you have to-- >> How can you tell? >> You know but they can, right? I think you know, your point about it craft, you're going to start tracking developers as they go through their career and invest and bet on them. >> Don't reveal our secrets to theCUBE. We have scouts everywhere, be careful out there. (laughs) >> But think about that, imagine it's like there's such a core focus on hiring from college, but we had an intern from high school two years ago. We hire freshman. >> Okay so let's go, I want to do a whole segment on this but I want to just get this point because we're both sports fans and we can riff on sports all day long. >> I'm just not getting the chance >> And the greatness of Tom Brady >> to talk about the Patriots. >> And Tom Brady's gotten his sixth finger attached to his hands for his sixth ring coming up. No but this is interesting. Sports is highly data driven. >> Alan: Yep. >> Okay and so what you're getting at here, with an MVP economy, token economics is more of a signal, not yet mainstream, but you can almost go there and think okay data driven gives you more accuracy so if you can bring data driven to the tech world, that's kind of an interesting point. What's your thoughts on that? >> Yeah I mean look, I think you have to track everything. You have to follow things, and by the way, we have great tools now, you can track people through LinkedIn. There's all kinds of vehicles to tracking individuals, you track products, you track everything, and you know look, we were talking about this before we went on the show right, people make decisions based on analytics increasingly. Now the craft part is what's interesting and I'm not the complete expert, I'm on the business side, I'm not an engineer by training, but look a lot of people understand a great developer is better than five bad developers. >> Well Mark Andris' 10x is a classic example of that. >> There's clearly a star system involved, so if I think in middle school or in high school, you're going to be a good developer, and I'm going to track your career through college and I'm going to try to figure out how to attach. That's why we started hiring freshmen. >> Well my good friend Dave Girouard started a company that does that, will fund the college education for people that they want to bet on. >> Sure, they're just taking an option in them. >> Yeah, option on their earnings. Exactly. >> They are. >> It sounds like token economics to me. (laughs) >> You know you can sell anything. We are in that economy, you can sell those pieces. The good news is I think it can be a great flattener, meaning that it can move things back more to a meritocracy because if I'm tracking people in high school, I'm not worrying whether they're going to go to Stanford or Harvard or Northwestern, right? I'm going to track their abilities in an era and it's interesting, speaking about craft, you know, what are internships? They're apprenticeships. I mean it is a little bit like a craft, right? Because you're basically apprenticing somebody for a future payout for them coming to work for you and being skilled because they don't know anything when they come and work, I shouldn't say that, they actually know a lot of things. >> Alan, great to have you on theCUBE as always, great to come in and get the update. We'll certainly do more but I'd like to do a segment on you on the startup scene and sort of the venture capital dynamics, we were tracking that as well, we've been putting a lot of content out there. We believe Silicon Valley's a great place. This mission's out there, we've been addressing them, but we really want to point the camera this year at some of the great stuff, so we're looking forward to having you come back in. My final question for you is a personal one. I love having these conversations because we can look back and also look forward. You do a lot of mentoring and you're also helping a lot of folks in the industry within just your realm but also startups and peers. What's your advice these days? Because there's a lot of things, we just kind of talked a lot of it. When people come to you for advice and say, "Alan, I got a career change," or "I'm looking at this new opportunity," or "Hey, I want to start a company," or "I started a company," how is your mentoring and your advisory roles going on these days? Can you share things that you're advising? Key points that people should be aware of. >> Well look, ultimately ... I never really thought about it, you just asked the question so, ultimately, I think to me it comes down to own your own fate. What it means is like do something that you're really passionate about, do something that's going to be unique. Don't be the 15th in any category. Jack Welch taught us a long time ago that the number one player in a market gets 70% of the economic value, so you don't want to play for sixth place. It's like Ricky Bobby said, if you're not first, you're last. (John chuckles) I mean you can't always be first, but you should play for that. I think for a lot of companies now, I think they have to make sure that, and people participating, make sure that you're not playing the old playbook, you're not fighting yesterday's battle. Rhett Butler in Gone With the Wind said, "There's a lot of money in building up an empire, "and there's even more money in tearing it down." There are people who enter markets to basically punish encumbrance, take share because of innovation, but I think the really inspirational is you know, look forward five years and find a practical but aggressive path to being part of that side of history. >> So are we building up or are we taking down? I mean it seems to me, if I'm not-- >> You're always doing both. The ocean is always fighting the mountains, right? That is the course of, right? And then new mountains come up and the water goes someplace else. We are taking down parts of the client server industry, the stack that you and I built a lot of our personal career of it, but we're building this new cloud and mobile stack at the same time. And you're point is we're building a new currency stack and we're going to have to build a new privacy stack. It's never, the greatest thing about our industry is there's always something to do. >> How has the environment of social media, things out there, we're theCUBE, we do our thing with events, and just in general, change the growth plans for individuals if you were, could speak to your 23 year old self right now, knowing what you know-- >> Oh I have one piece of advice I give everybody. Take as much risk as humanly possible in your career earlier on. There's a lot of people that have worked with me or worked for me over the years, you know people when they get into their 40s and they go, "I'm thinking about doing a startup," I go, "You know when you got two kids in college "and you're trying to fund your 401K, "working for less cash and more equity may not be "the most comfortable conversation in your household." It didn't work well in my household. I mean I'm like Benjamin Button. I started in big companies, I'm going to smaller companies. Some day it's just going to be me and a dog and one other guy. >> You went the wrong way. >> Yeah I went the wrong way and I took all the risk later. Now I was lucky in part that the transition worked. When I see younger folks, it's always like, do the riskiest thing humanly possible because the penalty is really small. You have to find a job in a year, right? But you know, you don't have the mortgage, and you don't have the kids to support. I think people have to build an arc around their careers that's suitable with their risk profile. Like maybe you don't buy into bitcoin at 19,000. Could be wrong, could be 50,000 sometime, but you know it's kind of 11 now and it's like-- >> Yeah don't go all in on 19, maybe take a little bit in. It's the play and run-- >> Dollar cost averaging over the years, that's my best fidelity advice. I think that's what's really important for people. >> What about the 45 year old executive out there, male or female obviously, the challenges of ageism? We're in economy, a gig economy, whatever you want to call, MVP economics, token economics, this is a new thing. Your advice to someone who's 45 who just says "Hey you're too old for our little hot startup." What should they do? >> Well being on the other side of that history I understand it firsthand. I think that you have an incumbent role in your career to constantly re-educate yourself. If you show up, whether you're a 25, 35, 45, 55, or 65, I hope I'm not working when I'm 75, but you never know right? (mumbles) >> You'll never stop working, that's my prediction. >> But you know have you mastered the new skills? Have you reinvented yourself along the way? I feel like I have a responsibility to feed the common household. My favorite part of my LinkedIn profile, it says, "Obedient worker bee at the Cohen household," because when I go home, I'm not in charge. I've always felt that it's up to me to make sure I'm not going to be irrelevant. That to me is, you know, that to me, I don't worry about ageism, I worry about did I-- >> John: Relevance. >> Yeah did I make myself self-obsolescent? I think if you're going to look at your career and you haven't looked at your career in 15 years and you're trying to do something, you may be starting from a deficit. So the question, what can I do? Before I make that jump, can I get involved, can I advise some small companies? Could I work part time and on the weekends and do some things so that when you finally make that transition, you have something to offer and you're relevant in the dialogue. I think that's, you know, nobody trains you, right? We're not good as an industry-- >> Having a good community, self-learning, growth mindset, always be relevant is not a bad strategy. >> Yeah, I mean because I find increasingly, I see people of all ages in companies. There is ageism, there is no doubt. There's financial ageism and then there's kind of psychological bias ageism, but if you keep yourself relevant and you are the up to speed in your thing, people will beat a path to want to work for you because there's still a skill gap in our industry-- >> And that's the key. >> Yeah, make sure that you're on the right side of that skill gap, and you will always have something to offer to people. >> Alan, great to have you come in the studio, great to see you, thanks for the commentary. It's a special CUBEConversation, we're talking about the future of technology impact the society and a range of topics that are emerging, we're on a pioneering, new generational shift and theCUBE is obviously covering the most important stories in Silicon Valley from figuring out what fake news is to impact to the humans around the world and again, we're doing our part to cover it. Alan Cohen, CUBEConversation, I'm John Furrier, thanks for watching. (upbeat music)

>> So as folks make their way over from Javits I'm going to give you the least interesting part of the evening and that's my segment in which I welcome you here, introduce myself, lay out what what we're going to do for the next couple of hours. So first off, thank you very much for coming. As all of you know Wikibon is a part of SiliconANGLE which also includes theCUBE, so if you look around, this is what we have been doing for the past couple of days here in the TheCUBE. We've been inviting some significant thought leaders from over on the show and in incredibly expensive limousines driven them up the street to come on to TheCUBE and spend time with us and talk about some of the things that are happening in the industry today that are especially important. We tore it down, and we're having this party tonight. So we want to thank you very much for coming and look forward to having more conversations with all of you. Now what are we going to talk about? Well Wikibon is the research arm of SiliconANGLE. So we take data that comes out of TheCUBE and other places and we incorporated it into our research. And work very closely with large end users and large technology companies regarding how to make better decisions in this incredibly complex, incredibly important transformative world of digital business. What we're going to talk about tonight, and I've got a couple of my analysts assembled, and we're also going to have a panel, is this notion of software is eating the Edge. Now most of you have probably heard Marc Andreessen, the venture capitalist and developer, original developer of Netscape many years ago, talk about how software's eating the world. Well, if software is truly going to eat the world, it's going to eat at, it's going to take the big chunks, big bites at the Edge. That's where the actual action's going to be. And what we want to talk about specifically is the entangling of the internet or the industrial internet of things and IoT with analytics. So that's what we're going to talk about over the course of the next couple of hours. To do that we're going to, I've already blown the schedule, that's on me. But to do that I'm going to spend a couple minutes talking about what we regard as the essential digital business capabilities which includes analytics and Big Data, and includes IIoT and we'll explain at least in our position why those two things come together the way that they do. But I'm going to ask the august and revered Neil Raden, Wikibon analyst to come on up and talk about harvesting value at the Edge. 'Cause there are some, not now Neil, when we're done, when I'm done. So I'm going to ask Neil to come on up and we'll talk, he's going to talk about harvesting value at the Edge. And then Jim Kobielus will follow up with him, another Wikibon analyst, he'll talk specifically about how we're going to take that combination of analytics and Edge and turn it into the new types of systems and software that are going to sustain this significant transformation that's going on. And then after that, I'm going to ask Neil and Jim to come, going to invite some other folks up and we're going to run a panel to talk about some of these issues and do a real question and answer. So the goal here is before we break for drinks is to create a community feeling within the room. That includes smart people here, smart people in the audience having a conversation ultimately about some of these significant changes so please participate and we look forward to talking about the rest of it. All right, let's get going! What is digital business? One of the nice things about being an analyst is that you can reach back on people who were significantly smarter than you and build your points of view on the shoulders of those giants including Peter Drucker. Many years ago Peter Drucker made the observation that the purpose of business is to create and keep a customer. Not better shareholder value, not anything else. It is about creating and keeping your customer. Now you can argue with that, at the end of the day, if you don't have customers, you don't have a business. Now the observation that we've made, what we've added to that is that we've made the observation that the difference between business and digital business essentially is one thing. That's data. A digital business uses data to differentially create and keep customers. That's the only difference. If you think about the difference between taxi cab companies here in New York City, every cab that I've been in in the last three days has bothered me about Uber. The reason, the difference between Uber and a taxi cab company is data. That's the primary difference. Uber uses data as an asset. And we think this is the fundamental feature of digital business that everybody has to pay attention to. How is a business going to use data as an asset? Is the business using data as an asset? Is a business driving its engagement with customers, the role of its product et cetera using data? And if they are, they are becoming a more digital business. Now when you think about that, what we're really talking about is how are they going to put data to work? How are they going to take their customer data and their operational data and their financial data and any other kind of data and ultimately turn that into superior engagement or improved customer experience or more agile operations or increased automation? Those are the kinds of outcomes that we're talking about. But it is about putting data to work. That's fundamentally what we're trying to do within a digital business. Now that leads to an observation about the crucial strategic business capabilities that every business that aspires to be more digital or to be digital has to put in place. And I want to be clear. When I say strategic capabilities I mean something specific. When you talk about, for example technology architecture or information architecture there is this notion of what capabilities does your business need? Your business needs capabilities to pursue and achieve its mission. And in the digital business these are the capabilities that are now additive to this core question, ultimately of whether or not the company is a digital business. What are the three capabilities? One, you have to capture data. Not just do a good job of it, but better than your competition. You have to capture data better than your competition. In a way that is ultimately less intrusive on your markets and on your customers. That's in many respects, one of the first priorities of the internet of things and people. The idea of using sensors and related technologies to capture more data. Once you capture that data you have to turn it into value. You have to do something with it that creates business value so you can do a better job of engaging your markets and serving your customers. And that essentially is what we regard as the basis of Big Data. Including operations, including financial performance and everything else, but ultimately it's taking the data that's being captured and turning it into value within the business. The last point here is that once you have generated a model, or an insight or some other resource that you can act upon, you then have to act upon it in the real world. We call that systems of agency, the ability to enact based on data. Now I want to spend just a second talking about systems of agency 'cause we think it's an interesting concept and it's something Jim Kobielus is going to talk about a little bit later. When we say systems of agency, what we're saying is increasingly machines are acting on behalf of a brand. Or systems, combinations of machines and people are acting on behalf of the brand. And this whole notion of agency is the idea that ultimately these systems are now acting as the business's agent. They are at the front line of engaging customers. It's an extremely rich proposition that has subtle but crucial implications. For example I was talking to a senior decision maker at a business today and they made a quick observation, they talked about they, on their way here to New York City they had followed a woman who was going through security, opened up her suitcase and took out a bird. And then went through security with the bird. And the reason why I bring this up now is as TSA was trying to figure out how exactly to deal with this, the bird started talking and repeating things that the woman had said and many of those things, in fact, might have put her in jail. Now in this case the bird is not an agent of that woman. You can't put the woman in jail because of what the bird said. But increasingly we have to ask ourselves as we ask machines to do more on our behalf, digital instrumentation and elements to do more on our behalf, it's going to have blow back and an impact on our brand if we don't do it well. I want to draw that forward a little bit because I suggest there's going to be a new lifecycle for data. And the way that we think about it is we have the internet or the Edge which is comprised of things and crucially people, using sensors, whether they be smaller processors in control towers or whether they be phones that are tracking where we go, and this crucial element here is something that we call information transducers. Now a transducer in a traditional sense is something that takes energy from one form to another so that it can perform new types of work. By information transducer I essentially mean it takes information from one form to another so it can perform another type of work. This is a crucial feature of data. One of the beauties of data is that it can be used in multiple places at multiple times and not engender significant net new costs. It's one of the few assets that you can say about that. So the concept of an information transducer's really important because it's the basis for a lot of transformations of data as data flies through organizations. So we end up with the transducers storing data in the form of analytics, machine learning, business operations, other types of things, and then it goes back and it's transduced, back into to the real world as we program the real world and turning into these systems of agency. So that's the new lifecycle. And increasingly, that's how we have to think about data flows. Capturing it, turning it into value and having it act on our behalf in front of markets. That could have enormous implications for how ultimately money is spent over the next few years. So Wikibon does a significant amount of market research in addition to advising our large user customers. And that includes doing studies on cloud, public cloud, but also studies on what's happening within the analytics world. And if you take a look at it, what we basically see happening over the course of the next few years is significant investments in software and also services to get the word out. But we also expect there's going to be a lot of hardware. A significant amount of hardware that's ultimately sold within this space. And that's because of something that we call true private cloud. This concept of ultimately a business increasingly being designed and architected around the idea of data assets means that the reality, the physical realities of how data operates, how much it costs to store it or move it, the issues of latency, the issues of intellectual property protection as well as things like the regulatory regimes that are being put in place to govern how data gets used in between locations. All of those factors are going to drive increased utilization of what we call true private cloud. On premise technologies that provide the cloud experience but act where the data naturally needs to be processed. I'll come a little bit more to that in a second. So we think that it's going to be a relatively balanced market, a lot of stuff is going to end up in the cloud, but as Neil and Jim will talk about, there's going to be an enormous amount of analytics that pulls an enormous amount of data out to the Edge 'cause that's where the action's going to be. Now one of the things I want to also reveal to you is we've done a fair amount of data, we've done a fair amount of research around this question of where or how will data guide decisions about infrastructure? And in particular the Edge is driving these conversations. So here is a piece of research that one of our cohorts at Wikibon did, David Floyer. Taking a look at IoT Edge cost comparisons over a three year period. And it showed on the left hand side, an example where the sensor towers and other types of devices were streaming data back into a central location in a wind farm, stylized wind farm example. Very very expensive. Significant amounts of money end up being consumed, significant resources end up being consumed by the cost of moving the data from one place to another. Now this is even assuming that latency does not become a problem. The second example that we looked at is if we kept more of that data at the Edge and processed at the Edge. And literally it is a 85 plus percent cost reduction to keep more of the data at the Edge. Now that has enormous implications, how we think about big data, how we think about next generation architectures, et cetera. But it's these costs that are going to be so crucial to shaping the decisions that we make over the next two years about where we put hardware, where we put resources, what type of automation is possible, and what types of technology management has to be put in place. Ultimately we think it's going to lead to a structure, an architecture in the infrastructure as well as applications that is informed more by moving cloud to the data than moving the data to the cloud. That's kind of our fundamental proposition is that the norm in the industry has been to think about moving all data up to the cloud because who wants to do IT? It's so much cheaper, look what Amazon can do. Or what AWS can do. All true statements. Very very important in many respects. But most businesses today are starting to rethink that simple proposition and asking themselves do we have to move our business to the cloud, or can we move the cloud to the business? And increasingly what we see happening as we talk to our large customers about this, is that the cloud is being extended out to the Edge, we're moving the cloud and cloud services out to the business. Because of economic reasons, intellectual property control reasons, regulatory reasons, security reasons, any number of other reasons. It's just a more natural way to deal with it. And of course, the most important reason is latency. So with that as a quick backdrop, if I may quickly summarize, we believe fundamentally that the difference today is that businesses are trying to understand how to use data as an asset. And that requires an investment in new sets of technology capabilities that are not cheap, not simple and require significant thought, a lot of planning, lot of change within an IT and business organizations. How we capture data, how we turn it into value, and how we translate that into real world action through software. That's going to lead to a rethinking, ultimately, based on cost and other factors about how we deploy infrastructure. How we use the cloud so that the data guides the activity and not the choice of cloud supplier determines or limits what we can do with our data. And that's going to lead to this notion of true private cloud and elevate the role the Edge plays in analytics and all other architectures. So I hope that was perfectly clear. And now what I want to do is I want to bring up Neil Raden. Yes, now's the time Neil! So let me invite Neil up to spend some time talking about harvesting value at the Edge. Can you see his, all right. Got it. >> Oh boy. Hi everybody. Yeah, this is a really, this is a really big and complicated topic so I decided to just concentrate on something fairly simple, but I know that Peter mentioned customers. And he also had a picture of Peter Drucker. I had the pleasure in 1998 of interviewing Peter and photographing him. Peter Drucker, not this Peter. Because I'd started a magazine called Hired Brains. It was for consultants. And Peter said, Peter said a number of really interesting things to me, but one of them was his definition of a customer was someone who wrote you a check that didn't bounce. He was kind of a wag. He was! So anyway, he had to leave to do a video conference with Jack Welch and so I said to him, how do you charge Jack Welch to spend an hour on a video conference? And he said, you know I have this theory that you should always charge your client enough that it hurts a little bit or they don't take you seriously. Well, I had the chance to talk to Jack's wife, Suzie Welch recently and I told her that story and she said, "Oh he's full of it, Jack never paid "a dime for those conferences!" (laughs) So anyway, all right, so let's talk about this. To me, things about, engineered things like the hardware and network and all these other standards and so forth, we haven't fully developed those yet, but they're coming. As far as I'm concerned, they're not the most interesting thing. The most interesting thing to me in Edge Analytics is what you're going to get out of it, what the result is going to be. Making sense of this data that's coming. And while we're on data, something I've been thinking a lot lately because everybody I've talked to for the last three days just keeps talking to me about data. I have this feeling that data isn't actually quite real. That any data that we deal with is the result of some process that's captured it from something else that's actually real. In other words it's proxy. So it's not exactly perfect. And that's why we've always had these problems about customer A, customer A, customer A, what's their definition? What's the definition of this, that and the other thing? And with sensor data, I really have the feeling, when companies get, not you know, not companies, organizations get instrumented and start dealing with this kind of data what they're going to find is that this is the first time, and I've been involved in analytics, I don't want to date myself, 'cause I know I look young, but the first, I've been dealing with analytics since 1975. And everything we've ever done in analytics has involved pulling data from some other system that was not designed for analytics. But if you think about sensor data, this is data that we're actually going to catch the first time. It's going to be ours! We're not going to get it from some other source. It's going to be the real deal, to the extent that it's the real deal. Now you may say, ya know Neil, a sensor that's sending us information about oil pressure or temperature or something like that, how can you quarrel with that? Well, I can quarrel with it because I don't know if the sensor's doing it right. So we still don't know, even with that data, if it's right, but that's what we have to work with. Now, what does that really mean? Is that we have to be really careful with this data. It's ours, we have to take care of it. We don't get to reload it from source some other day. If we munge it up it's gone forever. So that has, that has very serious implications, but let me, let me roll you back a little bit. The way I look at analytics is it's come in three different eras. And we're entering into the third now. The first era was business intelligence. It was basically built and governed by IT, it was system of record kind of reporting. And as far as I can recall, it probably started around 1988 or at least that's the year that Howard Dresner claims to have invented the term. I'm not sure it's true. And things happened before 1988 that was sort of like BI, but 88 was when they really started coming out, that's when we saw BusinessObjects and Cognos and MicroStrategy and those kinds of things. The second generation just popped out on everybody else. We're all looking around at BI and we were saying why isn't this working? Why are only five people in the organization using this? Why are we not getting value out of this massive license we bought? And along comes companies like Tableau doing data discovery, visualization, data prep and Line of Business people are using this now. But it's still the same kind of data sources. It's moved out a little bit, but it still hasn't really hit the Big Data thing. Now we're in third generation, so we not only had Big Data, which has come and hit us like a tsunami, but we're looking at smart discovery, we're looking at machine learning. We're looking at AI induced analytics workflows. And then all the natural language cousins. You know, natural language processing, natural language, what's? Oh Q, natural language query. Natural language generation. Anybody here know what natural language generation is? Yeah, so what you see now is you do some sort of analysis and that tool comes up and says this chart is about the following and it used the following data, and it's blah blah blah blah blah. I think it's kind of wordy and it's going to refined some, but it's an interesting, it's an interesting thing to do. Now, the problem I see with Edge Analytics and IoT in general is that most of the canonical examples we talk about are pretty thin. I know we talk about autonomous cars, I hope to God we never have them, 'cause I'm a car guy. Fleet Management, I think Qualcomm started Fleet Management in 1988, that is not a new application. Industrial controls. I seem to remember, I seem to remember Honeywell doing industrial controls at least in the 70s and before that I wasn't, I don't want to talk about what I was doing, but I definitely wasn't in this industry. So my feeling is we all need to sit down and think about this and get creative. Because the real value in Edge Analytics or IoT, whatever you want to call it, the real value is going to be figuring out something that's new or different. Creating a brand new business. Changing the way an operation happens in a company, right? And I think there's a lot of smart people out there and I think there's a million apps that we haven't even talked about so, if you as a vendor come to me and tell me how great your product is, please don't talk to me about autonomous cars or Fleet Managing, 'cause I've heard about that, okay? Now, hardware and architecture are really not the most interesting thing. We fell into that trap with data warehousing. We've fallen into that trap with Big Data. We talk about speeds and feeds. Somebody said to me the other day, what's the narrative of this company? This is a technology provider. And I said as far as I can tell, they don't have a narrative they have some products and they compete in a space. And when they go to clients and the clients say, what's the value of your product? They don't have an answer for that. So we don't want to fall into this trap, okay? Because IoT is going to inform you in ways you've never even dreamed about. Unfortunately some of them are going to be really stinky, you know, they're going to be really bad. You're going to lose more of your privacy, it's going to get harder to get, I dunno, mortgage for example, I dunno, maybe it'll be easier, but in any case, it's not going to all be good. So let's really think about what you want to do with this technology to do something that's really valuable. Cost takeout is not the place to justify an IoT project. Because number one, it's very expensive, and number two, it's a waste of the technology because you should be looking at, you know the old numerator denominator thing? You should be looking at the numerators and forget about the denominators because that's not what you do with IoT. And the other thing is you don't want to get over confident. Actually this is good advice about anything, right? But in this case, I love this quote by Derek Sivers He's a pretty funny guy. He said, "If more information was the answer, "then we'd all be billionaires with perfect abs." I'm not sure what's on his wishlist, but you know, I would, those aren't necessarily the two things I would think of, okay. Now, what I said about the data, I want to explain some more. Big Data Analytics, if you look at this graphic, it depicts it perfectly. It's a bunch of different stuff falling into the funnel. All right? It comes from other places, it's not original material. And when it comes in, it's always used as second hand data. Now what does that mean? That means that you have to figure out the semantics of this information and you have to find a way to put it together in a way that's useful to you, okay. That's Big Data. That's where we are. How is that different from IoT data? It's like I said, IoT is original. You can put it together any way you want because no one else has ever done that before. It's yours to construct, okay. You don't even have to transform it into a schema because you're creating the new application. But the most important thing is you have to take care of it 'cause if you lose it, it's gone. It's the original data. It's the same way, in operational systems for a long long time we've always been concerned about backup and security and everything else. You better believe this is a problem. I know a lot of people think about streaming data, that we're going to look at it for a minute, and we're going to throw most of it away. Personally I don't think that's going to happen. I think it's all going to be saved, at least for a while. Now, the governance and security, oh, by the way, I don't know where you're going to find a presentation where somebody uses a newspaper clipping about Vladimir Lenin, but here it is, enjoy yourselves. I believe that when people think about governance and security today they're still thinking along the same grids that we thought about it all along. But this is very very different and again, I'm sorry I keep thrashing this around, but this is treasured data that has to be carefully taken care of. Now when I say governance, my experience has been over the years that governance is something that IT does to make everybody's lives miserable. But that's not what I mean by governance today. It means a comprehensive program to really secure the value of the data as an asset. And you need to think about this differently. Now the other thing is you may not get to think about it differently, because some of the stuff may end up being subject to regulation. And if the regulators start regulating some of this, then that'll take some of the degrees of freedom away from you in how you put this together, but you know, that's the way it works. Now, machine learning, I think I told somebody the other day that claims about machine learning in software products are as common as twisters in trail parks. And a lot of it is not really what I'd call machine learning. But there's a lot of it around. And I think all of the open source machine learning and artificial intelligence that's popped up, it's great because all those math PhDs who work at Home Depot now have something to do when they go home at night and they construct this stuff. But if you're going to have machine learning at the Edge, here's the question, what kind of machine learning would you have at the Edge? As opposed to developing your models back at say, the cloud, when you transmit the data there. The devices at the Edge are not very powerful. And they don't have a lot of memory. So you're only going to be able to do things that have been modeled or constructed somewhere else. But that's okay. Because machine learning algorithm development is actually slow and painful. So you really want the people who know how to do this working with gobs of data creating models and testing them offline. And when you have something that works, you can put it there. Now there's one thing I want to talk about before I finish, and I think I'm almost finished. I wrote a book about 10 years ago about automated decision making and the conclusion that I came up with was that little decisions add up, and that's good. But it also means you don't have to get them all right. But you don't want computers or software making decisions unattended if it involves human life, or frankly any life. Or the environment. So when you think about the applications that you can build using this architecture and this technology, think about the fact that you're not going to be doing air traffic control, you're not going to be monitoring crossing guards at the elementary school. You're going to be doing things that may seem fairly mundane. Managing machinery on the factory floor, I mean that may sound great, but really isn't that interesting. Managing well heads, drilling for oil, well I mean, it's great to the extent that it doesn't cause wells to explode, but they don't usually explode. What it's usually used for is to drive the cost out of preventative maintenance. Not very interesting. So use your heads. Come up with really cool stuff. And any of you who are involved in Edge Analytics, the next time I talk to you I don't want to hear about the same five applications that everybody talks about. Let's hear about some new ones. So, in conclusion, I don't really have anything in conclusion except that Peter mentioned something about limousines bringing people up here. On Monday I was slogging up and down Park Avenue and Madison Avenue with my client and we were visiting all the hedge funds there because we were doing a project with them. And in the miserable weather I looked at him and I said, for godsake Paul, where's the black car? And he said, that was the 90s. (laughs) Thank you. So, Jim, up to you. (audience applauding) This is terrible, go that way, this was terrible coming that way. >> Woo, don't want to trip! And let's move to, there we go. Hi everybody, how ya doing? Thanks Neil, thanks Peter, those were great discussions. So I'm the third leg in this relay race here, talking about of course how software is eating the world. And focusing on the value of Edge Analytics in a lot of real world scenarios. Programming the real world for, to make the world a better place. So I will talk, I'll break it out analytically in terms of the research that Wikibon is doing in the area of the IoT, but specifically how AI intelligence is being embedded really to all material reality potentially at the Edge. But mobile applications and industrial IoT and the smart appliances and self driving vehicles. I will break it out in terms of a reference architecture for understanding what functions are being pushed to the Edge to hardware, to our phones and so forth to drive various scenarios in terms of real world results. So I'll move a pace here. So basically AI software or AI microservices are being infused into Edge hardware as we speak. What we see is more vendors of smart phones and other, real world appliances and things like smart driving, self driving vehicles. What they're doing is they're instrumenting their products with computer vision and natural language processing, environmental awareness based on sensing and actuation and those capabilities and inferences that these devices just do to both provide human support for human users of these devices as well as to enable varying degrees of autonomous operation. So what I'll be talking about is how AI is a foundation for data driven systems of agency of the sort that Peter is talking about. Infusing data driven intelligence into everything or potentially so. As more of this capability, all these algorithms for things like, ya know for doing real time predictions and classifications, anomaly detection and so forth, as this functionality gets diffused widely and becomes more commoditized, you'll see it burned into an ever-wider variety of hardware architecture, neuro synaptic chips, GPUs and so forth. So what I've got here in front of you is a sort of a high level reference architecture that we're building up in our research at Wikibon. So AI, artificial intelligence is a big term, a big paradigm, I'm not going to unpack it completely. Of course we don't have oodles of time so I'm going to take you fairly quickly through the high points. It's a driver for systems of agency. Programming the real world. Transducing digital inputs, the data, to analog real world results. Through the embedding of this capability in the IoT, but pushing more and more of it out to the Edge with points of decision and action in real time. And there are four capabilities that we're seeing in terms of AI enabled, enabling capabilities that are absolutely critical to software being pushed to the Edge are sensing, actuation, inference and Learning. Sensing and actuation like Peter was describing, it's about capturing data from the environment within which a device or users is operating or moving. And then actuation is the fancy term for doing stuff, ya know like industrial IoT, it's obviously machine controlled, but clearly, you know self driving vehicles is steering a vehicle and avoiding crashing and so forth. Inference is the meat and potatoes as it were of AI. Analytics does inferences. It infers from the data, the logic of the application. Predictive logic, correlations, classification, abstractions, differentiation, anomaly detection, recognizing faces and voices. We see that now with Apple and the latest version of the iPhone is embedding face recognition as a core, as the core multifactor authentication technique. Clearly that's a harbinger of what's going to be universal fairly soon which is that depends on AI. That depends on convolutional neural networks, that is some heavy hitting processing power that's necessary and it's processing the data that's coming from your face. So that's critically important. So what we're looking at then is the AI software is taking root in hardware to power continuous agency. Getting stuff done. Powered decision support by human beings who have to take varying degrees of action in various environments. We don't necessarily want to let the car steer itself in all scenarios, we want some degree of override, for lots of good reasons. They want to protect life and limb including their own. And just more data driven automation across the internet of things in the broadest sense. So unpacking this reference framework, what's happening is that AI driven intelligence is powering real time decisioning at the Edge. Real time local sensing from the data that it's capturing there, it's ingesting the data. Some, not all of that data, may be persistent at the Edge. Some, perhaps most of it, will be pushed into the cloud for other processing. When you have these highly complex algorithms that are doing AI deep learning, multilayer, to do a variety of anti-fraud and higher level like narrative, auto-narrative roll-ups from various scenes that are unfolding. A lot of this processing is going to begin to happen in the cloud, but a fair amount of the more narrowly scoped inferences that drive real time decision support at the point of action will be done on the device itself. Contextual actuation, so it's the sensor data that's captured by the device along with other data that may be coming down in real time streams through the cloud will provide the broader contextual envelope of data needed to drive actuation, to drive various models and rules and so forth that are making stuff happen at the point of action, at the Edge. Continuous inference. What it all comes down to is that inference is what's going on inside the chips at the Edge device. And what we're seeing is a growing range of hardware architectures, GPUs, CPUs, FPGAs, ASIC, Neuro synaptic chips of all sorts playing in various combinations that are automating more and more very complex inference scenarios at the Edge. And not just individual devices, swarms of devices, like drones and so forth are essentially an Edge unto themselves. You'll see these tiered hierarchies of Edge swarms that are playing and doing inferences of ever more complex dynamic nature. And much of this will be, this capability, the fundamental capabilities that is powering them all will be burned into the hardware that powers them. And then adaptive learning. Now I use the term learning rather than training here, training is at the core of it. Training means everything in terms of the predictive fitness or the fitness of your AI services for whatever task, predictions, classifications, face recognition that you, you've built them for. But I use the term learning in a broader sense. It's what's make your inferences get better and better, more accurate over time is that you're training them with fresh data in a supervised learning environment. But you can have reinforcement learning if you're doing like say robotics and you don't have ground truth against which to train the data set. You know there's maximize a reward function versus minimize a loss function, you know, the standard approach, the latter for supervised learning. There's also, of course, the issue, or not the issue, the approach of unsupervised learning with cluster analysis critically important in a lot of real world scenarios. So Edge AI Algorithms, clearly, deep learning which is multilayered machine learning models that can do abstractions at higher and higher levels. Face recognition is a high level abstraction. Faces in a social environment is an even higher level of abstraction in terms of groups. Faces over time and bodies and gestures, doing various things in various environments is an even higher level abstraction in terms of narratives that can be rolled up, are being rolled up by deep learning capabilities of great sophistication. Convolutional neural networks for processing images, recurrent neural networks for processing time series. Generative adversarial networks for doing essentially what's called generative applications of all sort, composing music, and a lot of it's being used for auto programming. These are all deep learning. There's a variety of other algorithm approaches I'm not going to bore you with here. Deep learning is essentially the enabler of the five senses of the IoT. Your phone's going to have, has a camera, it has a microphone, it has the ability to of course, has geolocation and navigation capabilities. It's environmentally aware, it's got an accelerometer and so forth embedded therein. The reason that your phone and all of the devices are getting scary sentient is that they have the sensory modalities and the AI, the deep learning that enables them to make environmentally correct decisions in the wider range of scenarios. So machine learning is the foundation of all of this, but there are other, I mean of deep learning, artificial neural networks is the foundation of that. But there are other approaches for machine learning I want to make you aware of because support vector machines and these other established approaches for machine learning are not going away but really what's driving the show now is deep learning, because it's scary effective. And so that's where most of the investment in AI is going into these days for deep learning. AI Edge platforms, tools and frameworks are just coming along like gangbusters. Much development of AI, of deep learning happens in the context of your data lake. This is where you're storing your training data. This is the data that you use to build and test to validate in your models. So we're seeing a deepening stack of Hadoop and there's Kafka, and Spark and so forth that are driving the training (coughs) excuse me, of AI models that are power all these Edge Analytic applications so that that lake will continue to broaden in terms, and deepen in terms of a scope and the range of data sets and the range of modeling, AI modeling supports. Data science is critically important in this scenario because the data scientist, the data science teams, the tools and techniques and flows of data science are the fundamental development paradigm or discipline or capability that's being leveraged to build and to train and to deploy and iterate all this AI that's being pushed to the Edge. So clearly data science is at the center, data scientists of an increasingly specialized nature are necessary to the realization to this value at the Edge. AI frameworks are coming along like you know, a mile a minute. TensorFlow has achieved a, is an open source, most of these are open source, has achieved sort of almost like a defacto standard, status, I'm using the word defacto in air quotes. There's Theano and Keras and xNet and CNTK and a variety of other ones. We're seeing range of AI frameworks come to market, most open source. Most are supported by most of the major tool vendors as well. So at Wikibon we're definitely tracking that, we plan to go deeper in our coverage of that space. And then next best action, powers recommendation engines. I mean next best action decision automation of the sort of thing Neil's covered in a variety of contexts in his career is fundamentally important to Edge Analytics to systems of agency 'cause it's driving the process automation, decision automation, sort of the targeted recommendations that are made at the Edge to individual users as well as to process that automation. That's absolutely necessary for self driving vehicles to do their jobs and industrial IoT. So what we're seeing is more and more recommendation engine or recommender capabilities powered by ML and DL are going to the Edge, are already at the Edge for a variety of applications. Edge AI capabilities, like I said, there's sensing. And sensing at the Edge is becoming ever more rich, mixed reality Edge modalities of all sort are for augmented reality and so forth. We're just seeing a growth in certain, the range of sensory modalities that are enabled or filtered and analyzed through AI that are being pushed to the Edge, into the chip sets. Actuation, that's where robotics comes in. Robotics is coming into all aspects of our lives. And you know, it's brainless without AI, without deep learning and these capabilities. Inference, autonomous edge decisioning. Like I said, it's, a growing range of inferences that are being done at the Edge. And that's where it has to happen 'cause that's the point of decision. Learning, training, much training, most training will continue to be done in the cloud because it's very data intensive. It's a grind to train and optimize an AI algorithm to do its job. It's not something that you necessarily want to do or can do at the Edge at Edge devices so, the models that are built and trained in the cloud are pushed down through a dev ops process down to the Edge and that's the way it will work pretty much in most AI environments, Edge analytics environments. You centralize the modeling, you decentralize the execution of the inference models. The training engines will be in the cloud. Edge AI applications. I'll just run you through sort of a core list of the ones that are coming into, already come into the mainstream at the Edge. Multifactor authentication, clearly the Apple announcement of face recognition is just a harbinger of the fact that that's coming to every device. Computer vision speech recognition, NLP, digital assistance and chat bots powered by natural language processing and understanding, it's all AI powered. And it's becoming very mainstream. Emotion detection, face recognition, you know I could go on and on but these are like the core things that everybody has access to or will by 2020 and they're core devices, mass market devices. Developers, designers and hardware engineers are coming together to pool their expertise to build and train not just the AI, but also the entire package of hardware in UX and the orchestration of real world business scenarios or life scenarios that all this intelligence, the submitted intelligence enables and most, much of what they build in terms of AI will be containerized as micro services through Docker and orchestrated through Kubernetes as full cloud services in an increasingly distributed fabric. That's coming along very rapidly. We can see a fair amount of that already on display at Strata in terms of what the vendors are doing or announcing or who they're working with. The hardware itself, the Edge, you know at the Edge, some data will be persistent, needs to be persistent to drive inference. That's, and you know to drive a variety of different application scenarios that need some degree of historical data related to what that device in question happens to be sensing or has sensed in the immediate past or you know, whatever. The hardware itself is geared towards both sensing and increasingly persistence and Edge driven actuation of real world results. The whole notion of drones and robotics being embedded into everything that we do. That's where that comes in. That has to be powered by low cost, low power commodity chip sets of various sorts. What we see right now in terms of chip sets is it's a GPUs, Nvidia has gone real far and GPUs have come along very fast in terms of power inference engines, you know like the Tesla cars and so forth. But GPUs are in many ways the core hardware sub straight for in inference engines in DL so far. But to become a mass market phenomenon, it's got to get cheaper and lower powered and more commoditized, and so we see a fair number of CPUs being used as the hardware for Edge Analytic applications. Some vendors are fairly big on FPGAs, I believe Microsoft has gone fairly far with FPGAs inside DL strategy. ASIC, I mean, there's neuro synaptic chips like IBM's got one. There's at least a few dozen vendors of neuro synaptic chips on the market so at Wikibon we're going to track that market as it develops. And what we're seeing is a fair number of scenarios where it's a mixed environment where you use one chip set architecture at the inference side of the Edge, and other chip set architectures that are driving the DL as processed in the cloud, playing together within a common architecture. And we see some, a fair number of DL environments where the actual training is done in the cloud on Spark using CPUs and parallelized in memory, but pushing Tensorflow models that might be trained through Spark down to the Edge where the inferences are done in FPGAs and GPUs. Those kinds of mixed hardware scenarios are very, very, likely to be standard going forward in lots of areas. So analytics at the Edge power continuous results is what it's all about. The whole point is really not moving the data, it's putting the inference at the Edge and working from the data that's already captured and persistent there for the duration of whatever action or decision or result needs to be powered from the Edge. Like Neil said cost takeout alone is not worth doing. Cost takeout alone is not the rationale for putting AI at the Edge. It's getting new stuff done, new kinds of things done in an automated consistent, intelligent, contextualized way to make our lives better and more productive. Security and governance are becoming more important. Governance of the models, governance of the data, governance in a dev ops context in terms of version controls over all those DL models that are built, that are trained, that are containerized and deployed. Continuous iteration and improvement of those to help them learn to do, make our lives better and easier. With that said, I'm going to hand it over now. It's five minutes after the hour. We're going to get going with the Influencer Panel so what we'd like to do is I call Peter, and Peter's going to call our influencers. >> All right, am I live yet? Can you hear me? All right so, we've got, let me jump back in control here. We've got, again, the objective here is to have community take on some things. And so what we want to do is I want to invite five other people up, Neil why don't you come on up as well. Start with Neil. You can sit here. On the far right hand side, Judith, Judith Hurwitz. >> Neil: I'm glad I'm on the left side. >> From the Hurwitz Group. >> From the Hurwitz Group. Jennifer Shin who's affiliated with UC Berkeley. Jennifer are you here? >> She's here, Jennifer where are you? >> She was here a second ago. >> Neil: I saw her walk out she may have, >> Peter: All right, she'll be back in a second. >> Here's Jennifer! >> Here's Jennifer! >> Neil: With 8 Path Solutions, right? >> Yep. >> Yeah 8 Path Solutions. >> Just get my mic. >> Take your time Jen. >> Peter: All right, Stephanie McReynolds. Far left. And finally Joe Caserta, Joe come on up. >> Stephie's with Elysian >> And to the left. So what I want to do is I want to start by having everybody just go around introduce yourself quickly. Judith, why don't we start there. >> I'm Judith Hurwitz, I'm president of Hurwitz and Associates. We're an analyst research and fault leadership firm. I'm the co-author of eight books. Most recent is Cognitive Computing and Big Data Analytics. I've been in the market for a couple years now. >> Jennifer. >> Hi, my name's Jennifer Shin. I'm the founder and Chief Data Scientist 8 Path Solutions LLC. We do data science analytics and technology. We're actually about to do a big launch next month, with Box actually. >> We're apparent, are we having a, sorry Jennifer, are we having a problem with Jennifer's microphone? >> Man: Just turn it back on? >> Oh you have to turn it back on. >> It was on, oh sorry, can you hear me now? >> Yes! We can hear you now. >> Okay, I don't know how that turned back off, but okay. >> So you got to redo all that Jen. >> Okay, so my name's Jennifer Shin, I'm founder of 8 Path Solutions LLC, it's a data science analytics and technology company. I founded it about six years ago. So we've been developing some really cool technology that we're going to be launching with Box next month. It's really exciting. And I have, I've been developing a lot of patents and some technology as well as teaching at UC Berkeley as a lecturer in data science. >> You know Jim, you know Neil, Joe, you ready to go? >> Joe: Just broke my microphone. >> Joe's microphone is broken. >> Joe: Now it should be all right. >> Jim: Speak into Neil's. >> Joe: Hello, hello? >> I just feel not worthy in the presence of Joe Caserta. (several laughing) >> That's right, master of mics. If you can hear me, Joe Caserta, so yeah, I've been doing data technology solutions since 1986, almost as old as Neil here, but been doing specifically like BI, data warehousing, business intelligence type of work since 1996. And been doing, wholly dedicated to Big Data solutions and modern data engineering since 2009. Where should I be looking? >> Yeah I don't know where is the camera? >> Yeah, and that's basically it. So my company was formed in 2001, it's called Caserta Concepts. We recently rebranded to only Caserta 'cause what we do is way more than just concepts. So we conceptualize the stuff, we envision what the future brings and we actually build it. And we help clients large and small who are just, want to be leaders in innovation using data specifically to advance their business. >> Peter: And finally Stephanie McReynolds. >> I'm Stephanie McReynolds, I had product marketing as well as corporate marketing for a company called Elysian. And we are a data catalog so we help bring together not only a technical understanding of your data, but we curate that data with human knowledge and use automated intelligence internally within the system to make recommendations about what data to use for decision making. And some of our customers like City of San Diego, a large automotive manufacturer working on self driving cars and General Electric use Elysian to help power their solutions for IoT at the Edge. >> All right so let's jump right into it. And again if you have a question, raise your hand, and we'll do our best to get it to the floor. But what I want to do is I want to get seven questions in front of this group and have you guys discuss, slog, disagree, agree. Let's start here. What is the relationship between Big Data AI and IoT? Now Wikibon's put forward its observation that data's being generated at the Edge, that action is being taken at the Edge and then increasingly the software and other infrastructure architectures need to accommodate the realities of how data is going to work in these very complex systems. That's our perspective. Anybody, Judith, you want to start? >> Yeah, so I think that if you look at AI machine learning, all these different areas, you have to be able to have the data learned. Now when it comes to IoT, I think one of the issues we have to be careful about is not all data will be at the Edge. Not all data needs to be analyzed at the Edge. For example if the light is green and that's good and it's supposed to be green, do you really have to constantly analyze the fact that the light is green? You actually only really want to be able to analyze and take action when there's an anomaly. Well if it goes purple, that's actually a sign that something might explode, so that's where you want to make sure that you have the analytics at the edge. Not for everything, but for the things where there is an anomaly and a change. >> Joe, how about from your perspective? >> For me I think the evolution of data is really becoming, eventually oxygen is just, I mean data's going to be the oxygen we breathe. It used to be very very reactive and there used to be like a latency. You do something, there's a behavior, there's an event, there's a transaction, and then you go record it and then you collect it, and then you can analyze it. And it was very very waterfallish, right? And then eventually we figured out to put it back into the system. Or at least human beings interpret it to try to make the system better and that is really completely turned on it's head, we don't do that anymore. Right now it's very very, it's synchronous, where as we're actually making these transactions, the machines, we don't really need, I mean human beings are involved a bit, but less and less and less. And it's just a reality, it may not be politically correct to say but it's a reality that my phone in my pocket is following my behavior, and it knows without telling a human being what I'm doing. And it can actually help me do things like get to where I want to go faster depending on my preference if I want to save money or save time or visit things along the way. And I think that's all integration of big data, streaming data, artificial intelligence and I think the next thing that we're going to start seeing is the culmination of all of that. I actually, hopefully it'll be published soon, I just wrote an article for Forbes with the term of ARBI and ARBI is the integration of Augmented Reality and Business Intelligence. Where I think essentially we're going to see, you know, hold your phone up to Jim's face and it's going to recognize-- >> Peter: It's going to break. >> And it's going to say exactly you know, what are the key metrics that we want to know about Jim. If he works on my sales force, what's his attainment of goal, what is-- >> Jim: Can it read my mind? >> Potentially based on behavior patterns. >> Now I'm scared. >> I don't think Jim's buying it. >> It will, without a doubt be able to predict what you've done in the past, you may, with some certain level of confidence you may do again in the future, right? And is that mind reading? It's pretty close, right? >> Well, sometimes, I mean, mind reading is in the eye of the individual who wants to know. And if the machine appears to approximate what's going on in the person's head, sometimes you can't tell. So I guess, I guess we could call that the Turing machine test of the paranormal. >> Well, face recognition, micro gesture recognition, I mean facial gestures, people can do it. Maybe not better than a coin toss, but if it can be seen visually and captured and analyzed, conceivably some degree of mind reading can be built in. I can see when somebody's angry looking at me so, that's a possibility. That's kind of a scary possibility in a surveillance society, potentially. >> Neil: Right, absolutely. >> Peter: Stephanie, what do you think? >> Well, I hear a world of it's the bots versus the humans being painted here and I think that, you know at Elysian we have a very strong perspective on this and that is that the greatest impact, or the greatest results is going to be when humans figure out how to collaborate with the machines. And so yes, you want to get to the location more quickly, but the machine as in the bot isn't able to tell you exactly what to do and you're just going to blindly follow it. You need to train that machine, you need to have a partnership with that machine. So, a lot of the power, and I think this goes back to Judith's story is then what is the human decision making that can be augmented with data from the machine, but then the humans are actually training the training side and driving machines in the right direction. I think that's when we get true power out of some of these solutions so it's not just all about the technology. It's not all about the data or the AI, or the IoT, it's about how that empowers human systems to become smarter and more effective and more efficient. And I think we're playing that out in our technology in a certain way and I think organizations that are thinking along those lines with IoT are seeing more benefits immediately from those projects. >> So I think we have a general agreement of what kind of some of the things you talked about, IoT, crucial capturing information, and then having action being taken, AI being crucial to defining and refining the nature of the actions that are being taken Big Data ultimately powering how a lot of that changes. Let's go to the next one. >> So actually I have something to add to that. So I think it makes sense, right, with IoT, why we have Big Data associated with it. If you think about what data is collected by IoT. We're talking about a serial information, right? It's over time, it's going to grow exponentially just by definition, right, so every minute you collect a piece of information that means over time, it's going to keep growing, growing, growing as it accumulates. So that's one of the reasons why the IoT is so strongly associated with Big Data. And also why you need AI to be able to differentiate between one minute versus next minute, right? Trying to find a better way rather than looking at all that information and manually picking out patterns. To have some automated process for being able to filter through that much data that's being collected. >> I want to point out though based on what you just said Jennifer, I want to bring Neil in at this point, that this question of IoT now generating unprecedented levels of data does introduce this idea of the primary source. Historically what we've done within technology, or within IT certainly is we've taken stylized data. There is no such thing as a real world accounting thing. It is a human contrivance. And we stylize data and therefore it's relatively easy to be very precise on it. But when we start, as you noted, when we start measuring things with a tolerance down to thousandths of a millimeter, whatever that is, metric system, now we're still sometimes dealing with errors that we have to attend to. So, the reality is we're not just dealing with stylized data, we're dealing with real data, and it's more, more frequent, but it also has special cases that we have to attend to as in terms of how we use it. What do you think Neil? >> Well, I mean, I agree with that, I think I already said that, right. >> Yes you did, okay let's move on to the next one. >> Well it's a doppelganger, the digital twin doppelganger that's automatically created by your very fact that you're living and interacting and so forth and so on. It's going to accumulate regardless. Now that doppelganger may not be your agent, or might not be the foundation for your agent unless there's some other piece of logic like an interest graph that you build, a human being saying this is my broad set of interests, and so all of my agents out there in the IoT, you all need to be aware that when you make a decision on my behalf as my agent, this is what Jim would do. You know I mean there needs to be that kind of logic somewhere in this fabric to enable true agency. >> All right, so I'm going to start with you. Oh go ahead. >> I have a real short answer to this though. I think that Big Data provides the data and compute platform to make AI possible. For those of us who dipped our toes in the water in the 80s, we got clobbered because we didn't have the, we didn't have the facilities, we didn't have the resources to really do AI, we just kind of played around with it. And I think that the other thing about it is if you combine Big Data and AI and IoT, what you're going to see is people, a lot of the applications we develop now are very inward looking, we look at our organization, we look at our customers. We try to figure out how to sell more shoes to fashionable ladies, right? But with this technology, I think people can really expand what they're thinking about and what they model and come up with applications that are much more external. >> Actually what I would add to that is also it actually introduces being able to use engineering, right? Having engineers interested in the data. Because it's actually technical data that's collected not just say preferences or information about people, but actual measurements that are being collected with IoT. So it's really interesting in the engineering space because it opens up a whole new world for the engineers to actually look at data and to actually combine both that hardware side as well as the data that's being collected from it. >> Well, Neil, you and I have talked about something, 'cause it's not just engineers. We have in the healthcare industry for example, which you know a fair amount about, there's this notion of empirical based management. And the idea that increasingly we have to be driven by data as a way of improving the way that managers do things, the way the managers collect or collaborate and ultimately collectively how they take action. So it's not just engineers, it's supposed to also inform business, what's actually happening in the healthcare world when we start thinking about some of this empirical based management, is it working? What are some of the barriers? >> It's not a function of technology. What happens in medicine and healthcare research is, I guess you can say it borders on fraud. (people chuckling) No, I'm not kidding. I know the New England Journal of Medicine a couple of years ago released a study and said that at least half their articles that they published turned out to be written, ghost written by pharmaceutical companies. (man chuckling) Right, so I think the problem is that when you do a clinical study, the one that really killed me about 10 years ago was the women's health initiative. They spent $700 million gathering this data over 20 years. And when they released it they looked at all the wrong things deliberately, right? So I think that's a systemic-- >> I think you're bringing up a really important point that we haven't brought up yet, and that is is can you use Big Data and machine learning to begin to take the biases out? So if you let the, if you divorce your preconceived notions and your biases from the data and let the data lead you to the logic, you start to, I think get better over time, but it's going to take a while to get there because we do tend to gravitate towards our biases. >> I will share an anecdote. So I had some arm pain, and I had numbness in my thumb and pointer finger and I went to, excruciating pain, went to the hospital. So the doctor examined me, and he said you probably have a pinched nerve, he said, but I'm not exactly sure which nerve it would be, I'll be right back. And I kid you not, he went to a computer and he Googled it. (Neil laughs) And he came back because this little bit of information was something that could easily be looked up, right? Every nerve in your spine is connected to your different fingers so the pointer and the thumb just happens to be your C6, so he came back and said, it's your C6. (Neil mumbles) >> You know an interesting, I mean that's a good example. One of the issues with healthcare data is that the data set is not always shared across the entire research community, so by making Big Data accessible to everyone, you actually start a more rational conversation or debate on well what are the true insights-- >> If that conversation includes what Judith talked about, the actual model that you use to set priorities and make decisions about what's actually important. So it's not just about improving, this is the test. It's not just about improving your understanding of the wrong thing, it's also testing whether it's the right or wrong thing as well. >> That's right, to be able to test that you need to have humans in dialog with one another bringing different biases to the table to work through okay is there truth in this data? >> It's context and it's correlation and you can have a great correlation that's garbage. You know if you don't have the right context. >> Peter: So I want to, hold on Jim, I want to, >> It's exploratory. >> Hold on Jim, I want to take it to the next question 'cause I want to build off of what you talked about Stephanie and that is that this says something about what is the Edge. And our perspective is that the Edge is not just devices. That when we talk about the Edge, we're talking about human beings and the role that human beings are going to play both as sensors or carrying things with them, but also as actuators, actually taking action which is not a simple thing. So what do you guys think? What does the Edge mean to you? Joe, why don't you start? >> Well, I think it could be a combination of the two. And specifically when we talk about healthcare. So I believe in 2017 when we eat we don't know why we're eating, like I think we should absolutely by now be able to know exactly what is my protein level, what is my calcium level, what is my potassium level? And then find the foods to meet that. What have I depleted versus what I should have, and eat very very purposely and not by taste-- >> And it's amazing that red wine is always the answer. >> It is. (people laughing) And tequila, that helps too. >> Jim: You're a precision foodie is what you are. (several chuckle) >> There's no reason why we should not be able to know that right now, right? And when it comes to healthcare is, the biggest problem or challenge with healthcare is no matter how great of a technology you have, you can't, you can't, you can't manage what you can't measure. And you're really not allowed to use a lot of this data so you can't measure it, right? You can't do things very very scientifically right, in the healthcare world and I think regulation in the healthcare world is really burdening advancement in science. >> Peter: Any thoughts Jennifer? >> Yes, I teach statistics for data scientists, right, so you know we talk about a lot of these concepts. I think what makes these questions so difficult is you have to find a balance, right, a middle ground. For instance, in the case of are you being too biased through data, well you could say like we want to look at data only objectively, but then there are certain relationships that your data models might show that aren't actually a causal relationship. For instance, if there's an alien that came from space and saw earth, saw the people, everyone's carrying umbrellas right, and then it started to rain. That alien might think well, it's because they're carrying umbrellas that it's raining. Now we know from real world that that's actually not the way these things work. So if you look only at the data, that's the potential risk. That you'll start making associations or saying something's causal when it's actually not, right? So that's one of the, one of the I think big challenges. I think when it comes to looking also at things like healthcare data, right? Do you collect data about anything and everything? Does it mean that A, we need to collect all that data for the question we're looking at? Or that it's actually the best, more optimal way to be able to get to the answer? Meaning sometimes you can take some shortcuts in terms of what data you collect and still get the right answer and not have maybe that level of specificity that's going to cost you millions extra to be able to get. >> So Jennifer as a data scientist, I want to build upon what you just said. And that is, are we going to start to see methods and models emerge for how we actually solve some of these problems? So for example, we know how to build a system for stylized process like accounting or some elements of accounting. We have methods and models that lead to technology and actions and whatnot all the way down to that that system can be generated. We don't have the same notion to the same degree when we start talking about AI and some of these Big Datas. We have algorithms, we have technology. But are we going to start seeing, as a data scientist, repeatability and learning and how to think the problems through that's going to lead us to a more likely best or at least good result? >> So I think that's a bit of a tough question, right? Because part of it is, it's going to depend on how many of these researchers actually get exposed to real world scenarios, right? Research looks into all these papers, and you come up with all these models, but if it's never tested in a real world scenario, well, I mean we really can't validate that it works, right? So I think it is dependent on how much of this integration there's going to be between the research community and industry and how much investment there is. Funding is going to matter in this case. If there's no funding in the research side, then you'll see a lot of industry folk who feel very confident about their models that, but again on the other side of course, if researchers don't validate those models then you really can't say for sure that it's actually more accurate, or it's more efficient. >> It's the issue of real world testing and experimentation, A B testing, that's standard practice in many operationalized ML and AI implementations in the business world, but real world experimentation in the Edge analytics, what you're actually transducing are touching people's actual lives. Problem there is, like in healthcare and so forth, when you're experimenting with people's lives, somebody's going to die. I mean, in other words, that's a critical, in terms of causal analysis, you've got to tread lightly on doing operationalizing that kind of testing in the IoT when people's lives and health are at stake. >> We still give 'em placebos. So we still test 'em. All right so let's go to the next question. What are the hottest innovations in AI? Stephanie I want to start with you as a company, someone at a company that's got kind of an interesting little thing happening. We start thinking about how do we better catalog data and represent it to a large number of people. What are some of the hottest innovations in AI as you see it? >> I think it's a little counter intuitive about what the hottest innovations are in AI, because we're at a spot in the industry where the most successful companies that are working with AI are actually incorporating them into solutions. So the best AI solutions are actually the products that you don't know there's AI operating underneath. But they're having a significant impact on business decision making or bringing a different type of application to the market and you know, I think there's a lot of investment that's going into AI tooling and tool sets for data scientists or researchers, but the more innovative companies are thinking through how do we really take AI and make it have an impact on business decision making and that means kind of hiding the AI to the business user. Because if you think a bot is making a decision instead of you, you're not going to partner with that bot very easily or very readily. I worked at, way at the start of my career, I worked in CRM when recommendation engines were all the rage online and also in call centers. And the hardest thing was to get a call center agent to actually read the script that the algorithm was presenting to them, that algorithm was 99% correct most of the time, but there was this human resistance to letting a computer tell you what to tell that customer on the other side even if it was more successful in the end. And so I think that the innovation in AI that's really going to push us forward is when humans feel like they can partner with these bots and they don't think of it as a bot, but they think about as assisting their work and getting to a better result-- >> Hence the augmentation point you made earlier. >> Absolutely, absolutely. >> Joe how 'about you? What do you look at? What are you excited about? >> I think the coolest thing at the moment right now is chat bots. Like to be able, like to have voice be able to speak with you in natural language, to do that, I think that's pretty innovative, right? And I do think that eventually, for the average user, not for techies like me, but for the average user, I think keyboards are going to be a thing of the past. I think we're going to communicate with computers through voice and I think this is the very very beginning of that and it's an incredible innovation. >> Neil? >> Well, I think we all have myopia here. We're all thinking about commercial applications. Big, big things are happening with AI in the intelligence community, in military, the defense industry, in all sorts of things. Meteorology. And that's where, well, hopefully not on an every day basis with military, you really see the effect of this. But I was involved in a project a couple of years ago where we were developing AI software to detect artillery pieces in terrain from satellite imagery. I don't have to tell you what country that was. I think you can probably figure that one out right? But there are legions of people in many many companies that are involved in that industry. So if you're talking about the dollars spent on AI, I think the stuff that we do in our industries is probably fairly small. >> Well it reminds me of an application I actually thought was interesting about AI related to that, AI being applied to removing mines from war zones. >> Why not? >> Which is not a bad thing for a whole lot of people. Judith what do you look at? >> So I'm looking at things like being able to have pre-trained data sets in specific solution areas. I think that that's something that's coming. Also the ability to, to really be able to have a machine assist you in selecting the right algorithms based on what your data looks like and the problems you're trying to solve. Some of the things that data scientists still spend a lot of their time on, but can be augmented with some, basically we have to move to levels of abstraction before this becomes truly ubiquitous across many different areas. >> Peter: Jennifer? >> So I'm going to say computer vision. >> Computer vision? >> Computer vision. So computer vision ranges from image recognition to be able to say what content is in the image. Is it a dog, is it a cat, is it a blueberry muffin? Like a sort of popular post out there where it's like a blueberry muffin versus like I think a chihuahua and then it compares the two. And can the AI really actually detect difference, right? So I think that's really where a lot of people who are in this space of being in both the AI space as well as data science are looking to for the new innovations. I think, for instance, cloud vision I think that's what Google still calls it. The vision API we've they've released on beta allows you to actually use an API to send your image and then have it be recognized right, by their API. There's another startup in New York called Clarify that also does a similar thing as well as you know Amazon has their recognition platform as well. So I think in a, from images being able to detect what's in the content as well as from videos, being able to say things like how many people are entering a frame? How many people enter the store? Not having to actually go look at it and count it, but having a computer actually tally that information for you, right? >> There's actually an extra piece to that. So if I have a picture of a stop sign, and I'm an automated car, and is it a picture on the back of a bus of a stop sign, or is it a real stop sign? So that's going to be one of the complications. >> Doesn't matter to a New York City cab driver. How 'about you Jim? >> Probably not. (laughs) >> Hottest thing in AI is General Adversarial Networks, GANT, what's hot about that, well, I'll be very quick, most AI, most deep learning, machine learning is analytical, it's distilling or inferring insights from the data. Generative takes that same algorithmic basis but to build stuff. In other words, to create realistic looking photographs, to compose music, to build CAD CAM models essentially that can be constructed on 3D printers. So GANT, it's a huge research focus all around the world are used for, often increasingly used for natural language generation. In other words it's institutionalizing or having a foundation for nailing the Turing test every single time, building something with machines that looks like it was constructed by a human and doing it over and over again to fool humans. I mean you can imagine the fraud potential. But you can also imagine just the sheer, like it's going to shape the world, GANT. >> All right so I'm going to say one thing, and then we're going to ask if anybody in the audience has an idea. So the thing that I find interesting is traditional programs, or when you tell a machine to do something you don't need incentives. When you tell a human being something, you have to provide incentives. Like how do you get someone to actually read the text. And this whole question of elements within AI that incorporate incentives as a way of trying to guide human behavior is absolutely fascinating to me. Whether it's gamification, or even some things we're thinking about with block chain and bitcoins and related types of stuff. To my mind that's going to have an enormous impact, some good, some bad. Anybody in the audience? I don't want to lose everybody here. What do you think sir? And I'll try to do my best to repeat it. Oh we have a mic. >> So my question's about, Okay, so the question's pretty much about what Stephanie's talking about which is human and loop training right? I come from a computer vision background. That's the problem, we need millions of images trained, we need humans to do that. And that's like you know, the workforce is essentially people that aren't necessarily part of the AI community, they're people that are just able to use that data and analyze the data and label that data. That's something that I think is a big problem everyone in the computer vision industry at least faces. I was wondering-- >> So again, but the problem is that is the difficulty of methodologically bringing together people who understand it and people who, people who have domain expertise people who have algorithm expertise and working together? >> I think the expertise issue comes in healthcare, right? In healthcare you need experts to be labeling your images. With contextual information where essentially augmented reality applications coming in, you have the AR kit and everything coming out, but there is a lack of context based intelligence. And all of that comes through training images, and all of that requires people to do it. And that's kind of like the foundational basis of AI coming forward is not necessarily an algorithm, right? It's how well are datas labeled? Who's doing the labeling and how do we ensure that it happens? >> Great question. So for the panel. So if you think about it, a consultant talks about being on the bench. How much time are they going to have to spend on trying to develop additional business? How much time should we set aside for executives to help train some of the assistants? >> I think that the key is not, to think of the problem a different way is that you would have people manually label data and that's one way to solve the problem. But you can also look at what is the natural workflow of that executive, or that individual? And is there a way to gather that context automatically using AI, right? And if you can do that, it's similar to what we do in our product, we observe how someone is analyzing the data and from those observations we can actually create the metadata that then trains the system in a particular direction. But you have to think about solving the problem differently of finding the workflow that then you can feed into to make this labeling easy without the human really realizing that they're labeling the data. >> Peter: Anybody else? >> I'll just add to what Stephanie said, so in the IoT applications, all those sensory modalities, the computer vision, the speech recognition, all that, that's all potential training data. So it cross checks against all the other models that are processing all the other data coming from that device. So that the natural language process of understanding can be reality checked against the images that the person happens to be commenting upon, or the scene in which they're embedded, so yeah, the data's embedded-- >> I don't think we're, we're not at the stage yet where this is easy. It's going to take time before we do start doing the pre-training of some of these details so that it goes faster, but right now, there're not that many shortcuts. >> Go ahead Joe. >> Sorry so a couple things. So one is like, I was just caught up on your incentivizing programs to be more efficient like humans. You know in Ethereum that has this notion, which is bot chain, has this theory, this concept of gas. Where like as the process becomes more efficient it costs less to actually run, right? It costs less ether, right? So it actually is kind of, the machine is actually incentivized and you don't really know what it's going to cost until the machine processes it, right? So there is like some notion of that there. But as far as like vision, like training the machine for computer vision, I think it's through adoption and crowdsourcing, so as people start using it more they're going to be adding more pictures. Very very organically. And then the machines will be trained and right now is a very small handful doing it, and it's very proactive by the Googles and the Facebooks and all of that. But as we start using it, as they start looking at my images and Jim's and Jen's images, it's going to keep getting smarter and smarter through adoption and through very organic process. >> So Neil, let me ask you a question. Who owns the value that's generated as a consequence of all these people ultimately contributing their insight and intelligence into these systems? >> Well, to a certain extent the people who are contributing the insight own nothing because the systems collect their actions and the things they do and then that data doesn't belong to them, it belongs to whoever collected it or whoever's going to do something with it. But the other thing, getting back to the medical stuff. It's not enough to say that the systems, people will do the right thing, because a lot of them are not motivated to do the right thing. The whole grant thing, the whole oh my god I'm not going to go against the senior professor. A lot of these, I knew a guy who was a doctor at University of Pittsburgh and they were doing a clinical study on the tubes that they put in little kids' ears who have ear infections, right? And-- >> Google it! Who helps out? >> Anyway, I forget the exact thing, but he came out and said that the principle investigator lied when he made the presentation, that it should be this, I forget which way it went. He was fired from his position at Pittsburgh and he has never worked as a doctor again. 'Cause he went against the senior line of authority. He was-- >> Another question back here? >> Man: Yes, Mark Turner has a question. >> Not a question, just want to piggyback what you're saying about the transfixation of maybe in healthcare of black and white images and color images in the case of sonograms and ultrasound and mammograms, you see that happening using AI? You see that being, I mean it's already happening, do you see it moving forward in that kind of way? I mean, talk more about that, about you know, AI and black and white images being used and they can be transfixed, they can be made to color images so you can see things better, doctors can perform better operations. >> So I'm sorry, but could you summarize down? What's the question? Summarize it just, >> I had a lot of students, they're interested in the cross pollenization between AI and say the medical community as far as things like ultrasound and sonograms and mammograms and how you can literally take a black and white image and it can, using algorithms and stuff be made to color images that can help doctors better do the work that they've already been doing, just do it better. You touched on it like 30 seconds. >> So how AI can be used to actually add information in a way that's not necessarily invasive but is ultimately improves how someone might respond to it or use it, yes? Related? I've also got something say about medical images in a second, any of you guys want to, go ahead Jennifer. >> Yeah, so for one thing, you know and it kind of goes back to what we were talking about before. When we look at for instance scans, like at some point I was looking at CT scans, right, for lung cancer nodules. In order for me, who I don't have a medical background, to identify where the nodule is, of course, a doctor actually had to go in and specify which slice of the scan had the nodule and where exactly it is, so it's on both the slice level as well as, within that 2D image, where it's located and the size of it. So the beauty of things like AI is that ultimately right now a radiologist has to look at every slice and actually identify this manually, right? The goal of course would be that one day we wouldn't have to have someone look at every slice to like 300 usually slices and be able to identify it much more automated. And I think the reality is we're not going to get something where it's going to be 100%. And with anything we do in the real world it's always like a 95% chance of it being accurate. So I think it's finding that in between of where, what's the threshold that we want to use to be able to say that this is, definitively say a lung cancer nodule or not. I think the other thing to think about is in terms of how their using other information, what they might use is a for instance, to say like you know, based on other characteristics of the person's health, they might use that as sort of a grading right? So you know, how dark or how light something is, identify maybe in that region, the prevalence of that specific variable. So that's usually how they integrate that information into something that's already existing in the computer vision sense. I think that's, the difficulty with this of course, is being able to identify which variables were introduced into data that does exist. >> So I'll make two quick observations on this then I'll go to the next question. One is radiologists have historically been some of the highest paid physicians within the medical community partly because they don't have to be particularly clinical. They don't have to spend a lot of time with patients. They tend to spend time with doctors which means they can do a lot of work in a little bit of time, and charge a fair amount of money. As we start to introduce some of these technologies that allow us to from a machine standpoint actually make diagnoses based on those images, I find it fascinating that you now see television ads promoting the role that the radiologist plays in clinical medicine. It's kind of an interesting response. >> It's also disruptive as I'm seeing more and more studies showing that deep learning models processing images, ultrasounds and so forth are getting as accurate as many of the best radiologists. >> That's the point! >> Detecting cancer >> Now radiologists are saying oh look, we do this great thing in terms of interacting with the patients, never have because they're being dis-intermediated. The second thing that I'll note is one of my favorite examples of that if I got it right, is looking at the images, the deep space images that come out of Hubble. Where they're taking data from thousands, maybe even millions of images and combining it together in interesting ways you can actually see depth. You can actually move through to a very very small scale a system that's 150, well maybe that, can't be that much, maybe six billion light years away. Fascinating stuff. All right so let me go to the last question here, and then I'm going to close it down, then we can have something to drink. What are the hottest, oh I'm sorry, question? >> Yes, hi, my name's George, I'm with Blue Talon. You asked earlier there the question what's the hottest thing in the Edge and AI, I would say that it's security. It seems to me that before you can empower agency you need to be able to authorize what they can act on, how they can act on, who they can act on. So it seems if you're going to move from very distributed data at the Edge and analytics at the Edge, there has to be security similarly done at the Edge. And I saw (speaking faintly) slides that called out security as a key prerequisite and maybe Judith can comment, but I'm curious how security's going to evolve to meet this analytics at the Edge. >> Well, let me do that and I'll ask Jen to comment. The notion of agency is crucially important, slightly different from security, just so we're clear. And the basic idea here is historically folks have thought about moving data or they thought about moving application function, now we are thinking about moving authority. So as you said. That's not necessarily, that's not really a security question, but this has been a problem that's been in, of concern in a number of different domains. How do we move authority with the resources? And that's really what informs the whole agency process. But with that said, Jim. >> Yeah actually I'll, yeah, thank you for bringing up security so identity is the foundation of security. Strong identity, multifactor, face recognition, biometrics and so forth. Clearly AI, machine learning, deep learning are powering a new era of biometrics and you know it's behavioral metrics and so forth that's organic to people's use of devices and so forth. You know getting to the point that Peter was raising is important, agency! Systems of agency. Your agent, you have to, you as a human being should be vouching in a secure, tamper proof way, your identity should be vouching for the identity of some agent, physical or virtual that does stuff on your behalf. How can that, how should that be managed within this increasingly distributed IoT fabric? Well a lot of that's been worked. It all ran through webs of trust, public key infrastructure, formats and you know SAML for single sign and so forth. It's all about assertion, strong assertions and vouching. I mean there's the whole workflows of things. Back in the ancient days when I was actually a PKI analyst three analyst firms ago, I got deep into all the guts of all those federation agreements, something like that has to be IoT scalable to enable systems agency to be truly fluid. So we can vouch for our agents wherever they happen to be. We're going to keep on having as human beings agents all over creation, we're not even going to be aware of everywhere that our agents are, but our identity-- >> It's not just-- >> Our identity has to follow. >> But it's not just identity, it's also authorization and context. >> Permissioning, of course. >> So I may be the right person to do something yesterday, but I'm not authorized to do it in another context in another application. >> Role based permissioning, yeah. Or persona based. >> That's right. >> I agree. >> And obviously it's going to be interesting to see the role that block chain or its follow on to the technology is going to play here. Okay so let me throw one more questions out. What are the hottest applications of AI at the Edge? We've talked about a number of them, does anybody want to add something that hasn't been talked about? Or do you want to get a beer? (people laughing) Stephanie, you raised your hand first. >> I was going to go, I bring something mundane to the table actually because I think one of the most exciting innovations with IoT and AI are actually simple things like City of San Diego is rolling out 3200 automated street lights that will actually help you find a parking space, reduce the amount of emissions into the atmosphere, so has some environmental change, positive environmental change impact. I mean, it's street lights, it's not like a, it's not medical industry, it doesn't look like a life changing innovation, and yet if we automate streetlights and we manage our energy better, and maybe they can flicker on and off if there's a parking space there for you, that's a significant impact on everyone's life. >> And dramatically suppress the impact of backseat driving! >> (laughs) Exactly. >> Joe what were you saying? >> I was just going to say you know there's already the technology out there where you can put a camera on a drone with machine learning within an artificial intelligence within it, and it can look at buildings and determine whether there's rusty pipes and cracks in cement and leaky roofs and all of those things. And that's all based on artificial intelligence. And I think if you can do that, to be able to look at an x-ray and determine if there's a tumor there is not out of the realm of possibility, right? >> Neil? >> I agree with both of them, that's what I meant about external kind of applications. Instead of figuring out what to sell our customers. Which is most what we hear. I just, I think all of those things are imminently doable. And boy street lights that help you find a parking place, that's brilliant, right? >> Simple! >> It improves your life more than, I dunno. Something I use on the internet recently, but I think it's great! That's, I'd like to see a thousand things like that. >> Peter: Jim? >> Yeah, building on what Stephanie and Neil were saying, it's ambient intelligence built into everything to enable fine grain microclimate awareness of all of us as human beings moving through the world. And enable reading of every microclimate in buildings. In other words, you know you have sensors on your body that are always detecting the heat, the humidity, the level of pollution or whatever in every environment that you're in or that you might be likely to move into fairly soon and either A can help give you guidance in real time about where to avoid, or give that environment guidance about how to adjust itself to your, like the lighting or whatever it might be to your specific requirements. And you know when you have a room like this, full of other human beings, there has to be some negotiated settlement. Some will find it too hot, some will find it too cold or whatever but I think that is fundamental in terms of reshaping the sheer quality of experience of most of our lived habitats on the planet potentially. That's really the Edge analytics application that depends on everybody having, being fully equipped with a personal area network of sensors that's communicating into the cloud. >> Jennifer? >> So I think, what's really interesting about it is being able to utilize the technology we do have, it's a lot cheaper now to have a lot of these ways of measuring that we didn't have before. And whether or not engineers can then leverage what we have as ways to measure things and then of course then you need people like data scientists to build the right model. So you can collect all this data, if you don't build the right model that identifies these patterns then all that data's just collected and it's just made a repository. So without having the models that supports patterns that are actually in the data, you're not going to find a better way of being able to find insights in the data itself. So I think what will be really interesting is to see how existing technology is leveraged, to collect data and then how that's actually modeled as well as to be able to see how technology's going to now develop from where it is now, to being able to either collect things more sensitively or in the case of say for instance if you're dealing with like how people move, whether we can build things that we can then use to measure how we move, right? Like how we move every day and then being able to model that in a way that is actually going to give us better insights in things like healthcare and just maybe even just our behaviors. >> Peter: Judith? >> So, I think we also have to look at it from a peer to peer perspective. So I may be able to get some data from one thing at the Edge, but then all those Edge devices, sensors or whatever, they all have to interact with each other because we don't live, we may, in our business lives, act in silos, but in the real world when you look at things like sensors and devices it's how they react with each other on a peer to peer basis. >> All right, before I invite John up, I want to say, I'll say what my thing is, and it's not the hottest. It's the one I hate the most. I hate AI generated music. (people laughing) Hate it. All right, I want to thank all the panelists, every single person, some great commentary, great observations. I want to thank you very much. I want to thank everybody that joined. John in a second you'll kind of announce who's the big winner. But the one thing I want to do is, is I was listening, I learned a lot from everybody, but I want to call out the one comment that I think we all need to remember, and I'm going to give you the award Stephanie. And that is increasing we have to remember that the best AI is probably AI that we don't even know is working on our behalf. The same flip side of that is all of us have to be very cognizant of the idea that AI is acting on our behalf and we may not know it. So, John why don't you come on up. Who won the, whatever it's called, the raffle? >> You won. >> Thank you! >> How 'about a round of applause for the great panel. (audience applauding) Okay we have a put the business cards in the basket, we're going to have that brought up. We're going to have two raffle gifts, some nice Bose headsets and speaker, Bluetooth speaker. Got to wait for that. I just want to say thank you for coming and for the folks watching, this is our fifth year doing our own event called Big Data NYC which is really an extension of the landscape beyond the Big Data world that's Cloud and AI and IoT and other great things happen and great experts and influencers and analysts here. Thanks for sharing your opinion. Really appreciate you taking the time to come out and share your data and your knowledge, appreciate it. Thank you. Where's the? >> Sam's right in front of you. >> There's the thing, okay. Got to be present to win. We saw some people sneaking out the back door to go to a dinner. >> First prize first. >> Okay first prize is the Bose headset. >> Bluetooth and noise canceling. >> I won't look, Sam you got to hold it down, I can see the cards. >> All right. >> Stephanie you won! (Stephanie laughing) Okay, Sawny Cox, Sawny Allie Cox? (audience applauding) Yay look at that! He's here! The bar's open so help yourself, but we got one more. >> Congratulations. Picture right here. >> Hold that I saw you. Wake up a little bit. Okay, all right. Next one is, my kids love this. This is great, great for the beach, great for everything portable speaker, great gift. >> What is it? >> Portable speaker. >> It is a portable speaker, it's pretty awesome. >> Oh you grabbed mine. >> Oh that's one of our guys. >> (lauging) But who was it? >> Can't be related! Ava, Ava, Ava. Okay Gene Penesko (audience applauding) Hey! He came in! All right look at that, the timing's great. >> Another one? (people laughing) >> Hey thanks everybody, enjoy the night, thank Peter Burris, head of research for SiliconANGLE, Wikibon and he great guests and influencers and friends. And you guys for coming in the community. Thanks for watching and thanks for coming. Enjoy the party and some drinks and that's out, that's it for the influencer panel and analyst discussion. Thank you. (logo music)

>> Narrator: At the DataWorks Summit, Europe 2017. Brought to you by Hortonworks. >> Hey, welcome back everyone. We're here live from Munich, Germany at DataWorks 2017, Hadoop Summit formerly, the conference name before it changed to DataWorks. I'm John Furrier with my cohost Dave Vellante. Our next guest, we're excited to have Alan Nance who flew in, just for the CUBE interview today. Executive Vice President with Virtual Clarity. Former star, I call practitioner of the Cloud, knows the Cloud business. Knows the operational aspects of how to use technology. Alan, it's great to see you. Thanks for coming on the CUBE. >> Thank you for having me again. >> Great to see you, you were in the US recently, we had a chance to catch up. And one of the motivations that we talked with you today was, a little bit about some of the things you're looking at, that are transformative. Before we do that, let's talk a little about your history. And what your role is at Virtual Clarity. >> So, as you guys have, basically, followed that career, I started out in the transformation time with ING Bank. And started out, basically, technology upwards. Looking at converged infrastructure, converged infrastructure into VDI. When you've got that, you start to look at Clouds. Then you start to experiment with Clouds. And I moved from ING, from earlier experimentation, into Phillips. So, while Phillips, at that time had both the health care and lighting group. And then you start to look at consumption based Cloud propositions. And you remember the big thing that we were doing at that time, when we identified that 80% of the IT spend was non differentiating. So the thing was, how do we get away from almost a 900 million a year spend on legacy? How do we turn that into something that's productive for the Enterprise? So we spent a lot of time creating the consumption based infrastructure operating platform. A lot of things we had to learn. Because let's be honest, Amazon was still trying to become the behemoth it is now. IBM still didn't get the transition, HP didn't get it. So there was a lot of experimentation on which of the operating model-- >> You're the first mover on the operating model, The Cloud, that has scaled to it. And really differentiated services for your business, for also, cost reductions. >> Cost reductions have been phenomenal. And we're talking about halving the budget over a three year period. We're talking about 500 million a year savings. So these are big, big savings. The thing I feel we still need to tackle, is that when we re-platform your business, it should leave to agile acceleration of your growth path. And I think that's something that we still haven't conquered. So I think we're getting better and better at using platforms to save money, to suppress the expenditure. What we now need to do is to convert that into growth platform business. >> So, how about the data component? Because you were CIO of infrastructure at Phillips. But lately, you've been really spending a lot of time thinking about the data, how data adds value. So talk about your data journey. >> Well if I look at the data journey, the journey started for me, with, basically, a meeting with Tom Ritz in 2013. And he came with a very, very simple proposition. "You guys need to learn how to create "and store, and reason over data, "for the benefit of the Enterprise." And I think, "Well that's cool." Because up until that point, nobody had really been talking about data. Everyone was talking about the underlying technologies of the Cloud, but not really of the data element. And then we had a session with JP Rangaswami, who was at Salesforce, who basically, also said, "Well don't just think "about data lakes, but think also "about data streams and data rivers. "Because the other thing that's "going to happen here is that data's "not going to be stagnant in a company like yours." So we took that, and what happened, I think, in Phillips, which I think you see in a lot of companies, is an explosion across the Enterprise. So you've got people in social doing stuff. You got CDO's appearing. You've got the IOT. You've got the old, legacy systems, the systems of record. And so you end up with this enormous fragmentation of data. And with that you get a Wild West of what I call data stewardship. So you have a CDO who says, "Well I'm in charge of data." And you got a CMO who says, "Well I'm in charge of marketing data." Or you've got a CSO, says, "Yeah, "but I'm the security data guy." And there's no coherence, in terms of moving the Enterprise forward. Because everybody's focused on their own functionality around that data and not connecting it. So where are we now? I think right now we have a huge proliferation of data that's not connected, in many organizations. And I think we're going to hybrid but I don't think that's a future proof thing for most organizations. >> John: What do you mean by that? >> Well, if I look at what a lot of those suppliers are saying, they're really saying, "The solution "that you need, is to have a hybrid solution "between the public Cloud and your own Cloud." I thought, "But that's not the problem "that we need to solve." The problem that we need to solve is first of all, data gravity. So if I look at all the transformations that are running into trouble, what do they forget? When we go out and do IOT, when we go out and do social media analysis, it all has to flow back into those legacy systems. And those legacy systems are all going to be in the old world. And so you get latency issues, you get formatting issues. And so, we have to solve the data gravity issue. And we have to also solve this proliferation of stewardship. Somebody has to be in charge of making this work. And it's not going to be, just putting in a hybrid solution. Because that won't change the operating model. >> So let me ask the question, because on one of the things you're kind of dancing around, Dave brought up the data question. Something that I see as a problem in the industry, that hasn't yet been solved, and I'm just going to throw it out there. The CIO has always been the guy managing IT. And then he would report to the CFO, get the budget, blah, blah, blah. We know that's kind of played out its course. But there's no operational playbook to take the Cloud, mobile data at scale, that's going to drive the transformative impact. And I think there's some people doing stuff here and there, pockets. And maybe there's some organizations that have a cadence of managers, that are doing compliance, security, blah, blah, blah. But you have a vision on this. And some information that you're tracking around. An architecture that would bring it to scale. Could you share your thoughts on this operational model of Cloud, at a management level? >> Well, part of this is also based on your own analyst, Peter Boris. When he says, "The problem with data "is that its value is inverse to its half life." So, what the Enterprise has to do is it has to get to analyzing and making this data valuable, much, much faster then it is right now. And Chris Sellender of Unifi recently said, "You know, the problem's not big data. "The problem's fast data." So, now, who is best positioned in the organization to do this? And I believe it's the COO. >> John: Chief Operating Officer? >> Chief Operating Officer. I don't think it's going to be the CIO. Because I'm trying to figure out who's got the problem. Who's got the problem of connecting the dots to improving the operation of the company? Who is in charge of actually creating an operating platform that the business can feed off of? It's the C Tower. >> John: Why not the CFO? >> No, I think the CFO is going to be a diminishing value, over time. Because a couple of reasons. First of all, we see it in Phillips. There's always going to be a fiduciary role for the CFO. But we're out of the world of capex. We're out of the world of balancing assets. Everything is now virtual. So really, the value of a CFO, as sitting on the tee, if I use the racquetball, the CFO standing on the tee is not going to bring value to the Enterprise. >> And the CIO doesn't have the business juice, is your argument? Is that right? >> It depends on the CIO. There are some CIO's out there-- >> Dave: But in general, we're generalizing. >> Generally not. Because they've come through the ranks of building applications, which now has to be thrown away. They've come through the ranks of technology, which is now less relevant. And they've come through the ranks of having huge budgets and huge people to deploy certain projects. All of that's going away. And so what are you left with? Now you're left with somebody who absolutely has to understand how to communicate with the business. And that's what they haven't done for 30 years. >> John: And stream line business process. >> Well, at least get involved in the conversation. At least get involved in the conversation. Now if I talk to business people today, and you probably do too, most of them will still say there's this huge communication gulf. Between what we're trying to achieve and what the technology people are doing with our goals. I mean, I was talking to somebody the other day. And this lady heads up the sales for a global financial institution. She's sitting on the business side of this. And she's like, "The conversation should be "about, if our company wants to improve "our cost income ratio, and they ask me, "as sales to do it, I have to sell 10 times "more to make a difference. "Then if IT would save money. "So for every Euro they save. "And give me an agile platform, "is straight to the bottom line. "Every time I sell, because of our "cost income ratio, I just can't sell against that. "But I can't find on the IT side, "anybody who, sort of, gets my problem. "And is trying to help me with it." And then you look at her and what? You think a hybrid solution's going to help her? (laughs) I have no idea what you're talking about. >> Right, so the business person here then says, "I don't really care where it runs." But to your point, you care about the operational model? >> Alan: Absolutely. >> And that's really what Cloud should be, right? >> I think everybody who's going to achieve anything from an investment in Cloud, will achieve it in the operating world. They won't just achieve it on the cost savings side. Or on making costs more transparent, or more commoditized. Where it has to happen is in the operating model. In fact, we actually have data of a very large, transportation, logistics company, who moved everything that they had, in an attempt to be in a zero Cloud. And on the benchmark, saved zero. And they saved zero because they weren't changing the operating model. So they were still-- >> They lifted and shifted, but didn't change the operational mindset. >> Not at all. >> But there could have been business value there. Maybe things went faster? >> There could have been. >> Maybe simpler? >> But I'm not seeing it. >> Not game changing. >> Not game changing, certainly yes. >> Not as meaningful, it was a stretch. >> Give an example of a game changing scenario. >> Well for me, and I think this is the next most exciting thing. Is this idea of platforms. There's been an early adoption of this in Telco. Where we've seen people coming in and saying, "If you stock all of this IT, as we've known it, "and you leverage the ideas of Cloud computing, "to have scalable, invisible, infrastructure. "And you put a single platform on top of it "to run your business, you can save money." Now, I've seen business cases where people who are about to embark on this program are taking a billion a year out of their cost base. And in this company, it's 1/7th of their total profit. That's a game changer, for me. But now, who's going to help them do that? Who's going to help them-- >> What's the platform look like? >> And a million's a lot of money. >> Let's go, grab a sheet of paper how we-- >> So not everybody will even have a billion-- >> But that gets the attention of certainly, the CEO, the COO, CFO says, "Tell me more." >> You're alluding to it, Dave. You need to build a layer to punch, to doing that. So you need to fix the data stewardship problem. You have to create the invisible infrastructure that enables that platform. And you have to have a platform player who is prepared to disrupt the industry. And for me-- >> Dave: A Cloud player. >> A Cloud player, I think it's a born in the Cloud player. I think, you know, we've talked about it privately. >> So who are the forces to attract? You got Microsoft, you got AWS, Google, maybe IBM, maybe Oracle. >> See, I think it's Google. >> Dave: Why, why do you think it's Google? >> I think it's because, the platforms that I'm thinking of, and if I look in retail, if I look in financial services, it's all about data. Because that's the battle, right. We all agree, the battle's on data. So it's got to be somebody who understands data at scale, understands search at scale, understands deep learning at scale. And understands technology enough to build that platform and make it available in a consumption model. And for me, Google would be the ideal player, if they would make that step. Amazon's going to have a different problem because their strategy's not going down that route. And I think, for people like IBM or Oracle, it would require cannibalizing too much of their existing business. But they may dally with it. And they may do it in a territory where they have no install base. But they're not going to be disrupting the industry. I just don't think it's going to be possible for them. >> And you think Google has the Enterprise chops to pull it off? >> I think Google has the platform. I would agree with Alan on this. Something, I've been very critical on Google. Dave brings this up because he wants me to say it now, and I will. Google is well positioned to be the platform. I am very bullish on Google Cloud with respect to their ability to moon shot or slingshot to the future faster, than, potentially others. Or as they say in football, move the goal posts and change the game. That being said, where I've been critical of Google, and this is where, I'll be critical, is their dogma is very academic, very, "We're the technology leader, "therefore you should use Google G Suite." I think that they have to change their mindset, to be more Enterprise focused, in the sense of understand not the best product will always win, but the B chip they have to develop, have to think about the Enterprise. And that's a lot of white glove service. That's a lot of listening. That's not being too arrogant. I mean, there's a borderline between confidence and arrogance. And I think Google crosses it a little bit too much, Dave. And I think that's where Google recognizes, some people in Google recognize that they don't have the Enterprise track record, for sure on the sales side. You could add 1,000 sales reps tomorrow but do they have experience? So there's a huge translation issue going on between Google's capability and potential energy. And then the reality of them translating that into an operational footprint. So for them to meet the mark of folks like you, you can't be speaking Russian and English. You got to speak the same language. So, the language barrier, so to speak, the linguistics is different. That's my only point. >> I sense in your statements, there's a frustration here. Because we know that the key to some really innovative, disruption is with Google. And I think what we'd all like to do, even while I was addressing the camera. I'd love to see Diane, who does understand Enterprise, who's built a whole career servicing Enterprises extremely well, I'd like to see a little bit of a glimpse of, "We are up for this." And I understand when you're part of the bigger Google, the numbers are a little bit skewered against you to make a big impact and carry the firm with you. But I do believe there's an enormous opportunity in the Enterprise space. And people are just waiting for this. >> Well Diane Greene knows the Enterprise. So she came in, she's got to change the culture. And I know she's doing it. Because I have folks at Google, that I know that work there, that tell me privately, that it's happening, maybe not fast enough. But here's the thing. If you walked in the front door at Google, Alan Nance, this is my point, and he said, "I have experience and I have a plan "to build a platform, to knock a billion "dollars off seven companies, that I know, personally. "That I can walk in and win. "And move a billion dollars to their "bottom line with your platform." They might not understand what that means. >> I don't know, you know I was at Google Next a few weeks ago, last month. And I thought they were more, to your point, open to listening. Maybe not as arrogant as you might be presenting. And somewhat more humble. Still pretty ballsy. But I think Google recognizes that it needs help in the Enterprise. And here's why. Something that we've talked about in the past, is, you've got top down initiatives. You've got bottom up initiatives. And you've got middle out. What frequently happens, and I'd love for you to describe your experiences. The leaders say, the top CXO's say, "Okay we're going." And they take off and the organization doesn't follow them. If it's bottoms up, you don't have the top down in premature. So how do you address that? What are you seeing and how do you address that problem? >> So I think that's a really, really good observation. I mean, what I see in a lot of the big transformations that I've been involved in, is that speed is of the essence. And I think when CEO's, because usually it's the CEO. CEO comes in and they think they've got more time than they actually have to make the impact in the Enterprise. And it doesn't matter if they're coming in from the outside or they've grown up. They always underestimate their ability to do change, in time. And now what's changed over the past few years, is the average tenure of a CEO is six years. You know, I mean, Jack Welch was 20 years at GE. You can do a lot of damage in 20 years. And he did a lot of great things at GE over a 20 year period. You've only got six years now. And what I see in these big transformation programs is they start with a really good vision. I mean Mackenzie, Bain, Boston. They know the essence of what needs to happen. >> Dave: They can sell the dream. >> They can sell the dream. And the CEO sort of buys into it. And then immediately you get into the first layer, "Okay, okay, so we've got to change the organization." And so you bring in a lot of these companies that will run 13 work streams over three years, with hundreds of people. And at the end of that time, you're almost halfway through your tenure. And all you've got is a new design. Or a new set of job descriptions or strategies. You haven't actually achieved anything. And then the layer down is going to run into real problems. One of the problems that we had at the company I worked at before, was in order to support these platforms you needed really good master data management. And we suddenly realized that. And so we had to really put in an accelerated program to achieve that, with Impatica. We did it, but it cost us a year and 1/2. At a bank I know, they can't move forward because they're looking at 700 million of technology debt, they can't get past. So they end up going down a route of, "Maybe one of these big suppliers "can buy our old stuff. "And we can tag on some transformational "deal at the back end of that." None of those are working. And then what happens is, in my mind, if the CEO, from what I see, has not achieved escape velocity at the end of year three. So he's showing the growth, or she's showing the digital transformation, it's kind of game over. The Enterprise has already figured out they've stalled it long enough, not intentionally. And then we go back into an austerity program. Because you got to justify the millions you've spent in the last three years. And you've got nothing to show for it. >> And you're preparing three envelopes. >> So you got to accelerate those layers. You got to take layers out and you've got to have a really, I would say almost like, 90 day iteration plans that show business outcomes. >> But the technology layer, you can put in an abstraction layer, use APIs and infrastructure as code, all that cool stuff. But you're saying it's the organizational challenges. >> I think that's the real problem. It is the real problem, is the organization. And also, because what you're really doing in terms of the Enterprise, is you're moving from a more traditional supply chain that you own. And you've matriculated with SAP or with Oracle. Now you're talking about creating a digital value chain. A digital value chain that's much more based on a more mobile ecosystem, where you would have thin text in one area or insurance text, that have to now fit into an agile supply chain. It's all about the operating model. If you don't have people who know how to drive that, the technology's not going to help you. So you've got to have people on the business side and the technology side coming together to make this work. >> Alan, I have a question for you. What's you're prediction, okay, knowing what you know. And kind of, obviously, you have some frustrations in platforms with trying to get the big players to listen. And I think they should listen to you. But this is going to happen. So I would believe that what you're saying with the COO, operational things radically changing differently. Obviously, the signs are all there. Data centers are moving into the Cloud. I mean this is radical stuff, in a good way. And so, what's your prediction for how this plays out vis a vis Amazon Web Services, Google Cloud Platform Azure, IBM Cloud SoftLayer. >> Well here's my concern a little bit. I think if Google enters the fray I think everybody will reconfigure. Because if we'd assume that Google plays to its strengths and goes out there and finds the right partners. It's going to reconfigure the industry. If they don't do that, then what the industry's going to do is what it's done. Which means that the platforms are going to be hybrid platforms that are dominated by the traditional players. By the SOPs, by the Oracles, by the IBMs. And what I fear is that there may actually be a disillusionment. Because they will not bring the digital transformation and all the wonderful things that we all know, are out there to be gained. So you may get, "We've invested all this money." You see it a little bit with big data. "I've got this huge layer. "I've got petabytes. "Why am I not smarter? "Why is my business not going so much better? "I've put everything in there." I think we've got to address the operating problem. And we have to find a dialogue at the C Suite. >> Well to your point, and we talked about this. You know, you look at the core of Enterprise apps, the Oracle stuff is not moving in droves, to the Cloud. Oracle's freezing the market right now. Betting that it can get there before the industry gets there. And if it does-- >> Alan: It's not. >> And it might, but if it does, it's not going to be that radical transformation you're prescribing. >> They have too much to lose. Let's be honest, right. So Oracle is a victim of it's own success, pretty much like SAP. It has to go to the Cloud as a defensive play. Because the last thing either of those want is to be disintermediated by Amazon. Which may or may not happen anyway. Because a lot of companies will disintermediate if they can. Because the licensing is such a painful element for most enterprises, when they deal with these companies. So they have to believe that the platform is not going to look like that. >> And they're still trying to figure out the pricing models, and the margin models, and Amazon's clearly-- >> You know what's driving the pricing models is not the growth on the consumer side. >> Right, absolutely. >> That's not what's driving it. So I think we need another player. I really think we need another player. If it's not Google, somebody else. I can't think who would have the scale, the money to-- >> The only guys who have the scale, you got 10 cents, maybe a couple China Clouds, maybe one Japan Cloud and that's it. >> To be honest, you raise a good point. I haven't really looked at the Ali Baba's and the other people like that who may pick up that mantle. I haven't looked at them. Ali Baba's interesting, because just like Amazon, they have their own business that runs on platforms. And a very diverse business, which is growing faster than Amazon and is more profitable than Amazon. So they could be interesting. But I'm still hopeful. We should figure this out. >> Google should figure it out. You're absolutely right. They're investing, and I thought they put forth a pretty good messaging at the Google Next. You covered it remotely but I think they understand the opportunity. And I think they have the stomach for it. >> We had reporters there as well, at the event. We just did, they came to our studio. Google is self aware that they need to work on the Enterprise. I think the bigger thing that you're highlighting is the operational model is shifting to a scale point where it's going to change stewardship and COO meaning to be, I like that. The other thing I want to get your reaction to is something I heard this morning, on the CUBE from Sean Connelly. Which that goes with some of the things that we're seeing where you're seeing Cloud becoming a more centralized view. Where IOT is an Edge case. So you have now, issues around architectural things. Your thoughts and reaction to this balance between Edge and Cloud. >> Well I think this is where you're also going to have your data gravity challenge. So, Dave McCrory has written a lot about the concept of data gravity. And in my mind, too many people in the Enterprise don't understand it. Which is basically, that data attracts more data. And more data you have, it'll attract more. And then you create all these latency issues when you start going out to the Edge. Because when we first went out to the Edge I think, even at Phillips, we didn't realize how much interaction needed to come back. And that's going to vary from company to company. So some company's are going to want to have that data really quickly because they need to react to it immediately. Others may not have that. But what you do have is you have this balancing act. About, "What do I keep central? "And what do I put at the Edge?" I think Edge Technology is amazing. And when we first looked at it, four years ago, I mean, it's come such a long way. And what I am encouraged by is that, that data layer, so the layer that Sean talks about, there's a lot of exciting things happening. But again, my problem is what's the Enterprise going to do with that? Because it requires a different operating model. If I take an example of a manufacturing company, I know a manufacturing company right now that does work in China. And it takes all the data back to its central mainframes for processing. Well if you've got the Edge, you want to be changing the way you process. Which means that the decision makers on the business need to be insitu. They need to be in China. And we need to be bringing, systems of record data and combining it with local social data and age data, so we get better decisions. So we can drive growth in those areas. If I just enable it with technology but don't change the business model the business is not going to grow. >> So Alan, we always loved having you on. Great practitioner, but now you've kind of gone over to the dark side. We've heard of a company called Virtual Clarity. Tell us about what you're doing there. >> So what we're vested in, what I am very much vested in, with my team at Virtual Clarity, is creating this concept of precision guided transformation. Where you work on the business, on what are the outcomes we really need to get from this? And then we've combined, I would say it's like a data nerve center. So we can quickly analyze, within a matter of weeks, where we are with the company, and what routes to value we can create. And then we'll go and do it. So we do it in 90 day increments. So the business now starts to believe that something's really going to happen. None of these big, insert miracle here after three year programs. But actually going out and doing it. The second thing that I think that we're doing that I'm excited about is bringing in enlightened people who represent the Enterprise. So, one of my colleagues, former COO of Unilever, we just brought on a very smart lady, Dessa Grassa, who was the CDO at JP Morgan Chase. And the idea is to combine the insights that we have on the demand side, the buy side, with the insights that we have on the technology side to create better operating models. So that combination of creating a new view that is acceptable to the C Suite. Because these people understand how you talk to them. But at the same time, runs on this concept of doing everything quickly. That's what we're about right now. >> That's awesome, we should get you hooked up with our new analyst we just hired, James Corbelius, from IBM. Was focusing on exactly that. The intersections of developers, Cloud, AI machine learning and data, all coming together. And IOT is going to be a key application that we're going to see coming out of that. So, congratulations. Alan thank you for spending the time to come in. >> Thanks for allowing me. >> To see us in the CUBE. It's the CUBE, bringing you more action. Here from DataWorks 2017. I'm John Furrier with my cohost Dave Vallante, here on the CUBE, SiliconANGLE Media's flagship program. Where we've got the events, straight from SiliconANGLE. Stay with us for more great coverage. Day one of two days of coverage at DataWorks 2017. We'll be right back.

(mumbling) >> Voiceover: Covering Sapphire now. Headline sponsored by SAP HANA Cloud, the leader in platform as a service. With support from Console Inc., the cloud internet company. Now, here are your hosts, John Furrier and Peter Burris. >> We are here live at SAP Sapphire. This is SiliconANGLE Media's The Cube. It's our flagship program. We go out to the events and extract the signal to noise and want to do a shoutout to our sponsors SAP HANA Cloud and Console Inc. at console cloud, connecting the clouds together. I'm John Furrier with my co-host Peter Burris. Our next guest is Reggie Jackson, winner, athlete, tech athlete now, entrepreneur, overall great guy, and a cube alumni. Four years ago, we interviewed him here at SAP Sapphire. Welcome back, Reggie, to The Cube. Thanks for coming on. John, thank you very much. It's good to be here with old friends. We were havin' a little conversation about baseball there, but good to see you guys. Yeah, and obviously, the baseball, we were just talkin' about the whole fisticuffs and the glee of the grand slam walk-off. >> Reggie: Good stuff, good stuff. >> It's a good pivot point in some of the things that you're workin' on in here, the conversations in the tech world, which is social media and that notion of celebrating in a world of Instagram and Snapchat and social media. Certainly, ya flip the bat, the views go up. But then, baseball has these (laughing) unwritten rules, right. So does corporations. And so we're now a new era. Is baseball safe now with these unwritten rules and should they maintain those, certain things that have kept the game in balance? But yet with social media, the players are their own brand. And you certainly were a brand, even back in your day, which is a pioneer. What's your thoughts on that? >> You know John, Peter, I don't like the idea of someone going out of their way to promote their brand. Some of the great brands to me in history, Babe Ruth, Ty Cobb, the great Jim Brown, Joe Montana, Michael Jordan. And Michael Jordan would be a prominent example where technology and TV enhanced who he was. And he had someone behind him to enhance his brand, Nike, Phil Knight, who was a real pioneer. I'm not so in favor, I'm not in favor at all of someone manufacturing themselves as a brand. And I hear players talk about their brand and about trying to create something. If you're great, if you deserve it, I don't think Stephen Curry works on his brand. I think he works on bein' a great player. I think he works on bein' a great teammate. I think he does his best to maximize his skill set. And he's nothing but a gentleman along the way. He'll celebrate with joy once in awhile, with the Curry moves, which we've come to recognize. But for guys that talk about the manufacturing of their brand, there's something about it that's manufactured. It's not real, it's false. And I don't like it. I think it's okay, the Snapchats and the Google+ and all of the stuff, Twitter and Facebook and all that stuff, all of the things that go along with trying to create some hubbub, etc. I'm okay with that. >> So you're saying if it's not deserved. People are overplaying their hand before earning it. >> A lot of it, John, a lot of it. Joe Montana didn't work on his brand, he was great. Jim Brown didn't work on his brand, he was great. I don't want to use Jimmy Brown. I want to use Montana because even young people today will know Joe Montana. Tom Brady, Peyton Manning, they're not about their brand. They're about being classy, being great, being part of a team, being a leader, presenting themselves as something that's respected in the NFL, across the United States. Go ahead, Pete. >> So even though it's cheaper to get your name out there, you still believe in let your performance speak for itself. >> You got to be real about it. Ya got to be who you are. If you're not a great player, get out of the way. Get out of the space. So manufacturing your brand. I played with the Yankees. I was in the era of Cosell and Billy Martin and George Steinbrenner. We won championships with the team. I was part of something that helped me become recognized. And so in our era, the Sandy Koufax's became brands because they were associated with greatness around them. They stood out and so they earned that tremendous brand. >> We were just watching Graig Nettles gettin' taken out by George Brett in that big game and also the pine tar, we kind of gettin' some good laughs at it. You look at the balance of personalities. Certainly, Brett and Nettles and your team and you had a great personality, winning championships. Worked together as a team. And so I want to ask you that question about the balance, about the in baseball, certainly, the unwritten rules are a legacy and that has worked. And now in a era of personalities, in some cases, people self-promoting themselves, people are questioning that. Your thoughts on that because that applies to business too 'cause tech athletes or business athletes have a team, there are some unwritten rules. Thoughts on this baseball debate about unwritten rules. >> Pete and John, I'll try to correlate it between some tech giants that have a brand. I just left a guy with a brand, Bill McDermott, that runs SAP. Even Hasso, the boss. The face now of SAP is Bill McDermott. Dapper, slender, stylish, bright. It comes across well. So maintaining that brand, to me, relates to SAP, bills a great image for it. He's stylish, he's smooth, he's smart. He's about people. He presents himself with care. So that is a brand. I don't think it's manufactured. That's who he is in real life. If you take a look, and I'll go back to Steph Curry because that name resonates and everyone recognize it. That style of cool, that style of control, that style of team and care. And he presents to us all that he cares about us, the fan, his team, his family. And so those are things and I think you can go from the tech world. Bill Gates had a brand. Brilliant, somewhat reclusive, concerned about the world, concerned about the country, concerned about his company. And so that resonated it Microsoft because that's who he really was. Some of the people today don't really recognize that Jobs was thrown out of Apple. He was pushed out. All of his brilliance, which was marketing. And the gentleman there that really was the mind for the company, Steve Wozniak, happens to be here at SAP Sapphire. Today, I think he speaks. But those brands were real, not manufactured. And so, in today's world, I think you can manufacture a brand. And then all of a sudden, it'll crumble. It'll go away in the future. But the great brands of whether it's Jackie Robinson or whether it's Jack Welch or whether it's George Steinbrenner and the Yankee brand, those brands were real. They were not manufactured. Those guys were eccentric. They were brilliant. Go ahead. >> And also, they work hard. And I want to point out a comment you made yesterday here at the event. You were asked a question up on stage about that moment when you hit the home runs. I think we talked about it last time. I don't necessarily want to talk about the home runs. But you made a comment I'd like you to expand on and share with the audience. 'Cause you said, "I worked hard," but that day during warm-ups, you had batting practice. You made a comment that you were in the zone. So working hard and being great as it leads up to that. But also, in the moment, 'cause that's a theme these days, in the moment, being ready and prepared. Share your thoughts on what you meant by you had a great batting practice and you just felt it. >> I'm going to take it to what you say is in the moment. I remember when I was talkin' about it yesterday, which you reference to, when I had such a fantastic batting practice. I walked by a coupla sports writers in that era. Really well-known guys, Dave Anderson, New York Times. I can't think of his name right now, but it'll come to me, of the Daily News. It was like hey man. >> John: You were rockin' it out there. >> I kind of hope I didn't leave it out here. (laughing) That was in the moment and at the same time, >> I mean, you were crushing it. >> Yes, when the game started, I got back in that moment. I got back in what was live, what was now, what was going on. Certainly, I think our world now with the instant gratification of sending out a message or tweeting to someone or whatever certainly in the moment is about what our youth is and who we are today as a country, as a universe. >> But you didn't make that up. You worked hard, but you pulled it together in the moment. >> A comment with that is I went and did something with ESPN earlier this year in San Francisco, in Oakland with Stephen Curry. They said, "Reggie, we want ya to come up "and watch his practice, his pre-game." And it was very similar to your batting practice, where people come out and watch, etc. And so I was looking forward to it and I like to go to the games about an hour and a half or two hours early so I can see warm-up and see some of the guys and say hello. And I got a chance to watch Steph Curry. I know his dad. And happened to be the first time I went this year, the dad, Carolina, the Panthers were in town. Not the Panthers. Come on, help me, help me, help me. >> Peter: The Wizards? >> No, no, no, the Carolina. >> Peter: Carolina Panthers. >> The Carolina Hornets. >> John: Hornets. >> Were there and I know his dad, Dell Curry. And we talked a little bit. But then, Steph came out and I watched him. And I watched the dribbling exhibition. I watched the going between the legs and behind the back and the fancy passing, etc. And I watched the shots, the high-arcing threes, the normal trajectory threes, the high shots off the backboard and things like that that he did. The left-handed shots, the right-handed shots. And the guy asked me what I thought of the show. And I said, "Well, it's a cool show, "but I'm going to see all that tonight." And me watching him, the behind the backs, the between the legs, the passes, the high-arching shots from three, the high-arching touches off the glass. He does all that. >> John: He brought it into the game. >> Yeah, I said so, (laughing) >> Peter: That is his game. >> It's not a show, but that's his game. >> So Reggie, you did an interesting promotion, Reggie's Garage, where you bought a virtual reality camera and you created a really nice show of your garage demonstrating your love >> Reggie: 360. >> Peter: of cars, 360. Talk a little bit about that. And then if ya get a second, imagine what baseball's going to be like as that technology becomes available and how some of the conversation that we're having about authenticity, the fan coming into the game. >> An experience. >> Is going to change baseball. Start with the garage and how that went and then how ya think that's going to translate into baseball, if you've had any thoughts on that. >> In the technology that was used, certainly I enjoyed it. While I was doing it, I noticed where the cameras were in different spots. There was one on the floor of my car. There was one in the backseat. And then there was someone following us as closely as they could. But you could see everything. You'd see the shift and you could see my feet. It was like you were with me. When we did the 360 inside the garage as well, you could listen to me and then you could use your finger and spin around. And they had these special headset and special glasses that you could look around, just with your headset on, and see all around the room. Behind you, in front of you. And so it's an experience that I think is going to become part of who we are as a nation, who we are as a people watching television, that you're going to really feel like you're in the room. I think it's going to be exciting. And I think it's going to be fun. And when you're talking about products, when you're talking about my website, if you will, with the focus on automotive parts, where a guy can go in and shop and get any part he wants for a vehicle, you really can build a complete car from my website. You can buy a frame. You can buy body parts. You can buy a horn, an engine, brakes, tires, grills, turn signals, the whole nine yards. And it gives you an experience through 360 video of really walking into the store, walking into the building, walking into the stadium and looking around to see the hot dog stand, see the dugout, see the pitcher and the hitter, to see the parts in the garage, to see the cars and take a look and view at everything that's there. >> How are players going to react to havin' the fans virtually right there with them? >> I don't think it bothers you. I don't think ya notice. I don't think they'll show anything that will affect the player that he's going to be concerned about. I think you'd have to be sensitive if they start microphoning, start micing up and then the looseness of the language would impact. So I don't think they'll go that far. But I do think the more that you can see, the more attractive the game becomes, the more interested that you can get people. When I broadcast baseball for ABC back in the 80's, I always tried to broadcast for the lady of the house, while she worked, while she cooked the meal, she didn't have time to think about a backup slider or the fastball that painted the outside corner, the changeup, etc., the sinker. I tried to broadcast for her interpretation so I could attract another fan to the game. So I think that the technology and the viewing that you'll see from behind home plate, from under the player's feet while he's running down the bases and the slides and things of that nature, Pete, I think are going to be exciting for the fan and it'll attract more fans, attract a new type of television it's going to produce, etc. So it's exciting. >> Reggie, thanks for comin' on The Cube again. Appreciate your time. I ask ya final two questions that I want to get your thoughts on. One is obviously the cars. Reggie's Garage is goin' great. And you shared with us last time on The Cube, it's on YouTube, about you when you grew up and decide football and baseball. But when you were growin' up, what was your favorite car? What was that car that you wanted that was out of reach? That car that was your hot rod? And then the second question is, we'll get to the second question. Answer that one first. What was you dream car at the time? How did ya get >> Reggie: The dream car >> John: hooked on this? >> at the time. I had a '55 Chevrolet that I bought from a buddy by the name of Ronny Fog. I don't even know if he's still around anymore. Out of Pennsylvania. I had $300 and my dad gave me $200. I'd saved up mine from workin' for my dad. But my dream car was I went to school with a guy named Wayne Gethman and another guy named Irwin Croyes. I don't know Wayne Gethman anymore. But from the age of 16, I reengaged with Irwin Croyes, who happens to be a business investing type guy in the city of Philadelphia, right where we're still from. He's a car collector. And he drove a '62 Corvette and so did Wayne Gethman. And I always wanted one. And I now happen to have four. (laughing) >> He who get the most toys wins. Final question, 'cause you're such a legend and you're awesome and you're doin' so much work. And you're very active, engaged, appreciate that. Advice to young athletes coming up, whether they're also in business or a tech athlete or a business athlete. But the sports athletes today got travel ball, you got all this stuff goin' on. The idols like Stephen Curry are lookin' great. Great role models now emerging. What advice do you give them? >> John's got a freshman in high school. I got a junior in high school. What would ya say to 'em? >> You know, I'll tell ya. When you're young, the people you want to listen to are Mom and Dad. No one, and I'll say this to any child from the age of eight or nine years old, five, six years old to 17, 18, 19, 20, all the way up, now my daughter's 25. All the way up to the end of your parents' days. No one cares for you more than your mother or your father. Any parent, whether it's a job or whether their success in life, number one in that man or woman, mom or dad, number one in their life is their children. And so for kids, I say if there's any person you're going to listen to for advice in any path you want to walk down, it's the one that your parents talk to you about or how they show you. That is what I would leave as being most important. For kids, anything, idea that you have that you believe you can do, whether it's the athlete like Stephen Curry that has created shots and done things on the basketball court that he envisioned, that he thought about. Or whether it's the next Steve Jobs who happens to be Mark Zuckerman, who I don't know Mark is 30 years old yet. >> John: He just turned 30. >> It's an idea. He's born around the same time. He's born this week. His birthday is in this week. My birthday's tomorrow. >> John: Happy birthday. >> But thank you. Anything that you can think of in today's world of technology. With places like Silicon Valley where they take dreams and create foundations for them. I had a dream about a website that would sell automotive parts and you could go to my site and buy anything for your car. We've got about 75,000 items now. We'll get to 180,000 in a few months. We'll get to a half a million as soon as my technology is ready for it. But we have things to pay attention to and look into and issues to make sure that we iron out that aren't there for our consumer, for ease of navigation, ease of consumption and purchasing. Any idea that you have, take time to dream. It's much more so than taking time to dream when I was a young kid. Because my father would say, "Stop daydreamin' "and wastin' time." >> John: Get to work. >> Reggie: In today's world, for our children, I say take time to create a vision or to create something new. And go to someone that's in the tech world and they'll figure out a way of helping you manifest it into something that's a reality. >> Listen to your parents, kids. And folks out there, dream, build the foundation, go for it. Reggie Jackson, congratulations for being a Cube alumni again, multi-return. >> Peter: Thank you very much. >> John: Appreciate it. Congratulate on all your continued success. You're a legend. Great to have you on. And thanks so much for comin' on The Cube. >> Peter: And happy 70th birthday. >> John, Pete, always a pleasure. >> John: Happy birthday. >> Thank you very much. >> Have some cake for Reggie. It's The Cube, live here in Orlando. Bringin' all the action here on The Cube. I'm John Furrier with Peter Burris with Reggie Jackson. We'll be right back. (electronic music)