>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> OpenAI The company, and ChatGPT have taken the world by storm. Microsoft reportedly is investing an additional 10 billion dollars into the company. But in our view, while the hype around ChatGPT is justified, we don't believe OpenAI will lock up the market with its first mover advantage. Rather, we believe that success in this market will be directly proportional to the quality and quantity of data that a technology company has at its disposal, and the compute power that it could deploy to run its system. Hello and welcome to this week's Wikibon CUBE insights, powered by ETR. In this Breaking Analysis, we unpack the excitement around ChatGPT, and debate the premise that the company's early entry into the space may not confer winner take all advantage to OpenAI. And to do so, we welcome CUBE collaborator, alum, Sarbjeet Johal, (chuckles) and John Furrier, co-host of the Cube. Great to see you Sarbjeet, John. Really appreciate you guys coming to the program. >> Great to be on. >> Okay, so what is ChatGPT? Well, actually we asked ChatGPT, what is ChatGPT? So here's what it said. ChatGPT is a state-of-the-art language model developed by OpenAI that can generate human-like text. It could be fine tuned for a variety of language tasks, such as conversation, summarization, and language translation. So I asked it, give it to me in 50 words or less. How did it do? Anything to add? >> Yeah, think it did good. It's large language model, like previous models, but it started applying the transformers sort of mechanism to focus on what prompt you have given it to itself. And then also the what answer it gave you in the first, sort of, one sentence or two sentences, and then introspect on itself, like what I have already said to you. And so just work on that. So it it's self sort of focus if you will. It does, the transformers help the large language models to do that. >> So to your point, it's a large language model, and GPT stands for generative pre-trained transformer. >> And if you put the definition back up there again, if you put it back up on the screen, let's see it back up. Okay, it actually missed the large, word large. So one of the problems with ChatGPT, it's not always accurate. It's actually a large language model, and it says state of the art language model. And if you look at Google, Google has dominated AI for many times and they're well known as being the best at this. And apparently Google has their own large language model, LLM, in play and have been holding it back to release because of backlash on the accuracy. Like just in that example you showed is a great point. They got almost right, but they missed the key word. >> You know what's funny about that John, is I had previously asked it in my prompt to give me it in less than a hundred words, and it was too long, I said I was too long for Breaking Analysis, and there it went into the fact that it's a large language model. So it largely, it gave me a really different answer the, for both times. So, but it's still pretty amazing for those of you who haven't played with it yet. And one of the best examples that I saw was Ben Charrington from This Week In ML AI podcast. And I stumbled on this thanks to Brian Gracely, who was listening to one of his Cloudcasts. Basically what Ben did is he took, he prompted ChatGPT to interview ChatGPT, and he simply gave the system the prompts, and then he ran the questions and answers into this avatar builder and sped it up 2X so it didn't sound like a machine. And voila, it was amazing. So John is ChatGPT going to take over as a cube host? >> Well, I was thinking, we get the questions in advance sometimes from PR people. We should actually just plug it in ChatGPT, add it to our notes, and saying, "Is this good enough for you? Let's ask the real question." So I think, you know, I think there's a lot of heavy lifting that gets done. I think the ChatGPT is a phenomenal revolution. I think it highlights the use case. Like that example we showed earlier. It gets most of it right. So it's directionally correct and it feels like it's an answer, but it's not a hundred percent accurate. And I think that's where people are seeing value in it. Writing marketing, copy, brainstorming, guest list, gift list for somebody. Write me some lyrics to a song. Give me a thesis about healthcare policy in the United States. It'll do a bang up job, and then you got to go in and you can massage it. So we're going to do three quarters of the work. That's why plagiarism and schools are kind of freaking out. And that's why Microsoft put 10 billion in, because why wouldn't this be a feature of Word, or the OS to help it do stuff on behalf of the user. So linguistically it's a beautiful thing. You can input a string and get a good answer. It's not a search result. >> And we're going to get your take on on Microsoft and, but it kind of levels the playing- but ChatGPT writes better than I do, Sarbjeet, and I know you have some good examples too. You mentioned the Reed Hastings example. >> Yeah, I was listening to Reed Hastings fireside chat with ChatGPT, and the answers were coming as sort of voice, in the voice format. And it was amazing what, he was having very sort of philosophy kind of talk with the ChatGPT, the longer sentences, like he was going on, like, just like we are talking, he was talking for like almost two minutes and then ChatGPT was answering. It was not one sentence question, and then a lot of answers from ChatGPT and yeah, you're right. I, this is our ability. I've been thinking deep about this since yesterday, we talked about, like, we want to do this segment. The data is fed into the data model. It can be the current data as well, but I think that, like, models like ChatGPT, other companies will have those too. They can, they're democratizing the intelligence, but they're not creating intelligence yet, definitely yet I can say that. They will give you all the finite answers. Like, okay, how do you do this for loop in Java, versus, you know, C sharp, and as a programmer you can do that, in, but they can't tell you that, how to write a new algorithm or write a new search algorithm for you. They cannot create a secretive code for you to- >> Not yet. >> Have competitive advantage. >> Not yet, not yet. >> but you- >> Can Google do that today? >> No one really can. The reasoning side of the data is, we talked about at our Supercloud event, with Zhamak Dehghani who's was CEO of, now of Nextdata. This next wave of data intelligence is going to come from entrepreneurs that are probably cross discipline, computer science and some other discipline. But they're going to be new things, for example, data, metadata, and data. It's hard to do reasoning like a human being, so that needs more data to train itself. So I think the first gen of this training module for the large language model they have is a corpus of text. Lot of that's why blog posts are, but the facts are wrong and sometimes out of context, because that contextual reasoning takes time, it takes intelligence. So machines need to become intelligent, and so therefore they need to be trained. So you're going to start to see, I think, a lot of acceleration on training the data sets. And again, it's only as good as the data you can get. And again, proprietary data sets will be a huge winner. Anyone who's got a large corpus of content, proprietary content like theCUBE or SiliconANGLE as a publisher will benefit from this. Large FinTech companies, anyone with large proprietary data will probably be a big winner on this generative AI wave, because it just, it will eat that up, and turn that back into something better. So I think there's going to be a lot of interesting things to look at here. And certainly productivity's going to be off the charts for vanilla and the internet is going to get swarmed with vanilla content. So if you're in the content business, and you're an original content producer of any kind, you're going to be not vanilla, so you're going to be better. So I think there's so much at play Dave (indistinct). >> I think the playing field has been risen, so we- >> Risen and leveled? >> Yeah, and leveled to certain extent. So it's now like that few people as consumers, as consumers of AI, we will have a advantage and others cannot have that advantage. So it will be democratized. That's, I'm sure about that. But if you take the example of calculator, when the calculator came in, and a lot of people are, "Oh, people can't do math anymore because calculator is there." right? So it's a similar sort of moment, just like a calculator for the next level. But, again- >> I see it more like open source, Sarbjeet, because like if you think about what ChatGPT's doing, you do a query and it comes from somewhere the value of a post from ChatGPT is just a reuse of AI. The original content accent will be come from a human. So if I lay out a paragraph from ChatGPT, did some heavy lifting on some facts, I check the facts, save me about maybe- >> Yeah, it's productive. >> An hour writing, and then I write a killer two, three sentences of, like, sharp original thinking or critical analysis. I then took that body of work, open source content, and then laid something on top of it. >> And Sarbjeet's example is a good one, because like if the calculator kids don't do math as well anymore, the slide rule, remember we had slide rules as kids, remember we first started using Waze, you know, we were this minority and you had an advantage over other drivers. Now Waze is like, you know, social traffic, you know, navigation, everybody had, you know- >> All the back roads are crowded. >> They're car crowded. (group laughs) Exactly. All right, let's, let's move on. What about this notion that futurist Ray Amara put forth and really Amara's Law that we're showing here, it's, the law is we, you know, "We tend to overestimate the effect of technology in the short run and underestimate it in the long run." Is that the case, do you think, with ChatGPT? What do you think Sarbjeet? >> I think that's true actually. There's a lot of, >> We don't debate this. >> There's a lot of awe, like when people see the results from ChatGPT, they say what, what the heck? Like, it can do this? But then if you use it more and more and more, and I ask the set of similar question, not the same question, and it gives you like same answer. It's like reading from the same bucket of text in, the interior read (indistinct) where the ChatGPT, you will see that in some couple of segments. It's very, it sounds so boring that the ChatGPT is coming out the same two sentences every time. So it is kind of good, but it's not as good as people think it is right now. But we will have, go through this, you know, hype sort of cycle and get realistic with it. And then in the long term, I think it's a great thing in the short term, it's not something which will (indistinct) >> What's your counter point? You're saying it's not. >> I, no I think the question was, it's hyped up in the short term and not it's underestimated long term. That's what I think what he said, quote. >> Yes, yeah. That's what he said. >> Okay, I think that's wrong with this, because this is a unique, ChatGPT is a unique kind of impact and it's very generational. People have been comparing it, I have been comparing to the internet, like the web, web browser Mosaic and Netscape, right, Navigator. I mean, I clearly still remember the days seeing Navigator for the first time, wow. And there weren't not many sites you could go to, everyone typed in, you know, cars.com, you know. >> That (indistinct) wasn't that overestimated, the overhyped at the beginning and underestimated. >> No, it was, it was underestimated long run, people thought. >> But that Amara's law. >> That's what is. >> No, they said overestimated? >> Overestimated near term underestimated- overhyped near term, underestimated long term. I got, right I mean? >> Well, I, yeah okay, so I would then agree, okay then- >> We were off the charts about the internet in the early days, and it actually exceeded our expectations. >> Well there were people who were, like, poo-pooing it early on. So when the browser came out, people were like, "Oh, the web's a toy for kids." I mean, in 1995 the web was a joke, right? So '96, you had online populations growing, so you had structural changes going on around the browser, internet population. And then that replaced other things, direct mail, other business activities that were once analog then went to the web, kind of read only as you, as we always talk about. So I think that's a moment where the hype long term, the smart money, and the smart industry experts all get the long term. And in this case, there's more poo-pooing in the short term. "Ah, it's not a big deal, it's just AI." I've heard many people poo-pooing ChatGPT, and a lot of smart people saying, "No this is next gen, this is different and it's only going to get better." So I think people are estimating a big long game on this one. >> So you're saying it's bifurcated. There's those who say- >> Yes. >> Okay, all right, let's get to the heart of the premise, and possibly the debate for today's episode. Will OpenAI's early entry into the market confer sustainable competitive advantage for the company. And if you look at the history of tech, the technology industry, it's kind of littered with first mover failures. Altair, IBM, Tandy, Commodore, they and Apple even, they were really early in the PC game. They took a backseat to Dell who came in the scene years later with a better business model. Netscape, you were just talking about, was all the rage in Silicon Valley, with the first browser, drove up all the housing prices out here. AltaVista was the first search engine to really, you know, index full text. >> Owned by Dell, I mean DEC. >> Owned by Digital. >> Yeah, Digital Equipment >> Compaq bought it. And of course as an aside, Digital, they wanted to showcase their hardware, right? Their super computer stuff. And then so Friendster and MySpace, they came before Facebook. The iPhone certainly wasn't the first mobile device. So lots of failed examples, but there are some recent successes like AWS and cloud. >> You could say smartphone. So I mean. >> Well I know, and you can, we can parse this so we'll debate it. Now Twitter, you could argue, had first mover advantage. You kind of gave me that one John. Bitcoin and crypto clearly had first mover advantage, and sustaining that. Guys, will OpenAI make it to the list on the right with ChatGPT, what do you think? >> I think categorically as a company, it probably won't, but as a category, I think what they're doing will, so OpenAI as a company, they get funding, there's power dynamics involved. Microsoft put a billion dollars in early on, then they just pony it up. Now they're reporting 10 billion more. So, like, if the browsers, Microsoft had competitive advantage over Netscape, and used monopoly power, and convicted by the Department of Justice for killing Netscape with their monopoly, Netscape should have had won that battle, but Microsoft killed it. In this case, Microsoft's not killing it, they're buying into it. So I think the embrace extend Microsoft power here makes OpenAI vulnerable for that one vendor solution. So the AI as a company might not make the list, but the category of what this is, large language model AI, is probably will be on the right hand side. >> Okay, we're going to come back to the government intervention and maybe do some comparisons, but what are your thoughts on this premise here? That, it will basically set- put forth the premise that it, that ChatGPT, its early entry into the market will not confer competitive advantage to >> For OpenAI. >> To Open- Yeah, do you agree with that? >> I agree with that actually. It, because Google has been at it, and they have been holding back, as John said because of the scrutiny from the Fed, right, so- >> And privacy too. >> And the privacy and the accuracy as well. But I think Sam Altman and the company on those guys, right? They have put this in a hasty way out there, you know, because it makes mistakes, and there are a lot of questions around the, sort of, where the content is coming from. You saw that as your example, it just stole the content, and without your permission, you know? >> Yeah. So as quick this aside- >> And it codes on people's behalf and the, those codes are wrong. So there's a lot of, sort of, false information it's putting out there. So it's a very vulnerable thing to do what Sam Altman- >> So even though it'll get better, others will compete. >> So look, just side note, a term which Reid Hoffman used a little bit. Like he said, it's experimental launch, like, you know, it's- >> It's pretty damn good. >> It is clever because according to Sam- >> It's more than clever. It's good. >> It's awesome, if you haven't used it. I mean you write- you read what it writes and you go, "This thing writes so well, it writes so much better than you." >> The human emotion drives that too. I think that's a big thing. But- >> I Want to add one more- >> Make your last point. >> Last one. Okay. So, but he's still holding back. He's conducting quite a few interviews. If you want to get the gist of it, there's an interview with StrictlyVC interview from yesterday with Sam Altman. Listen to that one it's an eye opening what they want- where they want to take it. But my last one I want to make it on this point is that Satya Nadella yesterday did an interview with Wall Street Journal. I think he was doing- >> You were not impressed. >> I was not impressed because he was pushing it too much. So Sam Altman's holding back so there's less backlash. >> Got 10 billion reasons to push. >> I think he's almost- >> Microsoft just laid off 10000 people. Hey ChatGPT, find me a job. You know like. (group laughs) >> He's overselling it to an extent that I think it will backfire on Microsoft. And he's over promising a lot of stuff right now, I think. I don't know why he's very jittery about all these things. And he did the same thing during Ignite as well. So he said, "Oh, this AI will write code for you and this and that." Like you called him out- >> The hyperbole- >> During your- >> from Satya Nadella, he's got a lot of hyperbole. (group talks over each other) >> All right, Let's, go ahead. >> Well, can I weigh in on the whole- >> Yeah, sure. >> Microsoft thing on whether OpenAI, here's the take on this. I think it's more like the browser moment to me, because I could relate to that experience with ChatG, personally, emotionally, when I saw that, and I remember vividly- >> You mean that aha moment (indistinct). >> Like this is obviously the future. Anything else in the old world is dead, website's going to be everywhere. It was just instant dot connection for me. And a lot of other smart people who saw this. Lot of people by the way, didn't see it. Someone said the web's a toy. At the company I was worked for at the time, Hewlett Packard, they like, they could have been in, they had invented HTML, and so like all this stuff was, like, they just passed, the web was just being passed over. But at that time, the browser got better, more websites came on board. So the structural advantage there was online web usage was growing, online user population. So that was growing exponentially with the rise of the Netscape browser. So OpenAI could stay on the right side of your list as durable, if they leverage the category that they're creating, can get the scale. And if they can get the scale, just like Twitter, that failed so many times that they still hung around. So it was a product that was always successful, right? So I mean, it should have- >> You're right, it was terrible, we kept coming back. >> The fail whale, but it still grew. So OpenAI has that moment. They could do it if Microsoft doesn't meddle too much with too much power as a vendor. They could be the Netscape Navigator, without the anti-competitive behavior of somebody else. So to me, they have the pole position. So they have an opportunity. So if not, if they don't execute, then there's opportunity. There's not a lot of barriers to entry, vis-a-vis say the CapEx of say a cloud company like AWS. You can't replicate that, Many have tried, but I think you can replicate OpenAI. >> And we're going to talk about that. Okay, so real quick, I want to bring in some ETR data. This isn't an ETR heavy segment, only because this so new, you know, they haven't coverage yet, but they do cover AI. So basically what we're seeing here is a slide on the vertical axis's net score, which is a measure of spending momentum, and in the horizontal axis's is presence in the dataset. Think of it as, like, market presence. And in the insert right there, you can see how the dots are plotted, the two columns. And so, but the key point here that we want to make, there's a bunch of companies on the left, is he like, you know, DataRobot and C3 AI and some others, but the big whales, Google, AWS, Microsoft, are really dominant in this market. So that's really the key takeaway that, can we- >> I notice IBM is way low. >> Yeah, IBM's low, and actually bring that back up and you, but then you see Oracle who actually is injecting. So I guess that's the other point is, you're not necessarily going to go buy AI, and you know, build your own AI, you're going to, it's going to be there and, it, Salesforce is going to embed it into its platform, the SaaS companies, and you're going to purchase AI. You're not necessarily going to build it. But some companies obviously are. >> I mean to quote IBM's general manager Rob Thomas, "You can't have AI with IA." information architecture and David Flynn- >> You can't Have AI without IA >> without, you can't have AI without IA. You can't have, if you have an Information Architecture, you then can power AI. Yesterday David Flynn, with Hammersmith, was on our Supercloud. He was pointing out that the relationship of storage, where you store things, also impacts the data and stressablity, and Zhamak from Nextdata, she was pointing out that same thing. So the data problem factors into all this too, Dave. >> So you got the big cloud and internet giants, they're all poised to go after this opportunity. Microsoft is investing up to 10 billion. Google's code red, which was, you know, the headline in the New York Times. Of course Apple is there and several alternatives in the market today. Guys like Chinchilla, Bloom, and there's a company Jasper and several others, and then Lena Khan looms large and the government's around the world, EU, US, China, all taking notice before the market really is coalesced around a single player. You know, John, you mentioned Netscape, they kind of really, the US government was way late to that game. It was kind of game over. And Netscape, I remember Barksdale was like, "Eh, we're going to be selling software in the enterprise anyway." and then, pshew, the company just dissipated. So, but it looks like the US government, especially with Lena Khan, they're changing the definition of antitrust and what the cause is to go after people, and they're really much more aggressive. It's only what, two years ago that (indistinct). >> Yeah, the problem I have with the federal oversight is this, they're always like late to the game, and they're slow to catch up. So in other words, they're working on stuff that should have been solved a year and a half, two years ago around some of the social networks hiding behind some of the rules around open web back in the days, and I think- >> But they're like 15 years late to that. >> Yeah, and now they got this new thing on top of it. So like, I just worry about them getting their fingers. >> But there's only two years, you know, OpenAI. >> No, but the thing (indistinct). >> No, they're still fighting other battles. But the problem with government is that they're going to label Big Tech as like a evil thing like Pharma, it's like smoke- >> You know Lena Khan wants to kill Big Tech, there's no question. >> So I think Big Tech is getting a very seriously bad rap. And I think anything that the government does that shades darkness on tech, is politically motivated in most cases. You can almost look at everything, and my 80 20 rule is in play here. 80% of the government activity around tech is bullshit, it's politically motivated, and the 20% is probably relevant, but off the mark and not organized. >> Well market forces have always been the determining factor of success. The governments, you know, have been pretty much failed. I mean you look at IBM's antitrust, that, what did that do? The market ultimately beat them. You look at Microsoft back in the day, right? Windows 95 was peaking, the government came in. But you know, like you said, they missed the web, right, and >> so they were hanging on- >> There's nobody in government >> to Windows. >> that actually knows- >> And so, you, I think you're right. It's market forces that are going to determine this. But Sarbjeet, what do you make of Microsoft's big bet here, you weren't impressed with with Nadella. How do you think, where are they going to apply it? Is this going to be a Hail Mary for Bing, or is it going to be applied elsewhere? What do you think. >> They are saying that they will, sort of, weave this into their products, office products, productivity and also to write code as well, developer productivity as well. That's a big play for them. But coming back to your antitrust sort of comments, right? I believe the, your comment was like, oh, fed was late 10 years or 15 years earlier, but now they're two years. But things are moving very fast now as compared to they used to move. >> So two years is like 10 Years. >> Yeah, two years is like 10 years. Just want to make that point. (Dave laughs) This thing is going like wildfire. Any new tech which comes in that I think they're going against distribution channels. Lina Khan has commented time and again that the marketplace model is that she wants to have some grip on. Cloud marketplaces are a kind of monopolistic kind of way. >> I don't, I don't see this, I don't see a Chat AI. >> You told me it's not Bing, you had an interesting comment. >> No, no. First of all, this is great from Microsoft. If you're Microsoft- >> Why? >> Because Microsoft doesn't have the AI chops that Google has, right? Google is got so much core competency on how they run their search, how they run their backends, their cloud, even though they don't get a lot of cloud market share in the enterprise, they got a kick ass cloud cause they needed one. >> Totally. >> They've invented SRE. I mean Google's development and engineering chops are off the scales, right? Amazon's got some good chops, but Google's got like 10 times more chops than AWS in my opinion. Cloud's a whole different story. Microsoft gets AI, they get a playbook, they get a product they can render into, the not only Bing, productivity software, helping people write papers, PowerPoint, also don't forget the cloud AI can super help. We had this conversation on our Supercloud event, where AI's going to do a lot of the heavy lifting around understanding observability and managing service meshes, to managing microservices, to turning on and off applications, and or maybe writing code in real time. So there's a plethora of use cases for Microsoft to deploy this. combined with their R and D budgets, they can then turbocharge more research, build on it. So I think this gives them a car in the game, Google may have pole position with AI, but this puts Microsoft right in the game, and they already have a lot of stuff going on. But this just, I mean everything gets lifted up. Security, cloud, productivity suite, everything. >> What's under the hood at Google, and why aren't they talking about it? I mean they got to be freaked out about this. No? Or do they have kind of a magic bullet? >> I think they have the, they have the chops definitely. Magic bullet, I don't know where they are, as compared to the ChatGPT 3 or 4 models. Like they, but if you look at the online sort of activity and the videos put out there from Google folks, Google technology folks, that's account you should look at if you are looking there, they have put all these distinctions what ChatGPT 3 has used, they have been talking about for a while as well. So it's not like it's a secret thing that you cannot replicate. As you said earlier, like in the beginning of this segment, that anybody who has more data and the capacity to process that data, which Google has both, I think they will win this. >> Obviously living in Palo Alto where the Google founders are, and Google's headquarters next town over we have- >> We're so close to them. We have inside information on some of the thinking and that hasn't been reported by any outlet yet. And that is, is that, from what I'm hearing from my sources, is Google has it, they don't want to release it for many reasons. One is it might screw up their search monopoly, one, two, they're worried about the accuracy, 'cause Google will get sued. 'Cause a lot of people are jamming on this ChatGPT as, "Oh it does everything for me." when it's clearly not a hundred percent accurate all the time. >> So Lina Kahn is looming, and so Google's like be careful. >> Yeah so Google's just like, this is the third, could be a third rail. >> But the first thing you said is a concern. >> Well no. >> The disruptive (indistinct) >> What they will do is do a Waymo kind of thing, where they spin out a separate company. >> They're doing that. >> The discussions happening, they're going to spin out the separate company and put it over there, and saying, "This is AI, got search over there, don't touch that search, 'cause that's where all the revenue is." (chuckles) >> So, okay, so that's how they deal with the Clay Christensen dilemma. What's the business model here? I mean it's not advertising, right? Is it to charge you for a query? What, how do you make money at this? >> It's a good question, I mean my thinking is, first of all, it's cool to type stuff in and see a paper get written, or write a blog post, or gimme a marketing slogan for this or that or write some code. I think the API side of the business will be critical. And I think Howie Xu, I know you're going to reference some of his comments yesterday on Supercloud, I think this brings a whole 'nother user interface into technology consumption. I think the business model, not yet clear, but it will probably be some sort of either API and developer environment or just a straight up free consumer product, with some sort of freemium backend thing for business. >> And he was saying too, it's natural language is the way in which you're going to interact with these systems. >> I think it's APIs, it's APIs, APIs, APIs, because these people who are cooking up these models, and it takes a lot of compute power to train these and to, for inference as well. Somebody did the analysis on the how many cents a Google search costs to Google, and how many cents the ChatGPT query costs. It's, you know, 100x or something on that. You can take a look at that. >> A 100x on which side? >> You're saying two orders of magnitude more expensive for ChatGPT >> Much more, yeah. >> Than for Google. >> It's very expensive. >> So Google's got the data, they got the infrastructure and they got, you're saying they got the cost (indistinct) >> No actually it's a simple query as well, but they are trying to put together the answers, and they're going through a lot more data versus index data already, you know. >> Let me clarify, you're saying that Google's version of ChatGPT is more efficient? >> No, I'm, I'm saying Google search results. >> Ah, search results. >> What are used to today, but cheaper. >> But that, does that, is that going to confer advantage to Google's large language (indistinct)? >> It will, because there were deep science (indistinct). >> Google, I don't think Google search is doing a large language model on their search, it's keyword search. You know, what's the weather in Santa Cruz? Or how, what's the weather going to be? Or you know, how do I find this? Now they have done a smart job of doing some things with those queries, auto complete, re direct navigation. But it's, it's not entity. It's not like, "Hey, what's Dave Vellante thinking this week in Breaking Analysis?" ChatGPT might get that, because it'll get your Breaking Analysis, it'll synthesize it. There'll be some, maybe some clips. It'll be like, you know, I mean. >> Well I got to tell you, I asked ChatGPT to, like, I said, I'm going to enter a transcript of a discussion I had with Nir Zuk, the CTO of Palo Alto Networks, And I want you to write a 750 word blog. I never input the transcript. It wrote a 750 word blog. It attributed quotes to him, and it just pulled a bunch of stuff that, and said, okay, here it is. It talked about Supercloud, it defined Supercloud. >> It's made, it makes you- >> Wow, But it was a big lie. It was fraudulent, but still, blew me away. >> Again, vanilla content and non accurate content. So we are going to see a surge of misinformation on steroids, but I call it the vanilla content. Wow, that's just so boring, (indistinct). >> There's so many dangers. >> Make your point, cause we got to, almost out of time. >> Okay, so the consumption, like how do you consume this thing. As humans, we are consuming it and we are, like, getting a nicely, like, surprisingly shocked, you know, wow, that's cool. It's going to increase productivity and all that stuff, right? And on the danger side as well, the bad actors can take hold of it and create fake content and we have the fake sort of intelligence, if you go out there. So that's one thing. The second thing is, we are as humans are consuming this as language. Like we read that, we listen to it, whatever format we consume that is, but the ultimate usage of that will be when the machines can take that output from likes of ChatGPT, and do actions based on that. The robots can work, the robot can paint your house, we were talking about, right? Right now we can't do that. >> Data apps. >> So the data has to be ingested by the machines. It has to be digestible by the machines. And the machines cannot digest unorganized data right now, we will get better on the ingestion side as well. So we are getting better. >> Data, reasoning, insights, and action. >> I like that mall, paint my house. >> So, okay- >> By the way, that means drones that'll come in. Spray painting your house. >> Hey, it wasn't too long ago that robots couldn't climb stairs, as I like to point out. Okay, and of course it's no surprise the venture capitalists are lining up to eat at the trough, as I'd like to say. Let's hear, you'd referenced this earlier, John, let's hear what AI expert Howie Xu said at the Supercloud event, about what it takes to clone ChatGPT. Please, play the clip. >> So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest to get a, you know, another shot to the openAI sort of the level." You know, I did a (indistinct) >> Line up. >> A hundred million dollar is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So a hundred- >> Guys a hundred million dollars, that's an astoundingly low figure. What do you make of it? >> I was in an interview with, I was interviewing, I think he said hundred million or so, but in the hundreds of millions, not a billion right? >> You were trying to get him up, you were like "Hundreds of millions." >> Well I think, I- >> He's like, eh, not 10, not a billion. >> Well first of all, Howie Xu's an expert machine learning. He's at Zscaler, he's a machine learning AI guy. But he comes from VMware, he's got his technology pedigrees really off the chart. Great friend of theCUBE and kind of like a CUBE analyst for us. And he's smart. He's right. I think the barriers to entry from a dollar standpoint are lower than say the CapEx required to compete with AWS. Clearly, the CapEx spending to build all the tech for the run a cloud. >> And you don't need a huge sales force. >> And in some case apps too, it's the same thing. But I think it's not that hard. >> But am I right about that? You don't need a huge sales force either. It's, what, you know >> If the product's good, it will sell, this is a new era. The better mouse trap will win. This is the new economics in software, right? So- >> Because you look at the amount of money Lacework, and Snyk, Snowflake, Databrooks. Look at the amount of money they've raised. I mean it's like a billion dollars before they get to IPO or more. 'Cause they need promotion, they need go to market. You don't need (indistinct) >> OpenAI's been working on this for multiple five years plus it's, hasn't, wasn't born yesterday. Took a lot of years to get going. And Sam is depositioning all the success, because he's trying to manage expectations, To your point Sarbjeet, earlier. It's like, yeah, he's trying to "Whoa, whoa, settle down everybody, (Dave laughs) it's not that great." because he doesn't want to fall into that, you know, hero and then get taken down, so. >> It may take a 100 million or 150 or 200 million to train the model. But to, for the inference to, yeah to for the inference machine, It will take a lot more, I believe. >> Give it, so imagine, >> Because- >> Go ahead, sorry. >> Go ahead. But because it consumes a lot more compute cycles and it's certain level of storage and everything, right, which they already have. So I think to compute is different. To frame the model is a different cost. But to run the business is different, because I think 100 million can go into just fighting the Fed. >> Well there's a flywheel too. >> Oh that's (indistinct) >> (indistinct) >> We are running the business, right? >> It's an interesting number, but it's also kind of, like, context to it. So here, a hundred million spend it, you get there, but you got to factor in the fact that the ways companies win these days is critical mass scale, hitting a flywheel. If they can keep that flywheel of the value that they got going on and get better, you can almost imagine a marketplace where, hey, we have proprietary data, we're SiliconANGLE in theCUBE. We have proprietary content, CUBE videos, transcripts. Well wouldn't it be great if someone in a marketplace could sell a module for us, right? We buy that, Amazon's thing and things like that. So if they can get a marketplace going where you can apply to data sets that may be proprietary, you can start to see this become bigger. And so I think the key barriers to entry is going to be success. I'll give you an example, Reddit. Reddit is successful and it's hard to copy, not because of the software. >> They built the moat. >> Because you can, buy Reddit open source software and try To compete. >> They built the moat with their community. >> Their community, their scale, their user expectation. Twitter, we referenced earlier, that thing should have gone under the first two years, but there was such a great emotional product. People would tolerate the fail whale. And then, you know, well that was a whole 'nother thing. >> Then a plane landed in (John laughs) the Hudson and it was over. >> I think verticals, a lot of verticals will build applications using these models like for lawyers, for doctors, for scientists, for content creators, for- >> So you'll have many hundreds of millions of dollars investments that are going to be seeping out. If, all right, we got to wrap, if you had to put odds on it that that OpenAI is going to be the leader, maybe not a winner take all leader, but like you look at like Amazon and cloud, they're not winner take all, these aren't necessarily winner take all markets. It's not necessarily a zero sum game, but let's call it winner take most. What odds would you give that open AI 10 years from now will be in that position. >> If I'm 0 to 10 kind of thing? >> Yeah, it's like horse race, 3 to 1, 2 to 1, even money, 10 to 1, 50 to 1. >> Maybe 2 to 1, >> 2 to 1, that's pretty low odds. That's basically saying they're the favorite, they're the front runner. Would you agree with that? >> I'd say 4 to 1. >> Yeah, I was going to say I'm like a 5 to 1, 7 to 1 type of person, 'cause I'm a skeptic with, you know, there's so much competition, but- >> I think they're definitely the leader. I mean you got to say, I mean. >> Oh there's no question. There's no question about it. >> The question is can they execute? >> They're not Friendster, is what you're saying. >> They're not Friendster and they're more like Twitter and Reddit where they have momentum. If they can execute on the product side, and if they don't stumble on that, they will continue to have the lead. >> If they say stay neutral, as Sam is, has been saying, that, hey, Microsoft is one of our partners, if you look at their company model, how they have structured the company, then they're going to pay back to the investors, like Microsoft is the biggest one, up to certain, like by certain number of years, they're going to pay back from all the money they make, and after that, they're going to give the money back to the public, to the, I don't know who they give it to, like non-profit or something. (indistinct) >> Okay, the odds are dropping. (group talks over each other) That's a good point though >> Actually they might have done that to fend off the criticism of this. But it's really interesting to see the model they have adopted. >> The wildcard in all this, My last word on this is that, if there's a developer shift in how developers and data can come together again, we have conferences around the future of data, Supercloud and meshs versus, you know, how the data world, coding with data, how that evolves will also dictate, 'cause a wild card could be a shift in the landscape around how developers are using either machine learning or AI like techniques to code into their apps, so. >> That's fantastic insight. I can't thank you enough for your time, on the heels of Supercloud 2, really appreciate it. All right, thanks to John and Sarbjeet for the outstanding conversation today. Special thanks to the Palo Alto studio team. My goodness, Anderson, this great backdrop. You guys got it all out here, I'm jealous. And Noah, really appreciate it, Chuck, Andrew Frick and Cameron, Andrew Frick switching, Cameron on the video lake, great job. And Alex Myerson, he's on production, manages the podcast for us, Ken Schiffman as well. Kristen Martin and Cheryl Knight help get the word out on social media and our newsletters. Rob Hof is our editor-in-chief over at SiliconANGLE, does some great editing, thanks to all. Remember, all these episodes are available as podcasts. All you got to do is search Breaking Analysis podcast, wherever you listen. Publish each week on wikibon.com and siliconangle.com. Want to get in touch, email me directly, david.vellante@siliconangle.com or DM me at dvellante, or comment on our LinkedIn post. And by all means, check out etr.ai. They got really great survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, We'll see you next time on Breaking Analysis. (electronic music)

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation hey welcome back here writer jeff rick here with the cube we're in our Palo Alto studios you know kind of continuing our leadership coverage reaching out to the community for people that we've got in our community to get their take on you know how they're dealing with the Kovach crisis how they're helping to contribute back to the community to to bring their resources to bear and you know just some general good tips and tricks of getting through these kind of challenging times and we're really excited to have one of my favorite guests he's being used to come on all the time we haven't had them on for three years which I can't believe it sabi Mehta the CEO of true SATA founder to say to obby I checked the record I can't believe it's been three years since we last that down great to see you Jeff there's well first of all it's always a pleasure and I think the only person to blame for that is you Jeff well I will make sure that it doesn't happen again so in just a check-in how's things going with the family the company thank you for asking you know family is great we have I've got two young kids who have become video conferencing experts and they don't teach me the tricks for it which I'm sure is happening a lot of families around the world and the team is great we vent remote at this point almost almost two months ago down and can't complain I think their intellectual property business like you are so it's been a little easier for us to go remote compared to a lot of other businesses in the world and in America but no complaints it'll be very fortunate we are glad that we have a business and a company that can withstand the the economic uncertainty and the family's great I hope the same for the queue family I haven't seen Dave and John and it's good to see you again and I hope all of you guys are helped happy and healthy great I think in we're good so thank you for asking so let's jump into it you know one of the things that I've always loved about you is you know really your sense of culture and this kind of constant reinforcing of culture in your social media posts and the company blog post at true SATA you know celebrating your interns and and you really have a good pulse for that and you know I just I think we may even talked about it before about you know kind of the CEOs and leadership and and social media those that do and that and those that don't and you know I think it's it's probably from any kind of a risk reward trade-off you know I could say something group it versus what am I getting at it but really it's super important and in these times with the distributed workforce that the the importance and value of communicating and culture and touching your people frequently across a lot of different mediums and topic areas is is more important than ever before share with us kind of your strategy why did you figure this out early how have you you know kind of adjusted you know your method of keeping your team up and communicating absolutely like I guess I owe you guys a little bit of gratitude for it which is we launched our company and you know I'm showing a member on the cube it was a social media launch you know if you say that say it like that I think there are two or three things that are very important Jeff and you hit on all of them one is the emphasis on information sharing it becomes more important than times like these and we as as a society value the ability to share a positive conversation of positive perspective and a positive outlook more but since day zero at the seder we've had this philosophy that there are no secrets it is important to be open and transparent both inside and outside the company and that our legacy is going to be defined by what we do for the community and not just what we do for our shareholders and by its very nature the fact that you know I grew up in a different continent now live and call America now a different continent my home I guess I was it's very important for me to stay connected to my roots it is a good memory or reminder that the world is very interconnected unfortunately the pandemic is the is the best or worst example of it in a really weird way but I think it's also a very important point Jeff that I believe we learned early and I hope coming out from this is something that we don't lose the point you made about kindness social media and social networking has a massively in my opinion massively positive binding force for the world at the same time there were certain business models it tried to capitalize on the negative aspects of it you know whether they are the the commercialized versions of slam books or not so nice business models that capitalize on the ability for people to complain I hope that people society and us humans coming out of it learn from people like yourself or you know the small voice that I have on social media or the messages we share and we are kinda in what we do online because the ability to have networks that are viral and can propagate or self propagate is a very positive unifying force and I hope out of this pandemic we all realize the positive nature's of it more than the negative nature's of it because unfortunately as you know that our business models built on the negative forces of social media and I really really hope they're coming out of this are positive voices drown out the negative voices that's great point and and it's a great I want to highlight a quote from one of your blog's again I think you're just a phenomenal communicator and in relationship to what's going on with kovat and and I quote we are fighting fear pain and anxiety as much as we are fighting the virus this is our humble attempt to we'll get into what you guys did to help the thousands of first responders clerks rockstars but I just really want to stick with that kindness theme you know I used to or I still joke right that the greatest smile in technology today is our G from signal FX the guys are gonna throw up a picture of him he's a great guy he looks like everybody's favorite I love that guy but therefore signal effects and actually it's funny signal FX also launched on the cube at big data a big data show I used to say the greatest smile intact is avi Mehta I mean how can I go wrong and and what I when I reached out to you I I do I consciously thought what what more important time do we have than to see people like you with a big smile with the great positive attitude focusing on on the positives and and I just think it's so important and it segues nicely into what we used to talk about it the strata shows and the big data shows all the time everyone wanted to talk about Hadoop and big data you always stress is never about the technology it's about the application of the technology and you focus your company on that very where that laser focus from day one now it's so great to see is we think you know the bad news about kovat a lot of bad news but one of the good news is is you know there's never been as much technology compute horsepower big data analytics smart people like yourself to bring a whole different set of tools to the battle than just building Liberty ships or building playing planes or tanks so you guys have a very aggressive thing that you're doing tell us a little bit about is the kovat active transmission the coat if you will tell us about what that is how did it come to be and what are you hoping to accomplish of course so first of all you're too kind you know thank you so much I think you also were the first people to give me a hard time about my new or Twitter picture I put on and he said what are you doing RV you know you have a good smile come on give me the smile die so thank you you're very kind Jeff I think as I as we as you know and I know I think you've a lot to be thankful for in life and there's no reason why we should not smile no matter what the circumstance we have so much to be thankful for and also I am remiss happy Earth Day you know I'm rocking my green for Earth Day as well as Ramadan Kareem today is the first day of Ramadan and you know I I wish everybody in the world Ramadan Kareem and on that friend right on that trend of how does do we as a community come together when faced with crisis so Court was a very simple thing you know it's I'm thank you for recognizing the hard work of the team that led it it was an idea I came up with it you know in the shower I'm like there are two kinds of people or to your you can we have we as humans have a choice when history is being made which I do believe I do believe history is being made right whether you look at it economically and a economic shock and that we have not felt as humanity since the depression so you look at it socially and again something we haven't seen sin the Spanish blue history is being made in in these times and I think we as humans have a choice we can either be witnesses to it or play our part in helping shape it and coat was our humble tiny attempt to when we look back when history was being made we chose to not just sit on the sidelines but be a part of trying to be part of the solution so all riddled with code was take a small idea I had team gets the entire credit read they ran with it and the idea was there was a lot of data being open sourced around co-ed a lot of work being done around reporting what is happening but nothing was being done around reporting or thinking through using the data to predict what could happen with it and that was code with code we try to make the first code wonder oh that came out almost two weeks ago now when you first contacted us was predicting the spread and the idea around breaking the spread wasn't just saying here is the number of cases a number of deaths and know what to be very off we wanted to provide like you know how firefighters do can we predict where it may go to next at a county by county level so we could create a little bit of a firewall to help it from stop you know have the spread of it to be slower in no ways are we claiming that if you did port you can stop it but if he could create firewalls around it and distribute tests not just in areas and cities and counties where it is you know spiking but look at the areas and counties where it's about to go to so we use a inner inner in-house Network algorithm we call that Orion and we were able to start predicting where the virus is gonna go to we also then quickly realize that this could be an interesting where an extra you know arrow and the quiver in our fight we should also think about where are there green shoots around where can recovery be be helped so before you know the the president email announced this it was surrender serendipitous before the the president came and said I want to start finding the green shoes to open the country we then did quote $2 which we announced a week ago with the green shoots around a true sailor recovery index and the recovery index is looking at its car like a meta algorithm we're looking at the rates of change of the rates of change so if you're seeing the change of the rates of change you know the meta part we're declining we're saying there are early shoots that we if as we plan to reopen our economy in our country these are the counties to look at first that was the second attempt of code and the third attempt we have done is we calling it the odd are we there yet index it got announced yesterday and now - you're the first public announcement of it and the are we there yet index is using the government's definition of the phase 1 phase 2 phase 3 and we are making a prediction on where which are the counties that are ready to be open up and there's good news everywhere in the country but we we are predicting there are 73 different counties that ask for the government's definition of ready to open are ready to open that's all you know we were able to launch the app in five days it is free for all first responders all hospital chains all not-for-profit organizations trying to help the country through this pandemic and poor profit operations who want to use the data to get tests out to get antibodies out and to get you know the clinical trials out so we have made a commitment that we will not charge for code through - for any of those organizations to have the country open are very very small attempt to add another dimension to the fight you know it's data its analytics I'm not a first responder this makes me sleep well at night that I'm at least we're trying to help you know right well just for the true heroes right the true heroes this is our our humble attempt to help them and recognize that their effort should not go to its hobby that that's great because you know there is data and there is analytics and there is you know algorithms and the things that we've developed to help people you know pick they're better next purchase at Amazon or where they gonna watch next on Netflix and it's such a great application no it's funny I just finished a book called ghost Bob and is a story of the cholera epidemic in London in like 1850 something or other about four but what's really interesting at that point in time is they didn't know about waterborne diseases they thought everything kind of went through the air and and it was really a couple of individuals in using data in a new and more importantly mapping different types of datasets on top of it and now this is it's as this map that were they basically figured out where the the pump was that was polluting everybody but it was a great story and you know kind of changing the narrative by using data in a new novel and creative way to get to an answer that they couldn't and you know they're there's so much data out there but then they're so short a date I'm just curious from a data science point of view you know um you know there there aren't enough tests for you know antibodies who's got it there aren't enough tests for just are you sick and then you know we're slowly getting the data on the desk which is changing all the time you know recently announced that the first Bay Area deaths were actually a month were they before they thought they were so as you look at what you're trying to accomplish what are some of the great datasets out there and how are you working around some of the the lack of data in things like you know test results are you kind of organizing pulling that together what would you like to see more of that's why I like talking to you so I missed you you are these good questions of me excellent point I think there are three things I would like to highlight number one it doesn't take your point that you made with the with the plethora of technical advances and this S curve shift that these first spoke at the cube almost eleven years ago to the date now or ten years ago just the idea of you know population level or modeling that cluster computing is finally democratized so everybody can run complicated tests and a unique segment or one and this is the beauty of what we should be doing in the pandemic I'm coming I'm coming I'm quite surprised actually and given the fact we've had this S curve shift where the world calls a combination of cloud computing so on-demand IO and technical resources for processing data and then the on-demand ability to store and run algorithms at massive scale we haven't really combined our forces to predict more you know that the point you made about the the the waterborne pandemic in the eighteen eighteen hundreds we have an ability as humanity right now to actually see history play out rather than write a book about it you know it has a past tense and it's important to do are as follows number one luckily for you and I the cost of computing an algorithm to predict is manageable so I am surprised why the large cloud players haven't come out and said you know what anybody who wants to distribute anything around predictions lay to the pandemic should get cloud resources for free I we are running quote on all three cloud platforms and I'm paying for all of it right that doesn't really make sense but I'm surprised that they haven't really you know joined the debate or contribute to it and said in a way to say let's make compute free for anybody who would like to add a new dimension to our fight against the pandemic number one but the good news is it's available number two there is luckily for us an open data movement you know that was started on the Obama administration and hasn't stopped because you can't stop open movements allows people companies like ours to go leverage know whether it's John Hancock Carnegie Mellon or the new data coming out of you know California universities a lot of those people are opening up the data not every single piece is at the level we would like to see you know it's not zip plus 4 is mostly county level it's available the third innovation is what we have done with code but not it's not an innovation for the world right which is the give get model so we have said we will curate everything is available lie and boo cost anybody is used but they're for purposes and computations you want to enrich it every organization who gives code data will get more out of it so we have enabled a data exchange keep our far-off purple form and the open up the rail exchange that my clients use but you know we've opened up our data exchange part of our software platform and we have open source for this particular case a give get model but the more you give to it the more you get out of there and our first installations this was the first week that we have users of the platform you know the state of Nevada is using it there are no our state in North Carolina is using it already and we're trying to see the first asks for the gift get model to be used but that's the three ways you're trying to address the that's great and and and and so important you know in this again when this whole thing started I couldn't help but think of the Ford plant making airplanes and and Keiser making Liberty ships in in World War two but you know now this is a different battle but we have different tools and to your point luckily we have a lot of the things in place right and we have mobile phones and you know we can do zoom and well you know we can we can talk as we're talking now so I want to shift gears a little bit and just talk about digital transformation right we've been talking about this for ad nauseam and then and then suddenly right there's this light switch moment for people got to go home and work and people got to communicate via via online tools and you know kind of this talk and this slow movement of getting people to work from home kind of a little bit and digital transformation a little bit and data-driven decision making a little bit but now it's a light switch moment and you guys are involved in some really critical industries like healthcare like financial services when you kind of look at this not from a you know kind of business opportunity peer but really more of an opportunity for people to get over the hump and stop you can't push back anymore you have to jump in what are you kind of seeing in the marketplace Howard you know some of your customers dealing with this good bad and ugly there are two towers to start my response to you with using two of my favorite sayings that you know come to mind as we started the pandemic one is you know someone very smart said and I don't know who's been attributed to but a crisis is a terrible thing to waste so I do believe this move to restoring the world back to a natural state where there's not much fossil fuels being burnt and humans are not careful about their footprint but even if it's forced is letting us enjoy the earth in its glory which is interesting and I hope you don't waste an opportunity number one number two Warren Buffett came out and said that it's only when the tide goes out you realize who's swimming naked and this is a culmination of both those phenomenal phrases you know which is one this is the moment I do believe this is something that is deep both in the ability for us to realize the virtuosity of humanity as a society as social species as well as a reality check on what a business model looks like visa vie a presentation that you can put some fancy words on even what has been an 11-year boom cycle and blitzscale your way to disaster you know I have said publicly that this the peak of the cycle was when mr. Hoffman mr. Reid Hoffman wrote the book bit scaling so we should give him a lot of credit for calling the peak in the cycle so what we are seeing is a kind of coming together of those two of those two big trends crises is going to force industry as you've heard me say many for many years now do not just modernize what we have seen happen chef in the last few years or decades is modernization not transformation and they are different is the big difference as you know transformation is taking a business model pulling it apart understanding the economics that drive it and then not even reassembling it recreating how you can either recapture that value or recreate that value completely differently or by the way blow up the value create even more value that hasn't happened yet digital transformation you know data and analytics AI cloud have been modernizing trends for the last ten years not transformative trends in fact I've also gone and said publicly that today the very definition of technology transformation is run a sequel engine in the cloud and you get a big check off as a technology organization saying I'm good I've transformed how I look at data analytics I'm doing what I was doing on Prem in the cloud there's still sequel in the cloud you know there's a big a very successful company it has made a businessman out of it you don't need to talk about the company today but I think this becomes that moment where those business models truly truly get a chance to transform number one number two I think there's going to be less on the industry side on the new company side I think the the error of anointing winners by saying grow at all cost economics don't matter is fundamentally over I believe that the peak of that was the book let's called blitzscaling you know the markets always follow the peaks you know little later but you and I in our lifetimes will see the return to fundamentals fundamentals as you know never go out of fashion Jeff whether it's good conversations whether it's human values or its economic models if you do not have a par to being a profitable contributing member of society whether that is running a good balance sheet individually and not driven by debt or running a good balance sheet as a company you know we call it financial jurisprudence financial jurisprudence never goes out of fashion and the fact that even men we became the mythical animal which is not the point that we became a unicorn we were a profitable company three years ago and two years ago and four years ago and today and will end this year as a profitable company I think it's a very very nice moment for the world to realize that within the realm of digital transformation even the new companies that can leverage and push that trend forward can build profitable business models from it and if you don't it doesn't matter if you have a billion users as my economic professor told me selling a watermelon that you buy for a dollar or fifty cents even if you sell that a billion times you cannot make it up in volume I think those are two things that will fundamentally change the trend from modernization the transformation it is coming and this will be the moment when we look back and when you write a book about it that people say you know what now Jeff called it and now and the cry and the pandemic is what drove the economic jurisprudence as much as the social jurisprudence obvious on so many things here we can we're gonna be we're gonna go Joe Rogan we're gonna be here for four hours so hopefully hopefully you're in a comfortable chair but uh-huh but I don't I don't sit anymore I love standing on a DD the stand-up desk but I do the start of my version of your watermelon story was you know I dad a couple of you know kind of high-growth spend a lot of money raised a lot of money startups back in the day and I just know finally we were working so hard I'm Michael why don't we just go up to the street and sell dollars for 90 cents with a card table and a comfy chair maybe some iced tea and we'll drive revenue like there's nobody's business and lose less money than we're losing now not have to work so hard I mean it's so interesting I think you said everyone's kind of Punt you know kind of this pump the brakes moment as well growth at the ethic at the cost of everything else right there used to be a great concept called triple-line accounting right which is not just shareholder value to this to the sacrifice of everything else but also your customers and your employees and-and-and your community and being a good steward and a good participant in what's going on and I think that a lot of that got lost another you know to your point about pumping the brakes and the in the environment I mean we've been kind of entertaining on the oil side watching an unprecedented supply shock followed literally within days by an unprecedented demand shock but but the fact now that when everyone's not driving to work at 9:00 in the morning we actually have a lot more infrastructure than we thought and and you know kind of goes back to the old mob capacity planning issue but why are all these technology workers driving to work every morning at nine o'clock it means one thing if you're a service provider or you got to go work at a restaurant or you're you're carrying a truck full of tools but for people that just go sit on a laptop all day makes absolutely no sense and and I'd love your point that people are now you know seeing things a little bit slowed down you know that you can hear birds chirp you're not just stuck in traffic and into your point on the digital transformation right I mean there's been revolution and evolution and revolution people get killed and you know the fact that digital is not the same as physical but it's different had Ben Nelson on talking about the changes in education he had a great quote I've been using it for weeks now right that a car is not a is not a mechanical horse right it's really an opportunity to rethink the you know rethink the objective and design a new solution so it is a really historical moment I think it is it's real interesting that we're all going through it together as well right it's not like there quake in 89 or I was in Mount st. Helens and that blew up in in 1980 where you had kind of a population that was involved in the event now it's a global thing where were you in March 20 20 and we've all gone through this indeed together so hopefully it is a little bit of a more of a unifying factor in kind of the final thought since we're referencing great books and authors and quotes right as you've all know Harare and sapiens talked about what is culture right cultures is basically it's it's a narrative that we all have bought into it I find it so ironic that in the year 2020 that we always joke is 20/20 hindsight we quickly found out that everything we thought was suddenly wasn't and the fact that the global narrative changed literally within days you know really a lot of spearhead is right here in Santa Clara County with with dr. Sarah Cody shutting down groups of more than 150 people which is about four days before they went to the full shutdown it is a really interesting time but as you said you know if you're fortunate enough as we are to you know have a few bucks in the bank and have a business that can be digital which you can if you're in the sports business or the travel business the hotel business and restaurant business a lot of a lot of a lot of not not good stuff happening there but for those of us that can it is an opportunity to do this nice you know kind of a reset and use the powers that we've developed for recommendation engines for really a much more power but good for good and you're doing a lot more stuff too right with banking and in in healthcare telemedicine is one of my favorite things right we've been talking about telemedicine and electronic medicine for now well guess what now you have to cuz the hospitals are over are overflowing Jeff to your point three stories and you know then at some point I know you have you I will let you go you can let me go I can talk to you for four hours I can talk to you for but days my friend you know the three stories that there have been very relevant to me through this crisis I know one is first I think I guess in a way all are personal but the first one you know that I always like to remind people on there were business models built around allowing people to complain online and then using that as almost like a a stick to find a way to commercialize it and I look at that all of our friends I'm sure you have friends have lots of friend the restaurant is big and how much they are struggling right they are honest working the hardest thing to do in life as I've been told and I've witnessed through my friends is to run a restaurant the hours the effort you put into it making sure that what you produce this is not just edible but it's good quality is enjoyed by people is sanitary is the hard thing to do and there was yet there were all of these people you know who would not find in their heart and their minds for two seconds to go post a review if something wasn't right and be brutal in those reviews and if they were the same people were to look back now and think about how they assort the same souls then anything to be supportive for our restaurant workers you know it's easy to go and slam them online but this is our chance to let a part of the industry that we all depend on food right critical to humanity's success what have we done to support them as easy as it was for us to complain about them what have we done to support them and I truly hope and I believe they're coming out of it those business models don't work anymore and before we are ready to go on and online on our phones and complain about well it took time for the bread to come to my table we think twice how hard are they working right number one that's my first story I really hope you do tell me about that my second story is to your have you chained to baby with Mark my kids I'm sure as your kids get up every morning get dressed and launch you know their online version of a classroom do you think when they enter the workforce or when they go to college you and me are going to try and convince them to get in a oil burning combustion engine but by the way can't have current crash and breakdown and impact your health impact the environment and show up to work and they'll say what do you talk about are you talking about I can be effective I can learn virtually why can't I contribute virtually so I think there'll be a generation of the next class of you know contribute to society who are now raised to live in an environment where the choice of making sure we preserve the planet and yet contribute towards the growth of it is no longer a binary choice both can be done so I completely agree with you we have fundamentally changed how our kids when they grew up will go to work and contribute right my third story is the thing you said about how many industries are suffering we have clients you know in the we have health care customers we have banking customers you know we have whoever paying the bills like we are are doing everything they can to do right by society and then we have customers in the industry of travel hospitality and one of my most humbling moments Jeff there's one of the no sea level executives sent us an email early in this in this crisis and said this is a moment where a strong David can help AV Goliath and just reading that email had me very emotional because they're not very many moments that we get as corporations as businesses where we can be there for our customers when they ask us to be their father and if we as companies and help our customers our clients who area today are flying people are feeding people are taking care of their health and they're well if V in this moment and be there for them we we don't forget those moments you know those as humans have long-term memories right that was one of the kindest gentlest reminders to me that what was more important to me my co-founder Richard you know my leadership team every single person at Reseda that have tried very hard to build automations because as an automation company to automate complex human process so we can make humans do higher order activities in the moment when our customers asked us to contribute and be there for them I said yes they said yes you said yes and I hope I hope people don't forget that that unicorns aren't important there are mythical animals there's nothing all about profits there's nothing mythical about fortress balance sheet and there's nothing mythical about a strong business model that is built for sustainable growth not good at all cost and those are my three stories that you know bring me a lot of lot of calm in this tremendous moment of strife and and in the piece that wraps up all those is ultimately it's about relationships right people don't do business I mean companies don't do business with companies people do business with people and it's those relationships and and in strong relationships through the bad times which really set us up for when things start to come back I me as always it's I'm not gonna let it be three years to the next time I hear me pounding on your door great to catch up you know love to love to watch really your your culture building and your community engagement good luck I mean great success on the company but really that's one thing I think you really do a phenomenal job of just keeping this positive drumbeat you always have you always will and really appreciate you taking some time on a Friday to sit down with us well first of all thank you I wish I could tell you I just up to you but we celebrate formal Fridays that to Seder and that's what this is all so I want to end on a good on a positive bit of news I was gonna give you a demo of it but if you want to go to our website and look at what everything we're doing we have a survival kit around a data survival kit around kovat how am I using buzzwords you know a is let's not use that buzzword right now but in your in your lovely state but on my favorite places on the planet when we ran the algorithm on who is ready as per the government definition of opening up we have five counties that are ready to be open you know between Santa Clara to LA Sacramento Kern and San Francisco the metrics today the data today with our algorithm there are meta algorithm is saying that those five counties those five regions look like I've done a lot of positive activities if the country was to open under all the right circumstances those five look you know the first as we were men at on cream happy Earth Day a pleasure to see you so good to know your family is doing well and I hope we see we talk to each other soon thanks AVI great conversation with avi Mehta terrific guy thanks for watching everybody stay safe have a good weekend Jeff Rick checking out from the cube [Music]

(upbeat jazz music) >> From our studios, in the heart of Silicon Valley, Palo Alto, California. This is a CUBEConversation. >> Hello everyone, welcome to this special CUBEConversation. I'm John Furrier in theCUBE Studios in Palo Alto, California. We're excited to have a great tech talk here with good friend Howie Xu, who's currently the Vice President of Machine Learning and AI at Zscaler. Formally an entrepreneur, which he sold his company Zscaler. Before that entrepreneur resident Greylock. Before that VMWare, a variety of other endeavors. Howie and I, we've known each other for a while. Great to have you come in and chat about-- >> Great to be here! >> The Zoom, Zscaler, these are the new breed modern era companies, SaaS business models. Really interesting and this is something that we were talking about on email and over text, is our topic. >> Yeah. >> Thanks for coming in. >> Great. >> So you've seen the waves at VMWare, you saw the rapid growth there. And now, you work for Zscaler which is experiencing rapid growth. You saw Zoom go public, and I just interviewed Michael Dell. We were commenting about that on text as well. He said these big markets that have big total addressable dollars associated with them are ripe for disruption. They used to have high barriers to entry in the old ways to look at it, but now with cloud and with SaaS, with data, there's different innovation speeds. This has become a big deal. Talk about your view on this. >> Well to me, when Zoom and then Zscaler founded, many years ago, no one believed that they would become this big, right? When Zoom founded, they were plenty of the conference, free even, software available out there. When Jay founded Zscaler people thought, "Well, there was enough security companies, security solutions." Clearly, they defied conventional wisdom and then they just fought on and they saw something that other people didn't see which is precisely what you were talking about. The SaaS is so different, right? The business model, the innovation speed, the data driven kind of the thing, it's so different. A lot of people say, "Hey what's the difference "between SaaS versus the convention? "Isn't that just moving that thing over to the cloud?" I actually used to think that way too, right? Isn't that just the virtual price, moving on to Amazon Cloud? After living and breathing in SaaS company and then also observing that in the VC industry as well. It's just totally different, day and night different. >> Well I wanted to get into this with you 'cause I think you bring some good perspective onto these insights and to the rocket success of say Zoom and Zscaler, but Zoom in particular, recent successful IPO. Among the recent class this past quarter. Zoom, Lyft, Uber. Zoom is standing out. They're getting profitable. This is video conferencing. You know in the old days if someone said, "Hey, I want to compete with video conferences." Well, the barriers are actually too high, but they took a very innovative approach. Cloud, data, simplicity, and the big 800 pound gorilla was the WebEx's of the world. Who was defined, divine for sharing slides, not so much pure video. (laughing) >> Yeah. >> They really innovated the focus, the speed of success. Unprecedented, in my opinion. I think this is a huge success of what the opportunities are for entrepreneurs. >> Yeah, I think on the surface, right? If you ask Eric he would tell you that, look the WebEx was designed for sharing slides, and then the Zoom was designed from ground up for video sharing, or the video conferencing, so it's very different and it requires different architecture. So that's very true. But I think there is a more fundamental to that. The more fundamental for that is, there are a few things. One is the product, the life cycle is very different. How do you approach the customer? The release cycle, the sort of the feedback loop, right? Much tighter feedback loop, much faster feedback loop between the customer and you. The release cost is much lower now as a SaaS product. So, innovation is just accelerated because it's SaaS, because it's a true SaaS. >> And this is a unique thing, you said before, SaaS isn't just lifting a on-premises workload and moving it to the cloud. It's a completely different mindset. Talk about this dynamic, because it affords new kinds of risk taking. You and I were talking about before we came on camera, share your insight on that. >> Well, you know, as kind of the traditional software you have a release cycle, you want it to have a release date, right? And then once the product is in customer hand, if you have a bug, if you have something, it's so costly to change it, right? But as a SaaS, the form factor, you can take a little bit more risk. You can even give that feature set to 10% of your audience. Not the entire set of the audience. You can do those kind of magic, so you can accelerate the innovation and as a shrink-wrapped software the traditional way. You have one shot, if that software is not good, then you are toast. >> So you can move quicker. You can push code, you don't have the on-premise dynamics. >> Yeah, the innovation and then risk taking are kind of correlated, right? Relatively more risk, the more you are willing to take risk, relatively you can take more innovation. So, that's the thing. >> Well, you and I were talking, and one of the key things that you have been talking about publicly, and amongst friends, is innovation speed. Everyone wants the innovation fever. "I got to win to innovate, digital transformation, rah rah." Easier said then done. Innovation speed is critical with cloud and SaaS, why? What's the formula there for innovation speed? >> Well, one thing we discussed, the release cycle. For a, not necessarily for Zoom and Zscaler, but you know for SaaS in general, its possible for you to have daily, weekly, monthly release. Traditional software, there is no way you can do that but that's just the release cycles of that. The other thing is, you can actually take a risk. You can say, "Hey I want you to try to raise 1% of the customer and then see how they are going to react to this." But in the traditional way you have product manager debating for six months, six years on whether or how to do things. Here, let's not debate, let's just see. >> Let's ship it. >> Right, ship it. >> And Reid Hoffman always says, "If he's not embarrassed by your first shipment then you're not doing it properly." Which begs the question, I want to get your thoughts on this because, again with VMware, you saw how early that worked and their transforming cloud is now here unlike when they started the company. What is the right way to do it? And what's the wrong way to do it? When you look at an entrepreneur or a friend, who's trying to get a business off the ground, SaaS business, when you look at what they're doing, and you look at their mechanisms and how they're organizing their team, their code. What jumps out at you as the wrong way, and what's the right way? >> Well, the, I think the coach is really it, right? You know, the kind of the coach of incremental success and the fast iteration is the culture for a SaaS company, right? For the traditional one, you cannot afford to do that, because once you make a small mistake, you are toast. So I think, you know, that the culture difference, you really want it to have faster iteration basically. >> And that also comes down to the team, the people, right? >> Yes. >> The people selection. >> Yes, if you are kind of used to the waterfall thing, it's pretty hard to adapt to this kind of the SaaS world. >> And what's your advice to entrepreneurs? Reset, because if you say speed is of the essence, resetting is probably something that's not hard to do, then. >> Well, I wouldn't say easy, but not easy-- >> I hate to use the word pivot, but you know, resetting means okay, stop, rebuild. >> I think one way to think about it is actually looking at it and how to build enterprise software, like the consumer sort of product way, right? If you think of Facebook or Google, the traditional Google, of course Google now has enterprise product, but the traditional sort of, the Google, Facebook, kind of the product, it's more for consumers to consume. I mean they are fast iterations. How often? What's the criteria to release a product? Enterprise product is getting towards there. You need that kind of the thing, so, if you don't know how to do it look at a Facebook, how Facebook, of course Facebook and YouTube pulled the other way around, they need to care more about the privacy, care about more stability. So I think you are seeing the the two sides of the world, the enterprise side and the consumer side. They are learning from each other. >> Well, I want to get to the enterprise talk track in a second, because I think you can give a lot of insight, so I want to stay on SaaS cloud native or cloud specifically, 'cause that's where SaaS really shines when you're really talking about cloud scale. Data, you're doing AI now, and you and I have both talked about data many times. >> Yes. >> You know I'm a data hardcore person. I love data. I think software and data, I wrote a blog post in 2007, that says data is the new developer kit. The word "developer kit" was used back then. You're now seeing where data is part of the developer's piece of their value creation. Highly addressable, available, usable, not stored in some silo unaddressable, high latency to get it. How important is the data for the SaaS piece? Because that's where to make these kind of changes you're talking about, you need the data, data's giving you insights, that's something that's near and dear to your heart. Explain your vision of the role of data. >> Yeah, I think, you touched up on it. If you want to make sense out of something, you need the data, right? And if it's not SaaS, I would go, maybe a more extreme way, but it's not clear to me the data's even useful to you 'cause you know the data may be for some large software company, they may have hundreds of thousands of customers out there, but the data is spread around. I mean how are you going to train a model with all the data spread around hundreds of thousands of locations? So the real, the correct, or the optimal way, is actually the SaaS model, you actually have the data with you and then you kind of leverage the data. So I would say this is actually another benefit of the SaaS, why SaaS is going to change the world or eat the world. It owns the data for real, right? The data may be not the private data, but it's actually could be a behavior data. How people are reacting to your features. From VMware days we wanted to know, is people even using this feature? How often people use this feature? You know people are always debating, "Hey what's the maximum policy we need to give this and that?" But in the SaaS world, no debate just look at it. We always say, "Don't listen to what customers are wanting you to do." But watch how they do things, so that you can sort of understand, what product you want to develop, right? Here you actually can really watch how customers using your product. Don't listen to them, if you listen to them you will give them a faster horse as we all knew. >> But what's important about the data discussion, because, a security person would say, "Hey if you put into one spot, I can hack it." But, it's not just people's names, it's other data. It's gesture data, it's usage data, so you're not talking about sign in data, it's data. >> It could be the behavior, it could be second order data. Do people use my product, that's my data. That's something I wanted to know, I'm not necessarily talking about peeking into people's email, no. It's actually the thing surrounding it. >> It's looking for the good things in the data. All right, let's talk about the customer alignment and customer expectations, you know customer user experience is driven by customer's expectations usually, right? As expectations change. And I think the Zoom thing jumped out at me, the Zoom IPO and their great success and were a customer as well, is that they really nailed the expectation of the user and cloud certainly helped them get that speed, but this is a key thing, if you could just deliver a great experience. >> Yeah. >> For those customers, you can actually win big part of the market. >> Yeah, if you Google, Eric. Eric doesn't speak to me as much, but if you Google Eric. >> We'll get him on theCUBE. >> What's sort of the jump? Hopefully I can help you to bring him here too. But what's going to be obvious if you Google search Eric he is sort of the notion of customer successes, my success. If customer is happy, I'm going to happy. So, my happiness hinges on the customer's happiness. So that's, kind of very important because only the SaaS model made that more natural. In traditional model, whether traditional on prime or we're not, you sort of celebrate when you have customer signing your PO and then you don't hear from the sales guy or three years, the sales guy may move on to another company, you don't know, right? But for the SaaS, it doesn't stop when sign the PO. You actually have to earn customers' happiness every single day. >> Adoption's critical. >> Yeah, customer success is important and then that's kind of the, so there is a huge alignment, very interesting alignment between customer's happiness, customer success, customer adoption of your product and you're sort of, the success, right? 'Cause you know, when I came to Zscaler, one of our first meeting is about, okay, we had a lot of customer interest us. They sign a PO. How to get them ramp up the actual first use, right? So, that kind of conversation doesn't happen in the traditional software company. You sign a PO. If the customer doesn't use your product for another 18 month which is actually quite normal, no one is going to jump up and say, "This is crazy!" Right? >> You know, we're going to do that on our Part Two, about the impact of the enterprise. But you made up a good point there, I want to just close out our last talk point is, the data driving the experience isn't like the old way of throw in, get the PO and celebrate. You got to, kind of, keep that going. The enterprise is changing and the enterprise has a tsunami of onboarding of new types of developers. In some cases they grow. We just had Cisco inside here on theCUBE this morning. They're turning network guys into programmers from CL command line prompt dudes to gals to coders. You're seeing developers now enter the enterprise to build the apps so there's now a digital transformation initiative for enterprises to be, I guess, SaaS-like. But it's hard. >> Yeah, I think that's, you know, this is part of the digital transformation. Every company, Fortune 500 or Fortune 2000 company need to do it, right? So, another interesting part is, when they do this on this journey of digitalization, you cannot possibly build all the infrastructure yourself. You will have to consume public cloud, you know sometimes private and hybrid cloud, and you are actually going to consume lots of the SaaS, right? Whether Zoom, the Zscaler, or the PagerDuty, I mean you are not going to be all those thing from scratch but you want it to have a very good, sort of the stack on top of it and how you going to take advantage of the SaaS, is a very interesting aspect. >> Well in Part Two of our chat, when we come back on our next discussion, I want to get into the enterprise. But to wrap up Part One here, innovation speed, leveraging data and the beautiful risk taking and benefits of SaaS. Large scale, fast, high value, target and developing an app or a venture. >> Yeah. >> What is your advice to entrepreneurs out there and/or someone who's doing a digital transformation? Where they want to leverage Saas, what's the playbook, what's the starting point, what's your advice? >> Well, there are a number of things. One, there are so many SaaS companies out there taking advantage of them, right? In the old days you have to hire email admins, you have to do this. Nowadays, all the SaaS, that's your kind of, you only need to worry about the business logic, you have some unique insight in the business and then just have, hire programmers to codify that and then the rest will magically happen because of the public cloud, because of the SaaS. So, be very mindful about the new environment you are in, that's number one. The second thing I want to say is, how do you look at AI technology? The older way is program something in a definitive way. I think there will be a limit for that. It has taken the software industry a long way to where we are. But, if you look at the next 20 years, I think a lot of the lift is going to be done by the AI Center. But it's not going to be easy to be done, you have to think about your data strategy, where are you going to have the massive, sustainable, unique, ideally even labeled data. If you don't have the labeled data, you have to have the strategy. How are you going to have some unique model with the data you have? So, the data strategy, right? So, essentially, how to take advantage of the cloud? How to take advantage of the data? And then on top of that you are going to do something that's solving an unmet um-- >> Customer problem. >> Customer problem. >> An acute landing spot in the market place. >> Unmet need. >> In a big market. >> In a big, well, in a big market. >> There it is. >> Even if there is already a mature solution I bet, since those mature solutions would not develop from that native cloud era, and the native AI era. You have plenty of opportunities. >> Howie, you and I are on the same page on this, I have been saying it truly believe we are living in an entrepreneurial era where, with your advice and what you just laid out, the better mousetrap can take down a big market. >> And, I'm hopeful that you will also disrupt the media business, you know we're-- >> Don't tell anyone! (laughing) We're still going to do that top secret of Silent Running. Howie, we're going to get Part Two. We're going to dig Deep into the enterprise, because the enterprise now has an opportunity in the first historic time in tech history, to use tools and technologies to completely reset and re-architect for this kind of capability. >> Absolutely. >> So, we'll hit that in Part Two. >> I'm super passionate about it too. >> Howie Xu, here inside theCUBE. Friend of theCUBE, legend in the industry. Great entrepreneur and technologist here, sharing CUBEConversation. I'm John Furrier, thanks for watching. (upbeat jazz music)

(upbeat music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CUBEConversation. >> Hi everyone, welcome to the special CUBEConversation. We're in Palo Alto, California, at theCUBE studio. I'm John Furrier, co-host of the CUBE. We're here with Chris Yeh. He's the co-founder and general partner of Blitzscaling Ventures, author of the book Blitzscaling with Reid Hoffman, founder of LinkedIn and a variety of other ventures, also a partner at Greylock Partners. Chris, great to see you. I've known you for years. Love the book, love Reid. You guys did a great job. So congratulations. But the big news is you're now a TV star as one of the original inaugural contestants on the Mental Samurai, just premiered on Fox, was it >> On Fox. >> On Fox, nine o'clock, on which days? >> So Mental Samurai is on Fox, Tuesdays at 9 p.m. right after Master Chef Junior. >> Alright. So big thing. So successful shows. Take us through the journey. >> Yeah. >> It's a new show, so it's got this kind of like Jeopardy vibe where they got to answer tough questions in what looks like a roller coaster kind of arm that moves you around from station to station, kind of jar you up. But it's a lot of pressure, time clock and hard questions. Tell us about the format. How you got that. Gives all the story. >> So the story behind Mental Samurai is it's from the producers of American Ninja Warrior, if you've ever seen that show. So American Ninja Warrior is a physical obstacle course and these incredible athletes go through and the key is to get through the obstacle course. If you miss any of the obstacles, you're out. So they took that and they translated it to the mental world and they said, okay, we're going to have a mental obstacle course where you going to have different kinds of questions. So they have memory questions, sequence questions, knowledge questions, all these things that are tapping different elements of intelligence. And in order to win at the game, you have to get 12 questions right in five minutes or less. And you can't get a single question wrong. You have to be perfect. >> And they do try to jar you up, to kind of scrabble your brain with those devices, it makes it suspenseful. In watching last night at your watch party in Palo Alto, it's fun to watch because yeah, I'm like, okay, it's going to be cool. I'll support Chris. I'll go there, be great and on TV, and oh my, that's pretty interesting. It was actually riveting. Intense. >> Yeah. You have that element of moving around from station to station and it's dramatic. It's kind of a theater presence. But what's it like in there? Give us some insight. You're coming on in April 30th so you're yet to come on. >> Yes. >> But the early contestants, none of them made it to the 100,000. Only one person passed the first threshold. >> Right >> Take us through the format. How many thresholds are there? What's the format? >> Perfect, so basically when a competitor gets strapped into the chair, they call it Ava, it's like a robot, and basically they got it from some company in Germany and it has the ability to move 360 degrees. It's like an industrial robot or something. It makes you feel like you're an astronaut or in one those centrifugal force things. And the idea is they're adding to the pressure. They're making it more of a challenge. Instead of just Jeopardy where you're sitting there, and answering questions and bantering with Alex Trebek, you're working against the clock and you're being thrown around by this robot. So what happens is first you try to answer 12 questions correctly in less than five minutes. If you do that, then you make it through to the next round, what they call the circle of samurai and you win $10,000. The circle of samurai, what happens is there are four questions and you get 90 seconds plus whatever you have left over from your first run, to answer those four questions. Answer all four questions correctly, you win $100,000 and the official title of Mental Samurai. >> So there's only two levels, circle of samurai but it gets harder. Now also I noticed that it's, their questions have certain puzzles and there's certain kinds of questions. What's the categories, if you will, what's the categories they offer? >> Yes, so the different categories are knowledge, which is just classic trivia, it's a kind of Jeopardy stuff. There's memory, where they have something on screen that you have to memorize, or maybe they play an audio track that you have to remember what happened. And then there's also sequence where you have to put things in order. So all these different things are represented by these different towers which are these gigantic television screens where they present the questions. And the idea is in order to be truly intelligent, you have to be able to handle all of these different things. You can't just have knowledge. You can't just have pop culture. You got to have everything. >> So on the candidates I saw some from Stanford. >> Yeah. >> I saw an athlete. It's a lot of diversity in candidates. How do they pick the candidates? How did you get involved? Did your phone ring up one day? Were you identified, they've read your blog. Obviously they've, you're smart. I've read your stuff on Facebook. How did you get in there? (laughs) >> Excellent question. So the whole process, there's a giant casting department that does all these things. And there's people who just cast people for game shows. And what happened with me is many years ago back in 2014, my sister worked in Hollywood when I was growing up. She worked for ER and Baywatch and other companies and she still keeps track of the entertainment industry. And she sent me an email saying, hey, here's a casting call for a new show for smart people and you should sign up. And so I replied to the email and said hey I'm Chris Yeh. I'm this author. I graduate from Stanford when I was 19, blah blah blah blah. I should be on your show. And they did a bunch of auditions with me over the phone. And they said we love you, the network loves you. We'll get in touch and then I never heard. Turns out that show never got the green light. And they never even shot that show. But that put me on a list with these various casting directors. And for this show it turns out that there was an executive producer of the show, the creator of the show, his niece was the casting director who interviewed me back in 2014. And she told her uncle, hey, there's this guy, Chris Yeh, in Palo Alto. I think would be great for this new show you're doing. Why don't you reach out to him. So they reached out to me. I did a bunch of Skype auditions. And eventually while I was on my book tour for Blitzscaling, I got the email saying, congratulations, you're part of the season one cast. >> And on the Skype interviews, was it they grilling you with questions, or was it doing a mock dry run? What was some of interview vetting questions? >> So they start off by just asking you about yourself and having you talk about who you are because the secret to these shows is none of the competitors are famous in advance, or at least very few of them are. There was a guy who was a major league baseball pitcher, there's a guy who's an astronaut, I mean, those guys are kind of famous already, but the whole point is, they want to build a story around the person like they do with the Olympics so that people care whether they succeed or not. And so they start off with biographical questions and then they proceed to basically use flash cards to simulate the game and see how well you do. >> Got it, so they want to basically get the whole story arc 'cause Chris, obviously Chris is smart, he passed the test. Graduate when he's 19. Okay, you're book smart. Can you handle the pressure? If you do get it, there's your story line. So they kind of look from the classic, kind of marketing segmentation, demographics is your storylines. What are some of the things that they said to you on the feedback? Was there any feedback, like you're perfect, we like this about you. Or is it more just cut and dry. >> Well I think they said, we love your energy. It's coming through very strongly to the screen. That's fantastic. We like your story. Probably the part I struggle the most with, was they said hey, you know, talk to us about adversity. Talk to us about the challenges that you've overcome. And I tell people, listen, I'm a very lucky guy. A lot of great things have happened to me in life. I don't know if there's that much adversity that I can really complain about. Other people who deal with these life threatening illnesses and all this stuff, I don't have that. And so that was probably the part I struggled the most with. >> Well you're certainly impressive. I've known you for years. You're a great investor, a great person. And a great part of Silicon Valley. So congratulations, good luck on the show. So it's Tuesdays. >> 9 p.m. >> 9 p.m. >> On fox. >> On Fox. Mental Samurai. Congratulations, great. Great to be at the launch party last night. The watch party, there'll be another one. Now your episode comes out on April 30th. >> Yes. So on April 30th we will have a big Bay area-wide watch party. I'm assuming that admission will be free, assuming I find the right sponsors. And so I'll come back to you. I'll let you know where it's going to be. Maybe we should even film the party. >> That's, well, I got one more question on the show. >> Yeah. >> You have not been yet on air so but you know the result. What was it like sitting in the chair, I mean, what was it personally like for you? I mean you've taken tests, you've been involved with the situation. You've made some investments. There's probably been some tough term sheets here and there, board meetings. And all that experience in your life, what was it compared to, what was it like? >> Well, it's a really huge adrenaline rush because if you think about there's so many different elements that already make it an adrenaline rush and they all combine together. First of all, you're in this giant studio which looks like something out of a space-age set with this giant robotic arm. There's hundreds of people around cheering. Then you're strapped into a robotic arm which basically makes you feel like an astronaut, like every run starts with you facing straight up, right? Lying back as if you're about to be launched on a rocket. And then you're answering these difficult questions with time pressure and then there's Rob Lowe there as well that you're having a conversation with. So all these things together, and your heart, at least for me, my heart was pounding. I was like trying very hard to stay calm because I knew it was important to stay clam, to be able to get through it. >> Get that recall, alright. Chris, great stuff. Okay, Blitzscaling. Blitzscaling Ventures. Very successful concept. I remember when you guys first started doing this at Stanford, you and Reid, were doing the lectures at Stanford Business School. And I'm like, I love this. It's on YouTube, kind of an open project initially, wasn't really, wasn't really meant to be a book. It was more of gift, paying it forward. Now it's a book. A lot of great praise. Some criticism from some folks but in general it's about scaling ventures, kind of the Silicon Valley way which is the rocket ship I call. The rocket ship ventures. There's still the other venture capitals. But great book. Feedback from the book and the original days at Stanford. Talk about the Blitzscaling journey. >> And one of the things that happened when we did the class at Stanford is we had all these amazing guests come in and speak. So people like Eric Schmidt. People like Diane Greene. People like Brian Chesky, who talked about their experiences. And all of those conversations really formed a key part of the raw material that went into the book. We began to see patterns emerge. Some pretty fascinating patterns. Things like, for example, a lot of companies, the ones that'd done the best job of maintaining their culture, have their founders involved in hiring for the first 500 employees. That was like a magic number that came up over and over again in the interviews. So all this content basically came forward and we said, okay, well how do we now take this and put it into a systematic framework. So the idea of the book was to compress down 40 hours of video content, incredible conversations, and put it in a framework that somebody could read in a couple of hours. >> It is also one of those things where you get lightning in a ball, the classic and so then I'd say go big or go home. But Blitzscaling is all about something new and something different. And I'm reading a book right now called Loonshots, which is a goof on moonshots. It's about the loonies who start the real companies and a lot of companies that are successful like Airbnb was passed over on and they call those loonies. Those aren't moonshots. Moonshots are well known, build-outs. This is where the blitzscaling kind of magic happens. Can you just share your thoughts on that because that's something that's not always talked about in the mainstream press, is that a lot of there blitzscaling companies, are the ones that don't look good on paper initially. >> Yes. >> Or ones that no one's talking about is not in a category or herd mentality of investors. It's really that outlier. >> Yes. >> Talk about that dynamic. >> Yeah, and one of the things that Reid likes to say is that the best possible companies usually sound like they're dumb ideas. And in fact the best investment he's been a part of as a venture capitalist, those are the ones where there's the greatest controversy around the table. It's not the companies that come in and everyone's like this is a no-brainer, let's do it. It's the companies where there's a big fight. Should we do this, should we not? And we think the reason is this. Blitzscaling is all about being able to be the first to scale and the winner take most or the winner take all market. Now if you're in a market where everyone's like, this is a great market, this is a great idea. You're going to have huge competition. You're going to have a lot of people going after it. It's very difficult to be the first to scale. If you are contrarian and right you believe something that other people don't believe, you have the space to build that early lead, that you can then use to leverage yourself into that enduring market leadership. >> And one of the things that I observed from the videos as well is that the other fact that kind of plays into, I want to get your reaction, this is that there has to be a market shift that goes on too because you have to have a tailwind or a wave to ride because if you can be contrarian if there's no wave, >> Right. >> right? so a lot of these companies that you guys highlight, have the wave behind them. It was mobile computing, SaaSification, cloud computing, all kind of coming together. Talk about that dynamic and your reaction 'cause that's something where people can get confused on blitzscaling. They read the book. Oh I'm going to disrupt the dry cleaning business. Well I mean, not really. I mean, unless there's something different >> Exactly. >> in market conditions. Talk about that. >> Yeah, so with blitzscaling you're really talking about a new market or a market that's transforming. So what is it that causes these things to transform? Almost always it's some new form of technological innovation, or perhaps a packaging of different technological innovations. Take mobile computing for example. Many of the components have been around for a while. But it took off when Apple was able to combine together capacitative touchscreens and the form factor and the processor strength being high enough finally. And all these things together created the technological innovation. The technological innovation then enables the business model innovation of building an app store and creating a whole new way of thinking about handheld computing. And then based on that business model innovation, you have the strategy innovation of blitzscaling to allow you to grow rapidly and keep from blowing up when you grow. >> And the spirit of kind of having, kind of a clean entrepreneurial segmentation here. Blitzscaling isn't for everybody. And I want you to talk about that because obviously the book's popular when this controversy, there's some controversy around the fact that you just can't apply blitzscaling to everything. We just talk about some of those factors. There are other entrepreneurialship models that makes sense but that might not be a fit for blitzscaling. Can you just unpack that and just explain, a minute to explain the difference between a company that's good for blitzscaling and one that isn't. >> Well, a key thing that you need for blitzscaling is one of these winner take most or winner take all markets that's just enormous and hugely valuable, alright? The whole thing about blitzscaling is it's very risky. It takes a lot of effort. It's very uncomfortable. So it's only worth doing when you have those market dynamics and when that market is really large. And so in the book we talk about there being many businesses that this doesn't apply to. And we use the example of two companies that were started at the same time. One company is Amazon, which is obviously a blitzscaling company and a dominant player and a great, great company. And the other is the French Laundry. In fact, Jeff Bezos started Amazon the same year that Thomas Keller started the French Laundry. And the French Laundry still serves just 60 people a day. But it's a great business. It's just a very different kind of business. >> It's a lifestyle or cash flow business and people call it a lifestyle business but mainly it's a cash flow or not a huge growing market. >> Yeah. >> Satisfies that need. What's the big learnings that you learned that was something different that you didn't know coming out of blitzscaling experience? Something that surprised you, something that might have shocked you, something that might have moved you. I mean you're well-read. You're smart. What was some learnings that you learned from the journey? >> Well, one of the things that was really interesting to me and I didn't really think about it. Reid and I come from the startup world, not the big company world. One of the things that surprised me is the receptivity of big companies to these ideas. And they explained it to me and they said, listen, you got to understand with a big company, you think it's just a big company growing at 10, 15% a year. But actually there's units that are growing at 100% a year. There's units that are declining at 50% a year. And figuring out how you can actually continue to grow new businesses quicker than your old businesses die is a huge thing for the big, established companies. So that was one of the things that really surprised me but I'm grateful that it appears that it's applicable. >> It's interesting. I had a lot of conversations with Michael Dell before, and before they went private and after they went private. He essentially was blitzscaling. >> Yeah. >> He said, I'm going to winner take most in the mature, somewhat declining massive IT enterprise spend against the HPs of the world, and he's doing it and VMware stock went to an all time high. So big companies can blitz scale. That's the learning. >> Exactly. And the key thing to remember there is one of the reasons why somebody like Michael Dell went private to do this is that blitzscaling is all about prioritizing speed over efficiency. Guess who doesn't like that? Wall street doesn't like because you're taking a hit to earnings as you invest in a new business. GM for example is investing heavily in autonomous vehicles and that investment is not yet delivering cash but it's something that's going to create a huge value for General Motors. And so it's really tough to do blitzscaling as a publicly traded company though there are examples. >> I know your partner in the book, Reid Hoffman as well as in the blitzscaling at Stanford was as visible in both LinkedIn and as the venture capitalist of Greylock. But also he was involved with some failed startups on the front end of LinkedIn. >> Yeah. >> So he had some scar tissue on social networking before it became big, I'll say on the knowledge graph that he's building, he built at LinkedIn. I'm sure he had some blitzscaling lessons. What did he bring to the table? Did he share anything in the classes or privately with you that you can share that might be helpful for people to know? >> Well, there's a huge number of lessons. Obviously we drew heavily on Reid's life for the book. But I think you touched on something that a lot of people don't know, which is that LinkedIn is not the first social network that Reid created. Actually during the dot-com boom Reid created a company called SocialNet that was one of the world's first social networks. And I actually was one of the few people in the world who signed up and was a member of SocialNet. I think I had the handle, net revolutionary on that if you can believe that. And one of the things that Reid learned from his SocialNet experience turned into one of his famous sayings, which is, if you're not embarrassed by your first product launch, you've launched too late. With SocialNet they spent so much time refining the product and trying to get it perfectly right. And then when they launched it, they discovered what everyone always discovers when they launch, which is the market wants something totally different. We had no idea what people really wanted. And they'd wasted all this time trying to perfect something that they've theoretically thought was what the market wanted but wasn't actually what the market wanted. >> This is what I love about Silicon Valley. You have these kind of stories 'cause that's essentially agile before agile came out. They're kind of rearranging the deck chairs trying to get the perfect crafted product in a world that was moving to more agility, less craftsmanship and although now it's coming back. Also I talked to Paul Martino, been on theCUBE before. He's a tribe with Pincus. And it's been those founding fathers around these industries. It's interesting how these waves, they start off, they don't get off the ground, but that doesn't mean the category's dead. It's just a timing issue. That's important in a lot of ventures, the timing piece. Talk about that dynamic. >> Absolutely. When it comes to timing, you think about blitzscaling. If you start blitzscaling, you prioritize speed over efficiency. The main question is, is it the right time. So Webvan could be taken as an example of blitzscaling. They were spending money wildly inefficiently to build up grocery delivery. Guess what? 2000 was not the right time for it. Now we come around, we see Instacart succeeding. We see other delivery services delivering some value. It just turns out that you have to get the timing right. >> And market conditions are critical and that's why blitzscaling can work when the conditions are right. Our days back in the podcast, it was, we were right but timing was off. And this brings up the question of the team. >> Yeah. >> You got to have the right team that can handle the blitzscaling culture. And you need the right investors. You've been on both sides of the table. Talk about that dynamic because I think this is probably one of the most important features because saying you going to do blitzscaling and then getting buy off but not true commitment from the investors because the whole idea is to plow money into the system. You mentioned Amazon, one of Jeff Bezos' tricks was, he always poured money back into his business. So this is a capital strategy, as well financial strategy capital-wise as well as a business trait. Talk about the importance of having that stomach and the culture of blitzscaling. >> Absolutely. And I think you hit on something very important when you sort of talk about the importance of the investors. So Reid likes to refer to investors as financing partners. Or financing co-founders, because really they're coming on with you and committing to the same journey that you're going on. And one of the things I often tell entrepreneurs is you really have to dig deep and make sure you do more due diligence on your investors than you would on your employees. Because if you think about it, if you hire an employee, you can actually fire them. If you take money from an investor, there's no way you can ever get rid of them. So my advice to entrepreneurs is always, well, figure out if they're going to be a good partner for you. And the best way to do that is to go find some of the entrepreneurs they backed who failed and talked to those people. >> 'Cause that's where the truth will come out. >> Well, that's right. >> We stood by them in tough times. >> Exactly. >> I think that's classic, that's perfect but this notion of having the strategies of the elements of the business model in concert, the financial strategy, the capital strategy with the business strategy and the people strategy, all got to be pumping that can't be really any conflict on that. That's the key point. >> That's right, there has to be alignment because again, you're trying to go as quickly as possible and if you're running a race car and you have things that are loose and rattling around, you're not going to make it across the finish line. >> You're pulling for a pit stop and the guys aren't ready to change the tires, (snapping fingers) you know you're out of sync. >> Bingo. >> Chris, great stuff. Blitzscaling is a great book. Check it out. I recommend it, remember blitz scale is not for anyone, it's for the game changers. And again, picking your investors is critical on this. So if you picked the wrong investors, blitzscaling will blow up in a bad way. So don't, don't, pick properly on the visa and pick your team. Chris, so let's talk about you real quick to end the segment and the last talk track. Talk about your background 'cause I think you have a fascinating background. I didn't know that you graduated when you're 19, from Stanford was it? >> Yes. >> Stanford at 19, that's a great accomplishment. You've been an entrepreneur. Take us through your journey. Give us a quick highlight of your career. >> So the quick highlight is I grew up in Southern California and Santa Monica where I graduated from Santa Monica High School along with other luminaries such as Rob Lowe, Robert Downey, Jr., and Sean Penn. I didn't go at the same time that they did. >> They didn't graduate when they were 17. >> They did not, (John laughing) and Charlie Sheen also attended Santa Monica High School but dropped out or was expelled. (laughing) Go figured. >> Okay. >> I came up to Stanford and I actually studied creative writing and product design. So I was really hitting both sides of the brain. You could see that really coming through in the rest of my career. And then at the time I graduated which was the mid-1990s that was when the internet was first opening up. I was convinced the internet was going to be huge and so I just went straight into the internet in 1995. And have been in the startup world ever since. >> Must love that show, Halt and Catch Fire a series which I love reminiscing. >> AMC great show. >> Just watching that my life right before my eyes. Us old folks. Talk about your investment. You are at Wasabi Ventures now. Blitzscaling Ventures. You guys looks like you're going to do a little combination bring capital around blitzscaling, advising. What's Blitzscaling Ventures? Give a quick commercial. >> So the best way to think about it is for the entrepreneurs who are actually are blitzscaling, the question is how are you going to get the help you need to figure out how to steer around the corners to avoid the pitfalls that can occur as you're growing rapidly. And Blitzscaling Ventures is all about that. So obviously I bring a wealth of experience, both my own experience as well as everything I learned from putting this book together. And the whole goal of Blitzscaling Ventures is to find those entrepreneurs who have those blitzscalable opportunities and help them navigate through the process. >> And of course being a Mental Samurai that you are, the clock is really important on blitzscaling. >> There are actually are a lot of similarities between the startup world and Mental Samurai. Being able to perform under pressure, being able to move as quickly as possible yet still be accurate. The one difference of course is in our startup world you often do make mistakes. And you have a chance to recover from them. But in Mental Samurai you have to be perfect. >> Speed, alignment, resource management, capital deployment, management team, investors, all critical factors in blitzscaling. Kind of like entrepreneurial going to next level. A whole nother lesson, whole nother battlefields. Really the capital markets are flush with cash. Post round B so if you can certainly get altitude there's a ton of capital. >> Yeah. And the key is that capital is necessary for blitzscaling but it's not sufficient. You have to take that financial capital and you have to figure out how to combine it with the human capital to actually transform the business in the industry. >> Of course I know you've got to catch a plane. Thanks for coming by in the studio. Congratulations on the Mental Samurai. Great show. I'm looking forward to April 30th. Tuesdays at 9 o'clock, the Mental Samurai. Chris will be an inaugural contestant. We'll see how he does. He's tight-lipped, he's not breaking his disclosure. >> I've got legal requirements. I can't say anything. >> Just say he's sticking to his words. He's a man of his words. Chris, great to see you. Venture capitalist, entrepreneur, kind of venture you want to talk to Chris Yeh, co-founder, general partner of blitzscaling. I'm John Furrier for theCUBE. Thanks for watching. (upbeat music)

(upbeat music) >> Welcome to this special Cube Conversation. We're here in Palo Alto, California with a special guest. Dialing in remotely Paul Martino, the founder of Bullpen Capital and also the producer of an upcoming film called The Inside Game. It's a story about a true story about an NBA betting scandal. It's really, it's got everything you want to know. It's got sports, it's got gambling, it's got fixing of games. Paul Martino, known for being a serial entrepreneur and then an investor, investing in some great growth companies, and now running his own firm called Bullpen Capital, which bets on high-growth companies and takes them to the next level. Paul, great to see you. Thanks for spending the time. Good to see you again. >> John, always good to see you. Thanks for having me on the show. >> So, you're a unique individual. You're a computer science whiz, investor, entrepreneur, now film producer. This story kind of crosses over your interests. Obviously in Philly, you're kind of like me, kind of a blue collar kind of guy. You know hot starters when you see it. You also were an investor in a lot of the sports, gambling, betting, kind of online games, we've talked about in the past. But now you're crossing over into filming movies. Which is, seems like very cool and obviously we're living in a date of digital media where code is software, code is content, obviously we believe that. What's this movie all about? All the buzz is out there, Inside Game. You get it on sports radio all the time. Give us the scoop. Why Inside Game? What's it about? Give us the 411. >> Yeah, so John, I mean, this is a story that picked me. My producing partner in this is a guy named Michael Pierce who made a bunch of great movies, including The Cooler, one of the best gambling movies, with William H Macy. And he says sometimes the movie picks you and sometimes you pick the movie. And I wasn't sitting around one day going wow I want to be a movie producer, it was just much more that my cousin is the principal in the story. My cousin was the go-between between the gambler and the referee. The three of them were friends ever since they were kids. And when they all got out of jail Tommy called me, Tommy Martino. He said hey Paulie, you're about the only legitimate business guy I know. Could you help me with my life rights? And that's how this started almost six years ago. >> And what progressed next? You sat down, had a couple cocktails, beers, said okay here's how we're going to structure it. Was it more brainstorming and then it kind of went from there? Take us through that progression. >> It was a pure intellectual property exercise, and this is where being a startup guy was helpful. I was like, Tommy, I'll buy your life rights. Maybe we'll get a script written, we'll put it on the shelf, so that if anybody ever wants to make this story they have to go through us. Almost like a blocking patent or a copyright. And he's like okay cool. And so I said I have no delusions of ever making this movie. I actually don't know that, I don't know anybody to make a movie. This is not my skill set. But if anybody ever wants to make the movie, they're going to have to come deal with us. And then the lucky break happens, like anything in a startup. I have this random meeting with a guy named Michael Pierce, who was at a firm called WPS Challenger out of London. And we're down in Hillstone in Santa Monica, and I say to him, I say I've got this script written about this NBA betting scandal, would you do me a favor? He literally laughs in my face. He goes a venture guy from Silicon Valley is going to hand me a script. What a bad, anyway, I was like look dude, I'm a good guy to have owe you a favor so just read this dang thing. About 8 hours later my phone rings, he says who the hell is Andy Callahan? This is the best script I've ever read in my entire life. Let's go make a movie. Andy Callahan was a friend of a friend from high school who wrote the script. He actually once beat Kobe Bryant when he was a center at Haverford when Kobe Bryant played at Lower Merion here in the Philly suburbs. So, it's kind of this local Philly story. I'm a local Philly blue collar guy, we put the pieces together, and I'll be danged and now six years later the film is in the can and you're probably going to see it during the NBA finals this year in June. >> All right, so there's some news out there it's on the cover on ESPN Magazine, the site is now launched. I've been hearing buzz all morning on this in the sports radio world. A lot of buzz, a lot of organic virality around it. Reminds of the Crazy, Rich Asians, which kind of started organically, similar kind of community behind it. This has really got some legs to it. Give us some taste of what's some of the latest organic growth here around the buzz. >> Yeah so, think about this. This happened in, primarily '06 and '07. They were sentenced in 2010 and were in jail in 2011. It is 2019 and the front page story on ESPN is What Tim, Tommy, and Jimmy Battista Did. Those were the three guys, the gambler, the ref, and the go-between. And this is a front page story on ESPN all these years later. So we know this story has tremendous legs. We know this movie has a tremendous built-in audience. And so now it's just our job to leverage all those marketing channels, places we pioneered, like Zynga and FanDuel to get people who care about the story into the theaters. And we're hoping we can really show people how to do a modern way to market a film using those channels we've pioneered at places like FanDuel and Zynga. >> You and I have had many conversations privately and here on the Cube in the past around startups disruption, and it's the same pattern right? No one thinks it's a great idea, you get the rights to it, and you kind of got to find that inflection point, that magical moment which comes through networking and just hard work and hustle. And then you've got everything comes together. And then it comes together. And then it grows. As the world changes, you're seeing digital completely change the game on Hollywood. For instance, Netflix, you've got Prime, you've got Hulu. This is, essentially, a democratization, I'm not saying, well first of all you've made some money so you had some dough to put into it, but here's a script from a friend. You guys put it together. This is now the new startup model going to Hollywood. Talk about that dynamic, what's your vision there? Because this, I think, is an important signal in how digital content, whether it's guys in the Cube doing stuff or Cube Studios, which we'll, we have a vision for. This is something that's real. Talk about the dynamic. How do you see the entrepeneurial vision around how movies are made, how content's made, and then, ultimately, how they're merchandised in the future. >> Right, there's a whole, there's a whole bunch of buckets. There's the intellectual property bucket of the story, the script, etc. Then there's the bucket of getting the movie made. You know, that's the on the set and that's the director and that's post-production, and then there's the marketing. And what was really interesting is even though I'd never made a movie, two of those three buckets I knew a tremendous amount about from my experience as a startup investor. The marketing and the IP side I understood almost completely, even though I'd never made a film. And so all of the disruptive technologies that we learn for doing disruptive things like marketing a new thing called Daily Fantasy Sports, we were able to bring to bear to this film. Now, I had fun on the set and meeting all the actors, etc. But I had no delusion that I knew about the making of the movie part. So I plead ignorance there, but of the three buckets that you need to go make something in the media space 66% of what I knew as a startup guy overlapped and I think this is what the future of the media is. Because guys like me and you, John, we actually know a lot about this because we're startup people as opposed to we have to learn about it in terms of how to market and how to get an audience. I mean, my last company Aggregate Knowledge designs custom audiences for ad targeting. So we know how to find gamblers to go see this movie. That's literally the company I started. And so that's a thing that I'm very, very comfortable with and it's exciting to then work with the producer who did the creative and the director and I say hey guys, I've got this marketing thing under control, I know how to do it, oh by the way, the old Head of Marketing from FanDuel, he's a consultant to the project. Right, so, we got that. >> You got that, and the movie's being made. That's also again, back to entrepreneurship, risk. You got to take risks, right? This is all about risk management at the end of the day and you know, navigating as the lead entrepreneur, getting it done, there's heavy lifting and costs involved in making the movie, >> Right >> How did you, that's like production, right? You got to build a product. That is ultimately the product when it has to get to market. How did that go, what's your thoughts on your first time running a movie like this, from a production standpoint, learnings, observations? >> I learned a tremendous amount. I must admit, I was along for the ride on that piece of the puddle, puzzle. The product development piece of this was all new to me. But then again, I mean think about it, John, I started four companies, a social network, an ad targeting company, a game company, and a security company. I didn't know anything about those four companies when I started them either in terms of what the product needed to do. So learning a new product called make a movie was kind of par for the course, even though I didn't really know anything about it. You know, if you're going to be a startup person you got to have no fear. That's the real attribute you need to have in these kinds of situations. >> So I got to >> And so, witnessed that first-hand and, you know what, now, if I ever make a movie again I kind of know how to make that product. >> Yeah, well looking forward. You've got great instincts as an entrepreneur. I love hanging out with you. I got to ask you a question. I talk to a lot of young people, my son and his friends and I see people coming out of business school, all this stuff. You know, every college has an entrepreneurial program. Music, film, you know, whatever, they all have kind of bolted on entrepreneurship. You're essentially breaking down that kind of dogma of that you have to have a discipline. Anyone can do this, right? So talk about the folks that are out there, trying to be entrepreneurial, whether you're a musician. This is direct to consumer. If you have skills as an entrepreneur it translates. Talk about what it takes to be an entrepreneur, if you're a musician or someone who has, say, content rights or has content story. What do they do? What's your advice? >> We have lived through, perhaps the most awesome period of the last five to 10 years, where it got cheap to do a startup. You know, when we're doing our first startups 20 years ago, it cost 5 million bucks to go get a license from Oracle and go hire a DBA and do all that stuff. You know what, for 5 grand you can get your website up, you can build, you can use your iPhone, you can film your movie. That's all happened in the last five to 10 years. And what it's done is exactly the word you used. It's democratized who can become an entrepreneur. Now people who never thought entrepreneurship was for them, are able to do it. One of our great examples of this is Ipsy, our cosmetics company. You know, Michelle Phan was a cocktail waitress working in Florida, but she had this YouTube following around watching her videos of her putting her makeup on. And you know when we met her, we're like you know what? You're the next generation of what entrepreneurs look like. Because no, she didn't go to Stanford. She didn't have a PhD in computer science, but she knew what this next generation of content marketing was going to look like. She knew what it was to be a celebrity influencer. You know, that company Ipsy makes hundreds of millions of dollars every year now, and I don't think most people on Sand Hill would've necessarily given Michelle the chance because she didn't look like what the traditional entrepreneur looked like. So it's so cool we live in a time where you don't need to look like what you think an entrepreneur needs to look like or went to the school you had to think you'd go to to become an entrepreneur. It's open to everybody now. >> And the key to success, you know, again, we've talked about those privately all the time when we meet, but I want to get your comment on the record here. But I mean, there's some basic blocking and tackling that's independent of where you went to school that's being creative, networking, networking, networking, you know, and being, good hustle. And being, obviously good judgment and being smart. Do your thoughts on the keys to success for as those folks saying hey you know I didn't have to go to these big, fancy schools. I want to go out there. I want to test my idea. I want to go push the envelope. I want to go for it. What's the tried and true formula from your perspective? >> So when you're in the early stage of hustling and you want to figure out if you're good at being an entrepreneur, I tell entrepreneurs this all the time. Every meeting is a job interview. Now, you might not think it's a job interview, but you want to think about every meeting, this might be the next person I start my company with. This might be the person I end up hiring to go run something at my company. This might be the person I end up getting money for, from to start my company. And so show up, have some skills, have some passion, have a vision, and impress the person on the other side of the table. Every once in a while I get invited to a college and they're like well Paul, life's easy for you, you started a company with Mark Pinkus and you're friend with Reid Hoffman and this... Well how the hell do you think I met those people? I did the same thing I'm telling you to do. When I was nobody coming out of school, I went and did stuff for these guys. I helped them with a business plan. I wrote the code of Tribe, and then now all of the sudden we've got a whole network of people you can go to. Well, that didn't happen by accident. You had to show up and have some skills, talent, and passion and then impress the person on the other side of the table. >> Yeah >> And guess what? If you do that enough times in a row, you're going to end up having your own network. And then you're going to have kids come in and say, wow, how can I impress you? >> Be authentic, be genuine, hustle, do networking, do the job interview, great stuff. All right, back to final point I want to get your thoughts on because I think this is your success and getting this movie out of the gate. Everyone, first, everyone should go see Inside Game. Insidegamemovie.com is the URL. The site just went up. This should be a great movie. I'm looking forward to it, and knowing the work that went in, I followed your journey on this. It should be great. I'm looking forward to seeing it. Uh, digital media, um, your thoughts because we're seeing a direct to consumer model. You've got the big companies, YouTube, Amazon, others. There's kind of a, a huge distribution of those guys. The classic Web 2.0 search kind of paradigm and portal. But now you've got a whole 'nother set of distribution or network effects. Your thoughts, because you were involved in, again, social networking before it became the monster that it is now. How is digital media changing? What's your vision of how that's happening and how does someone jump on that wave and be successful? >> Yeah, we're in the midst of disruption. I mean, I'm in the discussions and final negotiations right now on how we're going to end up ultimately doing the film distribution. And I am very disappointed with the quality of the thinking of the people on the other side of the table. Because they come from very traditional backgrounds. And I'm talking to them about, I want to do a site takeover across Zynga. I want to do a digital download on FanDuel of a 20 minute clip of the film. And they're like what's FanDuel? Who's Zynga? And I'm sitting there, I'm like guys, this is the new media. Oh, by the way, there's a sports app called Wave and Wave is where the local influencers in the markets who want to write the stories are, and we want to do a deal with those guys. And oh, by the way, the CEO of that company is a buddy of mine I met years ago, right? One of those kids I gave advice to, and now I'm going to ask him for a favor from, right, that's how it works. But, it's amazing when you have these conversations with traditional old line media companies. They don't understand any of the words coming out of your mouth. They're like Paul, here's how much I'll give you for your film. Thank you, we'll go market it. I'm like, really? Seriously? I got the former CMO of FanDuel going to help out on this. You don't want to talk to him? >> Yeah >> And so this is where the industry is really ripe for disruption. Because the people from the startup world have already disrupted the apple cart and now we've just got to demonstrate that this model is going to continue to work for the future and be ready when the next new kind of digital transmedia thing comes along and embrace that, as opposed to be scared to death of it or not even know how to talk the language of the people on it. >> Well, you're doing some amazing venturing in your, kind of, unique venture capital model on Bullpen Capital. Certainly isn't your classic venture capital thing, so I'm sure people are going to be talking to you about oh, Paul, are all VCs going to be doing movies? I'm sure that's a narrative that's out there. But you're not just a normal venture capital. You certainly invest. So, venture capitals have reputation issues right now. People talk about, well, you know, they're group think. You know, they only invest in who they see themselves. You mentioned that comment there. The world's changing in venture. Your thoughts on that, how you guys started your firm, and your evolution of venture capital. And is this a sign that you'll see venture capitalists go into movies? >> Well, I don't know about that part. There have been a couple venture people who have done movies. But the part I will talk about is the you got to know somebody, it's an inside game, ha ha, we'll play double entendre on Inside Game here. You know, 20% of the deal we've done at Bullpen, we've done over 100. 20% of them were cold emails on something like LinkedIn or business plans at bullpen.com. 20%, now there's this old trope in venture if you don't get a warm intro I won't even talk to you. Well 20% of our deals came in and we had no idea who the person on the other side was. That's how we run the firm. And so if you're out there going I'm one of those entrepreneurs in the Midwest and no one, I don't know anyone. I'm not in a network, send me a plan. I'm someone who's going to look at it. It doesn't mean I'm going to be an investor, but you know what I'm going to do? I'm going to give you a shot. And I don't care where you're from or what school you went to or what social clique you're in or what your political persuasion is. Matter of fact, I literally don't care. I'm going to give you a shot. Come into my office and that, I think, is what was missing in a lot of firms, where it's a we only do security and we only look at companies that spun out of Berkeley and Stanford. And yeah, there can be an old boys network in that. But you know what, we like to talk to everybody. And the more blue collar the CEO is, the more we love them at Bullpen. >> That's awesome. Talk about the movie real quick on terms of how Hollywood's handling it. Um, expectations, in terms of reaction, was it positive, is it positive, what's the vibe going on in Hollywood, is this going to be a grassroots kind of thing around the FanDuels and your channels? What's your plan for that and what's the reaction of Hollywood? >> So it's going to be a lot of all of the above. But PR is going to be a huge component, I mean, part of the reason we're on today is there's a huge front page story on ESPN about Tim Donaghy and the NBA betting scandal of 2007. And so the earned media is going to be a huge component of this. And I think this is where the Hollywood people do understand the language we're speaking. We're like, look, we have a huge built-in audience that we know how to market to. We have a story. Actually, in the early days, you asked about risk? Back when I was thinking about if I would do this project I would do the following little market research. I'd walk into a sports bar, it didn't matter what town I was in. I could be in Dallas, I could be in Houston, I could be in Boston. I would literally walk up to the bar and say, hey, uh, six of you at the bar, ever hear of Tim Donaghy? It'd be amazing. About seven out of 10 people would go yeah he was the referee, crooked referee in the NBA. I'm like, this is amazing. Seven out of 10 people I meet in a bar know about the story I want to go tell. That sounds like a good chance to make a movie, as opposed to a movie that has no built-in audience. And so, a built-in audience with PR channels that we know work, I think we can really show Hollywood how to do this in a different way if this all works. >> And this comes back to my point around built-in audiences. You know, YouTube has got a million subscribers. That's kind of an old metric. That means they, like an RSS feed kind of model. That's a million people that are, could be, amplifying their network connections. It is a massive built-in audience. The iteration, the DevOps kind of mindset, we talk about cloud computing, can be applied to movies. It's agile movie making. That's what you're talking about. >> Yeah, and by the way, so we have a social network of all the actors and people in the film. So when it's ready, let's go activate our network of all the actors that are in the film. Each of them have a couple million followers. So let's go be smart. Let's, two weeks before the movie, let's send some screenshots. A week before the movie let's show some exclusive videos. Two days before the film, go see it, it's now out in the theaters. You know what, that's pretty, that's 101. We've got actors. We've got producers. Like, let's go use the influencer network we built that actually got the movie made. Let's go on Sports Talk, talk about the movie. Let's go on places like this and talk about how a venture guy made a movie. This is the confluence of all of the pieces all coming together at once. And I just don't think enough people in the film business or in the media business think big enough about going after these audiences. It's oh, we're going to take ads out on TV and I'm going to see my trailer and we're going to do this and that's how we do it. There's so many better ways to get your audience now. >> And this is going to change, just while I've got you here, it's just awesome, awesome conversation. Bringing it back to kind of the CMO in big companies, whether it's consumer or B to B or whatever, movies, the old model of here's our channels. There's certainly this earned media kind of formula and it's not your classic we've got a website, we're going to do all this instrumentation, it's a whole 'nother mechanism. So talk about, in your opinion, the importance of earned media, vis a vis the old other buckets. Owned media, paid media, well-defined Web 1.0, Web 2.0 tactics, earned media is not just how good is our PR? It's actually infrastructure channels, it's networks, a new kind of way to do things. How relevant and how important will this be going forward? Because there's no more website. It's a, you're basically building a media company for this movie. >> That is exactly right. We're building an ad hoc media business. I think this is what the next generation of digital agencies are going to look like. And there are some agencies that we've talked to that really understand all of what you've just said. They are few and far between, unfortunately. >> Yeah, well, Paul, this was theCube. We love talking to people, making it happen. Again, our model's the same as yours. We're open to anyone who's got signal, and you certainly are doing a great job and great to know you and follow your entrepreneur journey, your investment journey, and now your film making journey. Paul Martino, General Pen on Bullpen Capital, with the hot film Inside Game. I'm definitely going to see it. It should be really strong and it's going to be one of those movies like Crazy, Rich Asians, where not looking, not really well produced, I mean not predicted to be great and then goes game buster so I think this is going to be one of those examples. Paul, thanks for coming on. >> Love it, thank you! >> This Cube Conversation, I'm John Furrier here in Palo Alto, California, bringing ya all the action. Venture capitalist turned film maker Paul Martino with the movie Inside Game. I'm John Furrier, thanks for watching. (triumphant music)

>> Live from Las Vegas, it's theCUBE! Covering AWS re:Invent 2018. Brought to you by Amazon web services, Intel, and their ecosystem partners. >> Hey welcome back everyone, here at AWS re:Invent 2018, their sixth year of theCUBE coverage, two sets wall-to-wall coverage here, two more sets in other locations, getting all the content, bringing it in, ingesting it into our video cloud service on AWS, ah, Dave, >> Lot of content, John. >> Lot of people don't know that we have that video cloud service, but we're going to have a lot of fun, ton of content, ton of stories, and a special analyst segment, Jerry Chen, guest here today, CUBE alumni, famous Venture Capitalist and Greylock partners, partnering with Reid Hoffman, the founder of LinkedIn, great set of partners at Greylock , great firm, tier one, doing a lot of great deals, Rockset, recent one. >> Thanks, yeah. >> You're also, on the record, these six years ago, calling the shot of Babe Ruth predicting the future. You've got a good handle on, you've got VM where you have the cloud business, now you're making investments, you're seeing a lot of stuff on the landscape, certainly, as a Venture Capitalist, you're funding projects, what better time now of innovation to actually put money to work, to hit market share, and then the big guys are getting bigger, they're creating more robust platforms, game is changing big-time, want to get your perspective, Dave, so, Jerry, what's your take on the announcements, slew of announcements, which ones jumped out at you? >> I think there's kind of two or three areas, there's definitely the hybrid cloud story with the Outpost, there's a bunch of stuff around ML and AI services, and a bunch of stuff on data and storage, and for me I think what they're doing around the ML services, the prediction, the personalization, the text OCR, what Amazon's doing at that app layer is now creating AI building blocks for modern application, so you want to do forecasts, you want to do personalization, you want to do text analysis, you have a simple API to basically build these modern apowered apps, he's doing to the app infrastructure layer what he's done to the cloud infrastructure layer, by deconstructing these services. >> And API is also the center, that's what web services are, so question for you is, do you see that the core cloud players, Aussie, Amazon, Bigly, Google, Microsoft, others, it's a winner take most, you called that six years ago, and that's true, but as they grow there's going to be now a new cloudification going on for business apps, new entrepreneurs coming to market, who's vulnerable, who wins, who loses, as this evolution continues because it's going to enable a lot of opportunity. >> Yeah, well I mean Amazon in cloud in general is going to create a lot of winners and losers, like you said, so I think you have a shift of dollars from on prem and old legacy vendors, databay storage, compute, to the cloud, so I think there's a shift of dollars, there are winner and losers, but I think what's going to happen is, with all these services around AI, ML, and Cloud as a distribution model, a lot of applications are going to be rebuilt. So I think that the entire application stack from all the big SaaS players to small SaaS companies, you're going to see this kind of a long tale of new SaaS applications being built on top of the Cloud that you didn't see in the past. >> And the ability to get to markets faster, so the question I have for you is, if you're an entrepreneur out there, looking for funding and I can to market quicker, what's the playbook, and two, Jassie talked on stage about a new persona, a new kind of developer, one that can rethink and reimagine and reinvent something that someone else has already done, so if you're an entrepreneur, you got to think to take someone else's territory, so how does an entrepreneur go out and identify whose lunch to eat, so if I want to take down a company, I got to have a strategy, how do I use the cloud to >> I think it's always a combination when a founder in a thing attacks your market it's a combination of where are the dollars, where can I create some advantage IP or advantage angle, and thirdly where do I have a distribution advantage, how can I actually get my product in the hands of the users differently? And so I think those are the three things, you find intersection of a great market, you have a unique angle, and you have a unique route to market, then you have a powerful story. So, you think about cloud changing the game, think about the mobile app you can consist of, for consumers, that is also a new platform, a new distribution method, the mobile app stores, and so what happened, you had a new category of developers, mode developers, creating this long tale, a thousand thousand apps, for everything from groceries to cars to your Fantasy Football score. So I think you're going to see distribution in the cloud, making it easy to get your apps out there, going to see a bunch of new markets open up, because we're seeing verticals like healthcare, construction, financial services, that didn't have special apps beforehand, be disrupted with technology. Autodesk just bought PlanGrid for 800 million dollars, I mean that's unheard of, construction software company. So you can see a bunch of new inverdics like that be opened up, and then I think with this cloud technology, with compute storage network becomes free and you have this AI layer on top of it, you can power these new applications using AI, that I think is pretty damn exciting. >> Yes, you described this sort of, we went from client server to the cloud, brought a whole bunch of new app providers, obviously Salesforce was there but Workday, Service Now, what you described is a set of composeable digital services running on top of a cloud, so that's ripe for disruption, so do I have to own my own data centers if I'm big SaaS company, what happens to those big guys? >> I don't think you have to, well, you don't have to own your own data center as a company, but you could if you wanted to, right, so at some point in scale, a lot of big players build their own data centers, like AirBNB is on Amazon, but Dropbox built their own storage on Amazon early, then their own data center later. Uber has their own data center, right, so you can argue that at some point of scale it makes sense to build your own, so you don't need to be on Amazon or Google as your start, but it does give you a head start. Now the question is, in the future, can you build a SaaS application entirely on Amazon, Azure, or Google, without any custom code, right, can you hide read write call private SaaS, like a single instance of my SaaS application for you, John, or for you, Dave, that's your data, your workflow, your information personalized for you, so instead of this multi-tenet CRM system like Salesforce, I have a custom CRM system just for Dave, just for Jeff, just for Jerry, just for theCUBE, right? >> I think yes, for that, I think that's definitely a trend I would see happening. >> It's what Infor is trying to do, right, Charles Phillips says "Friends don't let friends "build data centers," but they've still got a big loss in legacy there, but it's an interesting model, focused on verticals or microverticals or like the healthcare example that you're giving, and lot of potential for something. >> Well here's why I think I like this because, I think, and I said this before in theCUBE maybe it's not the best way to say it is that, if you look at the benefit of AI, data-driven, the quality of the data and the power of the compute has to be there. AI will work well with all that stuff, but it's also specialized around the application's use case. So you have specialism around the application, but you don't have to build a full stack to do that, you could use a horizontally scalable cloud distribution system in your word, and then only create custom unique workloads for the app, where machine learning's involved, and AI, that's unique to the app, that's differentiation, that could be the business model, or the utility. So, multitenancy could exist in theory, at the scalable level, but unique at the top of the level so yes I would say I'd want that hosted in the most customized, agile, flexible way. So I would argue that that's the scenario. >> I think that's the future, I mean one of my, I think you were saying, Dave, friends don't let friends build data centers anymore, it's you probably don't need to build a data center anymore because you can actually build your own application on top of one of the two or three large cloud providers. So it's interesting to see what happens the next three, four years, we're going to see kind of a thousand flowers bloom of different apps, not everyone's going to make it, not everyone's going to be a huge Salesforce-like outcome, but there'll be a bunch of applications out there. >> And the IoT stuff is interesting to me, so observing a lot of what the IT guys are doing, it reminds me of people trying to make the Windows mobile phone, they're just trying to force IT standards down the IoT, what I've seen from AWS today is more of a bottoms up approach, build applications for operations technology people, which I think is the right way to go, what do you see in an IoT, IoT apps, what's the formula there? >> I think what Amazon announced today with their time series database, right, their Timestream prediction engine, plus their Outpost offering with the Vmware themselves, you're really seeing a combination of IoT and Edge, right, it's the whole idea is, one, there's a bunch of use cases for time series in IoT, because sentry data, cameras, self-driving cars, drones, et cetera, there's more data coming at you, it adds all of that. >> And Splunk has proven that big-time. >> Correct, Splunk's let 18 billion Marcap company, all on time series data, but number two, what's happening is, it's not necessarily centralized data, right, it's happening at the edge, your self-driving car, your cell phone, et cetera, so Outpost is really a way for Amazon to get closer to the edge, by pushing their compute towards your data center, towards remote office, branch office, and get closer to where the data is, so I think that'll be super interesting. >> Well the Elastic Inference engine is critical, now we got elasticity around inference, and then they got the chip set that worked Inferentia, that can work with the elastic service. That's a powerful combination. >> The AI plumbing war between Google and TetraFlow as technology there's like PyTorch, Google TPUs versus what Amazon is doing with inference chips today, versus what I'm sure Microsoft and else is doing, is fascinating to watch in terms of how you had a kind of a Intel Nvidia duopoly for a long time, and now you have Intel, Nvidia, and then everyone from Amazon, Google, Microsoft doing their own soul again, it's pretty fascinating to watch. >> What was the stat, he said 85% of the TensorFlow, cloud TensorFlow's running on AWS? >> Makes a lot of sense, I think he said Aurora's customers logoslide doubled, but let's break down real quick, to end the segment with the key areas that we see going on, at least my perspective, I want to get your reaction. Storage, major disruption, he emphasized a lot of that in the keynote, spent a lot of time on stores, actually I think more than EC2 if you look at it, two, databases, database war, storage rate configuration, and a holy trinity of networking, storage, and compute, that's evolving, databases, SageMaker, machine learning. All there and then over the top, yesterday's announcement of satellite as a service, that essentially kills the edge of the network, cause there is no edge if we have space satellites shooting connectivity to any device the world is now, there's no more edge, it's everywhere. So, your thoughts, those areas. Which one pops out as the most surprising or most relevant? >> I think it's consistent Amazon strategy, on the lowest layer they're trying to draw the cost to zero, so on storage, cheaper cheaper cheaper, they're driving the bottom layer to zero to get all your data. I think the second thing, the database layer, it makes sense, it's not open-source, right, time scale or time series, it's not, Timestream's not their open-source database, it's their own, so open-source, low cost, the lowest layer, their database stuff is mostly their own, Aurora, Dynamo, Timestream, right, because there's some level lock in there, which I think customers are worried about, so that's clever, it's not by accident, that's all proprietary, and then ML Services, on top of that, that's all cares with developers, and it's API locking, so clearly low-cost open-source for the bottom, proprietary data services that they're trying to own, and then API's on top of it. And so the higher up in the stack, the more and more Amazon, you look, the more and more Amazon you have to adopt as kind of a lock in stack, so it's a brilliant strategy the guys have been executing for the past six, seven years as you guys have seen firsthand, I think the most exciting thing, and the most shocking thing to me is this move towards this battle for the AI front, this ML AI front, I think we saw ML's the new sequel, right, that's the new war, right, against Amazon, Google, and Microsoft. >> And that's the future of applications, cause this is >> But you're right on, it's a knife fight for the data, and then you layer on machine intelligence on top of that, and you get cloud scale, and that's the innovation engine for the next 10 years. >> Alright Jerry Chen just unpacked the State of the Union of cloud, of course as an investor I got to ask the final question, how are you investing to take advantage of this wave, versus being on the wrong side of history? >> I have framers for everything, there's a framer on how to attack the cloud vendors, and so I'm looking at a couple things, one, a seams in between the clouds, right, or in between services, because they can't do everything well, and there were kind of these large continents, Amazon, Google, Azure, so I'm looking for seams between the three of them, I'm looking for two, deep areas of IP that they're not going into that you actually have proprietary tap, and then verticals of data, like source of the data, or workflows that these guys aren't great, and then finally kind of cross-data cross-cloud solution, so, something that gives you the ability to run on prem, off prem, Microsoft, Google, Azure. >> Yeah, fill in the white spaces, there are big white spaces, and then hope that could develop into, good. Jerry Chen, partner in Greylock , partners formerly Vmware part of the V Mafia, friend of theCUBE, great guest analysis here, with Dave Vellante and John Furrier, thanks for watching us, stay with us, more live coverage, day two of three days of wall-to-wall coverage at re:Invent, 52,000 people, the whole industry's here, you can see the formations, we're getting all of the data, we're bringing it to you, stay with us.

[Music] we're on welcome to the special cube conversation we're here with some breaking news we got some startup investment news here in the Q studios palo alto I'm John for your host here at Jerry Chen partnered Greylock and the CEO of rock said Venkat Venkat Rahmani welcome to the cube you guys announcing hot news today series a and seed and Series A funding 21 million dollars for your company congratulations thank you Roxette is a data company jerry great this is one of your nest you kept this secret forever it was John was really hard you know over the past two years every time I sat in this seat I'd say and one more thing you know I knew that part of the advantage was rocks I was a special company and we were waiting to announce it and that's right time so it's been about two and half years in the making I gotta give you credit Jerry I just want to say to everyone I try to get the secrets out of you so hard you are so strong and keeping a secret I said you got this hot startup this was two years ago yeah I think the probe from every different angle you can keep it secrets all the entrepreneurs out there Jerry Chen's your guide alright so congratulations let's talk about the startup so you guys got 21 million dollars how much was the seed round this is the series a the seed was three million dollars both Greylock and Sequoia participating and the series a was eighteen point five all right so other investors Jerry who else was in on this I just the two firms former beginning so we teamed up with their French from Sequoia and the seed round and then we over the course of a year and half like this is great we're super excited about the team bank had Andrew bhai belt we love the opportunity and so Mike for an office coin I said let's do this around together and we leaned in and we did it around alright so let's just get into the other side I'm gonna read your your about section of the press release roxette's visions to Korea to build the data-driven future provide a service search and analytics engine make it easy to go from data to applications essentially building a sequel layer on top of the cloud for massive data ingestion I want to jump into it but this is a hot area not a lot of people are doing this at the level you guys are now and what your vision is did this come from what's your background how did you get here did you wake up one Wednesday I'm gonna build this awesome contraction layer and build an operating system around data make this thing scalable how did it all start I think it all started from like just a realization that you know turning useful data to useful apps just requires lots of like hurdles right you have to first figure out what format the data is in you got to prepare the data you gotta find the right specialized you know data database or data management system to load it in and it often requires like weeks to months before useful data becomes useful apps right and finally you know after I you know my tenure at Facebook when I left the first thing I did was I was just talking you know talking to a lot of people with real-world companies and reload problems and I started walking away from moremore of them thinking that this is way too complex I think the the format in which a lot of the data is coming in is not the format in which traditional sequel based databases are optimized for and they were built for like transaction processing and analytical processing not for like real-time streams of data but there's JSON or you know you know parque or or any of these other formats that are very very popular and more and more data is getting produced by one set of applications and getting consumed by other applications but what we saw it was what is this how can we make it simpler why do we need all this complexity right what is a simple what is the most simple and most powerful system we can build and pulled in the hands of as many people as possible and so we very sort of naturally relate to developers and data scientists people who use code on data that's just like you know kind of like our past lives and when we thought about it well why don't we just index the data you know traditional databases were built when every byte mattered every byte of memory every byte on disk now in the cloud the economics are completely different right so when you rethink those things with fresh perspective what we said was like what if we just get all of this data index it in a format where we can directly run very very fast sequel on it how simple would the world be how much faster can people go from ideas to do experiments and experiments to production applications and how do we make it all faster also in the cloud right so that's really the genesis of it well the real inspiration came from actually talking to a lot of people with real-world problems and then figuring out what is the simplest most powerful thing we can build well I want to get to the whole complexity conversation cuz we were talking before we came on camera here about how complexity can kill and why and more complexity on top of more complexity I think there's a simplicity angle here that's interesting but I want to get back to your background of Facebook and I want to tell a story you've been there eight years but you were there during a very interesting time during that time in history Facebook was I think the first generation we've taught us on the cube all the time about how they had to build their own infrastructure at scale while they're scaling so they were literally blitzscaling as reid hoffman and would say and you guys do it the Greylock coverage unlike other companies at scale eBay Microsoft they had old-school one dotto Technology databases Facebook had to kind of you know break glass you know and build the DevOps out from generation one from scratch correct it was a fantastic experience I think when I started in 2007 Facebook had about 40 million monthly actives and I had the privilege of working with some of the best people and a lot of the problems we were very quickly around 2008 when I went and said hey I want to do some infrastructure stuff the mandate that was given to me and my team was we've been very good at taking open source software and customizing it to our needs what would infrastructure built by Facebook for Facebook look like and we then went into this journey that ended up being building the online data infrastructure at Facebook by the time I left the collectively these systems were surveying 5 plus billion requests per second across 25 plus geographical clusters and half a dozen data centers I think at that time and now there's more and the system continues to chug along so it was just a fantastic experience I think all the traditional ways of problem solving just would not work at that scale and when the user base was doubling early in the early days every four months every five months yeah and what's interesting you know you're young and here at the front lines but you're kind of the frog in boiling water and that's because you are you were at that time building the power DevOps equation automating scale growth everything's happening at once you guys were right there building it now fast forward today everyone who's got an enterprise it's it wants to get there they don't they're not Facebook they don't have this engineering staff they want to get scale they see the cloud clearly the value property has got clear visibility but the economics behind who they hire so they have all this data and they get more increasing amount of data they want to be like Facebook but can't be like Facebook so they have to build their own solutions and I think this is where a lot of the other vendors have to rebuild this cherry I want to ask you because you've been looking at a lot of investments you've seen that old guard kind of like recycled database solutions coming to the market you've seen some stuff in open source but nothing unique what was it about Roxette that when you first talk to them that but you saw that this is going to be vectoring into a trend that was going to be a perfect storm yeah I think you nailed it John historic when we have this new problems like how to use data the first thing trying to do you saw with the old technology Oh existing data warehouses akin databases okay that doesn't work and then the next thing you do is like okay you know through my investments in docker and B and the boards or a cloud aerosol firsthand you need kind of this rise of stateless apps but not stateless databases right and then I through the cloud area and a bunch of companies that I saw has an investor every pitch I saw for two or three years trying to solve this data and state problem the cloud dudes add more boxes right here's here's a box database or s3 let me solve it with like Oh another database elastic or Kafka or Mongo or you know Apache arrow and it just got like a mess because if almond Enterprise IT shop there's no way can I have the skill the developers to manage this like as Beckett like to call it Rube Goldberg machination of data pipelines and you know I first met Venkat three years ago and one of the conversations was you know complexity you can't solve complex with more complexity you can only solve complexity with simplicity and Roxette and the vision they had was the first company said you know what let's remove boxes and their design principle was not adding another boxes all a problem but how to remove boxes to solve this problem and you know he and I got along with that vision and excited from the beginning stood to leave the scene ah sure let's go back with you guys now I got the funding so use a couple stealth years to with three million which is good a small team and that goes a long way it certainly 2021 total 18 fresh money it's gonna help you guys build out the team and crank whatnot get that later but what did you guys do in the in those two years where are you now sequel obviously is lingua franca cool of sequel but all this data is doesn't need to be scheming up and built out so were you guys that now so since raising the seed I think we've done a lot of R&D I think we fundamentally believe traditional data management systems that have been ported over to run on cloud Williams does not make them cloud databases I think the cloud economics is fundamentally different I think we're bringing this just scratching the surface of what is possible the cloud economics is you know it's like a simple realization that whether you rent 100 CPUs for one minute or or one CPU 400 minutes it's cost you exactly the same so then if you really ask why is any of my query is slow right I think because your software sucks right so basically what I'm trying to say is if you can actually paralyze that and if you can really exploit the fluidity of the hardware it's not easy it's very very difficult very very challenging but it's possible I think it's not impossible and if you can actually build software ground-up natively in the cloud that simplifies a lot of this stuff and and understands the economics are different now and it's system software at the end of the day is how do I get the best you know performance and efficiency for the price being paid right and the you know really building you know that is really what I think took a lot of time for us we have built not only a ground-up indexing technique that can take raw data without knowing the shape of the data we can turn that and index it in ways and store them maybe in more than one way since for certain types of data and then also have built a distributed sequel engine that is cloud native built by ground up in the cloud and C++ and like really high performance you know technologies and we can actually run distributor sequel on this raw data very very fast my god and this is why I brought up your background on Facebook I think there's a parallel there from the ground this ground up kind of philosophy if you think of sequel as like a Google search results search you know keyword it's the keyword for machines in most database worlds that is the standard so you can just use that as your interface Christ and then you using the cloud goodness to optimize for more of the results crafty index is that right correct yes you can ask your question if your app if you know how to see you sequel you know how to use Roxette if you can frame your the question that you're asking in order to answer an API request it could be a micro service that you're building it could be a recommendation engine that you're that you're building or you could you could have recommendations you know trying to personalize it on top of real time data any of those kinds of applications where it's a it's a service that you're building an application you're building if you can represent ask a question in sequel we will make sure it's fast all right let's get into the how you guys see the application development market because the developers will other winners here end of the day so when we were covering the Hadoop ecosystem you know from the cloud era days and now the important work at the Claire merger that kind of consolidates that kind of open source pool the big complaint that we used to hear from practitioners was its time consuming Talent but we used to kind of get down and dirty the questions and ask people how they're using Hadoop and we had two answers we stood up Hadoop we were running Hadoop in our company and then that was one answer the other answer was we're using Hadoop for blank there was not a lot of those responses in other words there has to be a reason why you're using it not just standing it up and then the Hadoop had the problem of the world grew really fast who's gonna run it yeah management of it Nukem noose new things came in so became complex overnight it kind of had took on cat hair on it basically as we would say so how do you guys see your solution being used so how do you solve that what we're running Roxette oh okay that's great for what what did developers use Roxette for so there are two big personas that that we currently have as users right there are developers and data scientists people who program on data right - you know on one hand developers want to build applications that are making either an existing application better it could be a micro service that you know I want to personalize the recommendations they generated online I mean offline but it's served online but whether it is somebody you know asking shopping for cars on San Francisco was the shopping you know was the shopping for cars in Colorado we can't show the same recommendations based on how do we basically personalize it so personalization IOT these kinds of applications developers love that because often what what you need to do is you need to combine real-time streams coming in semi structured format with structured data and you have no no sequel type of systems that are very good at semi structured data but they don't give you joins they don't give you a full sequel and then traditional sequel systems are a little bit cumbersome if you think about it I new elasticsearch but you can do joins and much more complex correct exactly built for the cloud and with full feature sequel and joins that's how that's the best way to think about it and that's how developers you said on the other side because its sequel now all of a sudden did you know data scientist also loved it they had they want to run a lot of experiments they are the sitting on a lot of data they want to play with it run experiments test hypotheses before they say all right I got something here I found a pattern that I don't know I know I had before which is why when you go and try to stand up traditional database infrastructure they don't know how what indexes to build how do i optimize it so that I can ask you know interrogatory and all that complexity away from those people right from basically provisioning a sandbox if you will almost like a perpetual sandbox of data correct except it's server less so like you don't you never think about you know how many SSDs do I need how many RAM do I need how many hosts do I need what configure your programmable data yes exactly so you start so DevOps for data is finally the interview I've been waiting for I've been saying it for years when's is gonna be a data DevOps so this is kind of what you're thinking right exactly so you know you give us literally you you log in to rocks at you give us read permissions to battle your data sitting in any cloud and more and more data sources we're adding support every day and we will automatically cloudburst will automatically interested we will schematize the data and we will give you very very fast sequel over rest so if you know how to use REST API and if you know how to use sequel you'd literally need don't need to think about anything about Hardware anything about standing up any servers shards you know reindex and restarting none of that you just go from here is a bunch of data here are my questions here is the app I want to build you know like you should be bottleneck by your career and imagination not by what can my data employers give me through a use case real quick island anyway the Jarius more the structural and architectural questions around the marketplace take me through a use case I'm a developer what's the low-hanging fruit use case how would I engage with you guys yeah do I just you just ingest I just point data at you how do you see your market developing from the customer standpoint cool I'll take one concrete example from a from a developer right from somebody we're working with right now so they have right now offline recommendations right or every night they generate like if you're looking for this car or or this particular item in e-commerce these are the other things are related well they show the same thing if you're looking at let's say a car this is the five cars that are closely related this car and they show that no matter who's browsing well you might have clicked on blue cars the 17 out of 18 clicks you should be showing blue cars to them right you may be logging in from San Francisco I may be logging in from like Colorado we may be looking for different kinds of cars with different you know four-wheel drives and other options and whatnot there's so much information that's available that you can you're actually by personalizing it you're adding creating more value to your customer we make it very easy you know live stream all the click stream beta to rock set and you can join that with all the assets that you have whether it's product data user data past transaction history and now if you can represent the joins or whatever personalization that you want to find in real time as a sequel statement you can build that personalization engine on top of Roxanne this is one one category you're putting sequel code into the kind of the workflow of the code saying okay when someone gets down to these kinds of interactions this is the sequel query because it's a blue car kind of go down right so like tell me all the recent cars that this person liked what color is this and I want to like okay here's a set of candidate recommendations I have how do I start it what are the four five what are the top five I want to show and then on the data science use case there's a you know somebody building a market intelligence application they get a lot of third-party data sets it's periodic dumps of huge blocks of JSON they want to combine that with you know data that they have internally within the enterprise to see you know which customers are engaging with them who are the persons churning out what are they doing and they in the in the market and trying to bring they bring it all together how do you do that when you how do you join a sequel table with a with a JSON third party dumb and especially for coming and like in the real-time or periodic in a week or week month or one month literally you can you know what took this particular firm that we're working with this is an investment firm trying to do market intelligence it used age to run ad hoc scripts to turn all of this data into a useful Excel report and that used to take them three to four weeks and you know two people working on one person working part time they did the same thing in two days and Rock said I want to get to back to microservices in a minute and hold that thought I won't go to Jerry if you want to get to the business model question that landscape because micro services were all the world's going to Inc so competition business model I'll see you gets are funded so they said love the thing about monetization to my stay on the core value proposition in light of the red hat being bought by by IBM had a tweet out there kind of critical of the transactions just in terms of you know people talk about IBM's betting the company on RedHat Mike my tweet was don't get your reaction will and tie it to the visible here is that it seems like they're going to macro services not micro services and that the world is the stack is changing so when IBM sell out their stack you have old-school stack thinkers and then you have new-school stack thinkers where cloud completely changes the nature of the stack in this case this venture kind of is an indication that if you think differently the stack is not just a full stack this way it's this way in this way yeah as we've been saying on the queue for a couple of years so you get the old guard trying to get a position and open source all these things but the stacks changing these guys have the cloud out there as a tailwind which is a good thing how do you see the business model evolving do you guys talk about that in terms of you can hey just try to find your groove swing get customers don't worry about the monetization how many charging so how's that how do you guys talk about the business model is it specific and you guys have clear visibility on that what's the story on that I mean I think yeah I always tell Bank had this kind of three hurdles you know you have something worthwhile one well someone listen to your pitch right people are busy you like hey John you get pitched a hundred times a day by startups right will you take 30 seconds listen to it that's hurdle one her will to is we spend time hands on keyboards playing around with the code and step threes will they write you a check and I as a as a enter price offered investor in a former operator we don't overly folks in the revenue model now I think writing a check the biz model just means you're creating value and I think people write you checking screening value but you know the feedback I always give Venkat and the founders work but don't overthink pricing if the first 10 customers just create value like solve their problems make them love the product get them using it and then the monetization the actual specifics the business model you know we'll figure out down the line I mean it's a cloud service it's you know service tactically to many servers in that sentence but it's um it's to your point spore on the cloud the one that economists are good so if it works it's gonna be profitable yeah it's born the cloud multi-cloud right across whatever cloud I wanna be in it's it's the way application architects going right you don't you don't care about VMs you don't care about containers you just care about hey here's my data I just want to query it and in the past you us developer he had to make compromises if I wanted joins in sequel queries I had to use like postgrads if I won like document database and he's like Mongo if I wanted index how to use like elastic and so either one I had to pick one or two I had to use all three you know and and neither world was great and then all three of those products have different business models and with rocks head you actually don't need to make choices right yes this is classic Greylock investment you got sequoia same way go out get a position in the market don't overthink the revenue model you'll funded for grow the company let's scale a little bit and figure out that blitzscale moment I believe there's probably the ethos that you guys have here one thing I would add in the business model discussion is that we're not optimized to sell latte machines who are selling coffee by the cup right so like that's really what I mean we want to put it in the hands of as many people as possible and make sure we are useful to them right and I think that is what we're obsessed about where's the search is a good proxy I mean that's they did well that way and rocks it's free to get started right so right now they go to rocks calm get started for free and just start and play around with it yeah yeah I mean I think you guys hit the nail on the head on this whole kind of data addressability I've been talking about it for years making it part of the development process programming data whatever buzzword comes out of it I think the trend is it looks a lot like that depo DevOps ethos of automation scale you get to value quickly not over thinking it the value proposition and let it organically become part of the operation yeah I think we we the internal KPIs we track are like how many users and applications are using us on a daily and weekly basis this is what we obsess about I think we say like this is what excellence looks like and we pursue that the logos in the revenue would would you know would be a second-order effect yeah and it's could you build that core kernels this classic classic build up so I asked about the multi cloud you mention that earlier I want to get your thoughts on kubernetes obviously there's a lot of great projects going on and CN CF around is do and this new state problem that you're solving in rest you know stateless has been an easy solution VP is but API 2.0 is about state right so that's kind of happening now what's your view on kubernetes why is it going to be impactful if someone asked you you know at a party hey thank you why is what's all this kubernetes what party going yeah I mean all we do is talk about kubernetes and no operating systems yeah hand out candy last night know we're huge fans of communities and docker in fact in the entire rock set you know back-end is built on top of that so we run an AWS but with the inside that like we run or you know their entire infrastructure in one kubernetes cluster and you know that is something that I think is here to stay I think this is the the the programmability of it I think the DevOps automation that comes with kubernetes I think all of that is just like this is what people are going to start taking why is it why is it important in your mind the orchestration because of the statement what's the let's see why is it so important it's a lot of people are jazzed about it I've been you know what's what's the key thing I think I think it makes your entire infrastructure program all right I think it turns you know every aspect of you know for example yeah I'll take it I'll take a concrete example we wanted to build this infrastructure so that when somebody points that like it's a 10 terabytes of data we want to very quickly Auto scale that out and be able to grow this this cluster as quickly as possible and it's like this fluidity of the hardware that I'm talking about and it needs to happen or two levels it's one you know micro service that is ingesting all the data that needs to sort of burst out and also at the second level we need to be able to grow more more nodes that we we add to this cluster and so the programmability nature of this like just imagine without an abstraction like kubernetes and docker and containers and pods imagine doing this right you are building a you know a lots and lots of metrics and monitoring and you're trying to build the state machine of like what is my desired state in terms of server utilization and what is the observed state and everything is so ad hoc and very complicated and kubernetes makes this whole thing programmable so I think it's now a lot of the automation that we do in terms of called bursting and whatnot when I say clock you know it's something we do take advantage of that with respect to stateful services I think it's still early days so our our position on my partner it's a lot harder so our position on that is continue to use communities and continue to make things as stateless as possible and send your real-time streams to a service like Roxette not necessarily that pick something like that very separate state and keep it in a backhand that is very much suited to your micro service and the business logic that needs to live there continue should continue to live there but if you can take a very hard to scale stateful service split it into two and have some kind of an indexing system Roxette is one that you know we are proud of building and have your stateless communal application logic and continue to have that you know maybe use kubernetes scale it in lambdas you know for all we care but you can take something that is very hard to you know manage and scale today break it into the stateful part in the stateless part and the serval is back in like like Roxette will will sort of hopefully give you a huge boost in being able to go from you know an experiment to okay I'm gonna roll it out to a smaller you know set of audience to like I want to do a worldwide you know you can do all of that without having to worry about and think about the alternative if you did it the old way yeah yeah and that's like talent you'd need it would be a wired that's spaghetti everywhere so Jerry this is a kubernetes is really kind of a benefit off your your investment in docker you must be proud and that the industry has gone to a whole nother level because containers really enable all this correct yeah so that this is where this is an example where I think clouds gonna go to a whole nother level that no one's seen before these kinds of opportunities that you're investing in so I got to ask you directly as you're looking at them as a as a knowledgeable cloud guy as well as an investor cloud changes things how does that change how is cloud native and these kinds of new opportunities that have built from the ground up change a company's network network security application era formants because certainly this is a game changer so those are the three areas I see a lot of impact compute check storage check networking early days you know it's it's it's funny it gosh seems so long ago yet so briefly when you know I first talked five years ago when I first met mayor of Essen or docker and it was from beginning people like okay yes stateless applications but stateful container stateless apps and then for the next three or four years we saw a bunch of companies like how do I handle state in a docker based application and lots of stars have tried and is the wrong approach the right approach is what these guys have cracked just suffered the state from the application those are app stateless containers store your state on an indexing layer like rock set that's hopefully one of the better ways saw the problem but as you kind of under one problem and solve it with something like rock set to your point awesome like networking issue because all of a sudden like I think service mesh and like it's do and costs or kind of the technologies people talk about because as these micro services come up and down they're pretty dynamic and partially as a developer I don't want to care about that yeah right that's the value like a Roxanna service but still as they operate of the cloud or the IT person other side of the proverbial curtain I probably care security I matters because also India's flowing from multiple locations multiple destinations using all these API and then you have kind of compliance like you know GDP are making security and privacy super important right now so that's an area that we think a lot about as investors so can I program that into Roxette what about to build that in my nap app natively leveraging the Roxette abstraction checking what's the key learning feature it's just a I'd say I'm a prime agent Ariane gdpr hey you know what I got a website and social network out in London and Europe and I got this gdpr nightmare I don't we don't have a great answer for GDP are we are we're not a controller of the data right we're just a processor so I think for GDP are I think there is still the controller still has to do a lot of work to be compliant with GDP are I think the way we look at it is like we never forget that this ultimately is going to be adding value to enterprises so from day one we you can't store data and Roxette without encrypting it like it's just the on you know on by default the only way and all transit is all or HTTPS and SSL and so we never freaked out that we're building for enterprises and so we've baked in for enterprise customers if they can bring in their own custom encryption key and so everything will be encrypted the key never leaves their AWS account if it's a you know kms key support private VP ceilings like we have a plethora of you know security features so that the the control of the data is still with the data controller with this which is our customer but we will be the the processor and a lot of the time we can process it using their encryption keys if I'm gonna build a GDP our sleeves no security solution I would probably build on Roxette and some of the early developers take around rocks at our security companies that are trying to track we're all ideas coming and going so there the processor and then one of the companies we hope to enable with Roxette is another generation security and privacy companies that in the past had a hard time tracking all this data so I can build on top of rocks crack okay so you can built you can build security a gbbr solution on top rock set because rock set gives you the power to process all the data index all the data and then so one of the early developers you know stolen stealth is they looking at the data flows coming and go he's using them and they'll apply the context right they'll say oh this is your credit card the Social Security is your birthday excetera your favorite colors and they'll apply that but I think to your point it's game-changing like not just Roxette but all the stuff in cloud and as an investor we see a whole generation of new companies either a to make things better or B to solve this new category problems like pricing the cloud and I think the future is pretty bright for both great founders and investors because there's just a bunch of great new companies and it's building up from the ground up this is the thing I brought my mother's red hat IBM thing is that's not the answer at the root level I feel like right now I'd be on I I think's fastenings but it's almost like you're almost doubling down to your your comment on the old stack right it's almost a double down the old stack versus an aggressive bet on kind of what a cloud native stack will look like you know I wish both companies are great people I was doing the best and stuff do well with I think I'd like to do great with OpenStack but again their product company as the people that happen to contribute to open source I think was a great move for both companies but it doesn't mean that that's not we can't do well without a new stack doing well and I think you're gonna see this world where we have to your point oh these old stacks but then a category of new stack companies that are being born in the cloud they're just fun to watch it all it's all big all big investments that would be blitzscaling criteria all start out organically on a wave in a market that has problems yeah and that's growing so I think cloud native ground-up kind of clean sheet of paper that's the new you know I say you're just got a pic pick up you got to pick the right way if I'm oh it's gotta pick a big wave big wave is not a bad wave to be on right now and it's at the data way that's part of the cloud cracked and it's it's been growing bigger it's it's arguably bigger than IBM is bigger than Red Hat is bigger than most of the companies out there and I think that's the right way to bet on it so you're gonna pick the next way that's kind of cloud native-born the cloud infrastructure that is still early days and companies are writing that way we're gonna do well and so I'm pretty excited there's a lot of opportunities certainly this whole idea that you know this change is coming societal change you know what's going on mission based companies from whether it's the NGO to full scale or all the applications that the clouds can enable from data privacy your wearables or cars or health thing we're seeing it every single day I'm pretty sad if you took amazon's revenue and then edit edit and it's not revenue the whole ready you look at there a dybbuk loud revenue so there's like 20 billion run which you know Microsoft had bundles in a lot of their office stuff as well if you took amazon's customers to dinner in the marketplace and took their revenue there clearly would be never for sure if item binds by a long shot so they don't count that revenue and that's a big factor if you look at whoever can build these enabling markets right now there's gonna be a few few big ones I think coming on they're gonna do well so I think this is a good opportunity of gradual ations thank you thank you at 21 million dollars final question before we go what are you gonna spend it on we're gonna spend it on our go-to-market strategy and hiding amazing people as many as we can get good good answer didn't say launch party that I'm saying right yeah okay we're here Rex at SIA and Joe's Jerry Chen cube cube royalty number two all-time on our Keeble um nine list partner and Greylock guy states were coming in I'm Jeffrey thanks for watching this special cube conversation [Music]

(upbeat music) >> Narrator: Live from Los Angeles, it's theCUBE, covering Open Source Summit North America 2017, brought to you by The Linux Foundation and Red Hat. >> Hello there and welcome to our special exclusive SiliconANGLE Media CUBE coverage here in Los Angeles, California, for the Open Source Summit North America. I'm John Furrier, my co-host, Stu Miniman, for the two days of wall-to-wall coverage, this is day two of our coverage of what's going on in the Open Source world as the Linux Foundation consolidates their shows into a big tent event. This is the inaugural event of now consolidated, a bunch of little shows come together. This is the big show where the Linux Foundation brings their entire communities together to talk and cross-pollinate with Jim Zemlin, the Executive Director, as they outline that. Stu, we're in our kickoff of day two, we're going to do some analysis and commentary, but before we start I want to get your thoughts on just day one. Yesterday we had a lot of guests, a lot of activities going on at night, we kind of divided and conquered. What did you find out? >> Yeah so John you'd done some coverage of LinuxCon a couple of years ago, it's my first time coming to this show. We do a lot of Open Source coverage with theCUBE's over the years, so coming in it was like, okay, what are we going to be talking about, what's the vibe? And being a big tent event, you know, I was a little surprised to see, I mean, the conversation's the same that we've been hearing the last year. Kubernetes, kind of the big wave that's coming in, not just in Open Source, but really the conversation in cloud, and really was kind of the top issue that kind of containerization, the new way of architecting things, you know, Linux absolutely is down there underneath, and majorly important but, you know, it seems to be that rallying around everything Kubernetes. MesosCon's right next door, and we said two years ago you never would have thought that, Kubernetes, that Mesos would be saying, you know, the best place to run Kubernetes is on DCOS. You know, it was the container wars, the orchestration wars, all those things. Kubernetes really leading the charge there, and it really fed into a lot of the conversations we had here. And in our conversations, like with Christine Corbett, and in some of the keynotes this morning, really talking about the power of collaboration, community, you know, stuff like that, we were passionate about John. >> Yeah, I mean, Stu, here's my take on the big story coming out of L.A. for this event. And I think the top line story is this. The Open Source community has had so much success going in the early days and depending which generation you want to call it, you know, we're a little bit older, old school, maybe fourth generation, you can argue the point but here's the bottom line. The big story is that the Linux Foundation, Linux apps, are everywhere, it's a global standard, it is happening. And the scale of which the growth that's going to be coming is unprecedented, and I think for the first time in the history of the computer industry, you're seeing a pause. You're seeing a moment of excitement from the executive director, the Linux Foundation, the board members, and the participants in the community who are realizing, holy shit, this is going to grow very huge. And Open Source is going to go to a whole 'nother growth level, it's going to be exponential in scale, and you're going to see some blitzscaling going on, as Jerry Chen at Greylock and Reid Hoffman talk about. And that's going to change the nature of the participation. You're going to start to see new accelerated things, certification, the role of the foundation certainly has always been to serve the sustainable communities of Open Source. Their role will change as stewards of Open Source, the responsibility and the reliance on the Open Source software will continue to grow, and I think that scale phenomenon of Open Source is, potentially, might be the biggest wave of all, Stu, and I think some people are going to be washed like driftwood and some people are going to thrive and survive. >> You know, it's interesting, we look back at Linux, and Linux took a long time, you know, more than a decade, to really kind of gain mainstream adoption. You know, Red Hat, of course came out of with kind of the leadership and the dollars, but Linux was the foundation for everything being built today. There would be no Google without Linux. There would be no Amazon as we know it today without Linux. And I really liked, I think it was strong resonance, everybody's a little surprised, Joseph Gordon-Levitt in the keynote this morning, someone that we know, you know, from the movies, and we're here in L.A., they're like, oh great, they brought an actor. Well, he's actually pretty passionate. He has this website hitrecord.org, where they do, you know, collaboration, and it's people that are drawing and creating music and creating little clips and everything and they said how a community can help build on what they're doing. He said it's about community, fair compensation, and collaborating, rather than just socializing and sharing or any of those things. And something we've talked a lot is, what is the translation of participating in the community translate into dollars, translate into value. I know it's something you're really passionate about. >> Yeah, Stu, this is again, the big story is the growth. But let's unpack that a little bit. Open Source has always been about sharing, it's always been about community, it's been about innovation, freedom, they called them radicals in the early days but now they got to grow, flexibility, and execution. Here's the bottom line. The leadership of the Open Source is going to morph radically. Look at the program here. You got inclusion, you got a little politics, not like politics of open source, politics of cultural shaping with Christine Corbett Morgan, so she's talking about that, it's very relevant. You have Dan Lyons coming in, talking about the programmer culture, you have the actor coming in talking about collective intelligence. I believe that there's going to be a new way of how people are going to be compensated, how participation's going to scale and this comes down to some key tell tale signs. One, a new generation's coming into the Open Source world, this younger generation. They love Serverless, the love DevOps, because they don't want to deal with the infrastructure. So all the old folks, guys like our age, and gals, they have to provide leadership. I talked with Sam Ramji about this in detail, about how some of these stewards in the community have to step up and be leaders in a new way of governing because as the onboarding of more source code, more projects with IOT, with cloud, you're going to see a new generation of young developers that quite frankly are going to want to run fast, run faster, and they don't want to deal with networking, they don't want to, they want serverless, they want true programmable infrastructure, and that's going to potentially cause some changes, maybe at the leadership level but also how they run things. So, I think, Stu, this is something that we're watching as a big wave. >> Yeah, and it's funny because, we always talk, I'd love to be able to extract a way, even virtualization, oh, we're going to make it real simple, you don't have to worry it anymore, well, you know, John, we got some more interviews today, you know. Networking, storage, these things just don't magically, fairy dust, everything works really well, you know. Data has gravity, networking has lots of challenges we have to worry about. Open Source is now infused into all of these environments. Really helping to build those distributed architectures. We had a number of interviews yesterday talking about, these things are not easy, these are tough challenges. You know, even you talk to people and say, "Kubernetes is awesome," sure is not simple, it is not easy to crawl out. >> They've not graduated any projects out of the CNCF yet, talking to Chris yesterday, the COO, he said, "look, we haven't even graduated anything out of," but this is the point, Stu. Kubernetes is a tell sign, that's not fully-baked yet, it's an under-the-hood feature. Serverless, which I love the name and hate it at the same time because there's servers out there. The notion is that the due developers don't want a provision hardware, to them they just want a resource pool, so serverless is a good trend. The name is kind of weak in my opinion, but I kind of love it and hate it at the same time, I mean. >> John, it's just like cloud was 10 years ago. >> What do you think of Serverless, Stu? I mean bottom line is that how could you not like Serverless because as a developer you're just programming infrastructure as code. >> Right, absolutely, I want to be able to use things in a much more granular format, I want to be able to when I'm not using it not pay for it, it really fits into that environment. Something of course, with this show we're talking about is today, you say Serverless, I think AWS Lambda. The proprietary offering, how does something like Kubernetes fit into that? There's containers underneath, but there are a few different Open Source versions that functions as a service. There's Open FaaS, there's OpenWhisk, there's a couple of others, so how will I be able to take what we were liking about containers in general and Kubernetes specifically, that I can work across a number of environments to make sure that I'm not, John, I'm going to say the word, locked in, to a certain provider or a certain piece of the ecosystem. >> Well, Open Source is so robust right now. Again, 10% of the original ideas can be written in code that could be part of the 90% Open Source base code base. Jim Zemlin, the executive director called that the Code Sandwich. But the bottom line in my opinion, Stu, and you were just pointing it out is that the leadership has to scale. And I think one of the things that came up in some of my hallway conversations last night, talking to some folks who have been early on in Open Source, in the old days you had to hate someone, there was an enemy. There was Microsoft, and now they're on board. There was the big proprietary main mini-computer guys, the proprietary operating systems, they were the enemy. Who's the enemy now? The enemy is slowness, right? So, kind of the fundamental question is, Open Source doesn't have that enemy anymore, it's the standard. So the question is what is going to motivate the organizations? To me, I think it's speed. Speed is the new normal, scale is the new normal. Slowness and silos will be the enemy. >> Absolutely, John. It's something I've heard at a number of events we've been at recently, companies' number one thing is not cost, it's speed, and one of the reasons that so many companies work on, contribute to Open Source is to help them with that speed. They can't wait for the turn of the crank from the old software beast, or oh gosh, there are some chips or hardware involved in that? Open Source, I want to be able to contribute to the code, work on the code, ship it, move faster. >> And the other thing that came up yesterday, I want to get your thoughts and reaction to, is do you have a fashion model going on here? Never fight fashion, as we say, a good marketer would say. You have CNCF is very fashionable right now. But there's blogging and tackling projects that have been around for a while, like the networking piece. These are stable, great projects. They just don't have the pomp and circumstance as CNCF have. So, the balance of being trendy is an issue now for these Open Source communities. No one wants to work on a project that's boring but the relevance is important. So how do you react to that, Stu, because this is now a dynamic, it's kind of been there for a while, but now with the plethora of projects out there, are you nervous that fashion, fashionable trendy projects like CNCF, might suck all the option out of the governance? >> No, John, I mean, from a press and a marketing standpoint they get the attention, but I think that the stats really prove out, there's so many projects out there. Everybody's contributing to a lot of them, but it is something the developers should think about. We did an interview of a company, I remember years back, said, "how do you get the best people "and how do they choose what to do?" "Oh, whatever they feel is good." And I'm like, well, come on, you got to put a little bit of a business guidance on that to make sure what's going to help your business, what's going to help your career, if you're an individual contributing to this. There are plenty of options out there, both for starting new things as well as contributing to the big ones out there. And I liked what I was hearing from the Linux Foundation as to how they're going to give some governance to companies as to the health, that whole CHAOSS that they rolled out, talk about the health and the circular maintenance of things out there, but you know, so much activity. Kubernetes by no means is taking all of the attention, it just happens to be the current hotness. >> Well, there's some key under-the-hood details that are being worked on, that's the exciting part. Linux is a standard, it is powering. Most of the apps that are written are essential Linux apps if you look at the OS underneath. And again, the apps, again, the DevOps mindset is here, and now it's scaling and things like Serverless are going to be more greatness for developers, certainly as companies like Google, IBM, and others come in with real code and share and collaborate, a lot of people can participate in the greatness of Open Source, and I think that's, the future is bright for Linux and the Open Source Summit community. Stu, day two continues, live coverage here in Los Angeles. This is theCUBE, I'm John Furrier, Stu Miniman. Coverage of the Open Source Summit North America, in Los Angeles. We'll be right back with more after this short break. (upbeat music)

prepare for the extraction point we've been briefed on all the important stories and events in the world of emerging information now it's time to extract the data and turn it into action live from the silicon angle studios in the heart of Silicon Valley this is extraction point with John furrier okay we're live back in the palo alto studios i'm john furrier for the extraction point we extract the signal from the noise and my special guest today i'm excited to have here is Paul Martino who is the founder of aggregate knowledge and also storied entrepreneur in Silicon Valley who now lives in Philly with his family comes out here Paul is known for among other things being a great entrepreneur tech geek loves tech loves to build build startups started one of the first social networks with Mark Pincus called tribe started his own company funded by Kleiner Perkins with his partner Chris law called aggregate knowledge which is booming and doing great and now more famous for being the first round investor in zynga company that is exploding with revenue as Kleiner Perkins said is the of all their portfolio comes in the history more than Google's made more money faster than anybody Paul Martino welcome to the extraction point great to see you John as always awesome to see you first I got to start with your now I forgot to mention that you're actually running a venture firm so in addition to being famous with Zynga you're running bullpen capital so first give the folks out there an update and first confirm or deny you were in the first round of Zynga or not yes the the first round of Zynga there were several institutional investors and several individual investors Morocco me Reid Hoffman were individual investors Avalon Union Square accelerator ventures and foundry where the institutional investors in that first round Peter was Peter Thiel yeah Peter was also an individual investor in the first round so that's officially the first round investors of Zynga we have clarified that and that is now hot on the books but now you're you've been successfully founded aggregate knowledge you know have a CEO running that what's the update with aggregate knowledge yeah so great guy runs that company as a guy you need to meet and have on this show Dave jakubowski aggregate knowledge really went in a direction where all of the focus was on providing data and analytics to the major ad agencies and John John Nelson who started organic one of the first agencies is now the CEO of Omnicom digital joined the board and I said look we got to get a guy who's an ad heavy in here and jakubowski was previously the GM of microsoft adcenter and had a senior position at specific media and we brought him in and he's just been kickin butt our greek knowledge has really really made a significant significant contribution in the area of data and analytics for these major agencies and he was very able to bring in a crew of people know exactly how to run that business so you're a big fan of big data then mm-hmm oh yeah we just had a big special yesterday on Big Data mentioned about it so that's cool we're going to get into a lobbyist I was just kind of get the small talk out of the way here your current role is the founder of bullpen capital right so bullpen to me I'm a baseball not I love baseball bullpen means you go the bullpen for relief right yep thank God close the game out hopefully or mid-innings relief so tell us about what bullpen is it's a special fund as I know from reading talk to you to target an expansion of this new seed and explosive new funding environment Bryce plain force right I'll tell you how we got the name at the end too so here's what happened I've been investing with a lot of the so-called super angels and that's kind of a misnomer because they really are actually in some cases actual small venture firms to I've been investing with a lot of them since they got off the ground Josh Kopelman from first round is one of the first investors in aggregate knowledge mike maples was an early advisor to the company I've known Jeff claw be a who run soft tech since he was at Reuters and with the late 90s and so I've worked with these guys done a lot of investing and we were me and my buddies Duncan Davidson rich Melman were sitting around over summer of 09 doing a little bit data analysis right another big data assignment we realized that as more and more these seed funds got created they were creating an inventory of companies that weren't quite ready to go to the traditional venture guy but we're also difficult to bridge from just the seed guys because the see guys at that time didn't have really big funds so wait a minute you've got some really good companies here is to clarify the for the folks out there seed funds don't traditionally have follow-on big funds like a VC firm right that's what you're referring to yeah they tend not to have as bigger reserve so if a big fun writes you a five-million-dollar check and you stub your toe you can probably get some more money to get through the hardships but a lot of the the new super angel funds or smaller funds and you get a five hundred thousand dollar check and if you need another five hundred thousand dollars it can frequently be very difficult because they make so many investments with smaller reserves yeah and so you've got dave McClure clavey a maples first round capital true ventures made the first round truevision more traditional VC then say dave McClure and mike maples and claw VA they're out doing some really good work out their funding really good company spending a lot of time I know I've seen them working their butt off yeah they need some air support right they need some cover the little bullpen is that that's you come in and say hey for your stars they're going to rise up yep and so that's exactly right so what happens is here's what the analysis we did turned out of their portfolio thirty percent of their portfolios in aggregate quickly are really exciting companies you know and they quickly go up to a venture auction and the guys and sandhill rotor excited about it about twenty percent of their deals you know that they don't like too much it's kind of just floating there yeah that you know the entrepreneur wasn't a fit that team didn't execute that left fifty percent of their deals in the middle which they kind of were too early to tell as Mike maple sometimes says they were in an extended learning and discovery phase they hadn't quite figured out what their models yeah and this de pivoting stuff's going on right now the Marcus changes turbulence so these guys are right and so you look you look at some examples and you go well wait a minute for every zynga that goes up into the right immediately go look at the stories of chegg and modcloth and etsy and quite frankly the in-between round on twitter and for everyone Zynga that you find that just hits it out of the park the right way there were four to five companies that went through that hard intermediate round that it was difficult in the environment where you have only a potentially thinly capitalized seed fund in front of you go get through that difficult point I said guys you need a bull pen and way we came up with the name is I'm involved in a deal with Chad Durbin who used to pitch for the Phillies and now as a relief pitcher for the cleveland indians and he was in our office and we were talking about this idea and Chad said yeah it's kind of like you're building a bullpen for the seed guys I'm like that's exactly right that's the name we got to go with and so fortunately I was involved in in this company called showcase you which is actually cool cited suppose for recruiting for college scholarships for a collegiate athletes right you're a high school student you throw 80 miles an hour left hand it and you're in 10th grade how do you figure out where the right scholarships are so Durbin and some of the Phillies where the original investors in this company called showcase you it's actually a cool company as the combine work out online basically fries for the high school kids and because the high school kids sometimes are in tough geographies to get to you're in you're in a small rural area in Nebraska how do they find out that you're the guy who can throw 89 miles an hour great so I mean this VC market so basically you're referring to with bullpen right now is an innie and you've been in our sprayer so you live through classic you know classic financing your last company financed by kleiner perkins and a tribe i forget who financed tribe yet Mayfield was the lead investor may feel again another traditional VC firm all tier 1 VCS although may feel people are you now is slipped a little bit that's some of their key partners who have slipped away but they've all moved on what you're really referring to is there's a new dynamic of entrepreneurship going on now we're now there are some break outcomes that just need a little bit more time to mature in the old model they just be kind of closed down the VC guy would be on the Bora has just a pain in the ass and you know really not growing and do another round it's they get kind of lazy in a way if they got 10 10 boards are on so with the super angels and the fact that does take a lot of cash to start a company you've got more deals getting done so the the Y Combinator the Dave McClure's and chef claw va's in the mike maples and sometimes SiliconANGLE labs which we're doing here is telling you about right we're funding companies the more [ __ ] is funded a better will you come in as you keep them alive longer just wreck the pivot possibly that's right and so what happens is right now the venture industry is being disrupted the same way the venture industry has funded companies that have rupted other industries they are being disrupted in the exact same way and the disruption happened from below as always happens it started in seed stage now in order for the disruption to go all the way through there need to be companies that come after seed stage investors that have the same philosophy and mentality pro entrepreneur easy terms operating people who get their hands dirty to get deals done you need that in the B stage and in the sea stage and here's what our prediction is John our prediction is a few years from now there'll be a company that comes after bullpen that does series c and series d financing or mezzanine financing but the same philosophy is bullpen and then DST s at the end of that chain and you can imagine building companies that go all the way to liquidity that you got money from maples first bullpen second this unnamed company third and you went quasi-public with DST and you've bypassed the entire venture scheme entirely and the entire institutional public markets complete liquidity wealth creation companies creating jobs I mean this is new paradigm I mean this isn't amazing I mean this is a potentially amazing point in the history of us finance the idea that you could go two billion dollar outcomes by passing not only the public markets on the back side but the traditional venture ecosystem on the front side I mean that is a disruption if ever there was one amen I mean hi and with you a hundred percent the other some people who will argue regulation is if market forces first of all I'm a big believer in market forces so I think what you're doing is clearly identifying an opportunity that dynamics are all lying lining up entrepreneurs are validating it and so but the questions are regulations I mean first of all I'm anti-regulation but as you start to get to that liquidity and some are arguing I even wrote a blog post about saying hey you know basically Facebook's public merry go buddy what do you say to those guys this is the change in the history of this financial asustor we want the government regulating this yeah so my co-founder of both i started bullpen with two really good guys Duncan Davison who was the founder covad was advantage point for years asking them to buy government regulation would go bad i mean what happened then because of the I lack warsi like Wars but only that the some extent covet doesn't exist unless the telco 1994 happens through in some ways a creation of the government to good point it's social right but but think about it the arbitrariness of government as opposed to a well-thought-out centralized plan so anyway so Duncan sometimes uses that phrase you know he talks a lot about the way in which the government you know that the worst thing you can ever hear is I'm with the government I'm here to help right i mean that's about the way it goes but his point around the the the new quasi public markets is money we'll find a way yeah and when sarbanes-oxley happens and it's tough to go public and you're a CEO like Pincus who's running one of the great all-time companies in Silicon Valley at Zynga he says you know going public is not an entrance is not an exit it's an entrance that's that's this quote what why would I why do I need that headache I mean I was just talking with Charles beeler who sold for the hell dorado he sold to compel in one of his investments to dell for over a billion dollars and and 3 para nother firm he wasn't on that one that was sold to HP during storage wars he's talking about the lawsuits literally this shakedown of immediately filed lawsuits you know you could have got more money so this is this public markets brutal no doubt no doubt i think what you're doing is a revolution I'm all excited about this new environment again anything with his liquidity wealth creation with the engine of innovation can be powered that's fantastic look back the startups okay get back to where you're playing yeah the history of Silicon Valley was built on the notion of value add some have said over the past 10 years venture capital has not been truly value add and some were arguing value subtract and then just money so what you're talking about here is getting in and helping me stay alive what's the value added side of the equation mean I know that a lot of these folks like like like ourselves here it's looking angle McClure Xavier and maples and true ventures they roll their sleeves up first round capital right before we can only provide so much it kind of expands right you guys are filling in the capital market side right how are you guys helping out on the value add because a lot of those companies may be the next Twitter right you've got a bridge to finance that's right allow them to do the pivot or get the creative energy to grow and they hit that market if they hit that hit it going vertical you got it kind of sometimes nurture it you guys have a strategy for that talk about the so let me let me give you my perspective on that so I think 10 years ago when you're starting a company the name of the venture firm was more important than potentially the partner on your board ten years later the name of the firm matters much less and it's the name of the partner and it's the operating experience that that partner partner brought to bear and you go talk to the 24 year old entrepreneur verse the 34 year old entrepreneur the 24 entrepreneur 24 year old entrepreneur wants a guy like you or a guy like me on his board he wants have been there done that started a company was a CEO exited it got fired hired people fired other people scar tissue scars knowledge experience exactly and if a good friend of mine who's in the traditional business I'll leave his name out of it he sometimes says the following phrase the era of the gentleman VC is over and what he means by the era of the gentleman VC is over is you know if your background is you were a junior associate who came in with a finance degree in an MBA and it never started a company you're not going to get picked by the entrepreneur anymore in 10 years from now almost everyone in the business is going to have a resume that looks more like a Cristal Paul Martino a mark pincus that you name all the people who we've started our companies with if there's a lot more hochberg with track record certainly with with the kind of big companies in the valley just in our generation yet started with netscape google paypal right now i want to see facebook is and then now's inga either the ecosystem is just entered intertwined I mean for every failure that spawns more success right so that's right that's a Silicon Valley way yeah well a tribe was tribe was a perfect example of a successful failure tribe was not a successful outcome but it was in many ways a very successful way to actually pioneer what became social networking you know investments got made into Facebook as a result of that Zynga in aggregate knowledge were both the outcrops of what was learned to some extent the original business case of Zynga was remarkably simple there is a ton of time being spent on social networks and after you get done finding your buddies and looking at photos what do you do and Pincus is original vision to some extent was let's have games to play and that insight doesn't happen that way unless you don't do tribe and go into the trenches and get the scars on your back and your in your your second venture of our adventure right at the tribe was aggregate knowledge was similar concept people are connected I mean you got to be excited though I mean you know you were involved in tribes very early on all the stuff that you dealt with activity streams newsfeed connections the social science you know the one that one of the nicest pieces of validation of this recently was over in q4 of 2010 seven of the patents that me Chris law Elliot low and Brian Waller wrote got issued now they're all owned by Cisco Cisco bought tribe in the end they bought the assets in the and the patent filings but there are patent filings that go back to 2002 on the corner stones and hallmarks of what social networking really is that we wrote back then that have now issued order granted or sitting in the cisco portfolio and well that's kind of like a consolation prize and that there wasn't a big outcome for tribe it is very validating to see that those original claims on really cutting-edge stuff have been had been issued and I'm excited about that you should be proud i'm proud to know your great guy you have great integrity you're going to do well as a venture capitalist i think you people will trust you and you're fair and there's two types of people in this world people who help people people who screw people so you know you really on one side of the other you're you're not in between you're truly on the on the good side I really enjoy you know having chatting with you but let's talk about entrepreneurship from that perspective about patents you know I'm try was an outcome that we all can relate to the peplum with Facebook of what Zuckerberg and and those guys are doing over there that's entrepreneurship so talk to the entrepreneurs out there yeah hey you know what you do some good work it all comes back to you talk about the the Karma of entrepreneurship a failure is not a bad thing it's kind of a punch line these days I'll failures are stepping stone to the next thing but talk about your experience and lets you and i talk about how to deal with faith for those first-time entrepreneurs out there in their 20s what just give them a sense of how to approach their venture and if it fails or succeeds what advice would you give them yeah well like winning and losing is important part of the game I mean certain companies are going to be successful in certain ones art and if you go and start ten unsuccessful companies maybe this isn't exactly the business for you but that said how you the game is important as well and if you're a high integrity guy who gets good investors and you make quality decisions and let's say the market wasn't a fit you're going to get the money the second time because people said you know I work with that guy that guy really did a good job you know they never got it quite right but this is a guy learn the right lessons so when I'm coaching a first-time CEO and i'm the CEO coach of a couple guys now you know i'm looking for someone who's sitting there going hey i not only want to do this to win and be successful but i want to learn i I want to do this better than no one no one walks in and says I learn from my failure I hope I'm successful I mean you let it go and say hey I'm gonna be successful I want to win failure is not an option but failure happens right i mean you know it's bad breaks that mean but but here is the key less I tell this to all of the entrepreneurs I work with you will not be successful if you're making mistakes that were made by those before you if you make novel mistakes you're in good company right and so only ever make a novel mistake I made a good example this is one claw and I started Chris law and I started aggregate knowledge aggregate knowledge was the original business model was around recommendations and there were dead bodies in front of us there was net perceptions there was fire fly and she was in the office this morning with Yazdi one of the founders of [ __ ] cast with it man yeah so predictive analytics residi what did we do we went out and we I flew out and met John riedle University of Minnesota who was the founder of net perceptions I dug up yes d i got these guys on my advisory board and while aggregate knowledge was not successful in the recommendation business and pivoted into the data management thing we made novel mistakes we did not repeat the mistakes of met perceptions and firefly and so i think that's an important important lesson to an entrepreneur if you're going into an area that has dead bodies in front of you you better research them you better know who they are you better know what happened and you better make sure that if you screw it up you at least screw it up in a way which none of us could have predicted yeah that's the only way you're going to get a hall pass on that well let's talk about talk about some of the hot Renisha of activity saw so you're in that sector where you're feeding the seed the super angels in the first rounds early stage guys and it's a good fit what about some of the philosophies on like the firms out there there's of this to this two philosophies I just taught us to an entrepreneur here you met on the way out a street speaker text and there at seven you know under a million dollars in financing hmm series a yeah and then you got in the news yesterday color 41 million dollars building to win magnin flipboard a hundred million dollars i got this is these guys that we know i mean there are yep our generation and a little bit around the same time and certainly they have pedigree so remember the old days the arms race mentality right when the sector at all costs right that's kind of what's going on here i mean some of the command that kind of money there's actually an auction going on what do you make of that I mean bubble is an arms race so so rich Melman inside a bullpen de tu fascinating analysis he looked at the full portfolio of 28 took about 20 of the best super angels by the way the super angles are all different some are micro vc summer buying options etc so so first off super angel is a weird word but it's everybody from Union Square and foundry on one side first round and flooding but any take the top 20 or so of these guys and look at their portfolios what's amazing about their portfolios is the unlike 10 and 20 years ago in prior tech bubbles there are not 20 companies doing the same thing when you categorize them yeah ten percent are in ad tech ten percent our direct-to-consumer consider but like forty percent are one-offs that is this is I think one of the first times in the history of venture that forty percent of the deal flow is a one-off unique business idea that there aren't 30 guys going to do and I think that the importance of that to what happens in this next stage of the tech boom we don't know what that means yet because back in the day well we need to just we're venture firm we need to disk drive company okay so your venture firm you've got your disk drive companies and I'll 20 venture friend knows if drive out and created the herd mentality everyone talks about with venture yep mean I was an opponent on a talk on here in the cube and I don't think I actually put in a blog post but I called the era of entrepreneurship like with open sores and low cost of entry with cloud computing and now mobility the manure of innovation where you know in the manure that's being out in the mark place mushrooms are growing out of it right and these you don't know what's going to be all look the same in a way so how do you tell the good ones from the bad ones so it's hard right so you have a lot of one you have a lot more activity hence angel list hence the super in rice so so the economics and the deal flow are all there the question is how do you get them from being just a one-off looked good on paper flame out the reality yeah well look in my opinion seed stage investing is about investing in people and I think when big firms trying to seed stage investing there's an impedance mismatch a lot of times because they want more evidence they want to know did the market work to the management then this is this is an early stage venture and am I going to want to go in a foxhole with this person and in many ways the good super angels are instinctive investors who are betting on people that they want to be in the foxhole with and yeah did they do it before do they know how to hire people is the market reasonably interesting but guess what they're probably gonna pivot three times so wait a minute at the end of the day you got to invest in people later stage venture is not you can look at discounted cash flows you can look at mezzanine financing you can do traditional measures but if you're going to invest in two people who have a prototype and need five hundred thousand dollars you're investing in people at that point what do you think about the OC angel is I'm a big fan of and recently was added thanks to maybe out there but even though i'm not i don't really co-invest with anyone else other than myself maybe you guys would bullpen but but if that's a phenomenon you don't have angel list which is opening up doors for deal flow companies are getting funded navales getting yeah a ton of activity nivea doing great job with venture hacks i get y combinator which I called the community college of startups they bring in like they open the door and I mean that an actually good way don't mean that negatively I mean they're giving access to entrepreneurs that never had access to the market right and now you have Paul Graham kind of giving the halo effect or thrown the holy water on certain stars and they get magically funded but yesterday at an event and they're they're packed right I've heard from VC saying I'm not invited because I didn't wasn't part of the original investment class so it seems that Y comma day is getting full yeah so do you see that you agree is there will be an over lo y combinator you know kind of like I've TED Conference has you know Ted they'll be you know y combinator Boston little franchises will be like barcamp for sure I mean look and look at techstars they franchise they'd I was over there with Dave Tisch in New York there's TechStars New York after those TechStars older in techstars seattle there is no doubt in my mind that right now there is an over investment in the seed stage meaning that there is a little bit of a seed bubble going on that's not necessarily bad though because in terms of raw dollars there's not a bubble yet Rory who's over at rafi it smells like a bubble it looks like a bubble but when you look at the mechanic when you look at the actual total dollars it's not a bubble rory who has a hinge recent Horowitz been said that that it's a boom not a bubble yeah so don't be confused it looks like bubbles and booms kind of look together the same right I actually I'm not quite sure I had the exact data right but here's the quick summary if you take a look at venture capital investment as a percent of GDP historically it's been something like point one percent of GDP in the bubble back in 99 it went to one percent something like it went 10x higher right now we're still at point one percent but since it's very much centered around the seed stage investing you see this frothiness in the sea but until that number goes from point 1 percent of GDP back up to one percent there's no real bubble because the tonnage of money hasn't come in yet and so so it's starting but this is what a tech boom feels like the early stages are excitement and lots of ideas and lots of flowers blooming and then the big money comes in because John I'll bet you're your brother and your sister and your mom haven't invested in a tech startup back in 99 video there's no public market that supports seven in a way that's a good and bad star basement yeah there's no fraud going on and most of the companies that are out there whether their lifestyle business or seed or bullpen funded are actually generating income the entrepreneur he has any earlier Mike was saying that he could a business deal so people are kind of like saw the old bubble and said shoot I don't want to do that again I gotta have at least revenue right and so companies didn't seem to start out with cash so you know that because you invested it but you know Pincus was getting some cash flow in the door from day one that's right that company was company was profitable the first day it started basically so talk about you know so I'm with Paul Martino by the way with bullpen capital entrepreneur wrote the patents on social networking which he sold the cisco when they sold the company now with bullpen capital huge dynamic you're a company out there this is exactly the positive dynamic you want to see because mainly you know dave mcclure jeff clavier mike maples have been kind of getting their butts handed to them in the press about super angels not having the juice to kind of go anywhere and it's been kind of a negative press there so you know this is the kind of void that's been filled by you guys to show the market that look at this there's a road map here so even though that the McClure's and clubs don't have big funds that there's a path to follow on financing so that the vc's can't shut them down and i've heard some pc say that so a lot of traditional venture guys would like to say that you know this little disruption we nipped it in the butt and it stopped after the seed stage but that's not the history of disruptions the history of disruptions are they start from the bottom then they get ecosystem support and then they grow and they disrupt the incumbents and I think we're halfway there so so the Angel gate thing that Arrington reported on was interesting because you know essentially what happened there it was a lot of him fighting Ron Conway I was not happy you can't be happy about competition I mean this is competition that increases prices right so you know in the short term prices have been inflated on valuations true or false that's true but but but I think I think the whole way angel gate was reported was absurd the most Pro entrepreneurial venture people perhaps in the history of the business are the guys who were supposedly at those tables I mean mike maples Jeff claw VA josh cop and Ron Conway fired his guy that was there I I understand suppose again suppose a key are right these are the most Pro entrepreneurial venture guys in the history of the business so I think that turned into something that it never was yeah well I mean that's the thing you know good for content producers who want page views I got to create some drama and you know as you know SiliconANGLE doesn't have any banner ads on our site quick plug for us we are motivated by content not page views so thanks for coming in today no but seriously I mean there's a there's a black cloud over the super angels has been since Angel gate I've heard privately from VCS that super angels it's been kind of a scuttlebutt they're misaligned just rumors I completely overblown and you know their business model threatens the incumbents and you know someone needed someone needed a piece of fodder to start a you know start a techcrunch discussion right there's no doubt that the market is need in need of a new ecosystem for the early stage because individual angels traditionally were wealthy individuals but now you have people with more experience like yourselves and entrepreneurs from google and facebook etc coming out and doing some things okay so next topic more on a personal kind of professional note k last final question is I know you got to run appreciate your time you're a technologist a lot of folks don't know that you're hardcore computer science guy and our model southern angles computer science meet social science right in your wheelhouse so with that just kind of final parting question what gets you excited technically right now I mean I'll see you have roots in both comps I and social Iran Zynga's early investor roster you got a bullpen capital you're looking at a lot of deals outside of that you as a computer scientist geek mm-hmm what gets you jazz what do you see in the horizon that's not yet on the mega trend roster that kind of you can't put your finger on it truly we might really get a good feeling well so I think you'll be disappointed with this answer because I think it's now cross the chasm to start being one of those mega trends it's called consumerization of enterprise and that's now the buzz word for it but what is it really mean and why do I think it's for real look you've got cool self-service applications for everything you can go do home banking by logging into a portal you can go to an ATM you can go do these things but you know go bring a new laptop into your big stodgy fortune 500 company and you know it's like getting a rectal exam right you know we got to install this we got to give you this private key yet that's TSA it writes like going through TSA exact idea that IT inside of big fortune 500 companies is going to stop being this gatekeeper to new technology I think look how long do you think it'll be until pick your favorite fortune 500 company the IT people know how to deal with the ipad 2 but how many people bought an ipad 2 into the off already everyone and so this to me is going to be the big next deck the next decade are going to be self service offerings for the enterprise getting around a very frustrating gatekeepers inside of you know the IT department etc and that's going to lead to an awesome boom of everything from security to auditing to compliance etc that's the convergence question Paul Martino my friend entrepreneur great guy venture capitals now on the good side helping the seed Super Angel micro VCS great to have you consumerization of IT that hits the cloud mobile social it's everything so that I was buzzword compliant on that great job great to have you know you're busy got to have you in again thanks so much for time that's a wrap thank you very much great thank you John