>> 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)

(upbeat music) >> Commentator: From our studios in the heart of Silicon Valley, Palo Alto, California, this is a Cube conversation. >> Welcome to this special Cube conversation here in Palo Alto, California. I'm John Furrier, host of the Cube. We're here with Fletcher Previn, who's the CIO of IBM, part of a series we're calling a new brand of tech leaders, where we profile leaders in technology and business, where there's innovation and a changing of the guard of approaches and results. Fletcher, thanks for joining me today. >> Thanks for having me. >> So we were talking before you came on camera, you have an interesting background. You kind of went to an arts school, got into entertainment as an intern, Conan O'Brien... >> David Letterman. >> David Letterman. You were fast track to be a comedian and get into the business of entertainment, (laughter) and you ended up as the CIO. How does that happen? Tell us the story. >> The comedy's better in tech. (laughter) >> These days, certainly, watching the Senate hearings, it's phenomenal. >> Well, yeah. As you said, I thought I very well might go into entertainment, that's kind of more of the family business. And I spent a lot of time on movie sets and worked as a production assistant on a couple movies, and then was an intern at the David Letterman Show and Conon during college. But I did always have this strong other thread of really loving technology and being drawn into it. First family computer was a Commodore 64, but my first real computer for me was the original Mac 128K. And I knew something was awry when I was working at the Letterman Show, I was kind of more interested in the phone system than who the guest that night was. And so, when I graduated, I just accepted it. Why keep fighting this? I'm going to go out to the West coast and start my career in tech. >> That's interesting, you know you always gravitate towards what your affinity is, and I think a lot of people look at today's work environment as an environment where there's so many shifts and new kind of waves. To me, we've always said on theCube, you know, this wave that we're living on, tech wave, is kind of a combination of main frame, mini computers, localary networks and PCs all kind of rolled up in one. Because there's so many different touchpoints that's changing things. You know, you don't need to be a coder to be successful in cyber security, you can be a policy person. Lot of societal changes with self-driving cars, which side of the street do they drive on? All these new things are happening. And so it's really putting the pressure on digital, and the notion of data, IT has become a central part of it. You're the CIO at IBM, how do you look at that world? Because now, being a technologist, we'll get to the idea of it in a minute, but as a technologist, as someone who's the Chief Information Officer, when you look at the world today, you look at the wave we're on, what does that wave of technology mean to you? >> Yeah, well I think as you said, there is no part of our modern life that is not touched, and hopefully augmented in some way, by technology. And so, you know, that's the answer to the question why am I at IBM. Because the kinds of businesses that IBM is involved in, the kinds of enabling technology that it provides, really underlies a lot of the critical infrastructure and systems for our modern way of life. And so, being able to be at a company that has a narrative position in what our collective future looks like is what drives me. >> Yeah, a lot of the application developers, you guys have a huge portfolio of applications. You got cloud computer, you got on-premise, you got IOT, a lot of things, AI changing. You're changing the nature of application development, but also the role of data. At IBM as the CIO, what is your strategy in looking at all these changes? And how do you implement it with IBM? What is specifically your strategy? >> Well, certainly our strategy is there will be no part of the IT portfolio that is not augmented with IBM technology, and in particular AI. And an AI strategy is a data strategy, for us to be able to really collect, organize, harness the power of that data and then leverage it in innovative ways to be a more effective and efficient business. More broadly though, in terms of what is my strategy to deliver IT services to a huge company of IT professionals, it's to lead with design. And there's a lot underneath that, but one of the first changes that I made when I became CIO of IBM was adding, as a direct report to myself, a person responsible for design and user experience. And IBM's got a huge focus on design thinking and leading with the user experience, but for us to be successful, we got to create an environment where successful, excuse me, where talented people want to work. And that requires us to have empathy, and engineer from the user in instead of IT out. >> And making service is a big part, because we've got consumption, people consuming IT. >> Yeah, exactly. The barrier to entry for people to make decisions about what they use or don't use is very different. I think people coming to the business 10 years ago, very different set of expectations, even 5 or 3 years ago. And so, it's got to be carrot, it can't be stick. People just won't do something because you tell them to do it, they have to perceive that this is making their work life better in some way. >> Culture's a huge thing, I want to get your thoughts on engineering for excellence, this is something that you believe in. What's your view on that? What does that mean? What does engineering for excellence mean for you as CIO? >> Yeah, well we spend a lot of time thinking of IT as the driver of culture change. And when people say we're a culture that values engineering excellence, what does that really mean? And it means that we recognize and reward people who are really passionate about what they do for a living, deep subject matter experts in their field. You know, I sometimes get asked, what are you looking for when you're hiring people? And I'm looking to hire people who are kind, passionate about what they do for a living, and believe in our purpose as a company. And if we surround ourselves with those kind of people, we will be successful in whatever kind of problem we happen to be trying to solve at that moment. >> What are some of the guiding principles in an organization that's engineered for excellence? What are some of the guiding principles that you hire and push forth through your organization? >> Yeah, well as I said, we are trying to attract and retain, and ultimately reward the people who are deeply passionate about what they do and believe in our collective purpose. And so I think the era of the generalist is probably a bygone era. I'm looking to attract people that are doing in their spare time and in their hobbies and at home the same thing that we're paying them to do at work, because they love it and they feel fulfilled by it. >> And the roles are changing too. Talk about the skill gap, this is a big talk track we hear at every event we go to and exec we talk to. The new brand of tech leaders have to address the skill gap because there's more job openings in jobs that don't have a degree requirement. Meaning, the job doesn't have a certificate or a diploma because it's new. Whether it's cyber security, or data science, new kinds of roles and the skill gaps there. Talk about that, that challenge, that opportunity. >> Yeah, well these new and emerging fields, AI, blockchain, cloud, or otherwise, you're right. A lot of those are new, and there are not well established four-year degrees around those kinds of professions. And so, IBM is very heavily involved in what we call the P Tech, or the Pathway to Technology Program, where people can have a successful career in technology without having a traditional four-year college degree. But more broadly, yeah, there is a gap. A gap between the demand and the supply for people in these fields, and so the best protection all of us have against obsolescence is continuous upscaling and education. And that happens organically if you're passionate about what you do, because you're eating, breathing and sleeping the area that you work in. >> Yeah, and sometimes learning on the job too is key, and getting content on the internet, people can self-learn and apply that. Talk about how your organization's structured for learning. How do you retain the best talent? What are some of the strategies you deploy to keep people motivated, keep them informed, and keep them engaged with a good assignment? >> Yeah, well that is a challenge in any large organization, and IBM is 350,000 plus people in 170 countries. And so the era of us being able to get everybody together in a town hall meeting is long gone. And so, how we communicate and get everybody on the same page around mission alignment, what is our strategy, and what skills do you need, and how do you stay informed and educated. That's an ongoing challenge. I think, ultimately, we try to attract people with our purpose as a company. It's an employer of purpose, the kinds of work IBM's involved in attracts people that are mission driven. And then, there is a tremendous focus on providing distance based self-paced learning, online learning, in person learning, badgen programs, the P Tech Program that I mentioned. And to make sure that a person who is motivated and wants to grow their skills, that they have all the vehicles to do that. But I think the other thing I spend a lot of time focused on is, does everybody in this organization have a good understanding of what our purpose as a company is, and how what they do contributes to that purpose, and can they map back really clearly I'm not just a widget in a machine doing something and I have no idea what the impact of it is. I see that what I'm doing contributes to our collective success. >> People want to work for a mission driven company, that's a new data point we've been seeing. >> Fletcher: Yes. >> Talk about the outcome of focus. You know, you hear digital transformation being kicked around, I think it's happening now more than ever, obviously been hyped up. But now you're starting to see companies really digging in. You guys are going through a digital transformation over many years. You supply technology for companies that are transforming digitally. The notion of business outcomes becomes a big part of that. How have you evolved your organization, from an outcome standpoint, that's new and different from the old ways? Can you give an example and talk about that? Old way of doing things and the new way of doing things. How do you talk about technology for business outcomes in a new way? >> Well, ultimately it's a business problem that you're solving. And so there has to be a business driver behind any project that we engage in. And having good discipline around... organizations tend to die of indigestion, not starvation, and getting really disciplined about what we say no to, in some cases is more important than what we agree to do. And it's much harder to stop work than it is to start work in a large organization. And so we've really leveraged Agile as a new way of working to say, "We have a well-defined methodology for "one funnel of work, that gets prioritized "in partnership with the business in a transparent way." where we say, "You submit this many units of demand, "we have this much unit of supply, let's go through "the story definitions, backlog grooming, "future presentations, retrospectives, the mechanics "of working in an Agile way, to be really disciplined "about everyone's on the same page about what "we are going to do and what we're not going to do." >> Yeah, that's a great point. We hear this all the time. Certainly, it's looking valid here, where I'm located. The notion of Agile, fail fast, the lean startup. You know, I never bought into the fail fast thing. No one wants to fail, but in the spirit of learning Agile, failure is a part of the process. So getting to yes is what people want to get to, but you can't say yes to everything. IT has failed in that area. You can't say yes to everything. So you got to say no. >> Yep. >> You got to also get to what you don't want to do. So knowing what is not the right way to go is where Agile kicks in. So Agile, you want to get to a fail point and know what not to do, at the same time you got to say no to all the requests that you possibly could do. >> Yes. >> Is kind of the formula. Talk about that dynamic. Because this is where Agile translates or DevOps translates into business. It's the same kind of concept applied to organizations, process, and people. >> Yeah, so I think in terms of how do we have good discipline around what we do and don't do. It's very important that people understand what their role in the company is and what their lane is and what their mission is. And if we say no to something, it's not an indictment that that piece of work is not valuable. It just may not be something that is aligned to our mission or something that we're supposed to do. And I think those things can get blurry if you don't have really well defined Agile frameworks and ways of working and everybody on the same page. And so all kinds of things can sound like a good idea potentially, but if it's ultimately not really what we're supposed to be doing, that's what creates friction, right? >> I'd love to get your thoughts just as a person in tech who's got a lot of responsibility in IBM. But you talk about IBM, from an IBM capacity or as a person, but we have a lot of conversations here in the Cube, from Netflix to IBM, to practitioners in the field around the role of data. [Fletcher] Mhmm. Everyone wants to be data driven, so there's no debate there. Data driven is a good approach to take on things. >> Fletcher: Yes. >> But how you look at data depends on what you're lookin' at. You can correlate data and you've got causation. So a lot of conversation's been around don't get too caught up in the data for data's sake. Because if you look at just correlation, you might not know what's causing something. So most data scientists love correlation because it's numbers, they're there, you can look at all those correlations, but not understand the cause of something. Can you talk about how you view this? Because this has become an important part of decision making with data. >> Yeah, for sure. And AI very closely related to having a good data and data governance and taxonomy strategy. To really be able to harness the insights from all that data, you got to have a good data governance strategy behind it. But behind every piece of data is a business process. And so ultimately, being able to really map back and understand which business processes are generating this data is sort of the methodology for trying to put your arms around all the massive amounts of data that are being collected. And I think our old strategy was, we'll have a data lake and we'll just dump everything into it. The advent of AI sort of requires a different data strategy and says we need to have a good governance process around this and have a data platform, not a data lake. That we can then build automation against, run AI against it, and be a business that makes better, more informed decisions based on that data, and then help our customers do the same thing. >> And this has certainly come up a lot in AI around bias and contextual relevance, I think it's a big part of what's behind the data. >> Yeah, right. And you need to have explainability and transparency into the recommendations that AI is making. You know, if it's a black box, that's an issue. If AI came back and told you, "I think you should make "your product more expensive." Your first question would be why? And if you can't answer that... And so, AI's autonomous driving is a good example of that. Where you put a human being in the seat and he or she drives the car, and the system compares the inputs that they would make versus what the human is doing, and can explain why they had variances. But if it's just a complete mystery, that's not going to work. >> Yeah, the contextual why is a great question. I want to get your thoughts on security. [Fletcher] Mhmm. But you had made a comment earlier around the general purpose, IT person is kind of a thing of the past. Meaning that specialism and or variety and diversity of skills are always going to be out there. >> Fletcher: Yeah. >> With security, no one company has the same security makeup. Because their posture and or their organization structures are different because their organization mission is different. No one company is the same. >> Right. >> It's kind of like we as individuals, our DNA, everyone's different. So that means that security's not always the same in every company. As the CIO of IBM, you guys are a large multi-national, you're obviously huge. >> Other companies might have different approaches. How do you see security playing out? Because in some cases, CIOs manage security, in some cases the CSO is bolted out separately. >> Fletcher: Right. >> Either way, we know security's a board issue, as is IT. What's your view on security and the role of security within an organization. >> Security's a huge focus for us, it consumes a large amount of my time. And as much as we worry about our data, we really worry about customer data. And the kinds of threats that we're seeing are evolving rapidly, and as an industry statement I would say the advantage continues to go to bad guys, not good guys. Red is easier than blue. And so this really becomes an exercise in do we understand our networks and the systems that underlie those networks better than the people who are trying to break into it? And in particular, some of the more Apex predator, advanced nation state activities. In terms of the organizational construct of CSO, and where it fits in the company, we've had different models. Where we're at today is that the CSO is a peer of mine, and we work very closely together. And the CSO really, for the most part, defines risk and understands what is the attack surface and threat profile of any particular area. And then anything operational falls to the IT department. And so, in our environment, you know IBM's 350,000 plus employees, the IT department that I lead is about 12,000 people. And so, we have to work very closely together on very different threat profiles of general back office workers, people building commercial software, researchers building quantum computers, people doing outsourced IT. All of them have very different security profiles, and we have to be able to meet those requirements for each of those segments. >> We could do a whole hour just on security, one of my favorite topics. But you guys do have large surface area. >> Fletcher: Yes. >> You got a large employee base, diverse virtual workforce and offices. >> Mhmm. >> You got applications. I mean this is a really complicated security framework you guys have. Well, not framework, but just in terms of challenge, opportunity. >> It's a large surface area, hopefully the framework is not complicated, but it does require vigilance and focus. And so as an example, I am a customer of IBM's Xforce and managed security services. IBM's a market leader in the security services business and they're my kind of perimeter defense on some of these things. But no, you're right. It's something that we can't take our focus off of. >> You know, I had a conversation recently with General Keith Alexander, formally the original commander of cyber command, now he's CEO of a startup, doing a private version of NSA. Signaling is huge in security. >> Fletcher: Yep. >> And I know one of your hobbies is to study kind of the general national security thing as a techie. >> Fletcher: Mhmm. >> The enterprises, they're private organizations. You know, the government's job is to protect IBM. But you guys have to protect yourselves. So you have a new world now where there's a private, public partnerships going on where signaling is super important. Where's the data coming, so real time, and sometimes systems can slow that down for the sake of protecting. But at the same time, you need real time. Not just for security, but in business. Retail, to users. So real time's become a big part of it. What's your thoughts on the notion of real time and security? >> It's huge. Our capacity to detect, respond, and remediate a threat in real time, or as near real time as we can, is the name of the game. You're exactly right, the partnership between governments and public sector and private sector, I think is evolving in a positive way. Where we're beginning to see, as an industry statement, more of these kind of advanced nation state type tactics even being used outside of governments. And so that requires a different kind of response. And then we've got to kind of move forward from an environment where things that are publicly available get enriched and analyzed in some way and then become classified and we can't have access to it. And so the kind of information sharing between companies and governments is really helpful in being able to detect threat on the internet in a real time way. And by the way, if you think we got threats now, when you get to AI and then eventually quantum, threat in the future is not going to be about getting you to click on a link in your email that you think is a legitimate email and install some piece of malware. It's going to be about injecting the minimum amount of data required to teach a system something incorrect or different. So you think of image classification in autonomous driving, with a very small piece of data you can teach it that a stop sign is a yield sign. And that's a fairly benign kind of use case, a simple one, but now imagine financial systems, healthcare systems. So that is leading to quantum resistance cryptography, which is how long do you need to retain data and then what is your encryption strategy around it. >> You know it's interesting. The cost of malware injection can be applied to anything with this. So, I got to ask you, 'cause you guys are leading a lot in quantum, Baba Giano and I have had many conversations. You guys got a great group over there, you got power, amazing stuff happening in quantum. Quantum does change security. What specifically should people know about when they hear quantum. Good for security? Potentially harmful for security? It's an opportunity in both ways. You have a quantum computer, you can crack things much faster. The notion of passwords pretty much goes away. So I need multi-factorial authentication. I mean the whole world's changing with quantum. What's your view? >> Well, like all technology, it can be leveraged for good or less good, and it's a reflection of what the human beings who are using that technology intend to do with it. At IBM, we are working on both sides of that issue. We are developing quantum computers, and then on the other side of it developing encryption methodologies that are quantum resistant or quantum proof. So things like lattice cryptography, where you can mathematically prove you can hide keys in N number of layers such that even a quantum computer can't decrypt it. And so then, how long do you really need to keep that data? If it's two or three years, maybe quantum resistant cryptography is less of an issue for you. If you are the social security administration and you got to keep data for the next 50 years, you got to start investing now in what does the quantum future look like and what are the implications to me from a data and encryption perspective? >> Quantam's super exciting. Fletcher, thanks for coming on and sharing your insight, final question for you. As a person in the tech industry, you've had a chance to see the waves, you got a big one coming up from quantum cloud to AI. What are you most excited about? What should people be paying attention to? In terms of the macro trends. Not necessarily just IBM, just your personal view. To be a new brand of tech leader, what are some of the things that people should pay attention to? And what are you excited about? >> Well, what I'm excited about is what all of this technology is going to bring to bear on our lives. I mean, autonomous driving is going to be life changing for people. The insights that AI will drive. And think about how much time all of us spend doing menial, non-value added tasks at work and in our personal lives. And those things we won't have to worry about as much, with RPA and AI and all kinds of technologies. And I think that will free us to be more creative and be more fulfilled, and I feel very optimistic about the future. In terms of the second part of your question, what advice would I have for tech leaders, I think it's do what you're passionate about. I spend a lot of time focused on trying to create an environment where I think talented people want to work, and that means understanding our purpose, communicating that purpose well. And as I say, kind, passionate about what you do, and believe in the company's purpose. >> Yeah, that's interesting. You mentioned tech for good is always an underbelly in every new trend. And if you look at what happened with, say Facebook, I mean we were talking in 2012 around how data could be weaponized. That was years before so called election or other things meddling. >> Fletcher: Yeah. >> I think there's a community obligation, from sharing data for security risks to seeing the good as a vision, but also identifying bad actors that are going to weaponize the good first. Right? You always have those kind of early adopters. Might not be the best characters. So there's kind of a community has to come together and be faster to identify those. >> Yeah, I do think all of us as leaders have an obligation to understand that risk, and then make decisions around, we as the designers of these systems have to make sure that we're engineering them with fairness and without bias. And then, are the people that we're consuming technology from, are the people creating that technology, are their business models compatible with people who are consuming that technology? And making decisions around who is an ethical, trustworthy partner that I want to be in business with to develop the future. >> Fletcher, thanks for coming on. CIO of IBM here inside theCube, as part of this special program, new brand of tech leaders. I'm John Furrier, thanks for watching. (upbeat music)

[Music] [Applause] hello everyone welcome to the cube conversation here in palo alto california i'm john furrier host of thecube we got a special breaking news at scale has hired a new ceo chris lynch is the big news and taking over dave mariano with the evp of technology important because one cube alumni and also we've seen about all the big data events doing amazing work in the cloud scale data market for many many years we're very familiar at scale both david and chris lynch both cube alumni chris great to see you congratulations new ceo of atscale thanks john i really appreciate being here so um we know each other you've been on the cube before you're formerly the ceo of vertica sold to hp other ceos before that also a venture capitalist at atlas ventures for that distinguished career why this move right now what's attracted you to at scale take over the helm from the co-founder who will be partnering with you on this it's a great question um i'm still asking myself that but i think what it comes down to is i met dave years ago when i was at atlas and um it didn't work out the time for us to make an investment but i tracked the company and what they were doing and i left accomplished a little over a year ago and working with some companies out in the west coast app and be out here and i reached out to dave and said hey you want to grab dinner which we did and um by the end of the evening he was like you know you should come help us really commercialize this and take it to the next level they've been on our radar they've been on our radar for a while obviously i mean david at hadoop summit i think three four years ago and he was formerly a cloud we kind of hit it off clearly a big data um visionary and also entrepreneur but they had a unique model at that time hadoop was certainly viewed as you know the king of the castle for in big data at that time but cloud scale wasn't on everyone's radar on the mainstream they had a unique perspective has anything changed with the tech is that what's attracted to you the scaled piece of it what's the what's the secret sauce that that got you enticing so so i'm aware of the company's history that's not what got me interested um what got me interested is i think that they're the only player today in in the market that has a production product that can actually take customers from the data center to the cloud and do so transparently and i liken it to what we did at copia we virtualized file systems and frankly when we virtualized http traffic at arrow point so the idea of an abstraction layer a federation layer made sense to me and um you know as a venture capitalist i've seen the lack of adoption of big data workloads in the cloud you know there's a 200 billion dollar opportunity i think these guys are uniquely qualified to take advantage of it so that's really what drove me from a from a business perspective i see this opportunities unique versus anything i've seen on either coast we get a great reputation as an operator also someone who can manage and operate businesses and grow them and ultimately you have some great exits in your day vertica is well known in in the history of tech for two reasons one is it was probably the best deal hp ever has ever done on acquisition value-wise also it was before and during the whole vertica and autonomy autonomy acquisition was billions of dollars so and they ended up throwing that away keeping vertica and that became the flagship so you've seen how companies can take a wave and get in the right position you've done that with stone breaker in the past founder of vertica do you get the same movement here with this company it's the same playbook what's different is it the same what's the opportunity for this company so i think the opportunity for this company is different at vertica it was about executing against the excellent product that they had built in a known market they were targeted for my vision for at scale is to move beyond the data lake hadoop market and really take all the legacy warehousing vendors to the cloud cloud proof those solutions behind the firewall and begin to deliver those workloads in earnest to the cloud transparent to the user irrespective of the bi tool whether the the technology is behind the firewall in front of the firewall and i think that's a game changer certainly we've seen on the cube and the big conversation in the industry has been hybrid cloud multi-cloud but if you squint through that those trend lines it's really about integration right so you mentioned getting people to the cloud how big is that right now from an action standpoint is it is it accelerating is it early stages where is the progress bar on companies accelerating to the cloud it's it's stalled frankly because there are thousands of tens of thousands of applications in the fortune 500 that the the ability to take those applications and that data and move it to the cloud is it's on par with trying to operate do heart surgery on a patient while they're running the boston marathon so it's too difficult it's too disruptive to a business too risky what we do is we create a federation layer that basically abstracts all that complexity from the user and makes that transition transparent so to the user they don't have to care whether it's behind the firewall in front of the firewall what cloud it sits on what analytics store you're drawing from what bi tool it doesn't matter to the user so they've basically been able to separate those two things and that's going to allow people to scale and evolve into the cloud right today cloud is a revolution not an evolution it needs to be an evolution for fortune 500 companies to take advantage of it i got to ask you the hard question because ultimately let amazon they're kicking ass 10 ways from saturday they're obviously the numbers are off the chart even in public sectors just down there last week you got azure retooling and essentially they're going to try to replicate the the uh the congress of scale i think they're going to have a hard time but still no they're not going anywhere either and you get google changing the game focusing on their core competencies and where they can differentiate all that is potentially competition so this company at scale they definitely have tech chops so that's you know we know the team there so they had a lot of credit for that but 25 million dollars raised in their last round of funding total capital day 45 million how are you going to compete how are you going to take this and commercialize this opportunity and not be driftwood instead ride that wave it's a terrific question i actually think that one of the things that excites me about this opportunity it's the first opportunity as an operator that i've had that i haven't been in the david goliath thing i actually don't think that any of those people are competitors i think when atscale wins bi vendors win traditional data stores win and the cloud provider wins and ultimately the customer wins so my view is all those companies you mentioned if google wants to be relevant in the enterprise they need to get those big data workloads to their cloud we can do that we can continue to help amazon do that we can help oracle secure cloud do that we can help microsoft do that and all the time we're future proofing the legacy data stores of the teradatas and the oracles and the ibms so this is the first opportunity that i've seen where the game isn't to go disrupt and call out the competition it's to work with all these people to drive workloads to the cloud in a in a scale that hasn't been done before so you'd have to unseat anyone you've got to ride the cloud wave pretty much yeah we have to we have to demonstrate to these guys that we do what we say we we do um but my view is when we win all those participants can potentially win awesome how about uh staff funding you feel good that enough try powder in there is there another round of funding on the horizon or yeah i mean you know i haven't even started yet but you know my expectation is that in this marketplace with my track record raising capital or attracting capital will not be an issue it'll be about figuring out the business model and making sure it's right and then investing behind that business model it's enough cash now certainly do that talk about the boston california you're going to stay in boston that's news companies based in california you have a pedigree in boston certainly and being a vc down there but also you run businesses down there there's talent down there is there plans for a boston expansion a boston bi-coastal situation what's their opportunity so the company will remain headquartered in san mateo and i'll take up residence here and i'll go back and forth so my family's not moving so i'll have a residence in boston and one here um but you can absolutely expect that i'm going to leverage the ecosystem that i've grown up in and we will have a significant presence on the east coast awesome chris final question machine learning you guys were close to that for a long time at vertica you guys were doing some of the most cutting-edge machine learning before it became super popular as it is now as they call it ai now but essentially that was the beginning of the commodore store database which you guys pioneered speed and using data for competitive advantage how is that now scaled up in the market now how how robust is it how mature is it how ready is it and how does atscale take advantage of of that of that growth so i think that the world of data science in general has matured if you look at one of my proudest investments company called data robot they are the leaders in automated machine learning and their business is growing triple digits every year the level of adoption is really only gated by practitioners and people to apply the technology to these business problems but it's gaining incredible momentum for us i plan to integrate automated ai into components of our architecture which i think makes it really a game changer so of course we expect competition um but by the time that you know they get you know 100 miles behind us you know we're going to hit that what's that button that you have in those teslas you guys drive out here insane mode and it'll be automated machine learning will be powering that what's your impression of the marketplace right now is that um you know obviously you're seeing global landscape you know we see the china situation going on asia a lot of activity a lot of growth outside the united states um and obviously cloud you're seeing region specialties any thoughts on how that's going to play into it is it not relevant to you guys right now what's the what's your thoughts on the global landscape i mean i think it's it's relevant to everyone because i think it's what's driving valuations and this influx of money coming from these different places i mean if if you look at the middle east you know they're writing checks to any sort of tech company they can because they're pr trying to divest of what they know is a dead business right so that's going to drive valuations it's going to drive in my opinion um a lack of discipline and and bad behavior as we've seen you know in 2000 and other times in 2008 um i think for us as a company we're going to be disciplined and you know the fact that we can raise money and raise money attractive valuations isn't a reason to do it if you have a business model of fund that's a reason to do it so you know i don't think it'll be a distraction for us but i think it will increase you know the amount of noise in all the key markets and i think cyber we've seen it you know ai for sure um iot bitcoin all these what's the most exciting thing in the data business that's as it evolves now to the center value proposition that you see and as the ceo now of at scala you're going to capture this i think i would say two things in the in the ai machine learning space i think the fact that with democratization of data you're now actually seeing people applying machine learning way broader in organizations and way deeper than ever before and that's going to transform businesses low-tech business as well as high-tech businesses for us i think that the real opportunity exists it's a question of just taking these lit these legacy workloads and moving them to the cloud and that's not a trivial task not just technically but um you always have to be sensitive to companies ability to absorb technology i think one of the challenges is you know you're trying to transform a business that you know basically was informed as it developed in technology that was 1980. well chris congratulations on the ceo opportunity at at scale um what can people expect from you what what if you can write the narrative of the first couple moves off the line of scrimmage here what are you going to do what's your order of business what can they expect from you well the first thing i'd like to do after i meet the customers and the employees and the par existing partners is go out and get two significant partnerships i like to see a couple partnerships in cloud a couple partnerships with the classic data store vendors so that's probably going to be my first mission to get that moving and you know we'll see how quickly it goes but i think that's super important to do yeah and certainly scale right now has been a big competitive advantage here's a company at scale five year on their five year anniversary interesting gestation period for this big data world because hadoop you can look back into 2010 days hadoop was supposed to be the biggest thing since sliced bread but what happened was the world became bigger and from a date not just outside hadoop gave these guys an opportunity and their architecture fits well you see it's scaling quicker what's your what's your where's your point of scale how do you see this so i think i think that the company probably rightly so at the time hitch their wagon to hadoop but i think as you said it's it's really a subset of the data landscape and it's actually a pretty small one the real opportunity is in driving all the legacy data and analytics stores those islands of analytics and bringing them to the cloud and that like i said i think is a you know 100 billion dollar business well certainly great to see you congratulations getting back at the chief position and did a great job at vertica great journey we followed you on that one that was fantastic and then certainly watch it unfold certainly at hpe create a lot of value congratulations and at scale's got a good hire there congratulations thank you i appreciate it alright this is thecube conversation here inside the palo alto studios i'm john furrier thanks for watching [Music]

>> Narrator: From Gillette Stadium in Foxborough, Massachusets, it's theCUBE, covering VTUG Winter Warmer 2018. Presented by SiliconANGLE. (upbeat music) >> I'm Stu Miniman and this is theCUBE's fifth year at the VTUG Winter Warmer. 2018 is the 12th year of this event, always love when we get to talk to some of the users at the conference which's why I'm really happy to introduce to our audience Sue Morrow, who is a network manager at United Methodist Homes. Thanks for joining me Sue. >> No problem. >> First, tell me a little bit about yourself and what brings you all the way from Upstate New York to come to the VTUG. >> Well, I like to go to conferences whenever I can continue my education in IT. I grew up with computers in my house in the '80s. My dad was a physics teacher and a scientist so we always had a Commodore 64 or an Amiga in our house, growing up, when most people had Atari, we had computers. >> Totally, so Commodore 64, classic. I myself was a Tandy Radioshack, the TRS-80 Model III. So, in a similar era. >> Yep, I actually took a basic coding class on a TRS-80 when I was around 10, I think. Anyway, grew up with computers and somehow stumbled into IT later in life. So, that's why I'm here. >> United Methodist Homes, tell us just a little bit about what the mission of the company is. >> United Methodist Homes is a longterm care corporation. We have four facilities, two in the Binghamton area and two in Northeastern Pennsylvania. We have all levels of care from nursing homes, skilled care, up to independent living, and everything in between. >> Okay, and as network manager, what's under your purview? >> Well, it's kind of a silly title, actually. In longterm care or in healthcare or nonprofits, as we are, you often wear many hats and so that's, sort of, a weird title for me, but I supervise our help desk which we serve centrally from our corporate office. We serve about 600 actual computer users and, all in total, about 1200 employees who interface with the technology, in some way. So, I supervise the help desk, I make sure our network is running well. IT has changed over the years so that we're now providing more of a service and making sure that everything is up and running, network-wise, for everyone instead of keeping our servers running all the time. >> Yeah, reminds me of the old saying, it was like oh, the network is the computer, things like that, so you've got both ends of it. >> Sue: Yes. >> What kind of things are you looking at from a technology standpoint when you come to event like this? Did you catch some of the keynotes this morning, there was a broad spectrum? >> Yes. >> What are the kind of things that you're digging in to and find interesting? >> Yeah, the keynotes are really interesting. I think the first one that I went to with Luigi and Chris was great just to, kind of, expand your thinking about your own career personally, and where you want to go with your life was really interesting. I also watched Randall do his coding which is completely outside of what I do everyday, but was fascinating. And then the last major keynote was fantastic. I think that from my perspective in my company, we're kind of small and we don't do a whole lot of, we don't run apps and things like that, so the things that we have ritualized is mostly storage, so I'm looking at better ways that we can manage our storage and stuff. Most of the applications that we run now are SAS applications hosted by somebody else and their cloud, or a public cloud, or wherever, so I'm not so much looking at the cloud technologies like more businesses are that are providing an application for their company. >> It sounds like cloud and SAS's being a part of the overall strategy, have you been seeing that dynamic change in your company? How does it impact what you're doing or is it just a separate organization. >> It's definitely been a shift in the last few years, we used to run all of our applications in-house. Longterm care has caught up now, with the hospitals, so we have our electronic medical record which is a hosted application, whereas, up until five years ago, that was an on-premises application that we hosted and had to run and maintain, and update and upgrade, and make sure was available. That is definitely been a shift, that everything is now hosted. So we just make sure that our network is up and running and support our users and all of their issues when they break things, flip their screens, drop something, provide hardware for them all that sorts of stuff. >> The constant pace of innovation change. On the news this week they were saying, okay, medical records on your iPhone is up for debate. Does regulation impact your day to day activities and what are some of the challenges in that area? >> Absolutely. One of the other things we have to do is interface with the providers. We have medical providers that come in from the outside and they need to access our EMR also, so we need to provide access for them on, sometimes, whatever device they bring in, which is not always compatible, so we have a whole other set of challenges there. Where we can manage our computers for our employees by pushing out policies and things that are required for the application. When someone comes in from the outside, it isn't, necessarily, setup right, so we have that other set of challenges, and regulation-wise, yes. The government is always pushing out new and updated regulations for healthcare and we have to keep on top of that too. Of course, we have HIPAA concerns and things like that, which is also comes into play when you're talking about cloud host, and any hosted application. We have to be concerned about HIPAA, as well. >> Yeah, wondering when I look at the space that you're in, the ultimate goal is you want the patients, the people at your company, be able to spend more time, help them, not be caught up in the technology of things. Could you, maybe, talk a little bit about that dynamic? >> Yeah, one of the things that I always say is, we need to give our employees the tools that they need to do their job most efficiently. A nurse needs to be ready to go at the beginning of her shift on her laptop, ready to pass meds, and when they can't remember their password or that computer isn't working, my team needs to work as quickly as we can to get them back to work. We serve our users, really. We're not there being all techy. They want us to fix them and get them back to work, and that's what we do. We put tools in their hands, any device that they need to make them more efficient. I try hard to provide a variety of devices, people have different preferences on how they do their work. Some people prefer a laptop, some people prefer to stand at a wall-mounted touchscreen and document, some people want to carry a tablet with them. I try to provide a range of devices so that they can have whatever suits them and makes them most comfortable to get their job done. >> Love that, it's not, necessarily, about the cool or trendier thing, it's about getting business done, helping, and in you're case, enabling your employees to really help the people that are there. Anything you want to highlight as to things you're excited to look at this show, or just technology in general? >> I'm just kind of here for the general nature of it. I enjoy the networking and getting to talk to people, and keeping current in what's happening in the industry and my career, so that's why I come. >> Alright, well Sue Morrow, really appreciate you coming, sharing with our audience. >> Absolutely. >> User groups like this, all about the users. Happy to have lots of them on the program, so big thanks to the VTUG group for bringing us some great guests. We'll be back with more coverage here. I'm Stu Miniman, you're watching theCUBE. 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>> Lisa: I'm Lisa Martin with theCUBE. We're on the ground at Google for the 6th Annual CloudNOW Top Women in Cloud Awards. Very excited to be joined by award winner and CUBE alumni Erica Windisch, founder and CTO of Iopipe. Welcome back to theCUBE, Erica. >> Erica: Thank you. Great to have you here, and congratulations on being one of the top women in Cloud. >> Yeah, of course. >> Tell me, when you heard about that you were being recognized, what did that mean to you and where you are in your career? >> Well, oh gosh, I mean it really meant, it was really big for me. I actually wasn't really expecting it. I think I was nominated and I totally forgot. I think somebody had mentioned to me that they were nominating me and I had no idea about it. I totally forgot about it. But I mean, for me it's just so validating because as much as I've, well one, because I've done a lot of interesting things in Cloud and in tech, but I've never really gotten a lot of recognition for that. And also, just recognition, I mean to be quite honest, I'm transgender. So the fact that I was recognized as a woman, Top Ten Women in Cloud Computing, was extra important and special for me. >> Oh, that's awesome. So tell me about your path to being where you are now. Were you always interested in computers and technology, or is that something that you kind of zigzagged your way to? >> Yeah, well, it was one of these things I guess I had some interest. When I was a child, we had BASIC exercises printed in our math books but our teachers never went over it. So I got kind of interested and I would read through those like those little appendums in my math books, and I would start teaching myself BASIC. And I picked up a Commodore 64 and it didn't work and I taught myself BASIC, more BASIC with those manuals. And I just had these little tiny introductions to technology and just self-taught myself everything. Eventually using a high school job to buy myself books and just teaching myself from those books. Managed to grab Linux on some floppy disks, installed it and tried to figure out how to use it. But I didn't really have lot of mentors or anything that I could really follow. At best there were other kids at school who were into computers and I just wanted to try and do what they were doing or do better than they were doing. >> I love that, self-taught, you knew you liked this and you were not afraid to try, "Hey, let me teach myself." That's really inspiring, Erica. >> Yeah. >> So, speaking of inspiring, tell me about the Iopipes story. So you're a TechSource company, tell us a little bit about TechSource, what that investment in IOpipe means. >> Yeah, so, I started, I guess I first started IOpipe two years ago. And I found the co-founder Adam Johnson, who joined me. And we applied for Techstars, got in, and that was like the first validation that we had from outside of ourselves and maybe one angel investor at that time. And that was a really big deal because it really helped accelerate us, give us validation, allow us to make the first hire, and they also taught us a lot about how to refine our elevator pitch, and how to raise money effectively. And then we ended up raising money, of course. So with the end of Techstars we had a lot of visibility, and that helped us raise two and a half million dollars seed round. >> Wow, so a really good launching pad for you. >> Yes, yeah. >> That's fantastic. So tell us a little bit more about the technology, I know that there's AWS Lambda, we just got back from re:Invent last week, so tell us a little bit more about exactly what you guys do. >> Oh yeah, so what we do is we provide a service that allows developers to get better insights into their application, they get observability into the application running a Lambda, as well as debugging and profiling tools. So you can actually get profiling data out of your Lambda and load that into Google DevTools and get Flame Graphs and dig in deep into which function called which function inside of each function call, so every Lambda invocation you can really dig down and see what's happening. We have things like custom metrics and alerts for that. So you can, for instance, we built this bot. I built it in two days. It's a Slack bot that, if you put an image in a Slack, it will run it through Amazon Rekognition and tell you, describe the objects in it, and describe it. So, for instance, if you have visually impaired members of your team, they can find out what was in the images that people pasted. I built it in only two days, and I could use our tool, let's say to extract how many objects were found in that image, whether or not a specific object was found in that image, and then we can create alerts around those, and do searches based on those, and get statistics out of our product on the data that was extracted from those images. So that was really cool, and we actually announced that feature, the profiling feature, at Midnight Madness at re:Invent so it was like the opening ceremony for re:Invent. It was just us, Andy Jassy and Shaquille O'Neal. >> Lisa: What? >> Yeah, and we launched our product, and we did the demo of this Slack bot, and it was a lot of fun. >> Wow! So you were there last week, then? >> I was there, we were there last week, and we were actually the first, myself, my co-founder and one of our engineers were up there and we were the first non-AWS speakers at the entire arena, it was really amazing. >> Wow, amazing. Congratulations. >> Thank you. >> So with all the cool announcements that came out last week on Lambda, Serverless, even new features that were announced for recognition, how does that either change the game or maybe kind of ignite the fire under you guys even a little bit more? >> Well I think one of the biggest announcements relative to us was Cloud9. And we knew that this was going to happen, Amazon acquired them a year ago, a year and a half ago, but they finally launched it. And they really doubled down on providing a much better experience for developers of Lambda to make it easier for developers to really build and ship and run that code on Lambda, which provides a much tighter experience for them so that they can on-board into things like IOpipe more easily. So that was really exciting, because I think that's really going to help with the adoption of Lambda. And some of the other features like Alexa for work is really interesting. It will probably just again, a lot of Alexa apps are built on top of Lambda, so all of these are going to provide value to my own company because we can tell you things like, "Well, how are your users interacting "with those Alexa skills?" But I think it's just generally exciting because there's just so many really cool, I mean, I don't know how many things they announced at this re:Invent that were just really amazing. Another one I really loved was Fargate, because I mean I came from Docker, I used to be a maintainer of the Docker engine and something that I was pushing for at that time in OpenStack and other projects, was the idea of just containers completely as a service without the VM management side of things, because with like ECS, you had to manage virtual machines, and I was like, "Well that is a little, like, "I don't want to manage virtual machines, "I just want Amazon to give me containers." So I was really excited that they finally launched Fargate to offer that. >> So the last question in our last couple of minutes here, tell me about the culture and your team that you lead at IOpipe. You were saying before, you know, when you were a kid you were really self-taught and very inspired by your own desire to learn, but tell me a little bit about the people that work for you and how you help inspire them. >> Oh gosh, well I think first of all, we are, right now we're nine people. I would say about four or five of us are under-represented minorities in tech in one way or another. It's really been fantastic that we've been able to have that level of diversity and inclusion. I think part of that is that we started very diverse. You know, a lot of companies will say, well, one of their problems with not having enough diversity is that they hire within their networks, well we hire within our networks, but we started very diverse in the first place. So that organic growth was very natural and very diverse for us, whereas that organic pairing growth can be problematic if you don't start in a very diverse place. So I think that's been really great, and I think that the fact that we have that level of diversity and inclusion with our employees is kind of inspiring, because a lot of workplaces just aren't like that in tech. It's really hard to find, and granted we're only nine right now. I would really hope that we can keep that up and I would like to actually make our workforce even more diverse than it is today. But yeah, I don't know, I just think it's fantastic and I want what we're doing to be a role model and an inspiration to other companies and say, "Yes, you can do this." And also the work people in the workforce, yes, you can be a woman in tech, yes, you can be trans in tech, yes, you can be non-binary in tech. I am binary, but we have non-binary people in staff. And, I don't know, I hope that's inspiring to people and also myself being a transgender founder, I maybe know one or two other people who are transgender founders, it's very uncommon. And I hope that also is an inspiration for people. >> Well I think so, speaking for myself I find you very inspiring. You seem to be someone that's really known for thinking, "I'm not afraid of anything. "I'm just going to try it. "Starting a company, I'm going to try it." And it sounds like you guys are very purposefully building a culture that's very inclusive, and so I think that, as well as your recognition as one of the Top Women in Cloud, be proud of that, Erica. That's awesome. >> Thank you. >> And you got to meet Shaquille O'Neal? >> I got to meet Shaquille O'Neal, yeah. >> I've got to see the photo. (laughs) >> Yeah. >> Well thank you so much Erica for joining us back on theCUBE. Congratulations on the award, and we look forward to seeing exciting things that you do in the future. >> Okay great, thank you. >> I'm Lisa Martin on the ground with theCUBE at Google for the CloudNOW Top Women in Cloud Awards. Thanks for watching, bye for now.