>> 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) >> Announcer: From San Francisco, it's theCUBE. Covering Accenture Tech Vision 2020. Brought to you by Accenture. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're at the Accenture San Francisco Innovation Hub on the 33rd floor of the Sales Force Tower in downtown San Francisco. It's 2020, the year we know everything with the benefit of hindsight. And what better way to kick off the year than to have the Accenture Tech Vision reveal, which is happening later tonight, so we're really happy to have one of the authors who's really driving the whole thing. He's Michael Blitz, the managing director of the Accenture Tech Vision 2020, a very special edition. Michael, great to see you. >> Hey, thanks for having me. >> Absolutely, so you've been doing this for a while. I think we heard earlier, this thing's been going on for 20 years? >> It is. >> You've been involved for at least the last eight. >> Michael: I think a little bit more than that. >> More than that, so what's kind of the big theme before we get into some of the individual items? >> Yeah, so I mean, I think right now, what we're really talking about is that our real big theme is this: We the digital people. And it's that recognition that says that we've fundamentally changed. When you start looking at yourself and your lives, it's that you've gotten to a point where you're letting your cell phone track you. Your car knows where you are probably better than your spouse does. You're handing your key to Amazon and Walmart so they can deliver packages in your house. And more than that is that actually, we're trying to start to revolve our lives around this technology. I look at my own life, and we just sold our second car, specifically because we know that Uber and Lyft exist to fill that void. >> Right, well you don't have to look much further than phone numbers. How many people remember anybody's phone number anymore, right, 'cause you don't really have to. I think it's the 15th anniversary of Google Maps. >> Michael: Yep. >> This year, and to think of a world without Google Maps, without that kind of instant access to knowledge, is really hard to even fathom. But as you said, we're making trade-offs when we use all these services, and now, some of the costs of those things are being maybe more exposed? Maybe more cute or in your face? I don't know, what would you say? >> Yeah, I mean, I think what's happening now is that what we're realizing is that it's changed our relationship with companies. Is that suddenly we've actually brought them into our lives. And, on one hand, they're offering and have the ability to offer services that you could never really do before. But on the other hand is that, if I'm going to let somebody in my life, suddenly they don't have to just provide me value and this is useful, is that they actually, people are expecting them to retain their values, too. So, how they protect your data, what they're good for the community, for the environment, for society, whether it's sustainable or not. Is that suddenly, whereas people used to only care about what the product you're getting, now how it's built and how your company's being run is starting, it's just starting to become important, too. >> Right, well it's funny, 'cause you used to talk about kind of triple bottom line, shareholders, customers and your employees. And you talked about, really, this kind of fourth line, which is community and really being involved in the community. People care, suddenly you go to conferences where we spend a lot of time all the utensils are now compostable and the forks are compostable. And a lot of the individual packaging stuff is going away. So people do care. >> They do, and there's a fourth and a fifth. It says that your community cares, but your partners do, too. Is that you can't, I'm going to say, downgrade the idea that your B2B folks care is that suddenly, we're finding ourselves tied to these other companies, and not just in a supply chain, but from everything. And so, you're not in this alone in terms of how you're delivering these things. But now it's becoming a matter that says, Well, man, if my partners are going to get pummeled because they're not doing the right thing or they don't have that broad scope, that's going to reflect on me, too. And so, now you're suddenly in this interesting position where all of the things that we suspected were going to happen around digital connecting everybody is just starting to, and I think that's going to have a lot of positive effects. >> Yeah, so one of the things you talked about earlier today, in an earlier presentation was kind of the shift from kind of buyer and seller, seller and consumer, to provider and collaborator. Really kind of reflecting a very different kind of a relationship between the parties as opposed to this one-shot transactional relationship. >> No, and that's right, and it doesn't matter who you're talking about, is that, if you're hiring folks for skills that you're assuming that they're going to learn, that's going to be different in three years, in five years, you're essentially partnering with them in order to take all of you on a journey. When you start talking about governments, is that you're now partnering with regulators. You look at companies like Tesla, who are working on regulations for electric cars, they're working on regulations around battery technology. And you see that this go-it-alone approach isn't what you're doing. Rather, it's becoming much more holistic. >> Right, so we're in the innovation hub, and I think number five of the five is really about innovation today. >> Michael: It is. >> And you guys are driving innovation. And, rest in peace, Clayton Christensen passed away, Innovator's Dilemma, my all-time favorite book. But the thing I love about that book is that smart people making sound decisions based on business logic and taking care of existing customers will always miss discontinuous change. But you guys are really trying to help big companies be innovative. What are some of the things that they should be thinking about, besides, obviously, engaging with Mary and the team here at Innovation Hub? >> Yeah, no, and that's the really interesting thing is that when we talked about innovation, you know, five or even 10 years ago, you were talking about, just: How do I find a new product or a new service to bring to market? And now, that's the minimum stakes. Like, that's what everybody's doing. And I think what we're realizing as we're seeing tech become such a big part is that we all see how it's affecting the world. And a lot of times that things are good is that there's no reason why you wouldn't look at somebody like a Lyft or Uber and say that it's had a lot of positive effects. But from the same standpoint is that, you ask questions of: Is it good for public transit? It is good for city infrastructure? And those are hard questions to ask. And I think where we're really pushing now is that question that says: We've got an entire generation of not-tech companies, but every company that's about to get into this innovation game, and what we want them to do is to look at this not the way that the tech folks did, that says, here's one service or one technology, but rather, look at it holistically that says: How am I actually going to implement this, and what is the real effects that it's going to have on all of these different aspects? >> Right, Law of Unintended Consequences is always a good one. >> Michael: It is. >> And I remember hearing years ago of this concept of curb management. I'm like, Curb management, who ever thought of that? Well, drive up and down in Manhattan when they're delivering groceries or delivering Amazon packages and FedEx packages and UberEats and delivery dog food now. Where is that stuff being staged now that the warehouse has kind of shifted out into the public space? So, you never kind of really know where these things are going to end up. >> No, and I'm not saying that we're going to be able to predict all of it. I think, rather, it's that starting point that says that we're starting to see a big push that says that these things need to be factored and considered. And then, similarly, it's the, if you're working with them up-front, it becomes less of a fault, on a fight of whose fault it is at the end, and it becomes more of a collaboration that says, How much more can we do if we're working with our cities, if we're working with our employees, if we're working with our customers? >> Right, now another follow up, you guys've been talking about this for years, is every company is a tech company or a digital company, depending on how you want to spin that. But as you were talking about it earlier today, in doing so and in converting from products to service, and converting from an ongoing relationship to a one-time transaction, it's not only at that point of touch with a customer, but you've got to make a bunch of fundamental changes back in your own systems to support kind of this changing business model. >> Now, and that's right, and I think this is going to become the big challenge of the generation, is that we've gotten to a point where just using their existing models for how you interact with your customers or how you protect their data or who owns the data, all of these types of things, is that they were designed back when we were doing single applications, and they were loading up on your Windows PC. And where we're at now is that we're starting to ask questions that says, All right, in this new world, what do I have to fundamentally do differently? And sometimes that can be as simple as asking a question that says, you know, there's a consortium of pharma folks who have created a joint way for them to develop all of their search algorithms for new drugs. But they're using block chain, and so they're not actually sharing the data. So they do all the good things, but they're pushing that up. But fundamentally, that's a different way to think about it. You're now creating an entirely new infrastructure because what you're used to is just handing somebody the data, and what they do with the data afterwards is kind of their issue and not yours. And so now we're asking big, new questions to do it. >> Right, another big thing that keeps coming up over and over is trust. And again, we talked a little earlier. But I find this really ironic situation where people don't necessarily trust the companies in terms of the people running the companies and what they're going to do with their data, but they fundamentally trust the technology coming out of the gate and this expectation of: Of course it works, everything works on my mobile phone. But the two are related, but not equal. >> Michael: No, I mean, they're not, I mean, and it's really pushing this idea that says we've been looking at all these, I'm going to say scary headlines, of people not trusting companies for the last number of years, while at the same time, the adoption for the technology has been huge. So there's this dichotomy that's going on in people, where at one point, they like the tech. You know, I think the last stat I saw is that everybody spends up to six-and-a-half hours a day involved on the internet, in their technology. But from the same standpoint is that they worry about who's using it and how and what is going to be done. And I think where we're at is that interesting piece that says we're not worried about a tech lash. We don't think that people are going to stop using technology. Rather, we think it's really this tech clash that says they're not getting the value that they thought out of it, or they're seeing companies that may be using this technologies that don't share the same values that they do, and really, what we think this becomes, is the next opportunity for the next generations of service providers in order to fill that gap. >> Right, yeah, don't forget there was a Friendster and a MySpace before there was a Facebook. >> Yeah, there was. >> So, nothing lasts forever. So, last question before I let you go, it's a busy night. The first one was the I in experience, and I think kind of the user experience doesn't get enough light as to such a defining thing that does move the market if, again, I love to pick on Uber, but the Uber experience compared to walking outside on a rainy day in Manhattan and hoping to hail down a cab is fundamentally different, and I would argue, that it's that technology put together in this user experience that defined this kind of game-changing event, as opposed to it's a bunch of APIs stitching stuff together in the back. >> No, that's right, and I think where we're at right now is that we're about to see the next leap beyond that. Is that, most of the time when we look at the experiences that we're doing today, they're one way. Is that people assume that, Yeah, I have your data, I'm trying to customize. And whether it's an ad or a buying experience or whatever, but they're pushing it as this one-way street, and when we talk about putting the I back in experience, it's that question of the next step to really get people both more engaged as well as to, I'm going to say improve the experience itself, means that it's going to become a partnership. So you're actually going to start looking for input back and forth, and it's sometimes going to be as simple as saying that that ad that they're pushing out is for a product that I've already bought. Or, you know, maybe even just tell me how you knew that that's what I was looking for. But it's sometimes that little things, the back and forth, is how you take something from, what can be a mediocre experience, even potentially a negative one, and really turn it into something that people like. >> Yeah, well, Michael, I'll let you go. I know you got a busy night, we're going to present this. And really thankful to you and the team, and congratulations for coming up with something that's a little bit more provocative than, Cloud's going to be big, or Mobile's going to be big, or Edge is going to be big. So this is great material, and thanks for having us back. Look forward to tonight. >> No, happy to do it, and next year we'll probably do it again. >> [Jeff\ I don't know, we already know everything, it's 2020, what else is unknown? >> Everything's going to change. >> All right, thanks again. (upbeat music)

>>from San Francisco. It's the Cube covering Accenture Tech Vision 20 twenties Brought to you by >>Accenture. >>Hey, welcome back here. Ready? Jeff Frick here with the Cube. We're at the Accenture San Francisco Innovation Hub in the 33rd floor of the Salesforce Tower in downtown San Francisco. It's 2020 the year we know everything with the benefit of hindsight. It what better way to kick off the year than they have the Accenture Tech vision reveal, which is happening later tonight. So we're really happy to have one of the authors who's really driving the whole thing. He's Michael Built the managing director of the Accenture Tech Vision. 2020. A very special edition. Michael, great to see you. Thanks for having me. Absolutely. So you've been doing this for a while? I think we heard earlier. This thing's been going on for 20 years, but you've been involved with at least the last eight a little bit more and more than that. So what's the, uh, what's kind of the big theme before we get into some of the individual? Yeah, So I >>mean, I think right now what we're really talking about is that our real big theme is this ui the digital people? And it's that recognition that says that we fundamentally changed. I mean, when you start looking at yourself in your lives, is that you've gotten to a point where you're letting your cellphone track you. You know your car knows where you are, probably better than your spouse does. You know you're handing your key to all go to Amazon and Wal Marts. They deliver packages. Your help, and more than that, is that actually, we're trying to start to revolve our lives around this technology. You know, I look at my own life and we just sold our second car specifically because we know that uber and lift exists to fill that void, >>right? Well, you don't look much further >>than than phone numbers. How many people remember anybody's phone number anymore? Right, cause you don't really have to. I >>think it's 1/15 anniversary of Google maps this year, and to think of a world without Google Maps without that kind of instant access to knowledge is is really hard to even fathom. But as you said, we're making trade offs when we use all these services and and Now, some of the costs of those things are being maybe more exposed, maybe more cuter in your face. I don't know. What would you say? >>I mean, I think what's happening now is that what we're realizing is that it's changed our relationship with is that suddenly we've actually brought them into our lives. And on one hand they're offering and have the ability to offer services that you could never really do before, you know. But on the other hand is that if I'm gonna let somebody in my life suddenly they don't have to provide. Just provide me value. And this is useful is that they actually irks people expecting them to retained their values to, you know, so how they protect your data. What they're good for the community, for the environment, for society, whether it's sustainable or not, is that suddenly whereas people used to only care about what the products are getting now, how it's built, how your company is being run, it's starting like it's just starting, you know, to become important too, >>right? Well, it's funny cause you used to talk about, you know, kind of triple bottom line shareholders, customers and your employees and you talked about really kind of this fourth line, which is the community and really being involved in the community. People care suddenly go to conferences that we spend >>a lot of time and you know, all the utensils air now compostable and the forks air compostable. And you know, a >>lot of the individual packaging stuff is going away, so people do care. >>They do. And then there's 1/4 and 1/5 that says, the your community cares, you know? But it's also your partners. Do, too, is that you can't you know, I'm going to say downgrade. You know, the idea that you're B two b folks care is that suddenly we're finding ourselves tied to these other companies, and not just in a supply chain, you know, but from everything. And so you're not in this alone in terms of how you're delivering these things. But now it's becoming a data that says the man, if my partners are going to get pummeled because they're not doing the right thing or they don't have that broad scope, is the that's going to reflect on me, too, And so now you're suddenly in this interesting position Where all of the things that we suspected we're gonna happen around digital connecting everybody is just starting to. And I think that's gonna have a lot of positive effects. >>Yep. So one of the things you talked about earlier today, earlier presentation was kind of the shift from kind of buyer and seller seller, consumer to provider and collaborator, Really kind of reflecting a very different kind of a relationship between the parties as opposed to kind of this 11 shot transactional relationship >>now And that's right. And it doesn't matter who you're talking about. This is that, You know, if you're hiring folks, you know, for skills that you're assuming that they're going to learn, you know, that's going to be different in three years and five years. You're essentially partnering with them in order to take all of you on a journey. You know, when you start talking about governments, is that you're now partnering with regulators. You know, you look at companies like Tesla who are working on, you know, regulations for electric cars. They're working on regulations around battery technology. And you see that this go it alone approaches and what you're doing? You know, Rather, it's becoming much more holistic, >>right? So we're in the innovation hub, and I think Number five of the five is really about innovation today. And you guys are driving >>innovation and you know the rest of peace. Clayton Christensen passed away. Innovator's Dilemma. My all Time favorite book The Thing I love about that book is it's smart people. Making sound decisions based on business logic and taking care of existing customers will always miss this continuous change. But you guys are really trying to help companies be innovative. What are some of the things that they that they should be thinking about besides obviously engaging with marrying the team here? And >>that's the really interesting thing is that you know, when we talk about innovation, you know, five or even 10 years ago, you were talking about just how do I find a new product or new service to bring to market? And now that's the minimum stakes like that's what everybody's doing. And I think what we're realizing as we're seeing tech become such a big part is that we all see how it's affecting the world. And a lot of times the things they're good is that there's no reason why you wouldn't look at somebody like a lifter uber and say that it's had a lot of positive effects. But from the same standpoint is that you ask questions of Is it good for public transit? It's good for city infrastructure, and those are hard questions to ask. And I think where we're really pushing now is that question that says We've got an entire generation of not tech companies. But every company that's about to get into this innovation game and what we want them to do is to look at this, not the way that the tech folks did. That says, Here's one service or one technology but rather look at it holistically. That says, How am I actually going to implement this? And what is the real effects that it's gonna have on all of these Different >>lot of unintended consequences is always >>a good, and I remember hearing years ago >>this concept of of curb management, curb management you ever thought of that will drive up and down in Manhattan when they're delivering groceries or delivering Amazon packages and FedEx packages and uber eats and delivery dog food. Now where's that stuff being staged? Now? The warehouses kind of shifted. You got into the public space, so you never kind of really know where these things they're going to end up? >>No. And I'm not saying that we're gonna be able to predict all of it. I think rather it's that starting point that says that, you know, we're starting to see a big push, you know, that says that these things need to be factored in and considered. And then similarly, it's the If you're working with them up front, it becomes less of a fault in a fight of who's fault. It is at the end, and it becomes more of a collaboration that says, How much more can we do if we're working with our cities that we're working with our employees? We're working with >>another follow up. You guys been talking about this for years? Is every company is a tech company or a digital company, depending on how you want to spin that. But as you were talking about earlier today in doing so and then converting from products to services and converting from an ongoing relationship 21 time transaction, it's not only at that point of view touch with a customer, but you've got to make a bunch of fundamental changes back in your own systems to support kind of this changing business >>models. And that's right. And I think this is going >>to become The big challenge of the generation is that we've gotten to a point where just using their existing models for you know how you interact with your customers or how you protect their data or who owns the data. All of these types of things is that they were designed back when we were doing single applications and they were loading up on your windows PC. And where we're at now is that we're starting ask questions that says Alright in this New World order why it's a fundamentally do differently, you know, And, you know, sometimes that could be You know, a simple is asking a question that says, You know, there's a consortium of pharma folks who have created a joint way for them to develop all of their search algorithms for new drugs, but they're using Blockchain, and so they're not actually sharing the data, so they do all the good things but they're pushing that. But fundamentally, that's a different way to think about it. You're not creating an entirely new infrastructure because what you're used to is just handing somebody the data on what they do with the data afterwards. It's kind of their issue and not yours. And so now we're asking big new questions to do it >>right. Another big thing that keeps coming up over and over is trust. And again, we talked little. Really? I find this really ironic situation where people don't necessarily trust the companies in terms of the people running the companies and what they're gonna do with their data. But they fundamentally trust the technology coming out of the gate and this expectation of, of course it works. Everything works on my on my mobile phone, but the two are inter related, but not equal. >>No, I mean, they're >>not. I mean, it's really pushing this idea that says the we've been looking at all of these. I'm going to say scary headlines. People are not trusting companies for the last number of years, while at the same time the adoption for the technology has been huge. But there's this dichotomy that's going on and people were at one point is the they like the tech. I think the last stat I stall is that everybody spends up to six and 1/2 hours a day involved on the Internet in their technology. But from the same standpoint is that they worry about who's using it, how and what it's done. And I think where we're at is that interesting piece that says the we're not worried about a backlash. We don't think that people are going to stop using technology. Rather, we think it's really this tech backlash that says they're not getting the value that they thought out of it, you know? Or they're seeing companies that may be using this, technologies that don't share the same values that they do. And really, what we think this becomes is the next opportunity for the next generations of service providers in order to fill that >>right. Don't forget, there was a Friendster and MySpace before there was a Facebook. Nothing lasts forever. So last question finally goes busy night. The 1st 1 was the eye and experience, and I think you know the kind of the user experience doesn't get enough light as to such a such a defining thing that doesn't move the market again. I lived in an uber right, but the uber experience compared to walking outside on a rainy day in Manhattan and hoping to nail down a cab is fundamentally different. And I would argue that it's that technology put together in this user experience that defined this kind of game changing event as opposed to, You know, it's a bunch of AP I stitch and stuff together in the back. >>That's right. And I think where we're at right now is that we're about to see the next leap. Beyond that is that you know, most of the time when we look at the experiences that we're doing today, they're one way is that people assume that, Yeah, I have your data trying to customize and whether it's a ad or buying experience or whatever. But they're pushing it as this one way street. And when we talk about putting the I back experience, it's that question of the next step to really get people both more engaged as well as to I'm going to say improve the experience. Self means that it's going to become a partnership. So you're actually going to start looking for input back and forth, you know? And it's sometimes it's going to be a simple is saying that that ad that they're pushing out is for a product that I've already bought or, you know, maybe even just tell me how you knew, You know, that that's what I was looking for. But it's sometimes that little things that back and forth is how you take something from, you know, which could be a mediocre experiences, even potentially a negative one and really turned it into something that people like. >>Yeah, well, Michael, I let you go. I know you got a busy night, and we're going to present this and ah, I really think to you and the team And congratulations for coming up with something that's a little bit more provocative than Cloud's Going to be big or mobile is going to be big or edge is going to be big. So this is a great material. And thanks for having us back. Look forward to tonight happening. >>Happy to do it. And, you know, next year will probably do it again. >>So we already know everything is 20. >>20. What else is No, A All right. Thanks again. >>Yeah,