Four CEOs on the Future of AI: CoreWeave, Perplexity, Mistral, and IREN

28:27Listen, it does a lot of things having a boom-bust cycle. It clears out the underbrush. The strongest companies will be able to survive and take advantage of that. And it sows the seeds of future business. The other thing that it does is you put that infrastructure into the ground. You put the fiber into the ground, which became the backbone of how, you know, we watch movies every day and how we, you know, communicate and how we hop on a Zoom and, you know, COVID and all of these things were based on that infrastructure that was available to be consumed. Yeah, people don't recognize this fact.

29:05if you, the premise of YouTube from the founders who I knew, Chad Hurley and his other partner, they basically had the realization at this curve, storage is coming down so quickly, we could offer free unlimited uploads and bandwidth is coming down. So I guess we don't have to charge people for sharing a video online. Before that, if your video went viral, people are going to have their minds blown, but your server would turn off and it would say, this person, you know, needs to pay their bill. Yes. Because they were getting charged for carriage by the Megavit going out. Yes. I mean, look, and, you know, the business models change and evolve.

29:46And, you know, like you said, Moore's Law, and certainly Jensen will talk about the fact that, like, what is going on within the accelerated compute, say, dwarfs Moore's Law, right? And all of that is going to lead to more opportunity to build more companies that are going to do things like YouTube did, which has really changed the world. Yeah. I mean, the concept that I don't know if it was like a million hours being uploaded every hour or minute. But at some point, Susan Wojcicki, rest in peace, said, told me just like how much was being uploaded every minute. And it made no logical sense until you realized, well, there's three billion people, two or three billion people in the service and 1 % upload or 0.1, 10 bips upload.

30:36It's like, OK, one in a thousand people upload. It's a big it's a big denominator. I was sitting on a panel with Sarah Fryer, CFO of OpenAI. And every once in a while, she really puts out like interesting information. And so she was talking about the cost of a million tokens when ChatGP3 came out. And it was$32 in change. And now a million tokens cost$0.09. Yeah. Right. And so you just see the incredible power of how the capital markets, how capitalism is fueling engineering and fueling competition. And it's become recursive now, too. I mean, these models, if you say to the model, hey, make yourself more efficient, spend less money and lower the cost of tokens, it'd be like, OK, Captain.

31:32Yeah. I don't know if you saw Carpathie's recursive thing last weekend, but it's like now civilians who've never worked in a language model during computer science are like, I'm going to try to do something recursive this weekend. You know, it's one of the things that I that I talk to, you know, the other founders about, you know, and it's like. When you think about some of the things that AI does, right, it's lowering the barrier to operations. So if you have a good idea or a great idea, you can open up your model and you can tell your model, you can vibe code it, you can do all kinds of different things and create things that never existed before.

32:16That's amazing, right? That's bringing down this incredible barrier that kept human creativity contained. And now all of a sudden, this whole new vector of medical research or different approaches to baseball cards or whatever you want. If you've got a great idea, if you've got a new creative idea, that's the valuable kernel right now that allows you to build new things and to create new things. And I just think that's incredibly exciting. Like you're bringing the minds of 8 billion people, a tool that allows them to overcome what was insurmountable for forever. For humanity. Yeah. It's a bright new future, Michael.

32:56Appreciate you sharing the information with us and the vision. I am really delighted to have Aravind Srinivas on the program. Thank you for having me here, Jason. It's so great. I want to go through three stages in which I fell in love with your product. The first phase was I could go and pick my language model if I wanted to use OpenAI, if I wanted to use Claude, whatever it was. That was like a real unlock for me. And on the sidebar, I noticed you had done essentially like what Yahoo did in the early days, finance, sports. And when I pulled my Nick game up, it gave me a live version of that.

33:39When I pulled my stocks up, it summarized the news in real time. And I was like, wow, this execution is great. And I kind of made you my front door to different models and it made it easier to check it. Then you came out with the Comet browser. And I was like, holy cow, I can give this a series of instructions. Go to my LinkedIn, find everybody from this company, put them into a Google sheet and boom, you were the first out of the gate with that. And then just the last couple of weeks, I had been claw pilled and using OpenClaw, but you came out with computer. And I started using computer. and boy, it's good.

34:14It's a really strong start, allowing me to do repetitive tasks, very similar in some ways to co-work from Claude or basically an engineer or developer using it. So are these the evolution of the company? And I should think about it that way. But how do you look at perplexity now? You have a very loyal fan base. You're making a lot of money. I don't know if you disclose it, but I think it's hundreds of millions to billions. You can tell us. But what is perplexity in the face of, wow, Claude's having a great run, OpenAI still doing strong, Grok doing very well, Gemini coming on strong. There's like six or seven of you.

34:53And you just happen to be one of my top twos right now. Thank you. First of all, thank you. Thank you so much. Perplexity has always been built for people who are always looking for the extra edge, the curious people. So it's very natural that you are one of our flower users. One common theme for us for the last three and a half years is accuracy. Perplexity wants to be the company that's building the most accurate AI. So when you want to give somebody answers, accuracy is very essential for building trust. Because only then the user is going to ask the next set of questions it turns out it was a great idea to give ai access to the internet to be accurate so that's the perplexity ask product it turns out it's a great idea for ai to have full access to a browser so that it can be accurate when you task it to go do something that you would do yourself on a browser agentic browsing comment now the last phase is it turns out it's a great idea for ai to give it be given a full access to a computer so that it can do whatever you do on computer on its own essentially becoming the computer itself an orchestra of everything ai can do today every single capability each individual ai model has be it gpt or claud or gemini or anything else an orchestra of all those capabilities that what that's what perplexity computer is and all these sub-agents that are running inside computer are the musicians the models are essentially the instruments and they're like hundreds of models out there each having their own specialization some are good at coding some are good at writing some are good at multimodal visual synthesis image generation video generation audio but what matters is the end output the music you play that's the work AI gets done for you and that's what perplexity computers the AI is itself is the computer now still lives inside of a browser.

36:53Have you considered giving it desktop root access? That feels like the next place this is going but that comes with a lot of security issues, a lot of trust issues. As you mentioned, trust is paramount. Getting the right answer is what builds it but also not getting hacked and not having it delete your files. So yes, how do you think about root access to my Windows machine? Obviously iOS, they won't let you but with an Android phone, it would let you yes. So do you have that in the works? Yes, so we announced something called personal computer, perplexity personal computer. That's essentially going to take all the trust and reliability and the server side execution of perplexity computer, but synchronize it with your local computer so that you can use it from your phone.

37:36And we're going to do this with the Mac Mini, where you synchronize your computer with the Mac Mini. So that becomes your local server. all the agent orchestration that has to do with your local private data will run on that local orchestration loop that runtime with the mac mini not on your servers not on anthropics exactly yeah it could still ping frontier models if it needs to with your permission but it will be orchestrating everything on your local hardware yeah and if it needs to run on the server side hardware if you don't want very complicated long running tasks to be running on your local hardware you can delegate it to run on your server-side computer, which is, again, only accessible to you and you alone.

38:21So that way, we're going to bring this perfect hybrid of trustworthy hybrid between local and server-side. And you'll make it easy to do it, just be abstracted. You install one executable, boom, it's done. It's like open claw for dummies. Nobody needs to learn how to use it. Nobody needs to manage API keys. Nobody needs to manage separate billing across like 100 different services, figure out what you can give access to and not access to. We take care of that. So it's a Steve Jobs way of doing it, you know, end-to-end integration. And how do you think about local models? I have started running Kimi 2.5 on a Mac Studio.

38:58It's not as good as Claude or Gemini or Grok, but you can probably do about 80 % there for free, essentially. And so that's quite compelling considering some of my other bills, Claude and stuff were getting expensive. So do you have one of those? You started testing on your local Mac Studio. I assume you have a Mac Studio and you're doing this yourself. Yeah. Or now, I don't know if you saw Dell and NVIDIA announced a giant workstation. Yeah. Is it a 3 ,800? Something like that. Something like that. With 750 gigs of RAM. So what do you think about the desktop going back to workstation slash server status?

39:38I think it's very promising. um my set my prediction is to initially start off as a sub-agent so whatever you need to go uh like your tax returns your personal photos your emails your your calendar all that stuff those local apps your personal notes very personal notes you could make sure that the models that access those tokens will be running on your local hardware if you want to if you're that privacy conscious uh and more complicated stuff that accesses your data that's already on the server side example your google calendar yeah your gmail this is personal data still but uh ai runtime can access that through your connector your google calendar connector your google workspace connector and that could run on the server side because anyway the data is on the servers it's not even lying on your device so that sort of hybrid orchestration is where we are headed to I don't think it's a dichotomy between fully local versus fully server.

40:41It's all about choice. And anyway, when you're on your phone, you don't care actually which server that workload's running from because it's not going to be able to run on your phone anyway. The chips need to exist on a Mac Studio or a Mac Mini or on the server. Or this new Dell that's coming out. And I really think the idea of spending$10 ,000 on a powerful desktop will appeal to people if it lowers their$500 a month fraud bill. This is an incredible savings. Plus, you get the benefit of privacy and not educating the language models on your personal data. Yes. And it's going to be like you're buying a refrigerator, your internet modem.

41:23Like the cost for these will eventually go down. Yeah. But it's not going to feel like you're wasting your money. Every home has a lot of other sensors that runs your home that will also be part of this orchestration loop. So that's where it gets exciting because now you can just dictate something to your phone and that can control your entire home. So that's the dream that everybody has. And all that orchestration loop can run on your local hardware. No problem. And I'm curious what you think of the operating system. What's eventually going to be the operating system of this workstation? AI is the operating system.

42:04Like earlier in the traditional operating system, you execute programmatically. Now you start with objectives, not specific instructions. You come up with a high level objective. Go build this website for me that takes all the transcripts of all in podcasts and tracks the stock price just before the podcast and after. and chart it for the Mac 7 and chart it over time. That's the objective. But individually, it's running a file system, a code sandbox, access to the internet. It's having its own HTML tools. So I think that's basically where models, systems, and files and connectors are all coming together.

42:44You would think of that as an OS, except you're operating at an abstraction about that where you're thinking in terms of objectives. Yeah. Yeah. And does it need to eventually become its own operating system in your mind? It could be like people could think about it. It's like, yeah, I have my perplexity computer running all the time, whether it essentially it runs on Linux machines right now. Every server side computer is a Linux machine. So I think Mark in recent tweeted this right after our release that turns out Linux computers was the right idea. Desktop Linux computers are finally going to work.

43:20Yeah, I mean, they're stable, they're customizable, and you're not at the mercy of Apple's desire to contain the experience or Microsoft's surface area for hackers. Exactly. You build something rock solid, and it does feel like Linux might actually become the eventual winner. It may not need to have a front end. That's the thing. You could access the Linux machine on your phone. It could be running iOS or Android. It doesn't matter. The actual valuable runtime is running on Linux on the server. You've done great as a consumer company. A lot of love there. Now I'm starting to see corporations with computer starting engaging.

44:05In fact, you'll be happy to know this. Last week, I took two people in my back office and I said, stop working on OpenClaw. Your job is to do the back office automation at our venture firm only using perplexity. and they were perplexing a computer and they were like oh okay um it doesn't talk well in slack it doesn't have an agent in slack i was like it will i'm gonna see arm and i'll talk to him about that so we need a really strong slack connector it's already out it is okay great computer exists as a slack bot right now okay that you can add to your slack workspace on enterprise plan and our entire company works like that people are talking more to computer on slack than other than other people.

44:47In our first volley, we were sending reports in, but it wasn't interactive. That's perfect. So now you've got your company going in two different directions. This incredible consumer run you have. How many people are using the product every month? Several tens of millions. So tens of millions of people. That's very much similar to the trajectory of the Google and Yahoo consumer business. Now you've got corporate. How are you doing on the corporate side? thousands of companies? It's the fastest growing business for us. It's growing faster than the consumer and revenue. And things like computer unlock entirely new possibilities.

45:22For example, we've saved more than$100 million for our Enterprise Max customers who are on the highest tier of Enterprise. Explain what that is. What does it cost? $200 a month per person? So there are two tiers. One is the Enterprise Pro, which is$40 a month. And there's the enterprise max which is four hundred dollars a month and that that and and and and on a computer after you run out of your credits you would pay for the tokens you pay for the usage are you making money on the four hundred dollar a month five thousand dollar a year one or at this point in time are people going so crazy our uh one thing that perplexity has is every revenue we make unlike certain other wrapper companies every revenue perplexity makes has positive gross margins got it because uh we're not just selling tokens right most of our revenue is recurring because people are paying a subscription fee and because we route through multiple different models we are very efficient in terms of how we spend on the tokens because we have all this advantage with drag and orchestration and search we don't actually need to blow up the context window of the models yeah as a result of that we have positive gross margins on all the revenue every single penny we make, we make profits on that.

46:33Overall, the company is still yet to be profitable, but we're working towards that. You've had the opportunity to exit. A lot of rumors, Apple, other people were like, hey, this is a great team. How many people on the team now? About 400. Yeah. You've got a very coveted team. You obviously understand consumer. You obviously understand business. It's a product-driven organization. Reports are you declined, But the world's getting hyper competitive here. How do you keep up as a 400 person organization when you got Sam Altman over here raising a hundred billion dollars, you know, and then you have Elon putting data centers in space and merging with SpaceX and Twitter.

47:10You have Google with unlimited resources, Amazon getting in the game, and obviously Gemini, a very strong product and Google really good at consumer. I think we'd all agree Facebook and Meta haven't figured it out yet, except maybe for serving us better ads, but they haven't figured out the consumer case yet, but they'll copy it. They always do. How do you look at the playing field? Because the degree of difficulty, this isn't playing checkers or this is like playing against the 10 best chess players in the world. That's what you have to do every day. So how do you think about it long-term and independent company do you think you'll need to join forces at some point well and why didn't you take the deal this deals were incredible that you got offered so one advantage we have that all these companies you mentioned don't have is the multi-model orchestration we're like switzerland we don't have to have one horse in the race if gpt wins gemini wins claude wins llama wins it doesn't matter to us uh or even open source models can win no problem and you have them on the service yes deep seek and kimmy we have kimmy we have nematron and we have a lot of usage of quen alibaba quen yeah silently under the hood so for us like that advantage of being able to take the best in each model and give the user the orchestra of everything they can do i don't think any of the companies you mentioned can do that right nor would they nor would they it makes no sense for them it would be an admission that all the data centers and capex they have built out still couldn't produce them the best model.

48:50And Dario, CEO of Anthropics, said recently in an interview that models are specializing. Towards the beginning of last year, people thought models are going to commoditize. But towards the end of last year, models started specializing. Even with encoding, Cloud Code and Codex have very different capabilities. Our iOS engineers love using Codex. our backend engineers love using cloud code. So even within a specialization like coding, models have their own unique specialties. And there are many other use cases outside coding where different models are good at different things, which means the orchestra conductor that has no one model to the horse in the race can win by providing a very unique value and service to the customer that each of these amazing names that you mentioned cannot.

49:41And so you're buying tokens wholesale from them and then you'll charge customers to do it or do you think it's all We're gonna take care of all their orchestration. Yeah, so you don't have to manage tokens across different models Because I authenticate a couple of my different accounts my pro accounts into perplexity But does it I don't have enough knowledge to know if you are Abstracting that and people can just search across them and it's part of their perplexity subscription No, we're not bundling subscriptions into other AIs. Yeah. We just ping the models directly. Got it. What you get in us is the perplexity or orchestration.

50:18Got it. The harness. Right. So when models are kind of specializing, there's a bigger value in the one who knows how to build a great harness. Right. That can take the best in each model. Does it auto route today or do you still have the dropdown somebody's got to pick? It definitely autoroutes the best model for each prompt, but we also give users the flexibility to pick whatever model they want. What do you think of, I've seen a bunch of startups hack this together, but doing the same query across multiple. We built a thing called model council. Model council, yeah. So that's one of the modes and perplexity where I saw Jensen say in one of the interviews that he puts the same prompt in five different AIs and sees what each of them says.

51:00Yes, everybody does that. But then you still have to apply a biological compute to read every answer and then figure out where they differ. It's like talking to five lawyers about your trust or your - Five different doctors. Five different doctors trying to figure it out. Exactly. It's dumb. So the model council is a feature we built where it will not just give you the answers of each model, but it will tell you exactly where they agree, where they disagree, and where the nuances are. And that's in the interface? Yeah. Model council? I didn't know it was there. It's there. I mean, you release product at a pretty great cadence, huh?

51:31Yes. Where did you learn that and what's your philosophy of shipping product? Our philosophy is like speed is our moat. Like, you know, again, one of the things that big companies cannot do is move at the speed we do. Serve customers at the speed and quality. It's very hard to maintain quality, speed and trust at the same time. Yeah. Like Apple takes a long time to ship anything because they're very worried about people not trusting them. Yeah. And so some companies are bureaucratic and they just take forever to ship something. They don't maintain what they ship. They may make a big deal about an event, but nobody even knows how to go and use that feature.

52:05Yeah, they get abandoned. Exactly. So perplexity has those advantages of being very small. And towards the end of last year, we found that like AI coding tools have made it much faster for us to ship things, which is honestly one of the reasons why we built a computer, because now even non-engineers are shipping code here by just pinging a Slack bot and asking it to fix bugs. So the iteration has just been like exponential. the moment i had where i became claw pilled was when i was working with it and i was like hey i want to build my network i know these 20 people in japan i had dinner with them during my recent trip i want to know who they know so check out linkedin other things and who they're associated with and make me like a mind map of it and then the next trip i want to meet with the next circle of you know those connections so i started asking it's like okay i got the results i was like great and it said, where do you want me to put them?

53:00And I was like, well, where can you put them? And it said, well, I can put it in a Google sheet. I can put it in a Notion table. I can put it here. I can give you a PDF. I can give you a CSV file. Or I could write you a CRM. And I was like, yeah, sure. Make me a CRM system. And it made a CRM system. And I think that becomes, I think maybe one out of a thousand people working with AI have had that experience. Maybe it's one in 10 ,000 where your agent says, I'll make you bespoke software. Yeah. Have you had that yet? And do you see that as a part of computer that when a person needs a spreadsheet, you don't launch Excel or Google Sheets, you just pop up a spreadsheet?

53:40Yeah. Well, we have a board meeting tomorrow. Okay, I'll come. I'll pitch it to the board. Sure. Our computer made the memo. Oh, wow. Yeah. And we had a partner meeting to pitch a partnership idea. And earlier, we would have a design team do the whole deck. Yeah. Computer just one-shotted it. I had a press briefing with a bunch of journalists. My comms person would usually... Sorry about that. Oof. Brutal. And then my comms person would usually give me a memo of what to say. Yeah. Computer one-shotted him. So... It's crazy. It's crazy. The context is so good because the memory's getting better, yeah?

54:19Yeah. So it's like, I know that journalist from the last time I know the board meeting, I have all the previous decks. Yes. When did that happen? I think it happened with Opus 4.5. The anthropic Opus 4.5. That was the inflection point when models started being amazingly good at orchestration and reasoning and tool calls. And Cloud Code brought in this new idea in AI that everything can happen inside a sandbox, a console, a terminal, with access to tools where tools are just command line tools yeah they don't even need to have graphical user interface so when you did that and when you organize around files and subagents and skills and clis the models started becoming becoming very good at handling the context so the context window no longer became a problem it just put whatever necessary into the context whenever it wanted to and dumped them away when it wanted to yeah and that made it like suddenly so good at doing very long orchestration tasks.

55:25Yeah, it's pretty crazy. I have every episode of This Week in Startups, all the transcripts, and then all of All In. That was one of the tasks I did, by the way. I can send it to you. I asked it. I want you to download every All In podcast since the beginning. And I want you to take a mention of all the public companies they mentioned during that yes i want you to have a histogram of the counts and i also want you to chart it across time and then i want you to analyze the impact on the stock price and the sentiment of what we exactly and it did like it clearly said are we moving stocks around google's stock going up yes prior to that you guys were talking a lot about google yes and clearly i said i made a bet publicly on the thing i said i am buying a bunch of google because i believe even though they're behind it's because they're too precious.

56:15You were kind of mentioning a company that might be too precious at times and doesn't release. I was like, that's that company. They need to release more. And I told Sergey, I was like, give us the good stuff. And he started giving us the good stuff. It literally gives you the timestamps of every single, and then I can go click on it and actually hear exactly. That moment. Yeah. Sweet. So that's when I was like, damn, I would have had somebody do this as a week long project. It would have been 10 hours a week of researcher. I'm experiencing the same thing. When I do research notes, I've created my own like mega prompt.

56:54Yeah. And it will go and like tell me where you worked before and who's in your circle, who your competitors are, who your friends are, blah, blah, blah. And then go, I try to find old podcasts is one of my secrets. If you're an interviewer watching, I try to find what was the person talking about five years ago, 10 years ago? and then over 10 years ago. And I've gone into interviews now with Michael Dell and talked about things he was talking about in the 90s. And it finds me some ancient stuff. Like you would pay a researcher, a producer, you know,$70 ,000 a year,$80 ,000 a year to do this. And they would have done a third of the job in 10 times longer.

57:32It's really gotten weird just in the last six months. What do you think the next six months looks like? I think the dream that what we are going to try to do is help businesses run as autonomously as possible. You know, everybody talks about this. AI is going to create this one person, $1 billion company. Some people say it's already happened because people pay researchers like$1 billion. But it's not truly moving the GDP by$1 billion. It's not truly creating new value. So the best way to do that is to actually help a small business, people who would otherwise drive Ubers for like extra passive income to like buy like a Mac Mini, set up perplexity personal computer and run their business on that or like run it on the server doesn't matter uh and actually make real money yeah hundreds of thousands or even millions a year and uh grow it have computer go and run your ad campaigns on instagram or google i mean integrate with sem and seo tools find new users and uh integrate with stripe charge them ship new features, have your own intercom integration for customer support, and have this all working well.

58:41You can be sipping wine in Napa. That's the dream that we... It feels awesome to say. Everybody thinks, yeah, it's already there. It's not there yet. Someone has to do that hard work. That's what we want to do. Yeah. It's a great vision because... When I watched startups 20 years ago, there were so many checkboxes they had to do. I have to find an office space. I got to put up a bunch of servers. I got to hire an HR firm. I got to hire a PR person, all this stuff. And now I talk to young founders. They got a three-person team. They've come out of A16Z, my program, Launch Accelerator, whatever it is, Y Combinator.

59:18And I'm like, okay, you raised a half million, you raised a million. Who are you hiring? And they're like, I don't know if we need to hire anybody. I'm like, if you could hire somebody, what do you hire? They're like, well, I do my own HR. I have this partner. And I'm like, how are you hiring anyway? And they're like, well, I put out an ad. And then it sorts and ranks the candidates. And then it emails the top 10, asks them a bunch of questions. And then I meet with the last two. And I'm like, that's what a recruiter did. The entire recruiting job has been abstracted. And a tool-like computer is going to make that even faster.

59:52There's so much work to do. a lot of connectors a lot of specific workflows people don't want to like learn how to write like you know essay long prompts you know it needs to be so quick and fast and autonomous you just set it up and done and you have an idea you can turn it into a business and start making money yeah it's it's an incredible future uh and it feels like it's right here do you how do you think about job displacement because you're actually making the tool that enables people yeah to be a solo entrepreneur and get to a million in revenue, but it's also the same tool that doesn't require them to hire.

1:00:25And we've had this debate a million times on the podcast. Do you, I'm wondering if like me, you have moments where you're like, oh my God, this is really terrifying. A lot of people are going to lose their jobs really fast. And then, oh my God, you can learn any skill you want. And all the things that were hard are now easy. I go back and forth. I'm 70, 80 % super positive about this, but I do worry about like 20 % of the time I'm a little worried. Where do you sit? I mean, America has always been about like entrepreneur, entrepreneurship, right? Like we've been about like trying to build new things, discover new things, go explore.

1:01:02I think this whole like Henry Ford came and built factories and brought in jobs and things like that and like put people into a box. But I think the reality is people, most people don't enjoy their jobs they're doing it they hate them exactly so there's suddenly a new possibility a new opportunity to go use these tools learn them and start your own mini business and if it pays for your needs for your or multiple years and lets you have a high quality life and good work-life balance and true feeling of agency and ownership and passion to like get your ideas out there i think that is even if there is temporary job displacement to deal with that sort of glorious future is what we should look forward to.

1:01:45I think you're exactly right. There will be some displacement, but then there's also going to be so many opportunities open up. And it requires the individual to not be passive. Exactly. They have to be rugged individualists. They have to be resilient. Yeah. And they have to be resourceful. And I think once you start playing with these tools, that's what happens. Exactly. You all of a sudden feel like... It brings out the best in you if you truly are in a good space. Yeah. Yeah. And then today, Comet for iOS is out. Yeah. I'm a Comet super fan. I required everybody. You were nice enough when I emailed you.

1:02:19I was like, can you send me some licenses? You don't remember. You sent me a bunch of licenses. I said, everybody put this on because it was$300 a month when you first came out with the Comet browser. Now it's free, I think, for all users. Highly recommend it. Highly recommend getting a pro account. It's only 20 bucks a month to get into perplexity, which is a joke. so you can get on board for nothing, less than a dollar a day. But what does iOS allow me to do? And how does it connect to computer? Because that's another thing I'm having. Yeah. Cloud code, computer. There's not a good enough integration with this mobile device yet.

1:02:54Yeah. So computer is already on the perplexity app. So you can just toggle the computer and start using it. Comet's uniqueness and perplexity for the company and the strategy is the fact that you can control the browser. So the browser also becomes a tool for a computer, just like your Google Workspace and all these other things. Until the whole world is organized around CLIs and tools, there's still a lot of tasks we have to do manually on the web, on the browser, open tabs, fill up forms, click on things, upload stuff. All that stuff, if you want to automate, you need a browser. You need an AI that can natively control the browser.

1:03:34So that is Comet. And that's why no matter how many other tools in the market exist, like OpenClaw or like Claw Cowork, executing tasks on a browser on the server side, along with all the other things is something uniquely Perplexity can do. Yeah. My dream is that you'll create an Android app that roots my Android phone. Yeah. And that you just take over and see everything. because one of the blockers I have now is some of the websites have gotten a little persnickety. Yeah. I don't want to mention too many, but Reddit, LinkedIn. Yeah. And like, they're just, I am a great Reddit user. I'm a great LinkedIn supporter.

1:04:16But sometimes like I need to get my email from my LinkedIn and I just need to, you know, find seven people at a company. is there going to be a solution between the linkedin and reddits of the world and the clauds and perplexities is yeah how is that i mean the negotiation going you don't have to speak about any specific ones unless you want to yeah but it feels like there's got to be a solution and i'm willing to pay for it as a user i'm willing to play reddit to allow my bot to show up and behave properly well i i cannot speak about any particular company but yeah we are happy to work with anyone right?

1:04:52So I think with Comet, our idea is to give people the flexibility to set things up on their own. And any official APIs that anyone's willing to offer, we're always happy to put that as part of computer. Here's what I think should happen. Let me see if you agree. And this is for Steve Huffman at Reddit. I go on Reddit. I do a pro account for 20 bucks a month. And when I do that, I can authenticate whatever tool I want to do a series of well-behaved things a certain number of times a day. So it's not unlimited. I'm not going to scrape the whole site, but I would like it to just let perplexity or computer go and just tell me, hey, what are people saying on this week in startups and all in subreddit, summarize it for me so I get the customer feedback.

1:05:44And I would literally name my agent and I would say I won't post on my behalf. It won't vote on my have just needed to do a couple of little read only things. This would be an easy solution or LinkedIn. I would like if you I already pay LinkedIn like 50 bucks a month like they should just let the $50 a month one work with computer. Yeah, absolutely. I mean, okay, this is for Satya Nadella. Let LinkedIn work with perplexity and the other players and we'll pay you extra. perfect it's a revenue stream don't you think api access for customers is a revenue i think so i think so i think i think fundamentally giving users a choice and setting it up as a win-win for both the business and the user yeah is where the world should head to yeah and and i would say the same thing applies to any any website in the world like if you want an ai to use it on your behalf it should be okay for because that's what the user wants i mean i have a paid new york times subscription, like, let me go in there and do, you know, whatever, 100 searches a day, a week, a month, whatever they choose.

1:06:48But that would make the subscription that much more sticky. Exactly. All right. Arvind, love the product. Anybody at home, it's just tremendous. Go learn computer and get the Comet browser. It has changed my business for the last two years. Love the product. And we'll have you back soon when you launch your operating system and come up with your own server and desktop server but business is the focus yeah yes all right great seeing you thank you we have an amazing guest arthur manch is here the ceo of mistral ai how are you doing sir great thank you for having me and so you're here at uh nvidia's big conference big announcement you're going to be working with nvidia to build models uh to open source, then what is the big announcement here?

1:07:37Well, we're announcing that we are going to be training the next generation of Frontier models with NVIDIA. It's something that we've been doing before with NVIDIA, with Mistral Nemo, something we did like 18 months ago. And the point for us is really to be able to produce the best open source models out there so that we can actually use those assets to specialize them through products that we do for our customers like Forge that helps us customize the models for the enterprise we work with in engineering, in physics and science, in making them better at certain languages when we work with governments, et cetera.

1:08:09And Mistral, obviously, based in France, you're the leading AI company there. What's it like running the company and building a large language model in Europe? Obviously, there's regulations and all kinds of considerations. Privacy, the French are known for protecting privacy. In the United States, we're known for taking it away. How is the landscape there? And What do you have to deal with there that maybe you wouldn't have to deal with in America? What's the pros and the cons? Let's say first, we have 25 % of our business in the US and 25 % of our researchers are actually here. So I actually spend a lot of time here as well as in France, as well as in the UK, in Singapore, where we are.

1:08:47So of course, it's different markets. It's markets where you have language, which is a topic where there's much more manufacturing. Manufacturing is a bigger piece of the cake than it is here. And I'd say our strength has been to also work with European companies that are a bit lagging behind and that wants to adopt the technology to leap forward. And we've been able to do that through a forward deployment engineering engagement, through our Forge product, for our studio product that allows to deploy agents that do end-to-end automation. But on top of that, the thing that we have announced today, like Forge, is something that is actually being used today with customers in the U.S.

1:09:24because they come to us with needs for post-training, for making models specifically good at financial services. And what's happening is that we have this product and we can bring the models to specialize them as well. And so your belief is specialized, verticalized models, healthcare, finance, engineering, different verticals will win the day or a global model will win the day that does everything? Well, you need general purpose models to do the orchestration parts, et cetera. But at some point, enterprises sit on a lot of intellectual property, on a lot of signals coming from physical systems, from factories, from tools.

1:10:01And it's actually not trivial to connect those systems, to connect those data to models that are closed source. If you have open models, you can actually add new parameters. You can make a lot of deeper things that you cannot do with closed models. You can also, and that's something that we do, not only do we work at the model side, but also at the orchestration side. We sit with subject matter experts to understand their needs and we build business applications that are fully bespoke to their needs by modifying the models, but also modifying the harness on top, etc. So we believe that eventually building on open source technology is a way to save cost, is a way to have better control, because you can see the thing on every cloud that you want, on your hardware if you want, you can deploy it on the edge if you want.

1:10:42And eventually, from a customization perspective and from leveraging your decades of IP that you've been accruing in financial services, in heavy manufacturing, like companies like ISML, for instance, they do benefit from working with us because we take their data and we build models that are specifically good for their purposes. this training data using experts to come in and refine a model. Most people don't know this business that well, but this has become a very large part of the industry. Obviously, Scale AI was doing it. They went to Facebook, lost a lot of the customer base who didn't want to send their data, I guess, over to Meta.

1:11:19We're investors in a company called Micro One that's doing pretty well in this space. There's other folks doing it. Explain to the audience what you're doing specifically for companies and how this training works in a verticalized way, and then how you silo that data. Because if you're working with one customer in aerospace or fintech, they might have a need set, but they may not want that training to go to a competitor. I can use a few examples. I think overall, the data segregation is super important. And the way we have solved that is through a portable platform. So our technology is a set of services, a set of training tools, a set of data processing tools that I can take and that I can put on the infrastructure of my customers.

1:12:00So suddenly from an IT perspective, and when we talk to the CIOs, they realize that from security perspective, the flow of data doesn't go, there's no data flow coming back to Mistral because everything stays there. Now, the way we then use that technology that has been deployed is that we're going to be working with the teams that is doing image scanning and default detection with ISML, for instance. and we're going to be sending forward deployment engineers, scientists, they're all PhDs, they know how to train models and they spend some time with the subject matter experts that can explain how an image is being detected, how do you detect defaults, et cetera.

1:12:35And based on that, we're going to work out what kind of data needs to be used to train the models that it's going to solve the task in itself. And so we send the technology, typically we send a little bit of scientists because you do need that expertise transfer and that knowledge transfer in between our teams and the vertical experts. And then we make sure that eventually our team no longer needs to be there to retrain the models, to get more data access, et cetera. So that combination of data segregation, expertise transfer, knowledge transfer is the one thing that makes us quite unique and allows us to serve the most critical use cases, the most critical processes in industries that actually need to take their data and put it into models for it to work.

1:13:15Yeah, this seems to be once the entire open web, what was available legally, gray market, etc. I wouldn't have you comment on that controversy. But we kind of exhausted what's in the open crawl. Yeah, we have. And it's time to actually either make synthetic data or actually use experts. Do you believe in synthetic data? And where does that work? And where does it fail? We use synthetic data as a way to warm up the models. It's a way to actually be quite efficient at the beginning. If you have a large model and you want to train a small model, you will use your large model to process and to produce a lot of synthetic data at the beginning.

1:13:57But eventually, you do need to have human signal. So the human signal is something that is always a bit costly to acquire because you need to talk to the experts. They need to give feedback to the machines. And so at the beginning, synthetic data allows you to do the compression, to further compress the models, at the end, you do need to go and get data that is produced by humans. So yeah, it's mostly an efficient way of training models to have bigger models that are used as teachers for smaller models, but it's not enough. And so you also need human signal. Arthur, we've seen an incredible explosion.

1:14:31We're sitting here on AO52 after OpenClaw, the year of our Lord, 52 days. When you first saw OpenClaw and saw the reaction of hackers, founders, startup CEOs, just the amount of energy and it racing to the top of GitHub with the most number of stars and likes and all these contributors, what did that say to you as an executive in the space who's been grinding on this for many years? What does that OpenClaw moment mean? Well, it resonated a lot with what we were doing with our customers because pretty quickly enterprises realized that if they wanted to make some gains with artificial intelligence, generative AI, they would need to automate full processes.

1:15:16And to automate the full process as an enterprise, well, you can use OpenClo, but it's actually not really enough because you have data problems, you have governance problems, you can't observe the process that is running, and you can't control it. In many cases, when you run a KYC process, if you're HSBC, for instance, one of our customers, you will want to have deterministic gates that are going to always do the same thing in a way that is observable and that you can guarantee the CAO that it's always going to go through these gates. And that's not something that OpenFlow is providing because it doesn't have the kind of primitives that you need to work on collective productivity, observable productivity, and to work on mission critical systems.

1:15:56On the other hand, the autonomy it gives and the autonomy it brings to people that are just individuals that are hacking together things is a way to also show to enterprises that if you set up the right control plane, if you set up the right sandboxes, if you connect to the right data sources, if you make sure that your access controls are well respected, then you can actually unleash the power of agents doing things for your employees. And that's going to work. Work on the platform because otherwise you will not be at ease when you're sleeping. It is definitely something you have to be thoughtful about.

1:16:27When I installed it, I gave it, just for my agent, root access to my Google Docs and my G Suite, my Notion, my Zoom, and my Notion and G Calendar, everything. And then I realized, wow, I can, with my enterprise edition of Gmail, essentially, I can just summarize for my entire 21-person investment company, every conversation going on in Gmail, and then correlate it with every conversation in Slack. And then I realized, oh my gosh, there's compensation discussions going on. There is a person on a pip who we put them on a performance improvement plan, perhaps, or something like that. Oh, I have to make sure nobody else can access this because The power comes from giving it access to data, but with great power comes great responsibility.

1:17:18And I think people are learning that in real time. Yeah, it's a big problem because the enterprise data is not a single thing that you want to put into a single system that is going to be accessible by everyone. And so you need to have this layer that actually understands what is in the data. You need to have a semantic of what can actually be proposed to HR or what can be proposed to engineering. And typically, compensation is one of these things. You want to make sure that the compensation data does not flow back to all of the enterprise because you're going to have a lot of problems if that's the case.

1:17:51And so what you actually need, which is hard to do, is what we call a context engine. So a mapping of where the data sits that comes with a certain number of metadata that is telling you that this data is actually not accessible to this part of the company. And if you actually have someone in engineering that is asking for something related to comp, the thing is actually going to tell you, look, you actually can't access that data. So that's hard. It's actually hard. You need to rethink entirely the way your IT systems are being connected. And at some point, you also need to think about your management because your information flow is completely different today.

1:18:26If you're connecting agents together with your data sources than it used to be. And suddenly, maybe you don't need that manager whose only purpose was to take information from the bottom and put the information on the top, etc. So there's some IT problems to solve and you need the right primitives, you need sound boxes, you need airbag, rule-based access control and these kind of things. And you have change to do. You need to rethink your entire customer service department because suddenly you actually don't need that much transfer of information operated by humans. All right. You have to go. You got a flight to catch.

1:18:57I have. It is so great to see you, Arthur. Continued success with Mishkril. Thank you very much. Cheers. I'm really lucky to have Daniel Roberts here. He's the co-CEO and co-founder, along with his brother of Iren. They are a publicly traded company. They started in BTC. Welcome to the All In Interview Program. Thanks, Jason. Pleasure to be here. Yeah, and so you started in Sydney. You and your brother, it was seven, eight years ago, and you got in early on Bitcoin, and all these Bitcoin miners wanted to have data centers, huh? Yeah, that's directionally right. So the thesis we saw was this explosion of the digital world, the growth in the online.

1:19:37And at some point, the real world was going to struggle. So we set about to build out large scale data centers. Yes, the first use case was Bitcoin mining. But as we said to our seed investors, use that to bootstrap the platform, generate cash flow, layer in higher and better use cases over time as they emerge. Here we are today with AI. We are swapping out all the Bitcoin for AI chips. When did you first start seeing the demand in the company shift from, hey, Bitcoin miners, we need some H100s, whatever it is, to, hey, we're this nonprofit OpenAI. Hey, we're this research lab. We need some AI compute.

1:20:16When did that start hitting? Look, we had a bit of a false dawn, I would say, back in 2020. We signed an MOU with Dell to start bringing out customers and compute. But in hindsight, it was too early. So we went back to Bitcoin, kept bootstrapping the platform. Look, I would say about two years ago and month by month, the demand just continues to escalate. And you were in so early that when you were looking at data center space in the United States, you were one of one looking at the space, one of two or three people looking at the space. They were trying to sell you on space. Yeah. Yeah. So we actually developed the data centers ourselves.

1:20:51So we go and find the land, we go and get the permits, we go and apply for grid connections. And we were doing it at a scale that just amazed people at the time. Like 750 megawatts is our flagship Texas site. Four years ago, it was unheard of. In the middle of the desert, we're building these big data centers. The traditional data center industry going, what are you guys doing? We're saying, we believe in the future digitization, high performance computing. And obviously now today it's paying dividends. Yeah, I don't think anybody could have predicted when ChatGPT came out. OpenClaw recently as a turning point.

1:21:25And then, you know, Microsoft, Google, and everybody embracing this. And that's your big partner, Microsoft. Yes, Microsoft's one of our early partners. We signed a$9.7 billion contract with them late last year. But as I was explaining to you before the show, that's 5 % of our capacity. So things are busy at the moment. And when you do these build outs, the big conversation today is no longer the number of GPUs putting in. It's just power. Power is the constraint today, yeah? Look, for many of the industry, it is. But for us, because we started eight years ago tying up all this land and power, it's not.

1:22:06So we've got four and a half gigawatts. For context, that's almost as much power annually as the Bay Area uses in its entirety. Wow. It's huge. So for us, the hurdle or the constraint is really time to compute. And that's emerging across the industry as well. And time to compute means tradespeople coming to West Texas, living in a trailer that you set up to then break ground on a data center, build foundations, build water cooling systems. Like this is hard manual labor going on. Yeah, exactly. Exactly. And this is the whole real world challenge to respond to these digital exponential demand curves that are unconstrained by the real world in terms of their appetite.

1:22:51And it just compounds. You need thousands of people out in these locations that haven't supported it. You put stress on supply chains. We're seeing what's happening with the memory, every aspect of it. So it's just permanent whack-a-mole, permanent solving fires to try and bring online this compute. And you get to spend time there. what's it like when you set up a town or you bring a thousand people or two thousand people to what's a pretty much remote small town you i'm assuming that like when you bring a thousand there might only be 500 living there right now so what are those towns like i'm it sounds to me like something out of like the gold mining era when people first you know uh went and were prospectors yeah prospecting town pretty pretty much i mean the barbecue is great that was the draw card but apart from that uh look we've always had a policy of hiring locals supporting the local community uh this year we're hitting a million dollars in community grants cumulatively yeah that's things like local playgrounds supporting the fire departments but we will hire locally once we can't find that trade locally we will expand the radius by 20 miles and hire out of that and so on and so on for us that's very thoughtful yeah and and these folks are coming say an electrician or a construction worker they're coming having built houses or you know uh maybe building um corporate offices and now they come for a tour of duty here and the salaries go up massively but they got to leave their family for a three-month tour or something yeah yes and no because typically where we locate is where there's heavy electrical infrastructure.

1:24:30Where there's heavy electrical infrastructure is typically where old manufacturing and industry has closed down. So we go in, leverage that sunk CapEx, rehire, retrain local workforces and bring a new industry to town in these data centers. Has that workforce now been completely depleted and we need to train another generation, a younger generation to be generation two belt and really embrace the trades? 100%. We're partnering with universities, trade colleges. Absolutely. And you go to a trade school, you go to a college, people are getting degrees in philosophy and English literature. They're going 50K a year in debt, 200K a year in debt.

1:25:13What's the starting salary for a trades person working on a data center, doing electrical or construction or HVAC. What's the ballpark range? Oh, look, I won't talk specifics, but they are going up. The price is going up. Depends on the level. But yes, there is a rush for a good way. I'm hearing 150 to like 300K. Am I in the ballpark? The lower end direction, you're right. Yeah. I mean, it's incredible when you think about it. There's concern about, hey, AI shaking jobs. And then on this other side of the ledger, can't find enough talent to service it. Talk to me about energy sources and how you think about that.

1:25:52President Trump, Chris Wright, the administration, that kind of started with, hey, clean, beautiful coal. Year two, they're like, all sources matter. Nuclear. Obviously, Nat gas is plentiful in that area. We obviously got a lot of oil. People don't know this about Texas. In the United States, the number one source of solar installations. Yeah. Talk to us about energy. So our philosophy has been sustainability from day one we have used 100 renewable energy since inception what 100 where how is that possible we use hydro in british columbia we use wind and solar in west texas in west texas where we're located there's around 45 to 50 gigawatts of wind and solar yeah the transmission line to export that down to the load centers in dallas and houston is 12 gigawatts oh so you go and locate to the source of low cost excess renewable energy monetize it into this digital commodity export it at the speed of light as tokens great arbitrage and the wind is producing a lot but it's harder to get from those areas where people are willing to put up i mean people don't understand how big west texas is it is an incredible amount of land and you're coming from australia we're also on the west side people don't understand exactly how much just pure nature land there is yeah undeveloped so much land and the issue is distance you've got to spend billions of dollars on this transmission connection infrastructure to move that power to where people actually want it.

1:27:19You can build wind farms, you can build solar farms, but if you build it in the desert and no one can use it, then what's the point? So the whole opportunity for our industry is to go to the source of that power and monetize it. So the data centers follow the wind turbines, the solar installations. How do you think about batteries and are you able to put those online? Because obviously you're going to have periods where, hey, it's not a windy day. In Texas, we have very few days when it's overcast. So that problem is pretty much solved. But you're going to have 50 days where the sun's not beating down.

1:27:50So how do you deal with the demand and softening that duck curve? We don't need to. The utility does that on our behalf. So this is why these grid connections are so scarce, so hard to get, and so highly valued. Because once you get that grid connection, the utility underwrites all of that variability. They guarantee you 24-7 reliable power. Got it. So on their side, they're figuring it out. Something goes down and they could fall back, even though you're 100 % committed to renewables. If they needed to fall back to gas or whatever, they have that ability out there. So you have that as a backup.

1:28:25A lot of talk about or a debate. Are we getting ahead of our skis? Are people slowing down? There was some talk about the OpenAI project, maybe downscaling a little bit. Is OpenAI a partner as well or? Can't comment. Can't comment. OK, so we'll read into that whatever we want. But are there pockets where people are saying, hey, let's slow down or is it still gangbusters? It's right up the end of the spectrum. It's gangbusters. We cannot meet demand. That's why the whole industry now is around time to compute. There are no idle GPUs in the world sitting in a data center. Yeah. And what's your take on when software makes, and this is a big discussion from Jensen himself during his two and a half hour keynote yesterday.

1:29:14We're sitting here Wednesday, I think he did his keynote on Tuesday. He was talking about, hey, software is going to make it 50 times more, lower the cost of tokens, 50x. And then you have transport also contributing to that. But when do you think the curve goes from parabolic to simply growing at a ridiculous level? Is there a slowdown coming or how are you planning for the future? Look, I think it's actually the opposite. I think it feeds on itself. So I'll give you one example. You go into ChatGPT today and you generate an image. You enter the prompt. It's like the dial-up internet days. It is.

1:29:49Right? It takes minutes. You know, I better get this prompt right. Yeah. Finally, two minutes later, it comes. Now, I'll give you an example. If we 10x the amount of compute available, which is an enormous task from where we are today, and those images take five to 10 seconds, are we going to generate more or less images? Oh, many more. This is Jevin's paradox. This is the theory of induced traffic. You build a couple more lanes, people start to think, well, maybe the distance from Bondi Beach to the central business district in Sydney terms would be an acceptable commute. Love the analogy. Yeah.

1:30:23So what do you think about, or what are you seeing? I mean, we're hearing that Nvidia, obviously they make the leading edge chips. They just bought Grok. So now you've got two of the leading edge chips coming out of the same company. But custom silicon becoming a big discussion. Has that started to land in the data centers yet? Obviously Google, don't know if they're a customer you can tell us, but they're making custom silicon. Amazon is making custom silicon. Meta is making custom silicon. Talk to me about that revolution. And is it actually making it to the data centers yet? Look, to various degrees, it is.

1:30:58They're promoting their products. They're trying to tie up data center capacity. So yes, there's multiple silicon looking for homes. I think it's fair to say NVIDIA has a massive head start. The ecosystem they've incubated, the standards that they're setting. So I would say the safest pathway to build out at scale early is to follow the NVIDIA roadmaps. But absolutely over time, we are seeing these chips emerge. And in terms of desktop computing, I don't know if you saw the announcement that Dell and NVIDIA are making a really powerful desktop, 750 gigs of RAM, a lot of power. You're going to be able to run some local models, open source with OpenClaw and open source coming from Kimi and a bunch of the models out in China.

1:31:47Has the hacker group, which I think you started in like I did, probably in similar time periods, people are starting to get really obsessed with having a$10 ,000 or$20 ,000 desktop setup and running this local. What do you think of that trend? I'm curious. Yeah, I mean, the breakthroughs we're seeing in software, the way it's distributing power to every man and woman in every house, and their ability to code and use products like OpenClaw, the generation of demand and appetite for computers at a local level all the way through to these mega data centers, it's absolutely real. And as we see the emergence of agents using more and more, as we see autonomous vehicles and other automation, robotics, it's absolutely going to compound.

1:32:25And what about nuclear? The Trump administration really seemed to flip the switch on a growing belief that, hey, wait, nuclear is pretty great. It's clean. It's the original renewable in a way. and these new modular reactors have nothing to do with chernobyl fukushima or a three mile island they're much safer they're a completely different architecture have they have those started to land yet and are you since you followed correctly in in the great state of texas where i'm from you followed correctly that time are you following nuclear i think you have to i think the reality is it's going to take a decade a bit longer by the time big projects can come into commissioning But now is the time to start that conversation, put in place policies, mobilize capital and start that ball rolling.

1:33:17Yeah. Do you have a data center going up near nuclear? No, not at the moment. Not at the moment. But you're actively tracking that activity? Yes. Yeah. This seems pretty inevitable. Yeah. Feels like it. And if that happens, what impact does it have on your industry? If you could, because obviously it's happening in China and people always put the Bitcoin miners, they were like the canary in the coal mine near the hydro dams and near the nuclear where there was excess capacity. What impact do you think this has if you could actually have small modular reactors next to data centers? Well, I think it just opens up the market and enhances the US's competitive advantage in this space.

1:33:56Like AI is inevitable. Robotics is inevitable. The reality is the correlation between human progress and energy consumption is really, really high over a very long time period. So if we can find a way to unlock new generation, clean generation as nuclear, and locate that more at the source and enable more compute on a distributed basis, all those use cases we just discussed become easier, more fluid, faster, and then you get that positive flywheel around Jevons Paradox and demand. Talk to me about the architecture today of Ethernet and data moving between data centers within data centers. That backbone is going through a paradigm shift as well, yeah?

1:34:39Yeah, it is. And Jensen coins the term, the data center is the new computer. So you need to step back and you say, right, this big building is essentially the old desktop PC we had under our desk at home. You go, right, how does that work? So all the cabling, the latency, the number of hops between each GPU, how they talk to each other, the fabric around InfiniBand, Ethernet. It's absolutely critical because every millisecond matters in terms of performance of that cluster. Yeah. And where do you think or what do you think of Elon's vision? It's obviously a longer term vision of putting data centers in space.

1:35:20And there's a couple other people working on it as well. Yeah, I mean, it's very hard to argue with Elon. He's been very right on a number of things for a very long time. I think sitting here today, it feels exceptionally difficult, given the cost of moving things to space, the challenges around radiation. There's a huge amount of engineering challenges, but that's never scared Elon before. Yeah, he's uniquely qualified and he's inevitably right, but sometimes he's late. He might be late to the party. He might be late to the dinner party. you might show up at dessert, but generally he nails it.

1:35:54How much of an issue is getting the data out of the data center to consumers today? Is that not something people are worried about when you're building something out in West Texas? All that data, fiber, all that's been taken care of, or does that become a gating issue at some point? So this was one of the big myths that we had to bust when we started this business, because everyone said data centers must be located close to population centers, metropolitan areas. Latency is really important. And we say, yeah, that's right. Latency is important. But the reality is in the US, Texas especially, there is fiber everywhere underneath the ground.

1:36:30Lots and lots and lots of it. And when you look at latency from our site in the middle of the desert in West Texas down to Dallas, the big carrier hotel, six millisecond round trip latency. What's six milliseconds? There's a thousand milliseconds in a second. We're talking six. it's adjacent. Yeah, it's not even, it's definitely not material. Listen, continued success and you're hiring a lot of people. Yeah, I think we've got 129 job advertisements up at the moment. All right, so everybody go to the IRAN website and listen, company's doing fantastic. Thanks for spending some time with us here at All In at GTC.

1:37:15Thanks, Jason. Appreciate it.