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

Our, you know, we have real chops in risk management and how we think about capital and risk exposure and allocation and all of that. And so we were really careful around that right from the start. So we weathered crypto winter really well and began to scale the company and immediately started to look for other use cases that you could use this compute for because crypto was pretty volatile. Yeah. And crypto was a question mark at that time. Absolutely. Yeah. I mean, Bitcoin was speculative and there were many other speculative projects. The only other people using this type of hardware, quants, medical researchers. So a good way to think about it is like the progression of products that we kind of started to work on you know first was uh um crypto but we immediately moved from crypto to cgi rendering and we built projects that would allow uh um folks that were trying to animate and render images um you know kind of what makes the movies cool right and and uh we started to work on that and then we moved to batch computing and started to look at medical research and different ways of using the compute to be able to drive science um and we just kind of kept moving up the stack in terms of complexity uh uh on how gpus

could be used and ultimately uh in like call it like 2020 2021 we started to really try to figure out how you can go ahead and use gpus for neural networks and that was not something that uh we knew how to do um and so we actually went out and bought a bunch of a100s and donated them to a A group that was working on Eleuther AI, they were working on an open source project with the thought that these guys are taking the GPU compute because we're donating it. They can't really get pissed at us if we're not very good at it initially. And that worked out really well because they can't complain about the SLA.

They kept telling us, like, we need more of this. You got to work on this. And that began to really give us an understanding of what was necessary to run scale parallelized computing. And, you know, that we went through it. I kind of feel like buying those initial GPUs was the tuition we paid to learn how to run this business. And then one of the interesting things is all of those guys went back to their day jobs because they were all volunteers working on this. They were like minded scientists. And when they got to their day jobs, they were all like, I want that infrastructure. It's built the right way.

That's the way that researchers are going to want to use it. And that launched our business. It was an amazing story. So you went from crypto to these researchers into academia and deep research. What's the next card to turn over in the poker game? Yeah. So what became very clear to us very, very early on was that the scaling laws were going to drive. And remember, this is really back in the, you know, 2020, 2021, before ChatGPT moment occurred. And we began to understand that, like, computing decommoditizes its scale, right? Like when, you know, anybody can run a GPU, but can you run a cluster that's large enough to train a model that can change the world?

And that's a different question. And so we really began to think about, like, how do you go about scaling up your delivery of this computing to clients, larger and larger clients? And that was the next card to turn is to think about it from a, OK, you know, there's a component of this that is going to lean into our ability to access the capital to be able to deliver our solution to the broadest possible audience, to the most sophisticated consumers of this compute. And that was really the next card is thinking about it as a business rather than as a engineering project to be able to deliver the infrastructure and the software and really everything between, you know, when you're thinking about what we do, we kind of live above the NVIDIA GPUs, but below the models.

Yeah. And everything in there, all the software, the integration of software and operations and observability and all the things that you need to be able to build a cloud that's purpose built for this one specific use case. Right. So we don't we don't do everything. We really focus on one use case, which allows us to do web servers. You got AWS. You know what? They do a great job. It's like it's a great solution. It was a brilliant solution to solve a problem. We just looked at it and said, there's a new problem. And let's go about let's go about looking at this problem and try and come up with a solution to deliver compute that solves that problem.

And when did the language model start dialing and calling you for, you know, capacity? Yeah. So our our our first well, our first language model was really a Luther. Yeah. But our first like large commercial was inflection. And so, you know, we work with Mustafa and Inflection, and then we really diversified from there into the hyperscalers, into, you know, OpenAI across the model, the foundation models across, you know, and just kept scaling and scaling with the belief that, you know, once again, the decommoditization of compute, the ability to deliver a solution and the solution is building supercomputers that can change the world and that's really what we began to focus on that was the lead into training, and now the world has gone through, you know, this moment where we've moved from research into the productization of this. It's beginning to work its way in from the fringe of organizations into the core of what they do, and you can see that every day in the amount of inference compute that is being driven through, you know, our infrastructure layer, which is just massive, which is just like one of the people are consuming it, not just building models, but they're deploying them and utilizing. I always think of inference as the monetization

of the investment in artificial intelligence. So when we see our compute being used to stand up the massive scale of inference that's hitting our compute every day. And like, You know, inference is when people ask the model a question, it comes back with an answer. That's an inference. Or when you ask the model a question and then to go do something, that's inference, right? And that's actually where you have the opportunity to really drive value outside of the model itself, but into the real world. And that's really exciting for us. That's what we like to watch. That's what I like to watch in terms of gauging the health.

What chips are those? So really, we are the tip of the spear in bringing the new architecture out of NVIDIA into commercial production at scale. And so when we were the first ones to bring the H100s at scale, we were the first ones to bring the H200s at scale, first ones with the GB200s, and now you've got the GB300s. And one of the things that's amazing and really fascinating for us is, you know, people are using the bleeding edge GPUs to train models as the new architectures come out. And then they take those GPUs and they move them into different experiments. And then over time, they move them into inference and they continue to use them in inference for a very, very long time.

What is the shelf life of a 100 right now?

yeah, you could buy them and have them shipped, I would assume within... 30 days or less. Nowadays, what's the wait like even for you, a loyal old customer? And is there a bit of a battle? Is there politics to who gets the servers? Like you see some like very big names talking about they got to get an allocation. Is it still a little bit crazy? What's it like to be in that category, having to buy something everybody wants?

Look, you know, I think of it as an affirmation of the business that we're in, right? Like the fact that we are attracting competitors means that the business is healthy and there's a lot of people trying to deliver this service because the need for this infrastructure, the need to integrate the infrastructure, you know, into the software layers to deliver it to artificial intelligence, either at the model level or the inference level or the application level or whatever, you know, level of the five-layer cake that Jensen's, you know, focused on. the fact that there are more people coming into this it doesn't discourage me yeah um as far as getting access to the gpus we show up like everybody else with a um you know we'd like to buy here's a po and we're ready to pay um the one what's the wait time like and is it just really competitive or not because i talked to jensen about he said i said how do you manage all these like big egos and names and companies trying to buy stuff and he said well they order it and we give it to them in the order in which they order it. Is it really like that?

It really is. Right. Like, you know, he doesn't want to be in the position of playing favorites or like that. That just seems like a bad place to be with your clients. Or auctioning them off. Yeah. So yeah, that would that that'd be crazy. Yeah. I don't I'm not sure that would be good for the long term business. No. Yeah. So so our our approach is you might get some sovereigns coming in and saying I'll pay double. They do that with Ferraris too sometimes. I guess these are the Ferraris of computing, right? In a way, they are, yeah. The Bugattis. Our approach is to work with clients across the entire space to find opportunities that are really interesting companies that can fit into our contracting requirements, where we're going to be able to go out and structure the debt that we require in order to go out and build infrastructure at this scale. And how does all that debt work? That is something that you guys specialize in.

Corporate debt. I'm in the venture business. People are like, why should I be in venture when corporate debt pays so well? Corporate paper is so huge. I'm curious how this fits in and like what interest rate people are paying on a billion dollars in infrastructure. What do they pay on

It means you have to say no to maybe some people who want to be in the box. Yeah. Some customers. We look at some deals and we're just like, they want to buy GPUs for a year. And I look at it and say, that's not a deal that I can do because it's too short for me to amortize the expenses. And so I won't do that. And they can go to another provider who maybe wants to take that risk on who has extra capacity. Absolutely. But our business is really built around the risk management of being able to get to scale. Because in my mind, during this period of disequilibrium, during this period where there were not enough GPUs in the world to provide the compute for all of the different use cases in artificial intelligence, the part that's important for me and for my company is to get enormously large so we can drive down our cost of capital, so that we have information flow coming in from all different parts of the market, the large language models, high-speed trading, search, all of these things. And they're feeding information back into us that is letting us know what the next product we need to build is or where they need help scaling or what type of compute they need. And all of that information flow is incredibly valuable to us.

What can you tell us about demand? There's been reports of, hey, maybe the Oracle Starbase thing with OpenAI has been downsized or maybe not. And then, you know, other folks, Microsoft is going big and Google. Google's going big. Meta's going big. And those people obviously have massive cash flow. Apple seems to be MIA. They don't seem to want to play. You've named a lot of really big companies with really big balance sheets that have the capacity to drive a lot of demand. Look, I have been truly steadfast in this for years now, for four years. the depth of the demand for the service we provide has been relentless and overwhelms the global capacity of the world to deliver enough compute to enable all of the demand for artificial intelligence to be stated. And that has been, we have been relentless about that.

Sounds like Nick's tickets during the Patrick Ewing era. They got up to 50,000 people on the waitlist. So if magically the waitlist went away, if the constraint went away and we just had a large amount of GPUs available, a lot of energy available, a lot of data center available, how much capacity would just all of a sudden come out of the system? Or would be deployed, I should say. So remember how we build our business through this box. And it's a five-year bucks. So if we had an air pocket, if demand were suddenly to disappear because of a technology breakthrough, because of a war, anything, right? The why from a risk management perspective does not matter. You have to prepare your company for what happens if it happens. And so by entering into these long-term contracts, entering into contracts with counterparties that have large balance sheets, you are or we are protecting ourselves and our lenders so that we are confident and they are confident because you can see how confident they are by the rate that they're charging us continuing to decline, that they're ultimately going to get their money back. And that is the one rule of lending. And so, you know, if just in terms of the capacity, if you

were unconstrained and NVIDIA Jensen says, hey, order as many as you want, what would happen? So, it's also important to understand the constraints aren't just GPUs. Right. Electricity. It's power shells, it's memory, it's storage, it's networking, it's optics, all of the things. And there's various throttles that will limit the- Memory is a throttle right now, right? Oh, yeah, it is. Oh, yeah, it is. Why? How did memory become the throttle? Well, if memory and it has historically been a cyclical business, right? We have seen these waves of demand driving up the cost for memory and then it collapses and then it drives it up.

It's a very boom and bust business. It's cyclical in its nature because the fabs are so capital intensive that people invest in the fabs, build a ton of capacity, and then overbuild if there's any type of turn down. And we've seen that cycle again and again. What's happening right now is the confluence of two things, right? One is, with all the demand for artificial intelligence and the corresponding demand for compute and the ancillary services around the GPU, the demand is through the roof. That's number one. Number two is that there was probably an investment cycle that needed to happen back in 2023 that would have brought on the necessary fab capacity to be able to serve.

Impossible to predict what just happened. Just with energy, it's impossible to predict what just happened. And now people are chasing energy. The data centers are going where the energy is. It's not based on real estate. It's based on where is there some wind. And anytime you have a very cap, not every, anytime, but many times when you have a capital intensive business, like, you know, building fabs, you will get this booming by. cycle, just like in energy. They overbuild. Yeah. Fiber. Yeah. I mean, there's a lot of examples of that. Our approach- In some ways, when you look at that, it's a beautiful aspect of capitalism that we're able to have a boom-bust cycle, that we're able to weather it, right? If you think just like capitalism from first principles, something like that happens and we have too much fiber, it creates an opportunity for Google to buy it all up or the next person.

Listen, it does a lot of things having a boombox 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 we watch movies every day and how we, you know, communicate and how we help 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. If 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 can 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 needs to pay their bill 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. And, 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 you two 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, told me just like how much was being uploaded every minute and it made no logical sense until you realized, well, there's 3 billion people, 2 or 3 billion people in the service and 1% upload or 0.1, 10 bips upload.

And it'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 ChatGB3 came out. And it was thirty two dollars in change. and now a million tokens cost nine cents. Yeah. Right. And so you just see like 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, okay, Captain.

Yeah. I don't know if you saw Karpathy'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 talked 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. That's amazing, right? Like 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. 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. I appreciate 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 in, 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. When 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. It'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, and 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 there's only then the user is going to ask the next set of questions it turns out 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 face 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 a 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 Claude or Gemini or anything else, an orchestra of all those capabilities, 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 computer is the ai itself is the computer now still lives inside of a browser have 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 now 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 and 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.

So 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. It'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 clawed 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. 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 yeah status i think it's very promising um my set my prediction is 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 You can 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. And more complicated stuff that accesses your data that's already on the server side, example, your Google Calendar, your Gmail. This is personal data still, but 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 uh it's all about choice and anyway when you're on your phone uh you wanna 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 and or on the server or this new dell that's coming out and i i really think the idea of spending ten thousand dollars on a powerful desktop will appeal to people if it lowers their right five hundred dollar a month yes claude bill yes this is an incredible savings plus you get the benefit yes of privacy and not educating the language models on your personal data yes and it's going to be it's going to be like you're buying a refrigerator your your internet modem like the cost for these will eventually go down 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'll 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. Like 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. yeah and charted for the max seven yeah and and charted over time you can so that's the objective but individually it's running a file system a code sandbox access to the internet it's having like its own html tools and like yeah so i think that's basically where you know models systems and files and connectors are all coming together you 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. yeah i mean they're stable yeah they're customizable and you're not at the mercy of apple's desire to contain the experience exactly or microsoft surface area as for hackers exactly you build something rock solid and it does feel like linux might actually become the correct the eventual winner it may not need to have a front end right the thing you could you could access the linux machine on your phone right it could be running ios or android it doesn't matter right 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

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

and 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 going to take care of all that 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 i don't have enough knowledge to know if you're abstracting that and people can just search across them and it's part of their perplexity subscription no we're not bundling subscriptions from into other ais yeah we just ping the models directly got it uh what you get in us is the perplexity or orchestration got it the harness

right so the when when when models are kind of specializing the 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 drop down 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. 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.

Yes, everybody does that, yeah. 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 released product at a pretty great cadence, huh?

Yes. 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. Right. 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. In what they ship, they may make a big deal about an event, but nobody even knows how to go and use that feature.

Yeah, 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 um and it said where do you want me to put them and uh 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 notion table i can put it here i can give you a pdf i 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 crs system and i think that becomes and i think maybe one out of a thousand people working with ai have had that experience yeah maybe it's one in ten thousand yeah where your agent says i'll make you bespoke software yeah have you had that yet and 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 yeah well we have a board meeting tomorrow okay i'll come and so i'll pitch it to the board sure uh our computer computer made the memo oh wow yeah 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 shot at it. I had a press briefing with a bunch of journalists. My comms person. Sorry about that. Brutal. And then my comms person would usually give me a memo. A dossier. What to say. Yeah. Computer one shot at him. So.

It's crazy. It's crazy. And the context is so good because the memory is getting better. Yeah. yeah so it's like i know that journalist from the last time yeah i know the board meeting yeah i have all the previous decks yes when did that happen i think it happened with opus 4 5 the anthropic 4 5 that was the inflection point when models were 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 sub agents and skills and clis the models started 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 suddenly so good at doing very long orchestration tasks. Yeah, 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 said exactly and it did like it clearly said are we moving Around Google's stock going up. Yes. Prior to that, you guys were talking a lot about Google.

Yes. And 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. You 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. yeah he's already giving us the good stuff it literally gives you the time stamps of every single and then i can go click on it and actually hear exactly that moment yeah sweet yeah so that's when that's when i was like damn like this 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 uh like mega prompt yeah 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 ten years ago and then over ten years ago and i've gone into interviews now with michael dell and talked about things he was talking

about in the 90s yeah and it finds me some ancient stuff like you would pay a researcher a producer you know seventy thousand dollars a year eighty thousand dollars a year to do this and they would have done a third of the job in ten times longer yeah it's really gotten weird just in the last six months what do you think the next six months looks like i think the 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 one billion dollar company some people say it's already happened because people pay researchers like one billion but it's not truly moving the gdp by one 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 yes 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 like intercom integration for customer support and like have this all working well you can be sipping wine in napa that's the dream that you know so it feels awesome to say everybody thinks yeah it's already there it's not there yet someone has to do that hard work yeah 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 check boxes they had to do i have to find an office space i gotta put up a bunch of servers i gotta hire an hr firm i gotta 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. And 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 ask them a bunch of questions and then i meet

with the last two and i'm like that's what a recruiter did like the entire recruiting job has been abstracted and like a tool like computer is gonna make that even faster 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 an incredible future. And it feels like it's right here. How do you think about job displacement? Because you're actually making the tool that enables people 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. And 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 yeah a lot of people are going to lose their jobs really fast yeah and then oh my god you can learn any skill you want and all the things that were hard are now easy yeah i go back and forth i'm 70 80 yeah super positive about this but i do worry about like 20 of the time i'm a little worried yeah where do you sit i mean america has always been about like entrepreneur entrepreneurship right like yeah we've been about like trying to build new things discover new things go explore uh i 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 uh i think the reality is people most people don't enjoy their jobs they're doing it they hate them exactly so there is 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 a year 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 i i think you're exactly right if there will be some displacement but then there's also gonna 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 you all of a sudden feel like it brings out the best in you if you truly are in a good space yeah yeah i and then today uh comet for ios is out yeah i'm a comet super fan i required everybody you were nice enough when i i emailed you i was like can you send me some licenses you sent? 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 common 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 uh computer there's not a good enough integration with this mobile device yet yeah so computer is already on the perplexity app so you can just toggle the computer and start using it uh comet's uniqueness and perplexity for the company uh and and the strategy is the fact that you can control the browser so the browser also becomes a tool for a computer yeah just like your google workspace and all these other things uh until the whole world is organized around clis and tools yeah 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 so that is comet and that's why no matter how many

other tools in the market exist like open claw or like claw co-work yeah executing tasks on the browser on the server side along with all the other things is something uniquely perplexity 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 I don't know. lockers 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. But sometimes like I need to get my in-mail 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 claws and perplexities is 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 so um i think with comet our idea is to give people the flexibility to set things up on their own yeah and uh any um 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 um 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, um, to do a series of well-behaved things a certain number of times a day. Yeah. 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 and I would literally name my agent and i would say i it 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 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 but that would make the subscription that much more sticky exactly uh

all right arvin 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 uh 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 scene 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 uh and so you're here at uh NVIDIA's big conference big announcement you're going to be work with NVIDIA to build models to open source them what is the big announcement here? Well 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.

It helps us customize the models for the enterprise we work with in engineering, in physics, in science, in making them better at certain languages when we work with governments, et cetera. And 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?

And 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. So, 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 for 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. because 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. And 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. We 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. And 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. We'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.

52 after OpenClaw, the year of our Lord, 52 days. When you first saw OpenClaw and saw the reaction of hackers, founders, startups, CEOs, just the amount of energy and it racing to the top of github with the most number of stars and likes and 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 what does

All right, you have to go. You got a flight to catch. I have. It is so great to see you, Arthur. Continued success with Mishrl. 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 um it was seven eight years ago and you got in early on bitcoin and all these bitcoin monitor uh miners wanted to have data centers huh yeah that that's directionally right so the thesis we saw was this explosion of the digital world the growth in the online and 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 non-profit OpenAI. Hey, we're this research lab. We need some AI compute. When 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. So 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? And 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, open claw recently as a turning point. And then Microsoft, Google, and everybody embracing this.

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. What's the starting salary for a trades person working on a data center, doing electrical or construction or HVAC? What's the ballpark range? 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 i'm hearing 150 to like 300k am i in the ballpark the lower end directionally you're right yeah 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 to to service it talk to me about energy sources and how you about that uh president 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 uh source of solar installations yeah yeah talk to us about energy

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?

Can't comment. Can't comment. Okay. 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. We'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 uh you know lower the cost of tokens 50x and then you have um transport also contributing to that when do you think the curve goes from parabolic to simply growing at a ridiculous level is 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 chat gpt today and you generate an image you enter the prompt it's like the dial up internet days it is right 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 ten seconds are we going to generate more or less images oh many more uh this is jevin's paradox this is the theory of induced traffic you know you build a couple more lanes people start to think well maybe the uh distance from Bondi Beach to the central business district in Sydney terms would be an acceptable commute. Love the analogy. Yeah. So what do you think about, or what are you seeing? I mean, we're hearing at NVIDIA, obviously they make the leading edge chips, they just bought Grok. So now you've got, you know, 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. They'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. Has 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?

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. And 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 Three Mile Island.

They're much safer. They're a completely different architecture. Have those started to land yet? And are you, since you followed correctly 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. Yeah. 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 U.S.'s competitive advantage in this space. Like 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? Yeah, it is. And Jensen coins the term, the data center is the new computer. Yeah. 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. 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. And 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 so i'm not uniquely qualified and he's he he's inevitably right but sometimes he's late he might be late to the party he might be late to the dinner party he might show up at dessert but generally uh he nails it how much of an issue is getting the data out of the data center to consume.

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 lots 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 yeah six millisecond round trip latency what's six milliseconds there's a thousand seconds milliseconds in a second yeah we're talking six yeah it's it's adjacent yeah it's it's not even uh yeah it's definitely not material uh listen continued success uh and uh you're hiring a lot of people yeah yeah i think we've got 129 job advertisements up at the moment all right so everybody go to the iran website uh and listen company's doing fantastic thanks for spending some time with us here at all in

at GTC. Thanks, Jason. Appreciate it.