Lessons from Jensen Huang and Elon

I have nothing to lose . I came from nothing. I never even imagined myself to be doing all this. A twenty billion dollar company. Forty five million users. Over a billion searches a month. Built in three years by four hundred people. These numbers like doesn't motivate me. It's hard to get motivated by well. You want to get motivated by impact. This is perplexity with co-founder and CEO Arevin Shrinavas. No one's ever in a comfortable position. No one can relax. They forced Google to redesign their homepage, then bid thirty-four billion dollars to buy Chrome. More than their own valuation. Perplexity changed Google.com more than any product manager of Google has ever done. Now you look at AI mode, it looks exactly like Perplexity. He doesn't do defense. He doesn't do comfortable his words. shows. This is the single best podcast he has ever done. You know what I hate with podcasts? When people sit on the fence, Arav ind has really strong opinions in the show today. He says that Micron will be more valuable than meta. He says that the resistance to day SATA centers will continue and get worse. He says the biggest problem today is a lack of power. He claims that perplexity has changed Google more than any Google PM. You want opinions? This is the show for you. Aravin was on Stellar Form tod ay and this was such a joy to do. But before we dive into the show today, if you're a finance professional, you know the month and nightmare chasing down missing receipts and fighting with outdated tools that your employees hate using. It's time to enter the era of Nirvan. Nivan is an AI-powered travel and expense platform that gives you control and real-time visibility into every dollar spent. The experience is seamless for employees too. They can book a trip in just seven minutes, which is a fraction of the forty-five minute industry average. 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Oh yes, a special offer one thousand dollars off Vanter at vanta.com slash two zero vc. That's V A N T A dot com slash two zero V C for one thousand dollars off. You have now arrived at your destination. Aravin, dude, I am so excited that we get to see this. We've done one remote and then we did one at Founders Forum last year. So thank you so much for joining me in person. Thanks a lot, Harry. It's a weird start, but just roll with me on it. I asked this of the best founders that I meet, are you motivated more by the fear of failing or by the thrill of winning? Thrill of winning. Why? Because I have nothing to lose. I came from nothing. Like I I never even imagined myself to be doing all this. So my life has already been extraordinary beyond any level of imagination. I was just in India like doing my undergrad and you know, just just training neural nets with graphics cards that people in the labs were using for playing video games. It was all for fun. You know, my path led me all the way here. For my mom, just getting a job was success because we were not we were financi ally lower middle class in India, which is not even like lower middle class in U K or the US. And so from there, all we wanted to do was get a job in Google. Being an engineer at Google was considered a win. And so I'm I'm already doing remarkably well compared to that ambition we had as a family. So there's really nothing for me to lose. That's why any time I try to act like I'm trying to avoid failure and being on the defense, I remind myself that like that's the stupidest thing to do. It's bet better go all in and try your best, be on the offense all the time. Attack, attack, attack. That's that's that's my m moto. When you review then, what are you not being aggressive enough on today? Well I think today, maybe in the early days, we'd be very, very loud on social media talking about perplexity with Google and I I used to do that myself a lot. And some people don't like me for having done that. Today I'm a lot more measured in how I talk about our products, our competitors and stuff like that. But it's not a lack of aggression or anything. It's just that like it's that that is boring. People already heard that enough from me. Aaron Powell Do you regret the being so bold in your messaging? No. So it's not a nuance and maturation of message, it's uh that's stale and I need something new. Not just that. I I kind of don't think it's a relevant framing anymore. We worked on search. Perplexity started out as search. We built the first answer engine in the world that people know perplexity even today. If you mention the name perplexity, people will think, oh, that's an answer engine. We built a lot more things after that. We built a lot of agents, browser agents, deep research, computer. We built so many products after that, but we're still known product manager at Google has ever done. Make that argument for me. Well nobody ever wanted to ship an answer engine at Google. Nobody wanted to tinker anything on on the interface that made them two hundred fifty billion dollars a year. And then now you look at AI mode, it looks exactly like perplexity. There's there's not even any difference like the font, the citations, the specific building of inline text, inline hyperlinks, suggested follow-ups. The whole experience is literally looking like perplexity. Except Google to be what it should be. I believe that the frontier is where the money is. The frontier in AI is not about answering questions anymore. It's about actually going and doing work for you. You know, like we still have the state of the art deep research in the world. And that's actually where people subscribe to pay for our pro or Max products is not for getting answers in the in the traditional way. They're asking for sophisticated research reports. They're asking for agents that go and do things for you. And so we wouldn't have been able to do all that if we were sitting in twenty twenty four thinking we have everything settled here. We're we're good and comfortable. No. The answer engine was always a legion for the frontier products we built. You need something, right? Like think about it. Every company needs to have one successful product to build the next set of products. In AI, nobody can sit comfortably thinking they have it all sorted out, including anthropic. If anthropic thinks Claude Code is already a win, in six or twelve months from now they won't even be around. It's an uncomfortable fact about the whole field. Would you argue today? You just told me, if you don't mind me quoting you here before we started that you think open AI isn't ready for an IPO. Would you have believed you would be in a position to say this two years ago when nobody ha wanted to deal with any product other than ChatGPT? Think about it. So anyone, even in such a massive advantageous position , can be put in a position where they're no longer the kings. They're fighting from behind. That's the state of the field. It's less about perplexity or anthropic or open AI not having modes or having modes. Can I push back on you that? Yeah. I would stand by two years ago, even when they were a domin and they are still a dominant consumer product. But I would stand by it because I don't think they are financially ready. When you look at the the balance sheet of that maybe maybe I'll decouple that and I'll decouple that. Let's decouple that being like financial readiness for an IPO versus perception of a dominant leader. Yeah. Do you perceive them as a dominant leader right now? Yes. In what? Consumer search. Well, except there's no money there, right? It's been commoditized. Like for example, why why are they going all in on codecs? Because that's where the money is. We're doing the same on computer, Anthropics doing the same on Claude Code. Google doesn't yet have a product in this category, but I'm sure they're gonna come after that. Meta's trying to launch hatch for two hundred dollars a month. You see what's happening, right? But it that there has to be more money than just code, codecs, claw code. It's not about code. That's the main thing. The money, at least the non ad vertising. I'm I'm not talking about advertising revenue. In non advertising subscription or usage based revenue, the money is in whatever is the frontier. Today the frontier is about going out there and doing things for you. Do you not think then that there will be a hundred to two hundred billion dollar advertising business for open AI? Yet to be proven. Let's work through the categories of advertising. Who's the number one advertiser on Google? Amazon. It's the number two, booking.com. Number three or four, I think Sixpedia. So how much do you think booking.com spends on Google? Sixteen billion, something like that. Some crazy amount like that. How do you book your hotels or flights today? Do you book it on ChatGPT or do you book it on Google? Google Exactly, right? So the interface. The interface is less about conversations and more about exploration. So when when the decision making is more subjective and vibes based, you don't need an objective answer engine. And you think about the other category of advertising, direct to consumer products, fashion. Where is most of that advertising budget going into? It's going to meta, Instagram. Because you're just browsing, you're just like Doom scrolling or whatever you call it, right? And so the chat interface doesn't capture that user intent, that user behavior right now, which is why it was never a great fit for advertising . It also fundamentally corrupts the trust that people have when they go into a product and they want the accurate answer, which is what you know perplexity is known for. And then you're like, hey by the way, you ask for the best protein shake , but by the way, these are good protein shakes you you can check out. It kind of like hurts the trust that people have in your platform and your product. That's another ca reason why. If you think about it, like like what Meta or like I think some other companies in the past have tried to put ads inside messaging apps and emails and it's never really worked out. It it works out in China in WeChat because there's no other way for them to fund the whole thing. So the the the whole economy and and user behavior has been optimized around gamifying. It's not how things work in America. So I I'm bearish on advertising to really take off in in the chat interface. I'm happy to be proven wrong there, but I'm bearish on that. There are two areas that I want to unpack there. The first and just taking kind of chronologically and how you said them, money's in the frontier. The more I hear this, kind of the more I question it, because I think that we dramatically overestimate how important frontier models are to do quite basic work. Yeah, so frontier doesn't mean uh frontier model. Frontier just means whatever is the the frontier outcome you can have right now with AI. Greg Brockman recently tweeted, the model is no longer the product. And it's funny because you know that as a leader of a frontier lab, he has all incentive to say the model is the product. And that's what Google people tell. I think one of the Google people keeps tweeting that model is the product. And so the reason Greg is right is because if you take codecs or perplexity computer or clot code, what is that?'s It it's an orchestration. system It takes a model, pairs it with an agent harness. And what is an agent harness? Think of it the the simplest way of describing it is like rules for how the agent loop should run. What are all the skills and sub agents and connectors and tools it accesses? Without the harness, you don't necessarily capture and convert the intrinsic intelligence in the model into valuable output tokens. The output tokens, if you if' youre're literally just a reseller of model tokens, you have no business. Because the model will get commoditized. So even if you're a model builder, you don't have a business. As an infra layer, you have some business on serving those output tokens. But as an application layer or a model builder, you don't really have a business if you're just a reseller of tokens that come directly out of the model. You have business if you know how to take the model, ground it in valuable context, orchestrate it with a really good agent harness, connect it to the right set of tools and connectors, whether it's personal connectors or business connectors, and provide the experience to people in one single unified system. The way we differentiate ourselves at perplexity is we don't just orchestrate across tools and files and connectors, we also orchestrate across models. That is the differentiation that anthropic and open AI cannot claim because you wouldn't find GPT Fi Fi inside the Claude Code harness. You wouldn't find Claude Opus four, seven, or eight inside the codex harness. These are competing with each other. You would find both these models inside Perplexy Computer. That way we can increase the token value per watt per user. If you assume that whatever decides the do like the price, the dollars is the power of watts fundamentally, that's the thing that nobody else can subsidize other than the government, you know that whoever provides the most valuable output tokens with the least amount of power expended to produce them generates the greatest value to the end user and has the most pricing power, has the most value. And so that is the orchestration problem to solve. The most important metric in AI is token value per watt or user. What does it mean for the value of open AI and Anthropic if model is not the product and it becomes a utility, something you can switch into and switch out of the yeah? Everyone thinks we're all building m the model layer or the race. We're not actually. I would even argue that building models is a way to stay at the frontier, but you have to own an interface in which valuable AI output tokens are generated, the most valuable tokens. It doesn't have to be the product. This is the single most important thing to like unlearn for most founders, and I had to do it too, which is to be successful in AI product layer, whether you're a model builder or not. It's not about building something that gets a billion users. That mentality has to completely shift. There are a few power users who are propelling this token economy right now. If you look at like all these crazy stories of how there's this one engineer who got Amazon to spend like half a billion dollars a month because of some stupid way they set up like agent loop inside clock code. Okay, maybe that's a mistake, but there are real engineers in meta in other companies spending like ten million a year per engineer on these coding tools. There are users in perplexity computer. There's one user I think who spends upwards of like ten thousand dollars a month, something like that. Crazy. And not like wasting it. They're not wasting money. Their business runs using agent loops that are running inside these harnesses. And they use these products in sophisticated ways that I I couldn't even conceive when we were building the product ourselves. Even internally , inside our own company, there are some people who've set up these kind of like multi-agent hierarchy and agent loops that looks like its own software architecture. And I often just ask these guys to come explain to the rest of the company, hey, like what are you doing with these tools? Like you clearly are consuming it way over you know what we thought the average person in the company would do. And the single biggest differentiation between those who use agents a lot and those who don't is whether they run repetitive cron jobs. Whether you use AIs as one off tasks, you just delegate a task and then it gets done. That's like kind of using it for like deep research or like whatever, right? Like one single task, versus the AI is like continuously monitoring something for you. The AI is continuously like triggering based on certain events and going and doing certain things, giving you alerts. You set up workflows that keep running for all the time. Every time you get an inbound email, like or every time there's a latency spike, it has to identify which part of the code base cost that it has to go and do the root cause analysis and then identify the right engineer. All these things, th this is where the frontier is. And so going back to my main point, these products are not going to be used by you know 100 million people. But they will generate revenue that's going to be higher than the advertising revenue of Google or Meta. It's going to happen. I do just want to focus in on a specific element there. When you were saying like the power users, because I think one of the core numbers is actually Mark Baniol said they spend three hundred million on anthropic, which works out to be about three. It'll be interesting to know from him if that three hundred million came from you know, what is the distribution across employees?aron Powell So it works out to be that was on developers within Salesforce. So it's about three point eight percent of developer salaries. What percent of developer salaries do you think will be spent on tokens in twenty-four months' time. Because that fundamentally changes the value of open air and anthropic. If it stays at three point eight percent, they will not be five trillion dollar companies. But if it's a hundred percent like Brandon at McCaw said it will be in a year, they will they'll be ten trillion dollar companies. Well I think they can certainly be ten trillion dollar companies, whether it's gonna be a full percent of the developer payroll today or not, because there's a lot of nondeveloper work that 'll also be done with agents. And that's actually what we focus on for perplexity computer. We're not going after the developer market. We're going after anything that m non-developers do basically. Your finance department or your corp dev or your like sales reps or your data science teams. That's actually even bigger market. Like think of it as like clot code multiplied by ten. That that's the size of that market. If I push you on developer salary spend, what percent of token spend as a portion of salary do you think we'll see in twenty four months? It's hard to say. I think the costs are gonna go down. That's why it's hard to say. Do you think the costs will go down? Because this is the kind of the challenge that we've had. We thought when we went from chat to agent that costs would go down and token costs would go down. They've gone up. Yeah, for now. Help me understand that and how that changes. I think in software you kinda wanna pay for the frontier. It's kinda like if you know some engineer is awesome. If you know you have like a the next Jeff Teen. Would you rather hire that person and not hire people who are medium engineers but not Jeff Deen level with the same amount of budget you have? Yes. Let's say you had a million dollars. You could hire five people worth two hundred K, or you could hire one Jeff Teen and pay them a million. What would you do? One Jeff Deen. Yeah. So I think you would pay for the frontier. But what stays frontier keeps changing. In twelve months from now, let's say, thought experiment, there is an open source model as good as Opus 4.8. You still have to pay for inferen ce. Nothing is truly free. But it's gonna be like let's say ten times cheaper than Opus four eight. And when you pair it with the right agent harness and all the connectors, GitHub, everything, all their developer workflows work fine. Why would you assume that the token spend is going to be still high? It's not going to be. For the same things you're doing today. It's not going to be. But there might be a different set of things you might do with the frontier that you're not conceiving today. My prediction would be There is a large swath of people that is now bearish on your frontier models who open AIs and your anthropics because they're realizing that you can actually do a lot with open models for a fraction of the price. What you're saying is actually that is true, but we will still pay for the frontier and so they will still accrue great value. And I think this distinction it feels like a contradiction. It's not though. It feels like two things cannot be true simultaneously. But that that that's not quite the case. In fact I would argue that the frontier is increasingly gonna be a thing that very few individuals might even want. Like you could argue that after a point like it's not even interesting that AIs can write software. You you you we've normalized it, right? Let's say that that's going to be the case. Instead of companies being built with like tens of thousands of software engineers, unlike the past, there'll be a lot more companies with smaller software teams and each of us will be using a lot of AIs. That's actually good for the world. We'll be seeing a lot of different businesses. We'll be seeing allocation of software labor in places that was never even possible. Whatever is the frontier is gonna be things that AI is going and designing chips, AI is designing drugs, AI is figuring out how to build robots, AI is figuring out how to cure cancer. These are applications where you don't have like ten million users. It's like a few companies. But the effect of that work will touch a lot of human lives. I think to me that that's where the frontier is headed. You could also see that from the moves that Frontier Labs are making. Anthropic bought a wet lab. Could be for the talent, could be for the infrastructure to run like wet lab experiments. But imagine taking all those tokens and putting it in the mid training instead of just tokens from GitHub. So then that's gonna produce something interesting. Don't laugh. Is there an asymptote to frontier problems to be solved? I know that sounds ridiculous, but if you are continuously on the chase for the next frontier problem, you get to cancer, you get to climate change, and my word, I hope they solve both in like heaven, that's a huge amount to solve. But if you're on the treadmill of continuous on it, is there an asymptote to that? Well there's no mathematical argument to there being a cap on the amount of economic value one can create with AGI or ASI like systems. And Elon Elon has a good argument for this. Like he where he says money loses all meaning in a post AGI economy because you be producing an abundance of energy and labor and fundamentally the economy is grounded to energy and labor. If you can produce an abundance of them, well what meaning does money have? And so I I don't think we run out of things to solve at the frontier. I think we're always gonna be creat like like why did people even wanna understand the universe? Like like why did we wanna understand subatomic particles, quantum physics, black hole theory, you know, the origins of the univer But we still went ahead and did it because that's kind of what the purpose of humanity has always been to understand the unknown. You know, David Deutsch is famous for saying this, right? Like we are the only species capable of being curious about what is already familiar. Like you can stare at a fruit and you know that it's a mango and like you know exactly like how it tastes, you know how it looks, you know the shape, you know what seasons it grows in and and stuff, but you can still look at it and ask one more question about it that you haven't asked before. Other animal species cannot. Once they have it in their mental model what it looks like and touches and feels like, they're gonna ignore it. It's it's no longer interesting to them. Can I ask you you mentioned about agent usage and you said if you do repetitive tasks versus one off, say cron jobs. I think some said it's we're gonna have twenty four seven AI and you know they've talked about a hardware product that's gonna come out. Do you think we will have continuous agents running? Yeah. I think so. And I think that's kind of why I believe the orchestration problem I I talked about, maximizing the token value. Can you just help me on that? Sorry, when you say the orchestration problem.. Yeah So so okay, so there are like four objectives intelligence and accuracy, and then privacy and cost. You know, these are all competing with each other. So you can you could argue that you could max out on intelligence and accuracy by building giant, giant data centers and spending a lot of power to run you know run them. And uh you could miss out on privacy and costs because everything will be centralized and you're gonna be paying a lot. You could argue that everything can run locally, and so that'll be good for privacy and costs, but may not be frontier intelligence, may not be frontier accuracy. The solution is to figure out a sweet spot, you know, use local models when necessary, use server side models when necessary, and orchestrate across local models and server-side models, grounded in valuable personal context. Sometimes the intelligence might already be there, but the system might not work because the harness isn't grounded in the right set of tools. So build a world class harness that can even make an okayish model appear great and be able to use the right model for the right task and the right part of the task, sub agents, and even like utilize the compute we all have in our own devices all with That is an orchestration problem, a router, an awesome router, a master orchestrator router. Now if you do that, you can realize the vision of a twenty four seven AI without people freaking out about b going bankrupt. Because no one's gonna be able to afford a twenty four seven AI, frontier AI running on the server. Imagine you s turned it on and you ne you could never switch it off unless something crazy happened. The thing that most people worry about those AIs is like, oh, what if it does something crazy? But the real concern actually is the cost. Nobody's going to be able to afford a cron job at the fidelity of a few seconds that that runs all the time. The bottleneck there is actually orchestration and local compute. And so I believe one needs to build a continuously learning local model that can save you on like compaction, context windows, and try to preserve as much compute locally and rely on the server side frontier only when necessary. And keeps learning, keeps adapting, keeps evolving. And that model is not just a model, it's a model plus the harness, plus the local chip and the compute and the ecosystem of devices it controls, that system is gonna be your own intelligence. Essentially the data center moved to your local device and you you get to control it, you get to own it. You don't get to worry about somebody like spying on you or looking at all your tokens, very valuable personal tokens. Imagine you have like very sensitive deal materials. Let's say you're doing a deal and then a frontier lab has all your tokens that you use to like write a memo. Imagine somebody could hack into that server and steal your deal from you. You wouldn't want that, right? I'm gonna be honest, I think there's much more valuable things for people to steal from London London based VC. But yes, I can make it. imagine like you know you're already making your moves for the four billion dollar fund. E everyone has certain levels of like you know sensitive stuff. And and so I think that's where I believe that the 24-7 always on agent is going to be realized by the company that wants to play the role of the orchestrator, not the model builder, not the frontier model builder, but the orchestrator. And I think that's what that's what we want to do. Computers has been positioned explicitly as the agent orchestrator. The musicians in the orchestra are these sub-agents that utilize these different models. Think of them as the instruments and uh the tools, the connectors, the models, these are all the instruments. And the musicians are the sub agents, and the symphony is the work, and the system is the orchestra and and computer is the orchestra conductor. That's how it's been positioned. So what it orchestrates keeps evolving, right? It changes. It changes from you know models to files to tools to chips to devices. But it doesn't even matter. Like you don't care as long as it orchestrates things correctly and and maximizes the token value for what? Per user. If you can solve this problem, you will capture the most economic value in AI. Long term. Short term, it might look like, oh, like this other lab's revenue is growing, you know, exponentially, this, that, but long term, this is the one objective that truly matters. Who is best positioned to do that? I believe it's us. Because you have the incentive of not token maxing. You have the incentive of delivering the most value to the user. Every time any part of the AI stack improves, our product improves. Since the beginning of the year, Enthropics models have made tremendous progress. But what's also true is that our revenue has more than tripled since the beginning of the year. Tripled since this beginning of the year. And a lot of thanks to model progress made by Anthropic and we also brought our burn down thanks to OpenAI competing with them and bringing down the cost of the same capability. And now with progress in open source and local models and local chips, we're gonna move some of the inference back to the local devices and bring down the cost even more. Every time any part of the AI stack, whether it's chips, models, harnesses, any of these gets better, our system improves tremendously. And if our system improves tremendously , our users love it and they pay more. They spend more. And so our business grows. To your question of who's best positioned to win in that world for that objective of being an orchestrator is the one whose product or business benefits from other people's progress at any layer of the stack. If Jensen produces a better chip, it's great for us. If Dar io produces a better model, it's great for us. If Apple produces a better device, it's great for us. And I c I I love the fact that we are able to be a very posit ive player at every layer of the stack and not have to rely on any one person to win. We said kind of server side versus uh uh on device. When we look at server side, a lot of people want an AI infrastructure bubble, which I think is funny stupid and moronic. To what extent do we have a data center supply problem today from what you see? I think the biggest problem is actually in power. So what f let's break down. What is a data center? Is it like that you just buy like a bunch of chips from Dell or Supermicro? No, that that's just one part of it. You actually have to go secure land or you have to lease something, lease a property, you have to s buy a bunch of turbines to generate power, or you have to work with like power suppliers, grid suppliers. You also have to work on cooling. There's a lot of other work you gotta put in that is far, far slower. And so usually what's happening is there's a lot of lead time to doing this. And um the models that are already in use today, these have been trained with the hopper generation. So the blackwheel generation model, I think the first model that's blackwheel generation category is um mitos. And that's already scary. Like people are already like freaking out about it. So imagine that everyone pre-trains a model on like a million or like you know hundreds of thousands of black wheels. Now those models are going to be far more powerful than what exists today. And then the vererubens are coming next year in full capacity. Like like all the data centers of varirubens will be in next you know, used next year. That model will be even more powerful. So I think there is a certain physical build-out time that always bottlenecks frontier capabilities. That's why there's a value in that layer. Whoever knows how to do this puts together a bunch of GPUs and chips and networking and power and cooling and actually like orchestrating all this software layer on top and is able to convert that into frontier output tokens. That vertical integration has a lot of value. So that's why the markets are pricing infrastructure companies with a higher PE ratio than companies like Meta, for example. Even though Meta builds a lot of infra, it's valued as a software company. But when we see like you know Meta's capex spend and it wanting to increase in the last few days and thinking about raising more and more money to increase cap ex spend, I get it with a lot of the AI providers like your open eyes or anthropos, because they are making money from their AI products. For Meta, the CapExpend correlates to increasing accuracy on ads, which is like a six to eight percent bump in revenue. I I get it. But for the CapEx spend it doesn't make sense. Yeah. Well, I believe like they're they are they are understanding what the market 's saying, you know. They I don't think they're dumb to not see what what's being said. I think they're introducing a lot of subscription products. Basically the company needs to not just be a social platform, maximizing engagement and turning that into ad revenue, right? And I think that requires them to launch a lot of like agents, subscription based products, and maybe even a meta cloud that that rents out service like what Elon's doing at SpaceX. And and maybe once they do that, the the narrative might change. But to go back to my point, it might not be inconceivable that Micron, the supplier of HPMs, might be more valuable than Meta in the next six to twelve months. It's already at like a trillion and meta is like one point three to one point four trillion. Can you help me understand that? Because uh memory is already a massive bottleneck, it's increased five X in price in terms of the cogs. Right. But people are going, wow, micron is fully priced at this point. Why is it not fully priced? Because it's still the bottleneck. Whatever's the bottleneck will command the price. AMD is doing really well because CPUs became a bottleneck again. Agent loops, agent harnesses are all running on CPUs. The tokens are produced by the frontier models on GPUs, but whatever work let's say like Claude generates a coding script that decides to download five hundred files from different websites and then you know munges a lot of data and transforms it in certain ways and generates a plot and then hosts it on a website that you can share with your people. All that computers running on CPUs. Agents are using CPUs more than humans. And so suddenly there's a rise in enterprise CPUs. And the beneficiaries of these are like Intel and AMD. So then they get to be the bottleneck. Like whoever's going to be the bottleneck will win. And so infra is the bottleneck right now because there's a lot of demand and we just don't have the supply. And so whoever supplies memory, SSDs for storage, CPU compute, suddenly these are all like interesting. Like they're more important than companies that are just building data centers and not knowing how to turn that into valuable outputs. Aaron Powell Do you believe your Nebius and your core weaves will be a sustainable multi hundred billion dollar company in the future, or is it solving a short term supply problem? I certainly think they can be sustainable. Yeah. I think there are some I don't like look, I don't know particularly which of those is gonna win. And there's also other players like Crusoe and Firebird and there's a bunch of companies. It's all about being resourceful. You gotta take power from areas where there's a lot of natural resources and the cost to bring up the data center is pretty cheap and the time to bring up the data center is cheap. And your service is reliable. if Like somebody commits to buying 100,000 GPUs from you, the service should be pretty good. And uh you should be able to secure the supply ahead of time, plan well. And I think some companies are even innovating at the power layer, generating their own power is one way to bring down the margins. And so I think there's certainly like value in that layer because it's hard to replicate work. That's how I see it. You could argue that open AI can do all the work that core V was doing. And that's kind of what they wanted to do with Stargate. But why is Core V more successful at building data centers than OpenAI? It's hard to do. It's operationally intensive. Yeah, operationally intensive. You gotta focus, you gotta like spend most of your time secur ing permits, like figuring out power, figuring out like bottlenecks in the supply chain here and there and constantly plan ahead and like test all these systems c carefully, deal with like random physical issues that you know arise in like you know running a data center. There's something called TCO, you know, cost of operations. You gotta factor that in. So that said, I I I don't think there's value if you're just like a server renter. If you're just a GPU server rack renter, if you're just leasing it to different companies on certain hourly pricing rates, there's not a lot of value. You have to actually build some software on top, kind of like how AWS did. It's called Amaz on Web Services, not Amazon servers, right? You have to have some software orchestration on top that allows you to get software margins on top of what you're doing. I think that's why you're seeing moves like Nebus, like going for the AI model inference, you know taking open source models or hosting your models. That's a business model of certain other companies like fireworks and you know base 10 and all that. But you could imagine NeoClouds just going for that business. So I just had the co founder of Nabius on the show and uh the really clear takeaway was the challenge that he has, which is there's a huge amount of money that wants just capacity and compute with the awareness that he needs to build a full stat product if he wants to have a long-term sustainable business. That was a cool realiz ation for me. When I look at the inference layer, like you said, fireworks or base 10, how do you think that plays out? Do we have standalone hundred billion dollar companies in inference alone, or do we see that commodities? It's all about working backwards. Ten billion in revenue. Exactly. Ten billion in revenue, thirty to forty percent gross margins, good amount of net income, good cash flow. Okay, 10 billion in revenue is not that inconceivable for a company that can both do AI hosted inference and server capacity and data center build-outs very operationally well. You know, there there are some factors beyond their control, like open source models continuing to be awesome. If open source models stop to actually be good, where the gap between them the frontier is like more than twelve months, like fifteen months, eighteen months, then I don't think these companies really have a business model because they're only going to be able to rent capacity to open AI or anthropic. That's exactly what Roman at Nebia said. He said if consolidation happens and there's anthropic and open AI or two or three dominant providers, that is the biggest threat to Nebraska. That's correct.. Yeah But i y you gotta make a leap of faith assumption that the models from China or NVIDIA is making good progress on their models in Nimotron. You got so there there's gonna be enough factors in the market to keep consationolid as an outcome from from like stopping from happening. But you don't control your own destiny if you're those companies. That's basically the problem. Okay. So we can have standalone companies that are $100 billion in inference alone. So I'm just pillowing you for your knowledge. When we look at the model selection companies, like an open router or like factory AI just released that kind of model selection or model routing product, which did very well on launch. Is that a hundred billion dollar companies in the model selection and routing business? Probably not. I think you can just be a provider of a router. Actually most of the business value of open router is less than the router even though the product is called open router, it's not routing across models there. It's actually just routing across different endpoints of the same model. Okay, so maybe let's ask this question. If you wanted to use Claude , Opus , or I don't know, like GPT-5 as developer, why would you not want to just use it with your own API key versus using it inside OpenRouter? Number one argument. The single simplest argument as to why you would want to do that is model fallbacks. Sometimes your API keys might not have the rate limits, or even if you have the rate limits, there might be an error on open AI servers that you know don't guarantee you the response time you need to run your application. And open ro uter would go and they would pay for capacity for like one year ahead with the funding they have and secure the rate limits and multiple endpoints across multiple different providers of OpenAI models, be it Bedrock or Azure or OpenAI themselves. And so that routing is valuable. It's essentially an infra problem they're solving, which is reliable token supply. It's not actually, oh, like they're lowering the cost by deciding if this prompt should go to like GPT or Clot or something like that. That's not what they're actually selling to the developer. That's not actually the business model. And then for a lot of these Chinese open source models, you you probably don't want your API tokens from going to like let's say you don't want your API tokens going to China. And let's say you don't have the bandwidth to work with like different inference providers or verify who's good and you know who's not. You're just trusting open router to take care of all that and then, you know, they're gonna like supply the tokens to you. So it's routing, not at the level of like, oh like deciding which model is cheap for what task. It's more like a reliable token supply. And I think there's some value in that layer, definitely. Uh otherwise they wouldn't have these many users and these many trillions of tokens being routed a month. But it's not like you know high gross margins business. It's i the way the business model works for them is actually they would secure a discount from the model providers by guaranteeing a lot of supply. But they would still charge the user listing price on the API and that difference is their margins. We spoke about bottlenecks and you said about HBM, hyperam with memory and micron and the value that they have today and what it can be. What bottleneck will I think power will remain the bottleneck. It feels like that to me. Unless something dramatically changes in the way data center build-outs happen. I actually believe that there'll be a lot of resistance to building data centers. It's because people incorrectly think that data centers consume a lot of water or eat up a lot of power, which is no both both are untrue. Satya even made the statement that it it's like a can of water or something in terms of how efficient these companies are. Do you think that's why they're putting up resistance to them? I don't. I think it's because it's a symbol of job losses, increasing wealth in the world. It's a lot of things. It's a lot of apprehensions, fear about like what's gonna happen, channelizing in so many different ways. Sometimes it's channelizing through hatred for wealth inequality and like wanting to tax people. Sometimes it's channeling through like concerns for the environment and like climate change. Sometimes it's channelizing in a way where you're all like, oh like the price of the grid is going up because you guys are building all these data centers and then or like I'm paying more for my phones and laptops now because the RAM prices have gone up because you guys went and bought all of it. So I think there's a lot of different ways in which it's getting channelized, but the common sentiment is like like a pretty bad sentiment about AI. Do you think it will be meaningful to the development of those data centers? I think right now forty out of a hundred are not being developed because of public resistance. Yeah, so um th that's where the power bottleneck is. You could see maybe certain countries seize the opportunity for this and allow these model builders to go build data centers there. Elon's going to space to do that. So that's going to be an interesting experiment because there's a lot of energy from the sun that can be harnessed there. There's a lot of natural resources in other countries. Regulations might be more friendly. So we're still gonna see data center build outs. It might not not happen in the US. But the fact that you have to solve physical problems, like you actually have to deal with the supply chain, the permits, securing power, like making sure like things work and getting the lead times lower and lower. You're not solving problems like cloning some SaaS apps here, right? Yeah, or like you're building a go-to-market team or like doing better marketing against the competitors' products. Yes, those are also hard problems, but these are like much harder problems where like you're not in full control of your destiny and you need a lot of capital and connections and like the right people, sometimes even like political help to unlock progress. And so that's why this will continue to remain the bottleneck in my opinion. And there's a lot of risk as well because if you do And you built out all this capacity and you're like, damn, that's I over built. That's something far more efficient that can run on on people's local devices, their MacBooks, their Windows PCs. Yeah, like you're probably freaking out then. How likely do you think that is though? It's probably like twenty percent, thirty percent chance. The reason I think there is some possibility is that because of the export controls. So the deep seek is not building with the NVIDIA stack. They're building with the Huawei stack. And because there are export controls on not just NVIDIA GPUs but also on HPMs. These architectures that that Deep Seek's building are far more like memory efficient. They've made innovations on the KV cache to be really small enough that you can host it on the SSDs and you don't need high bandwidth memory for inference time. And they're gonna have a completely different architecture for inference, completely different architecture for storage, because they're not allowed to use the three D NANDs. So their architecture, it' not justs the model architecture. The model architecture is already pretty different. They've made innovations on the attention layer, they've made innovations on like the training algorithms so that it it doesn't consume a lot of interconnect capacity. So they they basically their whole stack is getting vertically integrated to their hardware and their chips and their fabs and so on. And so that's a very different bet from what America's making. Do you think the Sport controls have helped or hurt us? Jury still out. Short term is helping because my belief the only reason where why we uh there's even like a twelve month gap between open source and frontier is export controls. And so it's definitely helped and and and definitely like companies like Anthropic lobbied very hard for it. But there is a chance that because of that they now get really good at the physical layer. And one advantage they have is they can actually build data centers a lot, lot fas ter. Power is not a problem. Permits are not a problem. People are not a problem. Labor is not a problem. Expertise is not a problem. And so by forcing them to go out there and build all this, you're converting them into a far more like potent competitor. Do you think we still dramatically underestimate China's capabilities? I think so. If AI is like not just digital, that's also physical AI. You gotta build fabs, robots, chips, and harness the energy really well, package it into local devices. I think they have a lot more advantages than America. How important is it that we have our own TSMC in the US? TSMC is actually there is a fab of TSMC in Ariz ona. Like not a lot of people talk about this, but TSMC is investing like hundred, fifty billion dollars into building American fabs. They've already invested forty billion dollars or something like that, sixty billion last time I checked. So there is a TSMC in Ari zona that's coming up. There's also um Intel. And that's why you know American government owns 10% of Intel, Nvidia and Softbank own five percent each. So there is a lot of investment going into an American Fab as well as TSMC is investing into its American fabs. Elon's building TerraFab. Like I think it people have woken up to the importance of building fabs. But this is also why China is uh particularly very, very competent. Given the capabilities of China that we just mentioned that really articulately, I know it's a ridiculous question but sodder. If I were to say to you your job is to make sure America stays competitive, what would you do to ensure that you retained competitiveness in an increasingly strong China? I think take physical infrastructure a lot more seriously and continue funding it and not like have all these I I wouldn't say meaningless, it's more like not propagate fake news around data centers about how data centers are polluting and contaminating water or like they're sucking up all the water and actually be fact driven. And so, you know, I hope our product helps there. Like you you can you can go to perplexity and ask any question and get fact checked on your assumptions. But yeah, like it's very important that we educate the public about what's actually going on. In in a language they easily understand and not fear monger. Okay, like not be like, oh, like all their jobs are gonna go away. Like this, that like there's gonna be lots of amazing companies that are going to get built with far fewer people getting multi-billion dollar , multi-hundred million dollar valuations with like 20, 30 people, and propelling like trillions of dollars of new GDP. Like let's talk about how to enable that. Let's talk about how to build that and create a more positive future together, instead of oh like ninety percent of the jobs are gonna be gone, like you're all gonna get screwed over by our our models and like it's it's our it's our moral duty to tell you all this, like blah blah blah. Like that doesn't make any sense to me. Like you can't win by saying that and also like complaining about not being able to build data centers fast. Do you think we've done a complete disservice by having the marketing message that Dario has had that all jobs are going and it's all doom and glo Yeah, I think so. I mean, I think you know they have contradictory messages in their own like different social engagements so far, where the most recent one I heard was there is no evidence that AI is taking over jobs. There there needs to be a consistent communication around this. And I also think that very little is being spoken about how AIs can help you build companies in a very, very different way. Like the current AIs, genic AI. So many things you would hire people for you can do it with agents. But one way of looking at it is like, oh like what happens to all the jobs. But the other way of looking at it is like, hey, like I never had the chance to go build out a company on this idea that I've been having all this while and maybe me and a group of friends can come together and build this and can you guys figure out a way to give us compute credits or you know, Amazon gave a lot of compute credits to a lot of startups. Like when we started Perplexity, we had like around two hundred thousand dollars worth of Amazon credits and G C P credits and Azure credits that almost like together accumulated this was worth like a million dollars in compu credteits. Now in in today's world it's gonna be like a million dollars of computer credits. And we're doing that. Like we we're funding this thing called the billion dollar build where we're giving a million dollars of computer credits to any group of people who have a credible path to building I think we should do more of that. Yeah, that that's the right thing to do. We should do a lot more of this. Because you want new companies to be built. And even if they're worth multi hundred million dollars, it's good. If there are thousands of them, like that's a lot of new GDP. I I spoke to Anne Bordetsky before the show and she said how AI pilled the So will companies follow the same headcount trajectory that they have always followed and we will just solve new problems or will they be dramatically more efficient with a much fewer number of people? Definitely they'll be dramatically more efficient. And and that's why I I I am a believer in building a lot more efficient companies. Not an and being an example for all these companies ourselves. Like people should look at perplexity and be like, oh, like with four hundred people, you can build like a multi I, don't know, like twenty billion twenty billion dollar company. And so that means with like forty people, I could probably build a billion dollar or two billion dollar company. And that that that's totally doable. Totally doable. And and so for us maybe that means is with four thousand people, we could be worth two hundred billion. We could be worth two trillion dollars with like ten thousand people. That doesn't mean it's bad for all the hundred thousand people we did not hire for a typical two trillion dollar company. I would rather have those hundred thousand people be split into groups of like hundred, thousand groups like that, and each of those thousand groups are worth a few billion dollars. That's awesome. And I I think a lot more people need to be entrepreneurial. There are people who would be bad employees in any company because they're just like difficult to work with, they they don't listen to like instructions, so like they don't follow like roadmaps or not they're not like easy to collaborate with. But maybe the the flip side of that is those those are the kind of qualities that founders typically have. Aaron, there is a population and a very large population that are not AI native people, that are not using AI to improve workflows, improve efficiency. What would you advise them? Get started. First steps get started and channelise your curiosity. You don't need to use AIs to do your existing work. If your existing work is boring to you, you probably won't enjoy it even if you use AIs to do it. You got a lot of heat for saying uh uh people don't like I didn't say if you actually listen to my interview, I did not say that. So people want clickbait articles and they take something I said in one sentence and out of context and make it into a headline. What did you say? I specifically said this. Hey, like there are a lot of people who don't enjoy their jobs. By the way, the fact that thing went viral was not because I was completely wrong. I think a lot of people resonated with the fact that I was actually honest in saying a lot of people don't enjoy their jobs and that has nothing to do with your economic position or standing in society. You might even be like really wealthy, but doing a job that you completely don't enjoy and like destroying like the peak years of your adult life working on something that is horrible or like like depressing. My point is that if that's you and if the reason you could never leave your job is because you were always worried if you how how would you build a company from scratch. Like there are all these things to figure out. How you have to hire a lot of people, you have to like set up an office, this, that. Like that's changed. For the first time in history, you can get started on an idea with like one or two other friends and maybe have a real genuine shot at building a billion dollar company. Totally get that. Everything that we've discussed today has been on the back of unprecedented demand up and to the right. We need more memory, we need more data center supply , we need on demand and server side. Everything's like up and to the right. Seeing some cracks in and Uber's saying, hmm, I'm not sure I'm getting the productivity gains that I thought. Microsoft aligning with them, putting a fifteen hundred dollar token budget. Do you think we will have a continuous up and to the right acceptance that productivity gains are unwavering, we have to do this, or will there be falterings along the way? I mean, I'm sure there's going to be falterings along the way and people are rightfully freaking out about token maxing, which is why I think you need some form of hybrid agentic inference. You need some amount of inference compute to run locally that you're not paying for tokens on How will the best companies of the future structure token budgets? My hope is that they don't have to understand that. They will be able to work with an orchestrator who does it for them. It's not going to be easy for you to constantly keep track of like which models are the best at what things and how do you allocate oh this is the budget for coding, this is the budget for finance, or like like how do you even understand like which models are good at each of those things and like how much do you spend on each of these divisions? You're not gonna be I I had a friend on the show the other day say that Google will be the token king. They can produce the lowest cost tokens out of anyone. They own full stack, TPUs, data centers, networking, power, procurement. Do you think that's true that they will be the lowest cost token producer? They have advantages, all advantages one needs to have to be that. But they underestimated the importance of coding models. And so they're far behind the frontier right now. So again, they could catch up. Totally capable, totally competent team. But today they're not quite at the frontier. I was shocked the other day I saw the Cloudflare announcement that now agent traffic has overtaken human traffic for them Why why are you shocked? It was quicker than I thought. Okay. Personally. I thought that would happen, but in two years, maybe not now. How does the world change when agent traffic far exceeds human traffic? I think people are just gonna have a lot more agency. But do websites go away? Does design not matter? Does the advertising model of the internet die completely? My belief is that the advertising model around like travel or shopping or like fashion are not getting disrupted by agents because the judgment is not objective. Anything where the judgment is objective, the transaction is based on objective judgment, that's going to get disrupted by agents. Anything where the transaction is more subjective, like the decisions are more subjective. Like like what is the best piece of furniture inside this this this part? Like why this particular table? Or like those kind of things.ly Probab for the mic you would buy an objective decision. The table, you probably are caring about the aesthetics of the room. I think that's kind of how I I feel the world will split and subjective things will still be ad based. Objective things will be agent-based. I watched your commencement speech on the back of speaking to Samuel at Excel and he said I had to watch it. So obviously it watched it. And one of the points you made was the defining skill of the A era is asking better questions. Yeah. What question is no one ask ing today that maybe everyone should be asking? I think people need to ask more about like, okay, assuming I have a lot of agency available to me, what do I do? Imagine like I gave you a headcount of like 100,000 people or ten thousand people and you know, enough compute credits to run those agents. What would you do? Like let's say I ask you, Harry, like, you know, let's say I g you have suddenly like ten thousand agents at your disposal. What would you do? I I remember you telling me, uh not me br but but in some episode of yours where you said you're only you only did this podcasting because you felt like you didn't have an arbitrage to go and deals a hundred percent. Well, I still do. I mean Okay, so you've gotten some amount of distribution. So now assuming that you have let's say you could spend hundred million dollars on a genetic inference and ground it with all the connectors and stuff and it's all working. What what would you do to m with that capability to um further your goals? Like what what what should your goals even be then? I I think that's the question I would ask. Assuming that in the next three to five years you're gonna be able to like delegate whatever digital task you want and and with the right harness and agents and like be able to delegate that. Fundamentally it would be uh to build an agentic infrastructure to be able to find, identify, outreach, set up, win, great investments, and have the media sit on top and power that. That is intensely difficult to do and would be the holy grail to investing. But like that would power what my end goal, ambition is. Yeah. So your goal is to be the around like a ten to hundred X larger fund, right? That that that's basically what I'm hearing from you. So that's like let's assume that's like a forty billion dollar fund from four hundred million. Then all you gotta ask is like assuming I have all the headcount I need to do this, like how much faster can I do it? I th I think that's how I would frame this question. I think Elon has like a similar thing he spoke about once where okay, assume that a task, somebody tells you a task is gonna take 10 years. Ask the question: what would it take to do it in 10 months? Maybe it's impossible to do it in ten months, but you probably get pretty far asking those questions compared to somebody who takes it for granted that it's it's gonna take ten years. All right, interviewer. Put it on you. What's your ten year and how does that look in a ten month time frame? I think our mission beyond any level of capitalism is to make the planet more curious. The product is always intended to helping people ask the next question. My goal is to truly realize that, like that level of agency that needs to exist in this world is quite not there. I think that needs to be grounded in numbers, dude, to make it like possible. Like it's like me saying, Oh, I want the best investments. Which is why a forty billion dollar fund is helpful. Sure, like I can say the same thing, like two trillion. You know, it doesn't matter, right? Like hundred X, ten X, thousand X. These are all like motivational milestones. Do you think Poplexia will be a trillion dollar company? Anyone can be a trillion dollar company. SK Heinrich and Samsung are worth a trillion last last couple Did you know Samsung started off as a grocery store? They started selling dried fish. The SK group started off as um textiles company. So anyone can be worth a trillion dollar company. And like you just have to work your way towards that. I mean the exact same logic for you that you laid out for how can a company be worth a hundred billion dollars. Okay, you said you need to make a ten billion dollars in revenue. Isn't that the same for a trillion? Like you need to make a hundred billion dollars in revenue? Mm-hmm. And there was actually some very interesting data that CO2 revealed. I don't know it recently, which basically says about the probability of reaching the next level of that. It's much higher. So when you're at a billion, it's like much more likely to reach ten billion, ten billion, much more likely to be a little bit Yeah. Like it it's m way more likely for a person with a hundred million dollars in in liquid net worth to become a billionaire than someone with ten million dollars. Are you not worried about the wealth inequality? Being blump, we both are very lucky now to live in kind of nice worlds and rarefied airs. Are you not worried by just how much money a very small number of people have and how hard it is for everyone else and that gap is getting bigger. I think the way to like ensure that that doesn't remain the case is to distribute the benefits more widely. By the way the people who are using our tools, like I've had an Uber driver. I'm I'm not even like making this thing up. An Uber driver in San Francisco once told me that he watched one of my YouTube interviews where I explained how you can build a product or a web app with an AI from scratch. Went on to do it and um used AIs to add like billing and all that. And that makes more passive income for him than driving Ubers. And so he actually reduced the amount of time he's driving Uber because he he loves wipe coding new apps. That that already tells you that for the person with agency and a positive outlook for the future, anything is possible. And so if you keep communicating all the negative things you can about AI and wealth inequality all the time and that's the only thing news and press writes about, I think it'll perpetuate and people will only think the bad things. And so it's very essential that if you think you're already doing well, it's very essential that you talk about what are all the things that can go well and give hopes to people who were once upon a time like you, like you I mean you were you didn't you you started this podcasting circuit like when you had nothing, right? So nothing. Exactly. So it's possible. So you gotta you gotta talk more about that than be like, oh I feel so guilty that I made it and now I'm like uh you know, what about all these people who haven't made it? Like you can also make it. I I think I have a more pessimistic view of actual general public, which is I don't think that many people have agency. I think a lot of people have victim mandates. I think they gotta help themselves. People will help themselves once they see that okay, like I kinda wanna be like this guy. Let me work hard. You need an example, right? It's not like nobody can become get in shape. Like it it takes discipline. You gotta get rid of bad habits. And now is the best time ever to change your life in twelve months. The ability to go from nothing to to actually build Yes. Look, I'm not saying everyone's gonna make it and everyone's gonna be worth a billion dollars. Isn't that the caption from this this show? Aaron , everyone's gonna make it. Anyone has the potential to make it. It's it's as likely for perplexity to become worth two trillion dollars as as a founder who's yet to secure your funding to worth be worth a billion dollars. Equally hard. You just have to give yourself enough shots at the go We have space , we have anthropic, we have open AI going public. It feels like someone's kind of shot the gun and the race is on. Is there enough money to fund There will be some reallocation for sure. There might be some holders of like SaaS stocks who would put it into Anthropic or something. Let's say you believe that Enterprise AI is gonna take off. You might wanna hedge between having a lot of Microsoft stock and Salesforce stock versus like putting some of that into anthropic. So let's say like Vanguard or BlackRock own like, you know, cumulatively they own like two hundred billion dollars of Microsoft and Salesforce They might be like, okay, I'm gonna take thirty, forty billion of that and put it into anthropic. Fine, you know. Not a bad bet to make. What happens to all the enterprise SaaS companies that are public growing Yeah, fine. They have to weather the storm. the next thing. If you're just selling the same software, you're probably not gonna be around. IBM is still around because they went and bought Red Hat and HashiCarp and now they're buying Confluence. So there are ways for these companies to stay alive and extend their lifespans and stuff. So obviously gonna be hard to preserve a brand that's as relevant. I don't think the IBM brand is that relevant anymore in terms of like evoking an emotion in people to go use their products. But as a business it's gonna be awesome. You know, it's gonna be fine. I have to finish on you said IPO in twenty twenty eight. I had to ask this. I woke up to this in my like you know group where we have a team WhatsApp and it's like, Oh it's gonna happen, IPO twenty twenty eight. I hope I hope it can be sooner than that. When do you know when you're ready? Like is there like a a billion an air? You're at five hundred millionaires an hour? More than that. Far far more than that actually. Really? Revenue growth matters much more to you than profitability? Today. I think in general by the way you can look at public markets. People want top line growth more than bottom line efficiency right now. Because it's very hard. It's it's rare. Well you definitely need one. You need to have a model in place to get the bottom line efficiency when that becomes the objective. And and you need to also like have a path to getting there. Significantly better in two to three years. We're training our own models, post-training it on top of amazing open source models. And that will bring down the cost that we currently spend on Frontier model tokens. We expect to continue to use Frontier models for designing new experiences and new capabilities that do not exist today in our products. But whatever exists today in our products right now, we expected to completely re rely on like models we own and serve ourselves. And that's all gonna be the best way to bring down the costs and increase our margins. Will the largest enterprises in the world all be fine tuning open models to have tailored models that are much more specific to them? Absolutely. Because it's in your incentives to bring down the costs. Does that not provide another bad case for the large frontier model providers? Frontier model providers will only remain relevant if they remain at the frontier. If for six months you're not seeing a new capability, it's bad for them. And so that's the uncomfortable nature of this field. You no one's ever in a comfortable position. Like I said in in the start, no one's no one can relax. This is fucking a hard sh it's got harder. It's gonna get even harder. That's the nature. It's just the the price is too big. Like you've never seen like like take anthropic. I think it's um worth like one to one and a half trillion some something in that range. That's basically the valuation of meta . And this all was created in like six years. Meta took like twenty years to build. So the price is so big and so no one can no one can be comfortable. And anyone who's winning today can lose tomorrow, including including the model providers. Previous year there was like a three month period where people were like, Oh perplexity, what's happening with perplexity? I don't know. Do you pay attention? Do you give a shit? Of course I pay attention to all of that. Do you care? There was one in particular in San Francisco . Yeah, we were voted the most likely to fail. Cursor was voted the second most likely to fail. OpenAI was voted the third or something. You don't give a shit? I I feel like we're all doing well. Cursor I think is getting sold SpaceX. OpenAI is going public soon. We tripled our revenue since that judgment was made. So brought down the burn by more than fifty percent. I also feel most of those people who vo sit on these like meetups and vote don't actually build anything useful I I agree. Well yeah okay we're gonna do a quick fire round because uh I could talk to you all day. First one, what's one widely held belief that you think is completely wrong? I think a lot of people are obsessed about like, you know, identifying a mode in the first year or two of their company. I think like the only shot you have is to move fast. Like we'll lose in in my mind, like moving fast is a way of expressing humility because you you're constantly making contact with the world and trying to question your assumptions all the time. Where are you still moving too slow internally today? I think we can be even more AI built. It's insane I'm saying this because we are building some of the most interesting AI products and internal adoption of our own products, our competitors' products can be even higher. And this is despite us being extremely agent pilled internally and trying to delegate as much to agents. And so um yeah, that's where that that's like a big area for my hope is that we can turn this company almost into an AGI . And um that doesn't mean no hum no humans work here, but there will be an AGI that has all the context it needs to run different divisions of the company in a semi-autonomous way. But some scaffolding provided by humans here and there. And and that's not gonna feel scary at all. We'll normalize that feeling very fast. It's just gonna feel like the 10x engineer is running certain aspects of the company. If I gave you unlimited money, what would you do today that you're not doing? I'll build data centers. You would? Yeah. In space. I don't have expertise to do that, but I would start with land on Earth. You know, I think there's a lot of land and maybe you can be resourceful in securing permits and power in different countries. But I would start there. You know, I I like I said, like I think physical infrastructure build outs is like the return of the industrial age again. Like like the forefathers who built the industrial revolution, oil pipelines, steel bridges, factories producing cars. All these things that we take for granted today were built by people who, you know, spent a lot of time thinking about how to scale these things in a cost efficient way. And so we need to do that a lot for AI. Yeah, that's what I would do. Of course, you you you cannot just be building infra. You need to be able to utilize all that infra to producing valuable output tokens to You can buy and hold for ten years. SpaceX, Anthropic, or OpenAI, three IPOs coming in the next few months, which you buy and hold for ten years and why? SpaceX. Why? Yeah it's an N of one company. Anthropic and OpenAI can claim they do whatever each other does. But SpaceX is the only company building space infrastructure for connectivity. Have you been on a flight with Starlink? No. You should. You will hate being on a flight without Starlink after that. Imagine we can record this I can watch this podcast while flying on a plane. Starlink lets you do that Yeah, like there's a lot of gonna like I I'm excited about possibilities to travel from Australia to like San Francisco in like 30 minutes. You know, all this feels like Aaron Powell What job does not exist today that will be incredibly common in five years' time? Aaron Powell I think it already exists. So the if the forward deployed engineer is definitely on the rise. I guess like people with a really good sense of like um quality control. Maybe a better way to answer this is like most jobs that exist, like valuable jobs that exist are usually like reincarnations of something that already existed. Like so I don't think we're gonna see completely You can advise your little sibling who's finishing university today and just done a computer science degree. One thing. What would you advise them? Stay curious. Don't give into like FOMO and trying to max out on something here in the short term. Don't go to Twitter and feel like a loser that people on um frontier labs are getting so rich and like you're everything feels hopeless to you or something. There is so much more to build. Like we are just getting started. The application layer era or like infrastructure build outs. There there's like a lot of opportunities. We are seeing more spin outs from OpenAI anthropic, you name it every single day. Do we have hundreds of these neo labs and vertical models? No. Not not a big believer in too many of them. I think you gotta produce some differentiation. That's the most important thing. Like like I I if would you call deep seek a neolab? No . Why? I think very stupidly for me I don't call it a Neolab because I I attribute neolabs to like spin outs from larger labs. I see. And kind of verticalized, which is probably wrong on both axes. But it's horizontal and it's not a spin out. build on NVIDIA GPUs or something like that, foundational bets. Makes or or somebody bu goes out and builds for robotics models. I think I think that's like somewhat uncorrelated and different and that makes sense for a lab, but I feel like they're like just labs for the sake of being lab and I don't think they're gonna make it. Can you paint for me? What was the most plausible story where Poplasty becomes a trillion dollar company? What do you do then? The orchestration layer the I mean accuracy in orchestration is like two goals that have been consistently true since the beginning of our company. So I think we'll continue to do that. We'll be orchestrating across devices, chips, models, tools, files, connectors, everything, right? So what would I do once that happens? I don't know, we'll we'll chart our path to ten trillion. Are you happy now? Are you enjoying this? Of course. Like there are so many things I could be doing if not for this. I think the process is what is is what motivates you. So you asked me, I think, somewhere in between you need to give me a number of where you want. I don't I don't work like that actually. Like for example, like the these numbers like getting to two trillion or twenty trillion are exciting, but like that that doesn't motivate me. It's hard to get motivated by wealth. You you you want to get motivated by impact. Who's the smartest person you've met, final one? You've met Jensen Huang, you've met the best of the best. I've been fortunate enough to who's the smartest? People are smart in their own ways. It's hard to compare. Like I met Jensen, Elon, all these guys and l like Bezos. What was it like meeting Elon? Amazing. I mean Elon's like a very focused person. P he might not appear that way on Twitter, but you know, with a lot of like random tweets, but he's extremely laser sharp focused on whatever he's doing at that moment in time. Actually the the one skill that as an entrepreneur that I would really like to take build from somebody like him, like tak e from somebody like him and have it for myself is that ability to just zone out of all the other things that's happening in your business or other businesses and just focus on that limiting problem right now. Like the bottleneck problem. And ignore everything else. It's very hard to do. Like l even within perplexity, I I cannot just focus on like one part of the business alone. It's very difficult. Like I'm I'm always looking at other things simultaneously. And his style is to just always look at the limiting problem and just ignore everything else. That's very hard to do. Because you you actually have to be really good at concentration. You you have to be really good at ignoring even important things which are distractions to your core objective right now? Was Jensen Huang what you thought he'd be? Far better. Jensen is so truth seeking, it's insane. I think he or somebody else told me or read in a book that he is so intense that he wakes up every day and tells himself that he sucks and like he's so intense that he tells everybody around him that they're thirty days away from going out of business. Think about it. Five trillion dollars guaranteed to make five hundred billion dollars in revenue in the next two years, has the most advanced chips in the world, and he operates with that mentality that he could be thirty days away from going out of business. That is what it takes to be Jensen Huang. And uh there's so much to learn from these guys. There's so much to learn. There's one aspect of like, you know, being comfortable where you are, thinking you made it, that that feels good to get here so far. But these guys are not stopping. Like I I don't think Elon wants to stop it. Uh if you look at his pay package for SpaceX, it's structured around creating a colony in Mars with a million inhabitants, building enough compute in space. It's not like motivating to be worth a ten trillion in net worth or something. If he does these things, I'm sure he's gonna get there. But it's more motivated around like making the impossible things happen and having like that long term outlook. Like you I think that has been the biggest thing to learn from maybe these two individuals in particular . A lot of people view this like entrepreneurship as like, oh if it wins, if if I win and I have a great outcome and I sell my company, I would have like generational money, I don't have to work ever again . And then what? You end up just staying at home and like your kids will obviously have like trust funds and they're not gonna get inspired watching their dad play Papel. Yeah. You're not gonna set the right example for them. They're not gonna be able to take your wealth and multiply it. Because they a they didn't watch somebody who actually did that. You did it before they were like adults. And so I think you always need to be doing something. Jensen said some s recently that he hopes to die on the job or something like that. Like that's the attitude you need to have. Like you got you you need to work forever. I was so upset though when Jensen said if I'd known how hard it was going to be I wouldn't have done it. When he did I didn't know if you saw that into you, I was like, oh Yeah. I think it's pretty hard, but you do it despite that. I think I think that's how it works. You do it despite that. Aaron, listen, this has been so fantastic to do. I so appreciate you taking the time while you're in London. So thank you so much for joining me. Appreciate it. But before we leave you today, if you're a finance professional, you know the month and nightmare, chasing down missing receipts and fighting with outdated tools that your employees hate using. It's time to enter the era of Nirvan. Nivan is an AI-powered travel and expense platform that gives you control and real-time visibility into every dollar spent. The experience is seamless for employees too. They can book a trip in just seven minutes, which is a fraction of the 45-minute industry average. 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