The Exchanges, every show

Q bunch of checks as we have done for the last 10 years, and a next generation, or to your point, a back to the future era of venture capital where you co-found the business side by side? Can they run side by side? Or are we actually entering an era where we're back to the future era, as you say, where value accrual is in the co-founding and incubation side?

A Um, I, I think it's very hard for them to coexist inside of one person, and it's very hard to coexist sometimes inside of even one firm because, you know, the reason I'm sitting here at Periodic Labs, I work here three days a week. Every day from eight a.m. to 8:30 a.m. for the last year, Liam Doge and I have had a stand-up every morning where we go through the priorities of the company, and then we, we make them, we prioritize, we go and execute. I mean, the compute team of AMP is sitting upstairs, procuring compute for, for the periodic guys. My role models have always been the Arthur Rocks and the Bob Swansons and the Mike Marcola, personal computing. Effectively, the first CEO for the first year of Apple was Mike Marcola. He was an angel investor, and he was the one doing all the CapEx, you know, supply chain and capital and all of that stuff that allowed Steve and Jobs and Woz to focus on the product and the engineering. And, and that kind of deep partnership is what I get really excited about.

AI assessment note: “it's very hard for them to coexist inside of one person”

Q Dude, I'm confused. Help me out. I had Demis on the show the other day from DeepMind. He was like, yeah, I'm not sure if we're seeing scaling laws, but we are definitely seeing slightly diminishing, like, returns slash performance as we scale. So potentially, are we getting to a stage where increased compute is no longer leading to increased performance?

A Oh no, absolutely not. No, that's, that's not true at all. In, in certain domains that are well explored, like coding, for example, yes, there's an increasing amount of compute required to get an incremental gain in some eval that's super saturated. But if you said, Anj, what about material science? You know, I'm sitting here at Periodic Labs office. This is my incubate, like my latest incubation is called Periodic Labs. I spent three days a week here. In, in Menlo Park, we have a 30,000 square foot facility where we have LLMs that then predict new materials, new superconductors. We then have robots synthesize those new materials, and then we have, we have physical machines like x-ray diffraction machines validate whether those materials have the properties that were predicted by the LLMs, and then we pipe that, we, we, we pipe that verification data back into our training run You know, how many other times we need. And I can tell you throwing more compute at the problem is probably having super exponential gains right now per iteration. So it depends on which domain you're talking about, which modality. There's no saturation in superconductor discovery, for example, at all. The bitter lesson is holding is well and alive.

AI assessment note: “Oh no, absolutely not. No, that's, that's not true at all.”

Q bunch of checks as we have done for the last 10 years, and a next generation, or to your point, a back to the future era of venture capital where you co-found the business side by side? Can they run side by side? Or are we actually entering an era where we're back to the future era, as you say, where value accrual is in the co-founding and incubation side?

A Um, I, I think it's very hard for them to coexist inside of one person, and it's very hard to coexist sometimes inside of even one firm because, you know, the reason I'm sitting here at Periodic Labs, I work here three days a week. Every day from eight a.m. to 8:30 a.m. for the last year, Liam Doge and I have had a stand-up every morning where we go through the priorities of the company, and then we, we make them, we prioritize, we go and execute. I mean, the compute team of AMP is sitting upstairs, procuring compute for, for the periodic guys. My role models have always been the Arthur Rocks and the Bob Swansons and the Mike Marcola, personal computing. Effectively, the first CEO for the first year of Apple was Mike Marcola. He was an angel investor, and he was the one doing all the CapEx, you know, supply chain and capital and all of that stuff that allowed Steve and Jobs and Woz to focus on the product and the engineering. And, and that kind of deep partnership is what I get really excited about.

AI assessment note: “it's very hard for them to coexist inside of one person, and it's very hard”

Q Do you worry that basically the CCP is subsidizing a generation of Chinese models that are now being used by American companies whereby they have frontier models to essentially set where model capabilities can be and then have a real effort to make the open source Chinese models as close to those benchmarks as possible much, much cheaper?

A I mean, the engineering execution right now Up and down the stack in China is, here's what's happening, right? What they realized is that the AI scaling race is not a chip race. It's a full stack systems co-design race, where if you, if you can't compete head to head on chips for now, what do you do? You compete on systems design. You say, okay, we can't, we don't have leading edge chips here, right, yet. So let's try to compete on systems. The, you co-design the chip that you have, might be Huawei, with the computer infrastructure, with the training run, and then you design that, ok, to, to have a bunch of performance improvements at every layer of the stack, and then what you do is you do adversarial distillation at scale, where you take western models, and then you, from various different endpoints, you distill the, the state of the art, and then you try to get as many performance gains as possible on that data, And then you release that back out to the world as open models, and then you see what people react to, and then you get feedback, and then you do the next run, and the next run, and then you catch up. And at the point you catch up, you say, wait a minute, we're starting to be at the frontier. Why do we need to open source anymore? This is good enough for our local domestic needs. It's beautiful. It's actually, and, and that has actually, by the way, resulted in innov…

AI assessment note: “you do adversarial distillation at scale, where you take western models”

Q I'm sorry, what does that mean? An iron dome for inference in terms of sustaining it?

A It means that all inference is served, no matter which company is serving it, is served through a shared proxy that can tell each other when there's an attack happening on one part of the frontier. Think of it as an iron dome across the entire western front, right? And just cause you're here, you're in one company, you, you, you can't see that your model being served through this other company is being distilled. So it's a, it's a deployment coordination protocol. It's, it's basically my group chat that I've got with like, you know, a bunch of different founders, but scales, where people go, we're seeing this attack today, and others go, we are too. Let's coordinate on defensive response.

AI assessment note: “It means that all inference is served... through a shared proxy”

Q a sort of, uh, business strategy perspective. You know, maybe we saw Meadow with maybe the first big open source push. Um, you know, OpenAI has sort of evolved their tune. I, I've seen even Anthropix seems to be evolving their dialogue, um, a, a little bit. Um, how should we think about open sources as a, as a business strategy in terms of what, what's changed here and why?

A Oh, look, I, I don't think this is, this part is actually, is, is playing out beautifully along the same trend lines of all previous computing infrastructure, databases, analytics, operating systems, like Linux. The, the way it works is the closed source bioneers the frontier of capabilities. It introduces new use cases, and then the enterprises never know how to consume that technology, and when they do figure out eventually that they want cheaper, faster, more control, they need somebody like a Red Hat to then introduce them And, and provide solutions and services and packaging and forward deployed engineering and all of that around it. And which is why the arc generally in enterprise infrastructure has been closed source wins applications and open source tends to do really well in infrastructure, especially in large government customers, regulated industries where there's a bunch of security requirements. Things need to run on prem. The customer needs total control over it. Broadly, you could call that the sovereign AI market right now. Lots of governments and lots of legacy industries are going, wait, this open source thing is really critical to us. So I think Whereas two, three years ago, it was open source was viewed as like this, like, largely philosophical endeavor, which it is. Open source has always been political and philosophical by definition, but now there's an ex…

AI assessment note: “now there's an extraordinary business case for it”

Q Well, that is very, very kind of you to say. I do want to kick off with you today. I've never done this before, so I'm slightly winging it, but I spoke to Finn Barnes before the show, and he said, I have to ask Ask about your childhood. So what did he mean by that, and how did that lead to the founding of Ubiquity Six?

A I'm not sure which part of my childhood he was talking about. I had a pretty weird childhood. I've basically lived away from home since I was 10 years old, a few 100,000 miles away from family. I spent the ages of 10 through 16 in a boarding school in rural India that had no access to computers or the internet. Then I was dropped into the middle of a gleaming metropolis, which was Singapore. I did high school in Singapore and then moved to the U.S. For college at Stanford, and I think the aha moment for me that he was maybe referring to was when I put on my first VR headset as a freshman at Stanford and realized this was going to be way more immersive and communicative of a way for me to stay in touch with my family and friends that I'd left on the other side of the planet than anything I'd ever tried before, whether that was a video call or a texting thread. Everything seemed so limited up until that point, and then I knew that This new thing we had called six degrees of freedom, and whether that would be through augmented reality or virtual reality, being able to be physically embodied with the people you care about on the other side of the planet was the light moment for me, I think. And so that's what the company's focused on, right? How to create shared, persistent, mixed reality experiences for anyone, no matter what device they're on in real time. And I think being on th…

AI assessment note: “I've basically lived away from home since I was 10 years old”

Q I totally get that. Can I ask you, when we look at the bottlenecks around performance and progression today, what are the bottlenecks that really persist most significantly to you? Is it, is it algorithms? Is it data? Is it compute? Can you help me understand which is most lagging?

A So there's four or five. It's, um, context feedback, which I'm happy to talk about. It's compute. There's Capital, which you need to like, you know, continuously sort of deploy the compute and context feedback loops. And then there's culture. And I think that culture actually might be. The most important bottleneck of all time, but those are the four I would say. Now, look, algorithmic innovation, I think, is a function of culture, basically, because if you have the right culture, you get to attract the best researchers, the best researchers, the best research talent, then wants to work on pushing the frontier, and algorithmic innovation just falls out of having a really good team that's very flexible on what kind of architecture they want to use. If you have the right culture, The algorithmic innovation bottleneck solves itself because then the, the researchers are not focused or like tied to one architecture versus another. They're not going, I'm all in on LLMs or transformers versus diffusion models. The best scientists and researchers just want to solve the problem, the mission. And if you have a very mission driven culture where they're like, we want to move the frontier of coding or the frontier of material science, the algorithm, the algorithmic stuff takes care of itself. But, so I'm not that, that's actually not the bottleneck anymore in my view. Two, three years ago, …

AI assessment note: “I think that culture actually might be. The most important bottleneck of all time”

Q I'm sorry, what does that mean? An iron dome for inference in terms of sustaining it?

A It means that all inference is served, no matter which company is serving it, is served through a shared proxy that can tell each other when there's an attack happening on one part of the frontier. Think of it as an iron dome across the entire western front, right? And just cause you're here, you're in one company, you, you, you can't see that your model being served through this other company is being distilled. So it's a, it's a deployment coordination protocol. It's, it's basically my group chat that I've got with like, you know, a bunch of different founders, but scales, where people go, we're seeing this attack today, and others go, we are too. Let's coordinate on defensive response.

AI assessment note: “It means that all inference is served... through a shared proxy”

Q Are frontier models moving faster than the pace of Uh, chips, as you said there, with H-one hundreds, where you, you have newer and newer models, and then you're training them on older and older chips, because that's what's free, and it's not moving in lockstep. Is that, is that the problem that we're articulating?

A No, no, no. The problem we're articulating is that compute is not fungible. There are no standards for fungibility, and there are no institutions enforcing standardization of compute enough. So we are in the pre-standardization era of compute today, which, which was the pre-standardization era of electricity in 18, 85. And the next, I hope we can, we can self-regulate, self-standardize, and self, um, enforce Standardization so that we can skip the boom and bust cycles that happened with electricity over the next 50 years, and this happens with every infrastructure cycle in the pre-standardization era. It happened with electricity in 1885, it happened with steel, it happened with railroads, and every time you have this boom and bust cycle, what happens is wars are fought, companies backstab each other, It's super painful. It's annoying. And my view is that compute not being fungible is what's resulting in the, all this talk about AI, the AI bubble. But what people forget is that we don't have AI capabilities. Bubble. The capabilities are extraordinary in every domain. We have an infra infrastructure wastage crisis right now, and it's because there are no open standards. There's no open protocol for how flops from one, um, data center can flow to somebody else who needs it across chip types, across secure boundaries. And, uh, it's resulting in a lot of pain for the ecosystem. Peo…

AI assessment note: “No, no, no. The problem we're articulating is that compute is not fungible.”

Q What does that mean? Perfect competition is for losers.

A It means that if you have 10 different, like, 50 companies all doing LLM training or doing coding models, that's, that's a losing proposition. It's, it's like, you know, perfect competition is like restaurants. There's no defensibility. That's why restaurants go out of business all the time. It's very hard for them to differentiate. On the other hand, in monopolistic, monopolies are mafias. If once you have a monopoly at one part of the stack, they stop innovating and instead they try to go up or down by using the balance sheet to acquire. They start hoarding resources. They start saying, you give me this and I will force you to basically subsume yourself to me. And I'm seeing that kind of behavior up and down the stack. And mafias are not good for innovation. I, I think we're in an era of op. What we need is optimal competition. The optimal competition set set up is you have three or four teams. In every frontier that are making extraordinary progress. And so if you invest in them, you get extraordinary returns, but they're not so comfortable as, uh, to be a monopoly such that they can stop innovating. And that's important because when they stop innovating as humanity, we're fucked. And so I believe that optimal competition, we're, we are living, we, we need to transition to the optimal competition in frontier technology. And I think we need leaders, stewards, venture capitali…

AI assessment note: “It means that if you have 10 different, like, 50 companies all doing LLM training”

Q I totally get that. Can I ask you, when we look at the bottlenecks around performance and progression today, what are the bottlenecks that really persist most significantly to you? Is it, is it algorithms? Is it data? Is it compute? Can you help me understand which is most lagging?

A So there's four or five. It's, um, context feedback, which I'm happy to talk about. It's compute. There's Capital, which you need to like, you know, continuously sort of deploy the compute and context feedback loops. And then there's culture. And I think that culture actually might be. The most important bottleneck of all time, but those are the four I would say. Now, look, algorithmic innovation, I think, is a function of culture, basically, because if you have the right culture, you get to attract the best researchers, the best researchers, the best research talent, then wants to work on pushing the frontier, and algorithmic innovation just falls out of having a really good team that's very flexible on what kind of architecture they want to use. If you have the right culture, The algorithmic innovation bottleneck solves itself because then the, the researchers are not focused or like tied to one architecture versus another. They're not going, I'm all in on LLMs or transformers versus diffusion models. The best scientists and researchers just want to solve the problem, the mission. And if you have a very mission driven culture where they're like, we want to move the frontier of coding or the frontier of material science, the algorithm, the algorithmic stuff takes care of itself. But, so I'm not that, that's actually not the bottleneck anymore in my view. Two, three years ago, …

AI assessment note: “culture actually might be. The most important bottleneck of all time”

Q Is it not impossible not to be hauled up in front of Congress if you reach a certain scale? Whether you're Google, or whether you're Facebook, or whether you're anthropic fighting against the Pentagon, you get to a scale where it is impossible not to have that conflict.

A Oh, absolutely. No, what are you talking about? Look, I started AMP as a public benefit corporation, because I, I think it's actually a very aligned model. Have you heard of REI, right? REI is a public benefit corporation. They make billions of dollars in revenue and profit. Have they ever been hauled up in front of Congress? No. Like Ben and Jerry's, public benefit corporation, have they been, you know, hauled up in front of Congress? No, it's because they self-moderated, right? At the time when they said, here's our mission, but we have to make, we have to build a business. And as long as you hold those two things in sort of, those things are not in conflict long term. If your goal in life is long term to push humanity forward in some stable, reliable way, then you all, there are always tensions where you have your mission, and then you have your profit motive, and you've got to be able to, to like moderate between those two. And I think public benefit governance allows you to do that. And I think we need more public benefit charters in Silicon Valley and in technology, and I think we will get there. If you look at the arc of infrastructure businesses, for example, right?

AI assessment note: “Have they ever been hauled up in front of Congress? No.”

Q What decision can you foresee with AMP that is aligned to your mission but does not put the profit motive slash incentive first?

A There are many up and down the stack because we see ourselves as a full stack scaling partner to the best frontier technology teams, and we also kind of see ourselves a little bit as how our job is to propose independent standards for AI and as an institution try to Uh, evangelize the adoption of those standards through, you know, profit generating businesses. We have a venture capital business. We also have an infrastructure business. A good example of this for now is we're actually giving away most of our compute at cost. Now, if you're a shareholder, you'd go, wait on, do you have billions of dollars of compute infrastructure you're giving away at cost? Yes, because we think that's the right thing for humanity. And we think that's the right way long-term to have a healthy independent ecosystem, which is what our mission is. Our mission says AMP is a public benefit holdings company. Our, our, our vision is, is to ensure there's a healthy independent frontier technology ecosystem. Our mission is to maximize the world's frontier output. To do that long-term, we think the teams that are truly doing innovation, like truly doing, pushing the frontier of science and engineering, need act, compute access. And many of those teams today can't afford to pay price gouging in extraordinary prices for compute infrastructure today. And so, you know what? Yeah, we're happy to provide them a…

AI assessment note: “A good example of this for now is we're actually giving away most of our compute at cost.”

Q Are frontier models moving faster than the pace of Uh, chips, as you said there, with H-one hundreds, where you, you have newer and newer models, and then you're training them on older and older chips, because that's what's free, and it's not moving in lockstep. Is that, is that the problem that we're articulating?

A No, no, no. The problem we're articulating is that compute is not fungible. There are no standards for fungibility, and there are no institutions enforcing standardization of compute enough. So we are in the pre-standardization era of compute today, which, which was the pre-standardization era of electricity in 18, 85. And the next, I hope we can, we can self-regulate, self-standardize, and self, um, enforce Standardization so that we can skip the boom and bust cycles that happened with electricity over the next 50 years, and this happens with every infrastructure cycle in the pre-standardization era. It happened with electricity in 1885, it happened with steel, it happened with railroads, and every time you have this boom and bust cycle, what happens is wars are fought, companies backstab each other, It's super painful. It's annoying. And my view is that compute not being fungible is what's resulting in the, all this talk about AI, the AI bubble. But what people forget is that we don't have AI capabilities. Bubble. The capabilities are extraordinary in every domain. We have an infra infrastructure wastage crisis right now, and it's because there are no open standards. There's no open protocol for how flops from one, um, data center can flow to somebody else who needs it across chip types, across secure boundaries. And, uh, it's resulting in a lot of pain for the ecosystem. Peo…

AI assessment note: “No, no, no. The problem we're articulating is that compute is not fungible.”

Q What does that mean? Perfect competition is for losers.

A It means that if you have 10 different, like, 50 companies all doing LLM training or doing coding models, that's, that's a losing proposition. It's, it's like, you know, perfect competition is like restaurants. There's no defensibility. That's why restaurants go out of business all the time. It's very hard for them to differentiate. On the other hand, in monopolistic, monopolies are mafias. If once you have a monopoly at one part of the stack, they stop innovating and instead they try to go up or down by using the balance sheet to acquire. They start hoarding resources. They start saying, you give me this and I will force you to basically subsume yourself to me. And I'm seeing that kind of behavior up and down the stack. And mafias are not good for innovation. I, I think we're in an era of op. What we need is optimal competition. The optimal competition set set up is you have three or four teams. In every frontier that are making extraordinary progress. And so if you invest in them, you get extraordinary returns, but they're not so comfortable as, uh, to be a monopoly such that they can stop innovating. And that's important because when they stop innovating as humanity, we're fucked. And so I believe that optimal competition, we're, we are living, we, we need to transition to the optimal competition in frontier technology. And I think we need leaders, stewards, venture capitali…

AI assessment note: “It means that if you have 10 different, like, 50 companies all doing LLM training”

Q a sort of, uh, business strategy perspective. You know, maybe we saw Meadow with maybe the first big open source push. Um, you know, OpenAI has sort of evolved their tune. I, I've seen even Anthropix seems to be evolving their dialogue, um, a, a little bit. Um, how should we think about open sources as a, as a business strategy in terms of what, what's changed here and why?

A Oh, look, I, I don't think this is, this part is actually, is, is playing out beautifully along the same trend lines of all previous computing infrastructure, databases, analytics, operating systems, like Linux. The, the way it works is the closed source bioneers the frontier of capabilities. It introduces new use cases, and then the enterprises never know how to consume that technology, and when they do figure out eventually that they want cheaper, faster, more control, they need somebody like a Red Hat to then introduce them And, and provide solutions and services and packaging and forward deployed engineering and all of that around it. And which is why the arc generally in enterprise infrastructure has been closed source wins applications and open source tends to do really well in infrastructure, especially in large government customers, regulated industries where there's a bunch of security requirements. Things need to run on prem. The customer needs total control over it. Broadly, you could call that the sovereign AI market right now. Lots of governments and lots of legacy industries are going, wait, this open source thing is really critical to us. So I think Whereas two, three years ago, it was open source was viewed as like this, like, largely philosophical endeavor, which it is. Open source has always been political and philosophical by definition, but now there's an ex…

AI assessment note: “now there's an extraordinary business case for it, which is why I think you're seeing”

Q Well, that is very, very kind of you to say. I do want to kick off with you today. I've never done this before, so I'm slightly winging it, but I spoke to Finn Barnes before the show, and he said, I have to ask Ask about your childhood. So what did he mean by that, and how did that lead to the founding of Ubiquity Six?

A I'm not sure which part of my childhood he was talking about. I had a pretty weird childhood. I've basically lived away from home since I was 10 years old, a few 100,000 miles away from family. I spent the ages of 10 through 16 in a boarding school in rural India that had no access to computers or the internet. Then I was dropped into the middle of a gleaming metropolis, which was Singapore. I did high school in Singapore and then moved to the U.S. For college at Stanford, and I think the aha moment for me that he was maybe referring to was when I put on my first VR headset as a freshman at Stanford and realized this was going to be way more immersive and communicative of a way for me to stay in touch with my family and friends that I'd left on the other side of the planet than anything I'd ever tried before, whether that was a video call or a texting thread. Everything seemed so limited up until that point, and then I knew that This new thing we had called six degrees of freedom, and whether that would be through augmented reality or virtual reality, being able to be physically embodied with the people you care about on the other side of the planet was the light moment for me, I think. And so that's what the company's focused on, right? How to create shared, persistent, mixed reality experiences for anyone, no matter what device they're on in real time. And I think being on th…

AI assessment note: “that's what the company's focused on, right? How to create shared, persistent, mixed reality”

Q I am enjoying this so much. What's the last one?

A The last one is basically probably the most controversial, which is, as you know, venture capital is a business about outliers, and when somebody succeeds, their opinion, and I think their decision-making gets over-indexed on their successes, which often, as you know, are outliers, and it's hard to generalize from a single outlier, and my belief is the most successful people in venture capital should have a transition timeout. Type of distribution, basically. So my point is, if you're really good at what you do, you should be forced to retire because it affects the decision making of everybody else around you. And my belief is the best venture firms actually have figured out how to manage those transitions where they force their most successful investors to step back. And that's a really hard counterintuitive thing to do, right? Why ask your top performers to stop performing? Well, because it's your product, actually, your primary product is decision making. And when decision making starts getting worse after the Successes, because you're over-indexing on a few successes and not actually assessing the true risk of new investments, I think bad things happen.

AI assessment note: “The last one is basically probably the most controversial”

Q From Finn Barnes, how is your relationship with your seed investors different to your later stage investors? Emoji of a winky face.

A The seed investors got the better sweatshirts. The later stage ones didn't. Um, no, I'm kidding. I think our seed investors were able to dream the dream with us at the five, 10 and 50 year mark. And I think our later stage investors are able to do the same, but they got the benefit of a bunch of missing blanks filled in. And so I think it's helpful to be able to go back at times when you're figuring out new questions to your earliest seed investors and talk about why they believed. And which parts were the clearest to them so that, you know, what your most unique strengths were even before you had a ton of progress.

AI assessment note: “seed investors were able to dream the dream with us at the five”

Q How is Silicon Valley and DC not on the same alignment?

A For one, I don't think we have standardized on whether AI should be regulated, treated, procured as just as good old-fashioned software or like a new kind of system. You know, look, I, again, I went to grad school for machine learning, and what you learn in machine learning one-on-one is models are statistical. They're not deterministic, right? So when you have a statistical system, it's different from, there are some properties of a statistical system that are different from a spreadsheet. A spreadsheet is deterministic software and a statistical model today is not. And so should the procurement of a spreadsheet be the same from an IT perspective as a statistical model? Open debate. That is the core debate. That's the problem. Like AI alignment, don't get me wrong, is hard, but not the hardest problem. Human misalignment, human alignment is really, is really the problem right now we have in, in the world. We need technologists who are, who understand the difference between deterministic software and statistical systems to propose a set of standards for how procurement for this should work. And then we need standards people in DC. We have this thing called NIST. We have various bodies in the government that should get together and say, thank you guys for proposing the standard. This is where it makes sense. This is where it doesn't. This is called an RFC process. And we're goin…

AI assessment note: “I don't think we have standardized on whether AI should be regulated”

Q How much more cash do we need in Europe for Frontier AI to be what we think it can be? Is it like two X? Is it 10 X?

A That's a good question. I would try to go about it from a top downs approach and bottoms up sizing approach. Um, you know, for us at AMP, when I look at the grid, we are building out, which is sort of a reasoning by analogy, uh, we have started securing about 1.3 gigawatts of computer infrastructure. That's roughly forty billion dollars of cloud spend over the next four years. And that is financed roughly, you know, between with about 20% of equity. The remaining is debt. So 20%, that's about ten billion dollars of equity capital. The remaining is all debt capital. We have a bunch of partners. That help us put together these equity and debt packages to secure computer infrastructure for our companies. I would say in Europe, I would talk to Arthur and figure out how much he thinks is required for the independent ecosystem over there. But in multiples of gigawatt, like if you, if you're doing sort of your atomic unit of math in gigawatts, I would, from a, from a top down perspective, you know, I think Google Is roughly at 12 to 15 gigawatts of that I'm aware of, of, of infrastructure for internal and external deployed needs. Now they have a huge land power shell pipeline coming, but you know, if Europe does not have access to Google level infrastructure, then what are you guys even doing? Right? Like that's roughly what the continent needs for full sovereignty, right? To have as,…

AI assessment note: “that's roughly what the continent needs for full sovereignty”

Q And don't laugh, what should they be talking about on the topic instead?

A Look, I think this is another thing I learned from being inside venture capital is it's no fault of investors. They're constantly being asked for opinions, whether that's in the media, whether that's on a podcast, whether that's in an interview for opinions that are short, they're pithy, they're good sound bites, and they're sort of accessible to the somewhat informed audience. And I think AR and VR is a perfect example of that. VCs love applying on formats. I think throughout the ages, this always happens, right? Is it Web versus mobile. What ends up winning here? In many ways, that doesn't matter. If you actually go look at a bunch of old press clippings, you'll see it was the zeitgeist for a lot of investors to be discussing. I think in the late 2000, what is the winning format? Is it a VHS? Is it DVD? The answer was, it doesn't matter. The winner was Netflix. You're looking in the wrong place because the company or the service that ends up figuring out how to deliver that the same experience to people No matter what device they're on, what platform they're on, in a way that makes more sense to them, ultimately always ends up winning, right? And so if you were debating web and mobile in 2008, you just missed the point. YouTube was going to be big on both. That's very similar to how I think about AR or BR, where they're both viewing mechanisms. They're both really windows int…

AI assessment note: “the real revolution that's happening here is in real time, three D rendering”

Q They don't just care about jobs. They care about all the other stuff around it, right? Like they care about power grid, they care about environments.

A Power grid, permitting, and so on. And imagine, I think if you said there's a new AI deal. If we're bringing up a data center in your community, we're actually going to reduce the cost of your electricity bill. Okay, now we're talking, right? The community is going, okay, now this is a deal. I feel like a partner in this. Right now, that's not happening. There will be audits. There will be investigations, and when the, when the regulators come, I don't know when it's going to be. The folks who are moving fast and breaking things in the name of AI progress better be prepared. That's certainly not how we're procuring compute. We're trying as much as we can to work with partners who have long-term track records, many of whom, by the way, are not like AI providers. I think this whole idea of NeoCloud being somehow this new category is a lot of marketing speak. There are really good, reliable, trusted data center providers in America who've been around 20 plus years. I love those folks. They know how to, sure, have they, are they sponsoring happy hours at NeurIps? No. Are they legibly bitterless and billed? No. Are they hanging out in my, you know, in like situationally aware parties? No. But they're adults.

AI assessment note: “Power grid, permitting, and so on. And imagine, I think if you said”

Q What decision can you foresee with AMP that is aligned to your mission but does not put the profit motive slash incentive first?

A There are many up and down the stack because we see ourselves as a full stack scaling partner to the best frontier technology teams, and we also kind of see ourselves a little bit as how our job is to propose independent standards for AI and as an institution try to Uh, evangelize the adoption of those standards through, you know, profit generating businesses. We have a venture capital business. We also have an infrastructure business. A good example of this for now is we're actually giving away most of our compute at cost. Now, if you're a shareholder, you'd go, wait on, do you have billions of dollars of compute infrastructure you're giving away at cost? Yes, because we think that's the right thing for humanity. And we think that's the right way long-term to have a healthy independent ecosystem, which is what our mission is. Our mission says AMP is a public benefit holdings company. Our, our, our vision is, is to ensure there's a healthy independent frontier technology ecosystem. Our mission is to maximize the world's frontier output. To do that long-term, we think the teams that are truly doing innovation, like truly doing, pushing the frontier of science and engineering, need act, compute access. And many of those teams today can't afford to pay price gouging in extraordinary prices for compute infrastructure today. And so, you know what? Yeah, we're happy to provide them a…

AI assessment note: “we're actually giving away most of our compute at cost.”

Q Is it not impossible not to be hauled up in front of Congress if you reach a certain scale? Whether you're Google, or whether you're Facebook, or whether you're anthropic fighting against the Pentagon, you get to a scale where it is impossible not to have that conflict.

A Oh, absolutely. No, what are you talking about? Look, I started AMP as a public benefit corporation, because I, I think it's actually a very aligned model. Have you heard of REI, right? REI is a public benefit corporation. They make billions of dollars in revenue and profit. Have they ever been hauled up in front of Congress? No. Like Ben and Jerry's, public benefit corporation, have they been, you know, hauled up in front of Congress? No, it's because they self-moderated, right? At the time when they said, here's our mission, but we have to make, we have to build a business. And as long as you hold those two things in sort of, those things are not in conflict long term. If your goal in life is long term to push humanity forward in some stable, reliable way, then you all, there are always tensions where you have your mission, and then you have your profit motive, and you've got to be able to, to like moderate between those two. And I think public benefit governance allows you to do that. And I think we need more public benefit charters in Silicon Valley and in technology, and I think we will get there. If you look at the arc of infrastructure businesses, for example, right?

AI assessment note: “Have they ever been hauled up in front of Congress? No.”

Q What makes Dario so good that other people don't see from the outside?

A One, sheer scientific brilliance. Truly, like, world-class technical ability in his domain. An obsessive, um, desire for truth-seeking. To admit, like, to, to, to keep Reasoning, reasoning, reasoning, to keep doing experiments until he's, he's a physicist at heart, right? Like, I think Dyer is a physicist at the end of the day. He's not actually a computer scientist. Um, and so a physicist, a world-class physicist tries to derive, and he's an applied physicist, um, derive laws, general laws of reality by looking at data and running empirical experiments. He's an empiricist, and he has an obsessive desire to be a good empiricist. And the third is mission alignment culture. He said, this is our focus. This is our mission. No drift. We won't take shortcuts. We are willing to make huge trade-offs to hit this mission, and that attracts the best talent. Incredible talent. In the face of criticism of people saying, you're a mercenary, you're blah, blah, blah, you're just doing this for profit. No, actually, it turns out there's a ruthless desire to, to stay focused on the mission. And that results in hard trade-offs and priorities. And if you don't, if you're not aligned on that mission, then you'll just think he's crazy or, you know, he's evil or whatever. It's crazy how much ad hominem attacks people I've seen against him, but he's that caught that clarity of mission.

AI assessment note: “One, sheer scientific brilliance. Truly, like, world-class technical ability in his domain.”

Q Would you let your children have social media?

A Yes. I, I, I, I think it'd be crazy to not let them have it, have access to social media, but I, I think it has to be done in moderation, and most parents have a really hard time moderating it with their, with their kids, and then it's really hard to moderate. You know, I, with Rishi Valley, I had access to a computer once a week, and so you need to enforce something like that, where you, you don't take it for granted. It's within a structured sort of Environment. And then you develop good habits and protocols and practices and not be dependent on it, but usually I would plan my Wikipedia sessions. Like I had to plan my, like you got one hour a week in the computer room in Rishi Valley. So you really got to plan like the highest use of that time. And so you're not dependent on it, but you just use it as a high leverage strategic asset. I, that's how I think technology should be viewed. You shouldn't take it for granted. Like the problem is, you know, people keep saying we're, we're, we're going to have the singularity soon. I'm like, have you realized where we've been at this for like 10 years? Half of you outsourced your brain and thinking to this device anyway.

AI assessment note: “Yes. I, I, I, I think it'd be crazy to not let them have it”

Q What makes Dario so good that other people don't see from the outside?

A One, sheer scientific brilliance. Truly, like, world-class technical ability in his domain. An obsessive, um, desire for truth-seeking. To admit, like, to, to, to keep Reasoning, reasoning, reasoning, to keep doing experiments until he's, he's a physicist at heart, right? Like, I think Dyer is a physicist at the end of the day. He's not actually a computer scientist. Um, and so a physicist, a world-class physicist tries to derive, and he's an applied physicist, um, derive laws, general laws of reality by looking at data and running empirical experiments. He's an empiricist, and he has an obsessive desire to be a good empiricist. And the third is mission alignment culture. He said, this is our focus. This is our mission. No drift. We won't take shortcuts. We are willing to make huge trade-offs to hit this mission, and that attracts the best talent. Incredible talent. In the face of criticism of people saying, you're a mercenary, you're blah, blah, blah, you're just doing this for profit. No, actually, it turns out there's a ruthless desire to, to stay focused on the mission. And that results in hard trade-offs and priorities. And if you don't, if you're not aligned on that mission, then you'll just think he's crazy or, you know, he's evil or whatever. It's crazy how much ad hominem attacks people I've seen against him, but he's that caught that clarity of mission.

AI assessment note: “One, sheer scientific brilliance. Truly, like, world-class technical ability in his domain.”

Q What have you changed your mind on in the last 12 months?

A You know, the biggest one is, um, health. Um, I, I've had some health experiences between both the family members and myself have had health experiences that made me realize We all just don't know how much time we have on earth, and that makes you stop taking for granted How much time we have. And so I started taking time much more seriously, but I would say, and this was my, my kind of on, you know, every lecture I do at Stanford, um, we talk a lot about scaling laws and technical stuff, but I also give the kids like an on just life scaling laws lesson, uh, you know, at every, I'm very inspired by Richard Feynman, uh, Feynman's lectures, you know, always kind of combined technical education with a little bit of life coaching for them. And in my, my, my like number one scaling law for them, for the students was, Take life seriously, but don't take it so seriously that you forget what makes it worth living, which is have fun with friends, work on interesting projects with people you love. Don't take relationships for granted. It's humans that make the world go around, and if you're so focused on your next fund or your next raise or whatever, you just take for granted the one thing we all don't know how much we have, which is time with each other. And so I just start valuing my time more, my relationships with people. You know, there's so many people. I mean, My parents. You know…

AI assessment note: “the biggest one is, um, health. Um, I, I've had some health experiences”