This Is How OpenAI Goes Broke — ft. Sebastian Mallaby

28:15Thank you. It was named the top pick for data removal services by Wirecutter. And our producer, Jennifer Sanchez, has tried DeleteMe. She was surprised to find out how much personal information was actually already out there. But DeleteMe made it very easy for her to clean it up. Take control of your data and keep your private life private by signing up for DeleteMe. Now at a special discount for our listeners. Get 20 % off your Delete Me plan when you go to joindeliteme.com slash profg and use promo code profg at checkout. The only way to get 20 % off is to go to joindeliteme.com slash profg and enter code profg at checkout.

29:26That's joindeliteme.com slash profg, code profg.

29:33Get business done with the new American Express Graphite Business Cash Unlimited card. With unlimited 2 % cash back on all eligible purchases, unlimited 5 % cash back on flights and prepaid hotels booked through American Express Travel Online, and a flexible spending capacity that can grow with your business, you'll have the confidence to keep building. Apply today and earn a welcome offer of$1 ,500 cash back after you spend$50 ,000 in qualifying purchases on your new card within the first six months of card membership. Terms apply. Learn more at go.amex.com. When it's time to scale your business, it's time for Shopify.

30:08Get everything you need to grow the way you want. Like, all the way. Stack more sales with the best converting checkout on the planet. Track your cha-chings from every channel, right in one spot. And turn real-time reporting into big-time opportunities. Take your business to a whole new level. Switch to Shopify. Start your free trial today.

30:38We're back with ProfG Markets. This is a good segue into China, which is a topic that you also wrote about recently. The title of your piece was, quote, I went to China to see its progress on AI. We can't beat it. I was in the New York Times recently, your op-ed. What did you learn about Chinese progress on AI and why do you think that we can't beat it?

31:02Sebastian Mallaby:We haven't mentioned this yet, but I'm going to mention it now because you've given me the excuse. So I published a book this year called The Infinity Machine about Demis Hassabis. I was going to get to it. I'm glad you mentioned it. Go read The Infinity Machine, folks. But no, seriously, the thing about China is it does everything faster. And so they published, although they got my manuscript last, and then they had to translate it into Chinese, and then they wanted photographs and other embellishments. they produce in a way a more complex product, but they actually published it before Penguin Press in the United States or any of the other deals I had in other countries.

31:39Sebastian Mallaby:So I go to China right at the beginning of my book tour. I spend eight days, you know, going to four different cities, Hangzhou, Shenzhen, Shanghai, Beijing, talking to both computer scientists at the private labs like, you know, Huawei and Ant Group and so forth. And then also talking to academic computer scientists from universities. And what struck me about these guys is that first of all, they talk about safety. They just bring it up. The notion, which I've heard from friends in Washington, that the Chinese don't give a damn about AI safety is just not true. They do talk about safety. Now, I'm not claiming that the government's policy is to pursue safety or that the majority view in China is that they want safety.

32:24Sebastian Mallaby:China is like the US. China has some accelerationists and some people who want to go slower because they're worried about the safety issue. That's the same as the US. So neither side is going to de-escalate and start going slower unless the other one does as well. But what I'm saying is, to caricature China as like only accelerationists 100%, that's just wrong. And so there is scope to talk to them about safety, and maybe we'll come on to that. But the other thing which I observed is that China is very good and very focused on applications. And so if you go to a company like, you know, Hike Vision, which is under US sanctions, and it's kind of a out of body sort of double take experience when you go there, because on the one hand, it feels like an American tech company.

33:11Sebastian Mallaby:I love tech companies. They're kind of all about building cool things and making the world better. I kind of buy that. I drink that Kool-Aid. I kind of believe in it. I like technology, right? So I see these people trying to build cool technology and they show me stuff like, for example, there is an AI kind of scanning camera thing and you point it at some water and you get a reading on the pollution count in the water. And because they've created that, guess what? There is an internal market in water pollution reduction between different Chinese cities. So if you're the downstream city, you will pay the upstream city to reduce the pollution in the water that's going to come downstream to you.

33:50Sebastian Mallaby:and so you can do pollution reduction when you can measure the pollution and this is what they're doing at this company this is what they're building but they're also under sanctions these guys by the u.s because the u.s says and you know historically this was actually true that they're building other kinds of cameras which are good for surveillance of civilians and so forth in xinjiang and whatever so so they're both bad guys and they're cool guys it's a difficult thing to figure out but whatever they think whether they are bad or cool they ain't going away. These guys are for real. They are building cool technology.

34:20Sebastian Mallaby:You go to Huawei, they've got application after application. You know, here is our special, you know, AI to service the bullet train between Shanghai and Beijing every evening. We used to have human technicians, mechanics, who would go under the train and make sure it's all fine. Now we just have AI cameras and a couple of robots and they fix the train for you. They are doing this. We're not stopping them. We have imposed chip export controls on China to try to hold them back. It hasn't worked. These guys are moving ahead. And the latest thing, as you probably saw, is this model from a group called Xipu in China, which isn't quite as good as Mythos from Anthropic, but it's pretty close.

35:02Sebastian Mallaby:So we are kidding ourselves if we kind of assume away the reality of China being a technology superpower. And we need to, on the contrary, get our heads out of the ostrich position in the sand and start talking to China about what happens when they have a mythos-level model which could hack every single bank in the global financial system and wreak havoc. We need to persuade them not to release it on an open source, open weight basis because then any criminal can do it and there won't be an off switch. What is your view then on AI policy with China? Obviously, the big debate is, should we have these export controls?

35:42Should we sell chips to China? Are we selling weapons to our enemy? Or do we need to sell dumber chips, basically dumber weapons to the enemy? Or should we not have these export controls at all? I mean, do you think that we should have a policy or is the path forward more of a method of diplomacy?

35:59Sebastian Mallaby:I believe in American power, first of all. I work at the Council on Foreign Relations in New York. And, you know, we do geopolitics all day long. And I believe that US power is generally a force for good. So I would rather that the Chinese were behind on AI, okay? And so to the extent that a chip export ban helps us to be ahead, I support it. And indeed, when it was first announced in 2022, I wrote a massive long essay in the Washington Post about why this was a good idea. But the reason I've had my doubts recently is that I look at the results and I'm not seeing that Chinese models are that far behind.

36:39Sebastian Mallaby:And in the meantime, because they're not far behind, I think we have to reckon with the reality that they are building models which are going to destabilize the global cyber system. And unless we persuade them not to release them on an open weight basis, which is what they're doing at the moment, we have serious trouble on our hands. It's like everything in cyberspace will be destabilized. And we need a policy to deal with this proliferation risk. And I would be willing, I'm in favor of the chip export ban if we could have it for free and there'd be no downside. But if the effect of having chip export controls is that we can't talk to them about an agreement on not doing open weight mythos, then I'm willing to trade a bit on the chip export ban.

37:24Just looking at some of the, how these models have affected the ecosystem. And something we were saying earlier, in the US, you've got Anthropic, you've got OpenAI, you've got Gemini. Those are kind of the heavyweights in the US right now. But it does seem that as pricing becomes more of an issue, companies are more interested in cheaper models, which usually means Chinese models. And indeed, that is exactly what we're seeing when we look at OpenRouter, which is basically a Trax developer marketplace for AI models. Chinese models went from less than a third of developer traffic in late 2025 to 60 % by mid-2026.

38:05There are some companies that, American companies, that have started using Chinese models. Cursor, Airbnb, Shopify, Uber, Microsoft is currently testing DeepSeek. What do you make of this transition over to the Chinese models, specifically the cheap Chinese models, and what role does that play in potentially a policy discussion?

38:28Sebastian Mallaby:Well, I mean, it shows you that they make good models that serious American companies are thinking of using. And so that's another argument for why you can't just pretend that China can be beaten and that's the end of it. And these guys are for real, and we have to work with them, not just against them. Now, I think it's useful to just, for a moment, think through the lens of the Cold War, where when there were nuclear weapons in the Cold War, there were two kinds of big risk, right? One was a nuclear conflagration between the Soviet Union and the United States. And the way we prevented that was through mutually assured destruction, basically close to parity in the power of the two arsenals, and therefore deterrence.

39:13Sebastian Mallaby:On the other hand, there was a different category of risk from nuclear weapons, which was the proliferation of these systems to rogue states or terrorists and so forth. And we dealt with that with a separate mechanism, which was the non-proliferation regime. Now, the point is, we were both competing with Russia, having an arms race with Russia, having a Cuban missile crisis with Russia, being told by the Russians at the United Nations, we will bury you, as Khrushchev said when he banged his shoe on the table. So there was deadly serious competition between the two superpowers, but at the same time there was cooperation on a non-proliferation agreement.

39:51Sebastian Mallaby:And the way I see the future with AI is that we'll do the same. We will have inevitable competition between China and the US, but we'll also, I hope, have collaboration because the proliferation risk is too awful to contemplate unless you have some collaboration. It seems, though, that what they're doing is basically stealing what we have. People are calling it distillation. And you wrote about this and your definition of distillation, quote, every time a U.S. lab produces a cutting edge model, Chinese rivals quickly reverse engineer its capabilities and build a copycat version. The follower has the advantage.

40:33And when I look at how, I mean, companies are switching to Chinese models because Chinese models are cheaper. And as you say, maybe they'll use the more advanced, cutting-edge models in America that are more expensive for certain tasks, the Chinese models for other tasks, which essentially means that we are kind of, maybe we're collaborating, but also you could say that we're sort of seeding advantage to the enemy, to the Chinese players in the AI ecosystem. And it seems that the reason that those models are good cheap is because of distillation, i.e. theft. I don't know if I'm being crude by calling it theft.

41:11I don't think I am. And I think the Chinese have shown a pretty strong track record of stealing intellectual property from the U.S. and then going out and monetizing it on their own terms. I mean, what do we know about this process of distillation? And what do we know about why and how the Chinese models have gotten so cheap and therefore so successful on a global scale.

41:35Sebastian Mallaby:So distillation is a process which involves asking a very strong model, like a new American model comes out. A Chinese copycat would ask a ton of questions to that model and get the answers. and the answers amount to training data such that, you know, you can train the Chinese model, like if the question is like this, the answer should be like that. And when a frontier, like a first mover, an American lab has to train the model in some specific, very complicated frontier expertise, like let's say, you know, quantum physics, they expensively hire a bunch of quantum physicists and engage them in creating problem sets and model questions and answers.

42:26Sebastian Mallaby:And generating that training data for the AI is a super expensive, time-consuming, painful process. But once you've created the AI that can replicate all those quantum physicists, the Chinese can come along and not hire the human quantum physicists, but just query the machine equivalent. And that's what distillation is. Now, when these Chinese companies do this, it is not illegal, but it is against contract. In other words, when you sign up to use an American model, you check some boxes and you sign an agreement saying, you know, I'm not going to query you a gazillion times and then train my own model by copying what you've done.

43:11Sebastian Mallaby:And so they are violating contract, but not sort of federal law. That's my understanding of it. Now, whatever the legal niceties, the question is, can you stop it? I mean, I'm all in favor of stopping that if we can. And it seems to me that Anthropic and Google and OpenAI have all of the commercial incentives in the world to put in anti-distillation safeguards if they can come up the sun. So I think this is a self-solving problem insofar as it has a solution. And by the way, I should add, Elon Musk the other day or a few months ago casually admitted that his company, XAI, had distilled from one of the US frontier competitors.

43:56Sebastian Mallaby:So it's not just the Chinese who do this. But look, this is the rough and tumble of the marketplace. It's not nice. But the practical question is, you know, let's stop it if we can. But insofar as we can't, we have to live with a reality on the ground, which is that the Chinese models are good. Something I can't figure out is, I mean, if these AI labs are as capable as they say they are, can they not figure out some cybersecurity method to stop the distillation from happening? If Mythos is the most powerful cybersecurity technology and software that the world has ever seen, but we can't figure out how to get these Chinese developers to stop querying and replicating the same software.

44:39I'm sort of like, surely you guys can figure it out. I guess my follow-up would be, say they do figure it out. Say we do put an end to Chinese distillation of US AI. Would that not, one, solve America's problems in one fell swoop, and two, kind of put an to Chinese AI, or at least the progress that they have been making. I mean, is that not kind of a poison pill for China?

45:11Sebastian Mallaby:I'm not sure, is the answer. Whether, if you could stop distillation, and by the way, I think the latest anthropic models do have some anti-distillation technology built into them. So we'll see how effective that turns out to be. It's going to be obviously a, you know, cat and mouse, both sides trying to get smarter on this one. But to answer your question, let's posit that US labs figure out a way to stop distillation. Would the Chinese fall behind like a lot or just a bit? I'm not sure anybody really knows the answer. I kind of suspect that, you know, if they needed to generate their own data, they would.

45:55Sebastian Mallaby:And they would pay more money and it would be more expensive and it would take them a bit more time, but they would get there because they've got plenty of extremely smart Chinese scientists that they could engage in generating training data. We'll be right back. And for even more markets content, sign up for our newsletter at ProftyMarkets.com.

46:43We'll see you next time. the customer. Availability, amount of discounts and savings, and eligibility vary by state. At OLLI, we've got wellness down to a science. From PMS to pregnancy to menopause, our women's wellness line offers science-backed support for every stage. No judgment, no shame, none of the stigma. Just supplements designed to meet you wherever you're at. OLLI, choose science over shame. Find support at a retailer near you or on OLLI.com. That's O-L-L-Y.com. Got a Sam's Cafe pizza order up. You know the best part about this spicy Italian sausage? I voted for this topping. Yeah, just another perk of being a member.

47:28Come join us. Sam's Club.

47:35We're back with Prof G Markets. Okay, let's turn to the book for a moment. Your most recent book was The Infinity Machine, Demis Hassabis. Deep Mind and the Quest for Superintelligence. There was one quote from the book that really stood out. You said, quote, if you couldn't negotiate safety mechanisms inside one company, what chance would there be to negotiate common safeguards among multiple labs in multiple countries? Which really relates to kind of what we're discussing here in terms of AI safety and AI policy. But also, there's an important implication in that, which is that safety mechanisms were not able to be negotiated within a company.

48:18What did you learn about the inner workings of these AI labs, and why can't they figure that stuff out?

48:24Sebastian Mallaby:Embedded in the story of Google DeepMind and Demis Asabis is this sort of morality tale about somebody who really wanted to make AI safe, and that was his sort of driving passion from the time he founded DeepMind in 2010. He bonded with his co-founder, Shane Legg, at a safety lecture in which they discussed the potential for AI to attack humanity by the year 2030, which turns out to be perhaps a prescient projection. At least the capability is going to be there, whether the AI attacks is a different question. But I mean, anyway, the point is Demis Hassabis was thinking about safety since the beginning.

49:05Sebastian Mallaby:And so when he sold his company to Google in 2014, a condition of the sale was, you've got to give me safety and ethics oversight board. I can't let AI be rolled out into the world just on the say-so of the Google corporate board. There has to be these independent people from outside. They mentioned Barack Obama as an example when Barack Obama was leaving the presidency. You know, could we have somebody of that stature who would be on a board saying when it's safe to roll it out, right? That was Demis' vision, and it was coupled with another hope, which was that all of the major scientists would come together in one single effort to roll AI out into the world, so there would be no competitive pressure to go unsafely and too quickly, right?

49:51Sebastian Mallaby:And it turns out, and this kind of transpires through the story that I tell, that all of Demis' optimistic stories about how he was going to make AI safe, they all crashed and burned. the idea of just one lab building ai turned out to be a pipe dream it turns out that humanity is too tribal and competitive and disputatious there will be multiple labs when you are kind of confronted with the prospect of being able to build a god machine there'll be plenty of different sects of worshippers trying to do that right um and and the idea of oversight within google ultimately the Google board would not agree to giving some outside grandees a veto over how they used this technology that they were spending billions of dollars on developing.

50:39Sebastian Mallaby:They weren't going to do that on a fiduciary basis, obligation to their shareholders. They couldn't, they felt. So the point being that the experiment that Demis ran at DeepMind, and I discovered all these internal documents which had the back and forth between the red lines from one team of lawyers to the other team about the exact safety mechanisms that they might use and all this sort of secret strategizing that Demis did to threaten to spin out of Google if he didn't get the safety oversight he wanted. And then the Google DeepMind General Counsel threatened me and said I wasn't allowed to publish any of this.

51:17Sebastian Mallaby:And I said, the heck with you, I'm publishing it anyway. So it was all quite dramatic. But the bottom line of the story is, you know, it turns out to be impossible to impose safety restraints within one AI lab when that lab is in a competitive posture with respect to others. And we saw the same thing play out, of course, at OpenAI, but more in public, when the safety board temporarily fired Sam Altman for like five days. So, you know, what this shows us is that if you want to stop a race which has multiple players, you need the government to enforce restraint on all of the players at once. And if there are players in China, you need the Chinese government to buy in and also agree to put restraints on their guys when the US puts restraints on labs within the US.

52:06Sebastian Mallaby:France, Canada, that's fine. Basically, the US can compel compliance in those places because Cohere in Canada or Mistral in France depend on American technology and the American market to function. But with China, you can't compel them. So there needs to be two countries, two governments that do a deal where everybody agrees to put some caution and like checking of models before they're released. It was the policy of the US government that they were going to do none of that. And they said, I mean, they even issued an executive order banning states from trying to regulate AI in their own way. But then it seems like they've kind of turned on this.

52:55Last month, Trump signed a new executive order where he basically asks companies to hand over their models to the government, let the government check them and then kind of green light them. But, I mean, on the one hand, it's progress in the direction that you think is the right direction. But also, it's not very harsh or strict or strong. It's basically just like, hey, could you please send your model over? We'd appreciate that. What do you make of Trump's AI policy at this point in terms of government oversight over these AI models and their safety?

53:32Sebastian Mallaby:Given my perspective that government needs to get involved, I've been very much cheered up by what's happened since April when Mythos first came on the scene and galvanized the U.S. government into paying attention and restricting the release. Because although you could argue, you know, correctly that on paper the executive order is kind of a voluntary collaboration system with Frontier Labs, blah, blah, blah, blah. The reality is it's not voluntary in the least, right? I mean, Commerce recently called up Sam Altman at OpenAI and ordered him to seek government permission before he gave his latest model to any customer.

54:14Sebastian Mallaby:Government has to sign off on each customer, customer by customer. This is extremely heavy-handed. So I think they're in it for real, the government. They have realized that they can't let this stuff disseminate around the world without being controlled by government. And so we're going to get pretty tough controls. I think the gap in the system is that they're not talking about doing this in coordination with China. Because the US policy world has two kinds of China expert. That you've got the kind of people who are always hawkish on China. And then the people who used to be a bit hopeful about collaborating with China, but then Xi Jinping rose to power and seemed to kind of frustrate all those hopes of collaboration.

55:01Sebastian Mallaby:And so that group of former doves flipped and became uber hawks on China. So you've basically got the traditional hawks and the new hawks, but they're both hawkish, and nobody wants to say they want to talk to China. This is the problem. This is the huge gap in the posture, because the US government has done a 180 on domestic regulation of domestic models, and I welcome that. The next thing that's going to come, just because it's necessary and they're not going have a choice is they're going to have to get over their inhibition about talking to China. So is that sort of the solution is get in a room with Xi Jinping and become partners in tackling this together?

55:43I mean, it sounds like kind of simplistic, but maybe that actually is the way to do it. The alternative would be, you know, force their hand in some way, create some sort of policy where you say, no, you're not going to get any chips or you're not going to get this, so you're not going to get that. Your view is, we just need to talk with them and have more of

56:03Sebastian Mallaby:a relationship. It's a bit more complicated than that. I mean, I think you can talk and also put pressure on them at the same time. I mean, going back to that Cold War analogy, there was a vicious competition between the Soviet Union and the United States at the same time as there was collaboration over proliferation. And so I think there will be competition. And by the way, you know, there are ideas around strengthening the chip export controls. And I'm not against that. Like, there is one theory of the case, you know, economists sometimes talk about corner solutions. You can either have a fully pegged currency, or a fully floating one.

56:40Sebastian Mallaby:But if you go for some mushy middle ground where it's kind of semi pegged, then hedge fund speculators are going to see that you're not really determined to defend that. And they're going to eat you for lunch, breakfast and dinner. So it's the same thing with this AI policy. There are corner solutions. You could either give up the export controls or be willing to give them up and go talk to them and say, okay, we know you didn't like that. As a show of our sincerity in wanting to work with you, we're going to offer to loosen those controls. But in return, we want you to collaborate on fixing this non-proliferation risk, right?

57:15Sebastian Mallaby:That would be one corner solution. Or the other corner solution is you don't say that. To the contrary, you tighten up the chip export controls. There's this massive loophole right now whereby if you're a Chinese model builder, get this, you can train on NVIDIA chips, the most advanced versions, all day long because the cloud compute that you access is in Malaysia or some other offshore place which is fully allowed to import NVIDIA chips, the most recent sort. Right? This is a crazy loophole. You're telling the Chinese they can't use nvidia chips but then you're letting them just like use a data center kind of across the border it's nuts that that loophole exists right so the other corner solution is get serious about the policy that you've enunciated and cut off the loophole and cut off the distillation and put china in a position where it's so weak it's kind of begging for collaboration now i'm agnostic i'm like we need to collaborate i'm i'm flexible on how we get there i think there's different theories Just going back to Trump's changing of his positioning, it used to be we're not going to regulate, we're not going to have any oversight because we believe that if we do that, then it stifles innovation and we want markets to do their thing and AI labs to sort of run free, uninhibited, etc.

58:34Then Mythos happens, Anthropik's model that was a real concern for cybersecurity. And then Trump changes his tune and issues this executive order, which you believe in this, I think, is fairly so, that that actually is stringent. They do take it seriously. Why do you think that happened? What was it about Mythos? Was it maybe something to do with China? Why did they do this thing that ultimately did amount to a 180 on AI policy?

59:10Sebastian Mallaby:Simply because Mythos was so powerful, it was very threatening. I mean, the prospect that you could take this model and find code vulnerabilities in every single entity on the internet and then hack it, that's curtains for the financial system. So that's why they took it seriously. Yeah, fair enough. I mean, I think throughout this topic, throughout this topic, the logic of the technology is going to force governments to do things which six months earlier they said they would never ever do. And that's happened with domestic regulation already in the US. I believe it's going to happen with international collaboration.

59:47I've already started to see pushback from, I mean, Silicon Valley spent a long time not being friends with Washington. And then in the last couple of years, they became very close friends with people in Washington. And I would assume that this is going to be, I don't know, this is going to cause a rift again. Because a lot of the technologists said that what we want is government to have no involvement in AI, in artificial intelligence capabilities. And Trump said, sounds good. I'm with you. And now he's not. I'm not really sure what that means for the relationship between Silicon Valley and Washington, but I assume, I don't know if you have any insight into this, I assume it's not going to be great.

1:00:33Sebastian Mallaby:Well, look, I mean, you've got this sort of Putin and the oligarchs sort of story. You've got, you know, endless examples of authoritarian governments with, you know, big business titans. And, you know, where does the power lie and how stable is that relationship? And the answer is it tends not to be stable, point one, and point two, the government wins because they have the monopoly on coercion. And so I think Silicon Valley, you know, is figuring that out. And they realize that the government is too powerful to ignore. I mean, you know, Dariyama Day tried to say to the government, you shouldn't use these tools for certain things like mass domestic surveillance.

1:01:15Sebastian Mallaby:And the government said, get lost. We're going to call you a supply chain risk, and we're not going to be dictated to you. I mean, who won that fight? Clearly the government won. It has been fascinating watching Trump use the full power of that coercion even this week when he decided to step into the proceedings of the World Cup and he got exactly what he wanted and the US got their player back. Just as we start to wrap up here, you have studied a lot of the characters in AI. You wrote your book about Demis Osavis, founder of Google DeepMind, kind of the open AI before open AI. You studied a lot of these characters.

1:01:53From your research, from writing that book, what did you learn about the people in AI? And what has that kind of told you about what might ultimately happen next

1:02:03Sebastian Mallaby:and who might ultimately win the AI race? You've got Sam Altman, who is essentially a commercial opportunist who wants to win commercially or at least survive commercially. And, you know, his drive is to be a big shot. And he thought of running for governor of California at one point and being a political big shot. But then he decided that building AI was like a bigger big shot. And he wants to just like put his imprint on it. He's not obviously a PhD scientist. He doesn't have even a first degree because he dropped out of Stanford to do other stuff. It's not to say he isn't anything other than massively smart.

1:02:39Sebastian Mallaby:But he isn't a deep scientist. Then you've got people like Dario Amadei and Demis Isabis who are PhD scientists who come at this from that perspective, who want to use AI to advance deep science. That's their deepest motivation. And I believe it's very deep with both of them. And I believe that's the reason why they are number one and number two in this race. It's good for recruiting the best scientists. It's also good for holding together and leading a fundamentally scientific enterprise like building artificial general intelligence. And the point where this came home to me is when I was talking to Demis one day about his motivation for building AI.

1:03:18Sebastian Mallaby:And he started to say, listen, when I'm reading scientific papers at two o 'clock in the morning, Sebastian, I see reality staring at me in the face, calling at me, saying I'm here to be discovered. And if I had artificial general intelligence, I could discover the fundamental rules that explain the fabric of reality. It would be like understanding all of nature, which presumably may have been created by some kind of divine intelligence. And so in this sense, my quest for AGI is kind of like my way of getting closer to what I might call God. Sebastian Malaby is the Paul A. Volker Senior Fellow for International Economics, the Council on Foreign Relations, a two-time Pulitzer Prize finalist.

1:04:03He is the author of six books, including More Money Than God and The Power Law, which have become investment classics. His latest book is The Infinity Machine, Demetis Havas Deepmai, and the quest for superintelligence. He also co-hosts a weekly CFR podcast, The Spillover, which examines the ripple effects of global events across policy, geopolitics, economics, technology, and financial markets. Sebastian, thank you so much for your time. Thank you so much. Nice to talk to you. This episode was produced by Claire Miller and Alison Weiss and engineered by Benjamin Spencer. Our video editor is Jorge Carty.

1:04:37Our research team is Dan Chalon, Kristen O'Donoghue, and Mia Silverio. Jake McPherson is our social producer, Drew Burrows is our technical director, and Catherine Dillon is our executive producer. Thank you for listening to Prof G Markets from Prof G Media. If you liked what you heard, give us a follow and join us for a fresh take on markets on Monday.

1:05:12Reunion As the world turns And the dark flies In love, love, love, love