Invest Like the Best with Patrick O'Shaughnessy - Marc Andreessen - The Battle For Tech Supremacy - [Invest Like the Best, EP.410]

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Starting point is 00:00:26 To see what happens when you eliminate the busy work, check out Ramp.com slash Inverc. Hello and welcome everyone. I'm Patrick O'Shaughnessy and this is Invest like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. If you enjoy these conversations and want to go deeper, check out Colossus Review, our quarterly publication with in-depth profiles of the people shaping business and investing. You can find Colossus Review along with all of our podcasts at join colossus.com. Patrick O'Shaughnessy is the CEO of Positive Sum. All opinions.

Starting point is 00:01:02 expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of positive sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of positive sum may maintain positions in the securities discussed in this podcast. To learn more, visit psum.vc. My guest today is Mark is the co-founder of Andresen Horowitz and one of Silicon Valley's most influential figures. He combines deep technical knowledge from his engineering background with broad historical understanding and strategic thinking about societal patterns. He last joined me on Invest Like the Best in 2021, and the playing field looks a lot different than today. I've made sure to try to listen to all of Mark's

Starting point is 00:01:48 many recent great podcast appearances to make sure that we covered very different ground than Mark has covered elsewhere. He goes deep on the seismic shifts, reshaping technology and geopolitics. We discussed Deep Seeks open source AI and what it means for technological rivalry between America and China, his perspective on the evolution of power structures and the transformation of the venture capital industry as a whole. Please enjoy our conversation. And if you haven't yet heard, last week at Colossus, we formally launched a subscription to our new property, Colossus review. It's a quarterly print, digital, and audio publication that profiles the investors, founders, and companies that we respect most in more detail than we've ever gone before. To learn more,

Starting point is 00:02:25 go to join colossus.com slash subscribe or click the link in the show notes. Mark, I think we have to start at the White Hot Center. Can you just riff on your reaction to Deep Seeks R1? There's a ton of dimensions to it. It's a really big deal. The U.S. is still, like, by far in a way that's sort of describe as science and technology leader in AI. And so most of the ideas in Deep Seek are derived from work that's been done in America

Starting point is 00:02:51 or in Europe over the last 20 years or actually amazingly 80 years. The original work on neural networks was done all the way back, you know, in the 1940s, an American and European research universities. And so from an intellectual development standpoint, the U.S. is still way ahead. But what DeepSeek is, it's a really, really good implementation of those ideas. And then they did this marvelous thing, which is they gave it to the world in the form of open source. It's actually fairly amazing that this has happened. There's kind of an inversion that's happened because you had these American companies with names like OpenAI that basically are completely closed.

Starting point is 00:03:19 Part of Elon's lawsuit against Open AI is he's demanding they changed their name from Open AI to closed AI. The original thesis of Open AI is everything was going to be open source. Everything's been closed down. And these other big AI labs like Anthropic are all. also completely closed. And in fact, they've even stopped publishing research. They've really taken everything proprietary. And the deep seat guys, basically, for their own reasons, are delivering on the promise of actually open AI, actual open source. And so they've published for both their LLM, which is called V3, and then for their reasoner, which is called R1,

Starting point is 00:03:47 the two parts of their system. They publish the code and they publish technical papers that document in detail how they built it and basically serve as a roadmap for anybody else who wants to do the same kind of work. So it's out. And so there's kind of this fake narrative out there that basically it's like if you use Deepseek, you're giving all your data to the Chinese. And that is true if you use Deep Seek on the Deep Seek website, if you use the service the way they run it, but you can download the code and you can run it yourself. I'll just give you an example of that. There's an app called Perplexity now that's quite popular in American company. You can use Deep Seek R1 on Perplexity, completely hosted in the United States. Both Microsoft

Starting point is 00:04:18 and Amazon now have cloud versions of Deepseek running where you can run it in their clouds and obviously both American companies, American data centers. And this is really critical. You can download the system now and you can actually. you run it. You can't run the full version yet on your laptop, but you can run it on $6,000 worth of hardware in your house or in your business. It's a comparable capability as sort of the leading edge systems from Open AI and Anthropic. Those companies spent many, many multiples of money to build their systems. Now you can run it on $6,000. And you have total control. If you're running it yourself, you have total control, you have total transparency to what it's doing. You can

Starting point is 00:04:48 modify it. You can do all kinds of things with it. And then it has this characteristic that works really well called distillation where you can take the big model that takes $6,000 worth of hardware and you can create smaller versions of it. And people online have already created smaller versions of it and built them so that you can run it on your MacBook or you can run it on your iPhone. And those versions are not quite as smart as the full version, but they are quite smart.

Starting point is 00:05:08 And you can create custom-tailed distilled versions that are smart at specific things. This is a very big advance in the form of making both LLM reasoning, which is creative reasoning, and then also R1, which is actual reasoning reasoning for things like math and code and science, making this something that was super esoteric six months ago

Starting point is 00:05:25 and ultra-expensive and proprietary. to something that's just universally available to everybody for free forever. And then every major tech company, internet company, every startup, we have tons of startups. We have dozens or hundreds of startups this week who are either working on basically replanting on a deep seek or incorporating into their products or figuring out the techniques that they used and using it to make existing AI systems better. The team at meta, Mark Zuckerberg talked recently about the team at meta is ripping it apart, taking the ideas totally legally because it's open source and making sure that the next version of Lama will be at least as good at reasoning or better. this really propels the world forward. The two big things that we can derive from that, one is AI is going to be ubiquitous.

Starting point is 00:06:01 There's all these AI risk people, whatever, safety people, the regulators, the bureaucrats, the government, the EU, the Brits with their safety thing. There's all these people that want to lock down to control AI. This basically guarantees that none of that's going to happen, which I think is great. It's very much in the tradition of internet freedom and free speech. And so I think that's fantastic.

Starting point is 00:06:18 And then this was a 30x cost reduction for the same capability in one step. And then maybe the final thing to note, What this shows is reasoning is going to work. And reasoning is going to work basically for any domain of human activity in which you can generate answers that can be checked after the fact as to whether they're correct or not by a technical expert. We're going to have AI that's going to be able to do human and superhuman level reasoning for real. And that's going to work in domains like very important domains, coding math, physics, chemistry, biology, economics, finance, law, and medicine. This basically guarantees every human being on the planet in five years is going to

Starting point is 00:06:49 have a superhuman AI lawyer, AI doctor, met there back and call it all time. just as a standard thing on their phone, it just is going to make the world much better and a healthier and more wonderful place. Obviously, this is like the least static story of all time. And within two months, this model will be stale. Other models will come out. Lots of innovation happening at every level of the stack. But just zooming in on today and this new paradigm that we've entered, if you were writing like a winners and losers column of all the various stakeholders, whether that's new app developers, incumbent software developers, infrastructure providers like NVIDIA, et cetera, closed source versus open source model companies, who do you view as the major

Starting point is 00:07:25 winners and losers post R1 today? To your point, if you're taking a snapshot in time just today, we'll start with that. So if you look at it a zero-sum game and there's winners and losers just at a point in time, let's start with the winners. The winners are all the users. And so the winners are all the users, all the consumers, every individual, and then every business that uses AI. We have all these startups that are doing like AI legal, AI lawyer. And last week, they were spending 30 times as much on AI as they're spending this week. For example, take a company building an AI lawyer. If the cost of your key input drops by 30x, it's like driving a car and the cost of gasoline drops 30x, all of a sudden you can drive 30 times as far on the same dollar, or you can use

Starting point is 00:08:03 that additional spending power to buy more things. And so all of these companies are going to be either dramatically expanding the capability of what they can do with AI in all these domains, or they're going to be able over their services cheaper free instead. And so all the users, the world, it's great. On a fixed-size pie basis, the losers, the losers, are the proprietary model companies, so open AI, Anthropic, and so forth, you'll notice both open-aithropic put out pretty strong but clearly provoked messages in the last week explaining why this wasn't terminal for them and there's an old adage in business in politics when you're explaining you're losing. They definitely notice this. And then the other is, you know,

Starting point is 00:08:33 Nvidia is the other company. There's been a lot of commentary on this, but Nvidia makes the standard AI chips that people use. There are some other choices, but Nvidia is the one that most people use. The margins on their chips are as high as 90%. And the company stock price reflects that most valuable company in the world. One of the things the deep seat guys did and documented in their paper is they figured out a way to use cheaper, actually still using Nvidia chips, but they're using cheaper chips, and they are using them much more efficiently. Part of the 30s cost reduction is you just need a lot fewer chips. And then by the way, China's building its own supply chain of chips, and these guys are also starting to use the Chinese derived chips, which is, of course,

Starting point is 00:09:07 an even more fundamental threat to Nvidia. So that's the snapshot at a point in time. But the thing is, the implication your question is there's another way to look at it, which is overtime. And over time, what you want to look at is the elasticity effects. Sautja Nadell use this phrase called the Jevitz Paradox. Think of this like gasoline. If you drop the cost of gasoline dramatically, then all of a sudden people are going to drive a lot more. This comes up in traffic planning a lot. So you'll have a city like Austin or something, and it'll be gridlocked, and somebody will have the bright idea of building a new freeway alongside the current freeway. And within like two years, the new freeway will have also filled up with traffic. And maybe it'll even be harder to get

Starting point is 00:09:38 from place to place. And the reason is because reduced price of key inputs can induce demand. If AI is all of a sudden 30x cheaper, people might use it 30x as much, or by the way, they might use it 100x as much or a thousand X as much. This might mean that AI gets built into many more things than it was going to get built into before and much more quickly. The economic term there is elasticity. So following prices equals explosion of demand. I think there's a very plausible scenario here that on the other side of this is just what happens is usage explodes. And deep seat does really well. And by the way, so to open a anthropic.

Starting point is 00:10:07 And by the way, so does Ividia and so do the Chinese chip makers. Then you have like a rising tide effect where the entire industry explodes and so. were really only at the beginning of people figuring out how to use these technologies. Reasoning just started working in like the last four months. Open AI released their 01 reasoner not that long ago a few months ago. Yeah, it's incredible. This is like fire being brought down from the mountain being given to humanity. And most humanity is not yet using fire, but they're going to.

Starting point is 00:10:29 I tend to be a believer that it's much more of a, at least for a while here, it's going to be much more of a positive something where there's just going to be so much explosive growth. And then, quite frankly, part of this is the old idea of creative destruction, which is like, okay, if you're opening AI or whatever, whatever you were doing last week is no longer good enough. But by the way, that's the way of the world. You have to get better. These things are all races. You have to evolve. And so this is also a very big motivating catalyst for a lot of the current companies to really sharpen their game and get more aggressive. One of the things that's so interesting is immediately like the mind switches, I think you called it the Sputnik moment.

Starting point is 00:10:59 One axis of comparison is the Americans versus the Chinese is a new race, not so much like Anthropic versus Open AI versus Lama or whatever. How do you think about that axis of competition and comparison and what it will really? result in. What is the Sputnik moment? Maybe explain that idea and riff on that new source of competition a little bit as well. The Sputnik moment metaphor comes from the first Cold War, the 20th century Cold War between the U.S. and the USSR. A lot of your listeners are too young. I remember that. I grew up, at least, in the tail end of that. I remember it quite clearly as a kid. It was still going hot for the first 18 years of my life. I remember in high school in the 1980s, literally thinking there was a good chance that we were all going to die at a nuclear holocaust.

Starting point is 00:11:36 The whole nuclear weapons thing, tensions ran super high during the 80s. There's a great TV show called The Americans that recreates what it was like. that time and like, it was tense. Things were not good. And then basically, right, the U.S.S. are peacefully collapsed and one of the more amazing twist and turns of history in 1989 and the Cold War never became hot, but it was pretty intense. And then there was this very aggressive rivalry between the U.S. and the USSR through that period. And that rivalry was military in many ways, including proxy wars all over the world. But that rivalry was also economic. And many, many Western experts insisted for decades that communism was better than capitalism

Starting point is 00:12:07 and inevitably, American economics textbooks, as late as the 1980s, said that inevitably the Soviet economy would win because state planning, central planning was clearly better than the messy process of capitalism. And so there was this massive economic battle playing out. Then there was an ideological battle playing out, which was basically freedom and democracy, critique the West however you want, Western hallmarks of freedom and democracy and free speech and so forth against the Soviet totalitarian system. The thing about that, though, was that economies were just simpler in those days and technology was simpler. And so the main outputs of the USSR in that era were basically wheat and steel, which is to say basic agriculture,

Starting point is 00:12:41 exports and then basic raw materials exports, oil, relatively simple commodities. And by the way, part of the reason the USSR lost is because the U.S. raced way ahead on technology, particularly the computer, starting in the 1970s, the computer took off. The Soviet system, the Soviet communist centrally planned system was unable to build their own computer industry and that map that they were ultimately doomed. Basically, the minute the microprocessor was invented and it just took about 20 years for that to play out. But anyway, there was a technological fight that also happened. So the dynamic between the U.S. and China is similar in many ways, but not completely. the same. Neil Ferguson and others have talked about U.S. versus China as Cold War 2.0. There's competition

Starting point is 00:13:16 along each of those dimensions. There's very different worldviews. There's very different political systems, very different economic systems. And then both the U.S. and China want to proliferate their philosophy and their method of government and their technology stacks and their industries around the world. You may recall there was this whole thing that played out over the last decade with this Chinese company, Huawei, that was going to all these other countries and basically selling them telecom equipment to builds broadband and wireless networks using a Chinese stack. The Chinese tech stack for building a telecom network was something like a third the price of the Western stack. There has been this pitch battle playing out globally where both the U.S. and China are trying

Starting point is 00:13:51 to get the world on their tech stack. Why would China want to do that? One is because Huawei is a big export industry to export routers and switches and the things that they make. But the other is just control. If a country basis, it's wireless network on Huawei, then the Chinese have the ability to backdoor the network anytime they want, they can listen in on any telephone conversation happening in whatever country implements that. So they have a massive geopolitical national security intelligence reason to proliferate this. And the Chinese state puts a lot of weight behind their national champions to go out globally and do this. And so we saw that playing out over the course of the last decade. AI is the next version of that. AI is the next thing that America, especially, by the way, under this

Starting point is 00:14:28 new administration, the last administration was conflicted on this, which we can talk about. But under this new administration, the Trump administration, the U.S. is a very clear national security, interest, priority goal. The government has a very clear goal to make sure that the U.S. tech is the global standard for all the reasons that we discussed. And then the Chinese also have that goal, and they have these programs with names like digital, Belt and Road and so forth, where they're going out and doing this. And AI is the next turn on that. And so every country in the world is going to be buying and adapting AI into their healthcare system and into their education system and into their transportation system, into their telecom system, into their computing fabric, into all this, their energy

Starting point is 00:15:04 system. AI is going to get infused into all these systems that run countries. So there's going to be this big fight of whether that's U.S. derived AI or Chinese derived AI. The assumption, of course, up until basically last week, is that China runs a closed political and economic system with a lot of state control, top-down control. The U.S. runs an open, democratic, bottoms up, free market system. So the assumption up until last week would have been that, of course, we Americans are going to have the more open and freedom-oriented approach to AI. And of course, the Chinese are going to come in with a much more closed, controlled, censored version. Like we said earlier, like at least right now, the funny thing, not funny ha ha, but like funny ironic thing is that that has flipped. And

Starting point is 00:15:42 sitting here today, China took the lead last week in having the best open system. They've kind of done a judo move. They're kind of using our strengths against us. It's net good for the world because everybody gets to download and use their stuff. And like, it's fantastic for all the reasons I described. And so this is far from a hostile act on their standpoint. It's much more of a generous act. But it's the kind of generous act that you would expect the West to do, not communist China to do. And then in the U.S., we have to decide how we're going to respond that AI policy in the West has been very screwed up because we have not been clear-eyed on this. And the way I describe it is over the last several years, I got very involved in the AI policy

Starting point is 00:16:14 debates in the U.S. and in the U.K. and then from a distance in the EU. And what I would describe as very fuzzy, confused thinking where you had a lot of people in power basically thinking, oh, yes, if it's a competition of China, we have to win. But if it's not a competition of China, then we can adopt a Chinese model and we can lock it down in our own societies. And we can use AI is an instrument of control and censorship in our own society. So as long as China is not a challenge, essentially the U.S., the U.K., the EU, are going to become more Chinese. They're going to have more centralized control, more restrictions, more lockdowns, more censorship. The Chinese are doing us a favor in an ironic way, which is they're kicking us in the butt and basically saying, I'm going to

Starting point is 00:16:48 impute something to them they haven't said, but basically the message is you Westerners are basically betraying your core principles. You're letting us do this the way that it should be done as opposed to you guys doing it. And if you in the West don't adapt and actually return back to your core principles of freedom and democracy and openness. China's not going to just let the world coast along. China's going to go ahead and seize that mantle. And I think it would be ruinously destructive for the West, if that's what happens. I think we need policies and companies and products that respond to that in the right way. It seems like such a fascinating and complicated scenario where they've released an open source model where the closed, say, Anthropic and Open AI type companies in the U.S.,

Starting point is 00:17:24 which have been the pioneers in the space, are saying, look, this model wouldn't exist if it wasn't for us. It is being built on top of our work. I'm curious for your reactions to like IP and the ability for them to do that. And I have both like a theoretical or ideological curiosity here and a practical one. I'm curious how you think about it through both of those lenses. Like if you're anthropic, let's say, how are you approaching this if you're running that business? What are your ideas ideological and practical about a Chinese company using models that were developed here in the U.S. with lots of capital to make the thing that then leads to this abundance for the world. It's such a weird thing to wrap one's mind around,

Starting point is 00:18:01 and I just love your reaction through those two lenses. Yeah, so there's some real issues here. There is an irony to the line of argument, and you do hear that line of argument. There's an irony to it, which, of course, is Open AI did not invent the transformer. The core algorithm of a large language model is something called the transformer. It was not invented at Open AI. It was invented at Google. Google invented it and published a paper on it. And then, by the way, didn't pursue it. They continued to do research on it, but they didn't productize it. And they didn't productize it because of, quote, unquote, safety. They were like, ah, this could be unsafe. And so let's not do it. So they let it sit on the shelf for five years.

Starting point is 00:18:28 And then the Open AI guys figured it out, picked it up, and ran with it. Andthropic is a spinoff of Open AI. Anthropic also did not invent the transformer. And so both of those companies and every other American lab, by the way, working on large language models and every other open source project is built on something that none of them actually created and developed themselves. By the way, Google invented the transformer that was in 2017, but the transformer itself was a derivation of the idea of neural networks.

Starting point is 00:18:50 Neural networks, you know, are an idea that goes back literally to the 1943. So 82 years ago is that. actually when the original paper on neural networks came out. And the transformer built on 70 years of research and development, much of it funded by the federal government and by European governments at research universities for a very long time. And so this is one of those things where there's this incredibly long lineage of intellectual thought and development that's gone into it. The vast majority of the ideas that go into all these systems were not developed by the companies that are currently building the systems. Nobody sitting here, including none of our companies, have any special

Starting point is 00:19:21 moral claim that somehow we did like de novo build that we should have complete control over. It's just not true. So I would describe arguments like that. It's frustration in the moment. And then by the way, there are also kind of moot point arguments, which is China went ahead and did it. It's out. It's done. Now, there is an argument around copyright. If you talk to experts in the space, a lot of people have been trying to understand why Deepseek is as good as it is. And one of the theories, and this is unproven theory, but one of the things the experts believe is China probably trained on data that the U.S. companies don't train on. And in particular, one of the really surprising things about Deepseek is deep seek is really, really good at creative writing.

Starting point is 00:19:51 Deepseek is probably the best creative writing AI in the world right now in English. And this is fairly weird because China's a different language. There's some very good Chinese novelist in English. Generally speaking, you'd expect the best creative writing to be coming out of the West in English. And Deepseek is today probably the best. And it's shockingly good. And so one of the theories is Deepseek trained, for example, there's these websites with names like Libgen that are basically giant internet repositories of pirated books.

Starting point is 00:20:14 I myself would never use LibGen, but I have a friend who uses it all the time. It's like a super set of the Kindle Store. It's got like every digital book and it's up there as a PDF and you can download it for free. it's like Pirate May for watching movies or something. The U.S. labs might not feel like they can just basically download all the books from LibGen and train on it, but maybe the Chinese labs feel like they can. So there's potentially differential advantage there. That said, there is this looming copyright fight. People need to be careful on how they think about this, because there's this looming copyright fight where certain publishing companies that you would basically like to prevent generative AI companies like OpenAI.

Starting point is 00:20:46 Anatropic and Deepseek from being able to use their content. And there's one argument that says that that material is copyrighted and can't just be used willy-nilly. there is another argument that basically says an AI training on a book, you're not copying the book. You're reading the book. It's the AI equivalent of reading a book. And you and I are allowed to read a book out from the book. By the way, we're allowed to check a book out from the library. We're allowed to pick a book off the street. We're allowed to read a book. Those are all legal. We're allowed to read the book. And then we're allowed to read the book. And then we're allowed to go about our daily life and talk about the ideas that we learned of the book. There's another argument that says that training an AI is much more analogous to human being reading a book as opposed to stealing it. And then there's just this practical reality, which is if China doesn't doesn't care about US copyright, which they traditionally don't, and their AIs can get trained in all the books. And if the American companies are prohibited ultimately by law from being able to train of the books, then the U.S. may just lose on AI, just from a practical standpoint. That may be a deathblower, where it's just like they win and we lose. There's sort of that whole snarl of arguments in there. One of the things that DeepSeek has not revealed is the data that they train on. And so you don't

Starting point is 00:21:44 get a copy of the data when you download Deepseek, you get what are called the weights. And so you get the neural network that results from training on the material that they trained on. but from that, it's very difficult or impossible to look inside and sort of derive the training data. By the way, also neither do Anthropic or Open AI reveal the data that they train on. Then there's intense speculation in the field as to what's in the Open AI training data and what's not. They consider it a proprietary secret. They don't release that. And so the Chinese Deepseek may or may not be doing things differently than these companies.

Starting point is 00:22:11 They may or may not have a different approach to copyright. By the way, maybe this is all the moot point. Maybe they're all using the same data and Deepseek just figured out a better way to encode the algorithm. That we don't know. we don't actually know what the open-AI in Anthropic algorithms are because they're not open source. We don't know how much better or worse they are than the deep seek algorithms passed in public. Do you think that some of the closed source models, Open AI Anthropic and any others that enter the fray end up looking more like Apple to Google's Android or something? It's very hard to know what's going on inside of Apple.

Starting point is 00:22:37 It's an incredibly well-protected IP company. And better than this question is what you personally are rooting for, the set of outcomes that you think are best for America and for the world vis-a-I. I'm in favor of maximum competition. And by the way, like, that fits with the theme of I'm a VC. So one of the things about being a VC is if you're a company founder, if I'm like running an AI company, I need to have a very specific strategy that has pros and cons and tradeoffs. I need to think hard about that. As a VC, I don't need to do that.

Starting point is 00:23:04 I can make multiple bets that have contradictory feces. This is a little Peter Thiel thing, right, of determinate optimism versus indeterminate optimism. A company founder's CEO has to be a determinant optimist. They have to have a plan. And they have to make the hard tradeouts to be able to succeed at that plan. A VC is an indeterminate optimist. We can fund 100 different companies with 100 different plans with mutually conflicting assumptions. And so the nature of my job is I don't have to make the call that you just described.

Starting point is 00:23:28 And then that, let's just say, makes it easy for me to make a philosophical argument, which I really deeply agree with personally, which is I'm in favor of maximum competition. So I'm in favor of the free market. I'm in favor of maximum competition, maximum freedom. And essentially, if you think about it at one level down, a maximum rate of evolution. Being able to have as many smart people as possible come up with many different approaches as possible, run them against each other in the free market and see what happens. Specifically for AI, what that means is I'm in favor of the big labs running as fast as they can. I'm 100% supportive

Starting point is 00:23:56 of Open AI Anthropic doing whatever they want, bringing whatever products to market they want, running as hard as they want. As long as they're not getting preferential policy treatment or preferential subsidies or preferential support from the government, they should be able to do whatever it is that they do as a company. I'm in favor obviously of startups. I want lots of startups to try lots of different things. And we, of course, are very active in funding AI startups of every shape, size and description. So I want them to be able to run. And then I want open source to be able to run. And I want open source to be able to run in part because I think it's good. If stuff shows up in open source, even if it means that there are some business models for companies that don't work,

Starting point is 00:24:28 the benefit to the world and to the industry as a whole is so big, we'll find other ways to make money. AI will just be like a lot more common and a lot cheaper and a lot easier. And I think that would be a great outcome. And then the other really critical thing about open source and the reason we all need to defend and protect open sources, without open source, everything just becomes a black box. Without open source, everything becomes a black box owned and controlled by a small handful of companies that end up essentially colluding with the government,

Starting point is 00:24:49 which we could talk about. But you need open source to be able to look inside the box and see what's happening, all this stuff. And by the way, you also need open source for academic research. And you need open source, therefore, for teaching. And so one of the issues with AI prior to the open source models, so going back two years when there were no, basically, open source LLMs, meta released Lama, the two big ones,

Starting point is 00:25:09 Lama, then Mistrawl out of France, and then now deep seek. But before those open source models emerged, there was a crisis that was brewing in the universities in the educational system, which is the university researchers at places like Stanford and MIT and Berkeley didn't have the money to be able to buy a billion dollars worth of invidia chips to be able to actually be in the game. And so if you talk to computer science professors at the top universities two years ago, they were very worried. Actually, the first worry was my university is not going to have enough money to be able to stay in the game and do anything relevant in AI anymore. And then the other worry was all the universities together are not going to have enough

Starting point is 00:25:39 money to be able to do anything and stay in the game because nobody can keep up with the fundraising of these giant companies. Open source puts the universities back in the game. And it means that if I'm a professor at Stanford or MIT or Berkeley or any state school, whatever, University of Washington, whatever, I can now teach how this stuff works and I can teach using the Lama code or the Mistral Code or the Deep Seat code. I can do research on that. I can actually continue to make breakthroughs. I can publish my research so people can actually see what's happening. And then every new generation of kids coming along that shows up for freshman computer science course is going to learn how to do this now in a way that they wouldn't

Starting point is 00:26:09 if this was a black box. We need open source in the same way we need freedom of speech, academic freedom and freedom to research things. And so my model is basically let the big companies, the small companies and open source run and compete against each other. That's what happened in the computer industry. It worked really well. That's what happened in the internet industry. It worked really well. I believe that's what's going to happen in AI. I think it's going to work really well. One of those can work. Is there a limit to wanting max evolution speed and max competition? Perhaps if I said we know that the best things are going to come out of China for sets of reasons because they're willing to do things that we don't let our companies do in the U.S.

Starting point is 00:26:41 Would there be a version of this where you said, like, yes, I want max evolution and competition, but the national interest at some level supersedes the desire for max evolution and speed of development? That argument is a very real argument. It gets deployed frequently. It is being very actively deployed in the AI space. And in fact, as we sit here today, two things. So one is there are actually currently existing sanctions on, yes, for Western companies and

Starting point is 00:27:04 American companies to sell leading edge AI ships to China. It's actually not legal today, for example, for Nvidia to sell its leading edge AI chips to China. We actually live in a world in which that decision has been made and that policy has been implemented. And then the Biden administration had moved actually put out an executive order, which I think has now been revoked, but they had put out an executive order that was going to apply that same kind of restriction, basically sanctions process to software. This is a very live argument. And there's going to be another round of these arguments in D.C.

Starting point is 00:27:26 As a consequence of the deep seek thing, those conversations are underway. And then basically what you have there is kind of a classic thing that you have when you get into policy disputes, which is you have the rational version of that conversation. which is what's in the national interest from a theoretical standpoint. And then you have the political version of the conversation, which is, okay, what is the political process actually going to do with the rational argument? And let me just say, we all, I think, have a lot of experience watching. When a rational argument encounters the political process, it's usually not the rational argument that wins. What you get out of the other side of the machine is not what you

Starting point is 00:27:57 win in thinking you were going to get. And then there's a third factor that we always need to talk about, which is the corrupting influence of especially big companies. If you're a big company and you're threatened by what's happening in China or what's happening open source. Of course, you're going to try to weaponize the U.S. government to protect you. And maybe that's in the national interest and maybe it's not. But you're for sure going to push for that whether or not it's in the national interest. And so that's what makes the conversation complicated. And so let's just talk about the chip embargo for a second. So you can't sell leading edge AI chips to China. So that leads to basically a couple things. So one is for sure it sets them back in certain ways. There's certain things that they're not going to be

Starting point is 00:28:28 able to do. And maybe that's good because you've decided that's in the national interest. But let's just say there are three other interesting consequences of that. So consequence number one is you now given Chinese companies an incredible motivation to design how to do things on cheaper chips. And that's a big part of the Deep Seek breakthrough is that they figured out how to use the cheaper chips to be able to do things that take the American companies, the larger chips. And that's a big part of the news on Deep Seek. And that's one of the reasons why it's so much cheaper. One of the reasons you can run on a $6,000 with the hardware is because they put a lot of time and energy into optimizing the code so that it will run efficiently on the cheaper chips that are not

Starting point is 00:28:59 under the sanctions. You force an evolutionary response. So that's response number one. that maybe has already backfired in a significant way. Consequence number two is you are incenting the Chinese government and Chinese private sector to develop a parallel chip industry. So if they know that they can't get American chips, then they are going to, they're doing this right now. They have a whole national program to build up their own chip industry so that they're not dependent on American ships.

Starting point is 00:29:22 So in the counterfactual, maybe they would have bought American ships. Now they're going to figure out how to make their own. Maybe it will take them five years to be able to make their own. But once they get a position where they can make their own, then we have a direct competitor on the global market that we would not have had if we had just sold them the chips. And by the way, at that point, we're in no control over their ships. They're in total control.

Starting point is 00:29:39 They can backdoor them. They can sell them at below cost. They can do whatever they want. By the way, the other twist on that is Taiwan. China has wanted to reunify with Taiwan for its own reasons for a very long time. But if you're the CCP right now, Taiwan is a very tempting target in part because you already want it, but in part because it has these magic fabs. If you can't buy chips that come off those fabs, but you could seize the island and take the fabs, right?

Starting point is 00:30:01 That would be a double reason to go invade Taiwan. And so it's possible these sanctions are going to accelerate the timeline of China doing a military invasion of Taiwan. So that gets complicated. That gets very hairy. So the consequences of this get very tricky. It's very hard to calibrate these things. And again, the main thing I could just say here is the issues are real, the tensions are real, the tradeoffs are real. There are rational arguments that need to be discussed and need to be argued out.

Starting point is 00:30:22 But we need to actually do that rationally. And those of us participating in the system and watching from afar and voting need to basically keep our eye on this to make sure that the political process is taking rational arguments and twisting them into something. something that's either going to backfire or is going to end up just serving a small set of private interests. As always the case, these outcomes are so incredibly complicated and unintended consequences happen everywhere. I'm curious for a little extra thought on the software side. Everyone's aware of TikTok and whether or not that's going to persist as an app that our

Starting point is 00:30:49 kids can use here in the U.S. But Deepseek is another great example where it's the top of the app store or lots of American people downloading it. I'm curious what you personally, again, are rooting for in terms of our treatment of software provided by China, which tells the CCP or who may be. ever, tons of information about American users and their behavior and how you think about that, again, through the practical and ideological lenses. So I'm a single-celled organism on this question.

Starting point is 00:31:14 I have a single function. I want America to win. I want America to win. That's the only thing I care about. And the reason of that is not because I want America to dominate the world, but because I think the world's a much better place if America wins because the American values of freedom and democracy are superior values to, let's say, totalitarian, authoritarian values. Specifically, though, I don't want America to win like a war.

Starting point is 00:31:32 I don't want to have a war. I don't think we should go to war with China. I hope we never go to war with China. That would be very destructive. I would like to see America win this Cold War 2.0 the way we won the First Cold War. So basically what happened to the First Cold War was the Soviets. The Soviets was basically win. They were not going to be able to win. Their economy was not as effective. They were falling behind in technology. They were entering various kinds of social and economic crises as a result of their dictatorial approach to running countries. They had become very corrupt. Their system was not actually working. Contra, the American economists at the time, the communist system was not actually working, it wasn't performing. This is the famous story. If you go to the two grocery stores, go to grocery store in Moscow and a grocery store in New Jersey, and you're just like blown away by how much better the grocery store is in New Jersey. You just wanted to become basically so obvious that actually the correct thing for the Soviet Union in 1989 was to just simply say, we're done. We're not fighting this anymore. We're done. We're going to stop threatening

Starting point is 00:32:21 you. We're going to stop competing with you. We're going to stop all this stuff. We're just going to be a country. We're going to be a normal country. And we're going to have normal relationships. And the Russian people are much better off as a consequence. I would like to see the CCP and the Chinese people at some point basically just decide, look, there's no point in having this fight. We should just be partners. We should just be partners with America. We should be trading partners. We should have peaceful coexistence. And we should love each other. And it's all great. We just don't need to have this fight. I believe that the way to win this fight is not to get ultra aggressive. The way to win this fight is to be strong so that we know that we can obviously defend ourselves.

Starting point is 00:32:50 If push comes to shove. But fundamentally, to double down on our values and double down on our values of openness and freedom and democracy and peace. And in that sense, to be strong but not threatening. So it's like, yes, if you fight with us, we're going to win the hard way. But what we'd like to do is just have peace and understanding and trade and freedom. And we would like the Chinese people to flourish in the exact same way the American people flourish and everybody builds a better world. And this is a big part of my philosophical discussion I get in with people in D.C., which is like the impulse that people in D.C. can get into where they're like, we need to lock things down, control things, ban things, prohibit things. We need to do all these things, deny things to other

Starting point is 00:33:25 countries. It's like, okay, but are we sabotaging ourselves? Are we betraying our values? Are we sabotaging our ultimate geopolitical strategic position and the benefits of being America and of being the beacon of freedom and hope and democracy in the world. In other words, are we going to win by becoming more like China or more like the Soviet Union or are we going to win by becoming more like America? And so I'm kind of always pushing on the side of, no, let's be more like America. Let's be more free. Let's be more open. Strong, but more friendly, more collaborative, more cooperative, and essentially seduce the world into being on our side as opposed to restricting and controlling and overtly threatening. How do you think all of this will affect

Starting point is 00:34:00 capital allocation. I'm most curious for maybe your firm how you think it'll affect Andreessen Horwitz five years hence or something like that. If I think about investing firms as some bundle of the ability to form and raise capital, the ability to do great analytical work and the ability to judge people or something, especially in the earlier stages, how do you think that function, how capital gets allocated to entrepreneurs that are building the next great companies, will change as a result of 07 coming out and having this incredible reasoning ability, the incredible analytical ability. What will be the most different about capital allocation and investing because of all of this?

Starting point is 00:34:36 Yeah, so the analytical component hopefully will change dramatically. One assumes that the world's best investment companies are going to be very good at harnessing this technology for the use of the kind of analysis that they do that we do. Now, having said that the whole thing where the shoemaker's son has no shoes, one might say that maybe the venture firms that are the most aggressive at investing in AI might be among the less aggressive and actually figuring out how to use it. We have a bunch of internal efforts underway that I'm super excited about, but verbs like cars need to be on the ball here. So we need to actually do it. Some of that work happening yet,

Starting point is 00:35:01 probably not across the industry, probably not enough. Having said that, there is another side to it. And for like late stage investing or for public market investing, a lot of people you talk to have a very analytical lens. And there's even, you know, great investors. I think it's Warren Buffett. I think he never does management meetings. I don't know if it's true or not. But the story I've always heard is Warren doesn't want to meet with CEOs. He wants the ham sandwich companies. Yeah, yeah, he wants the ham sandwich companies. And I think he's also a little bit worried that he's going to get seduced by a good story. A lot of CEOs, they're very charming. Gavis describes that great hair, great teeth, their shoes are shiny, the suits impeccable. They're really good at selling. And

Starting point is 00:35:31 among the things they're really good at selling as their stock. And so if you're Buffett, you sit in Omaha, what you do is you read the annual reports. The companies put everything in the annual reports and they're constrained by federal law to make sure that it's true. And so that's how you analyze. And so should 01 or 03 or 07 or R4 or whatever the reasoning models are, should that be better at analyzing annual reports than at least most investors doing it by hand? Yeah, probably. As you know, investing is an arms race like everything else. And so if it works for one person, it'll work for everybody. It'll be an arbitrage for a little while, and then it'll close and it'll become standard. And so I would expect the investment management industry

Starting point is 00:35:59 will adopt this technology in that way. This will become a standard way to operate. I do think it gets a little bit different, especially earlier in the process for early stage venture. What I'm about to say may just be wishful thinking on my part. I might be the last Japanese soldier on the remote island in 1948 by saying what I'm about to say, I'm going to attempt fate. But I'm going to say, you know, look, so much of what we do on the early side in the first five years is really very deep evaluation of individual people. And then it's working with those people in very deep partnership. And this is one of the reasons, by the way, that venture doesn't scale well. Particularly venture doesn't scale well geographically. The geographic scale experiments tend not to work.

Starting point is 00:36:29 And the reason is just because you end up having to be face to face with the people for a long time, both during the evaluation process, but also during the building process. Because in the first five years, these companies generally aren't on autopilot, you actually work with them a lot to help make sure that they do the things that they're going to need to succeed. There's a part of this that is very, very deep interpersonal relationships, conversations, conversations, interactions, coaching. By the way, we learn from them. They learn from us. It's a lot of back and forth. We don't come in with all the answers, but we have one lens because we see a panorama. They have another lens because they're in the specific details a lot more than we are. And so there's

Starting point is 00:37:01 tremendous interpersonal interaction that happens. Tyler Cohen talks about this. I think he calls it project picking. Certainly talent scouting would be another version of this, which is basically like if you look back over hundreds of years, for any new area of human endeavor, you almost always have this thing where you have very idiosyncratic people who are trying to do something new. And then there's some professional support layer of the people who fund them and support them. For the music industry, that's David Geffen finding all the early folk artists and turning them into rock stars, or it's David O'Selznick finding the early movie actors and turning them into movie stars, or it's the guys sitting in a cafe, a tavern in Maine 500 years ago figuring out which whaling

Starting point is 00:37:39 captains are going to be able to go get the whale. There, you know, is Queen Isabella getting the pitch from Christopher Columbus or the Royal Chambers and saying, yeah, that sounds plausible. Why not? there's this alchemy that has developed over time between the people who do the new thing and then the people who sort of enable support and fund those people. Let's just say, like, there's no guarantee that this continues, but that's like a 400, 500 year endeavor. Honestly, probably it's thousands of years old. You probably had tribal chieftains 2,000 years ago, three thousand years ago sitting around a fire and the young warrior would come up and say, I want to go take a hunting party into this other thing and I want to see if there's better game

Starting point is 00:38:11 over there and the chief sitting around the fire and trying to figure out whether to say yes or no. So there's something very human about that. My guess would be that that continues. Having said that, if I meet the algorithm that can do that better than I can, I will instantly retire. We'll see what happens. I mean, you're building one of the biggest firms in this part of the capital allocation universe. How, if at all, have you adjusted your plans and strategy for building the business in the face of this technology down to the practical now we're doing more of this or less of this? How have you adjusted the direction of the ship based on this new technology? A big part of running a venture firm in our view is there's a set of values you

Starting point is 00:38:45 need to have in a set of behaviors that are what we call timeless. Respect for the entrepreneur, for example. You need to have tremendous respect for the entrepreneur and the journey that they're going on. You need to be deep in the details to really understand what they're doing. You don't do drive-bys. You're building deep relationships. You're going to work with people for a long time. By the way, the companies are going to take a long time. We don't believe in the overnight success. Most of the great companies get built over 10 years, 20 years, 30 years. V VD is a great example. I think coming up on their 40th anniversary. And I think actually one of the original VCs and VDIS, I think actually still on the board. That's like a great example of one of these long-term

Starting point is 00:39:14 builds. Anyway, so there's this core set of beliefs and views and behaviors that we're not changing at all that kind of have to do with that. Another is the face-to-face thing. You have to be face-to-face of these things remote. That's the one hand. But on the other hand, you need to be very up to the minute because the technologies change so fast. The business models change so fast. The competitive dynamics change so fast. If anything, the environment's getting more complicated because you've got many countries and now you've got all these political issues, which also make things more complicated. We never really worried about the political system interfering with, bringing pressure to bear on the things that we invested in, really up until basically about eight years ago,

Starting point is 00:39:46 and then it really intensified about five years ago. But for the preceding 10 years of us as a firm and the preceding 60 years of venture capital, it was never a big deal, but now it is. And so now we need to adapt and we need to be involved in politics in a way that we weren't before. Or now we need to adapt and we need to figure out maybe AI companies are going to be very fundamentally different. Maybe they're going to be structured in a totally different or to your point, maybe software companies are going to work totally different. You have an example of the question we ask a lot right now, which is like, what does the org chart look like for a company that actually fully uses AI?

Starting point is 00:40:12 is it similar or is it actually very different? And there's no single answer to that, but we're thinking hard about that. So that side of our brain basically says, you need to be up to the minute. You need to be extremely fluid in reacting to new information. And then I think the delicate dance that we do every day is to try to figure out what's timeless and then what's up to the minute. And that's a big part conceptually of how I think about the firm is we need to navigate through that and make sure that we know which is which. It's so interesting to me that your firm, which is obviously a huge footprint now, is similar in some senses to like the KKRs or Blackstones of the world where you and Ben were founders, seasoned founders when you started this

Starting point is 00:40:45 firm. And similar with Blackstone, I think Schwartzman had never made really an investment before starting Blackstone. And look what it's become. And it seems like the founder approach, previous founder approach to building asset management investing firms is that they build these real big, ubiquitous platforms. You've got verticals in most of the major exciting technology frontiers. Do you think there's some credence to that that the very best capital allocation platforms have and will be started by founders more so than by investors. Yes, a couple things. So one is, I mean, I think the observation makes a lot of sense.

Starting point is 00:41:16 The way that people in the business talk about it is basically there's a lot of investment operations that are usually the term as partnership is what you hear, right? A lot of venture firms work like this historically. It's just a partnership. It's like a small tribe of people sitting in a room together trying to bounce ideas off of each other. And then they make the investments. By the way, they don't have a balance sheet.

Starting point is 00:41:32 You know, some private partnership. They pay out the money in the form of compensation at the end of every year. That's a traditional venture capital. A traditional venture capital model was six GPs sitting around. on table doing that. They had their assistance. They had a couple of associates. But the point is like, it's completely based on the people. And by the way, it actually turns out in most cases what you discover is the people actually don't like each other that much. Mad Men did a good job of this. Remember in Mad Men, it's like the members went off and started their own company in the

Starting point is 00:41:53 four season, third season, four season. They actually didn't like each other. They kind of knew they had to come together to start a firm. And that's how a lot of these firms operate. And so they're like these loosely affiliated tribes. And then you get this phenomenon. They call you eat what you kill. Each person wants to make the most of the money off the things that they do and they don't want freeloaders, but it's a partnership and it's a vote to try to change anything. And so it's hard to fire people. So anyway, it's like private partnership. And it's fine for what it is. But then what you see with those is basically they have a hard time sustaining. There's no franchise value. There's no underlying enterprise value. It's not a business. And what you see with those is

Starting point is 00:42:23 basically when the original partners at a firm like that are ready to retire or do something different, they hand it off to a new generation. Most of the time, the new generation can't keep it going. And most firms in that model, I think now are kind of phasing out for that reason. But even if they can keep it going, there's no underlying asset value. That next generation is just going to have to hand it off to the third generation. It's probably going to fail on the third generation. And then it's going to be on Wikipedia someday. It's like, yeah, that firm existed at one point and then it went away and other firms took over and

Starting point is 00:42:48 ships passing in the night. So that's the standard way to do it. And by the way, if you trained as a classical investor, you've been trained how to do the investment part, but you've never been trained in a business building, to your point. And you've never built a business. And so it's not natural for you to build a business. You don't have the skill setter experience.

Starting point is 00:43:00 And so you just don't do it. And many investors have made tons of money as investors running in that model for a long time, so it can work really well. The other way is to build a company, build a business, build something with enduring franchise value in there. You alluded to firms like Blackstone and KKR, where they're huge public companies, Apollo, these huge firms. You probably know the original banks actually were all private partnerships. Goldman Sachs and JPMorgan 100 years ago looked like little venture capital firms much more than they look like what they look like today. But then their leaders over time turned them into these huge franchises and they're also big public

Starting point is 00:43:29 companies. So that's the other thing to do is kind of build a franchise. Now, to do that, you need a theory as to why a franchise should exist. You need a conceptual theory. as to why it makes sense to do that. And then, yeah, you need the business skills. And then at that point, you're running a business and it's like running any other business, which is like, okay, I've got a company, it's got an operating model, it's got an operational tempo, it's got management capabilities. It has staff. It has multiple layers. It has training programs. It has performance management. It professionalizes its operations. It has division of labor internally with specialization. And then you think in terms of scaling. And then you think in terms of over time, you think an

Starting point is 00:43:59 underlying asset value where the thing has a value that's not just the people who happen to be there at the moment. It's not like we're like chomping at the bit to take it public or whatever, but a big part of what we've been trying to do is build something that has that kind of enduring aspect to it. Are there aspects of the firm that you hope are new and different in 10 years that don't currently exist? And are there any non-compromisables? Ways that you hope the firm never evolves to look more like traditional large-scale asset managers. We evolve very rapidly in what we invest in. And so what the companies are, what they do, what the models are, what the founder backgrounds are, that stuff changes all the time. I'll give you an example, like for 60 years of venture capital, the one thing you

Starting point is 00:44:35 never did, everybody knew the one thing you never do is you never back a researcher. You never back a PhD to like start a company and do research. He'll just do research, burn the money out, and you'll have nothing at the end. Now, the best AI company, many of the best AI companies were founded by researchers. That's one of those things where it turned out that was not a timeless value that needed to be an up-to-the-minute thing that you needed to adapt. We need to be very fluid on that. And then as a consequence of that, what those companies need to succeed, what they need from us, the kinds of help that they need from us, that also changes. And The most significant change at our firm, I mentioned before, but it's, we now have a big political

Starting point is 00:45:04 operation by even just general business standards. We have one of the largest and now most sophisticated political operations, I think, in the business world. And four years ago, we had nothing. We had zero in politics. And so that's a function that we didn't imagine we would need. I'm sure that in 10 years, we will both be investing in things I can't even conceive of today, and we will have operations that I can't even conceive of today. So I'm sure that will all change. We're totally open to change in all those dimensions. There's a bunch of timeless values. I would hope that the firm values are going to be the same in 10 years, because I think those are pretty well thought through. But the other thing that I'm always telling our people internally and always

Starting point is 00:45:32 telling our LPs is we are not trying to build for scale in order to be a large scale asset manager. Like the pejorative in the industry, an investment industry is asset gatherer. The firm reaches a point where it just decides to go for size and scale, tens to hundreds of billions of dollars to to trillions of dollars. And it's not going for great returns anymore. It's just going for scale and mass. And the accusation of firms that do that is they're trying to harvest the fees more than they're trying to outperform on the investments. That's not what we're trying to do. We're not going for scale for scale sake. When we go for scale, it's because we think it's necessary to support the kinds of companies that we want to help our founders build. But the way I describe it is the core of the

Starting point is 00:46:05 firm is always and will always be early stage venture. And so no matter how big we get, if we raise these larger growth funds, whatever, can be able to write bigger checks. Some of the companies need very large amounts of money. We didn't start with a growth fund and now we have a growth fund. But the point is the core of what we do is always going to be early stage venture. And that confuses people a bit. I would say people get confused on this because from the outside, it's like you guys are managing so much money, why as a founder of an early stage startup would I believe that you would want to spend time with me because it's not worth your time. You A16Z are going to invest $5 million in my Series A or whatever, but you have these other investments that you've invested

Starting point is 00:46:36 $500 million in. Why are you going to spend time with me? And the reason is because the core of the business is early stage venture. By the way, the return opportunity off that early stage investment is as big as the return opportunity from the later stage companies, which is a characteristic of startups. So number one, financially it actually makes sense for us to spend time with the early stage. But the second is all of our knowledge and all of our relationships and everything that makes us special as a firm is all the deep insight and all the people that we know and who trust us at that early stage. And so what I always tell people is, look, if push comes to shove and the world goes sideways and we need to like sacrifice things, the thing that will never get sacrificed

Starting point is 00:47:09 is the early stage venture business, that will always be the core of it. And the big part of what I try to do with that is then have a lot of my time free. And I think generally our founders actually get fairly surprised by this is I have a lot of time free in order to work with the early stage founders. Number one, it's super fun, but also like you learn the most. If you think about the changing nature of power structures in the world, we talked a lot earlier about America, China as like Cold War 2.0. I've always seen you tweeting about tons of books studying this specific topic transitions in power through world history. Where else do you have your eye today on power centers that are changing, either gaining or losing power, that interests

Starting point is 00:47:44 you most? The Machiavellians, I'm sure you've probably had a dozen people on your show that have recommended it. It's one of the great books of the 20th century, and it goes through kind of this theory of political power and social and cultural power. And one of the key things in that book I see everywhere right now is this idea of elites and counter elites. The idea goes like this. It's basically democracy per se is a myth. You never have an actual fully democratic society. By the way, the U.S. of course, is not a democracy. It's a republicans. It's a republicans. Experiments in direct democracy historically have worked very badly. The systems that work, even the democratic systems that work, they tend to be Republican in nature, small, are a Republican in

Starting point is 00:48:14 nature. They tend to have a parliament or they have a house and senator or something. They have some sort of representative body. The reason for that is a phenomenon described in that book is called the Iron Law of Oligarchy, which basically is the following, which is the problem with, quote, direct democracy is that the masses can't organize. You can't actually get 350 million people to organize in anything as too many people. So what you have in basically every political system in human history is you have a small organized elite that governs a large, disorganized mass. You had that in the original hunter-gather tribes all the way up through to America and every other political system in the modern era. By the way, this was Greeks, and it was the Romans, and it was

Starting point is 00:48:49 every other political society that ever worked. Every empire in history, every country in history. So a small organized elite governing a large, unorganized mass. And that's a relationship that's fraught with peril, because the unorganized masses will go along with the elite for a while, but not necessarily forever. And if the elite becomes abusive towards the masses, the masses, greatly outnumber the elites. And at some point, they're going to show up with pitchforks and torches. So there is some tension there. And a lot of revolutions occur when the masses decide that the elites are no longer representing them properly. And so our society is no different than any other society, which is we have large, disorganized masses, we have a very small organized elite. We have two elites,

Starting point is 00:49:22 our political system, our founders set up. We have our Democrat elites and our Republican elites. And by the way, with quite a bit of overlap between them, some people actually call that the Unip Party. Maybe those elites have more in common with each other than they do with any of the people. Those elites cruise along. We had an establishment Republican elite for a long time with its policies that kind of culminated in the bushes. We had a Democratic elite with its policies that kind culminated with Obama. In the last decade, basically on both sides in the U.S., there's basically been a revolt within the elites. And this is actually the key point in the Machiavellians is the way change happens usually is not the masses activating against the elites directly. What happens is

Starting point is 00:49:54 it's the emergence of a new counter elite. You'll have a new counter elite that will compete to take over from the current elite. My read of current affairs broadly throughout the world is generally the elites that run the world are being found to have done a bad job. And we can talk about why in a second, but like generally speaking, if you look at approval ratings of political leaders, approval ratings of institutions, everything is crashing. The uniform thing that's happening in the world, political people call this anti-incumbency. Basically, if you're an incumbent institution, if you're an incumbent newspaper, if you're an incumbent TV network, if you're an incumbent university, if you're an incumbent government, generally speaking, your poll ratings are a disaster. That's the people

Starting point is 00:50:30 basically saying the elites in charge are failing us. And then you have the emergence of these country elites who are coming along and saying, oh, I know, I have a better way to represent the masses, and I have a better way to take over, and my new counter-elite movement should take over from the elite movement. And the Democratic Party, this was Bernie Sanders in 2016. It's AOC. It's that whole wave. Republican Party, obviously, is Trump, and it's the mega movement and everything that that represents. But by the way, this exact same dynamic is playing out in the UK. The Tories have collapsed, and now you've got this reform party with Nigel Farage that is very threatening. You had Jeremy Corbyn, who was a counter-elite coming in from the left. You have that in Germany.

Starting point is 00:51:04 Actually, this week in Germany, there's this very dramatic thing happening, which is this, quote unquote far right party AFD is rising very fast and there's this leader Alice Widel. And this is the first week in German political history in like forever in like 50 years or whatever. The CDU in Germany actually partnered with AFD on something. All of a sudden, AFD is like a viable competitor. They're the counter elite trying to take over the right of the German political system. So basically everywhere in the world you go, you've got a counter elite basically showing up and saying, oh, I can do this better.

Starting point is 00:51:30 And it's a fight between elites. It's a fight between the elite and the counter elite. It's a fight that the masses are aware of and they're watching. In democratic societies, they're ultimately going to decide because they're going to decide who they vote for. This was when Republican voters decided they were going to vote for Trump and not Jeb Bush. That was the counter-elite beating the elite. This actually goes to the critiques of Trump, which is so interesting, which is Trump gets criticized a lot by the existing elites. It's like, oh, he's not actually a man of the people.

Starting point is 00:51:52 He's like a super-rich billionaire who lives in a golden penthouse and gets driven around everywhere in a limo. You know, if you're a rural farmer in Kentucky or Wisconsin, you shouldn't think this is one of your people. And the point never was that Trump is a man of the people. The point was Trump is a counter-elite who's able to represent the people better. that's the whole basis of his movement. And anyways, that's the general pattern. And I just think you see that everywhere in our society. And then look, you're an example of this with what's happening in the media.

Starting point is 00:52:14 Everything I just described is exactly what's happened in the media. You had elite media for 50 years and it was network news and cable news and newspapers and these prestige magazines. And now you've got the counter elite. And the counter elite is you and Rogan and dot, dot, dot on and on. By the way, you look at the numbers and it's very clear where the people are going. The people, the viewers, the masses, the readers are fleeing the old and they're going to the new.

Starting point is 00:52:34 the incumbent elites are absolutely furious about it. They're furiously writing all these hit pieces about how you guys are all a bunch of white supremacists and the whole thing is horrible, right? And it's like, yeah, it's the way of the world. And so we're in the middle of this. I don't even know it's just transitions the right term. It's a pitch battle, basically, between old elites and new elites. What were the original seeds of demise for the previous generation of elites that led to all

Starting point is 00:52:56 those 11% approval ratings? What would you attribute most of that to? There's really two theories. There's the theory that those approval ratings are wrong. and there's the theory that those approval ratings are right. And by wrong, I mean, they're being measured correctly, but the people are wrong. People are giving the wrong answer. And so if you're running CNN or if you're running Harvard or if you're running whatever and your approval rating is coming at 11%. And by the way, for your listeners, Gallup for 50 years has been doing

Starting point is 00:53:21 this incredible survey panel, which is trust in institutions. And you can just Google 24 Gallup trust institutions. And you get these spectacular charts. And what you find is basically trust institutions basically peaked in the late 60s, early 70s and has been falling off a cliff ever since. And so this phenomenon, by the way, predates the internet, interestingly. It gets blamed a lot of the internet, but it predates the internet. So it's something that basically started developing the 70s and has been accelerating since. And by the way, those ratings have fallen off a cliff dramatically since 2020. They slide like this and then after 2020, they just plummet. TV network news, you know the number. It's like tiny. It's like single digit percentage.

Starting point is 00:53:52 People are just completely done with it. They don't believe what's on it anymore at all. By the way, also viewership is collapsing in the same way. So one theory, if you're running NBC News or if you're running CNN, Harvard, your theory is, oh, the people are wrong. The people have been misinformed. They've been lied to. They've been fed misinformation. This is why the whole misinformation thing became such a big meme. There's a Marxist concept called false consciousness, which basically is the people are incorrect. The people have been lied to by malicious actors, by populists and demagogues. And it's just a matter of time until we can explain to the people that they've been lied to and they're going to come around and they're going to

Starting point is 00:54:23 believe us again. So that's one theory. The other theory is the elites have become rotten. They have become rotten and dysfunctional and corrupt, and they're not delivering. And on that theory, the numbers, the ratings are correct. The collapse and approval is correct because every time you look at Congress, they're turbo-shotgunning money out the door at all kinds of crazy stuff taken out of your pocket as a taxpayer with no regard at all for you. If you go watch CNN or NBC News, they're just lying to you about a thousand different things all the time. If you go to Harvard, they're teaching you race communism and America's evil and crazy, crazy things. In that theory, the people are correct. The people are onto these elites. These elites basically

Starting point is 00:55:00 have been in power too long. They've had too much power. They haven't had. enough scrutiny. They haven't been subject to enough competitive pressure, and they've rotted in place, and they're just not delivering anymore. The reality is probably some of each. It's very easy for the next rabble-rauser to show up and just start hurling stones whoever's in power and saying whatever. And if you're a, you know, I'm going to pick on people, but if you're like, whatever, somebody who doesn't have political power today, but you want it, easiest thing to do is show up and just start yelling about how the current elites are corrupt. Maybe it's somewhat correct. Demagoguery has something to do with this or whatever, misinformation. But I think

Starting point is 00:55:28 an awful lot of it is the elites are rotten. My version of that is very straightforward, which is Burnham talks about this in the book. There's this concept called the circulation of elites. And so one of the things he says is for an elite to actually stay healthy and real and productive and to not rot in place, it needs constant infusions of new talent. And it does that through a process of circulation of elites. And so what it does is it identifies young, promising people and it invites them to join the elite. And it does that for two reasons. One is so it can refresh itself. And then the other is those are the people who would be the most likely to become the counter elite. So it's also a way to head off future competition. So this has been my experience, basically, since I was like 22, is,

Starting point is 00:55:59 oh, hey, Mark, we would love for you to come to Davos. We would love for you to come to Aspen. We would love to you to come to this big conference in New York. We would love to invite you at the dinner parties. We would love to have you come hang out with reporters the New York Times. For like 25 years, this is what I did, which is like, oh, that sounds great. These are like, the best people in the world. They're in charge of everything. They've got the best degrees. They went to the best schools. They're in all the positions of power. They love me. They think I'm great. They keep complimenting me. And I'm in these rooms and these important people and they're taking me seriously. And it's just this ego bath that's just like incredible.

Starting point is 00:56:28 Wow. I'm like a kid from the cornfields of Wisconsin. I'm like, I've arrived. And I'm in the And all I have to do is stay in the elite is not argue with anything. All I have to do is just agree with whatever's in the New York Times and whatever's being said at Davos and vote for and vote for and donate to the ones you're supposed to donate to and never, ever, ever deviate off the track and then you just become part of the elite. And I have lots of contemporaries who have done that. Some of them are like the world's largest Democratic donors now where they're fully minted and they're in there and they're having a great time and they think it's all incredible and it's all wonderful. Some people are fine going along with that and maybe that's the right thing to do. And then some of us reach a point

Starting point is 00:56:58 where we kind of look around. This is the JD Vance story. He tells a very similar story. grew up in rural Kentucky, whatever, Ohio, Appalachia. He ends up at Yale. He ends up being invited in the inner circle of all these places. And he finally looks around and he's just like, wow, these people are not at all what I thought they were. This is horrible. These people are like self-interested, corrupt and they're lying about everything and

Starting point is 00:57:16 they're engaging in speech suppression and they're incredibly authoritarian and they're looting the public treasury. Like, oh my God, I was lied to my entire life. These people don't deserve the respect that they have and maybe there should be a new elite in charge. And so that's a lot of the attention that's playing out right now. Yeah, I'm a case study of it myself. If we take an optimistic lens, your emphasis on an early stage venture, you get to meet all these young, brilliant people that are about to go build the future. Let's take the optimistic lens and say AI has the most positive impact that we can imagine and all the places where we can verify the outcomes, reasoning becomes so powerful. What are the other related showpoints that get in the way of the sort of explosive technology revolutions that we all want? That could be clinical trials in medicine or something that's just going to go slower than AI is going to go. And AI is not going to be the problem. We're going to have,

Starting point is 00:58:01 bursting at the seams of wanting to make progress, but in the world of atoms or the world of regulation or the world of clinical trials or whatever it might be are going to become the rate limiters, not intelligence and knowledge. Which of those choke points have you most personally interested today? The way I've always thought about technological change, a set of lines on a graph, used to be three lines now, it's four lines. So one is the pace of technological change. That's a line where everything generally gets better and better and then every once in a while you have these discontinuous step functions up or something gets dramatically better, like what happened last week with AI. Then you've got another line on top of that, which is sociological change, which basically is

Starting point is 00:58:35 when is the world ready for the new thing? And sometimes you get this phenomenon where the new thing actually exists before the world's ready for it. And for some reason, it doesn't take. And then five years later or 50 years later, it actually takes it off and away it goes. So there's a sociological layer. And then on top of that, there's the financial layer, which is, are the capital market's willing to fund it? And can it generate a return? The way I think about it is the technology line is kind of a squiggle like this up to the right. The social line is this big sweeping curve, is large numbers of people reevaluate what they want. And then the financial line is like an EKG of a heart attack where the market's going through its patterns of panic and euphoria.

Starting point is 00:59:08 The art of being an entrepreneur or a tech investor is to try to slice across all three of those. You're trying to back something where the technology is really ready, society's ready to adopt it, and you can actually get the thing funded or get the thing exited and taken public. And so you've got to kind of line that up. A lot of what we do in the day job is line up those three curves. The fourth one now in the last five years is politics. And as I said earlier, for a very long time, people in Washington just had an attitude of benign neglect towards the tech industry, and they're like, yeah, their kids building fun toys, whatever, it's fine. It doesn't matter. And now there's just, as you know, just like intense political scrutiny on almost every

Starting point is 00:59:40 aspect of the tech industry and like incredible attempts to control and suppress new technologies. The harshest version of that is in places like the EU, but we've had our own versions of that here. And so all of a sudden we have this fourth factor now. In the last four years, overwhelmingly, the answer to your question is politics. In the last four years, overwhelmingly, the biggest issue that we had was government. That was very bizarre and disconcerting to me when it first started because I wasn't used to it. And I had never viewed us as being involved in politics or being partisan or really, we were not in Washington trying to curry favor. We were not trying to get subsidies, but we also didn't think we had to do anything to avoid getting stepped on. And then that just

Starting point is 01:00:11 radically changed. That's the single biggest thing. You're probably well aware at this point or your listeners are well aware. The policy implications on crypto were just devastating for the last five years, FinTech also extremely damaging. Social media got tremendously stomped on by the state, which led to all the censorship stuff. And then AI, I spoke in other places about what they were basically going to do to AI. For the last four years, I've just been in this bizarre situation where it's like my main enemy is my own government, which is very, very strange. And by the way, talk about accelerating my evolution from an elite into a counter elite. It's like, okay, if they hate me and want to destroy me, it makes the call relatively easy for what I need to do. How did you most feel that? Like, how did you

Starting point is 01:00:48 feel the elite wanting to destroy you? How did it manifest most? It was sort of coincidental with a national mood shift, probably between, I would describe it between kind of 2013 to 2017, which is I grew up politically. I'm like a child of the 90s. I happen to be at business at that point in high profile. So I knew Clinton and Gore quite well. And I was sort of just a default Clinton Gore Democrat. It was what I call the deal with a capital D, which is, yeah, you're a Democrat, but the Democrats are pro-business. They're pro-tech. They're pro-startup. Clinton and Gore love Silicon Valley. They loved new technologies. They were always thrilled to see what we were doing. They were incredibly supportive. They would try to help us. If we other countries came at us or whatever,

Starting point is 01:01:23 they would try to help us and support us. And yeah, it was great. You could be a pro-business, pro-tech Democrat. It was great. They could make a bunch of money. People would write all these great articles about you. And then you give all the money away and you're a philanthropist. And it's great. and you die. And your obituary says he was a great entrepreneur and a great philanthropist. And everything is wonderful. Basically, that deal collapsed starting in 2013, specifically every single part of that deal collapsed in 2013, including when a lot of the political system turned on philanthropy, which I found to be probably the most amazing thing of all. It turns out philanthropy is evil, if you haven't been updated on this yet, because the correct role of money is it should all

Starting point is 01:01:55 go to the government and the government should hand it out. They created a slur around 2013 called Philanthro-capitalism, basically these rich people who think that they can make private choices of how they give away money as opposed to letting the government do it and that that's evil. Basically, every aspect of that deal between, let's call it, the tech elites and the democratic elites broke down. That showed up in a thousand ways, but it showed up as press coverage. The official organs of the elite turned on us and everything we did was evil. It was actually fairly amazing. In 2012, social media was considered an absolute unalloyed good by the mainstream press because it had gotten Obama reelected and it had been the catalyst for the Arab Spring.

Starting point is 01:02:27 Everybody knew that it would only ever get the right political candidate elected, like Obama, and everybody knew that the Arab Spring would result in peace of democracy throughout the Middle East forever. And then by 2016, the narrative had completely flipped to social media and the internet and tech are destroying democracy and everything is being ruined by it. And so the press coverage, all of that was like a canary in the coal mine. Part of it was the employee base got radicalized. By the way, a bunch of the professional investors got radicalized. I had this bizarre situation where you had these big investment managers showing up demanding radical politics in your company, which was completely bananas. At the time, you had a thousand other versions of this. And then

Starting point is 01:03:00 ultimately what happened was the government itself showed up. And the bureaucracy under Trump started to do this, kind of outside of his direct control. But under Biden, it became a concerted campaign, I would describe as destruction with just like an endless barrage of prosecutions, investigations, Wells notices, debanking, censorship attacks, a comprehensive attempt to basically destroy entire sectors. Of course, that's what we ultimately ended up reacting to. My hope is that's over, which is to say the new administration is taking a very different approach and not doing all those things. And then my hope is the next Democratic government basically realizes that attacking tech and attacking startups was actually not necessary. And in fact,

Starting point is 01:03:36 was probably counterproductive because like if you drive Elon Musk out of your party, it has consequences. I talked to a lot of Democrats. We support a lot of Democrats at the firm, a lot of Democratic congressmen and senators. And I talk to them a lot. I'll be out there again next week talking to them. Basically what they tell me is like, look, there's a civil war inside the Democratic Party between basically those of us who think the party should come back to the center and just stop basically attacking capitalism and attacking business and attacking tech and just get back to winning elections. And then there's a bunch of us who think that the party actually needs to become more radical. We need to differentiate more from the other side and we need to become more

Starting point is 01:04:07 on-use pejoratives, but more extreme and economic policy, more extreme in tech policy, more extreme in social policy. They're fighting that. My hope is that they're going to work their way back to the center, so we never have to go through this again. And we can have positive relationships with both sides, but we'll see what happens. I'm incredibly interested, as so many are by the nature and state of the global supply chain. And this is indirectly a little bit of another China question. But when you dig into the components of pharmaceuticals or really the components of lots of things, you see how incredibly interdependent the world is, especially the U.S. and its reliance on places outside of the U.S. for just supply chain, generally speaking. I'm curious how you think and hope this will evolve

Starting point is 01:04:45 in the next decade or so, because obviously there were benefits. We went global for a reason, but I think that there are now lots of fragile spaces in supply chain around the world. How do you think about this part of the evolving economy and the economic story for back to your point, you want the U.S. to win, how do you think the U.S. should and might win in supply chain manufacturing all these exciting ideas you hear swirling around today? Yeah, this is really important, and this is where it's so much different than the past. This is where our interaction with China is so different than our interaction with the Soviet Union 50 years ago, which is, to your point, just the overall level of activity of offshoring. American manufacturing companies never really

Starting point is 01:05:25 offshoreed anything into the Soviet Union, but they offshoreed a lot of stuff. into China, so there's a lot more activity that's gone overseas. But the other thing you know this, but it's really important, is the complexity of the supply chain. Take the iPhone as the canonical product. There's a document you can download online. There's probably a little bit dated now, but it goes through the componentry that make up an iPhone and where that stuff comes from. And at least, it's probably a decade old document now. There might be a more recent one, but the one I read a decade ago, there's parts in the iPhone from 40 different countries. And so by the time that iPhone is getting assembled at Foxconn and China, it literally has had 39 other countries have sent stuff in, getting built

Starting point is 01:05:57 into subcomponents of subcomponents into components, and cars are the same way, and robots are going to be the same way, and anything sophisticated, anything computerized or mechanical is going to have that attribute. And so, by the way, it's actually hard to even get this from the trade numbers, because I believe this to be the case, China actually gets to take credit for the export value of the completed iPhone in their export numbers, even though the economic value add of what happened in China is single digit percentages. Because so much of what's in the iPhone comes from 39 other countries, the analysis you really want to do is what's called economic value added. You want to basically say, okay, of the $1,000 that went into the iPhone, what's the pie chart of the value

Starting point is 01:06:32 of where those things came from in dollars? And the answer is from all over the world. This is the problem with a simplistic argument about reshoring or about reversing globalization, which is this. We're not talking about bringing a steel plant back from China. We're talking about unwinding a supply chain that has 40 countries involved with things going back and forth all over the place as everything is built up and assembled. And look, the modern economy, the reason an iPhone cost $1,000, and not a billion dollars is because the efficiency gains from that level of economic specialization and trade have been profound. We have a material standard of living today far higher as a consequence of this. Our standard of living in the U.S. is much higher than it was, and then billions of people

Starting point is 01:07:09 around the world have been brought out of poverty. So economically, that system has done quite well in many ways. The problem is it runs up against reality in a bunch of ways. So one is national security. So this is the problem with the Taiwan chips, the Taiwan fabs, is like, okay, if the U.S. military is going to be running on autonomous, AI-driven drones and self-piloted fighter jets and self-piloted submarines in the future as opposed to what we have now, boy, we're going to need those leading as chips to power our military. If China seizes Taiwan, they own the means of production of those chips, the American military even get those chips. And so there's the direct supply chain implications into the military. There's also just the geopolitical thing we talked about before, which is just

Starting point is 01:07:46 do countries start to use their ownership of different areas of this more as leverage in geopolitical fights. Then there's what we saw under COVID, which is okay, when the world goes into crisis, and there's a big fight over even things that you would consider to be relatively prosaic. This is a great example. You remember in the early days of COVID, there was this idea where if you did enough testing, you could do it. It was called test and trace. So you could isolate COVID clusters before they spread, which is a standard thing that people try to do for infectious disease. And it turned out, they couldn't get the COVID tests out fast enough to do it. And it turned out the plastic tip that goes into the COVID testing thing. It's made by some factory in China,

Starting point is 01:08:17 and it's a piece of plastic. But if you can't get it, you can't make the test. test. And so it doesn't even have to be the world's most sophisticated components that end up holding you up. It can be actually relatively simple things if you're not capable of building them internally. And then that could determine which country can respond to a pandemic. And then you just have the political and economic pressure of it, which is we just all assume, the American political system assumed for 30 years, you could just offshore manufacturing out of the U.S. and that the communities that saw all their plants closed throughout the Midwest and the South were just going to sit and take it. And that it was just going to be fine. And they were going to figure out something else to do. In a lot of the U.S., they never figured out a new thing to do. And it turned out they can still vote. Part of what's happened in our political system is they've decided that they're just not having it anymore and they're going to vote for something different. People argued that at the time, but the economic efficiency argument won and had its benefits, it paid off in some ways, but a lot of people in the country were radicalized. I come from a part of the country in which a lot of people were radicalized by the fact that the government and businesses apparently thought it was fine to just hollow out the economy and send everything offshore.

Starting point is 01:09:13 And so even if you are getting the payoff from the economic efficiency, your political system may not be able to withstand that. You may end up really regretting that. And so, I don't think there are any easy answers here. Anybody in my view who says there's an easy answer here is wrong, this is complicated. Probably what's going to happen is that the world will remain extremely interdependent. And there will be a lot of pressure and a lot of back and forth. This whole dynamic is playing out with tariffs and trade negotiations. It will be a constant thing and has been forever.

Starting point is 01:09:38 And there will be twists and turns along the way. But fundamentally, the world will just stay interconnected in lots of ways and we'll muddle through it. The fear is that at some point there's a war or an even more severe pandemic or something like that. in which this all gets stressed to the point where it really breaks hard. I hope that doesn't happen. But in a way, the more interconnected to the world gets, the more resilient it gets, because there's just more ways to do things and more ways for people to adapt and everything change.

Starting point is 01:10:01 And then in some ways, the more interconnect to the world gets, the more dangerous things get, because if any one part of it breaks, the whole thing breaks. And so there's a real push-pull on that. There's another lurking area of technology frontiers that I haven't seen you talk about a ton, which is robotics. Everyone's very excited by the potential. It's very easy to imagine a humanoid robot, especially lurking around. doing all sorts of stuff that humans don't have to do anymore.

Starting point is 01:10:23 There's tons of technological breakthroughs that are required to make that world of reality. What do you think is going to happen in the world of robotics? What's being overestimated? What's being underestimated? How do you think about it? I would make a list of four things. So I would say phones, drones, cars, and robots. And basically, this is the ladder that China's climbing.

Starting point is 01:10:43 And to your point, this is the ladder of not just products, but entire supply chains. And so China became the place that all the phones were assembled, manufactured. And so, as you know, they built up this entire ecosystem in China of thousands and thousands of specialist companies to basically do phones. This particular environment called Shenzhen, which is this cluster of thousands and thousands of companies that basically manufacture all kinds of electronic and hardware and mechanical and computer kind of things. So they did that in phones and they produced billions of phones a year. And so that worked and that's running at high scale. That supply chain was then levered for China winning the drone market, consumer drones like DGI drones. And basically what happened was China won the global drone market.

Starting point is 01:11:17 their 99.something percent share of the global drone market. By the way, as a consequence of that, they're well over 90 percent of all the drones used by the American military, which is interesting because every single one of those drones is potentially backdoor to be a surveillance platform or to be used as a kamikaze weapon. So there's a real issue with this. Great example of the issues that emerge. But a big part of why China wanted drones, at least up until now, was they had this entire supply chain that started out building phones that they adapted and then they built all those stuff to make drones. And a drone in a lot of ways, it's like a flying phone. It has a lot of the same equipment, then it has some new stuff, but they wanted that, at least up until recently.

Starting point is 01:11:51 Now they're going to cars. And the reason they're going to cars is because a modern self-driving electric car is much more like a rolling laptop on wheels or a rolling phone on wheels than it is like an old-fashioned internal combustion car. And Tesla is our example of that in the U.S. where a Tesla is a computer and a lot of batteries wrapped in a frame with some tires. The great illustration of the change here is if you just go visit the service bay at a traditional car dealership versus the service bay at a Tesla dealership. The service bay in a traditional car industry is oil and grease everywhere and all kinds of stuff going on. And everybody's got the overalls and they've got the dirty rag that they've been wiped their hands on all day.

Starting point is 01:12:23 You go to a Tesla dealership and it's like an operating room. Everything's clean because it's not internal combustion. There's none of this stuff. It's just a computer. The Chinese basically are now doing in cars what they did in drones and what they did in phones, which is they've built an entire ecosystem, leveraging those other supply chains. They built an entire ecosystem of all the parts needed to build self-driving electric cars.

Starting point is 01:12:41 And they're now bringing those cars to market. And now all of a sudden, they're really good. and they're really good in the same way that Chinese phones are really good, and the Chinese drones are really good, which is they're fully modern, they're super advanced, they're super inexpensive, they're leading edge technology, and the cars are getting to be really good. And they're third the price or a fourth the price of the equivalent car in the U.S. And then the fourth phase is robots.

Starting point is 01:12:59 And if you have the supply chain for phones, drones, and cars, you have most of what you need to do robots, and that's the next phase, and they're doing it. And so we have obviously Elon and other companies in the U.S. building humanoid robots, and I hope and expect that they'll do well, but China is doing that for sure. the company I've been watching most closely is one of their national champions

Starting point is 01:13:17 is a company called Unitri. We're not involved in this, but Unitary sells a robot dog that's equivalent to the Boston Dynamics Robot Dog. The Boston Dynamics Robot Dog costs between $50,000 to $100, which is why you don't see very many of them. The Unitary dog starts at $1,500.

Starting point is 01:13:31 By the way, we have two of them, and they're great. And they do backflips and they do climb stairs and they talk to you and they got an LLM built in and they'll teach you quantum physics as you're running around in the yard. And it's great. And then they have humanoid robots coming out now that are also at much, much lower prices.

Starting point is 01:13:45 They are coming for robots in a major way. Again, this is going to be a real push-pull because it's like, all right, if you believe that humanoid robots are going to happen, which I do, and at large scale, and if China's willing to make them for $10,000 or $20,000, and we can buy a billion of them, and all of a sudden we have robots building our houses, doing lawn care and doing everything else that you'd want robots to do, waiting on your hand and foot, then it's great that China's making them and selling

Starting point is 01:14:07 to you and that they're super cheap and that they work really well. Having said that, if there's ever a war, between the countries, every one of those robots could go rogue and start to attack you. You might want to think about that. It might be important to have robots that are made in the U.S. It might be important that the robots that the military uses are made in the U.S. You might want the robot in your house to be made in the U.S. The robot that's taking care of your kid changing his diaper.

Starting point is 01:14:29 Phones and drones are already intense issues, but cars and robots are going to be ultra-intense. It hasn't quite happened yet because the robot thing hasn't quite tipped yet, but I think the robot thing is going to tip in the next few years. And then I think there's going to be a giant geopolitical, let's say, drama that's going to play out to try to figure out what we should do. It's been fascinating to watch the race to build not just the bodies of the robots, but the brains, companies like physical intelligence and others, American base trying to build the data sets that we just don't have yet. We had the open web

Starting point is 01:14:54 to train AIs on. Are there areas elsewhere in all the young people you're seeing and all the companies you're seeing that you are incredibly excited about, but you feel like the market has not yet realized what is going on and what is possible? I guess maybe biotech. The good news is, modern world, there are a lot of people who are in a new technology, and there are a lot of people who talk about it. When I was a kid, early adopter markets were tiny. So the number of people who wanted their first personal computer, whatever, was just a tiny number of people. And now you've got 50 or 100 million early adopters who just want whatever is the new thing and talk about it all the time and talk about it online. So I don't know that there's that much of a delay anymore.

Starting point is 01:15:30 But probably biotech, everything, it's sort of the cluster of life extension, embryo selection, potentially the reproductive technologies, getting embryos from stem cells. For example, embryos from stem cells, couples that can't, you know, you probably know a lot of people like this, people who get to a point, either they had a fertility problem when they were young or they get to an age where they have fertility issues, but they want more kids. And then they're forced into very difficult choices having to do with IVF or donors of different kinds. It looks like we're going to be able to have embryos from stem cells. And so you can have children that are actual biological, children much later in life. External gestation is a while away still, but at some point, that might be a big

Starting point is 01:16:06 deal. People talk about the birth rate a lot. Well, if you could continue to have kids into your 60s, And if you could have a dozen kids because you could have external gestation, would more people choose to do that? And maybe yes. So that would be one. Another might be, say, genetic optimization. So one of the endlessly spicy topics is intelligence augmentation. There's CRISPR.

Starting point is 01:16:24 We now have gene editing technology. So in theory, you can go in and do genetic reprogramming of people, especially at the early stages. And then the scientists are figuring out the hundreds of genes that correspond to IQ. And so should you have the ability to boost IQ that has all kinds of downstream questions? So probably it's in that vanguard, those kind of vanguard movements. The inflammatory version of this was the guy in China who made the babies who were immune to AIDS. So there was the Chinese guy who did a homebrew CRISPR thing.

Starting point is 01:16:49 And he created two embryos that are now, I think, living children, as far as I know, that used CRISPR to splicing genes that make them immune to HIV. And it became this dramatic firestorm a controversy because CRISPR has not developed well enough yet to do that in a predictable way. And so there were accusations that he was really going to be damaging these kids. and this global health ethics world came up in one and basically it was horrified by what he did. And then George Church, who's probably the leading biology researcher in the West right now, actually gave a counter argument. And he's like, no, people need to do this. We need to actually try these things.

Starting point is 01:17:19 I'm not even taking a position on this. I'm not even saying these things are good or bad or should be allowed or should be banned or whatever. They're damned interesting. Everything I just described is becoming possible. And they have these just incredible implications on everything from health to society, which will play out for hundreds of years to come. And so I think more and more people are probably going to realize that there's a lot more to discuss on those fronts than we've been doing. Two closing questions. The first is around you and your firm having coined this concept of American dynamism and increasingly defense technology, which used to be a backwater for early stage investors, has now become an incredibly popular category, lots of capital flowing into it.

Starting point is 01:17:54 And people are thinking about national defense and evolving ozone that has a lot more massing of drones and less soldiers and all these different changes. Is there anything in that world that you're most attuned to personally and learning the most about today? Yeah, so American Dynamism covers a lot of territory and we do a lot in there. We're doing more in energy. We have our first nuclear investment. We're doing education, other fields. And so there's a lot in there, this theme of upgrading America. For me, the most fascinating thing is the change in military affairs.

Starting point is 01:18:19 So the change in the nature of war and defense that's coming from the rise of technologies like AI and autonomy. A highly a couple of things there. So one is it's actually happening. And in particular, the tragedy of the Ukraine battle. battlefield is also just turns out to be a living laboratory for extremely rapid evolution of military technology. And the Ukrainians and the Russians both have adapted technology enormously in the last few years to both attack and defend. Of course, there's just incredible use of drones and incredible innovation happening there. And so military planners are watching what's happening on that battlefield

Starting point is 01:18:47 very closely. The entire nature of defense systems is changing in real time in response to watching that play out. The loose concept that we have on that is the wars in the past were won by the side that had the most men and material. So if you had the biggest army and the most weapons you want, probably in the future, wars are won by the people with the most money and the most technology. And the reason is because if you've got the most money, you can buy the most technology or develop it. But the future of warfare probably has a lot more to do with machines fighting with each other than people. And there's an obvious social welfare benefit to that, which is you'll have a lot fewer soldiers and sailors and Marines and pilots dying in war.

Starting point is 01:19:23 But it changes the dynamics, the calculus of what it means to go to war. Maybe the fear would it makes it easier to go to war because the human cost is lower. Maybe countries become bolder and willing to enter military conflicts more aggressively. So there's all kinds of questions and implications there, but this shift is happening. It's going to happen. China has a massive program. A lot of what China's focused on AI is to be able to apply it in military settings. So they have a whole program on that. And then our defense establishment has the same thing and many other countries have the same thing. So that's going to be very dramatic. I was talking to a very senior military planner a while ago. And he said in his view, the weaponized drone that fits in a

Starting point is 01:19:56 backpack that you can fly over a hill and can basically destroy a tank, what they call suicide drone. He said in his view, it's the biggest innovation in defense technology since the stirrup. Wow. He said the stirrup was a big deal because the stirrup is the thing that took a soldier who previously had to get off his horse to attack somebody, to the horseman being able to stay on the horse, stand up and be able to fire a bow and arrow. The stirrup was a massive extension of individual lethality on the battlefield. And he said a squad of well-trained human soldiers with drones, the 20 human soldiers with drones should be able to hold off thousands or tens of thousands of regular troops. It's a fundamental change in the economics of attack and defense. It still feels

Starting point is 01:20:30 like we're on the front end of trying to process through what that means. So as we don't end there, I'll ask a quick final question. I love how you are always reading these incredible books and then taking from them frameworks to apply to your understanding of the world. If you could leave everyone with one book that has an interesting framework beyond the Machiavellians that you mentioned earlier, what would you pick? I'm still very locked in this book called the weirdest people in the world, the Joseph Henrich book, which is probably a decade old now, but I think that book never quite gets a lot. That book is extremely insightful into the nature of cultures and in the nature, particularly of different cultures, which as we're in this more globalized world with all these

Starting point is 01:21:03 geopolitical conflicts, it's a very insightful look into what makes cultures and then in particular what makes Western cultures. As you know, so much of our politics have to do now with the nature of Western cultures and what it means to immigration, all the different debates around that and so forth. And so to me, it's been the most informative book to try to understand how to think about cultures. Awesome place to close. Mark, thank you so much for your time. Good. Thank you, Patrick. Awesome. Thanks for having me back. If you enjoyed this episode, visit join colossus.com, where you'll find every episode of this podcast complete with hand-edited transcripts. You can also subscribe to Colossus Review, our quarterly print, digital, and private audio

Starting point is 01:21:36 publication featuring in-depth profiles of the founders, investors, and companies that we admire most. Learn more at joincolossus.com slash subscribe.

Invest Like the Best with Patrick O'Shaughnessy - Marc Andreessen - The Battle For Tech Supremacy - [Invest Like the Best, EP.410]

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