A (2:56)

This episode is presented by usvc, a public venture fund that every American can invest in. Venture capital has been unreachable for most investors. You've got your nose up to the glass, watching companies compound to trillion dollar valuations in the private markets while you wait for them to go public. You USVC was built to change that. It's a single basket of high growth venture capital across stages. SEC registered, professionally managed with no accreditation requirement and a low $500 minimum. It's for US investors only for now. The fund includes OpenAI, Anthropic, Xai and Vercel. As USVC adds companies, investors will own a piece of those too. And Naval is chairman of the investment committee. Venture is not for the money you need tomorrow. It's risky and illiquid. Don't invest anything you can't afford to lose. But if you have the appetite, there may be no harder working way to deploy a dollar than true venture capital. The smartest young people in the world working insane hours to build the future. Investing is easy. Go to usvc.com podcast before investing, carefully read the objectives, risks, fees and expenses in the Fund's prospectus@usvc.com Investing in USVC is speculative, high risk and shares are liquid. With no public trading market, the fund is new with limited operating history and financial information. It may not achieve its investment objectives or provide distributions and investors may lose all or a substantial portion of their investment. Past performance does not guarant returns. Distributed by Alps Distributors, Inc. Now, AI

B (4:14)

is implicitly still a very helpful tool within the organization. And I can give you two examples, although there are more. One is just if you're reading code that was written by somebody else and it's very complicated, you can just have the AI read it for you and give you a summary papers. They can read other people's papers and give you a summary. It can actually go through the code base and tell you who in the organization is likely to be an expert on what topic and guide you to them. So AI can do a lot of that digging for you. You don't need the explicit intranet as much anymore. You don't need the explicit marking down of things because the AI can figure out where you are. You could even unleash the AI on the code base on the designs. Like say you have hardware designs, you can unleash them on designs. If you have suppliers and vendors, you can release them on the database or the file folder in which all the documents with suppliers and vendors are kept. You could even unleash it on the company email if you wanted to, and just say, where are we? How far are we actually from shipping? Draw me a gantt chart based on where you think we actually are in terms of the estimates and the timelines and who's behind and who's ahead, which division's lacking resources. AI can constantly be doing this data analysis and digging and reporting for you reports on demand. You don't need specific charts and dashboards and business integration systems. You can just have AI literally recreate on the fly. You maybe don't want to doing it every time because it might be too slow, but you can have it build these dashboards on demand and you can have it update them on demand. So that's one huge thing. The other is that traditionally in a company, you would have the hardware people. In a company like ours, you have the hardware people, you have the software people, you're the AI people. And they kind of wouldn't be doing each other's work. But now with AI, they can at least get to 20%, 30% each other's work. So it makes the gluing between them a little easier. The AI people, for example, can create their own software harnesses if they need to test something. May not be good for production deployment, but it's better than having to sit around and wait for a software person to come by and write you some custom code. Same way the hardware people can also write a little bit of software to bring up a new hardware device where otherwise they might have needed to wait for software people. So having AI just lets everybody do a little bit of everything. It makes them more generalist. And by being more generalist, it means that you have better touch points to interface with other people. You don't necessarily need to have someone write you an explicit API to work with their code. You can actually just have the AI go and discover an API or create its own API, or you can just bypass the AI, connect directly at whatever level it wants to, whether in the database or within the code base. So it's naturally a force multiplier, but we haven't done anything explicit with it.

A (6:55)

What are you trying to figure out right now? The reason I ask is because you rarely get to see work product from smart people while it's in motion. One of my obsessions is trying to excavate the secrets and inner thoughts of smart people.

B (7:11)

The world is very different than it was a few years ago. There are two, maybe four companies that are dominating AI, or five if you count hardware with Nvidia. And the question is, is that the stable situation? Is this going to be a commodity business or is this going to be a monopoly business? Or is it going to be an oligopoly business? Does it top out at some point? Do they run out of data and do the models stop improving? Or do we go all the way to AGI? Certainly the people inside the labs or believe it as an AGI and think that all value is going to disappear into the AI labs? Does this end up even more consolidated than the Mag 7 world, whether it's just Mag 2 or Mag 1? Or does it somehow fragment? Does open source really have a chance? Or do people just always want the smartest model? And so for that they'll give up privacy, they'll give up open source and they'll just pay up in the cloud. So I think these are huge questions, Huge. These are world shattering questions, but I don't know the answer to this. Can you train AI in a distributed way? Is distributed training possible? Or are these things going to centralize more and more and more? I think now the conventional wisdom is going to centralized training, two to four companies, dominating data centers and power are the limits and everyone is rushing towards that. But what if that's wrong? That would be an interesting contrarian bet, but I don't yet see the evidence. I mean, I think the emerging conventional wisdom for that part in AI is Right. As for AGI, I don't know. I don't want to be in the futurist business. Certainly the people in the Frontier Labs believe it. They believed it for quite a while. The AI that I'm seeing has jagged intelligence. It's also pretty bad at multimodal reasoning. I don't think it has a good model of the world, although there are all these world model companies coming up. Although I think they confuse something that looks like a world that you navigate in which people are like, oh, that's a world model. Because it looks like you're generating something that looks like a world and I can wander around it. That's not a world model. A world model is when you have an agent that has a model of the world inside its head, which allows it to take actions and then predict the consequences of its actions and then adjust its own behavior based on what happened, whether it learned or not. So have like a reinforcement learning loop. That's a world model. And so we're seeing world model companies emerging. I think Yann Lecun famously did one recently with jepa. And so we are going to see new kinds of models, new kinds of agents, new kinds of intelligence. Are we going to get to AGI? I don't know. Now that's the same thing that everybody's trying to figure out, right? But this world is changing. The famous meme, I think an X was like, nothing ever happens. Right. I think that's over. I haven't quite been able to put my finger on why, but I think anyone who is paying attention would tell you that post Covid, the world is changing a lot faster. There was some dislocation around Covid, or perhaps it was just we were in unstable equilibrium and Covid just broke that equilibrium. Then we had a phase shift. But the world seems to be moving a lot faster now. And that's true geopolitically, that's true economically, that's true technologically. VCs are now being forced to fund more hardware. Rockets, drones, AI, you know, sci fi technologies, if you would call it. So. I think sci Fi technologies are in high demand. Sci fi scientists and sci fi authors are in low supply. Sci fi engineers are in low supply. So we are seeing the world shift. And maybe it's for the better, maybe it's for the worse. But things are changing very, very fast. Now. We are living within that Chinese curse of may you live in interesting times.

A (10:40)

Is there anything you're trying to figure out in the world of hardware?

B (10:43)

I think drones are still under leverage Even though they've come to prominence in the battlefield recently, we still haven't seen anywhere near the end game of drones. There's nothing in particular I'm trying to figure out there. I mean, I think drone defense is going to be very difficult because a drone that's attacking has the advantage of both kinetic energy, because it's coming down on you, and it's got the advantage to surprise where the attacker can mass all the attack drones in one area, whereas the defender is always spread thin. The defender has one advantage, which is short range. The defender has to traverse a much smaller range going up. Then the attacking drone probably had to cover coming in. But I think that drone warfare changes the structure of violence in society. So it's going to actually fundamentally change how militaries and entire states are architected. You could argue that the modern state rose up as a consequence of the rifle, because a rifle allowed a former peasant to take down a feudal knight on the battlefield. Then you need a factory to make rifles, and you had to drill musket men and arm them and train them. And so nation states sprung up and became dominant instead of feudal states as the right structure to do that within. And then post nuclear, there's only seven to nine, really independent sovereign nations. And everybody else lives underneath someone else's nuclear umbrella. So those seven to nine call the shots, whether in the Security Council or elsewhere. And so nuclear weapons were the new logical violence after 1945. Now the newest logical violence is drones. And that's going to fundamentally shift the game again, because drones bring the logic of mutually assured destruction down to the individual level. If you really hate somebody in the future, a drone will be able to get them. That's a weird form of violence coming up that's going to basically restructure society as we know it. I don't know which way it goes. Is it going to be the case that you have a few very large, very powerful countries that control all the drones, or is that drones get so democratized that any individual can be deadly? Also, I think one of the fears with AI is biological weapons. I don't want to get people worked up, but in theory, if you were smart in the past, you could have figured out how to make a biological weapon. But the number of people who could have done it, who had both the expertise and had the access were very low, although it was still too high because the coronavirus that coincidentally got unleashed right next to the bioweapons lab in Wuhan figured it out. So now that power is going to be democratized, just like Vibe coding is democratized. Now the number of people who can Vibe code is hundreds or thousands of times greater than the number of people who were coding. And so the same way the number of people who can get access to biological weapons or viruses is hundreds or thousands of times what could have gotten access to them before. So that's a pretty scary thought. Now we can also do the opposite, which is hopefully now the same AIs can also research how to create vaccines or how to create things to stop them. But the problem is that all the official research, all the good guy research, is always gated behind regulations. And there are almost no regulations out there as bad as medical regulations. One of the real opportunities out there, I think, is for AI to solve medicine and biology and therapies. But to do that, you need the data. You need to be able to look at everyone's data set. You need to be able to look at all the outcomes. You want as much data as possible. And this data is hidden behind so many silos and so many regulations and rules. And for good reason. You don't want to target individuals. But if you could anonymize, clean up and allow that data set to get out there, and then you could let people test therapies with a right to try, then I think you could have reasonable defenses. But my fear is this will only happen in an emergency situation. Even during COVID when we had the emergency situation, we took a long time with the vaccines, which turned out not to be that effective anyway. But it took a long time with the vaccines because we just didn't let people operate under volunteer situations and right to try. It just took way too long. Whereas I think in the old days, like you would have had a bunch of healthy young volunteers who would have said, sure, give me this vaccine and then give me Covid, I'll take one for the team. But now, because of quote unquote bioethicists, we don't even allow that. There's just too much bureaucracy in the system, too many people who can say no to the few people who are trying to get things done. And so for that, I do worry a little bit about the future. What else is interesting in hardware? Hardware, I think is going to undergo a renaissance because historically the problem with a lot of hardware is that it's very hard to write good software. And so you get all this incredible hardware coming out, but the software's terrible, so the device itself doesn't function well. Apple has done really well because they integrate hardware with high Quality software. You know, most companies do one or two things well. Apple does two things really well. They build great hardware, they build great software. They're not that good at cloud and AI. Google is very good at cloud, very good at AI, but they're not very good at hardware, for example, and software. I would say they're good at certain kinds of software. They're good at cloud software, they're not good at consumer software. Now all of a sudden you have all these companies that are very good at hardware but not good at software. They can make good enough software or they don't even need to make software. My AI agent will interact with the hardware directly and I don't need software anymore. So if you're someone, for example, who was making security cameras, or you were making like toys for kids, or you were making programmable lamps, all of a sudden the software for that just got a lot easier. You can have some bright kid with Claude code just get in there and build you all the software that you need. Or maybe you don't need any software because your security cameras are not controlled by each person's agent and don't need custom software any longer. So I think that hardware itself is getting unlocked through software. And this is, I think, one of the reasons why China is so big into open source. Now. They're behind, so when you're behind, you try to catch up through open source. I think also it's a little bit of their nationalist pride that we're in it together. Maybe the government's funding them and encouraging them to do open source, but it also plays well into their hardware dominance. China is manufacturing most of the consumer electronics goods, and so for them, open source is hugely beneficial because it commoditizes their complement. Same thing for Nvidia. Nvidia just wants to sell as many cards as possible, so they want people to use as many AI models as possible. So they want it all to be open source. So you have a bunch of hardware players, including most of China and Nvidia, whose incentive is, hey, it should all be open source hyperscalers. Also, they want it all open source. So they drive open source in the AI models and then that commoditizes software and the software unlocks more hardware. So I think we're going to see more and more interesting, usable hardware because now the software is figured out enough that that hardware becomes unlocked and quite usable.

A (17:35)

I don't get scared or worked up about the future, partly because I'm a blind optimist and partly because I live in the first world.

B (17:41)

Yeah, I don't get worked up about it because I think it's just so much easier to imagine doom scenarios than it is to imagine positive scenarios, because optimism requires creativity. For example, the job loss thing is a clear example. It's very easy to look at existing jobs and see how they will go away, but it's very hard to predict what the next job will be. But yet, inevitably, there's always a next job. Because of that, I think people tend to fixate on the doom scenarios. It's much easier to imagine the methods of doom than to imagine the methods of rising up. There is no one, no one 200 years ago who could have imagined how we would end up where we are today in terms of technological advancement and capitalism and economics and, you know, the rise of various societies. They just couldn't have imagined it. They couldn't have imagined 10% of the jobs that exist today because back then everybody was working on a farm. But nevertheless, here we are. So the same way. I think the doom scenarios they imagined are actually very similar to the same doom scenarios that we imagine today. Like even a hundred years ago, every decade I've been alive, there's been a new environmental catastrophe to come along. Someone's talking about the end of the world because of the environment, and then every decade there's a catastrophe coming along because of a war that's going to end the world. And, yeah, sometimes you get really close. Covid was scary. If Covid had actually turned out to be a much more nasty virus, we could have been in a bad spot. If there was a World War 3 where we start exchanging nukes, that would be a very best scenario. So these things are easier to imagine. They're more legible to our mind, so we hold them closer to us. Plus, the outcome there is so catastrophic that people obviously fixate on it. But I think it's very hard to imagine creativity. It's very hard to be optimistic. And so I think we have to nurture optimism, we have to reward optimism. We have to be irrationally optimistic, because that's the only way out of this anyway. So whenever people sort of do the crabs in a bucket thing, where they try to pull the optimist back down and. And they keep saying, doom, doom, doom. They might be right, but it's certainly not helping matters. That's not the person you want to be in a foxhole with.