Anthony Pompliano: How to invest in the AI-bitcoin SUPERCYCLE

Well, I think that there's something called the fat protocol thesis in crypto that a lot of people have forgotten about. And the whole idea of the fat protocol thesis was that there was going to be a protocol that was going to continue to get fatter and fatter by eating more and more of the stack. And eventually, whether it was Bitcoin or Ethereum or Solana or whatever, that protocol is where all the value was going to accrue. What we saw in crypto is that's not true. Instead, what happens is the protocol's a very important part of the infrastructure and the foundation of these ecosystems, but actually you still got consumer software and many other components of kind of the infrastructure. And so, the fat protocol thesis, as I thought early on, was dumb and ended up not being true. We're seeing this play all over again in AI. The AI people should just be quiet and go listen to the crypto people. The fat protocol thesis is wrong and the fat AI model thesis is wrong as well. And so, what you end up finding is that once you realize that the fat model thesis is incorrect, then you start to realize that there's going to only be fragmentation. So, you're going to get consumer software, you're going to get specialized workflows, you're going to get kind of general purpose models and all the way through the stack, but also you're going to get rapid competition between closed source and open source, between American companies, Chinese companies, and many other different cuts of this.

And so, the reason why I keep talking about it is because right now everyone is like, 'Oh my god, the American closed source models of ChatGPT, Opus, Claude, you know, all these different models that everyone's been using are now getting their butts kicked on the playing field by the Chinese open weight open source models.' And frankly, I'm pretty disappointed in the American companies because they're basically crying like little babies, going to the White House saying, 'Oh, you should ban the Chinese open source open weight models.' No, the government shouldn't ban them. You should just build better models. You should compete on the field. And ultimately, what I think we are watching happen here is there's a last gasp of desperation. And the reason I call it the last gasp of desperation is because these large language model providers are realizing, wait a second, I'm spending all this money to go and train these foundational models. We as consumers should be thanking these companies for doing it. Sam Altman, Dario Amodei, all these folks, they have done an incredible service to the world by going and training these large language models. But what they now are realizing is that the Chinese companies are simply drafting off that work via inference and kind of all this stuff. And so the second that you start to see that there is a different way to do this,

It's almost like do you remember recently Josh Kerr broke the one-mile world record? Well, what a lot of people didn't see, didn't pay attention to as he ran those four laps and broke the world record, was when the race started, he ran out, but he was not number one. He was third. And there was two guys in front of him. And those two guys ran in front of him. The first guy ran the first two laps. At the end of the second lap, he stepped aside and he started walking. The second guy in line ran the third lap and then he stepped aside and started walking. And Josh Kerr was left with one lap left in number one place ready to run. Now, why is that? The first two guys, they were there to break the wind and let him draft off of them. So they basically knew, I can run as fast as I possibly can for two or three laps. I'm not going to break the world record, but I'm doing it in service of Josh Kerr who's behind me because he called his shot. He's going to go break the world record today. That's basically what the Chinese models are doing to the American companies. They say, 'That's so cute that you're spending so much time and money to go train these foundational models. Wouldn't it be bad if we simply drafted off of you and we were able to then go create these open weight open source models that are just as competitive and lower cost?' So, that's why the American companies are getting so upset. I hear them. I understand why they're upset. But, they got to figure out how to win in the market, not go and try to just yell and scream about, 'Hey, let's ban the Chinese models.' And so, where I ultimately believe a lot of value is going to accrue is in American open source models. We can get into why I think the American open source models will beat the Chinese ones, but that's why I'm talking about it so much is I think that open source, because of what I learned in crypto with the fat protocol thesis and the open source systems, etc., that is probably going to have a much, much bigger impact in the market than people give it credit for right now.

No.

The American open source models are going to beat the Chinese open source models. And the reason is because I think that people drastically underestimate America's ability to innovate. Literally, we created the foundation models, right? They're drafting off of us. We have the Godfather of AI. Jensen Huang is going all in on open source. He understands where this is all going, and I think that American open source models are going to be the winning strategy. Now, that doesn't mean that OpenAI or Anthropic or name your favorite, Grok and xAI, I don't think any of them are going to go to zero or go away. It just means that there's going to be more fragmentation in the market, and what you're going to find is that people are going to start reverting to these model routers. We've built one, Ramp just came out with one that is for other people to use, but I think that really people don't care what model they use. All they care about is, 'I want the most efficient completion of the task that I need done.'

So, what does that mean? I don't care what the token cost is, because token cost is only one input. What I care about is actually what was the total cost to complete this task. And so if you say to me, 'Hey, there's a really expensive token, but it uses way less tokens, overall it still may be cheaper than maybe a model that has cheaper tokens but uses way more tokens.' So ultimately as a business owner, as a product developer, what you care about is what is the total cost to accomplish this task. That has both cost, but it has token efficiency as part of it. And that's where these model routers and many of the things are becoming popular. And so what people are starting to realize is you're going to use multiple models in your product. You're going to route queries or tasks to the model that is best suited to do that job. Sometimes you need a general purpose model. Sometimes you need a closed-source zero data retention policy model. Sometimes you need an open-source model. Sometimes, like in for example with the product that we're building with Silvia, you don't want to use the Chinese open-source models because potentially they have more socialist ideas baked into the weights. And if you're talking about finance in the Western world, then the cultural weight, which is something that you're going to start hearing a lot more about, the cultural weight should be more towards capitalism than socialism. And so again, there's a lot of nuance here, and we're all figuring out together. If you had talked to me two months ago, I would have had way different understanding of this stuff, but I think that this is the rapid kind of group learning that's going on in this industry. And so I just think that open-source is going to be way, way more valuable, and American open-source is probably the dark horse in the entire race.

Of course, cost is always an important part. But guess what recently happened? Meta came out and they said that they're coming out with a cheaper model, right? Grok came out and they said they're coming out with a cheaper model. Nvidia and many other companies are starting to invest in American open source. And so the price war is on. What a lot of folks I think don't really realize, and some of this is unfounded critiques, but some of it has probably truth to it, is one of the big critiques against the big labs is are they marking up the tokens way more than they should be? Well, Jeff Bezos made the moniker, 'Your margin is my opportunity,' famous for a reason. And so there's a bunch of people who say that's a cute business you have there, wouldn't it be bad if I took it? So that's one thing. The second thing is when you are actually pinging an API, there's a lot of people who are wondering, are you actually routing my query to the highest value model that I'm supposed to be getting? Or are you routing it to a lesser model and therefore you're actually expanding your margin at my expense? Again, I'm not saying that they're doing that or not. I just see people online talking about this. And so when you use a single model like a DeepSeek or something, you know full well what is the cost of hosting, you know where your data is going, you understand what is the actual model that's being leveraged. Like there's all these components and you get to fine-tune it. And so people who are technical can then take something off the shelf, they can start to fine-tune it, they can start to mess with the weights, they can really start to make this valuable for their specialized use case. I think that's why you see adoption of these things.

Well, I think that most great investment themes have a barbell to them. And sometimes those barbells are opposing themes. So, there's a bunch of hedge funds in the public market, for example, they go long the disruptor, short the disrupted. And so, it's like a pair trade, right? Well, that's what we're watching play out with Bitcoin and AI. Well, what's the pair trade? You're getting abundance of intelligence, and you're getting scarcity of value. So, what you're getting is AI is delivering this abundance of intelligence to people at a very low cost. People have been searching all around the world for the highest intelligence available to mankind for decades and centuries, and now all of a sudden it's available on an API, right? And so, of course they're going to want that. But, that brings enormous abundance. When you have tons of abundance, what do you get? You get abundance of content, abundance of code, abundance of creativity, abundance of data and information, etc. Well, in a world of abundance, what becomes valuable is scarcity. And so, when you get abundance of intelligence, you then want scarcity of value. And I think that's where Bitcoin becomes really interesting. And so, it kind of comes back to this idea of like we have abundance of dollars, those don't seem to be getting more wealthy, right? They're not getting stronger. And so, I think that is ultimately the pair trade is abundance of intelligence and scarcity of value. AI and Bitcoin are actually all part of the same trade.

That is more related than people think. A very early argument for Bitcoin was there's going to be abundance of dollars. And my view is that AI is deflationary and robotics is deflationary. And so if you get deflationary forces, then you are going to print more money, which we already see. People forget, since 2019, inflation has been averaging 4% a year. That's a big number. That's double the Fed's stated target. Well, right now, if inflation is 3.5%, why since December has the Fed been expanding their balance sheet to the tune of $200 billion? They know what's going on. They're not going to admit that they are changing their inflation target. But the only reason why you would run inflation hot at over 4% per year since 2019 is because of either external shock, COVID, or you are okay with it being run hotter because you understand these deflationary forces of AI, robotics, deportations, tariffs, etc. And so if you have inflation at 3.5%, why are you expanding your balance sheet? It's because they realize that they're going to have to devalue the dollar, come deal with the national debt, the deflationary forces, etc. So in that world, which is now being kind of accelerated by AI, that leads to more value to Bitcoin because if there's abundance of dollars, there's scarcity of Bitcoin. And so it's all the same argument. It's just that AI, it's not that AI is like a new thing. AI has just become an accelerant to the story that was already there for Bitcoin. The problem is most people, they're not thinking kind of second and third order effects. They're just thinking about AI, Bitcoin, right? Like they just think of them as two separate industries.

A lot.

Which is why I don't think they're planning for an AI ecosystem. I don't think that they are. I think they know how to spell AI. That's probably about the extent of their knowledge. But I don't think that they're sitting there being like, 'Oh, AI is coming.' I think what they see is that there's more deflationary forces in the economy than most people realize. And so tariffs, I think they've kind of waved the white flag and be like, 'Hey, those weren't as inflationary as we thought they were going to be.' Deportations, they're not dumb. They realize that if we have, you know, no net growth to the population, that's deflationary, right? And then I think that they understand technology in general is deflationary. And they see the investment dollars flowing into technology. Now, do they go break out AI and robotics versus everything else? Probably not. But I think that they're not dumb. They understand that there are these deflationary forces and so that's probably why they're a little bit more comfortable with inflation running hot. You just can't tell the people that. Because the second you say, 'Hey, we're cool with 3% or 4%,' all hell breaks loose.

They're already crazy.