Jake Brukhman: Why Decentralized AI Is Set To Explode (What's Changed)

**SPEAKER_1** (0:00)
Ladies and gentlemen, welcome back to AI Supercycle. This is episode number 37 powered by our friends at Nier. Visit their nier.ai products. Learn more about private inference and more. I'm here with Jake Brukman. Jake, welcome to the tower.

**Jake Brukman** (0:12)
Thank you, thanks for having me.

**SPEAKER_1** (0:14)
It's good to have you. Jake is a founder and CEO of CoinFund, one of the earliest and longest standing funds in crypto and digital assets. Now more predominantly also in AI, other sectors. I'm sure you're dabbling in robotics perhaps.
Computer scientists grew up in St. Petersburg, Russia. Interesting background. Jake, good to meet you here. And let's have a conversation about investing in AI. NASDAQ is down 3% today. IPOs are coming out. Mythos released tomorrow. There's a lot going on.
How are you doing that?

**Jake Brukman** (0:49)
Doing well. Well, I just want to clarify. So when we think about investing in AI at CoinFund, which is historically now for 11 years has been a crypto firm, we're really thinking about the intersection of AI and decentralization. So I just want to be clear that the investments that we're making are very clearly in that space, and we don't really do pure AI plays.
But that intersection, I think, has some of the most interesting, highest risk reward bets in AI, and it's also advancing the state of the art of AI itself.

**SPEAKER_1** (1:22)
Yeah.
We had these iterations of the AI times blockchain, right? There was this early decentralized inference, decentralized training, like the Akash era. Then we moved into this Solana meme coin attached to a Twitter account, AI agent era, and we kind of entered like this agent era. Now we're in like this Venice, is this really cool private, unsensible chat CPT era. Companies like Antseed and other kind of inference based token production companies are getting a lot of traction. And now like entering into like the agents using blockchain era, I feel like of the space. I know you're very, very bullish on the decentralized nature of bringing these kind of AI suite to the market. Can you just give us your high level thesis for this convergence and kind of as it pertains to this evolution?

**Jake Brukman** (2:19)
Yes. So first I want to say, yes, we have been following this space for a while. I would say like our first investment in the space was Sam Altman's, what was known as WorldCoin back then and WorldNow. That was December 2020 or January 2021 I think the deal closed.
And then in March of 2022, we made our first investment in really decentralized training with our investment in Jensen AI. So when we launched our decentralized AI thesis, it was published in September of 2022 This is before ChatGPT came out. And it is the same today that it was in September of 2022 And that is, we think that decentralized networks can start to disrupt the supply chain of how AI products are made. And the core problem of being able to do that is to train AI models in a decentralized network.
Now, what would you guys tell me if I said, listen, you take these processes that today are in these giant state-of-the-art data centers, that some companies are building nuclear power plants to power that contain industrial strength GPUs who have hundreds of gigabytes of memory, terabytes per second of throughput. And this is what it takes to create a giant frontier model. And what if I told you that I'm going to do the same thing by going on regular 80-megabyte-per-second consumer internet using people's gaming devices and even their Macbooks? You would say, Jake, that sounds crazy and it's probably impossible. And four years ago, that is exactly what the AI experts in San Francisco and all my AI friends from Google told me as I was making these investments.
However, four years on, not only did we show that this is possible, we have a number of companies that are now essentially in a race where they're creating bigger and bigger size models in this way. I think the latest, just from last week, is 100 billion parameters from a company called Macro Cosmos and BitTensor. And this is really like heading for certainly commercial viability, but maybe even like frontier grade size at the end of the day, trained with these decentralized methods on hardware that is commodity hardware that wouldn't be able to be used in the data center if we wanted it to be.

**SPEAKER_1** (4:45)
Yeah.

**Jake Brukman** (4:47)
So just completely incremental compute in a market where more than ever before, we need to counterbalance the centralization of power game that these big companies are playing, and in a market where no one can get access to compute and can't do so cheaply. So that is the thesis that's been playing out over the last few years.