Building the Bitcoin Equivalent for AI Inference Compute with David and Daniil Liberman (Gonka)

Companies can easily change their statements.

You know, like Google promised all of us back in 2004 that there never will be an ad in the main feed of search query.

So where is this promise right now? And the same with, yeah, and especially in general, the structures, they are not built for immutability.

They're not built for making the promise set in code, set in stone.

Yes.

And crypto is actually originally started from that.

Bitcoin is this premise.

We put it in the code and it will never change.

And the rules will never change so that we can all entrust it and we can then invest more and more efforts in this structure together.

So same was original attraction for us when we decided who should trust us, that we will start with the ethical statement and then we'll not change it.

It should be a protocol.

It should be a certain code.

And that's where our crypto already proven itself.

In the very beginning, we ourselves considered, should we build a decentralized frontier lab? Should we build a technology which will allow training of open source truly open source completely open source open not just open weighted this Chinese models and some of the American models but with open pre context with open alignment rules with open everything they're open, but then we quickly turned away from the idea of doing decentralized training.

It is hard, but it's likely possible.

But why are we turned away from this? Because we realize it.

In any sense, it will require a lot of resources.

Tens of thousands in the beginning, and then hundreds of thousands of thousands of GPUs, high-end GPUs later on, to basically even train the model.

A lot of data centers, a lot of electricity.

Tens of billions, if not hundreds of billions of dollars investment to train those models.

And if it's so, then there would need to be a revenue behind it.

And because there would need to be a revenue behind it, revenue is clearly not in building the models themselves, but in providing the service out of these models.

So the revenue would come from the inference.

That was our conclusion around three years ago, that eventually there cannot be other paths but the path in which a major source of revenue is going to be inference and therefore the focus of any project which wants to be dominant or any like to take any share of the market space in the future would have to be inference would have to be providing the api access or like any type of a service access to ai rather than just basically training the ai And what was interesting is that we saw that Bitcoin, for us, turned into a financial framework rather than anything else, rather than a cryptocurrency.

We moved all of this aside a little bit.