Illia Polosukhin

And so crypto was a pretty natural, actually, like solution we needed for our own problem.

It's like, hey, how do we actually pay people globally without like setting up a ton of entities without, you know, needing to do all the kind of hard work?

payment provider work and crypto seemed like a solution like hey you know you don't need a bank you don't need a yeah an entity in every country you can just send people money over internet but this was already 2018 there was nothing that would like scale work you know in a simple and a cheap way right to to do this for you know we were paying 15 cents per task to people

And so that's kind of how we got into near blockchain.

And so I would say at a time it made a little sense because it was clearly that to us that blockchain was kind of a part of the story for kind of AI evolution.

And at the same time, the hardware, the scale of AI itself wasn't there for what we were trying to do.

Yeah, so I mean, the reason why we started Near AI in 2017 is because we thought it's going to happen like right now at the time, right?

So we actually were way more optimistic thinking that we're almost there, right?

We are on like kind of the curve we're seeing right now.

We thought we were on that curve in 2017, 2018.

And we were wrong.

So, I mean, the main part was the compute wasn't there.

Like there was not enough, like the individual and kind of cluster compute parts just weren't there.

I think as soon as that kind of crossed the chasm, that's when this model started to scale.

I mean, there are a few components.

Obviously, we started with this data labeling, crowdsourcing.

I mean, think of Scale.ai, right?

Scale.ai has, you know, sub-entities everywhere.

It's like a thousands of people company, which then employs, you know, hundreds of thousands of people to actually do the work.

Like, that's just a smart contract, right?