Matthew Prince

Like, that's what the LLMs are, right?

And I picture it as like a giant block of Swiss cheese.

There's a lot of cheese.

That's the knowledge.

But there's a lot of holes in the cheese.

And the same mathematical models actually show you where the holes are.

And so in the future, I actually think one of the things that would be really interesting is maybe we compensate people for filling in the holes in the cheese, right?

Which is different...

than compensating them for traffic.

We're actually compensating you for filling in where the gaps in human knowledge are.

And if I were running one of the big AI companies, I would launch, I don't know if it's the equivalent of like a Nobel Prize or an Academy Award, but every year across all of the different fields, they should publish, here is the person, here's the content creator

academic, you know, researcher, journalist, whoever it is, here's the content creator who did the most to advance, you know, biology or physics or journalism or whatever it is and actually reward that both with, you know, recognition, but then also with, you know, maybe compensation in some way.

And I think that it's amazing that for the first time we can actually measure

who did the most in terms of furthering human knowledge in any given topic which is out there.

And I think that's super exciting and then starts to suggest what that business model is.

Yes, except, and I don't know the solution to this, so I am all ears for ideas.

I think there are two potential problems.

Potential problem number one is it all depends on a subscription model for the AI companies, where the AI companies are collecting dollars and then they're basically putting those into a ASCAP, BMI, Spotify-like pool that then goes out to the different content creators that are out there.

And the challenge, again, is I think in the global south,

You know, people don't have the money to pay for this.