Daniel Kokotajlo

It just looks like, if you look at the history of invention, it just seems like...

People are just trying different random stuff.

Often even before the theories about how that industry works or how the relevant machinery works is developed, like the steam engine was developed before the theory of thermodynamics.

The Wright brothers were just experimenting with airplanes.

And it's often influenced by breakthroughs in totally different fields, which is why you have this pattern of parallel innovation because the background level of tech is at a point at which you can do this experiment.

I mean, machine learning itself is...

a place where this happened, right?

Where people had these ideas about how to do deep learning or something, but it just took a totally unrelated industry of gaming to make the relevant progress to get the whole... Basically, the economy as a whole advanced enough that deep learning, like Jeffrey Hinton's ideas, could work.

So...

I know we're accelerating way into the future here, but I just want to get to this crux.

Yeah, I think the fact that there's a million of them

Or the fact that they're comparable to maybe the size of the key researcher population of the world or something.

I don't think a million is... I think there's more than a million researchers in the world, but... Well, but it's very heavy-tailed.

That's right.

But it's not clear to me that most of the new stuff that is developed is a result of this researcher population.

I mean, there's just, like, so many examples in the history of science where...

a lot of growth or productivity improvements is just the result of... How do you count the guy at the TSMC process who figures out a different way to... I actually argued with Daniel about this recently, about one interesting case that I can go over.

I'm assuming the bombers were just much...

less sophisticated than the kind of humanoid robots.

Maybe to give one hypothetical here.