Dwarkesh

One of them is just continuing the next token prediction work.

So these AIs will have access to all human knowledge.

They will have read management books in some sense.

They're not starting blind.

There is going to be something like predict how Bill Gates would complete this next character or something like that.

And then there's the reinforcement learning in virtual environments.

So get a team of AIs to play some multiplayer game.

I don't think you would use one of the human ones because you would want something that was better suited for this task.

But just running them through these environments again and again, training on the successes, training against the failures, kind of combining those two kinds of things.

To me, it does not seem like the same kind of problem as inventing all human institutions from the Paleolithic onward.

It just seems like kind of applying those two things.

We have an estimate that about a year after the superintelligences start wanting robots, they're producing a million units of robots per month.

So I think that's pretty relevant because you have, I think it's Wright's Law, which is that your ability to improve efficiency on a process is proportional to doubling the amount of copies produced.

So if you're producing a million of something, you're probably getting very, very good at it.

The question we were arguing about is, can you produce a million units a month after a year?

And for context, I think Tesla produces like a quarter of that in terms of cars or something.

This is an amazing scale up in a year.

Yeah.

Yeah.

And the argument that we went through was something like, so it's got to first get factories.