Dwarkesh Patel

I think five is a good median.

Okay.

Five years.

So if you can fully autonomously run a house, then I think you've like – you can fully autonomously do most blue-collar work.

So your estimate is in five years it should be able to do most like blue-collar work in the economy.

I mean, separate from the question of whether people will get fired or not, a different question is like what will the economic impact be in five years?

Yeah.

The reason I'm curious about this is with LLMs,

the relationship between the revenues for these models to their inherent, their seeming capability has been sort of mysterious in the sense that, like, you have something which feels like AGI.

You can have a conversation where there really, like, is, like, you know, like, passes a soaring test.

It really feels like it can do all this knowledge work.

It's obviously doing a bunch of coding, et cetera.

But then the revenues for these AI companies are, like, cumulatively under the order of, like, $20, $30 billion per year.

And that's so much less than...

all knowledge work, which is $30, $40 trillion.

So in five years, are we in a similar situation that LLMs are now, or is it more like we have robots deployed everywhere and they're actually doing a whole bunch of real work, et cetera?

There's so many things that increase productivity.

Just like wearing gloves increases productivity or like, I don't know.

But then it's like you want to understand something which like increases productivity a hundredfold versus like, you know, wearing glasses or something which has like a small increase.

So robots already increase productivity for workers, right?