Trenton Bricken

Yeah, versus China.

Yes.

Yeah, and we're, like, 34 gigawatts off.

Yeah, yeah.

And I mean, the US like very clearly- Yeah, we just need so many more power plants.

Yeah, just to make it explicit, because we've been touching on it here, even if AI progress totally stalls, you think that the models are really spiky and they don't have general intelligence, it's so economically valuable and sufficiently easy to collect data on all of these different jobs, these white-collar job tasks, such that, to Sholto's point, we should expect to see them automated within the next five years.

Yeah.

Even if you need to hand spoon every single task to the model.

I do just want to flag as well that there's a really dystopian future if you take more of X-Paradox to its extreme.

Which is this paradox where we think that the most valuable things that humans can do or the smartest things are like add large numbers in our heads or do any sort of white collar work.

And then we totally take for granted our fine motor skill and coordination.

But from an evolutionary perspective, it's the opposite.

So we got like evolution has optimized fine motor coordination so much.

Oh, well, and if you look at, like, robot hands or, like, the ability to open a door is still just, like, really hard for robots.

Meanwhile, we're seeing this total automation of coding and everything else that we've seen is clever.

The really scary future is one in which AIs can do everything except for the physical robotic tasks, in which case you'll have humans with, like, AirPods and, like— Glasses.

glasses and there'll be some robot overlord controlling the human through cameras by just like telling it what to do and like having a bounding box around the thing you're supposed to pick up and so you have like human meat robots um and and not like necessarily saying that like that's what the ais would be like want to do or anything like that present like if you were to be like what are the relative economic value of things like the ais are out there doing computer programming and like the most valuable thing that humans can do is like be amazing robots

I do think there's this notion, the longer, the harder tasks, the more training is required.

And I'm sympathetic to that naively, but we as humans are very good at practicing the hard parts of tasks and decomposing them.

And I think once models get good enough at the basic stuff, they can just rehearse or fast forward to the more difficult parts.