Trenton Bricken

Yes.

And if it's human in the loop, then it's so much more effortful.

And unless it's getting, that's applying immediately.

I've noticed if I don't have a second monitor with cloud code always open in the second monitor, I won't really use it.

Yeah, yeah.

It's only when it's right there and I can send off something.

If it hits, great.

If not, I'm kind of working on it at the same time.

Yeah.

This goes back to the monkeys on the typewriter, I think, and the pre-training model.

Until you had something like GPT-3, GPT-4, it just couldn't generate coherent enough sentences to even begin to do RLHF and tell it what you liked and didn't like.

Yeah, I mean, I think more and more it's no longer a question of speculation.

If people are skeptical, I'd encourage like using Claude code or like some agentic tool like it and just seeing what the current level of capabilities are.

Tweeting is so much easier.

But seriously, like, the models are getting really capable at tasks that we care about and we can give them enough data for.

And, I mean, the circuits results from interpretability are also pointing in the direction that they're doing very reasonable, generalizable things.

And so, yeah, this question matters a lot, but...

I'm surprised by how many deep learning critics just haven't really interacted with the models or haven't in a while.

MARK MANDELMANN- Yeah, yeah, yeah.

Like, the Turing test used to be a thing, right?