Ian Dunning

There's got to be some sort of

forcing function where, you know, your margins go to zero as you keep investing more in compute.

Basically.

And we're not the only ones.

So in the end, can there be some Highlander type thing?

Like, what are we doing?

And this is like my scale.

And I guess the other thing I find interesting is, of course, the scale that everyone can see with the big labs and what they're doing with compute.

And it's like,

It looks awfully exponential to me.

We just had another model released today from Anthropic, and the spacing between them seems to be compressing.

I don't know.

I do sound delirious.

I sound feverish, and that's why it's so hard to... Literally everyone in this room probably is talking about this.

Everyone must feel a fever to some extent, yeah.

So, I mean, our primary use cases at Hudson River Trading are definitely kind of just like accelerating your own research.

So that can be coding, but it can also be coming up with experiment ideas, monitoring experiments.

We had a sort of a false start with AI, I would say, sometime last year with the Opus 4.0 models, especially from Anthropic.

where a cursory examination made us feel like, well, this is the moment we've crossed the dividing line.

And we had a very feverish week where we felt the AGI and we left feeling empty because we realized that it was not there and was not able to meaningfully augment human researchers.