How do you guys think about balancing all of these things as you keep making improvements on what you're releasing?

I think we're really excited about computer use at OpenAI.

We've invested in it a lot, and we've gotten to a place where I think we have the fastest, cheapest, and most reliable computer use product.

And I think there's actually so much further we can take that.

We spent a lot of time looking at speed.

Speed is really interesting because on one hand, the power of computer use is it can do tasks in the background.

So in some cases, it doesn't matter how long it takes because you can be going and doing other things while it's accomplishing the task for you.

Well, I want it to be able to communicate with people or I want it to be like, I don't know, a black box, just like maybe if you had to talk to founders right now, what advice would you give them as they try to use your models and capabilities to just solve problems for enterprises? In my mind, it

Uh, what are the bottlenecks? Is it models? Is it harnesses? What-- Where do you see it going in, like, two years? Do you see it just running for hours? How do we get there? Any, any predictions on where computer use goes?

Yeah, I mean, I, I think what's really crazy that I think, you know, the team's accomplished over the past couple months is that now computer use is, like, faster at accomplishing tasks than, like, the average human probably in, in most cases.

Um, and I think that the next frontier is to have computer use be, like, literally superhuman in its performance, where it actually is as fast or faster at using software than, like, expert computer users like us.

Um, and I think that'll be really consequential and exciting when that happens because I think we'll be able to all of a sudden build products, um, that, um, provide just much more real-time experiences, and I think it'll also lowering the barrier to entry of, um, or the activation energy, I suppose, of using computer use, I think will make us start to default to doing certain things in agents that we've become accustomed to doing manually, and I think that's exciting also 'cause it'll save us a ton of time.

Um, and I think there's a, the, you know, there are a lot of different little paper cuts and bottlenecks that are sort of standing in the way of that.

Um, um, I think that there's, um, yeah, there's things on the model side, there's things on the inference side, there's things on the harness side, there's things in the, in the representation.

You know, we find that as computer use gets faster, we're increasingly bottlenecked by just, like, the speed of doing an operation.

... encounter all this, uh, firsthand?