Demis Hassabis

Of course, there's the question of things like chaotic systems where the initial conditions really matter and then you get to some, you know, uncorrelated end state.

Now, those could be difficult to model.

So I think these are kind of the open questions.

But I think when you step back and look at what we've done with the systems and the problems that we've solved, and then you look at things like VO3 on like video generation, sort of rendering physics and lighting and things like that, you know, really core fundamental things in physics.

It's pretty interesting.

I think it's telling us something quite fundamental about how the universe is structured, in my opinion.

So, you know, in a way, that's what I want to build AGI for, is to help us as scientists answer these questions like P equals MP.

And so if there's one to follow and you can specify the objective function correctly, you know, you don't have to deal with all that complexity, which I think is how we maybe have naively thought about it for decades, those problems.

If you just enumerate all the possibilities, it looks totally intractable.

And there's many, many problems like that.

And then you think, well, it's like 10 to the 300 possible protein structures, 10 to the 170 possible go positions.

All of these are way more than atoms in the universe.

So how could one possibly find the right solution or predict the next step?

But it turns out that it is possible.

And of course, reality in nature does do it.

right?

Proteins do fold.

So that gives you confidence that there must be, if we understood how physics was doing that, in a sense, then, and we could mimic that process, i.e.

model that process, it should be possible on our classical systems is basically what the conjecture is about.

Yes, exactly.