Demis Hassabis

Everything that we see around us, including like the elements that are more stable, all of those things, they're subject to some kind of selection process, pressure.

Yeah.

I mean, I've always been fascinated by the P equals NP question and what is modulable by classical systems, i.e.

non-quantum systems, you know, Turing machines in effect.

And that's exactly what I'm working on actually in kind of my few moments of spare time with a few colleagues about should there be, you know, maybe a new class of problem that is solvable by this type of neural network process and kind of mapped onto these natural systems.

So, you know, the things that exist in physics.

and have structure.

So I think that could be a very interesting new way of thinking about it.

And it sort of fits with the way I think about physics in general, which is that, you know, I think information is primary.

Information is the most sort of fundamental unit of the universe, more fundamental than energy and matter.

I think they can all be converted into each other.

But I think of the universe as a kind of informational system.

That's right.

Yeah, I think it's one of the most fundamental questions, actually, if you think of physics as informational.

And the answer to that, I think, is going to be very enlightening.

Yeah, I think that there are actually a huge class of problems that could be couched in this way, the way we did AlphaGo and the way we did AlphaFold, where you model what the dynamics of the system is, the properties of that system, the environment that you're trying to understand, and then that makes the search for the solution or the prediction of the next step efficient.

basically polynomial time, so tractable by a classical system, which a neural network is.

It runs on normal computers, classical computers, Turing machines in effect.

And I think it's one of the most interesting questions there is, is how far can that paradigm go?

I think we've proven, and the AI community in general, that classical systems, Turing machines, can go a lot further than we previously thought.