Demis Hassabis

The way I think about that actually is like if I was to play a game of chess against Garry Kasparov, right, which I played in the past, or Magnus Carlsen, you know, the amazing chess players, graceful time, I wouldn't be able to come up with a move that they could, but they could explain to me why they came up with that move and I could understand it post hoc, right?

And that's the sort of thing one could imagine.

One of the...

capabilities that we could make use of these systems is for them to explain it to us and even maybe the proofs behind why they're thinking something.

Certainly in a mathematical, any mathematical problem.

Yeah, I could imagine that.

And this is where things like the sandbox simulations, I would hope we're experimenting in a safe, secure environment.

And then something happens in it where very unexpected happens, a new unexpected capability or something that we didn't want, explicitly told the system we didn't want that it did, but then lied about.

These are the kinds of things where one would want to then dig in

carefully with the systems that are around today, which are not dangerous in my opinion today, but in a few years they might be, have potential.

Then you would ideally pause and then really get to the bottom of why it was doing those things before one continued.

Well, look, first of all, there are practical limits.

How much compute can you actually fit in one data center?

And actually, you're bumping up against very interesting distributed computing kind of challenges, right?

Fortunately, we have some of the best people in the world on those challenges and cross data center training, all these kinds of things.

Very interesting challenges, hardware challenges, and we have our TPUs and so on.

that we're building and designing all the time, as well as using GPUs.

And so there's all of that.

And then you also have to, the scaling laws, they don't just work by magic.

You still need to scale up the hyper parameters and various innovations are going in all the time with each new scale.