Demis Hassabis

Yeah.

Well, I don't have prescribed specific numbers to it because I think there's so many unknowns and uncertainties and human ingenuity and endeavor comes up with surprises all the time.

So that could meaningfully move the timelines.

but i will say that when we started deep mind back in 2010 you know we thought of it as a 20-year project and and actually i think we're on track which is kind of amazing for 20-year projects because usually they're always 20 years away right so that's the joke about you know whatever it is quantum ai

take your pick.

But I think we're on track.

So I wouldn't be surprised if we had AGI-like systems within the next decade.

I think that's

potentially possible.

Um, I, I think it partly depends what we, uh, decide we as society decide to use the first AGI nascent AGI systems or even proto AGI systems for, um, so, uh, you know, even the current LLMs, uh, seem to be pretty good at coding.

So, uh, and, you know, we have systems like alpha code.

We also got theory improving systems.

So one could imagine, uh,

combining these ideas together and making them a lot better.

And then I could imagine these systems being quite good at designing and helping us build future versions of themselves.

But we also have to think about the safety implications of that, of course.

Well, look, we need a lot more understanding of the systems than we do today before I would be even confident of even explaining to you what we would need to tick box there.

So I think actually what we've got to do in the next few years in the time we have before those systems start arriving is come up with the right evaluations and metrics.

maybe ideally formal proofs, but it's going to be hard for these types of systems, but at least empirical bounds around what these systems can do.

And that's why I think about things like deception as being quite root node traits that you don't want, because if you're confident that your system is sort of exposing what it actually thinks, then you could potentially, that opens up possibilities of using the system itself to explain aspects of itself to you.