Demis Hassabis

I think we've got to try and get some international consensus around that.

And then also making sure that the benefits of these systems benefit everyone, for the good of everyone in society in general.

And that's why I push so hard things like AI for science.

And I hope that, you know, with things like our spin out isomorphic, we're going to start curing diseases, you know, terrible diseases with AI and accelerate drug discovery, amazing things, climate change and other things.

I think big challenges that face us and face humanity, massive challenges actually, which I'm optimistic we can solve because we've got this incredibly powerful tool coming along down the line of AI that we can apply and I think help us and

solve many of these problems.

So, you know, ideally, we would have a big consensus around that and a big discussion, you know, sort of almost like the UN level if possible.

Yeah, I think that just shows we're still at the beginning of this new era.

And I think that for these systems, I think there are some interesting use cases.

where you can use these chatbot systems to summarize stuff for you and maybe do some simple writing and maybe more kind of boilerplate type writing.

But that's only a small part of what we all do every day.

So I think for more general use cases, I think we still need new capabilities.

uh things like um planning and search but also maybe things like personalization and memory episodic memory so not just long context windows but actually remembering what i what we spoke about 100 conversations ago um and i think once those start coming in i mean i'm really looking forward to things like recommendation systems that that help me

find better, more enriching material, whether that's books or films or music and so on.

I would use that type of system every day.

So I think we're just scratching the surface of what these AI, say, assistants could actually do for us in our general everyday lives and also in our work context as well.

I think they're not reliable yet enough to do things like science with them.

But I think one day, once we fix factuality and grounding and other things, I think they could end up becoming like

the world's best research assistant for you as a scientist or as a clinician.

Yeah, I mean, sort of at the limit, one maybe could try and memorize everything, but it wouldn't generalize out of your distribution.