AGI requires creativity, physical skills and world models

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 6:26

   We've brought up AGI a couple of times. So let me put this to you, because I was speaking with Sam Altman towards the end of the year. And I asked him, I was like, you seem to be saying two things. We're not at AGI yet, but every time he talks about what GPT models can do, it seems like it fits his definition. And he said that AGI is underdefined. What he wishes everybody could agree to was that we've sort of whooshed by AGI and we moved towards super intelligence. Do you agree with that? I'm sure he does wish that. No, absolutely not. I don't think AGI should be sort of turned into a marketing term for commercial gain. I think there has always been a scientific definition of that. My definition of that is a system that can exhibit all the cognitive capabilities humans can. And I mean all. So that means, you know, the kind of highest

2. 7:19

   levels of human creativity that we always celebrate, the scientists and the artists that we admire. So it means, you know, not just solving a maths equation or a conjecture, but coming up with a breakthrough conjecture. That's much harder. You know, not solving something in physics or some bit of chemistry, some problem, even like alpha folds, you know, protein folding, but actually coming up with a new theory of physics, something like, you know, like Einstein did with general relativity, right?

3. 7:45

   Can a system come up with that? Because of course we can do that. The smartest humans with their brain architect, our human brain architectures have been able to do that in history. And the same on the art side, you know, not just create a pastiche of what's known, but actually be. Picasso or Mozart and create a completely new genre of art that we'd never seen before right and today's systems in my opinion are nowhere near that um doesn't matter how many you know Erdos problems you solve which for some reason you know I mean you know that's it's good that we're doing those things but I think it's far far from what uh you know a true invention or someone like a Ramanujan would have been able to do and you need to and you need to have a system that can potentially do that across all these domains and then on top of that I'd add in

4. 8:29

   physical intelligence, because of course, you know, we can play sports and control our bodies and to amazing levels, the elite sports people that are walking around, you know, here today in Davos. And we're still way off of that on robotics, as another example. So I think an AGI system would have to be able to do all of those things to really fulfill the original sort of goal of the AI field. And I think, you know, we're five to 10 years away from that.

5. 8:54

   I think the argument would be that if something can do all those things, it would be considered superintelligence but no you think agi is a good no of course not because the individual those individual humans could we can come up with new theories that einstein did feinman did all the all the greats that more my scientific heroes they were able to do that it's rare but it's possible with the human brain architecture so superintelligence is another concept that's worth talking about but that would be things that can really go beyond what human intelligence can do we can't think in 14 dimensions or you know plug in weather satellites into our brains Not yet, anyway.

6. 9:28

   And so those are truly beyond human or superhuman. And that's a whole other debate to have, but once we get to AGI. I was listening to you recently, and something you said really surprised me. You were asked on the Google DeepMind podcast, which is a great listen, if you have a system today that is close to AGI, I thought it might be Gemini 3. You named Nano Banana. Yes. The image generator. Yes. What? Well, you know, sometimes you have to have these fun names and have fun with those.

7. 10:01

   But how is an image generator close to AGI? Oh, well, of course, look, let's take image generators, but also let's talk about our video generator, VO, which is the state of the art in video generation. I think that's even more interesting from an AGI perspective. You know, you can think of a video model that can generate you 10 seconds, 20 seconds of a realistic scene. it's sort of a model of the physical world. Intuitive physics, we'd sometimes call it in physics land. And it's sort of intuitively understood how liquids and objects behave in the world. And that's, and obviously one way to exhibit understanding is to be able to generate it, at least to the human eye being accurate enough to be satisfying to the human eye.

8. 10:45

   Obviously, it's not completely accurate from a physics point of view, and we're going to improve that but it's it's it steps towards having uh this idea of a world model a system that can understand the world and the mechanics and the causality of the world and of course that would be i think essential for a gi because that would allow these systems to plan long-term plan in the real world um over perhaps very long time horizons which of course we as humans can do you know um i'll spend four years getting a degree so that i have more qualifications so that in 10 years i'll have a better job. These are very long-term plans that we all do quite effortlessly. And at the moment, without these systems, we still don't know how to do. We can do short-term plans over one timescale. But I think you need these kind of world models. And I think if you imagine robotics,

9. 11:32

   that's exactly what you want for robotics, is robots planning in the real world, being able to imagine many trajectories from the current situation they're in, in order to complete some task. That's exactly what you'd want. And then finally, from our point of view, and this is why