Demis Hassabis

Well, I've always been a huge proponent of simulations and AI. And it's also interesting to think about what the real world is in terms of a computational system. And so I've always been involved with trying to build very realistic simulations of things. And now, of course, that interacts with AI because you can have an AI that learns a simulator of some real world system

uh uh just by observing uh that system or all the data from that system so i think um the current debate is to do with uh these large foundation models um now pretty much use the whole internet right and and so then once you've tried to learn from those what's left right that's all the language that's out there of course there's other modalities like video and audio i don't think we've exhausted all of that kind of multimodal uh tokens but even that will reach some limit

uh uh just by observing uh that system or all the data from that system so i think um the current debate is to do with uh these large foundation models um now pretty much use the whole internet right and and so then once you've tried to learn from those what's left right that's all the language that's out there of course there's other modalities like video and audio i don't think we've exhausted all of that kind of multimodal uh tokens but even that will reach some limit

uh uh just by observing uh that system or all the data from that system so i think um the current debate is to do with uh these large foundation models um now pretty much use the whole internet right and and so then once you've tried to learn from those what's left right that's all the language that's out there of course there's other modalities like video and audio i don't think we've exhausted all of that kind of multimodal uh tokens but even that will reach some limit

So then the question comes of like, can you generate synthetic data? And I think that's why you're seeing quite a lot of progress with maths and coding, because in those domains, it's quite easy to generate synthetic data. The problem with synthetic data is, are you creating data that is from the right distribution, the actual distribution, right? Does it mimic the kind of real distribution?

So then the question comes of like, can you generate synthetic data? And I think that's why you're seeing quite a lot of progress with maths and coding, because in those domains, it's quite easy to generate synthetic data. The problem with synthetic data is, are you creating data that is from the right distribution, the actual distribution, right? Does it mimic the kind of real distribution?

So then the question comes of like, can you generate synthetic data? And I think that's why you're seeing quite a lot of progress with maths and coding, because in those domains, it's quite easy to generate synthetic data. The problem with synthetic data is, are you creating data that is from the right distribution, the actual distribution, right? Does it mimic the kind of real distribution?

And also, are you generating data that's correct, right? And of course, for things like maths, for coding and for things like gaming, you can actually test the final data and verify if it's correct, right? Before you feed it in as input into the training data for a new system.

And also, are you generating data that's correct, right? And of course, for things like maths, for coding and for things like gaming, you can actually test the final data and verify if it's correct, right? Before you feed it in as input into the training data for a new system.

And also, are you generating data that's correct, right? And of course, for things like maths, for coding and for things like gaming, you can actually test the final data and verify if it's correct, right? Before you feed it in as input into the training data for a new system.

So it's very amenable, certain areas, in fact, turns out the more abstract areas of human thinking that you can verify and prove that it's correct. And so therefore that unlocks the sort of ability to create a lot of synthetic data.

So it's very amenable, certain areas, in fact, turns out the more abstract areas of human thinking that you can verify and prove that it's correct. And so therefore that unlocks the sort of ability to create a lot of synthetic data.

So it's very amenable, certain areas, in fact, turns out the more abstract areas of human thinking that you can verify and prove that it's correct. And so therefore that unlocks the sort of ability to create a lot of synthetic data.

Yeah. Well, interestingly, if we talked about this earlier, Five years ago, or certainly 10 years ago, I would have said that some real world experience, maybe through robotics, usually when we talk about embodied intelligence, we're meaning robotics, but it could also be a very accurate simulator, right? Like some kind of ultra realistic game environment.

Yeah. Well, interestingly, if we talked about this earlier, Five years ago, or certainly 10 years ago, I would have said that some real world experience, maybe through robotics, usually when we talk about embodied intelligence, we're meaning robotics, but it could also be a very accurate simulator, right? Like some kind of ultra realistic game environment.

Yeah. Well, interestingly, if we talked about this earlier, Five years ago, or certainly 10 years ago, I would have said that some real world experience, maybe through robotics, usually when we talk about embodied intelligence, we're meaning robotics, but it could also be a very accurate simulator, right? Like some kind of ultra realistic game environment.

would be needed to fully understand, say, the physics of the world around you and the physical context around you. And there's actually a whole branch of neuroscience that is predicated on this. It's called action in perception. So this is the idea that one can't actually fully perceive the world unless you can also act in it.

would be needed to fully understand, say, the physics of the world around you and the physical context around you. And there's actually a whole branch of neuroscience that is predicated on this. It's called action in perception. So this is the idea that one can't actually fully perceive the world unless you can also act in it.

would be needed to fully understand, say, the physics of the world around you and the physical context around you. And there's actually a whole branch of neuroscience that is predicated on this. It's called action in perception. So this is the idea that one can't actually fully perceive the world unless you can also act in it.

And the kinds of arguments go is like, how can you really understand the concept of the weight of something, for example, unless you can pick things up?