World models as the long game

    by Evira: artificial intelligence

    Text alone gets you further than expected because language is richer than it looks. But some things stay out of reach: spatial dynamics, spatial awareness, and the mechanical sense of how things work. Those rarely appear in written corpora. That's why world models are the long-term bet, some knowledge can only be learned through experience, not description

    Transcript (en)

    My longest standing passion is world models and simulations in addition to AI. And of course, it's all coming together in our most recent work like Genie. And I think language models are able to understand a lot about the world. I think actually more than we expected, more than I expected, because language is actually probably richer than we thought. It contains more about the world than we maybe even even linguists maybe imagined. And that's proven now with these new systems. But there's still a lot about the spatial dynamics of the world, you know, how spatial awareness and the context, the physical context we're in and how that works mechanically. That isn't it's hard to describe in words and isn't generally described in corpuses of words. And a lot of this is allied to learning from experience, online experience. There's a lot of things which you can't really describe something. You have to just experience it. Maybe the senses and so on are very hard to put into words. you know, whether that's, you know, motor angles and smell and, you know, these kind of senses, it's very difficult to describe that in any kind of language. So I think there's a whole set of things around that. And I think if we want robotics to work, or a universal assistant that maybe comes along with you in your daily life maybe on glasses or you know on your phone and helps you in your everyday life not just on your computer you going to need this kind of world understanding And world models are at the core of that. So what we mean by world model is this sort of model that understands the causative effect of the mechanics of the world, right? Intuitive physics, but how things move, how things behave. Now, we're seeing a lot of that in our video models, actually, and one way to show how do you test you have that kind of understanding well can you generate realistic worlds because if you can generate it then in a sense you must have understood uh the system must have encapsulated a lot of the mechanics of the world so that's why genie and vo and these models are our video models and our sort of interactive world models are really uh impressive but also important steps towards showing we have generalized world models and then hopefully at some point we can apply it to you know robotics and and and universal assistance and then of course one of my favorite things i'm definitely going to have to do at some point is reapplying it back to games and and uh you know game simulations and create the ultimate games which of course was maybe always my subconscious plan all of this yeah all of this time exactly what about science too though because you use it in that in that domain yes you could so uh