Sergey Levine: evaluation

Transcript context

…Once we have, in 2035 or 2030, basically this sci-fi world, are you optimistic about the ability of true AGIs to build simulations in which they are rehearsing skills that no human or AI has ever had a chance to practice before? They need to practice to be astronauts because we're building the Dyson sphere and they can just do that in simulation. Or will the issue with simulation continue to be one regardless of how smart the models get? Here’s what I would say. Deep down at a very fundamental level, the synthetic experience that you create yourself doesn't allow you to learn more about the world. It allows you to rehearse things, it allows you to consider counterfactuals. But somehow information about the world needs to get injected into the system. The way you pose this question elucidates this very nicely. In robotics classically, people have often thought about simulation as a way to inject human knowledge. A person knows how to write down differential equations, they can code it up and that gives the robot more knowledge than it had before. But increasingly what we're learning from experiences in other fields, from how the video generation stuff goes from synthetic data for LLMs, is that probably the most powerful way to create synthetic experience is from a really good model. The model probably knows more than a person does about those fine-grained details. But then of course, where does that model get the knowledge? From experiencing the world. In a sense, what you said is quite right in that a very powerful AI system can simulate a lot of stuff. But also at that point it almost doesn't matter because, viewed as a black box, what's going on with that system is that information comes in and capability comes out. Whether the way to process that information is by imagining some stuff and simulating or by some model-free method is kind of irrelevant in our understanding of its capabilities. Do you have a sense of what the equivalent is in humans? Whatever we're doing when we're daydreaming or sleeping. I don't know if you have some sense of what this auxiliary thing we're doing is, but if you had to make an ML analogy, what is it?…

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