
Episode 21: Chelsea Finn, Stanford, on the biggest bottlenecks in robotics and reinforcement learning
Generally Intelligent
Resonance Learning - Sample Efficiency
We used to be really excited about object-centric models also. But then thought about it a lot more and it's like, well, what is an object? Is the brick an object? Well, the wall. What about this plan? Yeah. Objects are fractal in a way in the real world. And we form representations of objects in some other way. That is not how theseobject-centric models are learning. One also should be based off of the tasks that you're doing. If you want to ride a bike, you model the bike as a bike. Whereas if you want to fix a bike or fix a flat tire, you're going to model individual parts of the
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