Comment by naasking
5 days ago
> Robots take in sensory data and return movements, in real-time. There is no large data corpus of this pairing to do self-supervised learning on, like there is for text.
This is easily generated synthetically from a kinematic model, at least up to a certain level of precision.
That would be like trying to pretrain GPT-1 from synthetically generated data only. It probably wouldn't work because the synthetic data doesn't resemble real world data enough.
It did work for AlphaGo Zero (and later AlphaZero), which were entirely trained on synthetic data. But that's for very simple games with strict formal rules, like Go and chess.
A kinematic model of the robot is a physics simulation of the robot. I don't see why that wouldn't resemble real world data enough.
Not just the robot has to be simulated, the entire part of the world it interacts with also has to be. Even the most realistic video games resemble actual videos of the real world only very superficially.
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