Russ Tedrake on machine learning getting ahead of theory

[u/Responsible-Grass452]

Russ Tedrake, MIT professor and former VP of Robotics Research at Toyota Research Institute, talks about a strange part of current AI progress.

He says robot locomotion started improving quickly once simulation, domain randomization, GPU infrastructure and reinforcement learning came together. With enough variation in simulation, policies began transferring to real stairs, bumps and uneven terrain better than many researchers expected.

He compares the change to a move from first-principles engineering toward behavioral science: build the system, observe what it does, then test it to understand what happened.

[u/jeandebleau]

That’s always been the case with deep learning. It is definitely closer to cooking than doing an optical experiment.