While cool, this also seems utterly wasteful. Video games offer known "analytical" solutions for the interactions that the model provides as a "statistical approximation", so to say. I would consider a different approach, when the training phase watches games (or video recordings) and refines the formulas that describe its physics, the geometry of the area, the optics, etc. The result would be a "map" that is "playab…
I think this is precisely why they're doing it. Video games are where the data is, because the analytical solutions can generate it.
They aren't trying to make a video game. They're trying to make an android.