The end goal is to marry the lessons learned about HOW to learn in a virtual world with a high fidelity world model that's currently out of reach for this generation of AI. In a year or two once we have a world model that's realistic enough and fast enough, robots will be trained there and then (hopefully) generalize easily to the real world. This is groundwork trying to understand how to do that without having the models required to do it for real.
