In this talk, I will discuss recent publications from my group that attempt at learning models of the world and the effect of the actions of an agent within that world self-supervised, solely via interaction. In particular, I will discuss the potential and challenges of video generative models as a candidate for such a world model, the role of inductive biases using our recent work that discovers the kinematics of a robot as an example, and finally a new research direction in which we attempt to discover the physical rules underlying our world without any inductive biases whatsoever.