Randall and Keith discuss the intricate relationship between the dimensionality of the latent space and the complexity of the problem being solved. They delve into how the intrinsic dimensionality of a problem can impact the utilization of dimensions in the latent space, shedding light on the challenges of learning simple mappings with nonlinear deep networks.
