Strong Generalization from Small Brains and No Training Data

To survive in complex three-dimensional environments — and to behave effectively in unknown future settings — animals must possess the ability to represent and manipulate geometric representations of the world. Bruno Olshausen (UC Berkeley) and collaborators have been exploring the neural computations and representations that could underlie such abilities. In this talk from the recent workshop on Unknown Futures of Generalization, Olshausen presents recent progress on this problem, especially how such circuits could operate robustly at low power and small form factor.