What if evolution discovered that information itself is the most reliable local gradient for finding good solutions? Computer scientist Daniel Polani explains how information theory provides a normative framework for understanding why sensors are optimized, why brains are expensive, and why cognition is fundamentally constrained by the physics of embodiment. Subscribe for more from the Convergent Science Network podcast series. Daniel Polani joins Paul Verschure and Tony Prescott at the BCBT summer school to present his information-theoretic approach to embodied cognition. Starting from the observation that biological sensors often operate near their physical limits, Polani argues that information serves as a local proxy that evolution uses to direct adaptation , organisms that capture more relevant information gain access to new ecological niche ...