Exploring Perceptual Inference and Evolutionary Priors

The chapter delves into the philosophical limits of intelligence and prior expectations in sensory models, discussing perceptual inference and the origins of prior beliefs. It highlights the role of inductive biases, structural learning, and evolutionary priors in computational frameworks, addressing the complexity mismatches between inherited information and design elements. The conversation extends to language learning challenges, self-organizing systems in neural networks, and the importance of inductive biases in coordinating system elements for functional convergence.