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This episode delves into a groundbreaking active inference framework for robust 3D object-centric representations, inspired by biological perception. Discover how this approach disentangles "what" an object is from "where" it is located, leading to superior object classification and precise pose estimation, even for novel objects. The discussion highlights how active perception, unlike passive observation, significantly enhances an AI's ability to understand and interact with dynamic 3D environments.