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Intelligence and Movement

Karl discusses the limitations of current machine learning approaches, likening them to an oil droplet that passively absorbs data rather than actively seeking it out. He emphasizes the significance of movement and embodied understanding in intelligence, suggesting that true learning requires an active engagement with the environment. The conversation highlights the need for machine learning to evolve beyond merely processing large datasets to incorporating the dynamics of movement and exploration.