In this episode, Michael Cruz joins Digital Dialogs to explore world models — AI systems that learn internal representations of how the physical world works. The conversation covers what world models are, why current generative AI falls short in understanding physical reality, the technical challenges of teaching machines to simulate physics, causality, and spatial dynamics, and where these capabilities are heading across robotics, autonomous systems, and simulation. Listeners will gain insight into why building AI that truly understands the physical world is one of the field's most important open problems, and what it will take to get there at scale.
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