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Predictive Motion: How Transformers Are Learning to Walk

In this deep dive, Herman and Corn explore the radical convergence of large language models and robotics, marking a transition from digital logic to physical embodiment. They break down the mechanics of Vision-Language-Action (VLA) models, explaining how the transformer architecture is being repurposed to predict motor commands just as it predicts words. By treating physical movements as "action tokens," researchers are bridging the gap between abstract reasoning and real-world coordination. The discussion covers the critical "reality gap," the role of high-fidelity simulations like NVIDIA…

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