Jim Fan Declares 'RIP VLAs' — NVIDIA's Robotics Lead Bets on Physics-Grounded World Models and Human-Video Pretraining

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Fan argues Vision-Language-Action models are fundamentally brittle because they merely bolt robot actions onto LLMs, and says the field is converging on physics-grounded world models instead. NVIDIA's EgoScale approach leans on 20,000 hours of egocentric human video with essentially no robot data in pretraining, targeting a 'physical Turing test' in 2–3 years. It's a sharp reframing of the humanoid-robotics roadmap from one of its most visible voices.