NVIDIA's Jim Fan Discusses Robotics Strategy and the Future of Autonomous Research
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At Sequoia Capital’s AI Ascent 2026, Jim Fan, head of NVIDIA's Embodied Autonomous Research group, outlined a clear technical roadmap for robotics, marking the 'end game' as a near reality. He emphasized the ongoing 'Great Parallel' in robotics, mirroring the rapid evolution of Large Language Models (LLMs) and aligning robotic development with the four-stage GPT framework: pre-training, alignment, reasoning, and autonomous research.
Fan highlighted the limitations of current Vision-Language-Action (VLA) models, such as GR00T N1.5, which excel at recognizing objects but struggle with physical interactions. He introduced the World Action Model (WAM), represented by NVIDIA’s DreamZero, which predicts physical states rather than just language outputs. This new approach aims to overcome the challenges of traditional teleoperation, which cannot scale effectively for generalist intelligence.
Looking ahead, Fan discussed NVIDIA's shift towards sensorized human data and generative simulation, exemplified by EgoScale's pre-training on 20,854 hours of human video. He predicted that machines would pass the Physical Turing Test within 2–3 years and that by 2040, robots would autonomously design their successors, marking a significant evolution in robotics technology.
Original report
The Great Parallel: NVIDIA’s Jim Fan Outlines the Robotics "End Game" Strategy
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