Ex-OpenAI Scientist Trains Robots with RLHF Approach: Single Policy Masters Walking, Jumping, and Crawling
chris_j_paxton · x · 2026-07-25
The author argues that wheeled robots will fundamentally lose in many environments over a 5-10 year timeline, as legged robots offer far more ways to adjust their posture and remain stable.
The quoted post demonstrates a robotics breakthrough: when physically restrained, a robot trained with a single general policy can autonomously find its way back to stable walking without any scripted recovery moves. The startup behind this was founded by a former OpenAI scientist who worked on the RLHF method powering ChatGPT, applying similar reinforcement learning concepts to robotics.
Related event: Light Origin Unveils Single-Policy Locomotion System for Robots(3 posts)→
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