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On November 2, 2026, Dong Hao, associate professor at Peking University, took on the role of Chief Scientist at Qiyuan Robotics, leading a team to tackle general-purpose embodied intelligence for the home. He proposed that the key to victory in embodied intelligence lies in scalable post-training: using HIL-UMI body-free data collection for post-training, and using a world model to amplify a single real-robot trajectory into 50 equivalent samples, magnifying the value of real-robot data by 50 times. He also proposed a horizontal Scaling Law with dual axes of data volume and task volume, enabling new tasks to achieve higher initial success rates with fewer required samples. Currently, this judgment was disclosed in a Leiphone report, and no other sources have cross-verified it.
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Dong Hao proposes that the winning factor in embodied intelligence lies in scalable post-training
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Nov 2
Leiphone
Post-90s Peking University associate professor Dong Hao: How Qiyuan Robot uses HIL-UMI and the horizontal Scaling Law to tackle home embodied intelligence
Peking University associate professor Dong Hao has taken on the role of Chief Scientist at Qiyuan Robot, leading the team to tackle general-purpose embodied intelligence for the home. He proposes using HIL-UMI bodyless data collection for post-training, and using a world model to amplify one real-robot trajectory into 50 equivalent samples, magnifying the value of real-robot data by 50 times. He also proposes a horizontal Scaling Law with dual axes of data volume and task volume, enabling new tasks to have a higher initial success rate and require fewer samples.