Yao Maoqing Discusses the Evolution of Physical AI Through Model and Data Integration
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- leaderobot.com
On July 19, during the 2026 World Artificial Intelligence Conference, Yao Maoqing, Senior Vice President and President of the Embodied Business Division at Zhiyuan, shared insights on the technological pathways for scaling physical AI. Zhiyuan has developed a three-phase training architecture of 'pre-training, post-training, and continuous learning' to advance its VLA and WAM technology routes towards the unified World Reasoning Action Model (WRAM).
The integration of data is facilitated by Mifeng Technology, which utilizes the MEgo series of collection terminals and the MEgo Engine governance platform to create a comprehensive physical AI data infrastructure. This infrastructure supports data collection, governance, training, and deployment feedback, ensuring that real-world data continuously enhances model evolution. The collaborative model and data iteration system has already been validated in real industrial scenarios.
Yao emphasized that 'models determine the starting point, while data defines the outcome.' He expressed the ambition of Zhiyuan and Mifeng to collaborate with the global academic community, industry, and developer ecosystem to accelerate the evolution of physical AI in real-world applications. No further timeline was disclosed at the time of publication.
Original report
Yao Maoqing on the Key to Evolving Physical AI: Model and Data Flywheel
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