Qingyan Precision's Chen Chao: Building a Vocational School for Embodied AI Industrial Deployment

From September 17 to 20, the 22nd China Automotive Industry Development (TEDA) International Forum was held in Tianjin Binhai New Area. On September 18, at the embodied AI new track session, Chen Chao, co-founder and chief ecosystem officer of Qingyan Precision, delivered a speech titled "Let Robots Truly Enter Auto Factories: From Testing and Validation to Scale Delivery of Embodied Intelligence."

Qingyan Precision neither builds cars nor robots; it uses its expertise in automotive testing and validation to help embodied AI companies achieve batch delivery in industrial scenarios.

Chen said autonomous driving provides a paradigm for embodied AI but with a different path. Autonomous driving is a leading example of physical AI scaling, achieving commercial and technological closed loops in many scenarios.

It can be seen as a mobile agent solving free movement in the human world. In contrast, embodied AI and robots face the challenge of interacting with the real environment.

Autonomous driving defines safety boundaries well through collision risk metrics. But robots face a new problem: interaction with the real world requires close contact between two objects. For example, in force control, too much force may crush the object, while too little may fail to grasp it.