Interview with Fudan's Chen Tao: Embodied foundation model architecture urgently needs a breakthrough; a GPT moment is unlikely within two years

Chen Tao, director of Fudan University's Deep Learning Laboratory, said in an interview with The Paper's tech section that mainstream VLA models rely too heavily on successful-trajectory data and lack failure and error-correction data, leaving robots without autonomous error correction or continual learning capabilities. The embodied foundation model architecture urgently needs a breakthrough, and an embodied GPT moment will be hard to achieve within two years.