Wang Xingxing, founder and chairman of humanoid robotics company Unitree, said the main challenge facing physical AI is still the gap between models and the physical world. Speaking at the sub-forum on humanoid robots and embodied intelligence industry innovation and development cooperation during the ninth Hongqiao International Economic Forum, Wang said multimodal models already show fairly strong understanding capabilities on their own. In his view, the bigger problem now lies in input-output alignment errors. He pointed to two specific areas: deviations between sensor measurements and real-world states on the input side, and mismatches between action commands and actual motion on the output side. Wang added that this part of the problem may be solved within the next one to two years. The remarks focused on technical bottlenecks in physical AI rather than broader market or policy issues.
Wang Xingxing, founder and chairman of humanoid robotics company Unitree, said the core challenge in physical AI is aligning models with the physical world.
Input and output errors remain the main issue
Speaking at the sub-forum on humanoid robots and embodied intelligence industry innovation and development cooperation during the ninth Hongqiao International Economic Forum, Wang said multimodal models already have relatively strong understanding capabilities.
He said the biggest problem at this stage is input-output alignment error. On the input side, that includes deviations between sensor measurements and real states. On the output side, it refers to gaps between action commands and actual movement.
Wang sees a 1-2 year window for progress
Wang said this part of the problem may be resolved in the next one to two years.
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