Our image this week maps the extraordinary number of humanoid robots being developed across China. More than 140 Chinese manufacturers produced over 330 humanoid models in 2025, according to the industry ministry. Some are intended for factories, warehouses or customer service. Others dance, box, run marathons or provide inexpensive platforms for researchers. Many companies will disappear, but the level of experimentation is remarkable.
The regional differences explain some of this diversity. Beijing combines leading universities, AI labs and state-backed research platforms, so its companies often focus on models, general-purpose systems and shared datasets. Shanghai draws on automotive production, precision engineering and medical technology, with AgiBot and Fourier targeting factory and rehabilitation work. Shenzhen’s electronics supply chain enables companies such as UBTECH and LimX Dynamics to iterate hardware quickly. Hangzhou’s Unitree and Deep Robotics have transferred their experience building affordable quadrupeds into humanoids.
China has the necessary component suppliers, manufacturing capacity, engineering talent and research base. It also has factories, logistics networks and public spaces in which robots can be deployed and tested. Surveys show unusually high Chinese trust in AI, although that does not automatically translate into acceptance of robots at work or at home. Government and corporate investment are currently more important than consumer demand.
The physical machines are still limited by their intelligence. This week, Wenli Xiao, first author of Nvidia’s ENPIRE robot harness, showed GPT-6 Astra watching a recording of a human performing a novel task and then driving a robot arm to reproduce it. The model did not control the motors directly. It interpreted the video, identified the required actions and called tools within Nvidia’s ENPIRE harness.
Perception tools located the objects and estimated suitable grasping positions. Astra produced target positions for the robot gripper. Motion-planning software then calculated collision-free movements, while inverse kinematics converted those targets into joint instructions. The task reportedly worked on the first attempt.
This suggests a practical architecture for general-purpose robotics. Increasingly capable AI models can reason about goals and demonstrations. A harness can provide standard tools for vision, grasping, planning, control, testing and recovery. Robot manufacturers can concentrate on producing reliable and affordable bodies.
China is developing hundreds of competing robot designs while general-purpose AI is making them easier to instruct. Progress may come from combining standardised physical systems with models and harnesses that can rapidly create, test and improve new behaviour.