Circuit training: How China is teaching humanoid robots to do useful things
China has made humanoid robotics a national economic priority and is investing heavily in building the physical-world data needed to train these machines. That training currently depends on large amounts of repetitive human labor to generate the motion and environment data robots need to function usefully.
Why this matters: The part worth watching here is not the robots. It is the labor pipeline behind them. Someone has to do thousands of hours of physical demonstrations so a robot can learn to pick up a box or open a door. That is a new category of data work, mostly invisible, and it raises the same questions as other data labor: who does it, what are they paid, and who owns what they produce. China treating this as an economic priority also means the race to build capable humanoid robots is no longer theoretical. The physical AI layer is being built now, and the data decisions made early tend to be very hard to undo.
Who should care: General readers · AI governance · Policy
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