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Robots do not operate in the clean conditions their models are trained on. A cup can be wet, heavier than expected, or partly hidden, and suddenly the learned response is no longer enough. The harder problem in robotics is making a machine adapt when reality differs from what it has seen before.

Humanoid robots can walk, grasp and perform impressive demos, but real-world reliability remains low. The industry faces bottlenecks in physical AI, data, generality, hardware, economics and manufacturing. The challenge is no longer building humanoids, but making them reliably useful at scale.