The Robotics Bottleneck Isn't the Model — It's Failure Data
A detailed thread argues that the hardest part of training humanoid robots is collecting the expensive, messy data of things going wrong.
As frontier language models grab attention, the humanoid robotics field is grappling with a more stubborn constraint. A detailed thread argues that the real data problem for humanoid robots is that "data outside life is extremely expensive" — and that "failure data is the hardest part." Success is easy to demonstrate; the long tail of failure modes that a robot must learn to recover from is costly and slow to collect.
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