Delta-0: Why Humanoid Foundation Models Need Correctable Control
What makes a humanoid foundation model useful when its first attempt goes wrong? This episode examines how Delta-0 connects whole-body control, human-motion pretraining, and corrective learning—and what its experiments establish. We cover three questions: how its latent world-action model connects observations with motion commands; why relative end-effector corrections make human intervention easier; and what to make of the reported dishwasher success increase from 20% to 65% after targeted post-training. ([deltai.com](https://deltai.com/en/blog/delta-0)) The system runs on a Unitree G1 with…
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