ORCH lifts embodied-agent scores 63.97%

ORCH, a new framework for organizing embodied AI teams, improved final mission scores by 63.97% and execution efficiency by 74.29% on average across 25 wildfire-response missions versus four prior multi-agent approaches, according to the arXiv paper. Its result says task-specific roles and dependency-aware coordination can matter more than simply scaling the underlying model. That is a useful systems test for builders evaluating robots alongside Unitree’s warning that humanoid deployment still trails the market’s expectations: measure organization on your mission, not model size in isolation.