A Steerable Model with Emergent Capabilities

Introduced π0.7, a steerable general-purpose robotic foundation model that demonstrates compositional generalization. This model can perform a wide range of dexterous tasks with specialist-level performance without fine-tuning, and can solve novel tasks by recombining learned skills. Generalization is achieved through training with diverse multimodal prompts (language, metadata, control modalities, visual subgoals) that specify task execution details, enabling the integration of broader and more diverse datasets.