PhysBrain 1.5: From Vision-Language Models to Physical Foundation Models
We present PhysBrain 1.5, a unified model for understanding physical environments, generating actions, and predicting future states. Motivated by the physical loop of observation, interaction, and environmental change, we bring these capabilities into a common learning framework. Starting from a general vision--language model, we encode language responses, end-effector motion,
Reading in Plain English mode — toggle below to switch
We present PhysBrain 1.5, a unified model for understanding physical environments, generating actions, and predicting future states. Motivated by the physical loop of observation, interaction, and environmental change, we bring these capabilities into a common learning framework. Starting from a general vision--language model, we encode language responses, end-effector motion,
This model represents a significant step towards unified physical foundation models, integrating observation, interaction, and prediction. For ML engineers, understanding such models is crucial for developing autonomous agents and robots that can operate effectively in real-world physical environments.