Foundation Models

Embodied AI

Embodied AI is the study of intelligent agents that perceive and act within a physical or physically simulated environment through a body, in contrast to disembodied systems that process static datasets. The field spans robotics and simulated benchmarks, navigation, rearrangement, and embodied question answering in platforms such as AI Habitat, and is grounded in the thesis that intelligence develops through sensorimotor interaction with the world.

Why it matters for physical AI

The embodied framing drives the research agenda behind robot foundation models: internet-scale knowledge must be grounded in perception and action loops before it produces competent physical behavior.