Foundation Models

World Model

A world model is a learned model of environment dynamics that predicts future observations or latent states conditioned on actions, enabling an agent to plan or train policies in imagination rather than solely through real interaction. Ha and Schmidhuber's 2018 work named the paradigm, the Dreamer line trains policies inside recurrent latent dynamics models, and large video-generation models are now positioned as general-purpose world simulators.

Why it matters for physical AI

Real robot interaction is slow and costly, so learning inside a predictive model is a leading route to sample-efficient physical skill acquisition and to policies that anticipate consequences before acting.