PRIVATE COURSE · 7 CHAPTERS · SOURCE-GROUNDED

Build a mind that can rehearse the future.

A detailed course on world models: latent dynamics, explicit and implicit architectures, planning, physical AI, VLAs, and the research gap between plausible prediction and robust agency.

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I · Foundations

Define the predictive loop and the latent state that carries it.

01 · Predict before you actBuild the central mental model: an agent uses learned dynamics to test futures before spending real-world interaction.02 · Inside a latent world modelUnderstand the encoder, memory, dynamics, decoder, uncertainty, and the two clocks of training and imagination.

II · Model families

Compare explicit simulation with implicit predictive representation.

03 · Explicit world modelsCompare the Ha–Schmidhuber system, Dreamer, and MuZero as three ways to expose dynamics for control.04 · Implicit world modelsUnderstand predictive representations, generative video models, JEPA, and the limits of calling any large model a world model.

III · Acting in the world

Turn predictions into plans, robot actions, and physical feedback.

05 · Planning with imaginationTurn predictions into decisions using rollout evaluation, actor–critic learning, tree search, and receding horizons.06 · Physical AI and VLAsConnect world models to robots, autonomous driving, and vision-language-action systems operating under latency, safety, and embodiment constraints.

IV · Research frontier

Evaluate capability and mark the unsolved hierarchy and goal gaps.

07 · Frontiers, evaluation, and the AGI gapSynthesize the field, design an evaluation matrix, and separate promising directions from unsupported claims.