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Free interactive course on world models in AI. Nine visual chapters on prediction, latent dynamics, planning, JEPA, video models, and failure modes.

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World Models 101

A free, interactive course on how machines learn to predict, simulate, and plan.

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The World Models 101 course homepage

The phrase "world model" now describes at least five different classes of system, and the people using it rarely specify which. World Models 101 sorts that out first, then teaches the machinery.

Nine chapters. About two hours. No signup. Every chapter has an interactive and a printable PDF.

What people mean by world model

Definition Predicts Examples
Renderer Pixels Genie 3, Sora, GameNGen
Simulator Geometry and physics Marble, NVIDIA Cosmos*
Controller Compact state Dreamer, PlaNet, Ha and Schmidhuber
Representation Embeddings V-JEPA 2, I-JEPA
Implicit model Nothing; researchers find it rather than run it Othello-GPT

* Cosmos straddles Renderer and Simulator. That ambiguity is the point. Before asking whether something is a world model, ask what it predicts and what you can do with the why-prediction-is-learning.

The course

Chapter The thing you can poke
01 What Is a World Model? A map of five definitions and the question that separates them
02 How Do World Models Work? A planner that gets worse as it searches harder inside a flawed model
03 Why Is Prediction the Same as Learning? Possible futures collapsing as new evidence arrives
04 What Is Latent Space? A two-number space that decodes into a room
05 What Is a Dynamics Model? One model run with corrections, then left to consume its own output
06 Can an AI Learn Inside Its Own World Model? The point where cheaper imagined experience becomes worse experience
07 What Is JEPA, and Why Not Predict Pixels? Two possible futures and the impossible blur that scores above both
08 Are Video Models World Simulators? One starting frame and three futures selected by an action
09 What Is Still Broken in World Models? A thousand-step rollout showing which properties fail first

The chapters are ordered for learning rather than history. Each one states which definition of world model is in use, cites the underlying papers, and ends with a short quiz. You can read the whole course online or download any chapter as a PDF from its page.

Run it locally

pnpm install
pnpm dev

The production checks are:

pnpm lint
pnpm build

Print and PDF

Every chapter has a print layout. Interactive controls disappear, quizzes become static questions with an answer key, and unrevealed sections remain visible.

pnpm dev                         # in another shell
pnpm pdf what-is-a-world-model 1

The command writes to public/pdf/. A chapter page links its PDF automatically when the corresponding file exists.

Design rules

Colour carries meaning. Vermilion marks what a model imagined. Slate marks what happened. Neither colour is available for decoration.

Contrast is a contract. Every text token clears WCAG AA on the background where it appears. Muted text must also stay visibly separate from body text, or the reading hierarchy collapses. The contrast notes live at the top of src/app/globals.css.

State never depends on dimmed text. Lowering text opacity can break contrast. Active states add emphasis instead.

Sources and corrections

Videos come from the lab that built the system or a researcher who authored the work. Every YouTube ID is checked against the oEmbed endpoint before it ships. Claims that cannot be independently verified are attributed rather than stated as fact.

Technical corrections, translation fixes, and broken demos are worth reporting. Open an issue. Corrections are credited.

License and attribution

The application code and course material in this repository are licensed under CC BY-SA 4.0. Reuse must credit Nilushanan Kulasingham and World Models 101, identify changes, and keep adaptations under the same license.

About

Free interactive course on world models in AI. Nine visual chapters on prediction, latent dynamics, planning, JEPA, video models, and failure modes.

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