A world model is an AI system that learns a predictive representation of how an environment changes over time. It can use observations, actions, or language to estimate future states and possible outcomes before an agent acts. World models support planning in model-based reinforcement learning, robotics, embodied AI, autonomous driving, and interactive simulation. This site catalogs these systems with model records, research papers, benchmark context, and source links. Start with the world models database, compare systems on the leaderboard, or read the Performance Index methodology.
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The process of encoding raw video frames into a sequence of discrete or continuous tokens that a transformer can model. Video tokenizers (such as those released with NVIDIA Cosmos) are critical building blocks of foundation world models.
Video Tokenization is a glossary concept in the techniques layer of the world models knowledge base.
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| Attribute | Value |
|---|---|
| Term | Video Tokenization |
| Category | Techniques |
| Definition | The process of encoding raw video frames into a sequence of discrete or continuous tokens that a transformer can model. Video tokenizers (such as those released with NVIDIA Cosmos) are critical building blocks of foundation world models. |
| Related Models | 2 |
| Related Research | 1 |
| Model | Lab | Category |
|---|---|---|
| NVIDIA Cosmos | NVIDIA | Foundation World Model |
| IRIS | Microsoft Research | Model-Based RL |
| Topic | Summary |
|---|---|
| Foundation World Models | How foundation world models such as Cosmos and Genie 2 bring large-scale learned simulation to robotics, autonomous driving, and physical AI. |
| Term | Category | Definition |
|---|---|---|
| Latent Space | Architecture | A compressed, abstract representation of data learned by a neural network. In world models, the latent space encodes environment states in a compact form that captures essential dynamics while discarding irrelevant details. Models like DreamerV3 and PlaNet operate entirely in latent space for efficient planning. |
| Foundation Model | Paradigms | A large-scale model trained on broad data that can be adapted to many downstream tasks. Foundation world models (like NVIDIA Cosmos and Genie 2) learn general-purpose representations of world dynamics, analogous to how GPT models serve as foundations for language tasks. |
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Published by world-models.io editorial board.
Lead editor Bernard Grenat.
This glossary page publishes stable definitions linked to related models, research topics, and primary-source context.
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