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A generative model that learns to produce data by reversing a gradual noising process. In world models, diffusion-based architectures (used in NVIDIA Cosmos and UniSim) generate high-fidelity video frames representing possible future states of the environment.
Diffusion Model is a glossary concept in the architecture layer of the world models knowledge base.
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| Attribute | Value |
|---|---|
| Term | Diffusion Model |
| Category | Architecture |
| Definition | A generative model that learns to produce data by reversing a gradual noising process. In world models, diffusion-based architectures (used in NVIDIA Cosmos and UniSim) generate high-fidelity video frames representing possible future states of the environment. |
| Related Models | 2 |
| Related Research | 1 |
| Model | Lab | Category |
|---|---|---|
| NVIDIA Cosmos | NVIDIA | Foundation World Model |
| UniSim | Google DeepMind | Generative World Model |
| 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 |
|---|---|---|
| Autoregressive Model | Architecture | A model that generates outputs one element at a time, where each output depends on previous elements. IRIS treats world modeling as autoregressive token prediction, bridging language modeling and world modeling techniques. |
| 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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