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This article is part of our coverage of the latest in AI research.

Diffusion models are best known for their impressive capabilities to generate highly detailed images. They are the main architecture used in popular text-to-image models such as DALL-E, Stable Diffusion, and Midjourney.

However, diffusion models can be used for more than just generating images. A new paper by researchers at Meta, Princeton University, and University of Texas, Austin, shows that diffusion models can help create better reinforcement learning systems.