Diffusion Model

A generative model that learns to create data by reversing a gradual noising process. During training, noise is progressively added to real data; the model learns to denoise step by step. At generation time, it starts from pure noise and iteratively refines it into a coherent output. Diffusion models are currently the leading approach for high-quality image and audio generation, and underpin systems like Stable Diffusion and DALL-E.
See also: diffusion, denoising, generative AI.