Diffusion Model
A type of generative AI that creates images by gradually removing noise from a random starting point, guided by learned patterns.
Diffusion models work by learning to reverse a noising process. During training, clean images are progressively corrupted with noise, and the model learns to reverse each step. During generation, the model starts from pure noise and iteratively denoises it into a coherent image. This architecture powers many modern AI image generation and editing tools.