Diffusion Model

A diffusion model is the most common architecture behind image-generating AI. The way it works is unusual: you take a clean image, pile on so much noise that it becomes pure static, and train a model to reverse that process. By repeating the lesson "remove a little noise from a corrupted image and you get back the original" countless times, the model learns to do this reliably. In actual use, it starts from pure random noise and generates an image from scratch.

Midjourney, DALL-E, and Stable Diffusion all have different names, but the core engine underneath is diffusion. This is the technical foundation of the boom in "type a prompt, get an image" AI tools.

More recently, diffusion techniques have expanded beyond images into video (Sora), music, and 3D models. When you see "diffusion-based model" in the news, just understand it as an architecture that generates content by removing noise step by step.

"The new diffusion model produces more realistic results than existing image-generation AI" — this means the noise-removal process has been improved, boosting image quality.