Concept· 3 min
How does diffusion work?
Diffusion models learn to reverse noise: train by destroying an image, then generate by denoising from pure noise.
Key idea
Forward process adds Gaussian noise step by step. The model learns the reverse: predict the noise, subtract it, repeat.
Example
Stable Diffusion starts from random noise conditioned on your prompt and denoises for ~20-50 steps into a coherent image.
What to remember
- Powers image, video and even audio generation
- Latent diffusion works in a compressed space for speed
- Guidance (CFG) balances prompt fidelity vs diversity