AI engineering glossary · Generative media multimodal
What is reverse diffusion process?
Reverse diffusion process: The learned half of a diffusion model that starts from pure noise and removes noise step by step to recover a clean sample. A neural network predicts the noise (or the clean data) at each step, and repeating this many times turns random static into a coherent output.
Reverse diffusion process: an example
To generate one image, the network is called 25 to 50 times, each call slightly sharpening the picture from noise toward a plausible photograph.
Related terms
More Generative media multimodal terms
- RNN-Transducer
- Sample rate
- Score distillation sampling
- Score-based generative model
- Short-time Fourier transform
- SigLIP
- Speaker diarisation
- Speaker embedding
Where you learn it
Reverse diffusion process is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.