AI engineering glossary · Generative media multimodal
What is forward diffusion process?
Forward diffusion process: The fixed, non-learned half of a diffusion model in which small amounts of Gaussian noise are added to a clean sample over many steps until only random noise remains. Because it is defined in closed form, any noisy step can be produced directly from the original, which makes training efficient.
Forward diffusion process: an example
An image is corrupted over T = 1000 steps; by step 1000 it is indistinguishable from random static, and the network is trained on randomly chosen intermediate steps.
Related terms
More Generative media multimodal terms
- Fréchet Inception Distance
- Generative adversarial network
- Grapheme-to-phoneme
- Guidance scale
- Image captioning
- Image tokenizer
- Image-to-image translation
- Inception Score
Where you learn it
Forward 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.