Autoregressive generative models predict and emit one token or pixel at a time from left to right, whereas diffusion models generate through iterative coarse-to-fine denoising.

“the ways of building generative models, there is autoregressive, where you kind of like have a model that predicts the next token or the next pixel,”

“and then you generate left to right one token at a time, and then there's diffusion, which is a coarse-to-fine generation,”

“kind of like iterative denoising kind of generation,”