Diffusion Model
The architecture behind most AI image and video generation: start from noise, remove it step by step.
A diffusion model is trained to reverse a noising process. Given pure static and a text prompt, it iteratively denoises until an image emerges that matches the prompt. It replaced GANs as the default because it trains more stably and scales better.
In practice: Fifty denoising steps between random static and a finished illustration.
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