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Category: Technical Terms
Category: Technical Terms
Diffusion models create images by learning to remove noise from random static.
Start with pure noise. The model learns to gradually clean it up until it becomes a real image. It's like developing a photo in reverse - starting with static and ending with a clear picture.
Training shows the model millions of images with different amounts of noise added. It learns what each step of cleanup should look like.
Diffusion models power most AI image generators. DALL-E, Midjourney, and Stable Diffusion all use this approach because it creates high-quality, diverse images.
They work better than older methods because the step-by-step process gives more control over the final result.
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