Why AI Images Start as Noise

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Издатель Oct 12, 2026

# Why AI Images Start as Noise

Many diffusion-based image generators begin with random noise. During training, the model learns to predict added noise. During generation, text conditioning guides repeated denoising updates. In systems such as Stable Diffusion, these updates happen in an abstract latent representation; a decoder produces the final pixels.

Different starting seeds can produce different results from the same prompt. Learned patterns can also produce strange details.

All apple, noise, training and denoising graphics are original simplified teaching illustrations. The intermediate images are pedagogical blends, not captured model inference. This explanation does not apply to every image generator or guarantee freedom from memorization.

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#AI #Diffusion #StableDiffusion #HowAIWorks #Kernlab

## Sources
- [Denoising Diffusion Probabilistic Models](https://arxiv.org/abs/2006.11239)
- [High-Resolution Image Synthesis with Latent Diffusion Models](https://arxiv.org/abs/2112.10752)
- [Official Diffusers pipeline walkthrough](https://huggingface.co/docs/diffusers/using-diffusers/write_own_pipeline)

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