How AI Turns Noise Into a Picture #Shorts

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Издатель
How can a picture start as static? A 42-second visual guide to classic diffusion models: adding noise during training, predicting noise, generating through repeated updates, text guidance and compressed latent representations.

Original bicycle-and-rain illustrations and youthful English female narration. All noise blends, colored latent tiles and transitions are teaching sketches, not a recording of real model inference. Classic diffusion is one approach, not a description of every image generator. A convincing generated picture is not evidence that an event happened.

Sources:
Denoising Diffusion Probabilistic Models (2020):
https://hojonathanho.github.io/diffusion/
High-Resolution Image Synthesis With Latent Diffusion Models (2022):
https://openaccess.thecvf.com/content/CVPR2022/html/Rombach_High-Resolution_Image_Synthesis_With_Latent_Diffusion_Models_CVPR_2022_paper.html
https://ommer-lab.com/research/latent-diffusion-models/
Implementation explanation:
https://huggingface.co/blog/annotated-diffusion

#AI #Diffusion #GenerativeAI #MachineLearning #ScienceCorner #Shorts
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AI Картинки
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