AI Image Generation Explained : AI Foundations

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Издатель
Around eighty million AI images are generated every day, and almost nobody using these tools can explain what happens between typing a prompt and getting a picture. This episode breaks down the whole process in plain language: what an image looks like to a computer, why image models work completely differently from language models, and why the entire technique is better understood as removal than as drawing.

We cover the diffusion process from the ground up, how a text encoder like CLIP turns your words into coordinates that steer the image, why Stable Diffusion made all of this cheap enough to run at scale, and why the same prompt keeps giving you different results. If you use these tools every week and have never understood what is happening underneath, this one is for you.

0:00 What An Image Looks Like To A Computer
0:34 Why Image Models Differ From Language Models
0:57 The Noise Process
1:18 How The Model Learns To Clean
2:12 How Your Prompt Steers The Image
2:50 Stable Diffusion And Seeds
3:42 Visual Tokens, Inpainting, Outpainting

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