Concept

Diffusion Model

A diffusion model is a type of generative artificial‑intelligence system that learns how to reverse a gradual process of adding random noise to data. During training the model watches many examples being corrupted step by step, and it builds an internal recipe for undoing each tiny corruption so that starting from pure randomness it can gradually reconstruct realistic images, sound, or other kinds of signals.

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The AI That Reasons in Private Can Be Taught to Show Its Work
"Diffusion reasoning models threatened to take the page away. Instead of producing discrete words in sequence, they refine a dense vector of numbers across repeated denoising steps…"