Diffusion: AI Mental Model #7

======================================================= 📓 Free visual lecture notes for this episode: https://vizuaraai.github.io/great-mental-models-of-ai/lecture-07-reverse-the-corruption.html ======================================================= To create something, first learn how to destroy it. This is Lecture 7 of The Great Mental Models of Artificial Intelligence. In this episode, we explore Reverse the Corruption: the idea behind diffusion models, where generation is learned by slowly corrupting real data into noise, then training a model to reverse that corruption one tiny step at a time. In this lecture, we look at: (1) Why diffusion begins by destroying data (2) The forward process: adding noise step by step (3) The reverse process: learning to undo one tiny corruption (4) How images emerge from pure noise (5) Why diffusion works by chaining many easy steps (6) How Stable Diffusion, Midjourney, DALL·E, and Imagen use denoising (7) How diffusion can be applied to language (8) Why diffusion language models can generate tokens in parallel (9) How the same trick appears in video, audio, and molecule generation (10) Why creation can be understood as destruction played backward The core idea is simple: When creation is too hard to do in one shot, define a gradual corruption process and learn to reverse it. #ArtificialIntelligence #MachineLearning #DeepLearning #DiffusionModels #StableDiffusion #GenerativeAI #Denoising #LLM #Vizuara