Purpose

This collection keeps factual notes about artificial intelligence: histories of model families, the problems that shaped them, and the design choices that made them practical. The aim is a stable reference for orientation, not opinion pieces or predictions.

Current Reading Path

  1. From Noise to Images: A Short History of Diffusion Models

Planned Areas

  • Representation learning and embeddings
  • Sequence modeling and attention
  • Generative models
  • Reinforcement learning foundations

Status

From Noise to Images is the first complete bilingual note here. New pages should be added in English and Chinese together.