Chinese-first · Diagram-first · Static deployment

Interactive Illustrated AI History

Explore the evolution of AI from rules and statistical learning to deep learning, large models, RAG, and agents through clickable, step-by-step teaching demos.

Start with the overview View chapter list

Recommended learning path

First edition spine: one overview, eight interactive demos, and one system bridge chapter

About 5 minutes · Read the main thread

Use MDX to connect the evolution from rules and statistical learning to deep learning, RAG, and agents.

Demo 01Search Trees / A*

Switch among BFS, DFS, and A* to see how search strategies affect the frontier.

Demo 02Expert System Rule Reasoning

Select conditions and add exceptions to see how if-then rules produce conflicts.

Demo 03Bayesian Updating

Adjust the prior and evidence strength to see how evidence updates belief.

Demo 04Decision Boundaries

Compare linear, nonlinear, and overfit boundaries to understand data-driven learning.

Demo 05CNN Kernels

Choose a kernel and advance the window to see how a feature map is produced.

Demo 06Attention Map

Select a token and compare direct Attention connections with RNN chain propagation.

Chapter 07LLM System Map

Understand why context, retrieval, tools, memory, and evaluation surround large models.

Demo 08RAG Pipeline

Follow a question through embedding, retrieval, reranking, prompting, the LLM, and a cited answer.

Demo 09Agent Loop

Run the loop of planning, tool calls, observation, revision, and a final answer.

Overview Artifacts

Organize the project with a timeline, lineage map, and diagram source guide

TimelineAI Evolution Timeline

Connect search, rules, statistical learning, deep learning, Transformer, RAG, and agents across eras.

LineageAI Technical Lineage

See how symbolic AI, statistical learning, neural networks, foundation models, and agents relate by paradigm.

GuideDiagram Sources And Exports

Learn the SVG naming, screenshot-state, and source workflow conventions for contributors.