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The map of AI.

Every concept on Artifipedia, and every link between them. Drag a node, hover to trace its connections, click to read.

Deep LearningLanguage & LLMsAI AgentsGenerative AIMachine LearningComputer VisionSafety & EthicsFoundationsTools & EcosystemSpeech & AudioApplied AIdrag · hover · click to open
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How to read this map

Each circle is a concept. Each line means the two are genuinely related — one explains the other, one is built from the other, or you cannot understand the first without the second. Circle size is the number of connections. Colour is the field.

The map has 312 concepts and 1355 links, an average of 8.7 connections each. Density is 2.8% — most possible pairs are not linked, which is the point. A map where everything connects to everything tells you nothing.

What the shape tells you

Large Language Model (LLM) is the most connected concept, with 56 links. That is not an editorial choice — it falls out of the graph. The five most connected are Large Language Model (LLM) (56), Embeddings (35), Neural Network (32), Overfitting (32), Benchmark (31). If you are starting from nothing, start there: they are the concepts other concepts need.

620 of the 1355 links cross between fields. Those are the interesting ones. A field that only connects to itself is a silo; the concepts holding this map together are Embeddings, Large Language Model (LLM), Benchmark, Neural Network. They are why you cannot learn AI one topic at a time.

The periphery is real, not an oversight. Hierarchical Clustering, GRU, Question Answering sit near the edge with few connections. That reflects the field: some ideas are self-contained and you can learn them without much else. A map that pretended otherwise would be flattering, not accurate.

Honestly: by hand, per concept. Each entry declares what it connects to, and the graph is assembled from those declarations. That has a known consequence — the links are locally sensible and globally uneven. A foundational concept written early may have fewer links than a newer one written with more of the map in view.

They are not generated from text similarity, co-occurrence, or a model. That would produce a denser, smoother graph and a less honest one, because it would link things that merely appear together rather than things that explain each other.

If a link looks wrong to you, it might be. Tell us — corrections get made.

Using this map

It is free to embed on any site — the button above gives you an iframe. It stays current as concepts are added. The underlying data is open too: content.json has every concept and every relation in it.

Every concept below, grouped by field. The map is the index; these are the entries.

Where to go from here

The map shows the shape. These take you through it.