Learn AI / Concept Map
Concept map
Start with the sixteen categories. Open one to see its core terms, then select a term to see what it depends on and what it leads to. Everything on the diagram is also in the list below it, so nothing here requires seeing a picture.
Select a category on the map, or use the list below.
The same map as a list
Every category, its core terms, and for each term what it needs first and what it connects to. Expandable, keyboard-navigable, and identical in content to the diagram.
AI Foundations: 21 terms
The words people use before they use any of the others. What counts as artificial intelligence, what a model is, and why nobody agrees on the boundary.
How Machines Learn: 18 terms
Learning from examples instead of following written rules: what goes in, what changes inside, and what comes out.
Neural Networks: 12 terms
The layered arrangement of simple numerical steps that most modern AI is built from.
How Models Improve: 16 terms
The machinery of getting less wrong: measuring error, working out which settings caused it, and nudging them.
Model Quality and Evaluation: 21 terms
How anyone can tell whether a system actually works, and the many ways a good-looking score can mislead.
Large Language Models: 26 terms
The systems behind chat assistants: how they read text, how they produce it, and what they cannot do.
Transformers and Attention: 11 terms
The architecture that made modern language models possible, explained without the mathematics.
Search, Embeddings and RAG: 14 terms
Finding the right passage by meaning rather than by matching words, and handing it to a model so the answer has a source.
Training and Model Adaptation: 17 terms
The stages between a raw model and a usable one, and the several different things people mean by "training it on our data".
AI Agents and Automation: 20 terms
Systems that do not just answer but act: calling tools, taking steps, and needing supervision.
Generative Media: 13 terms
Producing images, audio, video and code, and the authenticity problems that follow.
Computer Vision and Language Technology: 19 terms
Reading pictures and reading prose: the task-shaped words that predate the chatbot era and still describe most deployed systems.
Data and Infrastructure: 25 terms
What models are built from and what they run on, including the parts that cost money and the parts that go stale.
Responsible AI, Human Rights and Safety: 28 terms
Who is affected, who is accountable, and what has to stay a human decision.
AI Security: 14 terms
The ways AI systems are attacked, and why an attack on a language model rarely looks like hacking.
AI Governance and UN Terminology: 32 terms
The vocabulary of the rooms where AI rules get negotiated, and the UN machinery the timeline records.