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The five foundations, in order

Artifipedia explains every idea in AI at the depth you choose, from plain English to the research frontier. If you are just beginning, start with these five. Each builds on the last, and together they explain almost everything else on this site.

1. What is artificial intelligence? The big picture: what "AI" actually means, why the definition keeps shifting, and what these systems can and cannot do. The map before the territory.

2. What is machine learning? The core idea under all modern AI: instead of programming rules by hand, we let systems learn patterns from data. This is the shift that made everything else possible.

3. What is deep learning? The engine of the current era. Deep neural networks learn their own layered representations of data, which is why they handle messy things like images and language that older methods could not.

4. What is a large language model? The technology behind ChatGPT, Claude, and Gemini. One deceptively simple idea, predict the next word, scaled up until it becomes broad competence.

5. What is generative AI? How AI creates new things, text, images, video, code, by learning the shape of data and sampling from it. The unifying idea behind the whole creative wave.

Read those five and you will understand the shape of modern AI. Everything else here is a deeper look at one part of this picture.

Where to go next

Once the foundations click, follow your curiosity:

• How large language models actually work — from your prompt to the answer, step by step.
• What are embeddings? — how AI turns meaning into numbers, the idea behind search and memory.
• How RAG works — giving a model access to knowledge it was never trained on.
• How AI agents work — models that take actions, not just answer.
• AI alignment and safety — making these systems do what we actually intend.

Or work backwards from what you want

If you already know what you are trying to understand, the learning path is the faster route. Name the concept, and it returns everything you need first, in order, computed from the prerequisite graph rather than from an opinion about curriculum. Mark off what you already know and it drops out.

How to use this site

Every concept page has five depths, from "Curious" in plain English to "Frontier" at the edge of research. Read at the level that fits, and go deeper when you want. Other ways in:

• Browse the concept map — see how the ideas connect.
• The glossary — every term you might meet, defined in a line.
• The blog — long-form explainers on how things actually work.

No account, no ads, no tracking beyond basic analytics. Just a place to understand AI, at your depth.