Explorable AI.
Type a sentence below and watch it move through a language model, one stage at a time: it splits into tokens, each token becomes a vector, the vectors weigh each other up (attention), and the model picks what comes next. It recomputes as you type, and you can hover a token to follow it through every stage.
The tokens and embeddings above are real: the GPT-4o tokenizer, and a small embedding model, both running in your browser. The next-word step is a stand-in, real prediction needs a full model (that is what the assistant in the corner runs).
Every explainer here works the same way: a short explanation next to something you can change. Five of them build on each other, in the order a sentence moves through a model:
- The atoms of a model, watch your words split into tokens.
- Embeddings, explained, where meaning becomes distance on a map.
- How a transformer thinks, click a word and see attention light up.
- Temperature and the next word, change how random the model’s choices are.
- Watch a model learn, roll a ball downhill, which is roughly what training is.
For the whole thing at once, see the whole model on one screen, or teach a neuron by drawing your own data.
There are also two browser tools: a token and cost calculator that counts any prompt with each model’s real tokenizer and estimates the cost, and a tokenizer comparison.
You can also search these notes by meaning: type a question and an embedding model in your browser finds the closest ones (a small RAG demo).
The concept notes are a small linked encyclopedia of AI terms. The graph at the top links notes that reference each other; the map below instead places every note by what it is about, reduced to two dimensions. Hover a dot for its nearest neighbours, click to open it.
And my GitHub commits over the last year, pulled in live:
- Recandle