Visual AI Explainer

Every concept, animated and interactive — from a single neuron to how frontier LLMs serve tokens.

The journey: each stop builds on the previous one. Click a node to jump to its page.

1 · foundations

Perceptron

The original artificial neuron (1958). Drag data points and watch it learn a decision boundary in real time.

 2 · foundations

Activation Functions

Sigmoid, ReLU, GELU, SiLU… why networks need non-linearity, with live plots you can probe.

 3 · networks

Multi-Layer Perceptron

Stack neurons into layers. Train a real network in your browser on 2D datasets and watch the boundary bend.

 4 · transformers

Self-Attention

Queries, Keys, Values — the mechanism that lets every token look at every other token. Fully animated.

 5 · transformers

Transformer Block

FFN, LayerNorm, residual connections, multi-head attention — click each part of the architecture to explore it.

 6 · frontier

LLM Inference

Prefill vs decode, the KV cache, sampling — how a trained model actually generates text, step by animated step.

 reference

Glossary

Searchable index of AI terminology, each term linked to the page where you can see it in action.