Visualizers
Learn by moving things
Interactive explainers for the ideas behind retrieval, embeddings, and agents. A formula tells you what is true; dragging a vector shows you why. Each one also appears inside the article it belongs to, and runs entirely in your browser, so drag, poke, and break it.
k-nearest-neighbor search
From: Vector Search (kNN) →Documents become points; the query is one more point. Drag it, pick k, and toggle euclidean vs cosine to watch the nearest neighbors change, and to see the two metrics disagree.
Press Step or Run to scan the points one at a time.
HNSW graph search
From: ANN at Scale: HNSW →How approximate nearest neighbor actually runs. Drag the query and step the greedy walk from the entry node through a navigable graph; it visits a handful of nodes instead of all of them, and sometimes settles on a near-miss.
Database search: scan vs graph
From: ANN at Scale: HNSW →A tiny food database queried with real phrases. Answer the same query two ways over the same data, scan every row (kNN) or follow the graph (HNSW), and watch the difference in what gets touched.