Blog
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The recall-latency curve
Every index parameter moves you along one curve with diminishing returns. How to measure recall honestly, and why distance concentration sets its ceiling.
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How cluster indexes search
Partition the space in advance, then only search the partitions near your query. Why boundary effects cost recall and what probing more of them buys.
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Quantization: trading memory for recall
Scalar, product and binary quantization compress vectors by discarding precision. What each one throws away, and why reranking recovers most of it.
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How graph indexes search
Greedy traversal over a proximity graph, why it gets stuck in local minima, and how layers and connectivity fix it — the mechanism behind HNSW.
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Distance metrics and when each is right
Cosine, dot product and Euclidean measure different things — except when they don't. What each compares, and why normalization collapses all three.