Machine Learning & Math
6 min read•Sep 11, 2026
Vector Embeddings Decoded: Cosine Similarity, HNSW, and High-Dimensional Spaces
Demystifying the linear algebra and indexing algorithms powering modern AI retrieval. Explore high-dimensional vector geometries, mathematical differences between Euclidean distance and Cosine similarity, and how Hierarchical Navigable Small World (HNSW) graphs achieve logarithmic search speed across millions of vectors in production.
RagAI Engineering Team
Principal Applied Mathematician