Understanding FAISS for Efficient Similarity Search of Dense Vectors

Learn about FAISS (Facebook AI Similarity Search) library in this 26-minute tutorial that demonstrates efficient similarity search and clustering techniques for dense vectors. Explore two primary approaches - IndexFlatL2 for exact L2 matching and IndexIVF (Inverted file) for clustered similarity search. Discover how these methods optimize searching through millions or billions of high-dimensional vectors, with particular emphasis on performance improvements for large datasets. Examine practical implementations with Python code examples, understanding when to use IndexFlatL2 for smaller datasets versus IndexIVF's clustering approach for larger-scale applications. Master the fundamentals of vector similarity search while referencing academic papers that detail the underlying algorithms and recent developments in the field.