- Doug Turnbull. Vector Search for the Uninitiated. 2/2023.
- Provides a brief overview of how traditional search works and how vector search differs as well as the relative strengths and weaknesses of each.
- Greg Kogan. Introduction to Vector Search for Developers.
- A high-level overview of vector search with a slight emphasis on Pinecone's product. Touches on traditional search, vector embeddings, semantic similarity, etc.
- Doug Turnbull. Vector Search: The Hard Way. 9/2023.
- 75 slides on the challenges of Vector Search.
- Dmitry Kan. Keynote: Where Vector Search is taking us. Haystack Conference, 9/2022.
- Slide deck and video presentation on the state of Vector Search and it's future.
- Ethan Steininger. Vector Search. 6/2023.
- A GitHub repo with a collection of articles and links relating to Vector Search.
- Panda Smith. Build a search engine, not a vector DB. Elicit, 12/2023.
- Guidance on using a solid search engine as the foundation for vector search.
- James Briggs. The Missing WHERE Clause in Vector Search. Pinecone.
- Discusses the difficult challenge of filtering results in vector search, explains the pre/post filtering techniques and Pinecone's single stage filtering.
- Gibbs Cullen has an additional post on Pinecone's implementation titled, Introducing the hybrid index to enable keyword-aware semantic search. Pinecone, 10/2022.
- Roie Schwaber-Cohen. Vector Embeddings for Developers: The Basics. Pinecone.
- Solid article for beginners looking for high-level overview. Touches on vectors, vector embeddings, embedding models, word2vec, and semantic similarity.
- Documentation: Vector Search Indexes
- Utilizes Apache Lucene, which uses HSNW Graph and k-ANN for querying.