Nearest Neighbor Indexes for Similarity Search | Pinecone
Vector similarity search is a game-changer in the world of search. It allows us to efficiently search a huge range of media, from GIFs to articles — with incredible accuracy in sub-second timescales for billion+ size datasets.
Nearest Neighbor Indexes for Similarity Search Jump to section Indexes in Search Flat And Accurate Locality Sensitive Hashing Hierarchical Navigable Small World Graphs Inverted File Index Vector similarity search is a game-changer in the world of search. It allows us to efficiently search a huge range of media, from GIFs to articles — with incredible accuracy in sub-second timescales for billion+ size datasets. One of the key components to efficient search is flexibility. And for that we have a wide range of search indexes available to us — there is no ‘one-size-fits-all’ in similarity search.
related reading
- Faiss: A library for efficient similarity search - Engineering at Metaengineering.fb.com
- Hierarchical Navigable Small Worlds (HNSW) | Pineconepinecone.io
- The vector database to build knowledgeable AI | Pineconepinecone.io
- GitHub - facebookresearch/faiss: A library for efficient similarity search and clustering of dense vectors.github.com
- Announcing ScaNN: Efficient Vector Similarity Searchai.googleblog.com
- Not All Vector Databases Are Made Equal | Towards Data Sciencetowardsdatascience.com
- Introduction to Facebook AI Similarity Search (Faiss) | Pineconepinecone.io
- Hierarchical Navigable Small Worlds (HNSW) | Pineconepinecone.io
- FAISS Python API for fast and efficient similarity searchlearnpainless.com
- turbopufferturbopuffer.com
- Welcome to Faiss Documentation - Faiss documentationfaiss.ai
- Voyage AI | Homevoyageai.com