[HN Gopher] Faiss: A library for efficient similarity search
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       Faiss: A library for efficient similarity search
        
       Author : tosh
       Score  : 42 points
       Date   : 2023-03-30 20:37 UTC (2 hours ago)
        
 (HTM) web link (github.com)
 (TXT) w3m dump (github.com)
        
       | lee101 wrote:
       | [dead]
        
       | mshachkov wrote:
       | There is a wip [0] on RAFT [1] integration to faiss as an
       | implementation of cuda gpu backed indices, although you can use
       | RAFT directly.
       | 
       | [0] https://github.com/facebookresearch/faiss/pull/2521 [1]
       | https://github.com/rapidsai/raft
        
       | fzliu wrote:
       | Faiss is a wonderful vector search library - in particular, the
       | ability to do hybrid indexes e.g. IVF-PQ, IVF-SQ is great. We
       | (https://milvus.io) use it as one of the indexing options (along
       | with Annoy, Nmslib, and DiskANN) to power our vector database.
        
         | mojoe wrote:
         | I've actually been looking at Milvus for storing embeddings,
         | why do y'all have options for both Pulsar and Kafka inside
         | Milvus? Seems like unnecessary choices for what we hoped would
         | just be a plug and play vector database
        
       | make3 wrote:
       | Huggingface Datasets also has an integrated interface to Faiss !
       | https://huggingface.co/docs/datasets/faiss_es
        
       | bobvanluijt wrote:
       | Faiss is awesome but note that it's an ANN library that might not
       | be suitable for all use cases; hence vector databases exist. Two
       | things that might be of interest: the main contributor of Faiss
       | on the Weaviate podcast: https://youtu.be/5o1YTp1IL5o and
       | Weaviate as vector DB itself: https://weaviate.io
        
       | ntonozzi wrote:
       | Check out https://github.com/erikbern/ann-benchmarks for some
       | benchmarks on some of the different ANN libraries out there. I'd
       | be interested in hearing other's experiences using these
       | libraries in production.
        
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       (page generated 2023-03-30 23:00 UTC)