Vector Search and Databases at Scale / Ashot Vardanian

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  • Опубліковано 14 бер 2024
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    Vector Search databases appear on every corner. Most have already heard about Pinecone, Weaviate, Qdrant, and the Open-Source libraries that precede them ― Facebook's FAISS and Google's SCANN. We will look into the algorithms for approximate nearest neighbors search, profile them, and highlight the bottlenecks that stop most of them from scaling beyond a billion entries. This will help you navigate the increasingly complex space of vector and semantic search products, choose the optimal configuration parameters for indexing, the right neural network to produce embeddings, and the appropriate hardware for the task.

КОМЕНТАРІ • 1

  • @linz4213
    @linz4213 2 місяці тому +1

    Ash the ninja