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34:35
YouTube
James Briggs
HNSW for Vector Search Explained and Implemented with Faiss (Python)
Hierarchical Navigable Small World (HNSW) graphs are among the top-performing indexes for vector similarity search. HNSW is a hugely popular technology that time and time again produces state-of-the-art performance with super-fast search speeds and flawless recall - HNSW is not to be missed. Despite being a popular and robust algorithm for ...
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The last One Most Annoying Fs😭 #funny #relatable #work #customer
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AI TECH SIMPLIFIED on Instagram: "What is FAISS? FAISS (Facebook AI Similarity Search) is a vectorDB that helps you quickly find “which vectors are most similar to this one?” even when you have millions or billions of vectors. Q.) Why do we even need a vector database? A.) In modern AI (LLMs, vision models): Text → converted to embeddings Images → converted to embeddings Audio → converted to embeddings A vector database lets you: Store embeddings Search nearest neighbors using cosine / L2 distan
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