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Unlock the power of vector search. Our guides will help you conquer vector embeddings and build better AI applications.

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During a search, HNSW starts at the topmost layer and makes 'big jumps' across the graph to quickly move closer to the target region. As it moves down the layers, the search becomes more refined, with smaller, more local jumps until the nearest neighbors are identified in the bottom layer.

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