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Unlocking Semantic Search with Vector Embeddings

How Machines Understand Meaning — And How You Can Use It for Smarter Search 1. Introduction: Why Do We Need Embeddings? Traditional search engines rely on keyword matching. If your search query includes the words “best pizza,” it looks for documents with those exact words. But what if a document talks about “top-rated Italian food” Continue reading
