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Traditional search engines have long relied on keyword matching, a method that often falls short when users express complex ideas, nuanced questions, or seek information based on conceptual similarity rather than exact word presence. As artificial intelligence models, particularly large language models (LLMs), become more sophisticated, the need for data retrieval that understands meaning rather than mere syntax has grown exponentially. This is where vector databases and semantic search come into play, offering a powerful paradigm shift in how we discover and interact with information.
How it Works
At its core, semantic search leverages the power of machine
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