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Neural Search

Neural search uses vector embeddings to match queries to results based on meaning, not just matching keywords. It’s what powers modern search inside AI systems and the semantic search on many enterprise platforms.

Neural search is why keyword stuffing stopped working: the algorithm doesn’t look at words anymore, it looks at concepts. Content that expresses ideas clearly wins over content that gaming the old keyword-density game.

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