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Artificial intelligence is reshaping search technology by moving from keyword-based methods to neural networks that understand context and user intent. This evolution enhances the accuracy, efficiency, and personalization of information retrieval. Insights from Durga Rao Manchikanti reveal how these advancements make search systems more intuitive and responsive to user needs.
The transition to semantic search allows AI-driven engines to interpret meaning rather than relying solely on keywords. This shift significantly improves user experience, particularly in sectors like e-commerce and medical research. As AI continues to evolve, search engines will increasingly anticipate user needs, refining the way information is accessed and consumed.
• AI enhances search technology by understanding context and user intent.
• Semantic search improves accuracy and reduces frustration from ambiguous queries.
Semantic search interprets meaning rather than relying on exact keywords, improving search accuracy.
Neural networks analyze data to understand complex relationships, enhancing search engine capabilities.
Large language models improve understanding of user intent by processing vast amounts of data.
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