EVOLUTION AND FUTURE OF SEARCH: HOW AI IS TRANSFORMING INFORMATION RETRIEVAL

Abstract

This article examines the transformative impact of artificial intelligence on search engines, enhancing query processing and information retrieval. It addresses the limitations of traditional keyword-based algorithms. It traces the evolution of search engines from early keyword-based models to the integration of AI, enabling semantic understanding and context-aware search. The article delves into crucial AI techniques like Natural Language Processing, deep learning, and reinforcement learning, highlighting their impact on query processing and retrieval accuracy. It further explores how AI facilitates semantic search, leverages knowledge graphs, and enables personalized search results. Real-world applications are illustrated through examples like Google's BERT model and AI-driven enhancements in e-commerce. Finally, the article addresses challenges such as data privacy, bias in AI models, and computational demands while exploring future directions like multimodal search, explainable AI, and continual learning. Ultimately, the article underscores the profound impact of AI in shaping the future of search engines and their crucial role in navigating the digital age.