Using LLMs for Web Search (ankursethi.com)

A user has shared insights on using Large Language Models (LLMs) like Claude for web search, highlighting a distinct utility beyond their well-known application in coding assistance. The process involves submitting a prompt to the LLM, which may ask a clarifying question before conducting a web search through traditional engines to gather relevant information. The LLM then compiles a comprehensive report, complete with citations, although the user primarily values the curated links for further exploration rather than the report's content itself. This development is significant for the AI and machine learning community as it indicates an evolving role for LLMs in enhancing information retrieval, enabling users to uncover a wider array of obscure resources and updates beyond typical search engine results. The user has compiled a wishlist for enhanced LLM-powered search functionalities, advocating for features that grant greater control over research parameters and result refinement. These improvements could streamline how users interact with AI in knowledge discovery, promoting more efficient and relevant searches while encouraging further discussion on the capabilities of LLM-assisted web exploration.