Large language models like ChatGPT and Gemini do not possess real-time knowledge and rely on a pipeline of tools to answer questions about current events or products. When a user asks a question, the model's prompt is rewritten into search queries. These queries are then used to search the web, and the model processes the retrieved passages to formulate an answer. This multi-step filtering process means that a brand must be indexed, fetchable, quotable, and corroborated by other sources to be recommended. AI
IMPACT Explains how LLMs use external tools to overcome knowledge cutoffs, impacting how users perceive and interact with AI recommendations.
RANK_REASON Article explains the operational mechanics of LLM product features (search tool integration) rather than a new model release or research.
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