Large Language Model (LLM)

A large language model (LLM) is an AI model trained on vast amounts of text to understand and generate human language. It's the underlying technology behind ChatGPT (OpenAI's GPT models), Claude (Anthropic), and Gemini (Google), and what every generative engine is built on top of.

Why it matters

Different LLMs retrieve and cite differently: Perplexity leans toward recently published, directly responsive sources, ChatGPT tends to concentrate citations among established media outlets, and Gemini cross-checks claims against Google's knowledge graph before citing. "Optimizing for AI" generically misses that each model has its own citation behavior worth tracking separately.

Related terms

• Generative Engine

  A generative engine is an AI system, such as ChatGPT, Perplexity, or Google's AI Overviews, that answers a query by synthesizing one direct response from multiple retrieved sources, instead of returning a ranked list of links for the user to click through themselves.

• Retrieval-Augmented Generation (RAG)

  Retrieval-Augmented Generation (RAG) is the architecture behind most AI search: the system retrieves a set of relevant documents or passages at query time, then generates its answer grounded in that retrieved material, rather than purely from what it learned during training.