Large Language Model (LLM)

Definition

A neural network trained on vast amounts of text that generates language by predicting the most likely next token.

An LLM learns statistical patterns from enormous text corpora and produces answers by predicting text one token at a time, which is why it can sound fluent yet occasionally state things that are not true. The knowledge baked into its parameters during training is fixed until the next update, so grounding and retrieval are used to supply current facts and sources. Understanding that an LLM reasons over probabilities, not a database of verified facts, explains both why brands can be misrepresented and why authoritative, well-structured signals help correct the picture.