Question

A product manager asks a general-purpose LLM to describe the technical specifications of a newly released internal device. The model produces a fluent, confident answer listing battery life, weight, and processor details — but none of these facts exist in any source, and the device was never in the model's training data. What is this behavior called?

Accepted Answer

A hallucination, where the model generates plausible-sounding but fabricated information

Answer

A context window overflow that dropped the correct answer

Answer

A tokenization error that corrupted the model's numeric output

Answer

An embedding mismatch between the query and the stored knowledge base