What does hallucination refer to in AI output?

Hallucination in AI output specifically refers to the phenomenon where an AI model generates information or responses that may seem plausible or coherent but are factually incorrect or misleading. This occurs when the model constructs answers based on patterns it has learned during training rather than relying on actual data or established facts. The term is often used to highlight situations where AI might "make up" details that are not grounded in reliable information.

For instance, in natural language processing, a model might create a realistic-sounding response that is completely fabricated, leading users to believe they are receiving accurate data when, in fact, it does not reflect reality. Understanding this aspect is critical for users and developers of AI since it underscores the importance of verifying outputs, particularly in contexts where accuracy is paramount.