An AI hallucination refers to a response generated by a large language model (LLM) that sounds plausible but is factually incorrect or fabricated. These occur when the AI confidently provides information with no basis in its training data, often contradicting established facts, essentially creating details to fill knowledge gaps.
An AI hallucination is a response from an LLM that seems credible but lacks factual accuracy. These responses are generated when the model confidently shares information that has no grounding in reality, often contradicting known facts or making up details.
Key challenges associated with hallucinations include:
Methods like Retrieval-Augmented Generation (RAG) help minimize hallucinations by anchoring AI responses to verified sources. However, human oversight is still crucial when dealing with AI-generated content.
Learn more: Discover ways to identify and address AI hallucinations in our AI Hallucinations guide.