When AI generates confident but factually incorrect outputs, it's known as an AI hallucination. This occurs when large language models invent details to fill knowledge gaps. Developers use this to test model robustness, while researchers benefit by improving accuracy. Businesses leveraging AI for customer service or content creation must monitor hallucinations to maintain trust and reliability.
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