What is AI Hallucination?

When AI systems generate plausible-sounding but factually incorrect or fabricated information not based on training data.

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Definition

AI Hallucination occurs when artificial intelligence systems generate information that appears plausible and coherent but is factually incorrect, fabricated, or not grounded in the training data or real-world facts.

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Purpose

Understanding hallucinations is crucial for identifying AI limitations, implementing verification systems, and developing strategies to improve AI reliability and accuracy in factual domains.

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Function

Hallucinations happen when AI models fill knowledge gaps with plausible-sounding content, extrapolate beyond their training data, or generate responses based on spurious patterns rather than factual information.

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Example

An AI assistant confidently stating that "The Eiffel Tower was built in 1912" (actually 1889) or providing detailed information about a non-existent scientific study with realistic-sounding authors and findings.

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Related

Connected to AI Reliability, Fact-Checking, Grounding, Model Limitations, Verification Systems, and Quality Assurance measures.

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Want to learn more?

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