Hallucination — When an AI model generates confident but factually incorrect information. It sounds right but isn’t. Causes: training data gaps, pattern matching without understanding. Mitigation: RAG, grounding, fact-checking layers, and trust scoring.
Why It Matters
Understanding Hallucination is essential for anyone building or evaluating AI systems. As AI tools proliferate, knowing the fundamentals helps you make better decisions about which tools to trust and deploy.
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