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In the context of AI, a hallucination refers to the generation of incorrect or misleading information by an AI model. This occurs when the AI produces content that is not factually accurate, relevant, or coherent. It's essentially the AI equivalent of a human hallucination, where the mind perceives something that isn't real.

Causes of AI Hallucinations:

• Insufficient training data: The AI model might not have enough information to accurately respond.
• Biased training data: If the data used to train the AI is biased, it can lead to biased outputs.
• Overfitting: The AI model might be too closely fitted to the training data, making it unable to generalize to new information.
• Model limitations: Some AI models are inherently prone to generating incorrect or misleading information.

It's important to note that AI hallucinations can be a significant issue, especially in applications where accuracy is crucial, such as medical diagnosis or financial analysis.