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AI hallucinations are incorrect or misleading results that AI models generate. These errors can be caused by a variety of factors, including insufficient training data, incorrect assumptions made by the model, or biases in the data used to train the model.

What are AI hallucinations?

An AI hallucination is when an AI model generates incorrect information but presents it as if it were a fact. Why would it do that? AI tools like ChatGPT are trained to predict strings of words that best match your query. They lack the reasoning, however, to apply logic or consider any factual inconsistencies they're spitting out.

What causes AI hallucinations?

AI hallucinations can occur for several reasons, including:

  • Insufficient, outdated, or low-quality training data. An AI model is only as good as the data it's trained on. If the AI tool doesn't understand your prompt or doesn't have sufficient information, it'll rely on the limited dataset it's been trained on to generate a response—even if it's inaccurate.
  • Overfitting. When an AI model is trained on a limited dataset, it may memorize the inputs and appropriate outputs. This leaves it unable to effectively generalize new data, resulting in AI hallucinations.
  • Use of idioms or slang expressions. If a prompt contains an idiom or slang expression that the AI model hasn't been trained on, it may lead to nonsensical outputs.
  • Adversarial attacks. Prompts that are deliberately designed to confuse the AI can cause it to produce AI hallucinations.