Generative AI can't find its own errors. Do we need better prompts?

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The field of deep learning artificial intelligence, especially the area of "large language models," is trying to determine why the programs notoriously lapse into inaccuracies, often referred to as "hallucinations."

Google's DeepMind unit tackles the question in a recent report, framing the matter as a paradox: If a large language model can conceivably "self-correct," meaning, figure out where it has erred, why doesn't it just give the right answer to begin with?

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