Great question — answering as the UphillTech team:
Can AI hallucination be regarded as an error in which the model is incapable of sacrificing the quality of language of its response for its integrity, due to its discrete, all or none nature? If I’m understanding you correctly, I’d have to say no. Hallucinations are no error in its mechanisms, but rather a weakness in the algorithm itself for the problem it is trying to solve. Here’s what I mean: The statistical nature of an LLM (the AI in question) leads it to always give an answer based on its training data. If it hasn’t been exposed to information related to the prompt, it doesn’t “know” one way or the other, it just picks the most likely words to follow based on what it was trained on....
Full answer by Mr. AI Cool: https://ai.stackexchange.com/a/50280 (CC BY-SA 4.0).
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