Hallucination Is Inherent, Not a Bug Being Fixed

Language models are next-token predictors. Given a sequence, they generate the most likely continuation based on patterns learned from training data.

The critical insight: “most likely” doesn’t mean “true.” The model has no concept of truth, only plausibility. It generates text that sounds right based on patterns, regardless of factual accuracy.

This means hallucination isn’t a malfunction. It’s inherent to probabilistic text generation. Mitigation strategies can reduce frequency but cannot eliminate it.

The governance implication: If hallucination can’t be eliminated technically, it becomes a governance problem. Instead of “how do we fix hallucination?” the better question is “for which use cases is this error rate acceptable?”

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