What structural feature of LLMs makes "confidently wrong" outputs possible?
Answer: Models are trained to produce fluent, plausible completions and are not calibrated to express uncertainty automatically
LLMs optimize for plausible, fluent continuations of text. They are not trained to withhold claims they cannot verify, which is why confident errors occur.