Which correction is accurate?

A language model generates the text most likely to follow the prompt; it is not reading a record, which is why it can produce confident-sounding statements that no source supports. The retrieval answer is the half-truth most executives hold, and it is wrong in a way that matters: the model is not looking anything up, even inside its own training data, so the limitation it names is real but the mechanism is invented. Checking claims against the web happens only when grounding or search is deliberately wired in, and never by default. A confidence figure has to be computed by the application; a fluent answer does not arrive carrying one. For factual work, add grounding, source checks and evaluation.