A knowledge cutoff is the latest point represented in an LLM’s training data. Questions about later events, fresh developments, or private organizational information may fall outside what the model learned. section 13.1
Because large models are expensive to retrain, updates occur infrequently. When prompted about information beyond that boundary, an LLM can produce a coherent but inaccurate answer rather than acknowledge that it lacks current knowledge. section 13.3
Current-information request
A request for tomorrow’s weather forecast illustrates the boundary: the model cannot answer accurately from training data alone. Applications requiring recent developments or sensitive internal data therefore need access to appropriate external information. section 13.1 section 13.3
