A chatbot starts 'forgetting' earlier parts of long conversations. Which foundation model limitation causes this?
A.Hallucination
Hallucination invents content — it doesn't lose memory.
B.The fixed context window — content beyond the window is dropped
Correct. Window overflow drops earlier context.
C.High temperature settings
Temperature controls randomness, not memory length.
D.Model quantization
Quantization reduces precision/size — unrelated to context.
Why this answer
Every FM has a finite context window (measured in tokens). When conversation history exceeds it, older content falls outside the window and the model can't 'see' it — the observed 'forgetting'. Mitigations: summarize history, retrieve relevant turns, or pick a model with a larger window.
Correct answer: B · Last reviewed 2026-11-02
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