Q9 — AWS AIF-C01 Ch.1

Question 9 of 100 | ← Chapter 1

A developer is using a large language model (LLM) to generate content for marketing campaigns. The generated content appears coherent and factually plausible, yet it is incorrect. What issue has the LLM encountered?

• A. Data leakage
• B. Hallucination ✓
• C. Overfitting
• D. Underfitting

Correct Answer: B. Hallucination

Explanation

This question tests understanding of common issues with large language models (LLMs). In AI, LLMs sometimes generate content that sounds credible but is factually incorrect — a phenomenon known as 'hallucination'. This occurs when the model fabricates information that appears reasonable but is not grounded in its training data. Option A (data leakage) refers to unauthorized exposure of sensitive information, which is unrelated. Option C (overfitting) describes a model performing well on training data but poorly on new data; Option D (underfitting) describes failure to capture underlying patterns in training data — neither matches the scenario. Therefore, the correct answer is B.