1Z0-1127-25 LLM Fundamentals Practice Question
Which of the following is a recognized limitation of large language models?
⚠ Common exam trap
The 1Z0-1127 exam often tests the misconception that LLMs are infallible or always correct, leading candidates to overlook the well-documented hallucination problem in favor of incorrect assumptions about connectivity or data types.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
They can generate factually incorrect information (hallucinations)
Large language models (LLMs) are known to generate factually incorrect information, often called 'hallucinations.' This occurs because LLMs are probabilistic models that predict the next token based on training data patterns, not verified facts. They lack a grounding mechanism to validate outputs against real-world truth, making hallucinations a fundamental limitation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
They always require internet access
Why it's wrong here
LLMs can run offline; they do not need internet access for inference.
- ✗
They cannot perform translation between languages
Why it's wrong here
Many LLMs are capable of translation.
- ✓
They can generate factually incorrect information (hallucinations)
Why this is correct
Hallucinations are a key limitation where models produce confident but false statements.
- ✗
They can only process numerical data
Why it's wrong here
LLMs process text, not just numerical data.
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