AI0-001 AI Concepts and Techniques Practice Question
A company is deploying a large language model for customer support. They want to reduce the number of off-topic or nonsensical responses while maintaining creativity. Which parameter adjustment would BEST achieve this?
⚠ Common exam trap
AI0-001 often tests the direction of each sampling parameter — candidates confuse top-k/top-p (which widen or narrow the candidate pool) with temperature (which sharpens or flattens the distribution), and pick a top-p change when temperature is the intended lever.
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
✓
Decrease temperature to 0.2
Lowering the temperature makes the model's probability distribution sharper, so it favors the highest-probability tokens and produces more deterministic, on-topic output. A value of 0.2 still allows some variation, preserving a degree of creativity while reducing off-topic or nonsensical responses.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Decrease temperature to 0.2
Why this is correct
Lowering temperature to 0.2 sharpens the model's probability distribution, favouring high-likelihood tokens and suppressing erratic sampling. This directly curbs off-topic or nonsensical output while retaining some stochastic variation, satisfying the requirement to preserve creativity rather than collapsing to fully deterministic greedy decoding at temperature zero.
- ✗
Set top-p to 0.1
Why it's wrong here
Top-p 0.1 restricts sampling to the smallest token set whose cumulative probability reaches 10%, sharply curtailing creative variation and often producing repetitive, generic replies. Top-p governs nucleus sampling breadth; a moderate value, such as 0.9, preserves creativity while trimming the long tail of unlikely tokens.
- ✗
Increase top-k to 100
Why it's wrong here
Raising top-k to 100 widens the sampling pool to the 100 most probable tokens, admitting lower-probability, off-topic tokens and increasing nonsensical output. Top-k is intended to constrain sampling breadth; a smaller value, such as 10, would restrict candidates and reduce off-topic responses.
- ✗
Increase temperature to 0.9
Why it's wrong here
Temperature 0.9 flattens the probability distribution, raising the chance of low-probability tokens and thus more off-topic or nonsensical output. Temperature controls randomness; a lower value, such as 0.3, sharpens the distribution and is the correct adjustment when creativity must be constrained.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.