The correct answer is to set temperature to 0 and top_p to 0.1. Temperature controls randomness by scaling the probability distribution of token selection, and setting it to zero forces the model to choose the most likely next token every time, eliminating creative variation. Top_p, or nucleus sampling, further restricts the model to only consider tokens whose cumulative probability reaches 0.1, meaning it will ignore all low-probability options and stick to the most predictable, high-confidence outputs. On the Microsoft Azure AI Engineer Associate AI-102 exam, this question tests your understanding of how to control output consistency in Azure OpenAI for financial reports, where precision is critical. A common trap is confusing these parameters with penalties: presence_penalty encourages topic diversity, and frequency_penalty reduces repetition, but neither improves factual consistency. Memory tip: think “zero temperature, zero creativity” and “low top_p, low risk.”
AI-102 Implement generative AI solutions Practice Question
This AI-102 practice question tests your understanding of implement generative ai solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are deploying a solution that uses Azure OpenAI Service to generate financial reports. You need to ensure the outputs are accurate and consistent. Which TWO parameters should you adjust? (Choose two.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set temperature to 0.
A and C are correct. Temperature set to 0 reduces randomness for consistent outputs. Top_p set to 0.1 forces high-probability tokens. B is wrong because presence_penalty encourages topic diversity, not consistency. D is wrong because frequency_penalty reduces repetition, which might be desired but not for consistency. E is wrong because max_tokens controls length, not accuracy or consistency.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Set presence_penalty to 0.5.
Why it's wrong here
Presence penalty encourages new topics, reducing consistency.
✓
Set temperature to 0.
Why this is correct
Low temperature makes output more deterministic.
Related concept
Read the scenario before looking for a memorised answer.
✗
Set max_tokens to 2000.
Why it's wrong here
Max_tokens doesn't affect accuracy or consistency.
✗
Set frequency_penalty to 0.7.
Why it's wrong here
Frequency penalty reduces repetition, which may affect consistency.
✓
Set top_p to 0.1.
Why this is correct
Low top_p restricts to high-probability tokens, improving consistency.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Implement generative AI solutions — This question tests Implement generative AI solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set temperature to 0. — A and C are correct. Temperature set to 0 reduces randomness for consistent outputs. Top_p set to 0.1 forces high-probability tokens. B is wrong because presence_penalty encourages topic diversity, not consistency. D is wrong because frequency_penalty reduces repetition, which might be desired but not for consistency. E is wrong because max_tokens controls length, not accuracy or consistency.
What should I do if I get this AI-102 question wrong?
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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