AI-900 Practice Question: Describe features of generative AI workloads on Azure
This AI-900 practice question tests your understanding of describe features of generative ai workloads on azure. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
A developer is using Azure OpenAI Service to generate Python code snippets. They notice that the generated code often contains repetitive function definitions and loops. Which parameter should be increased to reduce this repetition?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Frequency penalty
The frequency penalty parameter reduces repetition by penalizing tokens that have already appeared in the generated text, making the model less likely to reuse the same functions or loops. Increasing this value directly discourages the model from generating repetitive patterns, which is exactly the issue described.
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.
✗
Temperature
Why it's wrong here
Temperature controls randomness; lowering it makes output more deterministic but does not specifically reduce repetition.
✗
Max tokens
Why it's wrong here
Max tokens sets the maximum length of the generated text; it does not affect repetition.
✓
Frequency penalty
Why this is correct
A higher frequency penalty discourages the model from repeating the same tokens, leading to less repetition.
Related concept
Read the scenario before looking for a memorised answer.
✗
Top P
Why it's wrong here
Top P (nucleus sampling) controls the cumulative probability threshold for token selection but does not specifically penalize repetition.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Microsoft often tests the distinction between parameters that control randomness (temperature, Top P) versus those that control repetition (frequency penalty, presence penalty), leading candidates to mistakenly choose temperature when the issue is repetitive content.
Trap categories for this question
Command / output trap
Temperature controls randomness; lowering it makes output more deterministic but does not specifically reduce repetition.
Detailed technical explanation
How to think about this question
Under the hood, frequency penalty applies a multiplicative factor to the log-probability of tokens that have already appeared in the sequence, with a typical range of -2.0 to 2.0. A positive value reduces the chance of reusing tokens, while a negative value encourages repetition. In practice, combining a moderate frequency penalty (e.g., 0.5–1.0) with a slightly higher temperature can produce more varied and less repetitive code without sacrificing coherence.
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.
TExam Day Tips
→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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AI-900 question in full detail.
Describe features of generative AI workloads on Azure — This question tests Describe features of generative AI workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Frequency penalty — The frequency penalty parameter reduces repetition by penalizing tokens that have already appeared in the generated text, making the model less likely to reuse the same functions or loops. Increasing this value directly discourages the model from generating repetitive patterns, which is exactly the issue described.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
This AI-900 practice question is part of Courseiva's free Microsoft 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 AI-900 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.