Question 1mediummultiple choice
Full question →mediummultiple choiceObjective-mapped
A developer uses Azure OpenAI Service to generate short product descriptions. The developer notices that the model sometimes produces nonsensical or very low-probability words that make the output less coherent. The developer wants to reduce the chance of such outputs while still allowing some creative variability. Which parameter should the developer adjust in the API request?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
Decrease the temperature parameter to 0.1
Temperature controls the randomness of token selection; reducing it makes outputs more deterministic but does not directly filter out low-probability tokens. It may still choose a very improbable token if it has a high rank.
B
Best answer
Set the top_p parameter to a value like 0.9
Top_p (nucleus sampling) filters out low-probability tokens by only considering the smallest set of tokens whose cumulative probability is >= top_p. This reduces the chance of nonsensical words while allowing creativity from the remaining higher-probability tokens.
C
Distractor review
Increase the stop parameter to include more stop sequences
Stop sequences tell the model when to end generation, they do not influence which tokens are selected during generation.
D
Distractor review
Increase the max_tokens parameter to allow longer descriptions
Max_tokens limits the length of the output; it does not affect the probability distribution of token selection.
Common exam trap
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.
Technical deep dive
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.
Related practice questions
Related AI-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A developer wants to build a virtual assistant that can understand user intents such as 'Book a flight' or 'Check weather' and extract relevant entities like destination and date. The developer has a small set of labeled example utterances. Which Azure AI Language feature should the developer use?
Question 2
A developer is building a customer support chatbot using Azure OpenAI. The chatbot should never reveal its system instructions or internal configuration. The developer wants to add a rule at the beginning of the conversation to prevent prompt injection attacks. Which technique should they use?
Question 3
A developer is using Azure OpenAI Service to generate product descriptions from technical specifications. The generated descriptions sometimes include plausible-sounding but incorrect details (hallucinations). The developer wants to ensure the model's responses are strictly based on the provided product data and does not add any external or invented information. Which approach should the developer use?
Question 4
A developer is using Azure OpenAI with GPT-4 to build a chatbot that answers legal questions based on a company's internal policy documents. The developer wants the model's responses to be maximally deterministic and factual, avoiding any creative or speculative language. Which parameter should the developer set to the lowest possible value in the API call?
Question 5
A developer is using Azure OpenAI to generate creative product descriptions. The outputs are often repetitive and lack variety. The developer wants to increase the diversity of the generated text while still keeping it coherent. Which parameter should the developer increase?
Question 6
A developer is using Azure OpenAI Service to generate product descriptions. They want the output to be highly focused and deterministic, with less randomness. Which parameter should they decrease?
FAQ
Questions learners often ask
What does this AI-900 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Set the top_p parameter to a value like 0.9 — The top_p parameter, also known as nucleus sampling, controls the cumulative probability threshold for token selection. By setting top_p to a value lower than 1.0, the model only considers the smallest set of tokens whose cumulative probability exceeds top_p, effectively filtering out low-probability (and potentially nonsensical) tokens. This balances coherence with creativity. Temperature controls randomness but does not directly filter low-probability tokens. The stop parameter specifies sequences that end generation, not token selection. Max_tokens caps the output length but does not affect token probability filtering.
What should I do if I get this AI-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
Discussion
Loading comments…
Sign in to join the discussion.