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Implement generative AI solutionseasyMultiple ChoiceObjective-mapped

AI-102 Implement generative AI solutions Practice Question

You are developing a generative AI application that uses Azure OpenAI Service to summarize large documents. The application experiences high latency when processing requests. You need to reduce the latency without changing the model. What should you do?

⚠ Common exam trap

Watch out — candidates often confuse parameters that affect output length (max_tokens) with those that affect output diversity (temperature, top_p), mistakenly believing that adjusting randomness can speed up generation.

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

Reduce the max_tokens parameter in the API request

Reducing the max_tokens parameter limits the length of the generated response, which directly reduces the processing time required by the Azure OpenAI Service to produce the output. Since latency is caused by the model generating a long sequence of tokens, capping the output tokens decreases the number of autoregressive decoding steps, thereby lowering response time without altering the underlying model.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Increase the temperature parameter

    Why it's wrong here

    Increasing temperature does not reduce latency.

  • Increase the top_p parameter

    Why it's wrong here

    Increasing top_p does not reduce latency.

  • Reduce the max_tokens parameter in the API request

    Why this is correct

    Reducing max_tokens limits output length, reducing processing time.

  • Increase the max_tokens parameter

    Why it's wrong here

    Increasing max_tokens would increase latency.

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This AI-102 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-102 exam.