Q30 — AWS AIF-C01 Ch.1

Question 30 of 100 | ← Chapter 1

A company wants to perform sentiment analysis using a large language model (LLM) on Amazon Bedrock. The company requires the LLM to produce consistent responses to identical input prompts. Which inference parameter adjustment satisfies this requirement?

• A. Decrease the temperature value ✓
• B. Increase the temperature value
• C. Reduce the output token length
• D. Increase the maximum generation length

Correct Answer: A. Decrease the temperature value

Explanation

This question tests understanding of LLM inference parameter tuning. For sentiment analysis, consistency is critical. Lower temperature values reduce output randomness and increase determinism, yielding more consistent responses. Higher temperature increases variability. Output token length and maximum generation length affect response length—not consistency. Therefore, option A (decrease temperature) is correct.