AWS Certified Cloud Practitioner
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A social-media company uses Amazon Bedrock to draft unique post captions. The current outputs are too similar. What parameter should the team adjust?
Real Exam
Community
RRitesh
0
A
Lower temperature to 0.2
B
Raise temperature to 0.9
C
Reduce max-tokens to 50
D
Set stop-sequence to "End of post"
Explanation:
Explanation
Temperature parameter controls the randomness/creativity of the model's output:
- Lower temperature (0.0-0.3): More deterministic, predictable, and consistent responses
- Higher temperature (0.7-1.0): More creative, diverse, and unpredictable responses
Why B is correct:
- The problem states outputs are "too similar" - indicating lack of diversity
- Raising temperature to 0.9 increases randomness and creativity
- This will generate more unique and varied post captions
Why others are incorrect:
- A: Lowering temperature would make outputs even more similar and predictable
- C: Reducing max-tokens limits response length, not creativity
- D: Stop-sequence controls when generation stops, not output diversity
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