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
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:
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Lower temperature (0.0-0.3): More deterministic, predictable, and consistent responses
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Higher temperature (0.7-1.0): More creative, diverse, and unpredictable responses
Why B is correct:
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The problem states outputs are "too similar" - indicating lack of diversity
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Raising temperature to 0.9 increases randomness and creativity
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This will generate more unique and varied post captions
Why others are incorrect:
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A: Lowering temperature would make outputs even more similar and predictable
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C: Reducing max-tokens limits response length, not creativity
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D: Stop-sequence controls when generation stops, not output diversity
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