Generative AI Leader Fundamentals of Generative AI Practice Question
A marketing team wants to use a generative AI model to create blog post drafts from short product descriptions. They need the model to produce varied, creative text each time they run it. Which configuration parameter should they adjust to control the randomness of the output?
⚠ Common exam trap
Test-takers frequently confuse temperature with top-K or top-P, which also affect diversity but do not directly control the degree of randomness in the same way.
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
✓
Temperature
Temperature is the parameter that scales the logits before softmax, directly controlling the randomness of the output distribution. Higher values flatten the distribution, making less likely tokens more probable, which increases creativity and variation. For generating diverse blog drafts, the team should increase the temperature setting.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Temperature
Why this is correct
Temperature controls the randomness of the model's output. A higher temperature (e.g., 0.9) makes the output more diverse and creative, while a lower temperature makes it more deterministic. For generating varied blog post drafts, increasing the temperature is appropriate to encourage creative variation.
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Top-K
Why it's wrong here
Top-K limits the sampling pool to the K most likely tokens. While it affects diversity, it does not directly control the degree of randomness in the same way as temperature. Adjusting Top-K alone may not yield the desired creative variation; temperature is the primary parameter for randomness.
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Top-P
Why it's wrong here
Top-P (nucleus sampling) selects the smallest set of tokens whose cumulative probability exceeds P. It affects diversity but is not the primary control for randomness. Temperature is the parameter that directly scales the logits, thus controlling randomness more directly.
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Max output tokens
Why it's wrong here
Max output tokens sets the maximum length of the generated text. It does not influence the randomness or creativity of the content. Setting this too low could truncate the blog post, but it will not make the output more varied.
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Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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