AIF-C01 Applications of Foundation Models Practice Question

Which parameter controls the randomness of generated text in a foundation model?

⚠ Common exam trap

AWS often tests the distinction between temperature (which reshapes the probability distribution) and top_p (which truncates the token set), leading candidates to confuse 'randomness control' with 'diversity via cumulative probability threshold'.

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 correct parameter because it directly controls the randomness of token sampling in a foundation model. A lower temperature (e.g., 0.1) makes the model more deterministic by concentrating probability mass on the most likely tokens, while a higher temperature (e.g., 1.5) flattens the probability distribution, increasing the likelihood of less probable tokens and thus generating more diverse or creative outputs.

Answer analysis

Option-by-option breakdown

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

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top_p
Why it's wrong here
top_p controls nucleus sampling, also affects randomness but temperature is the primary parameter.
✗
stop sequences
Why it's wrong here
Stop sequences cause early termination, not randomness.
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max_tokens
Why it's wrong here
max_tokens limits output length, not randomness.
✓
temperature
Why this is correct
Temperature directly affects randomness.

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AIF-C01 Applications of Foundation Models Practice Question

Why each option matters

Option-by-option breakdown

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