Generative AI Leader Google Cloud's Generative AI Offerings Practice Question
A developer wants to use the Gemini API to generate creative text. Which TWO parameters can they adjust to influence the output?
⚠ Common exam trap
Google exams often test the distinction between model parameters that affect text generation (like Temperature and Top-k) versus media-specific parameters (like color space or image size), leading candidates to confuse domain-specific settings with generative AI controls.
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
✓
Top-k
Top-k (C) is correct because it limits sampling to the k most probable next tokens, directly shaping the randomness and creativity of the generated text. Temperature (E) is correct because it scales the logits before the softmax, controlling how deterministic or diverse the model's token choices are. Color space (A) is irrelevant since it pertains to image pixel encoding, not text generation parameters. Audio sample rate (B) applies to audio processing, not Gemini text output. Image size (D) affects image dimensions, which has no bearing on text generation creativity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Color space
Why it's wrong here
Colour space defines how image pixel values are interpreted, which is irrelevant to text generation. It would be a valid parameter when processing or rendering images, not when influencing the style or content of generated text.
- ✗
Audio sample rate
Why it's wrong here
Audio sample rate governs audio input or output fidelity, not text generation, so it has no effect on creative text output. It would be adjustable when configuring speech or audio processing features, not for controlling textual creativity.
- ✓
Top-k
Why this is correct
Top-k truncates the sampling pool to the k most probable next tokens, so lowering it makes output more focused and raising it increases variety. This is a sampling parameter that directly shapes creative text generation, satisfying the stem's requirement for a parameter that influences the Gemini API's output.
- ✗
Image size
Why it's wrong here
Image size controls the dimensions of generated or input images, not textual output. It would be adjusted when working with image generation or vision tasks, not when tuning creative text responses from the Gemini API.
- ✓
Temperature
Why this is correct
Temperature scales the logits before the softmax, flattening or sharpening the probability distribution. Higher values increase randomness and creativity in generated text; lower values make output more deterministic. This directly satisfies the stem's requirement for a parameter that influences the Gemini API's creative output.
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