1Z0-1127-25 Using OCI Generative AI Service Practice Question
Which TWO measures can help reduce the risk of generating toxic or unsafe content when using OCI Generative AI Service?
⚠ Common exam trap
Oracle often tests the misconception that increasing temperature or disabling monitoring improves safety, when in fact these actions increase randomness and reduce oversight, respectively.
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
✓
Use few-shot prompting with examples that demonstrate safe and appropriate responses.
Few-shot prompting provides the model with explicit examples of safe, appropriate responses, which helps steer the model's behavior toward desired outputs and reduces the likelihood of generating toxic or unsafe content. This technique leverages in-context learning to align the model's responses with the provided examples, making it a practical measure for content safety.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use few-shot prompting with examples that demonstrate safe and appropriate responses.
Why this is correct
Safe examples help steer the model toward desired behavior.
- ✗
Disable model monitoring and logging to reduce overhead.
Why it's wrong here
Disabling monitoring reduces the ability to detect and respond to toxic outputs.
- ✗
Increase the temperature parameter to make output more deterministic.
Why it's wrong here
Higher temperature increases randomness, which can increase the chance of toxic outputs.
- ✗
Fine-tune the model on a large dataset without any safety filtering.
Why it's wrong here
Fine-tuning without safety filtering can embed toxic patterns into the model.
- ✓
Enable the built-in content filtering features provided by OCI Generative AI Service.
Why this is correct
Content filters block harmful outputs based on predefined categories.
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