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NEW QUESTION # 102
Hotspot Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 103
You have a Microsoft Foundry project that has a generative AI model deployment.
You need to ensure that responses generated by the model minimize costs and remain within a defined length.
Which parameter should you configure?
Answer: D
Explanation:
To minimize cost and keep generated responses within a defined length, configure Max Completion Tokens.
Microsoft's Azure OpenAI / Foundry API reference defines max_completion_tokens as an upper bound for the number of tokens that can be generated for a completion. Because generated tokens contribute to usage and response length, limiting completion tokens helps control both output length and cost.
Temperature and Top P control randomness or sampling behavior, not maximum response length. Model version settings do not directly define the generated response length.
NEW QUESTION # 104
What is an example of a Microsoft responsible AI principle?
Answer: A
Explanation:
Correct:
* AI systems should be secure and respect privacy.
* AI systems should treat people fairly.
Incorrect:
* AI systems should be in the public domain.
* AI systems should make personal details accessible.
* AI systems should NOT reveal the details of their design.
* AI systems should protect the interests of developers.
* AI systems should use black-box models.
Note:
Responsible AI principles
*-> Fairness: AI systems should treat all people fairly.
AI systems should treat everyone equally and provide the same recommendations to all individuals. Fairness in AI systems prevents discrimination based on personal characteristics.
* Reliability and safety: AI systems should perform reliably and safely.
*-> Privacy and security: AI systems should be secure and respect privacy.
* Inclusiveness: AI systems should empower everyone and engage people.
* Etc.
Reference:
https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai
NEW QUESTION # 105
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Statement 1: Fairness can be achieved by focusing solely on improving the overall accuracy of an AI model. = No Overall accuracy alone does not guarantee fairness. A model can have high overall accuracy while still producing biased or lower-quality outcomes for specific demographic groups. Fairness requires evaluating and reducing differences in model behavior across groups.
Statement 2: Evaluating AI system outputs to identify and reduce bias across demographic groups supports fairness. = Yes This statement is correct. The Microsoft responsible AI principle of fairness means AI systems should treat people fairly and avoid unfair bias. Evaluating outputs across demographic groups helps identify and reduce bias.
Statement 3: Ensuring fairness for an AI system means that all users always receive the same output from the system. = No Fairness does not mean identical outputs for all users. It means the system should avoid unfair bias and provide equitable treatment. Different users may receive different outputs when differences are relevant and appropriate.
NEW QUESTION # 106
Which natural language processing feature can be used to identify the main talking points in customer feedback surveys?
Answer: A
Explanation:
To identify the main talking points in customer feedback surveys, use key phrase extraction . This feature identifies important words and phrases in text, which is useful for summarizing themes in feedback.
NEW QUESTION # 107
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