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NEW QUESTION # 16
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: C
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 # 17
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: An Azure Content Understanding in Foundry Tools analyzer returns results in the HTML format.
= No
Azure Content Understanding returns analysis results as structured output, typically JSON, not HTML.
Microsoft documentation states that the Content Understanding API returns analysis results in a structured JSON format.
Statement 2: The Content Understanding REST API analyzes content synchronously and returns results in the same response. = No Content Understanding analysis is asynchronous. The quickstart states that the response header includes an Operation-Location field, which is used to retrieve the results of the asynchronous analysis operation.
Statement 3: Azure Content Understanding in Foundry Tools can transform documents, images, audio, and video files into structured output. = Yes Microsoft describes Azure AI Content Understanding as processing documents, images, videos, and audio, and transforming them into user-defined output formats.
NEW QUESTION # 18
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
When using the OpenAI Responses API and a vision-enabled model, you can include an image in a request by providing the image as a base64-encoded image data.
Azure OpenAI / Microsoft Foundry vision requests support image input as an input_image item. The image can be provided by URL or as base64-encoded image data in the request. Microsoft documentation for Azure OpenAI batch examples also lists Base64 encoded image and Image URL as supported input patterns for Responses API requests.
The other options are incorrect:
a CSV file attachment is not an image input format for vision analysis.
an MP4 video stream is video content, not an image format.
a shared access signature (SAS) token is only an access token for a protected resource; it is not the image data itself.
NEW QUESTION # 19
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
The completed sentence is:
When developing an AI system for self-driving cars, the Microsoft reliability and safety principle for responsible AI should be applied to ensure consistent operation of the system during use.
Self-driving cars are safety-critical AI systems. The key requirement in the question is consistent operation of the system during use , which maps directly to the Microsoft responsible AI principle of reliability and safety .
The other options are incorrect:
Fairness focuses on reducing bias and treating people equitably.
Accountability focuses on ensuring people remain responsible for AI systems and their outcomes.
Inclusiveness focuses on designing AI systems that work for and empower diverse users, including people with different needs or abilities.
Therefore, the correct answer is reliability and safety .
NEW QUESTION # 20
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
The Model catalog is used for comparing and deploying a wide range of models for generative AI development.
Microsoft states that the model catalog in Foundry portal is the hub for discovering and using a wide range of models to build generative AI applications. Microsoft training also states that the model catalog is used to compare models by benchmark metrics and deploy models to endpoints.
NEW QUESTION # 21
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