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NEW QUESTION # 128
What should you use to compare benchmark metrics of different AI models?
Answer: B
Explanation:
To compare benchmark metrics across Azure AI models, navigate to the Azure AI Foundry portal, explore the model catalog, and use the benchmarking tools to assess model performance. You can then compare these metrics to choose the most suitable model for your needs.
Reference:
https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/benchmark-model-in-catalog
NEW QUESTION # 129
You are developing an application that extracts structured information from different types of content by using Azure Content Understanding in Foundry Tools.
You need to extract scanned invoices in the PDF format and voicemail recordings in the WAV format.
Which type of analyzer should you use for each content type? To answer, drag the appropriate analyzer types to the correct content types. Each analyzer type may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Azure Content Understanding analyzers define the type of content to process, such as documents, images, audio, or video , and what to extract, such as text, layout, fields, transcripts, and structured JSON output.
Microsoft lists base analyzer types such as prebuilt-document, prebuilt-audio, prebuilt-video, and prebuilt- image.
For scanned invoices in PDF format , the correct choice is document analyzer , because invoices are document/form content. Microsoft's Content Understanding quickstart specifically uses the prebuilt-invoice analyzer to extract structured data from an invoice PDF.
For voicemail recordings in WAV format , the correct choice is audio analyzer , because voicemail is audio content. Content Understanding supports structured data extraction from audio files, and the analyzer reference identifies prebuilt-audio as the base analyzer for audio content.
NEW QUESTION # 130
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:
In Microsoft Foundry Agent Service, tool_choice controls whether and how an agent uses tools during a run.
Statement 1: Yes
Setting tool_choice to auto lets the agent/model decide whether to call a tool. This statement is true.
Statement 2: No
Setting tool_choice to none does not mean the model decides whether to call a tool. It means the model will not call a tool. This statement is false.
Statement 3: Yes
Setting tool_choice to required means the agent must call one or more tools during the run. This statement is true.
Microsoft documentation describes the tool_choice values as follows: auto allows the model to decide whether to call tools, none prevents tool calls, and required forces one or more tool calls.
NEW QUESTION # 131
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: Azure Content Understanding in Foundry Tools can analyze only PDF documents. = No Azure Content Understanding is not limited to PDF documents. It can analyze different content types, including documents, forms, images, audio, and video.
Statement 2: Azure Content Understanding in Foundry Tools results are returned in the JSON format.
= Yes
Azure Content Understanding returns structured analysis output in JSON format.
Statement 3: Azure Content Understanding in Foundry Tools can extract structured fields from documents and forms. = Yes Azure Content Understanding can extract structured fields from documents and forms by using analyzers and schemas.
NEW QUESTION # 132
Match the principles of responsible Al to the appropriate descriptions.
To answer, drag the appropriate principle from the column on the left to its description on the light. Each principle may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
Explanation:
AI systems must consistently operate as intended, even under unexpected conditions. = Reliability and safety This description matches the Microsoft responsible AI principle of reliability and safety , which focuses on ensuring that AI systems behave consistently, safely, and as expected, including under unusual or unexpected conditions.
AI systems must protect and secure personal and business information. = Privacy and security This description matches the Microsoft responsible AI principle of privacy and security , which focuses on protecting personal, confidential, and business-sensitive information and preventing unauthorized access or misuse.
NEW QUESTION # 133
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