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NEW QUESTION # 57
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 58
You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You need to create a prompt that ensures the model produces a relevant and useful response.
What should you include in the prompt?
Answer: A
Explanation:
A description of the task must be included in the prompt to ensure the model produces a relevant and useful response.
A prompt's core purpose is to tell the model exactly what it needs to accomplish. To get a useful and relevant output, you must explicitly provide instructions, context, rules, or the objective of the task (such as "extract the total price from this receipt" or "describe the objects in this photo").
Reference:
https://learn.microsoft.com/en-us/azure/foundry/foundry-models/how-to/deploy-foundry-models
NEW QUESTION # 59
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Box: perform consistently under expected conditions
Reliability and safety is the specific Microsoft Responsible AI principle defined by the requirement that AI systems must operate reliably, safely, and consistently under expected conditions.
Reference:
https://learn.microsoft.com/en-us/agents/design-guidelines/responsible-ai
NEW QUESTION # 60
You have a Microsoft Foundry project that contains a generative AI model deployment.
You test the model by using the Foundry playground.
You need to develop an application that sends requests to the deployed model.
Which information must the application include to call the model?
Answer: C
Explanation:
1. Authentication Data
You must prove your application has permission to access the model. This is included inside the HTTP Headers:
API Key Authentication: Pass the secret key generated by your Foundry project inside the api-key header.
api-key: YOUR_FOUNDRY_SECRET_KEY
Microsoft Entra ID Authentication (Recommended for production): Instead of a static key, pass a dynamic bearer token inside the Authorization header.
Authorization: Bearer YOUR_ENTRA_ACCESS_TOKEN
2. Connection & Routing Data
Your application needs to know exactly where to send the web request. This data is provided via the HTTP Request URL (Endpoint):
Target URI / Base Endpoint: The primary destination host. For standard deployments, it typically aligns with the OpenAI/v1 compatible schema or the generic Azure AI Inference API format.
Deployment Name: Included in either the URL path
(/deployments/{deployment_name}/chat/completions) or inside the request payload body under the "model" parameter to ensure the request is routed to your specific instance.
Reference:
https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/deploy-models-managed
NEW QUESTION # 61
You are developing an application that will coordinate a travel-booking workflow by gathering user preferences, searching for options, requesting approval, and booking services. The solution will maintain context across the steps.
Which type of Al workload is this an example of?
Answer: B
Explanation:
The described solution coordinates a multi-step workflow: gathering user preferences, searching for options, requesting approval, booking services, and maintaining context across steps. This is an example of Agentic AI.
Agentic AI systems use AI agents to reason over user goals, maintain context, decide which actions to take, and use tools or services to complete tasks across multiple steps.
Why the other options are incorrect:
A). information extraction extracts structured data from content.
C). computer vision analyzes images or video.
D). generative AI creates new content, but the scenario specifically describes an autonomous, context-aware workflow with actions, which is Agentic AI.
NEW QUESTION # 62
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