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| Section | Weight | Objectives |
|---|---|---|
| Implement text analysis and information extraction solutions | 10-15% | - Analyze and extract information
|
| Implement computer vision solutions | 10-15% | - Analyze visual content
|
| Plan and manage Azure AI solutions | 25-30% | - Plan Azure AI resources
|
| Implement generative AI solutions | 25-30% | - Develop generative AI applications
|
| Implement agentic solutions | 20-25% | - Build AI agents
|
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NEW QUESTION # 89
You plan to build an agent that will combine and process multiple files uploaded by users.
You are evaluating whether to use the Azure AI Agent Service to develop the agent.
What is the maximum size of each file that can be uploaded to the service?
Answer: C
Explanation:
https://learn.microsoft.com/en-us/azure/ai-services/agents/quotas-limits
NEW QUESTION # 90
Hotspot Question
You have a Microsoft Foundry project that contains an agent.
The agent accepts user-uploaded screenshots and uses a multimodal chat model.
Some screenshots contain potentially malicious embedded text.
You need to prevent a prompt injection attack and ensure that third-party content is treated as lower trust.
How should you configure prompt shields for document attacks? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 91
Drag and Drop Question
You have a Microsoft Foundry project that contains an agent used by the financial analysts at your company.
You need to optimize the agent workflow by providing additional data access and processing capabilities. The solution must meet the following requirements:
- Ensure that the agent can perform calculations during conversations.
- Ensure that the agent can access up-to-date information from public
websites.
- Ensure that the agent can retrieve information from documents
uploaded directly to the agent.
What should you use for each requirement? To answer, drag the appropriate tools to the correct requirements. Each tool 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:
NEW QUESTION # 92
Hotspot Question
You need to create a new resource that will be used to perform sentiment analysis and optical character recognition (OCR). The solution must meet the following requirements:
- Use a single key and endpoint to access multiple services.
- Consolidate billing for future services that you might use.
- Support the use of Azure Vision in Foundry Tools in the future.
How should you complete the HTTP request to create the new resource? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: PUT
Need to create a Cognitive Services Multi-Service resource using the PUT method. This specific resource type provides a single endpoint and key for multiple AI services, consolidates billing, and supports Azure Vision.
Box 2: CognitiveServices
Using the CognitiveServices kind creates a multi-service resource. This fulfills all the requirements by providing a single key and endpoint for multiple services, consolidating billing, and enabling access to features like Azure AI Vision and Text Analytics under one roof.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/sdk-overview
NEW QUESTION # 93
You have a factory that contains a production line.
You need to develop a solution that will analyze a video feed to detect and track the movement of employees as they work on the production line.
Which service should you include in the solution?
Answer: C
Explanation:
Azure Vision in Foundry Tools (Spatial Analysis) can be used to analyze a video feed to detect and track the movement of employees as they work on the production line. This technology processes live or recorded video to understand spatial relationships and human activity.
Key capabilities for this application include:
Person Tracking & Movement: Spatial Analysis models identify human presence by detecting a body bounding box and tracking it in real time, enabling monitoring of movement patterns throughout a facility.
Zone & Line Monitoring: You can configure the system to detect when a person enters or exits a designated zone (e.g., a specific workstation) or crosses a line.
Dwell Time Calculation: The system can measure how long an employee spends in a specific zone, which can be useful for identifying bottlenecks.
Safety and Compliance: It can monitor for safety infractions, such as workers entering prohibited areas or failing to wear protective equipment (PPE).
Efficiency Analysis: By integrating these insights into Palantir Foundry's ontology, manufacturers can track assembly processes, optimize workflows, and enhance productivity.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/whats-new
NEW QUESTION # 94
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