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| Section | Objectives |
|---|---|
| Implement Natural Language Processing Solutions | - Implement question answering and conversational AI - Translate and interpret language using Azure AI services - Analyze text using Azure AI Language |
| Implement Computer Vision Solutions | - Extract information using OCR and form recognition - Implement custom vision models - Analyze images and videos using Azure AI Vision |
| Implement Generative AI Solutions | - Implement Azure OpenAI Service solutions - Integrate prompt engineering techniques - Build retrieval-augmented generation (RAG) solutions |
| Implement Knowledge Mining and Document Intelligence | - Implement document intelligence solutions - Enrich and index data for search scenarios - Build Azure AI Search solutions |
| Plan and Manage an Azure AI Solution | - Plan solution requirements and architecture - Manage security, compliance, and responsible AI - Select appropriate Azure AI services |
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NEW QUESTION # 122
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Azure subscription that contains an Azure OpenAI resource named AI1 and an Azure AI Content Safety resource named CS1.
You build a chatbot that uses AI1 to provide generative answers to specific questions and CS1 to check input and output for objectionable content.
You need to optimize the content filter configurations by running tests on sample questions.
Solution: From Content Safety Studio, you use the Safety metaprompt feature to run the tests.
Does this meet the requirement?
Answer: A
Explanation:
The Safety metaprompt feature is generally used to enhance safety by adding specific guidance to the model's responses. However, it is not designed for directly testing or optimizing content filter configurations with sample questions in Content Safety Studio.
To meet the requirement of testing content filters on sample questions, you should use the Moderate text content feature, as it specifically allows you to check for objectionable content in text input and output. Therefore, using the Safety metaprompt feature does not fulfill the requirement.
NEW QUESTION # 123
Which Azure Storage service implements the key/value model?
Answer: A
NEW QUESTION # 124
Hotspot Question
You are developing an application that will use the Azure AI Vision client library. The application has the following code.
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:
Reference:
https://learn.microsoft.com/en-us/rest/api/computervision/analyze-image-in-stream/analyze-image-in-stream
NEW QUESTION # 125
You are developing the smart e-commerce project.
You need to design the skillset to include the contents of PDFs in searches.
How should you complete the skillset design diagram? To answer, drag the appropriate services to the correct stages. Each service 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:
Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-concept-intro
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-ocr
NEW QUESTION # 126
You need to implement a table projection to generate a physical expression of an Azure AI Search index.
Which three properties should you specify in the skillset definition JSON configuration table node? Each correct answer presents part of the solution. (Choose three.) NOTE: Each correct selection is worth one point.
Answer: A,D,E
Explanation:
Defining a table projection.
Each table requires three properties:
- tableName: The name of the table in Azure Storage.
- generatedKeyName: The column name for the key that uniquely identifies this row.
- source: The node from the enrichment tree you are sourcing your enrichments from. This node is usually the output of a shaper, but could be the output of any of the skills.
Reference:
https://docs.microsoft.com/en-us/azure/search/knowledge-store-projection-overview
NEW QUESTION # 127
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