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NEW QUESTION # 48
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: To process prompts that contain images, you must deploy a multimodal generative AI model. = Yes Image prompts require a vision-enabled or multimodal model. A text-only model cannot interpret image content.
Statement 2: In the Foundry playground, you can provide an image by uploading a local file or by specifying a publicly accessible URL. = Yes The Foundry playground for vision-capable models supports adding image input to a prompt, including local uploads and image URLs.
Statement 3: A multimodal model can interpret multiple images included in a single prompt. = Yes Vision-enabled multimodal models can accept image content items in a prompt, and multiple images can be included for the model to analyze together.
NEW QUESTION # 49
You are building a knowledge base by using Azure AI Language service's custom answering feature. Which file format can you use to populate the knowledge base?
Answer: A
Explanation:
Azure AI Language service's custom answering can populate its knowledge base using various file formats, including structured text (.txt, .tsv), Microsoft Office documents (.docx, .xlsx, .pptx), and HTML, PDF, and Markdown files.
Reference:
https://docs.azure.cn/en-us/ai-services/language-service/question-
answering/reference/document-format-guidelines
NEW QUESTION # 50
You are developing a web app that processes invoices to calculate expenses.
You need to extract structured fields, including nested values, from the invoices by using a defined schema.
What should you use?
Answer: A
Explanation:
An analyzer in Azure Content Understanding within Foundry Tools can be used for this scenario.
Prebuilt Invoice Support: It offers prebuilt invoice analyzer templates specifically trained to identify common transactional data out of the box.
Schema-Driven Extraction: Instead of manual prompt engineering or tedious labeling, you can supply a strict JSON schema containing the specific fields you need.
Nested Values & Layouts: It handles hierarchical, nested elements (such as itemized tables, nested line items, or customer details) and maps them cleanly into arrays or structured objects.
Web App Integration: Activating the analyzer creates a highly scalable REST API endpoint. Your invoice-processing web app can query this endpoint to receive clean, machine-readable structured JSON payloads ready for downstream expense calculation.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/overview
NEW QUESTION # 51
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:
A system prompt, also called a system message, is used to guide how a generative AI model behaves, including its tone, role, response style, and output format. Microsoft states that system messages help steer an Azure OpenAI chat model toward the desired behavior, tone, and output format.
Statement 1: System prompts can be used to authorize users. = No
Authorization is handled by application identity, access control, authentication, and security configuration. A system prompt can guide model behavior, but it is not an authorization mechanism.
Statement 2: A system prompt is used to reduce tokens per minute (TPM). = No TPM is a quota or throughput setting for model deployments. A system prompt does not reduce or configure TPM.
Statement 3: A system prompt guides the behavior of a generative AI model. = Yes This is correct. Microsoft documentation says system messages help steer the model's behavior, tone, and output format.
NEW QUESTION # 52
Your company wants to build a recycling machine for bottles. The recycling machine must use cameras to automatically identify bottles of the correct shape and reject all other items.
Which type of Al workload should the company use?
Answer: A
Explanation:
A recycling machine that uses cameras to identify bottles of the correct shape and reject other items requires analysis of visual input. This is a computer vision workload.
Computer vision is used for image and video analysis tasks such as object detection, classification, shape recognition, and visual inspection.
The other options are incorrect:
A). knowledge mining extracts insights from large collections of documents or data.
B). natural language processing analyzes or generates language.
C). generative AI creates new content, but the requirement is to inspect camera images and identify objects.
NEW QUESTION # 53
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