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| Section | Objectives |
|---|---|
| Topic 1: Knowledge Mining and Information Retrieval | - Azure AI Search configuration - RAG (Retrieval Augmented Generation) patterns - Indexing and semantic search |
| Topic 2: Implement Computer Vision Solutions | - OCR and document intelligence - Image classification and object detection |
| Topic 3: Implement Natural Language Processing Solutions | - Language understanding and intent recognition - Translation and multilingual support - Text analytics and summarization |
| Topic 4: Develop Generative AI Applications and Agents | - Azure OpenAI Service integration
|
| Topic 5: Plan and Manage Azure AI Solutions | - Azure AI resource provisioning and configuration - Model selection and lifecycle management - Responsible AI principles and governance |
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問題 #131
You have a Microsoft Foundry project that processes procurement documents submitted by suppliers.
You need to implement two pipelines by using Azure Content Understanding in Foundry Tools. The solution must meet the following requirements:
* Include a pipeline named Pipeline1 that supports cost-effective, high-volume processing of standalone PDF invoices.
* Include a pipeline named Pipeline2 that supports cross-document validation by using multi-step reasoning and reference data.
How should you configure each pipeline? To answer, drag the appropriate configurations to the correct pipelines. Each configuration 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.
答案：
解題說明：
Explanation:
Pipeline1: Single-file task in standard mode
Pipeline2: Multi-file task in pro mode
Pipeline1 should use a single-file task in standard mode because the workload is high-volume processing of standalone PDF invoices. Azure Content Understanding standard mode is intended for individual files that require straightforward structured extraction, and Microsoft describes it as minimizing cost and latency for broad, data-centric processing scenarios. This makes it the best fit for cost-effective invoice extraction where each PDF can be processed independently.
Pipeline2 should use a multi-file task in pro mode because the requirement includes cross-document validation, multi-step reasoning, and reference data. Microsoft guidance states that pro mode is designed for advanced scenarios requiring multi-step reasoning and cross-file analysis, including processing multiple input files in a single request, validating or enriching data across documents, and using reference data to guide extraction and validation.
Single-file pro mode would add unnecessary capability for Pipeline1 and would not optimize for cost- effective high-volume standalone processing. Multi-file standard mode does not meet the pro-mode requirement for reference-data-based reasoning. Reference topics: Azure Content Understanding standard mode, pro mode, single-file tasks, multi-file tasks, field extraction, and procurement document validation.
問題 #132
You need to recommend an invoice review solution that resolves the issue reported by the finance department.
What should you include in the recommendation?
答案：A
解題說明：
The correct recommendation is Azure Content Understanding in Foundry Tools . The case study states that Contoso's finance department must manually review vendor invoices to verify that invoice details match vendor contract terms, and that the invoices contain tables, logos, and varied layouts that make consistent processing difficult. It also states that the planned solution must evaluate both the visual layout and textual content of the invoices.
Azure Content Understanding is designed for this type of multimodal document-processing workload.
Microsoft describes Content Understanding as a Foundry Tool that processes unstructured and multimodal content, including documents and images, and transforms it into structured output for AI applications. It can use document analyzers to extract text, layout, tables, fields, and relationships from diverse document types.
Chat completions alone would not reliably extract structured invoice fields from complex layouts. Azure Document Intelligence can extract OCR, layout, and tables, but Content Understanding is the better end-to- end Foundry capability for combining visual and textual understanding with structured extraction for downstream verification. Image Analysis focuses on image-level visual features and is insufficient for invoice field and table review. Reference topics: Content Understanding, document analyzers, multimodal extraction, invoice processing, tables, layout, and structured JSON output.
問題 #133
You have a Microsoft Foundry project that contains an agent.
You use a GitHub Actions workflow for CI/CD.
You need to configure the workflow to automatically evaluate the agent when a pull request (PR) is created and prevent branches from merging if the evaluation results do NOT meet the defined thresholds.
How should you configure the workflow? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
答案：
解題說明：
Explanation:
Authentication method: An Azure Login action that uses OpenID Connect (OIDC) If the evaluation results are NOT met, configure the workflow to: Fail The correct authentication method is Azure Login with OpenID Connect (OIDC) . Microsoft Foundry's GitHub Actions evaluation guidance recommends Microsoft Entra ID authentication and states that authentication can be automated by using the Azure Login GitHub action with OpenID Connect. The sample evaluation workflow also grants id-token: write, runs azure/login@v2, and then invokes the Microsoft AI Agent Evaluation action. This is the appropriate CI/CD authentication pattern because it avoids long-lived personal access tokens and supports secure federated authentication from GitHub Actions into Azure.
The workflow should be configured to fail when evaluation thresholds are not met. Foundry's evaluation GitHub Action is designed to automate pre-production assessment of Microsoft Foundry agents in CI/CD pipelines and produce evaluation results for the configured evaluators and test dataset. A failed GitHub Actions check can then be enforced through branch protection so the PR cannot merge until the quality gate passes. Locking the target branch or sending an alert does not directly implement a CI quality gate. Reference topics: Microsoft Foundry agent evaluation, GitHub Actions evaluation workflow, Microsoft Entra authentication, Azure Login with OIDC, pull-request quality gates, and CI/CD governance.
問題 #134
You have a Microsoft Foundry agent that grounds responses from an Azure Search index that contains the following:
- Searchable text fields for product names and product codes
- A vector field that stores embeddings for product descriptions
You need to ensure that users can query the index by using the following:
- Exact product names or codes
- Natural language descriptions of the products
What should you configure?
答案：C
解題說明：
To meet your requirements, you need to configure a Hybrid Search with Semantic Ranking in Azure AI Search. This setup combines keyword matching for exact identifiers with vector search for natural language queries, delivering the most accurate grounding data to your Microsoft Foundry agent.
Reference:
https://www.tredence.com/blog/searchsmart-enhancing-rag-with-azure-ai-search-service
問題 #135
You have a Microsoft Foundry project that generates short promotional product videos.
After several clips are approved, reviewers notice a small watermark in the top-right corner of some videos.
You need to remove the watermark without regenerating the videos.
What should you do?
答案：D
解題說明：
The correct action to take is to apply a mask-based inpainting edit to the affected part of the video.
This is the only option that directly modifies the existing, approved video files. Inpainting allows you to isolate the specific top-right corner using a mask and seamlessly blend it with the surrounding pixels to erase the watermark without altering or regenerating the rest of the video footage.
Reference:
https://openart.ai/features/ai-video-inpainting/
問題 #136
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Testpdf的AI-103考古題和實際的認證考試一樣，不僅包含了實際考試中的所有問題，而且考古題的軟體版完全類比了真實考試的氛圍。使用了Testpdf的考古題，你在參加考試時完全可以應付自如，輕鬆地獲得高分。
AI-103熱門題庫: https://www.testpdf.net/AI-103.html