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NEW QUESTION # 12
Hotspot Question
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:
Box 1: No
No - Retrieval Augmented Generation (RAG) requires model fine-tuning.
Retrieval Augmented Generation (RAG) does not require model fine-tuning; it is designed to enhance Large Language Models (LLMs) with external data without modifying their internal parameters. RAG enables fast knowledge updates and reduces hallucinations by fetching relevant information. While fine-tuning adjusts weights for domain-specific behavior, RAG is for dynamic, up-to-date knowledge.
Box 2: Yes
Yes - Retrieval Augmented Generation (RAG) is helpful when you need a generative AI solution that can access current, verifiable information.
Think of Retrieval Augmented Generation (RAG) as giving an AI an "open-book exam" instead of forcing it to rely solely on its internal memory.
By connecting the model to external, authoritative data sources-like a company's private knowledge base or real-time news-it becomes significantly more reliable in several ways:
Reduces Hallucinations: Because the AI must ground its answers in the retrieved documents, it's less likely to "make things up".
Transparency: You can see the exact source used for the answer, making it easy to verify facts.
Cost-Efficiency: It is often much cheaper and faster to update a RAG database than it is to retrain or fine-tune a massive model on new information Box 3: Yes Yes - Retrieval Augmented Generation (RAG) enables you to get more relevant responses based on your organization's documents without retraining the base model.
Retrieval-Augmented Generation (RAG) is an AI framework that improves the accuracy and relevance of Large Language Model (LLM) outputs by incorporating, in real-time, external data that was not part of the model's original training, all without the need to retrain or fine-tune the base model. This method is particularly effective for allowing AI systems to access and utilize an organization's proprietary, private, or constantly updating data to generate more contextually accurate and authoritative responses.
Reference:
https://www.redhat.com/en/topics/ai/rag-vs-fine-tuning
https://pub.towardsai.net/how-rag-powers-smart-ai-applications-8d005696baa3
NEW QUESTION # 13
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:
Answer Area
* Microsoft Foundry provides a unified platform for developers and data professionals to create custom end-to-end AI solutions. Answer: Yes
* Microsoft Foundry provides a unified platform for low-code developers and business users to create custom end-to-end AI solutions. Answer: No
* You need a Microsoft 365 Copilot license to access Microsoft Foundry services. Answer: No
* Yes - Microsoft Foundry is positioned by Microsoft as a unified AI platform for building, deploying, and scaling AI apps and agents, with enterprise governance in a single environment. Microsoft explicitly describes Foundry as enabling developers (and, in broader descriptions, data professionals
/enterprises) to build and operate AI solutions end-to-end, which aligns with the statement.
* No - While Foundry can streamline AI development workflows and may include experiences that reduce complexity, the statement specifically targets low-code developers and business users creating custom end-to-end AI solutions. In Microsoft's ecosystem, that "low-code/business-user" agent/app- building lane is more directly associated with tools like Copilot Studio/Power Platform , whereas Foundry is primarily presented as the platform for developers and technical teams building and governing AI solutions. Therefore, as written, the statement is not the best characterization.
* No - Access to Microsoft Foundry services is not gated by a Microsoft 365 Copilot license. Foundry is part of the Azure AI platform experience (formerly Azure AI Studio) and is accessed through Azure, using Azure subscription-based service consumption. Microsoft 365 Copilot licensing is for Microsoft
365 Copilot experiences, not a prerequisite to use Foundry services.
NEW QUESTION # 14
Hotspot Question
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:
Box 1: Yes
Yes - For a user to access organizational data from a mobile device, the user needs a Microsoft
365 Copilot license.
To access, summarize, and query organizational data (such as emails, chats, documents in SharePoint/OneDrive, and calendar items) via Microsoft 365 Copilot on a mobile device, a user must have a Microsoft 365 Copilot license assigned to them.
This license is an add-on to a qualifying base subscription (such as Microsoft 365 E3, E5, Business Standard, or Business Premium).
Box 2: Yes
Yes - To reason over your organizational data by using Microsoft Graph, you need a Microsoft
365 Copilot license.
To use the advanced AI reasoning capabilities of Microsoft 365 Copilot-specifically to analyze, summarize, and query your organizational data (emails, chats, documents, meetings) via Microsoft Graph-you need a Microsoft 365 Copilot license.
Box 3: Yes
Yes - To use the Analyst agent, you need a Microsoft 365 Copilot license To use the Analyst agent, you generally need a Microsoft 365 Copilot add-on license.
While a basic version of Copilot Chat is available for many Microsoft 365 and Office 365 subscribers at no extra cost, advanced "Frontier" agents like Analyst and Researcher are specifically built for deep reasoning and multi-step tasks, which are reserved for licensed Copilot users.
Reference:
https://learn.microsoft.com/en-us/copilot/microsoft-365/microsoft-365-copilot-minimum- requirements
https://learn.microsoft.com/en-us/copilot/faq
https://it.osu.edu/news/2025/07/22/new-microsoft-365-copilot-agents-available-research-and- analysis
NEW QUESTION # 15
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:
The answer Area
* A manufacturer can use Azure Vision in Foundry Tools to identify product defects on an assembly line.
The answer : Yes
* A logistics company can use Azure Vision in Foundry Tools to recognize package shipping labels.
The answer : Yes
* The HR department at your company can only use Azure Vision in Foundry Tools to extract written content from Microsoft Word files. Answer: No Azure Vision in Foundry Tools provides computer vision capabilities to analyze images, including identifying visual features and reading text with OCR. Because it is designed to "analyze images" and support vision scenarios, it can be applied to manufacturing quality inspection use cases where the goal is to detect anomalies
/defects from images captured on a production line. This aligns with statement 1 being Yes.
Statement 2 is also Yes because recognizing shipping labels is fundamentally text extraction from images (often plus some layout/field parsing). Azure Vision supports optical character recognition (OCR) to read printed text from images, and Microsoft documentation explicitly notes OCR can extract text from images such as product labels and similar real-world text surfaces-making shipping labels a direct fit.
Statement 3 is No because it is incorrectly restrictive. Azure Vision is not limited to extracting written content from Word documents, nor is OCR restricted to Word files. Vision capabilities apply broadly to images (and, depending on the capability, various document/image inputs) for tasks like image analysis and text recognition. HR could use it for many scenarios such as extracting text from scanned images, photos, or other visual inputs-not "only" Word files.
NEW QUESTION # 16
During AI adoption planning, leadership evaluates workforce readiness, operating models, and governance structures required to support AI at scale. Why is this step critical?
Answer: A
Explanation:
Assessing workforce skills, governance, and operating models ensures the organization can adopt AI responsibly and scale usage effectively.
Reference:
https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/plan
NEW QUESTION # 17
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