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NEW QUESTION # 67
You have a large language model (LLM) that was pretrained by using public data.
You want the LLM to generate responses that incorporate frequently updated proprietary content, such as internal documents and knowledge bases.
You need to recommend a solution to ensure that the LLM uses the most current information without retraining the model.
What should you include in the recommendation?
Answer: B
Explanation:
The correct answer is D. Retrieval Augmented Generation (RAG). A pretrained LLM does not automatically know frequently updated proprietary content unless that content is supplied to it during use or the model is retrained. RAG solves this by retrieving relevant, current information from internal documents, knowledge bases, or indexed repositories at runtime and adding that information to the model's prompt context. This keeps responses grounded in the latest approved business content without changing the model weights. Fine- tuning adapts the model but is more expensive and does not automatically keep up with frequently changing knowledge. Content filtering is a safety control, not a freshness mechanism. Prompt engineering improves instructions, but by itself it does not retrieve current proprietary content.
NEW QUESTION # 68
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:
NEW QUESTION # 69
Your company is developing an AI-powered customer support agent. You need to ensure that the solution follows Microsoft responsible AI principles. Which two actions should you perform? Select the two BEST answers. Each correct answer presents part of the solution.
Answer: A,B
Explanation:
To align an AI customer support agent with Microsoft's Responsible AI principles, two high-impact actions are fairness/inclusiveness validation and transparency to users . B is correct because testing for inclusive and culturally sensitive responses directly supports fairness and helps reduce harm. In practice, you evaluate responses across diverse user personas, languages/dialects, accessibility scenarios, and sensitive contexts. You look for biased assumptions, stereotyping, exclusionary language, and disparate quality of service. This also implies ongoing monitoring because model behavior can drift as prompts, knowledge sources, and user inputs evolve.
E is correct because a clear disclaimer supports transparency: customers should know they are interacting with an AI system, understand the type of assistance it can provide, and know what to do if the response is incorrect or they need a human. A disclosure is also a practical risk-control that reduces overreliance and sets expectations about limitations.
The other options are not best for Responsible AI alignment: A (retain all conversations) can conflict with privacy/data minimization; retention must be justified and governed, not automatic. C (operate independently) undermines accountability and human oversight. D (multiple purposes) increases scope and risk rather than improving responsible use.
NEW QUESTION # 70
HOTSPOT - 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
* You can use Azure Language in Foundry Tools to analyze the sentiment of customer reviews. Answer:
Yes
* You can use Azure Language in Foundry Tools to translate internal reports into multiple languages.
The answer: No
* You can use Azure Language in Foundry Tools to extract text from scanned documents. Answer: No Azure Language is designed for natural language processing (NLP) over text that is already machine- readable. That includes capabilities like sentiment analysis , key phrase extraction, entity recognition, summarization, and classification. Therefore, statement 1 is Yes : sentiment analysis of customer reviews is a standard NLP workload where the service scores text as positive/negative/neutral (and often provides confidence scores), helping organizations quantify customer satisfaction and detect recurring issues.
Statement 2 is No because translation is typically handled by a dedicated translation capability (commonly delivered as a separate translator service) rather than the core "Language" NLP features. While translation is an AI language workload, it's not what the Azure Language service is primarily used for in this context; the expected Microsoft service choice for multi-language translation is the translator capability, not Azure Language.
Statement 3 is No because extracting text from scanned documents is OCR (optical character recognition), which is a computer vision/document processing function. OCR is delivered through Azure Vision and/or Azure Document Intelligence , which can read printed/handwritten text from images and PDFs and return structured output. Azure Language can analyze extracted text after OCR, but it does not perform the image-to- text extraction step itself.
NEW QUESTION # 71
You need to create an AI assistant for a public customer support portal. The assistant must answer customer questions and start follow-up actions. The solution must minimize development effort.
What should you use?
Answer: D
Explanation:
The correct answer is D. Microsoft Copilot Studio. The requirement is to create an AI assistant for a public customer support portal that can answer customer questions and initiate follow-up actions with minimal development effort. Microsoft Copilot Studio is designed for building custom agents using a low-code approach. It can connect to knowledge sources, provide generative answers, define conversation behavior, and trigger actions through connectors or workflows. Microsoft 365 Copilot Chat is intended for workplace productivity and organizational users, not public customer support portals. Microsoft Security Copilot is for security operations and incident investigation. Microsoft 365 Copilot connectors only make external data available to Copilot experiences; they do not by themselves create a public-facing customer support assistant.
NEW QUESTION # 72
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