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NEW QUESTION # 32
Your company uses a fine-tuned generative AI solution trained on data that is representative of the general population.
You discover that some of the generated responses include inappropriate or exclusionary language based on ableist assumptions.
You need to prevent the inappropriate responses. Your solution must minimize costs.
What should you do?
Answer: C
Explanation:
Implementing a content moderation filter is a critical strategy for fine-tuned generative AI to prevent the output of inappropriate or exclusionary language, including content rooted in ableist assumptions. These filters serve as a "digital safety layer" that intercepts biased or harmful material before it reaches the user.
How Filters Address Ableism and Exclusion
Contextual Detection: Modern filters using Large Language Models (LLMs) and Natural Language Processing (NLP) can detect subtle discriminatory phrases and slurs that traditional keyword filters might miss.
Policy-Driven Guardrails: Developers can use tools like the Lakera Guard Content Safety template to apply specific policies that flag and block ableist speech in real-time.
Customizable Classifiers: Services such as Azure AI Content Safety allow for the detection of
"abusive, derogatory, or discriminatory language" through trained statistical models.
Personalized Moderation: Emerging tools are being designed specifically to help disabled users filter out ableist hate and harassment tailored to their unique experiences.
Reference:
https://www.lakera.ai/blog/content-moderation
NEW QUESTION # 33
Your company sells hiking and camping gear online. You need a generative AI solution that can interact with customers and ask questions about their needs. What should you include in the solution?
Answer: D
Explanation:
The requirement is an interactive generative AI experience that can converse with customers and ask clarifying questions (for example: "What climate are you hiking in?", "How many people will share the tent?", "What's your budget?", "Do you prioritize weight or comfort?"). The best solution component for that conversational, question-and-answer interaction is a chatbot (A), powered by a generative AI model.
A chatbot provides the dialog framework: maintaining conversational context across turns, prompting the user for missing requirements, and responding in natural language. This makes it suitable for customer support, guided shopping assistance, troubleshooting, and pre-sales Q & A-especially when customers don't know exactly what they need and benefit from a guided conversation.
The other options don't match the core requirement. Predictive AI (B) forecasts outcomes (like demand or churn) and isn't inherently conversational. Computer vision (C) analyzes images (like recognizing products from photos) and doesn't address asking questions in dialogue. A recommendation engine (D) can be useful in ecommerce, but it typically suggests items based on behavior or attributes; it doesn't by itself provide a conversational flow that asks users questions and adapts responses in natural language. In practice, you can combine a chatbot with a recommendation engine behind the scenes-but the "include in the solution" component that directly satisfies interactive questioning is the chatbot.
NEW QUESTION # 34
Your company manages an online catalog of office supplies. You plan to use a generative AI solution to create product descriptions for your company's website. The solution must ensure descriptions can be posted immediately after creation, enable selection/inclusion of product details, and be fast and simple for non- technical staff. What is the best type of solution to use? Select the BEST answer.
Answer: C
NEW QUESTION # 35
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:
* For a user to access organizational data from a mobile device, the user needs a Microsoft 365 Copilot license. No
* To reason over your organizational data by using Microsoft Graph, you need a Microsoft 365 Copilot license. Yes
* To use the Analyst agent, you need a Microsoft 365 Copilot license. Yes Top of Form Bottom of Form The key distinction here is between Copilot Chat capabilities available with a standard Microsoft 365 subscription and the full Microsoft 365 Copilot add-on that enables richer, in-context experiences grounded in organizational data.
Mobile access to organizational data does not inherently require a Microsoft 365 Copilot license. Microsoft's Microsoft 365 Copilot app (and related mobile experiences) can provide Copilot Chat for work/school accounts with a Microsoft 365 license, so simply accessing organizational content on a mobile device is not the same as having the paid Copilot add-on. The statement claims a Copilot license is required just to access org data from mobile, which is too broad-there are mobile Microsoft 365 apps that access org data without the Copilot add-on.
Reasoning over organizational data via Microsoft Graph is a core value proposition of Microsoft 365 Copilot.
Microsoft documents explain that Microsoft 365 Copilot connects LLMs to your organization's content and context through Microsoft Graph and generates responses "anchored" in organizational data. That deeper integration is tied to the Microsoft 365 Copilot experience (an add-on license).
Analyst is a "reasoning agent" within Microsoft 365 Copilot and Microsoft states that users with a Microsoft
365 Copilot license can use Analyst (with defined usage limits). Therefore, the Analyst agent requires the Microsoft 365 Copilot license.
NEW QUESTION # 36
Select the answer that correctly completes the sentence.
The Researcher agent in Microsoft 365 Copilot __________.
Answer:
Explanation:
Explanation:
uses reasoning capabilities to generate deep insights based on organizational data and the web.
The sentence is best completed by the option describing Researcher as a research-oriented reasoning agent that combines information from the web and your work data to produce deeper insights. Microsoft describes Researcher as an agent built into Microsoft 365 Copilot to tackle complex, multistep research and to help users gather, analyze, and summarize information from "the web, your work documents, or both," producing a structured output that supports decision-making. That is exactly what the completion "uses reasoning capabilities to generate deep insights based on organizational data and the web" captures.
The other dropdown options are better matches for different tools/agents: "creates visual dashboards from structured data in Excel and Power BI" is more aligned to BI/reporting workflows; "generates a pivot table and performs time series forecasting" is spreadsheet/analytics functionality; and "performs complex, multi- step, data analysis and code execution tasks over arbitrary datasets" is the hallmark positioning of the Analyst agent ("virtual data scientist") rather than Researcher. Researcher's differentiator is deep research across both organizational context and the open web, while Analyst's differentiator is data analysis and computation .
NEW QUESTION # 37
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