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>> AB-731 Valid Dumps Questions <<
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NEW QUESTION # 48
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 # 49
Your company is preparing to adopt Microsoft 365 Copilot and wants to follow Microsoft responsible AI principles.
As a business leader, you propose establishing an AI governance council to ensure alignment with the responsible AI principles.
What is the primary purpose of the council? More than one answer choice may achieve the goal.
Select the BEST answer.
Answer: A
Explanation:
Establishing an AI Governance Council is a critical step for organizations adopting Microsoft 365 Copilot to ensure that AI initiatives remain safe, ethical, and strategically aligned. This multidisciplinary body acts as the "operating system" for trustworthy AI, bridging the gap between technical teams and executive leadership.
Core Responsibilities of the Council
The council typically oversees the entire AI lifecycle across several key areas:
*-> Strategic Guidance: Aligning AI adoption with business goals and defining the organization's AI vision and acceptable use policies.
Ethical Oversight: Ensuring all solutions adhere to responsible AI principles such as fairness, transparency, and accountability.
Risk Management: Identifying and mitigating potential harms, including data leakage, algorithmic bias, and regulatory non-compliance.
*-> Cross-Functional Alignment: Bringing together stakeholders from IT, Legal, HR, Compliance, and individual business units to prevent siloed decision-making.
Policy Enforcement: Approving specific high-risk use cases and overseeing the implementation of technical guardrails like Microsoft Purview for data classification and protection.
Reference:
https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/strategy
https://adoption.microsoft.com/files/copilot/LeadingintheEraofAI_%20CreatinganAICouncil_Mar20
24.pdf
NEW QUESTION # 50
HOTSPOT - Select the answer that correctly completes the sentence.
You use __________ to train a model that will forecast product demand based on historical sales data.
Answer:
Explanation:
Explanation:
Azure Machine Learning
Forecasting product demand from historical sales data is a predictive analytics / machine learning use case.
It typically requires selecting an appropriate forecasting approach (for example, regression, tree-based methods, or time-series models), preparing and splitting historical data, training and validating the model, tuning hyperparameters, and then deploying the model for ongoing inference. The Microsoft service designed to support that end-to-end ML lifecycle is Azure Machine Learning , which is why it correctly completes the sentence.
Azure Machine Learning provides the tooling and infrastructure to: manage datasets, run training jobs on scalable compute, track experiments, compare model performance, register models, and operationalize them through managed endpoints and pipelines. This makes it well-suited for iterative forecasting work, where you may retrain on new data regularly, monitor drift, and update models as product lines, promotions, or seasonality patterns change.
The other options do not directly fit "train a model" for forecasting. Azure AI Search is an indexing/retrieval service used to search and ground generative AI responses, not for training predictive models. Azure OpenAI provides access to large language and multimodal models for generative tasks (drafting, summarizing, Q & A) and is not the primary platform for building classical forecasting models. Microsoft Foundry is a broader platform experience for building and governing AI apps and agents, but the specific service for training a forecasting model on historical sales data is Azure Machine Learning.
NEW QUESTION # 51
- Select the answer that correctly completes the sentence.
The Analyst agent in Microsoft 365 Copilot __________.
Answer:
Explanation:
Explanation:
uses structured data and provides insights by using text, charts, tables, and other visuals.
The Analyst agent in Microsoft 365 Copilot is positioned as a "data analysis" reasoning agent that helps users work through structured information (for example, tables, spreadsheets, and other dataset-like inputs) and then produces analytical outputs . The best completion is the option stating it "uses structured data and provides insights by using text, charts, tables, and other visuals," because that describes the hallmark outcome of analyst-style work: summarizing patterns, highlighting key drivers, and presenting results in formats that business users can act on. Analyst-style assistance typically includes exploring the data, identifying trends and anomalies, comparing segments, and explaining findings clearly-often accompanied by tables and visual representations that make the insights easier to consume.
The other dropdown options align to different use cases: "compiles background research for a new market or initiative" describes a research-oriented agent, "generate audio summaries" is a media summarization function, and "answer employee FAQs" describes a conversational knowledge assistant. Analyst is the one most directly associated with structured-data interpretation and producing a mix of narrative plus analytical artifacts (tables/charts) to communicate conclusions.
NEW QUESTION # 52
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: C
Explanation:
Retrieval-Augmented Generation (RAG) is the optimal, industry-standard approach for incorporating frequently updated proprietary data into an LLM's output. It works by connecting a pre-trained LLM to an external, dynamic knowledge base--such as company documents--using vector databases to retrieve relevant context in real-time, reducing hallucinations and eliminating the need for constant, costly retraining.
Reference:
https://shiftasia.com/community/retrieval-augmented-generation-rag-a-comprehensive-guide-to-smarter-more-accurate-ai
NEW QUESTION # 53
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