P.S.JpexamがGoogle Driveで共有している無料の2026 Microsoft AB-731ダンプ：https://drive.google.com/open?id=1xHgWqvivBgFYVZ_A6qG7-9e4Jg8FTfgt
偉大な事業を実現するために信心を持つ必要があります。あなたは自分の知識レベルを疑っていて試験の準備をする前に詰め込み勉強しているときに、自分がどうやって試験に受かることを確保するかを考えましたか。心配しないでください。JpexamはあなたがMicrosoftのAB-731認定試験に合格する確保です。Jpexam のトレーニング試験は問題と解答に含まれています。しかも１００パーセントの合格率を保証できます。JpexamのMicrosoftのAB-731試験トレーニング資料を手に入れたら、あなたは自分の第一歩を進めることができます。試験に合格してから、あなたのキャリアは美しい時期を迎えるようになります。
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社会の発展と相対的な法律と規制の完成により、私たちのキャリア分野でのAB-731証明書は私たちの国にとって必要になります。 AB-731に合格して証明書を取得することが、あなたの立場を変えて目標を達成するための最も迅速で直接的な方法かもしれません。そして、私たちはあなたを助けるためにちょうどここにいます。このキャリアで最も本物のブランドと見なされているプロの専門家は、お客様に最新の有効なAB-731試験シミュレーションを提供するために絶え間ない努力を行っています。
質問 # 59
You need to recommend a service that supports indexing information and knowledge mining by extracting insights from documents.
What should you recommend?
正解：B
解説：
Document Intelligence in Foundry Tools (formerly part of Azure AI Services) is a powerful, cloud- based service designed to automate data processing by extracting structured information, key- value pairs, tables, and text from unstructured documents like PDFs, images, and forms.
As part of the Azure AI Foundry ecosystem, it is designed for knowledge mining and accelerating document-heavy workflows, allowing you to convert raw files into actionable data for downstream analytics.
Reference:
https://azure.microsoft.com/en-in/products/ai-foundry/tools/document-intelligence
質問 # 60
Your company creates a custom Azure Machine Learning model that uses a generative AI assistant.
The model initially delivers strong results. However, six months later, the model predictions become noticeably less accurate.
What is a possible cause of the issue?
正解：A
解説：
This phenomenon is known as data drift.
It is one of the top reasons model accuracy declines after deployment. In the context of a generative AI assistant, data drift occurs when the statistical properties or distributions of the input data (the prompts or context provided by users) change significantly from what the model was originally trained on.
Key Causes of Data Drift
Changing User Behavior: Users may start interacting with the assistant differently, using new slang, jargon, or evolving topics of interest.
Real-World Changes: External events (like a pandemic or economic shift) can suddenly make the model's training data outdated and irrelevant.
Data Pipeline Issues: Changes in how data is collected, such as updated sensors or modified web forms, can alter the format or scale of inputs.
Seasonality: Patterns may fluctuate based on the time of year, such as different holiday shopping behaviors.
Impact on Generative AI
For a generative assistant, data drift often manifests as:
Reduced Relevance: Outputs feel outdated or fail to address contemporary topics.
Increased Hallucinations: When faced with unfamiliar input patterns, the model may produce factually incorrect or nonsensical responses.
Loss of Quality: Outputs may become less creative, more repetitive, or exhibit biased behavior.
Reference:
https://nexla.com/ai-infrastructure/data-drift
質問 # 61
Select the answer that correctly completes the sentence.
The Researcher agent in Microsoft 365 Copilot __________.
正解：
解説：
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 .
質問 # 62
Your company is reviewing a new AI solution before deploying it. The company wants to ensure that the solution follows Microsoft responsible AI principles.
What is the best approach to achieve the goal? More than one answer choice may achieve the goal. Select the BEST answer.
正解：B
解説：
The correct answer is B. Testing the AI solution to identify and mitigate unfair or inconsistent outcomes directly supports Microsoft responsible AI principles, especially fairness, reliability and safety, accountability, and inclusiveness. Before deployment, organizations should evaluate whether the system behaves consistently across different user groups, avoids discriminatory outcomes, and produces safe and reliable outputs. Automatically approving or rejecting loan applications increases risk unless strong governance and human oversight are in place. Collecting personal data can increase privacy exposure if it is not necessary and controlled. Prioritizing model performance alone is also insufficient because a technically accurate model can still produce biased, unsafe, or non-transparent outcomes. Responsible AI requires evaluation, mitigation, oversight, and monitoring.
質問 # 63
A legal services firm wants to deploy an AI assistant that answers employee questions about the firm's internal policies and procedures. The firm operates in a highly regulated industry with specialised legal terminology. A pretrained large language model produces responses that are generally accurate but frequently uses incorrect legal terms and occasionally misinterprets the firm's specific compliance requirements.
What should the firm do?
正解：D
解説：
When a pretrained model produces generally accurate responses but struggles with domain- specific terminology and context, fine-tuning is the appropriate solution. Fine-tuning trains the model on the firm's internal documentation, teaching it the correct legal terminology and compliance requirements specific to the firm's operations. This preserves the model's broad language capabilities while adding domain expertise.
質問 # 64
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AB-731予想試験: https://www.jpexam.com/AB-731_exam.html
P.S.JpexamがGoogle Driveで共有している無料の2026 Microsoft AB-731ダンプ：https://drive.google.com/open?id=1xHgWqvivBgFYVZ_A6qG7-9e4Jg8FTfgt