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そうでなければ、時代遅れになるリスクを負います。当社のAB-731認定テストは、技術スキルを向上させ、さらに重要なこととして、厳しい労働環境で明るい未来のために戦う自信を高めるのに役立ちます。当社の専門家は、AB-731学習ツールの開発に多くの時間とエネルギーを費やしています。あなたは私たちを信頼し、あなたの将来の発展において私たちをあなたの正直な協力者にすることができます。参考までに、AB-731試験の利点をいくつかご紹介します。
質問 # 68
- What should you use for each task? To answer, select the appropriate options in the answer area. NOTE:
Each correct selection is worth one point.
正解:
解説:
Explanation:
Answer Area
* Extracting structured data from forms and invoices: Answer: Azure Document Intelligence in Foundry Tools
* Summarizing written content from business reports: Answer: Azure Language in Foundry Tools
* Generating descriptive text for uploaded images: Answer: Azure Vision in Foundry Tools These three tasks align to three different Azure AI capability families: document processing, language understanding/generation, and computer vision.
* Forms and invoices are semi-structured documents where the business need is to extract specific fields (IDs, names, totals, dates) reliably into structured output. Azure Document Intelligence is designed for intelligent document processing and includes prebuilt models (such as invoices) as well as custom extraction options, making it the correct choice for structured data extraction from documents.
* Summarizing written business reports is an NLP task focused on compressing long text into key points, themes, and action items. Azure Language provides language processing capabilities (including summarization features within language service capabilities), so it is the best fit for summarization scenarios.
* Generating descriptive text for images (image captioning/description) is a computer vision task.
Azure Vision can analyze uploaded images and return descriptions/captions and other visual insights, which directly matches the requirement to produce descriptive text from images.
質問 # 69
- Select the answer that correctly completes the sentence.
Adopting Microsoft responsible AI principles is important for your organization because the principles
__________.
正解:
解説:
Explanation:
promote the ethical and accountable use of AI.
Microsoft's Responsible AI principles exist to guide organizations toward trustworthy, ethical, and accountable development and use of AI systems. Among the provided options, " promote the ethical and accountable use of AI " is the most accurate and comprehensive statement because it reflects the purpose of the principles themselves: ensuring AI is built and deployed in a way that respects people, reduces harm, and assigns clear responsibility for outcomes.
The other choices are either too absolute or too narrow. "Ensure that AI models deliver consistent and equitable results" is aspirational but not guaranteed-responsible AI practices reduce bias and improve reliability, but they cannot ensure perfect consistency or equity across all contexts. "Help organizations increase trust in fully autonomous AI systems" is not the intent; responsible AI emphasizes oversight and accountability, not pushing toward full autonomy. "Standardize model development practices across AI teams" can be a side benefit of governance, but it's not the primary reason to adopt responsible AI principles.
In practice, adopting these principles leads to concrete actions: defining governance and accountability, performing fairness and safety evaluations, protecting privacy and security, being transparent with users, and monitoring systems after deployment. These actions build stakeholder trust and enable sustainable adoption, but the foundational reason is that the principles provide a framework for ethical and accountable AI use.
質問 # 70
Drag and Drop Question
Match the business processes to the appropriate Microsoft Copilot solutions.
To answer, drag the Copilot solution from the column on the left to its business process on the right. Each solution may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
正解:
解説:
質問 # 71
Hotspot Question
Select the answer that correctly completes the sentence.
正解:
解説:
Explanation:
Box: crafting clear instructions to guide generative AI solutions in generating context-appropriate content.
Prompt engineering is the process of ___________________.
Prompt engineering is the process of crafting, evaluating, and improving prompts to gain more accurate outputs from an AI model. Factors that improve prompts include the LLM's preferred format, specificity of language, appropriately identifying the audience's expectations, and making function calls for external data.
At its core, prompt engineering is about reducing ambiguity so the model doesn't have to "guess" what you want. It's the bridge between a vague idea and a high-quality output.
Beyond just clarity, modern prompting often involves specific frameworks like Chain-of-Thought (asking the AI to think step-by-step) or Few-Shot Prompting (providing examples) to significantly improve reasoning and accuracy.
Reference:
https://www.linkedin.com/pulse/using-prompt-engineering-optimize-genai-models-iabac-nfa9c
質問 # 72
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.
正解:
解説:
質問 # 73
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