完璧なAB-731受験記対策 &合格スムーズAB-731科目対策 |一生懸命にAB-731トレーリングサンプル

Wiki Article

さらに、JPNTest AB-731ダンプの一部が現在無料で提供されています：https://drive.google.com/open?id=1knthgcF_khwhDPqu_PMBMjz4UjwtntRl

AB-731試験の厳密な分析と要約により、学習内容を把握しやすくし、受験者の理解を超えた部分を簡素化しました。さらに、インターフェイスをより直感的にするために、図と例を追加して説明を表示します。 AB-731試験の質問は学習のプレッシャーを軽減し、Q＆Aを少なくしてより重要な情報を伝え、AB-731トレーニング資料で学習すれば最高の使用経験を提供します。また、99％から100％の高い合格率により、AB-731試験は非常に簡単です。

AB-731テストトレントは高品質で、主に合格率に反映されます。 AB-731テストトレントは、過去数年間の試験問題と業界動向に基づいて、業界の専門家によって慎重に編集されています。さらに重要なことは、時間の変化に基づいてAB-731試験資料を速やかに更新し、タイムリーに送信することです。教材を使用している人の99％が試験に合格し、証明書に合格しています。これは、間違いなく、AB-731テストトレントの合格率が99％であることを示しています。

>> AB-731受験記対策 <<

AB-731科目対策 & AB-731トレーリングサンプル

最近多くの人はIT資格認定試験という悩みがあるようですが、実は、この時代では、Microsoft資格は難しくないです。我々JPNTestはIT資格認定試験資料の販売者のリーダーとして、信頼できるAB-731問題集を提供します。躊躇われずに我々の模擬試験を利用してください。

Microsoft AI Transformation Leader 認定 AB-731 試験問題 (Q29-Q34):

質問 # 29
Your company plans to use generative AI to help project managers and engineers work with construction blueprints stored as PDF files. You need to recommend a generative AI solution that processes both images and text, summarizes building design, answers questions, and extracts information such as locations of electrical, heating, and plumbing systems. What should you recommend?

正解：A

解説：
Construction blueprints in PDFs often contain a mix of text, symbols, linework, and diagrams . The requirements include understanding both visual layout (where systems are located) and textual annotations , producing summaries, and answering Q & A. That combination requires a multimodal generative AI approach-models that can reason over images and text together. Therefore, A is best.
OCR alone (B) can extract printed text, but it won't reliably interpret diagram geometry, symbols, or spatial relationships (e.g., "electrical riser is on the east core near gridline B-4"). Text completion (C) is too generic and doesn't address image understanding. Document summarization (D) is only one requirement (summary) and still depends on first extracting/understanding both visual and textual elements.
A multimodal solution can ingest the PDF pages as images (or rendered page images) plus extracted text, then answer questions grounded in both modalities. In practice, you may combine OCR and layout extraction with a multimodal LLM so the model can reference drawing regions, legends, callouts, and system diagrams to produce accurate explanations and field extractions.


質問 # 30
- Select the answer that correctly completes the sentence.
The cost of using generative AI language models is based typically on the number of __________ processed.

正解：

解説：

Explanation:
Most generative AI language model pricing is based on token consumption , which measures the amount of text processed by the model. Tokens are sub-word units used internally by language models (for example, parts of words, whole words, or punctuation). When you send a prompt, the model consumes input tokens (your prompt + any system instructions + retrieved grounding context). When it generates a response, it consumes output tokens (the generated completion). Costs typically scale with the total input + output tokens processed, which is why long prompts, large grounding passages, and lengthy responses increase spend. This also explains why prompt optimization, response length limits, caching, and careful grounding are common cost-control techniques in enterprise solutions.
By contrast, "documents" is too coarse (a document can be 1 page or 500 pages). "Requests" is not the primary unit for most LLM pricing models because request sizes vary dramatically. "Words" is not used because the model's actual compute unit is tokens, and tokenization differs across languages and text patterns.
Therefore, the most accurate completion is tokens .


質問 # 31
During AI adoption planning, leadership evaluates workforce readiness, operating models, and governance structures required to support AI at scale. Why is this step critical?

正解：C

解説：
Assessing workforce skills, governance, and operating models ensures the organization can adopt AI responsibly and scale usage effectively.
Reference:
https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/plan


質問 # 32
Your company has an AI solution that uses a prebuilt Azure OpenAI model to generate content. You need to reduce the cost of the solution while minimizing the impact on the quality of the generated output. Which two actions should you perform? (Select TWO.) NOTE: Each correct selection is worth one point.

正解：A、C

解説：
To reduce Azure OpenAI costs with minimal quality loss, you target the biggest cost drivers: token usage and model price per token (or throughput unit). C (Optimize the prompts) is a best practice because shorter, clearer prompts reduce unnecessary input tokens and often reduce output length by tightening instructions and formatting. Prompt optimization can preserve or even improve quality by removing ambiguity, adding constraints, and using compact context (for example, only the most relevant grounding passages). Lower token consumption directly lowers cost while maintaining response usefulness.
D (Switch to an alternate model) is also effective because different models have different price/performance tradeoffs. Moving from a premium model to a more cost-efficient model (or a smaller variant) can significantly reduce spend. You can minimize quality impact by validating outputs on representative scenarios and using a tiered approach (cheap model by default, expensive model only for complex cases).
The other options are less aligned to the goal. A (Fine-tune) typically increases cost (training and ongoing evaluation) and is not the first-line cost reducer. B (Content moderation) is primarily a safety control; it can add overhead and doesn't directly reduce token costs. E (Decrease hosting hours) applies to capacity-based hosting scenarios, but the question states a prebuilt Azure OpenAI model for content generation-cost reduction is best achieved by prompt/token optimization and selecting the right model.


質問 # 33
You plan to meet with a group of stakeholders to discuss how generative AI can benefit your company. You need to provide the stakeholders with a relevant description of generative AI during the meeting. Which description should you use?

正解：A

解説：
Generative AI's defining characteristic is that it creates new content (text, images, code, summaries, drafts) in response to instructions-most commonly natural language prompts. Option C captures that general- purpose description in a stakeholder-friendly way: users provide prompts and the system generates responses or content. This framing is broad enough to cover common business value scenarios such as summarizing documents, drafting communications, creating marketing copy, generating reports, building assistants, and producing structured outputs from unstructured requests.
Option A is a single use case (translation), not the defining description. Option B describes predictive analytics
/forecasting, which is a different AI category focused on outcomes and probabilities rather than content creation. Option D describes recommendation systems, typically driven by ranking/behavioral signals; while AI can enhance recommendations, that is not the core definition of generative AI. Therefore, the most accurate and relevant description for stakeholders is C.


質問 # 34
......

JPNTestのMicrosoftのAB-731試験トレーニング資料はPDF形式とソフトウェアの形式で提供します。それはJPNTestのMicrosoftのAB-731試験の問題と解答を含まれます。そして、その学習教材の内容はカバー率が高くて、正確率も高いです。それはきっと君のMicrosoftのAB-731試験に合格することの良い参考資料です。もし不合格になる場合は、ご心配なく、私たちは資料の費用を全部返金します。

AB-731科目対策: https://www.jpntest.com/shiken/AB-731-mondaishu

専門的にIT認証試験のためのソフトを作る会社として、我々の提供するのはMicrosoftのAB-731ソフトのような高質量の商品だけでなく、最高の購入した前のサービスとアフターサービスです、JPNTestの MicrosoftのAB-731試験トレーニング資料は高度に認証されたIT領域の専門家の経験と創造を含めているものです、更新サービス提供、Microsoft AB-731受験記対策 PDF（テストエンジンのコピー）：内容はテストエンジンと同じで、印刷をサポートしています、AB-731テスト準備の指示の下で、非常に短時間でタスクを完了し、間違いなく試験に合格してAB-731証明書を取得できます、JPNTest AB-731科目対策を選ぶのは、成功を選ぶのに等しいと言えます。

話をしよう、経験的根拠によると、ルールの確立はシステムに従い、実際のシステムは法律で起こったことに基づいています、専門的にIT認証試験のためのソフトを作る会社として、我々の提供するのはMicrosoftのAB-731ソフトのような高質量の商品だけでなく、最高の購入した前のサービスとアフターサービスです。

素敵なAB-731受験記対策 & 合格スムーズAB-731科目対策 | 実際的なAB-731トレーリングサンプル

JPNTestの MicrosoftのAB-731試験トレーニング資料は高度に認証されたIT領域の専門家の経験と創造を含めているものです、更新サービス提供、PDF（テストエンジンのコピー）：内容はテストエンジンと同じで、印刷をサポートしています。

AB-731テスト準備の指示の下で、非常に短時間でタスクを完了し、間違いなく試験に合格してAB-731証明書を取得できます。

P.S. JPNTestがGoogle Driveで共有している無料かつ新しいAB-731ダンプ：https://drive.google.com/open?id=1knthgcF_khwhDPqu_PMBMjz4UjwtntRl

Report this wiki page