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NEW QUESTION # 90
- 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:
Answer Area
* Azure Vision in Foundry Tools can extract and analyze key phrases from PDF files. Answer: No
* Azure Vision in Foundry Tools can generate images based on natural language descriptions. Answer:
No
* Azure Document Intelligence in Foundry Tools can be used to automate the processing of invoices and credit notes. Answer: Yes
* No - Azure Vision in Foundry Tools focuses on computer vision tasks such as image analysis and OCR (reading text from images and documents). While it can extract text from scanned PDFs via OCR, key phrase extraction is a natural language processing capability provided by Azure Language in Foundry Tools, not Azure Vision. Key phrase extraction analyzes text to identify main concepts, which is a different service family than vision.
* No - Azure Vision can analyze existing images (for example, generate captions/descriptions of an image), but generating new images from a text prompt is a generative model capability (for example, DALL E through Azure OpenAI/Azure AI Foundry model endpoints), not an Azure Vision feature.
Vision describes what it "sees"; it doesn't synthesize new images from natural language.
* Yes - Azure Document Intelligence in Foundry Tools is designed for intelligent document processing, including automating extraction of structured fields from financial documents. Microsoft provides prebuilt models for invoices and supports custom extraction for similar document types, which makes it suitable for automating workflows involving invoices and credit-note style documents (field extraction, validation, routing).
NEW QUESTION # 91
- 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:
Answer Area
* To use Microsoft 365 Copilot Chat, you must have a Microsoft 365 Copilot license. Answer: No
* Microsoft 365 Copilot Chat provides context-aware assistance in Microsoft 365 apps. Answer: Yes
* Microsoft 365 Copilot Chat can only access information in open files and read emails. Answer: No
* No - Microsoft documents and pricing guidance indicate that Copilot Chat is available for eligible Microsoft Entra ID users with a qualifying Microsoft 365 subscription , and that capabilities can vary depending on whether users also have the Microsoft 365 Copilot add-on . In other words, Copilot Chat isn't universally "Copilot-license required" in all cases; the add-on impacts which premium work features are enabled, but the baseline chat experience can be available without assigning the add-on to every user.
* Yes - Microsoft describes Copilot Chat as a side-by-side experience in select Microsoft 365 apps (for example Word, Excel, PowerPoint, OneNote, Outlook) that is aware of the user's open content , enabling context-aware help such as summarizing, drafting, and Q & A based on what the user is working on.
* No - The word only makes this statement inaccurate. Copilot Chat can be grounded in more than just open files and emails (for example, it can also be grounded in the web, and-depending on licensing and configuration-can use agents/connectors for broader scoped tasks). So limiting it strictly to "open files and read emails" is too restrictive compared to how Microsoft positions the feature set.
NEW QUESTION # 92
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Generative AI is designed to create new outputs, such as text, images, code, summaries, emails, product descriptions, and conversational responses, based on patterns learned from training data and the user's prompt. Predictive AI is different because it focuses on forecasting outcomes, classifying data, or estimating probabilities from historical patterns, such as predicting customer churn, sales demand, or equipment failure.
Generative AI does not necessarily use a smaller dataset, and it does not automatically produce more accurate results than predictive AI. Accuracy depends on data quality, grounding, model design, and validation. The defining distinction is content creation: generative AI produces new material, while predictive AI predicts likely outcomes.
NEW QUESTION # 93
You need to create an AI assistant for a public customer support portal. The assistant must answer customer questions and start follow-up actions. The solution must minimize development effort.
What should you use?
Answer: D
NEW QUESTION # 94
Your company receives thousands of scanned invoices each month. You need to recommend an AI solution that can automatically extract key details, such as invoice numbers, vendor names, and total amounts. What is the best solution to recommend? More than one answer choice may achieve the goal. Select the BEST answer.
Answer: B
Explanation:
For scanned invoices, the requirement is structured field extraction (invoice number/ID, vendor, totals) from document images or PDFs at scale. The best fit is Azure Document Intelligence because it is purpose- built for document processing and provides prebuilt invoice models that combine OCR with layout/structure understanding to extract common invoice fields into a structured output. Microsoft's invoice model is explicitly designed to analyze invoices (including scanned images) and return key fields and line items in structured form, which directly maps to this scenario.
Azure Vision (B) can perform OCR and basic image analysis, but OCR alone typically returns text without robust invoice-specific field interpretation (e.g., reliably identifying "Invoice ID" vs. "Order ID," totals vs.
subtotals, vendor vs. ship-to). Document Intelligence is optimized for advanced document structure extraction and is therefore the "best" single recommendation.
Azure AI Search (C) focuses on indexing and retrieval/knowledge mining across a corpus; it's not the primary service for extracting invoice fields for downstream processing. Azure Machine Learning (D) could be used to build a custom model, but that adds cost and time compared with a prebuilt invoice extractor designed for this document type.
NEW QUESTION # 95
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