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>> Latest AI-901 Dumps Sheet <<
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NEW QUESTION # 128
You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You use the Azure OpenAI Responses API to send a prompt to the model.
You need to provide an image for analysis.
Which content item should you include in the request?
Answer: D
Explanation:
When using the Azure OpenAI Responses API with a vision-enabled model, the image must be included as an input image content item. The correct content item type is:
{"type": "input_image", "image_url": image_url}
Microsoft's Azure OpenAI Responses API documentation states that the Responses API supports image inputs, and multimodal requests use structured input content items for the request.
Why the other options are incorrect:
A . image_base64 = Incorrect. Base64 data can be used as the image data format, but the content item type is still input_image.
B . image_generation = Incorrect. This is related to generating images, not providing an image for analysis.
C . output_image = Incorrect. This would refer to generated output, not image input.
D . input_image = Correct.
NEW QUESTION # 129
For each of the following statements, select if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Statement
Answer
Defining an AI system for a typical user profile is sufficient to support inclusiveness.
No
A high number of active users means an AI system provides an inclusive experience.
No
Providing accessible interfaces and language options helps support inclusiveness in an AI system.
Yes
Comprehensive and Detailed 150 to 250 words of Explanation From Azure AI Fundamentals/Course Guide
/topics:
The correct sequence is No, No, Yes .
Microsoft defines inclusiveness as designing AI systems so they work effectively for the full range of people they are intended to serve. The current AI-901 study guide explicitly includes the ability to describe considerations for inclusiveness in an AI solution as part of the Responsible AI objective domain.
The first statement is No because designing only for a hypothetical or "typical" user can exclude people with different abilities, languages, interaction styles, cultural backgrounds, or accessibility requirements. Inclusive design deliberately considers diverse and potentially underserved users.
The second statement is No because the number of active users is an adoption or usage metric. A system may have millions of users while still creating accessibility barriers or excluding particular groups. Usage volume therefore does not demonstrate inclusiveness.
The third statement is Yes . Accessible interfaces, assistive-technology compatibility, and suitable language options reduce barriers and broaden the range of people who can effectively interact with an AI system.
Microsoft specifically emphasizes accessibility and supporting varied user needs as core elements of inclusive AI design.
NEW QUESTION # 130
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:
NEW QUESTION # 131
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:
Statement 1: A summarization model is used to transcribe spoken audio into written text. = No Summarization creates a shorter version of existing text. Transcribing spoken audio into written text is a speech recognition / speech-to-text capability, not summarization.
Statement 2: A chat completion model can generate vector embeddings for semantic tasks. = No Chat completion models are used to generate conversational text responses. Vector embeddings for semantic search, similarity, and retrieval tasks are generated by embedding models, not chat completion models.
Statement 3: An embedding model can generate vector representations of the provided input. = Yes This is correct. Embedding models convert input such as text into vector representations that capture semantic meaning and can be used for tasks such as similarity search, clustering, and retrieval.
NEW QUESTION # 132
What are three Microsoft guiding principles for responsible AI? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: A,E,F
Explanation:
Microsoft's Six Responsible AI Principles
[C] Fairness: AI systems should treat all people equitably and avoid bias or discrimination.
[D] Reliability and Safety: Systems must operate dependably, consistently, and safely without causing harm.
Privacy and Security: AI must protect user data securely and respect personal privacy.
[E] Inclusiveness: Design should empower and engage diverse communities and users of all abilities.
Transparency: AI behavior and decision-making processes should be understandable to users.
Accountability: Creators and deployers of AI are responsible for how their systems operate.
Reference:
https://www.microsoft.com/en-us/ai/principles-and-approach
NEW QUESTION # 133
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