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| Topic | Details |
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| Topic 1 | - Implement AI solutions by using Microsoft Foundry: This domain is hands-on and focuses on building and deploying AI solutions using the Microsoft Foundry platform and its associated tools. It spans generative AI apps, text and speech processing, computer vision, and document intelligence all implemented through the Foundry portal and SDK.
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| Topic 2 | - Identify AI concepts and capabilities: This domain covers the foundational knowledge of AI from ethical principles and responsible design to understanding how AI models work and what kinds of tasks they can perform. It also explores the full range of AI workloads including generative AI, computer vision, speech, and information extraction.
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100% Pass Quiz Latest Microsoft - AI-901 - Valid Test Microsoft Azure AI Fundamentals Testking
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Microsoft Azure AI Fundamentals Sample Questions (Q93-Q98):
NEW QUESTION # 93
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.

Answer:
Explanation:

NEW QUESTION # 94
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:
Explanation:

NEW QUESTION # 95
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.

Answer:
Explanation:

Explanation:
Box 1: Yes
Yes, in enterprise environments like Microsoft Foundry, you can select a supported base model from the model catalog and deploy it directly to create a functional inference endpoint.
Box 2: No
Model deployments are created in the management portal or API first, and the playground is just a tool to test and use an already deployed model.
Box 3: Yes
Yes, after deploying an OpenAI model in an Azure or Microsoft Foundry environment, you can immediately use the built-in interactive playground within the portal to send prompts and review responses.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/foundry-models/how-to/deploy-foundry-models
NEW QUESTION # 96
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 # 97
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: In the Foundry playground, you can upload a local image and include text in the same message when prompting a multimodal model. = Yes Microsoft documentation for vision-enabled chat models states that in the chat session pane, you can select the attachment button, upload an image, add a text prompt such as "Describe this image," and then submit it.
Statement 2: When using the OpenAI Responses API and a vision-enabled model, images can be provided only as base64-encoded image data. = No Images are not limited to base64 data. The Responses API supports image input through an image URL, and Azure OpenAI documentation also describes examples using base64 encoded image data.
Statement 3: Prompts that include images require deploying a text-only model because multimodal capabilities are handled by the application layer. = No Image prompts require a vision-enabled multimodal model, not a text-only model. Azure OpenAI vision- capable models accept image and text inputs directly.
NEW QUESTION # 98
......
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