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NEW QUESTION # 87
You are deploying a generative Al model to a Microsoft Foundry project. You assign a higher tokens per minute (TPM) allocation to the model. What is the result of this change?
Answer: B
Explanation:
Tokens per minute, or TPM , is a throughput allocation for a model deployment. Assigning a higher TPM allocation increases the amount of token processing capacity available to the deployment, which affects the speed and scale at which the deployment can process requests.
It does not directly make responses longer, change region availability, or automatically add citations.
NEW QUESTION # 88
In Azure Machine Learning, what are two ensemble methods for combining models in automated machine learning (automated ML)? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: B,C
Explanation:
In Azure Machine Learning's automated machine learning (AutoML), two prominent ensemble methods for combining models are Voting and Stacking.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/concept-automated-ml 1
NEW QUESTION # 89
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: Voice Live returns only transcribed text. = No
Voice Live is not limited to transcription. Microsoft documentation states that the Voice Live API supports real-time bidirectional voice applications, including speech recognition, text-to-speech synthesis, avatar streaming, animation data, and audio processing.
Statement 2: Voice Live requires you to separately implement speech to text and text to speech services. = No Voice Live provides a single real-time voice API experience rather than requiring separate STT and TTS implementations for the conversational loop. Microsoft describes live AI voice conversations as combining speech capabilities for real-time interaction, and the Voice Live API includes speech recognition and text-to- speech synthesis features.
Statement 3: Voice Live combines speech to text, reasoning, and text to speech into a single conversational experience. = Yes This is correct. Microsoft's guidance explains that Azure OpenAI audio/realtime capabilities are for scenarios that combine audio with language understanding, reasoning, or generation in a single model call, and Voice Live supports real-time voice-enabled applications over WebSocket connections.
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:
Statement 1: An AI generative model is retrained before performing each user request. = No A generative AI model is not retrained for every user request. During normal use, the model performs inference: it receives input, processes the prompt, and generates a response based on the deployed model.
Statement 2: An AI agent responds by copying and pasting answers stored in a database. = No An AI agent does not simply copy and paste stored answers. Agents use generative AI models, instructions, context, and optionally tools or connected data sources to reason over user input and produce responses or actions.
Statement 3: An AI agent uses a generative AI model to establish actions based on user input. = Yes This is correct. An AI agent uses a generative AI model together with instructions and available tools to interpret user input, determine the next action, and generate a response.
NEW QUESTION # 91
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: No
No, you do not need to manually construct HTTP requests when using the Microsoft Foundry SDK. The SDK provides high-level client abstractions, such as AIProjectClient, that allow you to interact with your deployed models using standard programming languages and object-oriented paradigms.
Box 2: No
No, you do not need to create a separate web service to interact with a deployed model when using the Microsoft Foundry SDK.
The Microsoft Foundry SDK allows your application to communicate directly with the cloud-hosted model endpoint through built-in project clients.
Box 3: Yes
Yes, the AIProjectClient class in the Microsoft Foundry SDK (part of the Azure AI Projects client library) provides programmatic access to manage and interact with a deployed project and its connected resources.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/endpoints
https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/sdk-overview
https://learn.microsoft.com/en-us/dotnet/api/overview/azure/ai.projects-readme
NEW QUESTION # 92
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