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| Topic | Details |
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| Topic 1 | - 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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| Topic 2 | - 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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Microsoft Azure AI Fundamentals Sample Questions (Q45-Q50):
NEW QUESTION # 45
You plan to create an AI application that will use Azure OpenAI in Foundry Models. The solution requires that a specific amount of throughput be allocated. Which type of deployment should you use?
- A. standard
- B. data zone standard
- C. provisioned
- D. global batch
Answer: C
Explanation:
When a specific amount of throughput is needed with Azure OpenAI Service, you should use Provisioned Throughput Units (PTUs) for your deployment. PTUs allow you to reserve a fixed amount of processing capacity for your models, ensuring consistent performance and avoiding potential throttling or rate limits.
In contrast, the "Standard" deployment option in Azure OpenAI Service uses a "pay-as-you-go" model, where you are billed for the amount of usage. While this can be suitable for applications with fluctuating usage patterns, it does not provide the same level of throughput control as PTUs In summary: When you need to allocate a specific amount of throughput with Azure OpenAI Service, choose the "Provisioned" deployment type, which allows you to use PTUs.
Reference:
https://github.com/MicrosoftDocs/azure-ai-docs/blob/main/articles/ai-services/openai/concepts/provisioned-throughput.md
NEW QUESTION # 46
You are developing an application that continuously transcribes speech from a default microphone by using Azure Speech in Microsoft Foundry Tools.
You need to perform speech-to-text transcription from the microphone.
Which Python class should you use?
- A. SpeechSynthesizer
- B. AudioOutputConfig
- C. SpeechRecognizer
- D. SpeechConfig
Answer: C
Explanation:
speechsdk.SpeechRecognizer is the appropriate Python class to handle continuous real-time speech-to-text transcription from a default microphone.
How to Implement It
To achieve continuous transcription (rather than transcribing a single sentence and stopping), you instantiate this class and invoke its asynchronous long-running method.speechsdk.SpeechRecognizer: Acts as the core proxy client connecting your application to the Azure Speech service.
start_continuous_recognition(): The essential method on this class that instructs the SDK to stream microphone data indefinitely and process multi-sentence conversations.
Reference:
https://stackoverflow.com/questions/67691338/continuous-speech-recognition-from-microphone-on-ms-azure
NEW QUESTION # 47
Select the answer that correctly completes the sentence.

Answer:
Explanation:

Explanation:

The Microsoft responsible AI principle of transparency requires that AI systems be explainable to users
.
Transparency means users should understand when they are interacting with AI, what the system can and cannot do, and how outputs or predictions are generated at an appropriate level.
The other options map to different responsible AI principles:
protect sensitive user data = Privacy and security
reduce bias in decisions = Fairness
require human oversight = Accountability
NEW QUESTION # 48
Capturing text from images is an example of which type of Al capability?
- A. image description
- B. text analysis
- C. object detection
- D. optical character recognition (OCR)
Answer: D
Explanation:
Capturing or reading text from images is optical character recognition (OCR) . OCR is used to detect and extract printed or handwritten text from images, scanned documents, and other visual content.
NEW QUESTION # 49
You need to identify harmful content in a generative AI solution that uses Azure OpenAI Service.
What should you use?
- A. Language
- B. Video Analysis
- C. Content Safety
- D. Face
Answer: C
Explanation:
Azure AI Content Safety is a new Azure AI Service that can detect harmful user-generated and AI-generated content. This service is being integrated across MS products, including Azure OpenAI Service and Machine Learning prompt flow.
Reference:
https://ivanatilca.medium.com/testing-azure-ai-content-safety-ccd512f9b350
NEW QUESTION # 50
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