A manufacturing company wants to deploy a generative AI model that generates maintenance instructions on edge devices in factories. The devices have limited connectivity and must operate offline. The model is currently deployed as a REST endpoint in Azure. What should they do to meet the requirement?

Containerize the model and deploy it to Azure IoT Edge on the factory devices

Keep the model as a REST endpoint and rely on a VPN connection from the factory

Use Azure Functions to invoke the model on demand from the edge devices

Deploy the model to Azure Container Instances and access it over the internet

Which Azure AI service is specifically designed to help you monitor and trace the interactions between components in an AI application, including calls to generative models?

Azure AI Foundry (formerly Azure Machine Learning)

Azure AI Foundry's tracing and evaluation tools

A team has deployed a generative AI model that produces inaccurate responses for certain edge cases. They have collected feedback from users indicating these failures. They want to improve the model without retraining the entire model. Which approach should they prioritize?

Fine-tune the model on the entire dataset

Disable feedback collection to avoid negative data

Increase the temperature to get more diverse outputs

Analyze the failure patterns and refine the prompts for those cases

What is 'model reflection' in the context of generative AI?

The process of deploying a model to multiple regions

The process of retraining a model on new data

The process of converting a model to a different format

The process of having a model evaluate and critique its own outputs to improve future responses

Microsoft Certified:Azure AI Engineer Associate

Domain 2Objective 3

Optimize and Operationalize a Generative AI Solution AI-102 Practice Questions (Page 4)

Part of the Implement generative AI solutions domain, which accounts for 15-20% of the AI-102 exam. Microsoft does not publish an official question count, but from its 100-minute exam (~40–65 total, ~6–13 in this domain), expect 2–4 from this objective — we provide 47 practice questions to prepare you well beyond it. (estimate)

47questions here

10free pages

9concepts

15-20%of the exam

Questions 16–20

16application · medium
A manufacturing company wants to deploy a generative AI model that generates maintenance instructions on edge devices in factories. The devices have limited connectivity and must operate offline. The model is currently deployed as a REST endpoint in Azure. What should they do to meet the requirement?
Select an answer first
17foundation · easy
Which Azure AI service is specifically designed to help you monitor and trace the interactions between components in an AI application, including calls to generative models?
Select an answer first
18expert · hard
A team has deployed a generative AI model that produces inaccurate responses for certain edge cases. They have collected feedback from users indicating these failures. They want to improve the model without retraining the entire model. Which approach should they prioritize?
Select an answer first
19foundation · easy
What is 'model reflection' in the context of generative AI?
Select an answer first
20foundation · easy
Which Azure service provides a framework for building and orchestrating AI agents that can call multiple models and tools?
Select an answer first

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Optimize and Operationalize a Generative AI Solution AI-102 Practice Questions (Page 4)

Questions 16–20

Which Azure AI service is specifically designed to help you monitor and trace the interactions between components in an AI application, including calls to generative models?

A team has deployed a generative AI model that produces inaccurate responses for certain edge cases. They have collected feedback from users indicating these failures. They want to improve the model without retraining the entire model. Which approach should they prioritize?

What is 'model reflection' in the context of generative AI?

Which Azure service provides a framework for building and orchestrating AI agents that can call multiple models and tools?

Keep studying — Implement generative AI solutions