Ace the AI-102 exam! Learn the crucial first step: setting up an Azure Language Resource for your question answering project. Get the knowledge to deploy AI-powered customer support systems effectively.
Table of Contents
Question
Your organization, Xerigon Corporation, is developing an AI-powered customer support system that uses Azure’s question answering service to provide users with accurate answers based on a large set of FAQs and documentation. You have been tasked with creating a new question answering project to manage this knowledge base and deploy it for real-time use.
Which of the following is the first step you should take when creating a question answering project in Azure AI Language?
A. Deploy the project to an endpoint for real-time usage.
B. Set up a Language resource in Azure to manage the question answering service.
C. Create a knowledge base and upload relevant documents.
D. Define and configure intents for the project.
Answer
B. Set up a Language resource in Azure to manage the question answering service.
Explanation
Setting up a Language resource in Azure to manage the question answering service is the first step you would take when creating a question answering project in Azure AI Language. This resource enables you to use the question answering capabilities and provides the necessary infrastructure to manage the project. Once the Language resource has been created, you can create a question answering project using the Language Studio portal and create a knowledge base for question answering. You can create a Language resource using the Azure portal as follows:
- Log in to the Azure portal.
- Type Azure AI Services in the search field and hit Enter.
- Click Create under the Language Service resource in the results.
- Click the Custom question answering block. Then click Continue to create your resource. Provide the required details for the settings.
- Click Create + review, then click Create.
Creating a knowledge base and uploading relevant documents is not the first step in the given scenario. The knowledge base is where you store information, such as FAQs, manuals, and documentation, that the question answering model will reference to answer user queries. Documents uploaded to the knowledge base would be relevant and structured to ensure accurate responses. Before you can create a knowledge base, however, you must first set up a Language resource to enable question answering capabilities within your Azure environment.
Defining and configuring intents for the project is not the first step you would take in the given scenario. Defining and configuring intents is a step associated with natural language understanding (NLU) tasks in Language Understanding (LUIS) rather than with question answering. In LUIS, intents represent the goals or actions behind user queries, and they help categorize incoming queries for further action.
Deploying the project to an endpoint for real-time usage is not the first step you would take in the given scenario. This allows the model to be accessed in real time, enabling applications to send questions and receive answers instantly. It is essential for making the model functional and accessible to users, but it occurs only after the knowledge base has been created, populated, and tested.
Microsoft Azure AI Engineer Associate AI-102 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Engineer Associate AI-102 exam and earn Microsoft Azure AI Engineer Associate AI-102 certification.