AI-102 Implement generative AI solutions Practice Test 9 — 15 Questions

Question 1

You are using Azure OpenAI Service to generate marketing copy. The marketing team reports that the generated content sometimes contains factual inaccuracies. You need to improve the factual accuracy of the generated content. What should you do?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Include relevant context and facts in the prompt. Providing relevant context in the prompt gives the model factual information to base its response on. Option A is wrong because increasing max_tokens only allows longer responses, not more accurate ones. Option C is wrong because decreasing temperature reduces randomness, but does not directly improve factual accuracy; it may reduce creativity. Option D is wrong because disabling content filtering does not address factual inaccuracies.

Answer

Increase the max_tokens parameter

Answer

Decrease the temperature parameter

Answer

Disable content filtering

Question 2

You are building a generative AI application that uses Azure OpenAI Service. The application must handle sensitive user data and comply with GDPR. You need to ensure that the service does not store or log user prompts and completions. What should you configure?

Accepted Answer

Disable data logging in the Azure OpenAI Service resource. Azure OpenAI Service provides a data logging toggle that, when disabled, ensures Microsoft does not store or process your prompts and completions for monitoring or improvement purposes. This is essential for GDPR compliance when handling sensitive user data, as it prevents any retention of personal data in the service's logs.

Answer

Deploy the resource in a GDPR-compliant region

Answer

Configure content filtering to block sensitive data

Answer

Use a custom endpoint that anonymizes data

Question 3

You are using Azure OpenAI Service to generate text. You need to reduce the likelihood of the model generating repetitive sequences. Which TWO parameters should you adjust?

Accepted Answer

frequency_penalty. Frequency penalty reduces the likelihood of the model repeating the same tokens or phrases by subtracting a fixed penalty from the log-probability of tokens that have already appeared in the generated text. This directly discourages repetitive sequences, making it one of the two correct parameters to adjust.

Answer

max_tokens

Answer

top_p

Answer

temperature

Question 4

You are designing a generative AI solution using Azure OpenAI Service. The solution must support multiple languages and provide consistent quality across languages. Which THREE actions should you take?

Accepted Answer

Use a model that supports multiple languages (e.g., GPT-4). GPT-4 is a multilingual model pre-trained on diverse language corpora, enabling it to generate coherent and contextually appropriate responses across many languages without additional fine-tuning. This ensures consistent quality by leveraging the model's inherent cross-lingual capabilities, which is essential for a generative AI solution that must support multiple languages.

Answer

Fine-tune the model on a dataset of a single language

Answer

Set the temperature to 0 for all requests

Question 5

You are building a generative AI application using Azure OpenAI Service. You need to ensure that the application handles user data securely. Which TWO practices should you implement?

Accepted Answer

Disable data logging in the Azure OpenAI Service resource. Disabling data logging in Azure OpenAI Service ensures that prompts and completions are not stored by the service for monitoring or abuse detection. This is a key security practice for handling sensitive user data, as it prevents inadvertent retention of confidential information. By default, Azure OpenAI may log data for operational purposes, so explicitly disabling logging is necessary to meet data privacy requirements.

Answer

Store prompts and completions in Azure Blob Storage

Answer

Use system messages to instruct the model not to store data

Answer

Configure content filtering to block sensitive data

Question 6

Refer to the exhibit. You are configuring an Azure OpenAI Service deployment for document summarization. The current parameters produce summaries that are often too verbose. You need to make the summaries more concise while maintaining factual accuracy. Which parameter change should you make?

Accepted Answer

Decrease max_tokens to 100. Decreasing max_tokens to 100 directly limits the maximum length of the generated summary, forcing the model to produce shorter output. This addresses the verbosity issue without altering the model's factual accuracy, as max_tokens controls output length, not content selection or creativity.

Answer

Increase top_p to 1.0

Answer

Increase frequency_penalty to 0.5

Answer

Increase temperature to 0.7

Question 7

Refer to the exhibit. You have deployed a GPT-3.5 Turbo model in Azure OpenAI Service with the shown configuration. Users report that the model generates responses that are too repetitive. You need to reduce repetition. Which parameter should you modify?

Accepted Answer

Increase presencePenalty to 0.5. Increasing the presencePenalty parameter penalizes tokens that have already appeared in the generated text, encouraging the model to introduce new topics and reduce repetition. In Azure OpenAI Service, presencePenalty directly influences the logit scores of previously seen tokens, making them less likely to be selected again, which addresses the user's complaint of overly repetitive responses.

Answer

Increase frequencyPenalty to 0.5

Answer

Increase temperature to 1.0

Answer

Decrease topP to 0.5

Question 8

Refer to the exhibit. You are reviewing the configuration of an Azure OpenAI Service resource. The resource is configured with customer-managed keys for encryption. What is the primary benefit of this configuration?

Accepted Answer

Enhanced control over data encryption keys. Customer-managed keys (CMK) allow you to control and manage the encryption keys used to protect your data at rest in Azure OpenAI Service. This provides enhanced control over who can access the keys, when they are rotated, and how they are stored, which is critical for meeting compliance and security requirements. The primary benefit is not performance, cost, or deployment simplicity, but rather the ability to enforce your own key lifecycle and access policies.

Answer

Simplified deployment process

Answer

Improved model performance

Answer

Reduced operational costs

Question 9

You are developing a generative AI solution that uses Azure OpenAI Service. The solution must generate product descriptions in multiple languages. You need to ensure that the model consistently follows specific formatting rules, such as including a bullet list of features. Which strategy should you use?

Accepted Answer

Set a system message with explicit formatting instructions.. System messages in Azure OpenAI Service allow you to set persistent instructions that guide the model's behavior across the entire conversation. By including explicit formatting rules—such as requiring a bullet list of features—in the system message, you enforce consistent output structure without retraining the model. This approach is efficient, cost-effective, and directly leverages the API's design for controlling response format.

Answer

Fine-tune the model with a dataset containing formatted examples.

Answer

Increase the max_tokens parameter to allow longer outputs.

Answer

Adjust the temperature parameter to a lower value.

Question 10

Your company uses Azure AI Content Safety to moderate user-generated content in a chat application. You need to detect and block sexual content in multiple languages. Which pre-built category should you configure?

Accepted Answer

Sexual. Azure AI Content Safety provides pre-built severity-based categories for content moderation. The 'Sexual' category is specifically designed to detect and block explicit sexual content, including text and images, across multiple languages. This makes it the correct choice for your requirement to moderate sexual content in a chat application.

Answer

Self-harm

Answer

Hate

Answer

Violence

Question 11

You are building a generative AI application using Azure OpenAI Service. The application must provide factual answers based on your company's internal knowledge base. You need to minimize the risk of the model generating incorrect information (hallucinations). Which approach should you take?

Accepted Answer

Implement Retrieval-Augmented Generation (RAG) with Azure AI Search.. Retrieval-Augmented Generation (RAG) with Azure AI Search grounds the model's responses in your company's internal knowledge base by retrieving relevant documents in real time and injecting them into the prompt. This reduces hallucinations by ensuring the model generates answers based on retrieved facts rather than relying solely on its parametric memory. Azure AI Search provides vector and hybrid search capabilities that efficiently index and query your documents, making RAG the most effective approach for factual accuracy.

Answer

Fine-tune the model on your company's documents.

Answer

Use few-shot prompting with examples of correct answers.

Answer

Set the max_tokens parameter to a low value.

Question 12

You are deploying a generative AI application that uses Azure OpenAI Service. You need to ensure that the application can handle sudden spikes in traffic without exceeding your quota. Which scaling strategy should you implement?

Accepted Answer

Configure a provisioned throughput deployment with auto-scaling.. Provisioned throughput (PTU) deployments with auto-scaling are designed to handle sudden traffic spikes by automatically adjusting capacity within your configured limits, ensuring consistent performance without exceeding quota. This approach provides reserved throughput that can scale up during demand surges and scale down when traffic subsides, unlike pay-as-you-go which is subject to global rate limits and may throttle during spikes.

Answer

Use a Pay-as-you-go deployment and rely on Azure's automatic scaling.

Answer

Create a deployment with a high base TPM and manually adjust during peak times.

Answer

Deploy multiple instances of the model in different regions.

Question 13

You are building a chatbot using Azure OpenAI Service. The chatbot must not disclose sensitive information such as passwords or credit card numbers. Which Azure AI service should you integrate to filter such content?

Accepted Answer

Azure AI Content Safety. Azure AI Content Safety is the correct service because it provides pre-built content filters that can detect and block sensitive information such as passwords, credit card numbers, and other personally identifiable information (PII) in text and images. It integrates directly with Azure OpenAI Service to apply these filters to both input prompts and output completions, ensuring that sensitive data is not disclosed in chatbot responses.

Answer

Azure AI Language

Answer

Azure AI Bot Service

Answer

Azure AI Search

Question 14

Your company uses Microsoft Copilot for Microsoft 365. You need to ensure that Copilot only accesses data from approved SharePoint sites and does not use any other organizational data. What should you configure?

Accepted Answer

Apply sensitivity labels to the approved SharePoint sites.. Sensitivity labels can be configured to restrict Microsoft Copilot for Microsoft 365 to only access content from approved SharePoint sites. By applying a sensitivity label that includes the 'mark content' or 'encrypt content' setting with a specific scope, you can use the 'Microsoft Copilot for Microsoft 365' condition under 'Access control' to block Copilot from processing data from unlabeled or non-approved sites. This ensures Copilot respects the label's policy and excludes all other organizational data.

Answer

Configure Conditional Access policies in Microsoft Entra ID.

Answer

Use Microsoft Purview Data Map to catalog the approved sites.

Answer

Set up data retention policies in Microsoft Purview.

Question 15

You are designing a generative AI solution that uses Azure OpenAI Service. The solution must generate code snippets in Python and JavaScript. You need to ensure the model reliably outputs code in the correct language based on user input. Which approach should you use?

Accepted Answer

Use a system message to specify the desired language.. System messages in Azure OpenAI Service allow you to set the context or behavior of the model, such as specifying the desired programming language for code generation. This approach is lightweight, requires no retraining, and reliably guides the model to output code in the correct language based on the user's request, leveraging the model's existing training on both Python and JavaScript.

Answer

Set the top_p parameter to a low value.

Answer

Fine-tune the model on a dataset of code in both languages.

Answer

Set the temperature to 0 to make the model deterministic.