Generative AI Optimization

You are building a generative AI assistant for a financial advisory firm using Azure OpenAI. The assistant must answer questions based on a large repository of internal policy documents that are updated frequently. You need to reduce hallucination and ensure the model cites the most current policy versions. Which approach should you implement?

Which TWO techniques should you use to improve the accuracy of a RAG pipeline?

Which THREE factors contribute to increased latency in an LLM application?

You want to evaluate your prompt engineering changes quantitatively. Which method is most reliable for comparing two prompt versions?

You are configuring a chat application. What is the benefit of enabling streaming in the Azure OpenAI API?

You are monitoring an Azure OpenAI deployment used for a customer support chatbot. You notice that the model sometimes generates responses that include fabricated product features. You want to implement a technique that encourages the model to say 'I don't know' when it lacks information, rather than guessing. Which approach should you use?

You are optimizing a generative AI application that uses Azure OpenAI's GPT-4 model for summarizing long legal contracts. The summaries are often incomplete because the model truncates important details from the middle of the contract. You need to improve the completeness of the summaries without exceeding the model's context window. What should you do?

You are fine-tuning a model on Azure OpenAI and notice the training loss curve is fluctuating significantly. What is the most likely cause?

A user wants to restrict the model's output to valid JSON format. What is the most effective way to ensure this?

Your Azure OpenAI deployment is experiencing high latency during peak hours. You observe that input tokens are consistently high. Which strategy is most effective for reducing latency while maintaining quality?

You are optimizing a model for a specific domain language. Which fine-tuning approach minimizes cost while maximizing domain adaptation?

Which TWO of the following strategies are commonly used to optimize for cost in Generative AI?

Which THREE metrics are critical for monitoring a production Generative AI system?

You have a large set of documents for a RAG system. How should you optimize retrieval speed?

You are optimizing a generative AI solution that uses Azure OpenAI for a multilingual customer feedback analysis application. The application must process large volumes of text quickly and cost-effectively. You need to reduce token usage without sacrificing the quality of the analysis. Which two actions should you take? (Choose two.)

Which parameter in the Azure OpenAI API should be adjusted to make the model's output more deterministic and repeatable?

You are optimizing a long-context application. Which technique is most effective for reducing context window costs in Azure OpenAI?

An application is hitting rate limits on the Azure OpenAI service. Which action is the most standard approach for handling this in production?

Which feature in Azure OpenAI allows you to reserve throughput for a consistent user experience during high demand?

Which TWO methods are best for debugging an LLM pipeline that fails on complex queries?

You notice that your fine-tuned model is 'forgetting' base capabilities after training on a small dataset. What strategy should you use to mitigate this?

You are debugging a prompt that is performing poorly on edge cases. You decide to use a 'Chain-of-Thought' approach. Why does this improve performance?

Which TWO of the following are effective ways to reduce hallucination?

You notice your model is outputting redundant information. Which parameter specifically targets the penalty for repeating tokens?

Which THREE steps are necessary to successfully fine-tune an Azure OpenAI model?

To optimize costs for an enterprise chatbot, you want to implement token usage monitoring. Which Azure service should you integrate to track token consumption per user?

Which technique is most appropriate for optimizing RAG performance when the vector database returns too much noisy information?