You are developing a RAG pipeline and notice that the model often hallucinates when retrieving documents with low relevance. Which prompt engineering technique should you implement to improve grounding?
You are optimizing prompt latency by reducing tokens. Which of the following is the most effective way to reduce input token count for a recurring task?
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?
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 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?
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?
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 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 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.)