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NEW QUESTION # 197
When deploying a machine learning model in a highly regulated industry (e.g., healthcare or finance), which strategy is most effective to ensure ongoing model performance while adhering to AI governance standards?
Answer: C
NEW QUESTION # 198
In a system that generates product recommendations using a generative AI model, you are tasked with creating prompts that incorporate dynamic variables to ensure more relevant and personalized responses.
Prompt Template: "Recommend products for [customer_name] based on their interest in [product_category]." Which portion of the prompt is the best candidate to be replaced with variables to achieve greater personalization and flexibility? (Select two)
Answer: C,D
NEW QUESTION # 199
You are tasked with improving the performance of a generative AI model used for customer service automation. The model needs to respond quickly and with high accuracy, particularly for complex queries. You have access to Tuning Studio as part of your optimization toolkit.
Which of the following is a primary benefit of using Tuning Studio to optimize the model in this scenario?
Answer: C
NEW QUESTION # 200
In the context of prompt engineering for IBM Watsonx Generative AI, which of the following is the most accurate description of a prompt variable?
Answer: D
NEW QUESTION # 201
You are part of a team building an AI-powered assistant that helps software developers by answering technical queries. To handle the vast amount of technical documentation efficiently, the team has chosen to implement the Retrieval-Augmented Generation (RAG) pattern. LangChain is used to construct the retrieval-generation pipeline, and SingleStore is employed to store the document embeddings. You need to ensure that the integration of LangChain with SingleStore allows for real-time retrieval of relevant technical documentation.
Which of the following configurations should be used to ensure an optimal RAG implementation with LangChain and SingleStore?
Answer: B
NEW QUESTION # 202
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