C. Test the new prompt in production without monitoring and observe user feedback to gauge performance. D. Use a random subset of production data and test both versions in a local environment, as local tests always replicate the conditions of production. You are tasked with developing a customer support system for an e -commerce platform using the Retrieval -Augmented Generation (RAG) pattern. The system needs to retrieve relevant information from a large database of product specifications, user manuals, and FAQs. You decide to use LangChain for constructing the pipeline and SingleStore as the backend for storing and querying the document embeddings. The objective is to efficiently retrieve semantically similar documents and use them as input for a generative model that crafts human -like responses. Which of the following steps best describes the correct implementation of the RAG pattern using LangChain and SingleStore for this customer support system?
You are tasked with designing a LangChain -based AI workflow using watsonx.ai that incorporates multiple models for different tasks: document classification, entity extraction, and text generation. The final output should consist of a well-structured report that combines these processes. What is the best strategy to orchestrate this workflow to ensure seamless integration of all tasks and a coherent final output?
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)
this test is specifically designed for discrete distributions. C. Use Algorithm B to compare the entropy of the original and synthetic data distributions, ensuring both data sets have the same level of uncertainty. D. Use Algorithm B if you want to focus on minimizing the difference in mean squared error (MSE) between original and synthetic data distributions. A generative AI model designed for healthcare content generation is being evaluated for ethical risks. The model tends to give preference to certain demographic groups when recommending treatments. What is the most effective method to identify and mitigate this bias during the prompt engineering phase?
C. Text embeddings are used to reduce the dimensionality of the input text for faster training of the generative model. D. Text embeddings map words and phrases to high-dimensional vectors that capture their semantic meaning, allowing for efficient document retrieval based on contextual similarity. You are developing a Retrieval -Augmented Generation (RAG) system to enhance the responses of a legal chatbot by integrating it with a vast legal document repository. You are using LangChain to build the pipeline, Watson ML for model hosting, and Elasticsearch as your document store. What would be the most appropriate approach for combining these components into a RAG pipeline?
➢ TOTAL QUESTIONS: 379 In the context of IBM Watsonx and generative AI models, you are tasked with designing a model that needs to classify customer support tickets into different categories. You decide to experiment with both zero-shot and few -shot prompting techniques. Which of the following best explains the key difference between zero -shot and few -shot prompting?
