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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q278-Q283):
NEW QUESTION # 278
Which of the following best describes the benefit of using prompt variables when developing generative AI models in IBM Watsonx?
- A. Prompt variables allow for dynamic input customization without needing to manually modify the core prompt, increasing flexibility.
- B. Using prompt variables in Watsonx allows the model to learn from real-time data input, enabling self-training over time.
- C. Prompt variables ensure that the same text input will always yield the same output, improving consistency.
- D. Prompt variables reduce computational load by optimizing model performance, improving overall system efficiency.
Answer: A
NEW QUESTION # 279
You are designing a workflow using watsonx.ai to generate complex text summaries from multiple sources. To achieve this, you plan to implement a LangChain-based chain that orchestrates different generative AI tasks: document retrieval, natural language processing (NLP) analysis, and summarization.
What is the best way to structure the LangChain-based chain to ensure that each task is effectively handled and results in an accurate summary?
- A. Break the LangChain-based chain into individual steps that allow for manual intervention at each stage, ensuring control over the process at every step.
- B. Perform document retrieval first, followed by NLP analysis to extract relevant information, and then pass the processed data to watsonx.ai for summarization.
- C. Use watsonx.ai to generate a summary immediately, and then perform NLP analysis and document retrieval in parallel to verify the accuracy of the output.
- D. Start with NLP analysis, pass the data to watsonx.ai for summarization, and then perform document retrieval to verify the accuracy of the summary.
Answer: B
NEW QUESTION # 280
In prompt engineering, prompt variables are used to make your prompts more dynamic and reusable.
Which of the following statements best describes a key benefit of using prompt variables in IBM Watsonx Generative AI?
- A. Prompt variables automatically improve the accuracy of responses by reducing model variance.
- B. Prompt variables allow a single prompt template to handle multiple data points or scenarios by inserting different values.
- C. Prompt variables eliminate the need to change model parameters every time you generate a new response.
- D. Prompt variables ensure that the AI's response format will always be consistent, regardless of the input data.
Answer: B
NEW QUESTION # 281
You are working with a Generative AI model to generate a summary of a large financial report. To reduce costs, you are exploring different model parameters such as minimum and maximum token limits.
Which configuration would help minimize generation costs while ensuring an accurate summary of the document?
- A. Set both the minimum and maximum token limits to 1,000 to ensure the entire report is captured in detail, with no important information left out.
- B. Set the maximum token limit to 500 and the minimum token limit to 250 to ensure a balanced summary of key sections with some detailed
- C. Set the maximum token limit to 700 and the minimum token limit to 600 to ensure a well-rounded summary with all necessary sections and detailed information included.
- D. Set the maximum token limit to 300 and the minimum token limit to 0, allowing the model to generate a brief summary of the most relevant points while avoiding excessive verbosity.
Answer: D
NEW QUESTION # 282
In planning the deployment of a generative AI model that relies on a large corpus of data, you need to organize and version the data repository used for training prompts.
Which of the following approaches best ensures efficient data versioning, integrity, and easy rollback during prompt refinement?
- A. Use a relational database to store the corpus, but without tracking any changes to the datasets.
- B. Implement a data versioning system like DVC (Data Version Control) or MLflow, integrated with a cloud storage service, to track data changes and link specific data versions to corresponding model and prompt versions.
- C. Store all datasets in a monolithic repository and append new data versions as additional files with timestamps.
- D. Store data versions directly in the production environment without versioning to save on storage costs.
Answer: B
NEW QUESTION # 283
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