Quiz IBM - C1000-185 - Authoritative IBM watsonx Generative AI Engineer - Associate Test Guide Online
Quiz IBM - C1000-185 - Authoritative IBM watsonx Generative AI Engineer - Associate Test Guide Online
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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q14-Q19):
NEW QUESTION # 14
When optimizing the tuning process in IBM watsonx Tuning Studio, what is the main purpose of fine-tuning metering options?
- A. To monitor the effectiveness of early stopping techniques applied during training.
- B. To track the computational cost and time for fine-tuning models based on resource consumption.
- C. To enforce stricter thresholds for model accuracy in order to ensure high precision.
- D. To limit the number of iterations allowed for model training.
Answer: B
NEW QUESTION # 15
What is a key benefit of using Prompt Lab in IBM Watsonx to build reusable prompts for generative AI applications?
- A. Prompt Lab automatically adjusts prompts based on the user's previous interactions, ensuring personalized output.
- B. Prompt Lab allows for the creation of templates with dynamic placeholders, making it easier to reuse prompts in various contexts without modification.
- C. Prompt Lab uses machine learning to automatically improve prompts over time without the need for developer intervention.
- D. Prompt Lab uses predefined responses to train the model, eliminating the need for further prompt experimentation.
Answer: B
NEW QUESTION # 16
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 the maximum token limit to 500 and the minimum token limit to 250 to ensure a balanced summary of key sections with some detailed
- B. 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.
- C. 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.
- D. 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.
Answer: C
NEW QUESTION # 17
A client needs a Generative AI solution to summarize large legal documents into concise briefs. The solution must capture the critical legal arguments while preserving the formal language required in legal contexts. Additionally, the client wants the model to identify key legal clauses and ensure their inclusion in the summaries. You have a pre-trained LLM that was trained on general text, and now you must design a generative solution to meet the client's needs.
What would be your next step in analyzing and designing the most effective solution?
- A. Apply model quantization to optimize the LLM for handling long legal documents more efficiently.
- B. Use prompt engineering to instruct the model to focus on key legal clauses and adjust the output to match the legal context.
- C. Fine-tune the pre-trained LLM on a dataset of legal documents, specifically focusing on case law, contracts, and formal briefs.
- D. Use a zero-shot approach, prompting the model to summarize legal documents without further fine-tuning.
Answer: C
NEW QUESTION # 18
You are refining a prompt for an AI model that generates financial reports using IBM watsonx Prompt Lab.
To ensure the AI produces structured outputs such as sections on "Revenue," "Expenses," and "Net Profit," which of the following is the most effective prompt editing option to achieve this goal?
- A. Use static prompt text and avoid variables to maintain a consistent structure for each report.
- B. Adjust the temperature setting to generate more creative and detailed reports.
- C. Increase the randomness parameter to encourage diverse sections in the report structure.
- D. Incorporate specific section headers as part of the prompt to guide the model in generating the desired report format.
Answer: D
NEW QUESTION # 19
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