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IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. When optimizing a generative AI model using the Tuning Studio in IBM Watsonx, which two of the following actions can most effectively improve model performance when dealing with underfitting issues? (Select two)

A) Increase the number of training epochs
B) Enable early stopping
C) Decrease the batch size
D) Reduce the learning rate
E) Increase the model's complexity by adding more layers

2. You are tasked with optimizing the cost of text generation using a generative AI model by adjusting model parameters. One of the key parameters you consider is the temperature, which controls the randomness of the output. The client has requested outputs that are more predictable and closer to the intended meaning, without unnecessary creativity, in order to reduce unnecessary token usage and ensure the quality of generated responses. Given the following task:
"Generate a brief summary of a technical article that focuses on key innovations without including unrelated or creative content." Which of the following temperature settings would be most appropriate to optimize cost while maintaining focus and minimizing unnecessary token usage?

A) 0.0
B) 1.0
C) 0.1
D) 1.2

3. While generating synthetic data using IBM Watsonx's User Interface to supplement your fine-tuning dataset for a customer service chatbot, you notice some responses are incoherent or contain contradictions.
What steps should you take to maintain the quality and relevance of the synthetic data?

A) Only use synthetic data that matches predefined patterns exactly to avoid any incoherence or errors.
B) Manually adjust the temperature parameter in the UI to lower values to reduce randomness and increase coherence in the generated text.
C) Generate as much data as possible, then use external validation tools to filter out problematic responses.
D) Enable auto-validation in the UI to automatically discard any generated data that doesn't align perfectly with training data patterns.

4. 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) Incorporate specific section headers as part of the prompt to guide the model in generating the desired report format.
C) Adjust the temperature setting to generate more creative and detailed reports.
D) Increase the randomness parameter to encourage diverse sections in the report structure.

5. You are tasked with designing a prompt using a few-shot strategy for Watsonx AI to generate a legal contract summary. You provide two examples of contract summaries before asking the model to summarize a new contract.
Which of the following options best demonstrates an effective few-shot prompt for this task?

A) "Provide a summary of the following contract: [New Contract].
Example 1: [First Contract]
Summary: [First Contract Summary]
Example 2: [Second Contract]
Summary: [Second Contract Summary]."
B) "Example 1: [First Contract]
C) "Generate a summary for [New Contract]."
D) "Example 1: [First Contract] Summary: [First Contract Summary]
Example 2: [Second Contract] Summary: [Second Contract Summary]
Generate a summary of the following contract: [New Contract]."

Solutions: