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IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. You are working with IBM Watsonx to develop a generative AI solution that automatically generates product descriptions for an e-commerce website. The descriptions need to be concise, factual, and include important product features like size, color, and material.
Which prompt design approach would best ensure the output meets these requirements?

A) "Generate a creative and imaginative product description for the items listed below."
B) "Write a summary that provides information on each product, making the content engaging, humorous, and memorable."
C) "Generate a product description that highlights the unique aspects of the product and uses emotional language to engage the reader."
D) "Provide a product description for the following items, ensuring it is factual, concise, and includes specific details such as size, color, and material."

2. When addressing bias in a generative AI model, which of the following strategies is least likely to be effective in reducing biased outputs during text generation?

A) Incorporating fairness constraints during the model's training phase
B) Training the model on a diverse and representative dataset
C) Leveraging prompt rephrasing techniques to remove bias-inducing keywords or phrases
D) Using temperature control during generation to manage diversity in responses

3. You are working with a foundation model pre-trained on a large general-purpose dataset, and you plan to deploy it for a specialized task in healthcare-related text generation. However, before tuning the model, you want to assess whether tuning is necessary for your use case.
Which of the following is the best indicator that it is time to tune the foundation model for your task?

A) The model's inference time is longer than expected, and you need to reduce latency for real-time applications.
B) The model performs well on general datasets but fails to capture specific domain-related terminology and context.
C) You are noticing that the model occasionally makes grammar mistakes in the generated text.
D) The model's accuracy is already above 90%, but you want to achieve 95% accuracy for your task.

4. You are optimizing a Generative AI model for a business application where cost savings are a priority.
Which of the following modifications to the model's parameters will most effectively reduce the overall generation cost while minimizing the loss of output quality?

A) Reduce the number of layers in the neural network during inference.
B) Decrease the model's context window size.
C) Set a lower value for the frequency penalty parameter.
D) Set a lower value for the top-p (nucleus sampling) parameter.

5. 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?

A) Perform real-time continuous training of the model using live data from the production environment
B) Implement a model performance monitoring framework with fairness and bias detection metrics
C) Deploy the model with hard-coded rules to ensure it does not drift from expected behavior
D) Ensure model interpretability is maximized by simplifying the architecture to a linear model

Solutions: