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IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. You are tasked with creating a prompt template for generating environment descriptions in a generative AI model, which will be used for creating immersive virtual spaces.
Which of the following prompt best serves as a flexible template to generate diverse environment descriptions?

A) "Write about a dense jungle where wild animals roam freely, and the atmosphere is tense, full of suspense."
B) "Describe an environment where {mood} dominates, with {surroundings} contributing to the overall {atmosphere}. Include {time_of_day} and any other important details."
C) "Describe a futuristic city with towering skyscrapers and flying cars."
D) "Create a detailed description of a quiet forest during sunrise, focusing on the natural beauty of the trees, birds, and atmosphere."

2. You are tasked with building a generative AI model to help create automated marketing copy for a business. A key concern is the potential generation of biased or legally sensitive content, which could negatively impact the company's reputation.
Which of the following strategies would be the most effective in mitigating these model risks?

A) Use a comprehensive training dataset that includes diverse business domains to reduce biases.
B) Include fairness metrics in the model evaluation stage to monitor for biased outputs.
C) Use reinforcement learning to fine-tune the model based on user feedback to eliminate bias in the long term.
D) Implement a post-processing filter to remove any potentially offensive or legally sensitive content.

3. You are tasked with creating a prompt-tuned model using IBM watsonx.ai to enhance the quality of text generation for customer support. The goal is to fine-tune the model for improved context understanding based on specific customer queries.
Which of the following approaches would be the best method to initialize the prompt for tuning?

A) Construct a prompt using a large set of random tokens from the training corpus
B) Use a pre-trained general-purpose prompt with no domain-specific customization
C) Use a manually crafted prompt tailored to the specific context of customer support queries
D) Use a prompt with pre-defined output patterns to restrict the model's possible responses

4. Which of the following decoding strategies would most likely result in generating creative and diverse text outputs while minimizing repetition, when using a generative AI model?

A) Beam Search Decoding with a small beam size (e.g., 2)
B) Temperature Sampling with temperature = 0.0
C) Nucleus Sampling (Top-p) with p = 0.9
D) Greedy Decoding

5. You are tasked with building a customer service chatbot powered by a generative AI model for a large financial institution. Customers often provide sensitive personal and financial information in their queries.
What is the best method to ensure the model does not generate responses containing sensitive personal data?

A) Implement differential privacy to reduce the likelihood that sensitive data from user inputs is exposed in the model's responses.
B) Use supervised fine-tuning to train the model on data that excludes all personally identifiable information (PII).
C) Limit the model's ability to generate personalized responses by focusing on generalized outputs, reducing the risk of data exposure.
D) Restrict the model to only respond to predefined template-based answers to eliminate the risk of personal data being generated.

Solutions: