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IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. When optimizing a prompt-tuned model, which parameter adjustment would most likely help prevent overfitting without negatively impacting the model's ability to generalize to unseen prompts?

A) Reducing the model's learning rate
B) Increasing the model's dropout rate
C) Removing weight decay entirely
D) Increasing the model's learning rate

2. In the context of a Retrieval-Augmented Generation (RAG) system, which type of retriever is best suited for retrieving documents based on semantic similarity in a vector space?

A) Boolean retriever, which uses logical operators (AND, OR, NOT) to filter documents based on keyword presence.
B) Exact match retriever, which retrieves documents that exactly match the query string.
C) Dense retriever, which converts both the query and documents into vectors and retrieves based on similarity in the vector space.
D) Hierarchical retriever, which first applies keyword-based filters and then ranks documents using machine learning models.

3. You are fine-tuning a general-purpose language model on a medical dataset to generate summaries of patient consultations. After fine-tuning, you notice that the model sometimes generates hallucinations-statements that are factually incorrect or irrelevant to the specific domain. You suspect that the fine-tuning process did not sufficiently align the model with the medical domain.
Which of the following is the most effective technique to reduce hallucinations during fine-tuning?

A) Increase the model's batch size during training
B) Use domain-specific tokenization during fine-tuning
C) Add more general-purpose data to the fine-tuning dataset
D) Increase the number of layers in the model

4. You are experimenting with a generative AI model to write a personalized email response template. You want to ensure that the output maintains a formal tone but occasionally produces creative phrasing without making nonsensical sentences. You are advised to adjust the top-p (nucleus sampling) parameter.
Which of the following settings would most effectively balance between formal coherence and occasional creativity in the generated output?

A) Set top-p to 1.0
B) Set top-p to 0.5
C) Set top-p to 0.0
D) Set top-p to 0.95

5. In IBM Watsonx's Prompt Lab, you are refining a prompt to improve the clarity and relevance of the AI's responses. You need to understand which prompt editing options are available to optimize your results.
Which of the following is NOT an available prompt editing option?

A) Setting conditions within the prompt to handle different scenarios based on detected input patterns.
B) Adding dynamic variables to the prompt, allowing for flexible and context-specific responses.
C) Adjusting the context window to include or exclude specific sections of input text.
D) Using tone adjustments to modify the emotional tone or style of the AI's responses.

Solutions: