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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q37-Q42):

NEW QUESTION # 37
In a Retrieval-Augmented Generation (RAG) system designed for technical document retrieval, you are tasked with implementing text chunking techniques using the LangChain library. The technical documents are large and contain numerous tables, figures, and bullet points.
What is the most effective way to handle text splitting to ensure high-quality retrieval?

A. Use a hybrid approach, splitting the text by both semantic boundaries (like paragraphs) and content-specific markers (like bullet points and tables), while keeping chunks within the model's token limit.
B. Split the text into equal-sized chunks of 512 characters, regardless of the content structure, to improve consistency in retrieval.
C. Convert tables and figures into plain text and split the document by character count to maintain even chunk sizes.
D. Split the text only at paragraph breaks, ignoring tables and figures, as they can be processed separately.

Answer: A

NEW QUESTION # 38
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. Using tone adjustments to modify the emotional tone or style of the AI's responses.
B. Adjusting the context window to include or exclude specific sections of input text.
C. Adding dynamic variables to the prompt, allowing for flexible and context-specific responses.
D. Setting conditions within the prompt to handle different scenarios based on detected input patterns.

Answer: A

NEW QUESTION # 39
In the context of AI governance, what is the most important aspect of managing model performance in a production environment to ensure compliance with regulatory and ethical guidelines?

A. Deploying the model only in secure, on-premises environments to prevent data breaches
B. Minimizing the model's inference time to optimize user experience
C. Ensuring traceability of model decisions and providing auditability for each inference
D. Maximizing the number of datasets the model is trained on to cover more use cases

Answer: C

NEW QUESTION # 40
You are working on optimizing a generative AI model that will handle large-scale text generation tasks. The current model is slow during inference, and you need to improve its performance without increasing operational costs. You decide to use IBM Tuning Studio for optimization.
Which of the following is the most significant benefit of using Tuning Studio in this scenario?

A. It provides guidance on reducing the number of parameters in the model to improve inference speed.
B. It automatically scales the model up or down depending on the input data size.
C. It pre-loads commonly used datasets, reducing the need for data handling during the training process.
D. It optimizes hyperparameters such as learning rate and batch size to reduce computational overhead during inference.

Answer: D

NEW QUESTION # 41
In IBM Watsonx's Prompt Lab, example input prompts can be used to improve the effectiveness of generated responses.
Which of the following best describes a key benefit of utilizing example input prompts in Prompt Lab?

A. Example input prompts allow the model to learn new concepts and update its knowledge base dynamically.
B. Example input prompts help generate responses that are more aligned with the specific context or style intended by the user.
C. Example input prompts guarantee consistency across all outputs, regardless of variability in user-provided data.
D. Example input prompts automatically adjust the model's training dataset for more accurate predictions.

Answer: B

NEW QUESTION # 42
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