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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q348-Q353):

NEW QUESTION # 348
How can developers best ensure that prompt templates are version-controlled and any changes to the templates can be tracked efficiently in a collaborative team environment?

A. Manually keep a changelog of prompt template modifications in a shared document
B. Use a centralized cloud storage system that automatically saves all versions of the prompt templates
C. Implement a versioning system for prompt templates in a source control tool like Git
D. Update prompt templates directly in production and rely on error logs for tracking changes

Answer: C

NEW QUESTION # 349
You are developing a machine learning pipeline using IBM watsonx that includes fine-tuning an LLM with a dataset containing sensitive personal information. To ensure privacy, you decide to apply differential privacy.
Which of the following actions is most critical to configure in the user interface to meet the differential privacy requirements during model fine-tuning?

A. Apply a differential privacy mechanism that adds calibrated noise to both the model updates and synthetic data generation process.
B. Remove differential privacy settings for fine-tuning, but apply them in the final inference model to reduce performance degradation.
C. Use synthetic data only, which eliminates the need for differential privacy as it does not contain real user information.
D. Increase the learning rate and batch size to maximize the noise added by differential privacy algorithms.

Answer: A

NEW QUESTION # 350
Which of the following is a key component of IBM's InstructLab framework for customizing large language models (LLMs)?

A. Tools to iteratively optimize the model's alignment with human preferences, such as reinforcement learning from human feedback (RLHF)
B. A tokenization algorithm designed to reduce model size by removing unused tokens
C. Prompt engineering module designed to automatically generate synthetic training data for prompt-tuned models
D. A fine-tuning mechanism based on few-shot learning that only updates the model's output layer

Answer: A

NEW QUESTION # 351
You are working on generating creative text responses using IBM watsonx's generative AI model. You need to adjust the output so that it is more diverse and creative without losing coherence.
Which of the following model parameter settings would best achieve this objective?

A. Set temperature to 0.2
B. Set temperature to 2
C. Set temperature to 0
D. Set temperature to 1.5

Answer: D

NEW QUESTION # 352
You are building a RAG system in IBM watsonx for a legal document retrieval platform. The platform deals with highly structured legal texts and unstructured client queries. Your task is to ensure that both structured documents and unstructured queries can be efficiently retrieved using vector embeddings generated by the system.
Which of the following actions will help you optimize the generation of vector embeddings to support accurate retrieval in the RAG system, considering the diverse data types? (Select two)

A. Fine-tune the embedding model on legal text data to ensure embeddings capture the specific structure and semantics of the documents.
B. Use a separate embedding model for legal documents and client queries to account for differences in data structure.
C. Generate embeddings for legal documents at the sentence level rather than the document level, as this increases precision in retrieval.
D. Rely on pre-trained general-purpose embeddings without any domain-specific adaptation, as they provide broad coverage across many industries.
E. Ensure that embeddings for legal documents are based solely on the document metadata, as it contains the most important information.

Answer: A,B

NEW QUESTION # 353
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