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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q366-Q371):

NEW QUESTION # 366
In a Retrieval-Augmented Generation (RAG) system, the retriever plays a crucial role in retrieving relevant documents or passages from a knowledge base.
What is the primary function of a retriever in this architecture?

A. The retriever finds and retrieves documents from a knowledge base that are semantically similar to the input query, often using vector embeddings to compare similarity.
B. The retriever performs tokenization and splitting of large documents into smaller chunks, making them easier to index.
C. The retriever generates the final response based on the retrieved documents and the user's query.
D. The retriever modifies the transformer-based model's weights in real-time to improve the relevance of future retrievals.

Answer: A

NEW QUESTION # 367
In prompt engineering, prompt variables are used to make your prompts more dynamic and reusable.
Which of the following statements best describes a key benefit of using prompt variables in IBM Watsonx Generative AI?

A. Prompt variables eliminate the need to change model parameters every time you generate a new response.
B. Prompt variables ensure that the AI's response format will always be consistent, regardless of the input data.
C. Prompt variables automatically improve the accuracy of responses by reducing model variance.
D. Prompt variables allow a single prompt template to handle multiple data points or scenarios by inserting different values.

Answer: D

NEW QUESTION # 368
A client is planning to deploy a Watsonx Generative AI model and has raised concerns about ethical usage, bias, and accountability in decision-making.
Which of the following is the most critical step to ensure AI governance during the deployment phase of the model?

A. Training the model on additional data to improve accuracy
B. Testing the model's accuracy on a large set of random data
C. Monitoring and auditing AI decisions for bias and fairness
D. Implementing a feedback loop for continuous model improvement

Answer: C

NEW QUESTION # 369
When using few-shot prompting, which of the following is a common limitation you may encounter while working with Watsonx AI for text generation tasks?

A. The model may overfit to the few examples provided, leading to overly specific responses.
B. Few-shot prompting requires the model to be retrained with additional examples.
C. Few-shot prompting is only effective for classification tasks and cannot be used for text generation.
D. Few-shot prompting cannot handle open-ended tasks, as it only works for structured data inputs.

Answer: A

NEW QUESTION # 370
You are using IBM's Tuning Studio to fine-tune a large-scale foundation model for a customer service chatbot. The goal is to optimize the model for performance in handling a wide variety of customer queries while minimizing computational costs. Before making any changes, you want to understand how Tuning Studio can help achieve your optimization goals.
Which of the following is the most significant benefit provided by Tuning Studio when optimizing a generative AI model?

A. Tuning Studio provides real-time monitoring of model performance metrics during the fine-tuning process, allowing you to adjust hyperparameters effectively.
B. Tuning Studio allows the user to implement custom model architectures from scratch to meet specific task requirements.
C. Tuning Studio automatically deploys the fine-tuned model to production environments without requiring further testing.
D. Tuning Studio reduces the dataset size needed for training by implementing automated data augmentation strategies.

Answer: A

NEW QUESTION # 371
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