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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q81-Q86):

NEW QUESTION # 81
When optimizing the tuning process in IBM Watsonx Tuning Studio for a Generative AI model, which approach would best reduce training time and computational cost while maintaining model performance?

A. Increase the batch size and reduce the learning rate simultaneously to speed up the tuning process and minimize training iterations.
B. Perform full-scale retraining of the model for each new task to ensure maximum adaptability and accuracy.
C. Use all available training data, including unrelated examples, to ensure the model has a broad understanding of multiple tasks before tuning.
D. Focus the tuning on adjusting only the model's last few layers, which are responsible for task-specific outputs, while leaving the majority of the model unchanged.

Answer: D

NEW QUESTION # 82
A team is implementing a Retrieval-Augmented Generation (RAG) system for document search and retrieval. Their goal is to enable users to retrieve contextually relevant documents from a large, unstructured text corpus. They are considering using a vector database to handle this task.
In which scenario is a vector database the most appropriate choice for storing and retrieving documents?

A. When the system must support real-time updates and frequent data modifications, ensuring that query results always reflect the latest state of the data.
B. When all documents are structured and can be queried using traditional SQL queries, focusing on specific fields and categories.
C. When documents need to be retrieved based on semantic similarity to the user's query, even if the exact terms are not matched.
D. When exact match search is required, such as finding documents containing specific keywords or phrases.

Answer: C

NEW QUESTION # 83
You are tasked with integrating third-party embedding models into a Retrieval-Augmented Generation (RAG) system for document retrieval. Several models offer pre-trained embeddings that can be leveraged for a variety of downstream tasks.
Which of the following third-party models is designed for generating embeddings that capture semantic meaning and context, making it ideal for a RAG-based GenAI system?

A. BERT
B. WordNet
C. Naive Bayes Classifier
D. GPT-3 Embeddings

Answer: A

NEW QUESTION # 84
You are fine-tuning the output behavior of a generative AI model in IBM Watsonx for creative content generation. You decide to adjust the temperature parameter to influence the randomness of the model's output.
Which of the following best describes the effect of increasing the temperature value?

A. Raising the temperature makes the model more likely to repeat tokens, reducing variability in its responses.
B. A higher temperature setting reduces the length of the generated output by limiting the number of tokens in each response.
C. Raising the temperature encourages the model to consider less likely tokens, leading to more diverse and creative outputs.
D. Increasing the temperature makes the model generate more deterministic responses by always selecting the most probable token at each step.

Answer: C

NEW QUESTION # 85
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. Monitoring and auditing AI decisions for bias and fairness
B. Testing the model's accuracy on a large set of random data
C. Implementing a feedback loop for continuous model improvement
D. Training the model on additional data to improve accuracy

Answer: A

NEW QUESTION # 86
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