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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q131-Q136):

NEW QUESTION # 131
You are working on generating synthetic training data using IBM InstructLab to supplement a small dataset for a question-answering system.
Which strategy would most effectively enhance the dataset without introducing biases or artifacts?

A. Automatically generate synthetic data using a different model architecture than the one being fine-tuned.
B. Generate a large amount of synthetic data by directly feeding the model with random prompts, ensuring data diversity.
C. Use prompts that closely mimic the structure and semantics of the real dataset's questions to maintain consistency.
D. Manually tweak each generated response to ensure it's free of errors and aligns with the intended task.

Answer: C

NEW QUESTION # 132
IBM Watsonx's Prompt Lab offers various options to refine prompts for generating more effective AI outputs.
Which of the following is an accurate description of an editing option available in Prompt Lab?

A. Prompt Lab allows users to experiment with prompt structures, such as adjusting token limits or adding contextual instructions, to improve responses.
B. Users can disable the model's access to certain pre-trained knowledge domains within Prompt Lab to focus its output on specific areas.
C. Users can use Prompt Lab to train the AI model on new datasets and retrain it based on prompt performance.
D. Users can apply real-time machine learning to modify the underlying model parameters within Prompt Lab.

Answer: A

NEW QUESTION # 133
Which prompt engineering strategy is most effective for reducing the risk of generating biased content in a generative AI model?

A. Adjusting the model's temperature to a lower value to generate more deterministic and consistent outputs.
B. Designing prompts that explicitly ask for balanced perspectives, such as "Provide both pros and cons of this issue."
C. Including specific disclaimers or guidelines in the prompt instructing the model to avoid biased language.
D. Using a larger number of examples in the prompt to steer the model towards safer and more neutral outputs.

Answer: B

NEW QUESTION # 134
Which of the following practices are best suited to optimize the performance of a deployed generative AI model in IBM watsonx under real-world traffic conditions? (Select two)

A. Loading the entire model into memory at runtime to avoid latency issues
B. Using batch processing instead of real-time inference for all requests
C. Monitoring and adjusting resource allocation dynamically based on usage statistics
D. Relying on a single model configuration across all hardware types to simplify deployment
E. Employing model quantization techniques during deployment

Answer: C,E

NEW QUESTION # 135
When debating the drawbacks of soft prompts in a generative AI application, which of the following is the most significant challenge compared to hard prompts?

A. Soft prompts offer simpler debugging processes because the learned embeddings are directly linked to specific model behaviors and outputs.
B. Soft prompts significantly limit the flexibility of the model because they are tied to specific tasks, unlike hard prompts which can generalize to various scenarios.
C. Soft prompts introduce more complexity during the training phase, as the model must learn embeddings that are not inherently interpretable by humans.
D. Soft prompts require more human intervention during generation because they depend on predefined patterns and rules for guidance.

Answer: C

NEW QUESTION # 136
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