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IBM watsonx Generative AI Engineer - Associate Sample Questions (Q36-Q41):

NEW QUESTION # 36
You want a generative AI model to summarize a lengthy text in one sentence. You provide the following prompt: "Summarize the following paragraph in one sentence: 'Artificial intelligence (AI) is the simulation of human intelligence in machines that are programmed to think and learn. The field of AI includes everything from speech recognition to problem-solving and robotics.'" No prior examples are given.
What type of prompting is being used, and what are the expectations?

A. Few-shot prompting, but the model will likely struggle without a few examples of summaries provided.
B. Zero-shot prompting, but it requires the addition of a few examples for the model to generate a summary.
C. Zero-shot prompting, but the model may fail without detailed instructions on what aspects of the text to focus on.
D. Zero-shot prompting, with the expectation that the model can summarize common concepts like AI due to pre-training.

Answer: D

NEW QUESTION # 37
When conducting prompt engineering to reduce model risks related to hate speech and abusive content, which of the following strategies is least likely to be effective?

A. Applying ethical guidelines during the fine-tuning of the model to prioritize inclusive language
B. Creating a reward model during Reinforcement Learning to penalize hate speech outputs
C. Increasing the temperature during text generation to encourage more creative outputs
D. Modifying the prompt to include explicit instructions for civil language

Answer: C

NEW QUESTION # 38
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. Users can apply real-time machine learning to modify the underlying model parameters within Prompt Lab.
B. Users can use Prompt Lab to train the AI model on new datasets and retrain it based on prompt performance.
C. Users can disable the model's access to certain pre-trained knowledge domains within Prompt Lab to focus its output on specific areas.
D. Prompt Lab allows users to experiment with prompt structures, such as adjusting token limits or adding contextual instructions, to improve responses.

Answer: D

NEW QUESTION # 39
IBM Watsonx Tuning Studio allows users to fine-tune pre-trained models for their specific use cases.
Which of the following correctly describes the primary benefits of using Tuning Studio for optimizing a generative AI model?

A. It enables on-the-fly model optimization during inference, adjusting model weights dynamically based on real-time data input.
B. It significantly reduces the computational costs associated with model fine-tuning by only updating the model's parameters relevant to the specific task, preserving the general knowledge of the base model.
C. It fully retrains the base model from scratch, ensuring the highest possible accuracy for each new task, regardless of prior training.
D. It allows users to add new architectural layers to the model to improve accuracy without retraining the entire model.

Answer: B

NEW QUESTION # 40
You are optimizing a generative AI prompt for creative content generation, but you want to ensure that outputs with the same prompt can vary slightly across multiple runs to maintain freshness in the responses.
Which parameter should you adjust to strike a balance between random variability and consistent quality?

A. Set a fixed Random Seed to zero
B. Temperature = 0.1, Random Seed unset
C. Top-p = 0.9, Temperature = 1.0, Random Seed unset
D. Max Tokens = 300, Random Seed set to 42

Answer: C

NEW QUESTION # 41
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