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IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. You are tasked with deploying a watsonx Generative AI solution for a client who requires real-time inference with minimal latency. The solution will be used for large-scale text generation tasks, where throughput is critical. The client also requires the system to handle fluctuating loads efficiently.
What would be the most appropriate deployment strategy?

A) Deploy the model in a hybrid architecture, splitting inference tasks between on-premise servers and cloud resources.
B) Deploy the model on a single GPU-based cloud instance with auto-scaling enabled.
C) Deploy the model on a multi-node GPU cluster with Kubernetes to handle auto-scaling and fault tolerance.
D) Use a CPU-based deployment for cost efficiency, and manually adjust the number of instances as needed.

2. You are tasked with designing a prompt to fine-tune an IBM Watsonx model to summarize legal documents. The summaries must include only factual information, highlight key legal terms, and exclude any personal interpretations or subjective analysis.
Which of the following is the best prompt to achieve this goal?

A) "Create a brief summary of this legal document, ensuring to exclude any legal jargon and simplifying the content for a layperson audience."
B) "Generate a detailed and engaging summary of this legal document, adding your insights to clarify complex legal points for the reader."
C) "Summarize this legal document, focusing on key arguments and providing an analysis of the potential outcomes of the case."
D) "Provide a summary of this legal document, focusing on factual information, including key legal terms and avoiding personal interpretation or subjective analysis."

3. You are tasked with designing a prompt using a few-shot strategy for Watsonx AI to generate a legal contract summary. You provide two examples of contract summaries before asking the model to summarize a new contract.
Which of the following options best demonstrates an effective few-shot prompt for this task?

A) "Provide a summary of the following contract: [New Contract].
Example 1: [First Contract]
Summary: [First Contract Summary]
Example 2: [Second Contract]
Summary: [Second Contract Summary]."
B) "Generate a summary for [New Contract]."
C) "Example 1: [First Contract] Summary: [First Contract Summary]
Example 2: [Second Contract] Summary: [Second Contract Summary]
Generate a summary of the following contract: [New Contract]."
D) "Example 1: [First Contract]

4. When designing a generative AI system to minimize the risk of producing hate speech or abusive content, which of the following strategies in prompt engineering is the most effective?

A) Ensure that the model is trained on a larger dataset, even if the dataset contains diverse viewpoints, including some controversial opinions.
B) Use offensive words in prompts to test the model's robustness in handling them.
C) Implement real-time content moderation at the output level rather than relying on input prompts alone.
D) Use strict prompt filtering to block any input that contains offensive words.

5. 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 allows users to add new architectural layers to the model to improve accuracy without retraining the entire model.
D) It fully retrains the base model from scratch, ensuring the highest possible accuracy for each new task, regardless of prior training.

Solutions: