IBM C1000-185 - IBM watsonx Generative AI Engineer - Associate

You are building a RAG system that integrates LlamaIndex for efficient document retrieval from a knowledge base containing millions of documents.
Which of the following is the most critical consideration for ensuring the system performs well at scale?

• A. Ensuring LlamaIndex generates unique embedding vectors for each document and storing them in an optimized vector database for quick lookups.
• B. Adjusting LlamaIndex to prioritize documents that contain certain predefined keywords, optimizing retrieval for specific business terms.
• C. Setting LlamaIndex to index only a small subset of the documents to minimize the time it takes to retrieve any relevant document.
• D. Configuring LlamaIndex to perform real-time indexing of incoming data streams to ensure the most up-to-date documents are always retrieved.

You are tasked with deploying a versioned prompt for a customer-facing generative AI application. The prompts are iteratively improved based on feedback, and you need to ensure that each version of the prompt is tracked and accessible for rollback in case a newer version produces worse results.
Which strategy would best ensure that all prompt versions are stored and easily retrievable, while minimizing disruption to the current deployment?

• A. Leverage a cloud-based deployment pipeline with integrated versioning that automates prompt rollback and audit tracking.
• B. Deploy prompts directly to production without versioning and manually track changes in a spreadsheet.
• C. Store each version of the prompt as a separate file in a local folder and manually deploy the desired version when needed.
• D. Use a version control system like Git to track prompt changes and synchronize the latest version with the deployment environment.

You are designing a generative AI model to generate customer support responses. During testing, you notice that the model frequently outputs gendered language when referring to certain professions, reinforcing stereotypes.
Which of the following strategies would most effectively reduce bias in the model' responses?

• A. Increase the diversity of the dataset used to train the model, ensuring that all professions are equally represented.
• B. Apply a post-processing filter that removes any gendered language after the model generates the response.
• C. Train the model with a lower learning rate to make it less sensitive to biased patterns in the data.
• D. Reduce the maximum token limit so that the model generates shorter responses, minimizing the chance for bias.

IBM Watsonx Tuning Studio offers several benefits when fine-tuning pre-trained models for specific tasks.
Which of the following is not a key benefit of using Tuning Studio?

• A. Tuning Studio integrates with existing AI infrastructure to streamline model fine-tuning without requiring complex deployment processes.
• B. Tuning Studio enables real-time, dynamic adjustments to the model's architecture during inference to handle new tasks.
• C. Tuning Studio offers fine-tuning with minimal data, allowing users to adapt models to niche tasks without needing large datasets.
• D. Tuning Studio allows selective parameter updates, reducing the need to retrain the entire model for each new task.

In a generative AI model, you are tasked with producing creative yet coherent text for a marketing campaign. You want to ensure that the output contains varied word choices and diverse sentence structures while still maintaining some degree of logical consistency.
Which of the following settings for the temperature parameter would most likely achieve this balance?

• A. Temperature = 0.2
• B. Temperature = 2.0
• C. Temperature = 0.7
• D. Temperature = 0.0