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IBM C1000-185 Exam Syllabus Topics:

IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. A financial services company is building a generative AI model to assist with customer support. The company is concerned about potential legal liabilities if the model generates customer information, such as bank account numbers or personal identification data, as part of its responses.
Which of the following techniques would best mitigate the risk of generating Personally Identifiable Information (PII) during inference?

A) Train the model on sensitive customer data but ensure that the temperature is set low to avoid generating diverse outputs.
B) Use greedy decoding to ensure the model generates only the most probable tokens, which are less likely to include PII.
C) Implement a real-time PII filter that detects and removes sensitive data before the output is presented to the user.
D) Set a strict token limit to prevent the model from generating long sequences, assuming PII tends to appear in longer outputs.

2. In a project where watsonx.ai is deployed as the core generative model for text generation, you need to augment its capabilities by integrating it with IBM Watson Discovery to access a large corpus of documents for fact-checking and data retrieval.
What is the best way to integrate these two services to ensure that generated responses are both creative and factual?

A) Use watsonx.ai to generate all responses, and periodically train the model using data indexed by Watson Discovery.
B) Train watsonx.ai to automatically search Watson Discovery for factual information during the text generation process, eliminating the need for an external integration layer.
C) Deploy a custom API layer that combines watsonx.ai with Watson Assistant, letting the latter manage queries and retrieve documents from Watson Discovery on demand.
D) Have Watson Discovery preprocess user inputs to identify relevant documents, and then feed the retrieved information into watsonx.ai as a context for text generation.

3. A company is using IBM's InstructLab to fine-tune a large language model (LLM) to perform customer support tasks, such as answering frequently asked questions (FAQs) and troubleshooting product issues.
Which of the following components of InstructLab plays the most crucial role in ensuring the model learns to align its responses with the specific format and tone required for customer interactions?

A) The evaluation metrics dashboard, which tracks model performance on customer interaction tasks.
B) The user simulation environment, which provides real-time testing of model outputs.
C) The prompt-tuning engine, which fine-tunes model outputs based on pre-defined instructions.
D) The instruction optimizer, which tunes hyperparameters to improve task-specific performance.

4. You are tuning a generative AI model to control the length of the generated responses.
Which of the following parameter configurations will ensure that the model generates responses that are at least 50 tokens long but no longer than 150 tokens?

A) Setting no minimum token value but configuring the maximum tokens to 150
B) Setting the minimum tokens to 150 and maximum tokens to 50
C) Setting the minimum tokens to 50 and maximum tokens to 150
D) Setting the maximum tokens to 50 and minimum tokens to 150

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

Solutions: