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IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. In the context of AI governance, what is the most important aspect of managing model performance in a production environment to ensure compliance with regulatory and ethical guidelines?

A) Ensuring traceability of model decisions and providing auditability for each inference
B) Minimizing the model's inference time to optimize user experience
C) Deploying the model only in secure, on-premises environments to prevent data breaches
D) Maximizing the number of datasets the model is trained on to cover more use cases

2. You are tasked with generating creative text outputs using an AI language model for a marketing campaign. You want to ensure that the responses are diverse and unexpected but still somewhat relevant to the prompt.
Which combination of temperature and random seed should you use to achieve this?

A) Temperature: 0.7, Random Seed: None
B) Temperature: 1.0, Random Seed: 0
C) Temperature: 0.1, Random Seed: 42
D) Temperature: 1.5, Random Seed: 123

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

4. In the lifecycle of deploying a prompt template for a generative AI solution, which of the following best describes the stage where user feedback is integrated to refine the template's performance?

A) Deployment to production with regular monitoring and logging
B) Retraining the model based on emerging trends in data
C) Iterative prompt tuning based on A/B test results and feedback loops
D) Initial testing on synthetic datasets and model validation

5. A developer is using a GitHub Code Retrieval API to help build a search engine that can locate relevant code snippets from public repositories. The API is designed to retrieve code based on the semantic similarity of the query (e.g., a description of what the code does) to the code itself.
What is the primary advantage of using a vector-based approach for code retrieval in this scenario?

A) It retrieves code snippets based on the semantic similarity between the query and the code, enabling the discovery of relevant code even when the query and code do not use the same keywords.
B) It ensures that the code snippets returned are exact matches to the keywords in the query, avoiding irrelevant code.
C) It speeds up retrieval by limiting the search to repositories where the user has committed code in the past.
D) It provides real-time updates to the code embeddings, ensuring the latest code is always retrieved.

Solutions: