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IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. You are tasked with building a Retrieval-Augmented Generation (RAG) system using Elasticsearch for document storage, Watson ML for model hosting, and LangChain for orchestration. The chatbot is supposed to query a large database of medical records and generate responses based on the retrieved information. During testing, you notice that irrelevant documents are often retrieved, leading to low-quality responses.
What would be the best approach to improve document relevance in this RAG setup?

A) Implement a BM25 similarity algorithm in Elasticsearch to improve document retrieval.
B) Fine-tune the Watson ML model on a dataset containing both queries and relevant documents, then update Elasticsearch with the model outputs.
C) Pre-process the medical records in LangChain to remove irrelevant information before sending the query to Elasticsearch.
D) Update the Elasticsearch index by re-indexing documents using embeddings from the Watson ML model.

2. Which prompt engineering strategy is most effective for reducing the risk of generating biased content in a generative AI model?

A) Adjusting the model's temperature to a lower value to generate more deterministic and consistent outputs.
B) Designing prompts that explicitly ask for balanced perspectives, such as "Provide both pros and cons of this issue."
C) Using a larger number of examples in the prompt to steer the model towards safer and more neutral outputs.
D) Including specific disclaimers or guidelines in the prompt instructing the model to avoid biased language.

3. While optimizing the cost of running a Generative AI model, you are instructed to adjust the prompt structure.
Which of the following changes to a prompt would most reduce computational costs while still maintaining effective results?

A) Breaking complex prompts into simpler, sequential prompts.
B) Using stop tokens early in the prompt to minimize generation length.
C) Including multiple tasks in a single prompt to maximize efficiency.
D) Switching from a narrative-style prompt to a bulleted list format.

4. You are using IBM watsonx Prompt Lab to experiment with different versions of a prompt to generate accurate and creative responses for a customer support chatbot.
Which of the following best describes a key benefit of using Prompt Lab in the process of prompt engineering?

A) It provides a real-time environment for testing and refining prompts, helping to improve response quality.
B) It allows users to generate AI models without the need for training data.
C) It limits the number of iterations a user can test to prevent overfitting the prompt to specific outputs.
D) It automatically generates prompts based on industry-specific data without any user input.

5. When addressing bias in a generative AI model, which of the following strategies is least likely to be effective in reducing biased outputs during text generation?

A) Using temperature control during generation to manage diversity in responses
B) Leveraging prompt rephrasing techniques to remove bias-inducing keywords or phrases
C) Training the model on a diverse and representative dataset
D) Incorporating fairness constraints during the model's training phase

Solutions: