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IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. IBM Watsonx's Prompt Lab offers various options to refine prompts for generating more effective AI outputs.
Which of the following is an accurate description of an editing option available in Prompt Lab?

A) Users can use Prompt Lab to train the AI model on new datasets and retrain it based on prompt performance.
B) Prompt Lab allows users to experiment with prompt structures, such as adjusting token limits or adding contextual instructions, to improve responses.
C) Users can apply real-time machine learning to modify the underlying model parameters within Prompt Lab.
D) Users can disable the model's access to certain pre-trained knowledge domains within Prompt Lab to focus its output on specific areas.

2. You are generating product descriptions for an online marketplace using a generative AI model. The output is coherent but tends to repeat the same phrases and words excessively. You decide to apply a repetition penalty to reduce this repetition while keeping the temperature set to a value that maintains creativity in the text generation.
Which of the following adjustments would best achieve this goal?

A) Set repetition penalty to 1.5 and maintain temperature at 0.8
B) Set repetition penalty to 0.0
C) Set repetition penalty to 1.0 and decrease temperature from 0.8 to 0.3
D) Set repetition penalty to 2.0 and increase temperature from 0.7 to 1.2

3. A financial institution is using a generative AI model to create reports based on transaction data. During deployment, the institution notices that the model sometimes fabricates trends or patterns that do not exist in the underlying data. This is an example of a hallucination.
Which of the following techniques would best minimize this risk during inference?

A) Increase the top-p value to ensure more tokens are considered during generation.
B) Reduce the model size to decrease its capacity to hallucinate complex patterns.
C) Use a retrieval-augmented generation (RAG) model that incorporates external financial data into the generation process.
D) Disable the model's autoregressive capability to prevent it from generating future predictions.

4. You are working on a Retrieval-Augmented Generation (RAG) system to enhance the performance of a generative model. The RAG model needs to leverage a document corpus to generate answers to complex questions.
Which of the following steps is critical in the RAG pipeline to ensure accurate and relevant answer generation?

A) Retrieving only the longest document in the corpus as the generative model can synthesize information more effectively from detailed content.
B) Fine-tuning the generative model on the entire document corpus without retrieval components.
C) Using keyword-based search to retrieve documents and then allowing the generative model to synthesize answers from those documents.
D) Indexing the document corpus using embeddings, retrieving relevant documents, and feeding them as context into the generative model.

5. You're designing a prompt that should generate text for product descriptions using a generative AI model. You want to limit the model's word choices to ensure coherence while still allowing some flexibility for creativity. You decide to use Top-P (nucleus) sampling to achieve this.
Which of the following settings for the Top-P parameter is most appropriate to strike a balance between creativity and coherence?

A) Top-P = 0.3
B) Top-P = 0.1
C) Top-P = 0.9
D) Top-P = 1.0

Solutions: