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IBM watsonx Generative AI Engineer - Associate Sample Questions:

1. A generative AI model is given the following prompt: "Translate the following sentence into French: 'The sun is shining brightly today.'" No additional context or examples are provided.
This is an example of which type of prompting and why is it likely to succeed?

A) Zero-shot prompting, but it will only succeed if the prompt includes a few additional translation examples.
B) Zero-shot prompting, because the model is expected to perform the task without any example.
C) Few-shot prompting, because the task requires translation examples to guide the model.
D) Zero-shot prompting, but it will likely fail since translation tasks always need examples for accuracy.

2. In the context of generative AI, you are tasked with optimizing a model's performance for a variety of use cases by tuning the prompts. One of your colleagues mentions using a "soft prompt" to improve the model's adaptability.
What best describes the difference between a hard prompt and a soft prompt?

A) Hard prompts are less efficient because they need to be re-trained with each task, while soft prompts are more versatile and adaptive across multiple tasks.
B) A soft prompt is a fixed string of text used in fine-tuning, while a hard prompt adjusts dynamically based on input data.
C) Soft prompts are more readable and natural, whereas hard prompts consist of short, technical instructions.
D) A hard prompt explicitly specifies all constraints, while a soft prompt relies on implicit learning from continuous inputs during training.

3. You are tasked with optimizing the cost of text generation using a generative AI model by adjusting model parameters. One of the key parameters you consider is the temperature, which controls the randomness of the output. The client has requested outputs that are more predictable and closer to the intended meaning, without unnecessary creativity, in order to reduce unnecessary token usage and ensure the quality of generated responses. Given the following task:
"Generate a brief summary of a technical article that focuses on key innovations without including unrelated or creative content." Which of the following temperature settings would be most appropriate to optimize cost while maintaining focus and minimizing unnecessary token usage?

A) 1.0
B) 0.1
C) 0.0
D) 1.2

4. 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

5. Which of the following best describes the process of large-scale iterative alignment tuning in the context of customizing LLMs with InstructLab?

A) Repeated fine-tuning of a model using reinforcement learning, focusing on aligning its outputs with human preferences across a diverse set of tasks
B) Fine-tuning the model exclusively on binary classification tasks to improve its generalization on all other tasks
C) A single training run of the model on a dataset to generate better predictions for a fixed number of prompts
D) Direct training of the model on an expanded version of the dataset, without adjusting prompts or training tasks

Solutions: