Module 3: Course Quiz, Project, and Wrap-up
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Graded Quiz - Generative AI: Prompt Engineering Basics
Graded Assignment
1. What is the first step in writing a well-structured prompt through the process of prompt engineering?
- Refining the prompt based on testing and analysis
- Testing the prompt for response quality
- Analyzing responses from the generative AI model
- Defining the goal ✅
Explanation:
The first step is to clearly define the goal of the prompt, ensuring that you understand what you want to achieve with the generative AI model before refining or testing it.
2. Why is clarity important when writing prompts for generative AI models?
- Clarity helps the model understand the task and produce relevant responses ✅
- Clarity ensures the prompt is lengthy
- Clarity helps make the prompt less engaging
- Clarity adds to the complexity of the prompt
Explanation:
A clear prompt guides the AI model in understanding what is expected, leading to more relevant and accurate responses.
3. Which of the following is the main purpose of using the user feedback loop?
- To generate responses with examples
- To generate meaningful responses without needing prior training on specific prompts
- To iteratively refine text prompts based on the response generated by the LLM ✅
- To provide explicit instructions to generate neutral responses
Explanation:
The user feedback loop helps improve prompts by refining them based on AI-generated responses, ensuring better accuracy and quality.
4. How does the Tree-of-Thoughts approach differ from traditional linear prompting approaches?
- It eliminates all possible routes of thinking
- It explores multiple possibilities simultaneously using a hierarchical structure ✅
- It makes random decisions
- It encourages linear thinking
Explanation:
The Tree-of-Thoughts approach explores various possibilities at once in a structured way, unlike linear prompting, which follows a single path of reasoning.
5. What is the primary goal of prompt engineering tools?
- To provide suggestions for improving NLP techniques.
- To design user-friendly interface for generative AI models.
- To create applications for language model experiments.
- To optimize the creation of prompts for generative AI models. ✅
Explanation:
Prompt engineering tools help create and refine prompts to ensure the best possible interaction with generative AI models.
6. Which among the following statements is accurate about the Tree-of-Thought approach?
- The Tree-of-Thought approach only works for generating responses to marketing-related prompts.
- The Tree-of-Thought approach eliminates the need for any prompt instructions or constraints.
- The Tree-of-Thought approach is less effective than the Chain-of-Thought approach for generative AI reasoning.
- The Tree-of-Thought approach enables generative AI models to explore multiple paths simultaneously and assess potential outcomes. ✅
Explanation:
This approach allows the model to evaluate various paths and scenarios, helping to make more comprehensive and nuanced decisions.
7. Which among the following is a platform of integrated tools that can be used to train, tune, deploy, and manage foundation models?
- IBM watsonx.ai ✅
- Dust
- PromptPerfect
- Spellbook
Explanation:
IBM watsonx.ai is an integrated platform designed to handle foundation models for training, tuning, and deployment.