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Generative AI Instructor
This quiz assesses your understanding of the key strategies and best practices for crafting effective prompts to maximize the quality and relevance of responses from generative AI models.
1. Why is specificity important when crafting prompts for a generative AI model?
a) It helps reduce the model’s memory usage.
b) It guides the model to generate more accurate and relevant responses.
c) It prevents the model from generating long responses.
d) It makes the model more creative.
2. Which phrase is commonly used to establish a persona for the model?
a) “Write a story about…”
b) “Act as…”
c) “Summarize the following…”
d) “Provide an answer…”
3. What is the main purpose of using delimiters (e.g., triple quotes or XML tags) in prompts?
a) To make the model generate more words.
b) To help organize complex tasks and clarify different parts of the prompt.
c) To confuse the model into generating unexpected responses.
d) To reduce the length of responses.
4. What is a key benefit of breaking down a complex task into smaller, sequential steps?
a) It simplifies the model’s understanding of the task and leads to more accurate responses.
b) It makes the task appear more complicated to the model.
c) It prevents the model from understanding the task at all.
d) It causes the model to produce longer responses.
5. In which type of prompting do you provide one example for the model to generate a response?
a) Zero-shot prompting
b) One-shot prompting
c) Few-shot prompting
d) Multi-shot prompting
6. What is the main advantage of using reference text in a prompt?
a) It makes the model generate creative responses.
b) It provides the model with factual information to base its response on, improving accuracy.
c) It reduces the model’s output length.
d) It helps the model avoid generating multiple responses.
7. How can you guide the length of the output from the model?
a) By specifying an exact word count in the prompt.
b) By asking the model to provide bullet points, sections, or concise summaries.
c) By giving the model access to longer documents.
d) By repeatedly requesting shorter outputs.
8. What does using a Unique Token ID in a prompt help you achieve?
a) It increases the model's creativity.
b) It focuses the model on specific sections of a complex prompt.
c) It reduces the accuracy of the response.
d) It prevents the model from answering any questions.
9. Which of the following is an example of few-shot prompting?
a) “Analyze the sentiment of the following review.”
b) “Here’s an example of a positive sentiment: ‘Great service!’ Now, analyze: ‘The product was disappointing.’”
c) “Summarize the article in one sentence.”
d) “Write a poem about a dog.”
10. What is the purpose of using anchoring phrases like "Based on the previous information..." in a prompt?
a) To confuse the model.
b) To provide necessary context and ensure coherent responses.
c) To reduce the model’s ability to generate creative content.
d) To limit the model’s response length.
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Answer Key:
b) It guides the model to generate more accurate and relevant responses.
b) “Act as…”
b) To help organize complex tasks and clarify different parts of the prompt.
a) It simplifies the model’s understanding of the task and leads to more accurate responses.
b) One-shot prompting
b) It provides the model with factual information to base its response on, improving accuracy.
b) By asking the model to provide bullet points, sections, or concise summaries.
b) It focuses the model on specific sections of a complex prompt.
b) “Here’s an example of a positive sentiment: ‘Great service!’ Now, analyze: ‘The product was disappointing.’”
b) To provide necessary context and ensure coherent responses.