AWS Certified AI Practitioner
Get started today
Ultimate access to all questions.
Deep dive into the quiz with AI chat providers.
We prepare a focused prompt with your quiz and certificate details so each AI can offer a more tailored, in-depth explanation.
A data scientist is building an AI tutor that must explain how it arrived at its answer step-by-step for transparency. Which prompting technique is most appropriate?
Real Exam
Community
JJin
A
Zero-shot Prompting
B
Negative Prompting
C
Chain-of-Thought Prompting
D
Few-shot Prompting
Explanation:
Chain-of-Thought (CoT) prompting is specifically designed to make AI models explain their reasoning step-by-step. This technique encourages the model to break down complex problems into intermediate steps, making the thought process transparent and easier to understand.
Why other options are not correct:
- A) Zero-shot Prompting: This involves giving the model a task without any examples. While it can work for simple tasks, it doesn't inherently encourage step-by-step explanations.
- B) Negative Prompting: This technique is used to specify what the model should NOT do, often in image generation or to avoid certain outputs. It doesn't promote step-by-step reasoning.
- D) Few-shot Prompting: This provides examples to guide the model's response, but the examples themselves need to demonstrate step-by-step reasoning for the model to learn this behavior.
Chain-of-Thought prompting is the most appropriate choice because it explicitly instructs the model to show its work, which is essential for an AI tutor that needs to be transparent about its reasoning process.
Comments
Loading comments...