Which prompting technique tests a model’s ability to perform a task without prior examples? Get the expert answer for the IBM Artificial Intelligence Fundamentals certification exam, including a clear explanation of zero-shot prompting and its AI application.
Table of Contents
Question
Which prompting technique tests a model’s ability to perform a task without prior examples?
A. Zero-shot
B. Chain-of-thought
C. Transfer learning
D. In-context learning
Answer
A. Zero-shot
Explanation
Zero-shot prompting assesses an AI model’s ability to generate correct responses or perform tasks using only the task’s description, with no examples provided. The model must rely solely on its pre-existing knowledge and understanding, rather than learning from explicit samples given within the prompt.
This method is often used to evaluate the generalization and comprehension skills of advanced language models and is a core concept in both AI research and applied certification materials.
Chain-of-thought prompting (B) involves giving reasoning steps, while transfer learning (C) uses pre-trained models in new contexts, and in-context learning (D) typically gives one or more prior examples within the prompt—all different from zero-shot prompting.
Understanding zero-shot prompting is vital for anyone preparing for the IBM Artificial Intelligence Fundamentals certification exam.
IBM Artificial Intelligence Fundamentals certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Artificial Intelligence Fundamentals graded quizzes and final assessments, earn IBM Artificial Intelligence Fundamentals digital credential and badge.