Types of Prompts — Zero-shot, Few-shot, and Chain-of-Thought

Different prompting styles significantly influence how AI language models interpret tasks and generate responses. Zero-shot prompting relies on the model's internal knowledge without examples, while few-shot prompting enhances understanding through examples. Chain-of-thought prompting encourages step-by-step reasoning, improving outcomes particularly for complex tasks. Selecting the appropriate prompting style based on the task can dramatically enhance effectiveness.

Sections

  • 4

    Types Of Prompts — Zero-Shot, Few-Shot, And Chain-Of-Thought

    This section outlines three major types of prompting styles for AI models: zero-shot, few-shot, and chain-of-thought, highlighting their definitions, uses, and effectiveness.

    Learning Practice

  • 4.1

    Introduction To Prompting Styles

    This section introduces three primary prompting styles for AI models: zero-shot, few-shot, and chain-of-thought, each with distinct features and ideal use cases.

    Learning Practice

  • 4.2

    Zero-Shot Prompting

    Zero-shot prompting involves providing an AI model with a task without any examples, relying solely on its pre-existing knowledge to generate a response.

    Learning Practice

  • 4.3

    Few-Shot Prompting

    Few-shot prompting involves providing the AI model with example tasks to help it understand the desired output format or style.

    Learning Practice

  • 4.4

    Chain-Of-Thought Prompting

    Chain-of-thought prompting enhances reasoning in AI interactions by guiding models through step-by-step logic.

    Learning Practice

  • 4.5

    Prompt Style Comparison Table

    This section presents a comparative overview of zero-shot, few-shot, and chain-of-thought prompting styles used in AI.

    Learning Practice

  • 4.6

    When To Use Which Style?

    This section outlines guidelines for selecting the appropriate prompting style—zero-shot, few-shot, or chain-of-thought—based on the task at hand.

    Learning Practice

  • 4.7

    Prompt Engineering Tip

    This section highlights the importance of combining different styles of prompts in AI interactions to enhance accuracy and effectiveness.

    Learning Practice

  • 4.8

    Practice Exercise

    This section provides practice exercises for students to apply different types of prompts: zero-shot, few-shot, and chain-of-thought.

    Learning Practice

  • 4.9

    Summary

    This section summarizes the different types of AI prompting, emphasizing their distinct uses and advantages.

    Learning Practice

References

Chapter 4_ Zero-shot, Few-shot, and Chain-of-Thought.pdf

Class Notes

Memorization

What we have learnt

  • Zero-shot prompting is best...
  • Few-shot prompting is effec...
  • Chain-of-thought prompting ...

Final Test

Revision Tests

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