Introduction to Prompt Engineering
Prompt engineering involves crafting precise inputs to guide AI models in generating desired outputs. Understanding language model functionality is essential for effective prompt creation. Various types of prompts serve different purposes, influencing AI responses through context, role assignment, and examples. This chapter emphasizes both structured thinking and creativity in formulating effective prompts.
Sections
Navigate through the learning materials and practice exercises.
What we have learnt
- Prompt engineering is the skill of crafting precise inputs for AI language models.
- Different types of prompts include informational, instructional, role-based, contextual, and few-shot prompts.
- Understanding the components of an effective prompt, such as role and constraints, is crucial for successful outcomes.
Key Concepts
- -- Prompt Engineering
- The skill of crafting precise inputs (prompts) to guide AI language models to produce desired outputs.
- -- Language Model
- An AI model trained on large datasets to predict text completions based on input.
- -- Token
- A chunk of text (word or sub-word) that models process for prediction.
- -- Context Window
- The amount of text or conversation that the model can remember during interaction.
- -- Temperature
- A setting that controls the creativity of the model's output.
- -- Prompt Iteration
- The process of testing and refining prompts to achieve better outputs.
Additional Learning Materials
Supplementary resources to enhance your learning experience.