Prompt engineering
Prompt engineering is a concept in artificial intelligence (AI), particularly in natural language processing, that involves creating or designing prompts or inputs for an AI model that are capable of yielding desirable or useful results. The goal of prompt engineering is to improve the performance and accuracy of AI models, allowing them to generate more relevant and meaningful responses to user input.
Effective prompt engineering requires creating and maintaining a library of useful prompts. These libraries include different types of prompts such as questions, statements, examples or templates that are designed to elicit specific responses from an AI model and can be mixed and matched with other prompts to control output. Creating good prompts requires evaluating the strengths and weaknesses of different models and optimizing the prompts to minimize errors.
Applications
One example of prompt engineering in practice is in the development of chatbots. A programmer might design a prompt to guide a chatbot to ask relevant follow-up questions to understand the user's intent more accurately.
Recently prompt engineering has been applied to generating better datasets to improve the training of large language models, such as LongForm and Evol-Instruct.
Examples
A simple prompt to generate interesting prompts:[1]
What are the absolute coolest, most mind-blowing, out of the box, ChatGPT prompts that will really show off the power of ChatGPT? Give me 10. Focus the prompts around {TOPIC}.