Prompt engineering is a concept in artificial intelligence, particularly natural language processing (NLP).
It involves designing prompts or input text to generate specific output text using machine learning algorithms.
In prompt engineering, the description of the task is embedded in the input, e.g., as a question instead of it being implicitly given.
The process of crafting prompts that a chatbot uses to generate responses is also called "prompt engineering".
The effective prompt design increases the likelihood that the model will return a response that is both favorable and contextual.
Prompt engineering is a rapidly developing field that emerged out of necessity as the creators of AI models and systems struggled to effectively communicate with their creations.
The future of prompt engineering is likely to involve more research on how to design effective and robust prompts for different tasks and domains, how to optimize prompts with minimal data and computation, how to evaluate and test prompts for reliability and security, and how to leverage prompts for novel and creative uses of LLMs.
Prompt engineering has many applications in various domains such as enhancing productivity, automating tasks, facilitating creativity, and simplifying complex processes.