Prompt text engineers get the best results by creating and perfecting text prompts input into artificial intelligence. Unlike traditional programmers who use code languages, the job of cue engineers is to skillfully use natural languages on the premise of fully understanding AI.
This profession did first appear on American job websites. A position in Anthropic, an AI startup, explicitly mentioned the recruitment of "AI cue engineers". The job description is: "This is the combination of programming, guidance and teaching". Its main responsibility is to help the company build a clue library and let LLM (large language model) complete different tasks.
With the continuous development of artificial intelligence technology, the profession of cue engineer has attracted more and more attention. Their job involves interacting with AI and guiding AI to make corresponding answers or behaviors through carefully designed prompts. In this process, cue engineers need to have a solid language foundation and good communication skills in order to better understand human language and the operating principle of AI.
Hint words engineer's work content
1. Prompt engineers need to be able to handle user input from different languages and cultural backgrounds and provide accurate, natural and appropriate tips and suggestions to meet the needs of different regions and users.
2. Prompting engineers need to pay close attention to the latest development and technology in the fields of natural language processing and computer-aided language understanding, and constantly optimize and improve the techniques and methods of prompting engineering to improve the performance and accuracy of application programs.
3. Prompting engineers are important experts in the fields of natural language processing and computer-aided language understanding. Their job is to provide accurate, natural and appropriate tips and suggestions by training and learning language models and language knowledge, so as to help the development and implementation of applications and improve the effect and quality of natural language processing and computer-aided language understanding applications.