Known as a profession dedicated to asking questions about ai.

The occupation known as asking questions to ai is a prompt engineer.

Prompt engineers get the best results by creating and perfecting text prompts input to artificial intelligence. Different from the traditional programmer's use of code language, the job of cue engineer is to skillfully use natural language on the premise of fully understanding AI.

this profession first appeared on the American job search website Indeed. A position in Anthropic, an AI startup company, explicitly mentioned the recruitment of "AI cue engineer". The job description is: "This is a combination of programming, guidance and teaching". Its main responsibility is to help the company build a cue library and let LLM (large language model) complete different tasks.

With the continuous development of artificial intelligence technology, people pay more and more attention to the profession of cue engineer. Their work 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 solid language skills and good communication skills in order to better understand human language and the operating principle of AI.

job content of the cue engineer

1. The cue engineer needs to be able to handle user input in different languages and cultural backgrounds, and provide accurate, natural and appropriate tips and suggestions to meet the needs of different regions and different users.

2. Prompt 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 prompt engineering to improve the performance and accuracy of application programs.

3. Hint 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 hints and suggestions through 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.