The term language model fine-tuning comes from the fields of Artificial Intelligence, Digital Transformation, and Automation. It refers to a process where an existing language model, such as GPT-3 or GPT-4, is retrained to better adapt it to specific tasks or subject areas.
Imagine a language model is like a very well-trained interpreter who speaks many languages, but doesn't yet perfectly master your specific company language or industry topics. Through language model fine-tuning, this „interpreter“ learns precisely the words, phrases, and content that are important to your company or industry.
Here's an example: An insurance company wants to introduce a chatbot that not only understands customer queries but also answers them correctly and legally. By using language model fine-tuning, the AI model is retrained with insurance terms and typical customer questions. This makes the chatbot much more accurate and helpful.
Language model fine-tuning makes artificial intelligence even more precise and efficient for specific use cases, leading to better user experiences.
Deutsch 
English (UK)