Although fine-tuning can feel like the more natural option—training on data is how GPT learned all of its other knowledge, after all—we generally do not recommend it as a way to teach the model knowledge. Fine-tuning is better suited to teaching specialized tasks or styles, and is less reliable for factual recall. [...] In contrast, message inputs are like short-term memory. When you insert knowledge into a message, it’s like taking an exam with open notes. With notes in hand, the model is more likely to arrive at correct answers.
Recent articles
- Weeknotes: the aftermath of NICAR - 16th March 2024
- The GPT-4 barrier has finally been broken - 8th March 2024
- Prompt injection and jailbreaking are not the same thing - 5th March 2024
- Interesting ideas in Observable Framework - 3rd March 2024
- Weeknotes: Getting ready for NICAR - 27th February 2024
- The killer app of Gemini Pro 1.5 is video - 21st February 2024