Fine-tuning
Fine-tuning is the process of taking a pre-trained AI model and further training it on a smaller, specialized dataset to make it better at a specific task.
How it works
It works by adjusting the model's internal parameters using new data, allowing it to adapt its general knowledge to a particular domain or style. This matters because it's a cost-effective way to create a highly capable, custom AI without needing to build a model from scratch.
Examples
- 1.Adapting a general language model to write legal contracts in a specific firm's style.
- 2.Teaching an image generation model to produce artwork that mimics a particular artist's technique.
- 3.Training a customer service chatbot on a company's past support tickets to understand its products and terminology.