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On Tuesday, OpenAI announced fine-tuning for GPT-3.5 Turbo—the AI model that powers the free version of ChatGPT—through its API. It allows training the model with custom data, such as company documents or project documentation. OpenAI claims that a fine-tuned model can perform as well as GPT-4 with lower cost in certain scenarios.
In AI, fine-tuning refers to the process of taking a pretrained neural network (like GPT-3.5 Turbo) and further training it on a different dataset (like your custom data), which is typically smaller and possibly related to a specific task. This process builds off of knowledge the model gained during its initial training phase and refines it for a specific application.
So basically, fine-tuning teaches GPT-3.5 Turbo about custom content, such as project documentation or any other written reference. That can come in handy if you want to build an AI assistant based on GPT-3.5 that is intimately familiar with your product or service but lacks knowledge of it in its training data (which, as a reminder, was scraped off the web before September 2021).
