Fine-tuning GPT for your use case

If you want to customize ChatGPT further for your use cases, there are a few approaches that you can take. One approach you can do is something called fine-tuning, where you basically give ChatGPT a large data set of example inputs and example outputs for a given task, and that teaches the AI model how to perform your task. Another approach is to bring in outside context or data into your prompt itself. You could pull in data such as your company's support documents, internal wikis or any type of database, so that when you're asked a question, you can look up the most relevant information in that outside data set and then pull in the most relevant context to provide as support to ChatGPT as it generates the answer. There are a growing number of products and providers that are helping people do both of these approaches. Or your engineering team can use OpenAI's documentation to develop an internal version for yourself. But if you thought that ChatGPT was powerful as is, wait until you customize it for your data.