ChatGPT, developed by OpenAI, is an advanced language model that uses machine learning to engage in human-like text conversations. But have you ever wondered how it is trained? This article will delve into that.
The training of ChatGPT involves two main steps, with the first being pretraining. During this phase, the model is trained on a large corpus of text from the internet. However, it's important to note that it doesn't know specific documents or sources in the dataset. The model learns to predict the next word in a sentence, which helps it understand grammar, facts about the world, and some reasoning abilities, but also exposes it to biases in the data.
The second step is fine-tuning, which narrows down the model's behavior and makes it useful for specific tasks. OpenAI uses a more specific dataset, with demonstrations of correct behavior and comparisons ranking different responses. Some of the prompts used for fine-tuning are from users of the Playground and the ChatGPT app, but all data is anonymized and stripped of personally identifiable information.
Training ChatGPT is a complex process that involves a combination of broad pretraining and specific fine-tuning. This rigorous process enables it to engage in diverse and dynamic conversations, understanding and responding to a wide range of prompts.