At its core, ChatGPT uses a type of neural network called a Transformer network. This network is designed to process sequential data, such as text, and generate predictions about what should come next in the sequence. In the case of ChatGPT, the network is trained to predict the next word in a text conversation, based on the context of the words that came before it.

When a user inputs text into the model, the network processes the input and generates a response that is meant to be a continuation of the conversation. This response is generated by predicting the next word in the sequence and then using that information to generate a full response. The model repeats this process for each subsequent input in the conversation until the conversation reaches a natural end.
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