ChatGPT, like other GPT models, was trained on a massive corpus of text data, which includes a wide variety of sources such as books, articles, websites, and more. The model was trained on a diverse set of text to learn different styles and formats of language, so it can generate text that resembles human language.
The training data for GPT models comes from a variety of sources, including the internet, books, articles, and other text. The specific data that was used to train ChatGPT is not publicly available, but the training data for GPT-3, which is the latest and more advanced version of GPT, comes from a dataset called “WebText” which includes 570GB of text data scraped from the internet.
It is important to note that the text data used to train these models may contain biases, and the model can perpetuate these biases in its generated text. OpenAI and other companies are working to mitigate these biases by training models on more diverse data and by developing techniques to detect and correct biases in the generated text.
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