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ChatGPT, a language model developed by OpenAI, has been making waves in the AI industry. It's known for generating human-like text based on the input it receives. But how exactly is ChatGPT trained? Let's break it down.
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The training of ChatGPT starts with data collection. It's trained on a wide variety of internet text. However, it's important to note that it doesn't know specifics about which documents were part of its training set or any data source.
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After the data collection, the base model, known as a transformer, is trained. This is a creative text generation task where the model predicts the next word in a sentence. This initial training stage forms the 'base model' which is a creative text generator.
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Once the base model is trained, it's fine-tuned on a narrower dataset, generated with the help of human reviewers. These reviewers follow guidelines provided by OpenAI to review and rate possible model outputs for a range of example inputs.
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The performance of the model is constantly reviewed and the feedback is used to improve the model. This iterative process helps the model to learn and improve over time.
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In conclusion, the training of ChatGPT involves a series of steps and a lot of data. The result is a model that can generate creative and coherent text, much like a human would.