ChatGPT, a conversational artificial intelligence model, works by using large-scale machine learning to generate text based on patterns it identifies from extensive data sets. It utilises the transformer architecture, which allows it to handle sequences of data, such as sentences, in any order. This architecture also enables the system to consider the context of the entire input, rather than only focusing on the immediate vicinity of a word or phrase.
The model is trained using a two-step process. First, it learns patterns from a broad array of internet text, and then it is fine-tuned using human feedback. This feedback is collected from a variety of sources, including anonymised data from users of OpenAI’s applications.
ChatGPT has limitations, including generating incorrect or nonsensical responses, and being sensitive to small changes in input phrasing. It also can’t provide a reliable source for its information, as it doesn’t access the internet during its operation. Despite these challenges, OpenAI is committed to improving the system by refining its models and exploring novel approaches. It also encourages public input on system behaviour and deployment policies to ensure a wider perspective on the technology’s development.
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