Stephen Wolfram's latest article delves into the workings of ChatGPT, a large language model designed by OpenAI, and explores the reasons behind its success. ChatGPT, like other similar models, relies on an advanced neural network that has been trained on vast amounts of data. However, unlike previous models, ChatGPT is designed to generate human-like text that can respond to a wide variety of conversational prompts. This ability to understand and respond to natural language is what sets ChatGPT apart from its predecessors. Wolfram notes that the key to ChatGPT's success lies in the vast amount of data it has been trained on, which includes text from a wide range of sources, including books, articles, and even social media. This data is used to train the neural network to recognize patterns in language, allowing it to generate responses that are both coherent and contextually appropriate. To read more, use the button below to open the original external article.