Chat GPT is a powerful AI-based language model, capable of generating human-like answers to a wide range of questions and prompts. But how does it work? In this article, we'll explore the inner workings of Chat GPT and how it is able to generate such accurate responses. At the heart of Chat GPT is a neural network that has been trained with an enormous amount of data. This data is used to teach the model to recognize patterns and relationships in text, allowing it to generate new text similar to the text with which it was trained. The model is pre-trained on a large body of text, including Common Crawl, WebText2 and Wikipedia, allowing it to understand and produce natural language. The specific GPT used by Chat GPT has been adjusted based on a model from the GPT-3.5 series, according to OpenAI.
This model is trained with several data sets, each with different weights. In addition, the model uses a self-care mechanism which allows it to focus on different parts of the input text as it processes it and to dynamically weigh the importance of the different parts of the input depending on the task at hand. This self-care mechanism is what allows Chat GPT to generate contextually relevant responses even when it comes to very long input sequences. As such, Chat GPT represents an exciting step forward in the field of Natural Language Processing (NLP) and has the potential to be a powerful tool for improving the efficiency of many different applications.