Generative Pre-training Transformer (GPT)

A Generative Pre-training Transformer, or GPT, is a type of language model developed by OpenAI. Language models are machine learning models that are trained to predict the likelihood of a sequence of words. They are used in a variety of natural language processing tasks, such as language translation, text generation, and question answering.

GPT is a type of transformer, which is a neural network architecture that processes input data using attention mechanisms to weigh different input elements differently. This allows the model to effectively process sequences of data, such as sentences in a language. GPT is “generative” because it can generate text that is similar to human-written text. It does this by learning the statistical patterns of a large dataset of text, and then using this knowledge to generate new, similar text.

GPT is also “pre-trained,” which means that it is trained on a large dataset in an unsupervised manner before being fine-tuned on a smaller dataset for a specific task. This allows the model to learn general language patterns that can be useful for a variety of tasks, rather than just one specific task. GPT has been used to generate human-like text, translate languages, and answer questions, among other things. It has also been used as the basis for more advanced language models, such as GPT-2 and GPT-3, which have achieved state-of-the-art results on a number of natural language processing tasks.