Part of a series on |
Machine learning and data mining |
---|
Generative pre-trained transformers (GPT) are a type of large language model (LLM)[1][2][3] and a prominent framework for generative artificial intelligence.[4][5] They are artificial neural networks that are used in natural language processing tasks.[6] GPTs are based on the transformer architecture, pre-trained on large data sets of unlabelled text, and able to generate novel human-like content.[2][3] As of 2023, most LLMs have these characteristics[7] and are sometimes referred to broadly as GPTs.[8]
The first GPT was introduced in 2018 by OpenAI.[9] OpenAI has released significant GPT foundation models that have been sequentially numbered, to comprise its "GPT-n" series.[10] Each of these was significantly more capable than the previous, due to increased size (number of trainable parameters) and training. The most recent of these, GPT-4, was released in March 2023.[11] Such models have been the basis for their more task-specific GPT systems, including models fine-tuned for instruction following—which in turn power the ChatGPT chatbot service.[1]
The term "GPT" is also used in the names and descriptions of such models developed by others. For example, other GPT foundation models include a series of models created by EleutherAI,[12] and seven models created by Cerebras in 2023.[13] Also, companies in different industries have developed task-specific GPTs in their respective fields, such as Salesforce's "EinsteinGPT" (for CRM)[14] and Bloomberg's "BloombergGPT" (for finance).[15]
gpt1
was invoked but never defined (see the help page).© MMXXIII Rich X Search. We shall prevail. All rights reserved. Rich X Search