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Generative Pre-trained Transformer 4 (GPT-4) is a multimodal large language model trained and created by OpenAI and the fourth in its series of GPT foundation models. [1] It was launched on March 14, 2023, [1] and made publicly available via the paid chatbot product ChatGPT Plus, via OpenAI's API, and via the free chatbot Microsoft Copilot. [2]
Generative Pre-trained Transformer 3.5 (GPT-3.5) is a sub class of GPT-3 Models created by OpenAI in 2022. On March 15, 2022, OpenAI made available new versions of GPT-3 and Codex in its API with edit and insert capabilities under the names "text-davinci-002" and "code-davinci-002". [ 28 ]
GPT-4o ("o" for "omni") is a multilingual, multimodal generative pre-trained transformer developed by OpenAI and released in May 2024. [1] GPT-4o is free, but ChatGPT Plus subscribers have higher usage limits. [ 2 ]
Other such models include Google's PaLM, a broad foundation model that has been compared to GPT-3 and have been made available to developers via an API, [45] [46] and Together's GPT-JT, which has been reported as the closest-performing open-source alternative to GPT-3 (and is derived from earlier open-source GPTs). [47]
A Microsoft team argued in 2023 that GPT-4 "can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more" and that GPT-4 "could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence system": "Can one reasonably say that a system that passes exams ...
ChatGPT is a generative artificial intelligence chatbot [2] [3] developed by OpenAI and launched in 2022. It is currently based on the GPT-4o large language model (LLM). ChatGPT can generate human-like conversational responses and enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. [4]
At the time of the MMLU's release, most existing language models performed around the level of random chance (25%), with the best performing GPT-3 model achieving 43.9% accuracy. [3] The developers of the MMLU estimate that human domain-experts achieve around 89.8% accuracy. [ 3 ]
A blind study conducted at the University of Wollongong Law School compared GPT-3.5 and GPT-4 with 225 students in an end-of-semester criminal law exam. The findings revealed that the average score of the students was considerably higher than the GenAI models.