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  2. GPT Store - Wikipedia

    en.wikipedia.org/wiki/GPT_Store

    The GPT Store is a platform developed by OpenAI that enables users and developers to create, publish, and monetize GPTs without requiring advanced programming skills. GPTs are custom applications built using the artificial intelligence chatbot known as ChatGPT .

  3. ChatGPT - Wikipedia

    en.wikipedia.org/wiki/ChatGPT

    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]

  4. GPT-4o - Wikipedia

    en.wikipedia.org/wiki/GPT-4o

    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 with a usage limit that is five times higher for ChatGPT Plus subscribers. [ 2 ]

  5. Understanding images is just one way Chat GPT-4 goes ... - AOL

    www.aol.com/news/understanding-images-just-one...

    One of the most apparent changes with GPT-4, compared to the GPT-3.5 that was powering ChatGPT when it hit the public market in November, is that it accepts visual inputs alongside text.

  6. GPT-4 - Wikipedia

    en.wikipedia.org/wiki/GPT-4

    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]

  7. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.

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