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  2. OpenAI starts charging $200 per month for ChatGPT ‘Pro’ - AOL

    www.aol.com/news/openai-starts-charging-200-per...

    The AI giant said its new ChatGPT Pro subscription would give users ‘unlimited’ access to its OpenAI o1 model (PA) (PA Archive) ... OpenAI o1, as well as to o1-mini, GPT-4o, and Advanced Voice

  3. 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 ]

  4. 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]

  5. OpenAI - Wikipedia

    en.wikipedia.org/wiki/OpenAI

    Former headquarters at the Pioneer Building in San Francisco. In December 2015, OpenAI was founded by Sam Altman, Elon Musk, Ilya Sutskever, Greg Brockman, Trevor Blackwell, Vicki Cheung, Andrej Karpathy, Durk Kingma, John Schulman, Pamela Vagata, and Wojciech Zaremba, with Sam Altman and Elon Musk as the co-chairs.

  6. OpenAI unveils newest AI model, GPT-4o - AOL

    www.aol.com/openai-unveils-newest-ai-model...

    Free ChatGPT users will have a limited number of interactions with the new GPT-4o model before the tool automatically reverts to relying on the old GPT-3.5 model; paid users will have access to a ...

  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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