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  2. ChatGPT - Wikipedia

    en.wikipedia.org/wiki/ChatGPT

    ChatGPT is a chatbot and virtual assistant developed by OpenAI and launched on November 30, 2022. Based on large language models (LLMs), it enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. Successive user prompts and replies are considered at each conversation stage as context.

  3. GPT-4o - Wikipedia

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

    GPT-4o (GPT-4 Omni) is a multilingual, multimodal generative pre-trained transformer designed by OpenAI. It was announced by OpenAI's CTO Mira Murati during a live-streamed demo on 13 May 2024 and released the same day. GPT-4o is free, but with a usage limit that is 5 times higher for ChatGPT Plus subscribers.

  4. 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 ...

  5. ChatGPT in education - Wikipedia

    en.wikipedia.org/wiki/ChatGPT_in_education

    Though executives at Chegg were urging Rosenweig to work on developing a ChatGPT rival as early as possible since 2020, the technology firm ultimately decided against producing a ChatGPT competitor due to GPT 3.5 not being able to sufficiently lure away Chegg's 8 million subscribers, which makes up nearly 90% of the firm's revenue.

  6. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A fine-tuned variant of GPT-3, termed GPT-3.5, was made available to the public through a web interface called ChatGPT in 2022. GPT-Neo: March 2021: EleutherAI: 2.7: 825 GiB: MIT: The first of a series of free GPT-3 alternatives released by EleutherAI. GPT-Neo outperformed an equivalent-size GPT-3 model on some benchmarks, but was significantly ...

  7. Generative pre-trained transformer - Wikipedia

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

    History Initial developments. Generative pretraining (GP) was a long-established concept in machine learning applications. 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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