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  2. OpenAI Codex - Wikipedia

    en.wikipedia.org/wiki/OpenAI_Codex

    OpenAI Codex is an artificial intelligence model developed by OpenAI. It parses natural language and generates code in response. It powers GitHub Copilot, a programming autocompletion tool for select IDEs, like Visual Studio Code and Neovim. [1] Codex is a descendant of OpenAI's GPT-3 model, fine-tuned for use in programming applications.

  3. GPT-1 - Wikipedia

    en.wikipedia.org/wiki/GPT-1

    GPT-1 achieved a 5.8% and 1.5% improvement over previous best results [3] on natural language inference (also known as textual entailment) tasks, evaluating the ability to interpret pairs of sentences from various datasets and classify the relationship between them as "entailment", "contradiction" or "neutral". [3]

  4. OpenAI - Wikipedia

    en.wikipedia.org/wiki/OpenAI

    As of 2023, ChatGPT Plus is a GPT-4 backed version of ChatGPT [241] available for a US$20 per month subscription fee [242] (the original version is backed by GPT-3.5). [243] OpenAI also makes GPT-4 available to a select group of applicants through their GPT-4 API waitlist; [244] after being accepted, an additional fee of US$0.03 per 1000 tokens ...

  5. Common Core - Wikipedia

    en.wikipedia.org/wiki/Common_Core

    The Common Core State Standards Initiative, also known as simply Common Core, was an American, multi-state educational initiative begun in 2010 with the goal of increasing consistency across state standards, or what K–12 students throughout the United States should know in English language arts and mathematics at the conclusion of each school grade.

  6. BookCorpus - Wikipedia

    en.wikipedia.org/wiki/BookCorpus

    It was the main corpus used to train the initial GPT model by OpenAI, [2] and has been used as training data for other early large language models including Google's BERT. [3] The dataset consists of around 985 million words, and the books that comprise it span a range of genres, including romance, science fiction, and fantasy.

  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.

  8. GPT-3 - Wikipedia

    en.wikipedia.org/wiki/GPT-3

    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 ]

  9. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    It was partially released in February 2019, followed by full release of the 1.5-billion-parameter model on November 5, 2019. [ 3 ] [ 4 ] [ 5 ] GPT-2 was created as a "direct scale-up" of GPT-1 [ 6 ] with a ten-fold increase in both its parameter count and the size of its training dataset. [ 5 ]