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  2. GPT-3 - Wikipedia

    en.wikipedia.org/wiki/GPT-3

    GPT-3, specifically the Codex model, was the basis for GitHub Copilot, a code completion and generation software that can be used in various code editors and IDEs. [ 38 ] [ 39 ] GPT-3 is used in certain Microsoft products to translate conventional language into formal computer code.

  3. Generative pre-trained transformer - Wikipedia

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

    This was developed by fine-tuning a 12B parameter version of GPT-3 (different from previous GPT-3 models) using code from GitHub. [ 31 ] In March 2022, OpenAI published two versions of GPT-3 that were fine-tuned for instruction-following (instruction-tuned), named davinci-instruct-beta (175B) and text-davinci-001 , [ 32 ] and then started beta ...

  4. OpenAI Codex - Wikipedia

    en.wikipedia.org/wiki/OpenAI_Codex

    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. OpenAI released an API for Codex in closed beta. [1]

  5. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    Generative AI systems trained on words or word tokens include GPT-3, GPT-4, GPT-4o, LaMDA, LLaMA, BLOOM, Gemini and others (see List of large language models). They are capable of natural language processing, machine translation, and natural language generation and can be used as foundation models for other tasks. [62]

  6. OpenAI o3 - Wikipedia

    en.wikipedia.org/wiki/OpenAI_o3

    OpenAI o3 is a reflective generative pre-trained transformer (GPT) model developed by OpenAI as a successor to OpenAI o1. It is designed to devote additional deliberation time when addressing questions that require step-by-step logical reasoning. [1] [2] OpenAI released a smaller model, o3-mini, on January 31st, 2025. [3]

  7. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    Suppose we have two transformer models like GPT-3 and GPT-3-small, both with a context window size of 512. To generate an entire context window autoregressively with greedy decoding with GPT-3, it must be run for 512 times, each time generating a token x 1 , x 2 , . . . , x 512 {\displaystyle x_{1},x_{2},...,x_{512}} , taking time 512 T GPT-3 ...

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  9. GitHub Copilot - Wikipedia

    en.wikipedia.org/wiki/GitHub_Copilot

    Copilot's OpenAI Codex was trained on a selection of the English language, public GitHub repositories, and other publicly available source code. [2] This includes a filtered dataset of 159 gigabytes of Python code sourced from 54 million public GitHub repositories. [15] OpenAI's GPT-3 is licensed exclusively to Microsoft, GitHub's parent ...