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  2. Anyword - Wikipedia

    en.wikipedia.org/wiki/Anyword

    Anyword's AI platform generates and optimized marketing copy for ads, landing pages, product listings, social posts, emails and SMS. Anyword's Technology: Anyword's AI copywriting platform uses a combination of pre-trained and fine-tuned models, including GPT3, T5 and CTRL, to generate quality marketing copy for its customers.

  3. 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]

  4. GitHub Copilot - Wikipedia

    en.wikipedia.org/wiki/GitHub_Copilot

    GitHub Copilot was initially powered by the OpenAI Codex, [13] which is a modified, production version of the Generative Pre-trained Transformer 3 (GPT-3), a language model using deep-learning to produce human-like text. [14] The Codex model is additionally trained on gigabytes of source code in a dozen programming languages.

  5. Flux (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Flux_(text-to-image_model)

    Flux (also known as FLUX.1) is a text-to-image model developed by Black Forest Labs, based in Freiburg im Breisgau, Germany. Black Forest Labs were founded by former employees of Stability AI. As with other text-to-image models, Flux generates images from natural language descriptions, called prompts.

  6. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [ 1 ] [ 2 ] Like the original Transformer model, [ 3 ] T5 models are encoder-decoder Transformers , where the encoder processes the input text, and the decoder generates the output text.

  7. Tabnine - Wikipedia

    en.wikipedia.org/wiki/Tabnine

    With a focus on the meaning of code, Codota's AI-based autocompletion employed a semantic approach to automatically generate code. [14] [15] [6] Codota, the predecessor of Tabnine, secured $2 million in seed investment in June 2017. Following this, in June 2018, the company introduced the first AI-based code completion for Java IDE. [16] [10] [13]