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  2. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval augmented generation (RAG) is a type of information retrieval process. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information in preference to information drawn from its own vast, static training data.

  3. Artificial Intelligence Markup Language - Wikipedia

    en.wikipedia.org/wiki/Artificial_Intelligence...

    The XML dialect called AIML was developed by Richard Wallace and a worldwide free software community between 1995 [citation needed] and 2002. AIML formed the basis for what was initially a highly extended Eliza called "A.L.I.C.E." ("Artificial Linguistic Internet Computer Entity"), which won the annual Loebner Prize Competition in Artificial Intelligence [3] three times, and was also the ...

  4. Markdown - Wikipedia

    en.wikipedia.org/wiki/Markdown

    Markdown[ 9] is a lightweight markup language for creating formatted text using a plain-text editor. John Gruber created Markdown in 2004 as an easy to read markup language. [ 9] Markdown is widely used for blogging and instant messaging, and also used elsewhere in online forums, collaborative software, documentation pages, and readme files .

  5. Text-to-image model - Wikipedia

    en.wikipedia.org/wiki/Text-to-image_model

    A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description. Text-to-image models began to be developed in the mid-2010s during the beginnings of the AI boom, as a result of advances in deep neural networks. In 2022, the output of state-of-the-art text-to ...

  6. 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] [18] 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.

  7. 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.

  8. Generative artificial intelligence - Wikipedia

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

    Artificial general intelligence – Human-level or stronger AI for a wide range of tasks. Artificial imagination – Artificial simulation of human imagination. Artificial intelligence art – Machine application of knowledge of human aesthetic expressions. Artificial life – Field of study.

  9. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    e. Generative Pre-trained Transformer 2 ( GPT-2) is a large language model by OpenAI and the second in their foundational series of GPT models. GPT-2 was pre-trained on a dataset of 8 million web pages. [ 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]