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  2. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    Forcada and Ñeco simplified this procedure in 1997 to directly train a source encoder and a target decoder in what they called a recursive hetero-associative memory. [11] Also in 1997, Castaño and Casacuberta employed an Elman's recurrent neural network in another machine translation task with very limited vocabulary and complexity. [12] [13]

  3. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    It is a general-purpose learner and its ability to perform the various tasks was a consequence of its general ability to accurately predict the next item in a sequence, [2] [7] which enabled it to translate texts, answer questions about a topic from a text, summarize passages from a larger text, [7] and generate text output on a level sometimes ...

  4. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_AI

    Generative AI features have been integrated into a variety of existing commercially available products such as Microsoft Office (Microsoft Copilot), [85] Google Photos, [86] and the Adobe Suite (Adobe Firefly). [87] Many generative AI models are also available as open-source software, including Stable Diffusion and the LLaMA [88] language model.

  5. Generative pre-trained transformer - Wikipedia

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

    Meta AI (formerly Facebook) also has a generative transformer-based foundational large language model, known as LLaMA. [48] Foundational GPTs can also employ modalities other than text, for input and/or output. GPT-4 is a multi-modal LLM that is capable of processing text and image input (though its output is limited to text). [49]

  6. GPT-J - Wikipedia

    en.wikipedia.org/wiki/GPT-J

    GPT-J was designed to generate English text from a prompt. It was not designed for translating or generating text in other languages or for performance without first fine-tuning the model for a specific task. [2] Nonetheless, GPT-J performs reasonably well even without fine-tuning, even in translation (at least from English to French). [9]

  7. A list going viral reveals famous artists whose work was used ...

    www.aol.com/news/list-going-viral-reveals-famous...

    A list going viral reveals famous artists whose work was used to train AI generator. Angela Yang and Daniel Arkin ... one of the most popular of a new class of AI programs that can create images ...

  8. Natural language generation - Wikipedia

    en.wikipedia.org/wiki/Natural_language_generation

    Natural language generation (NLG) is a software process that produces natural language output. A widely-cited survey of NLG methods describes NLG as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems that can produce understandable texts in English or other human languages from some underlying non-linguistic ...

  9. Seq2seq - Wikipedia

    en.wikipedia.org/wiki/Seq2seq

    Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...

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