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  2. Category:Artificial intelligence papers - Wikipedia

    en.wikipedia.org/wiki/Category:Artificial...

    Download as PDF; Printable version; In other projects Wikidata item; ... Help. Pages in category "Artificial intelligence papers" The following 4 pages are in this ...

  3. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    The paper introduced a new deep learning architecture known as the transformer, based on the attention mechanism proposed in 2014 by Bahdanau et al. [4] It is considered a foundational [5] paper in modern artificial intelligence, as the transformer approach has become the main architecture of large language models like those based on GPT.

  4. Computing Machinery and Intelligence - Wikipedia

    en.wikipedia.org/wiki/Computing_Machinery_and...

    Computing Machinery and Intelligence" is a seminal paper written by Alan Turing on the topic of artificial intelligence. The paper, published in 1950 in Mind , was the first to introduce his concept of what is now known as the Turing test to the general public.

  5. Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence

    Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]

  6. Lighthill report - Wikipedia

    en.wikipedia.org/wiki/Lighthill_report

    Artificial Intelligence: A General Survey, commonly known as the Lighthill report, is a scholarly article by James Lighthill, published in Artificial Intelligence: a paper symposium in 1973. [1] It was compiled by Lighthill for the British Science Research Council as an evaluation of academic research in the field of artificial intelligence (AI ...

  7. Transformer (deep learning architecture) - Wikipedia

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

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...