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Papers

Papers that changed AI, with a plain-language explainer for each.

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  1. 1993

    Building a Large Annotated Corpus of English: The Penn Treebank

    Computational Linguistics

    A 1993 journal article by Mitchell P. Marcus, Beatrice Santorini and Mary Ann Marcinkiewicz describing the Penn Treebank: over one million words of Wall Street Journal text annotated with syntactic bracketing, built as a resource for work on English sentence structure.

    Large language modelsResearch historyData & datasets

  2. 1992

    A Training Algorithm for Optimal Margin Classifiers

    Published in 1992, this paper by Boser, Guyon and Vapnik presents a training algorithm that maximizes the margin between training patterns and the decision boundary, with experiments on optical character recognition.[^1]

    Research historyDeep learningData & datasets

  3. 1992

    Q-learning

    Machine Learning

    A 1992 technical note by Watkins and Dayan that set out Q-learning, an incremental and computationally light way for an agent to learn optimal action values, and proved it converges to the optimum with probability 1.

    Research historyDeep learningData & datasets

  4. 1990

    Elephants Don't Play Chess

    Rodney Brooks's 1990 paper argued for building artificial intelligence from the ground up, with ongoing physical interaction with the environment as the main constraint on design, rather than through the abstract manipulation of symbols that had dominated the field for roughly thirty years.

    Research historyRoboticsScience

  5. 1948

    A Mathematical Theory of Communication

    Bell System Technical Journal 27

    C. E. Shannon's 1948 paper set out a mathematical framework for communication, defining information in bits, channel capacity, and entropy, and treating messages statistically while setting aside semantic meaning.

    Research historyData & datasetsScience