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

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  1. 2017

    Proximal Policy Optimization Algorithms

    arXiv

    A 2017 paper by Schulman, Wolski, Dhariwal, Radford and Klimov that introduced proximal policy optimization (PPO), a reinforcement learning method that is much simpler to implement and tune and became OpenAI's default RL algorithm.

    Research historyDeep learningRobotics

  2. 1999

    The PageRank Citation Ranking: Bringing Order to the Web

    Brin and Page's PageRank technical report treats hyperlinks as citations to rank web pages and was used to build Google's search engine; it is one of the heavily cited papers on their early work.

    Research historyEnterpriseData & datasets

  3. 1998

    The Anatomy of a Large-Scale Hypertextual Web Search Engine

    A 1998 conference paper by Sergey Brin and Lawrence Page describing PageRank, an algorithm that ranks web pages by the number and quality of links pointing to them, and the search engine built on that algorithm.

    Research historyEnterpriseData & 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. 1988

    ALVINN: An Autonomous Land Vehicle in a Neural Network

    ANIPS11

    A 3-layer back-propagation network that takes camera and laser range finder images and outputs the direction to steer, trained on simulated road images and tested on Carnegie Mellon's autonomous navigation test vehicle.

    Research historyRoboticsComputer vision