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AI Research

Foundational AI papers

A curated reading sequence of papers that shaped modern AI.

  • A Mathematical Theory of Communication

    The founding document of information theory.

    01 · Shannon 1948
  • The Perceptron

    The first learning machine.

    02 · Rosenblatt 1958
  • Learning representations by back-propagating errors

    Popularized the algorithm deep learning runs on.

    03 · Rumelhart, Hinton & Williams 1986
  • ImageNet Classification with Deep CNNs (AlexNet)

    The deep learning big bang.

    04 · Krizhevsky et al. 2012
  • Sequence to Sequence Learning

    Encoder–decoder thinking.

    05 · Sutskever et al. 2014
  • Deep Residual Learning (ResNet)

    Skip connections unlock depth.

    06 · He et al. 2015
  • Attention Is All You Need

    The Transformer.

    07 · Vaswani et al. 2017
  • BERT

    Bidirectional pretraining.

    08 · Devlin et al. 2018
  • Scaling Laws for Neural Language Models

    Power laws for loss.

    09 · Kaplan et al. 2020
  • InstructGPT

    RLHF becomes a recipe.

    10 · Ouyang et al. 2022
  • Chinchilla

    Compute-optimal scaling.

    11 · Hoffmann et al. 2022