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Papers that changed AI, with a plain-language explainer for each.
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- 2010
Understanding the difficulty of training deep feedforward neural networks
AISTATS / PMLR
A 2010 paper by Xavier Glorot and Yoshua Bengio on why deep feedforward networks are hard to train: sigmoid saturation under random initialization and layer Jacobians whose singular values sit far from 1, plus a new initialization scheme that converges substantially faster.
- 2004
MapReduce: Simplified Data Processing on Large Clusters
OSDI
Jeffrey Dean and Sanjay Ghemawat's 2004 OSDI paper presents MapReduce, a programming model in which users write a map function and a reduce function while the run-time system parallelizes the work across large clusters of commodity machines.
- 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.