SCIENCE | Artificial intelligence faces reproducibility crisis

Published: 19 February 2018

At the AAAI meeting, Peter Henderson, a computer scientist at McGill University in Montreal, showed that the performance of AIs designed to learn by trial and error is highly sensitive not only to the exact code used, but also to the random numbers generated to kick off training, and to “hyperparameters”—settings that are not core to the algorithm but that affect how quickly it learns.

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