Home → Magazine Archive → December 2018 (Vol. 61, No. 12) → Learning Machine Learning → Abstract

Learning Machine Learning

By Ted G. Lewis, Peter J. Denning

Communications of the ACM, Vol. 61 No. 12, Pages 24-27

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Machine learning has evolved from an out-of-favor subdiscipline of computer science and artificial intelligence (AI) to a leading-edge frontier of research in both AI and computer systems architecture. Over the past decade investments in both hardware and software for machine learning have risen at an exponential rate matched only by similar investments in blockchain technology. This column is a technology check for professionals in a Q&A format on how this field has evolved and what big questions it faces.

Q: The modern surge in AI is powered by neural networks. When did the neural network field start? What was the first implementation?


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