Abstract of a good paper, describes well the reasons neural network methods evolved from our early uses in the 90s to the current day. Would not have guessed its current uses from early examples. How will it continue to evolve?
Learning Machine Learning By Ted G. Lewis, Peter J. Denning
Communications of the ACM, December 2018, Vol. 61 No. 12, Pages 24-27
10.1145/3286868
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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