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Poems That Solve PuzzlesThe History and Science of Algorithms$
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Chris Bleakley

Print publication date: 2020

Print ISBN-13: 9780198853732

Published to Oxford Scholarship Online: October 2020

DOI: 10.1093/oso/9780198853732.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 24 January 2021

Mimicking the Brain

Mimicking the Brain

Chapter:
(p.179) 11 Mimicking the Brain
Source:
Poems That Solve Puzzles
Author(s):

Chris Bleakley

Publisher:
Oxford University Press
DOI:10.1093/oso/9780198853732.003.0011

Chapter 11 traces the history of artificial neural networks (ANNs) from humble beginnings in the 1940s to their monumental successes in the 21st century. ANNs are algorithms which mimic the behaviour of the nerve cells in the human brain. The concept was originally proposed by Walter Pitts and Warren McCulloch but it was Frank Rosenblatt that popularised the idea, building an ANN to recognise simple shape in images. Rosenblatt’s Perceptron was heavily criticised and attention turned to other, more rigorours mathematical, approaches. In the 70s, three independent research teams invented an effective algorithm for training an ANN to perform pattern recognition tasks. By the 1990s, a handful of results suggested that the idea might work after all. Around 2006, it finally became apparent that computer performance had been the limiting factor. Large networks could perform many pattern recognition just as well humans. So-called deep learning was about to transform computing.

Keywords:   algorithm, artificial neural network, backpropagation, Perceptron, artificial intelligence, Walter Pitts, Warren McCulloch, Frank Rosenblatt, deep learning, Yann LeCun, Geoff Hinton, Yoshua Bengio

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