TY - JOUR
AU - 
AB - SIP (2018), vol. 7, e6, page 1 of 19 © The Authors, 2018. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. doi:10.1017/ATSIP.2018.6 industrial technology advances The artificial intelligence renaissance: deep learning and the road to human-Level machine intelligence 1 2 kar-han tan and boon pang lim In this paper we look at recent advances in artificial intelligence. Decades in the making, a confluence of several factors in the past few years has culminated in a string of breakthroughs in many longstanding research challenges. A number of problems that were considered too challenging just a few years ago can now be solved convincingly by deep neural networks. Although deep learning appears to be reducing the algorithmic problem solving to a matter of data collection and labeling, we believe that many insights learnedfrom‘pre-Deep Learning’works stillapply andwillbemorevaluablethaneveringuiding thedesignof novelneuralnetwork architectures. Keywords: Artificial intelligence, Deep learning, Machine learning, Computer vision, Speech recognition, Convolutional neural networks Received 25 September 2017; Revised 23 March 2018 I. INTRODUCTION II. ORIGINS It is rare for technology advancements to induce passionate John 
TI - The artificial intelligence renaissance: deep learning and the road to human-Level machine intelligence
JF - APSIPA Transactions on Signal and Information Processing
DO - 10.1017/atsip.2018.6
DA - 2018-01-01
UR - https://www.deepdyve.com/lp/unpaywall/the-artificial-intelligence-renaissance-deep-learning-and-the-road-to-W00MJXDEsc
DP - DeepDyve
ER -