Page 9 - Artificial Intelligence in the Age of Neural Networks and Brain Computing

Introduction

We live in the era of Artificial Intelligence (AI), and AI is everywhere. It is on the
front page of your favorite newspaper, it is in your pocket inside your smartphone,
on your kitchen table, in your car, on the street, at your office, on the trains and
airplanes, everywhere. The success of AI-based commercial products, proposed by
many important companies, like Google, IBM, Microsoft, Intel, Amazon, to name
a few, can be interpreted as the coexistence of a successful synergism among what
we call Computational Intelligence, Natural Intelligence, Brain Computing, and
Neural Engineering.
The emergence of AI in many IT technologies happened almost overnight, in the
past couple of years. The blessing and the curse of AI are here! And all this is just the
beginning, for the better or for the worse. How did all this happen all of a sudden?
Yes, it requires the powerful computing offered by advanced chips at a cheap cost.
It also requires massive amount of data available through the Internet and via prolific
communication resources, also called as Big Data. That is not all. Computational
algorithms, called deep learning (DL), provide the framework of the programming
approaches. Deep learning was coined about a decade ago, but many experts employ-
ing these technologies do not realize that DL is rooted in the technology developed by
the biologically motivated neural networks field in the 1960s.
Neural networks thus powerfully reemerged with different names and meanings
in different, also unexpected, contexts within the current new wave of AI and DL.
Neural networks represent a well-grounded paradigm rooted in many disciplines,
including computer science, physics, psychology, information science, and
engineering.
This volume collects selected invited contributions from pioneers and experts
of the field of neural networks. This collection aims to show that the present implica-
tions and applications of AI is nothing but a development of the endowed unique
attributes of neural networks, namely, machine learning, distributed architectures,
massively parallel processing, black-box inference, intrinsic nonlinearity, and smart
autonomous search engine. We strive to cover the major basic ideas of brain-like
computing behind AI and to contribute to give a framework to DL as well as to launch
novel intriguing paradigms as possible future alternatives.
This book has been designed to commemorate the 30th anniversary of International
Neural Network Society (INNS), following the 2017 International Joint Conference on
Neural Networks, in Anchorage, AK, USA, May 14e18, 2017. The conference is
organized jointly by the INNS and the IEEE Computational Intelligence Society
(CIS), and is the premiere international meeting for researchers and other professionals
in neural networks and related areas, including neural network theory, DL, computa-
tional neuroscience, robotics, and distributed intelligence.
The chapters included here are written by authors who are a blend of top experts,
worldwide-recognized pioneers of the field, and researchers working on cutting-edge
applications in signal processing, speech recognition, games, and adaptive control

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