Journal of Communication and Computer 15 (2019) 1-13
doi: 10.17265/1548-7709/2019.01.001
D
DAVID PUBLISHING
Artificial Intelligence Driven Resiliency with Machine
Learning and Deep Learning Components
Bahman Zohuri
1
, and Farhang Mossavar Rahmani
2
1. Research Associate Professor, University of New Mexico, Electrical Engineering and Computer Science Department, Albuquerque,
New Mexico USA
2. Professor of Finance and Director of MBA School of Business and Management, San Diego, California, USA
Abstract: The future of any business from banking, e-commerce, real estate, homeland security, healthcare, marketing, the stock
market, manufacturing, education, retail to government organizations depends on the data and analytics capabilities that are built and
scaled. The speed of change in technology in recent years has been a real challenge for all businesses. To manage that, a significant
number of organizations are exploring the Big Data (BD) infrastructure that helps them to take advantage of new opportunities while
saving costs. Timely transformation of information is also critical for the survivability of an organization. Having the right
information at the right time will enhance not only the knowledge of stakeholders within an organization but also providing them
with a tool to make the right decision at the right moment. It is no longer enough to rely on a sampling of information about the
organizations' customers. The decision-makers need to get vital insights into the customers' actual behavior, which requires enormous
volumes of data to be processed. We believe that Big Data infrastructure is the key to successful Artificial Intelligence (AI)
deployments and accurate, unbiased real-time insights. Big data solutions have a direct impact and changing the way the organization
needs to work with help from AI and its components ML and DL. In this article, we discuss these topics.
Key words: Artificial intelligence, resilience system, machine learning, deep learning, big data.
1. Introduction
In today’s growth of modern technology and the
world of Robotics, significant momentum is driving
the next generation of these robots that we now know
as Artificial Intelligence (AI). This new generation is
attracting tremendous attention of scientists and
engineers. They are eager to move them to the next
generation that is smarter and more cognitive, which
we now call them Super Artificial Intelligence (SAI).
Every day businesses are facing the vast volume of
data. Unlike before, processing this amount of data is
beyond Master Data Management (MDM) to a level
that we know it as Big Data (BD) that are getting
around at the speed of the Internet. Since our daily
operations within any organization or enterprises are
Corresponding author: Bahman Zohuri, Ph.D, Associate
Research Professor, research fields: electrical and computer
engineering. E-mail: zohurib@unm.edu.
expanding the Internet of Things (IoT) dealing with
these data either structured or unstructured also is
growing at the same speed, thus processing these data
for extracting the right information for the proper
knowledge growing accordingly.
With the demand of Power to make a decision with
minimum risk based on Knowledge of Information
from Data accumulated in Big Data (i.e., Fig. 1) [1]
repository, we need real-time processing of the data
coming to us from Omni-direction perspective. These
data are centric around the BD and get deposited at the
speed of Internet-driven mainly by IoT.
Thus, at this stage, we need to understand, what is
the Big Data (BD) and why it matters when we are
bringing the AI into play.
Toward real-time processing of data with
infrastructure around the Big data is a term that
describes the large volume of data — both structured
and unstructured — that inundates a business on a
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