Artificial Intelligence1

Recently, the media has spent an increasing amount of broadcast time on new technology.
The focus of high-tech media has been aimed at the flurry of advances concerning artificial
intelligence (AI). What is artificial intelligence and what is the media talking about? Are these
technologies beneficial to our society or mere novelties among business and marketing
professionals? Medical facilities, police departments, and manufacturing plants have all been
changed by AI but how? These questions and many others are the concern of the general public
brought about by the lack of education concerning rapidly advancing computer technology.
Artificial intelligence is defined as the ability of a machine to think for itself. Scientists and
theorists continue to debate if computers will actually be able to think for themselves at one point
(Patterson 7). The generally accepted theory is that computers do and will think more in the
future. AI has grown rapidly in the last ten years chiefly because of the advances in computer
architecture. The term artificial intelligence was actually coined in 1956 by a group of scientists
having their first meeting on the topic (Patterson 6). Early attempts at AI were neural networks
modeled after the ones in the human brain. Success was minimal at best because of the lack of
computer technology needed to calculate such large equations.
AI is achieved using a number of different methods. The more popular implementations
comprise neural networks, chaos engineering, fuzzy logic, knowledge based systems, and expert
systems. Using any one of the aforementioned design structures requires a specialized computer
system. For example, Anderson Consulting applies a knowledge based system to commercial loan
officers using multimedia (Hedburg 121). Their system requires a fast IBM desktop computer.
Other systems may require even more horsepower using exotic computers or workstations. Even
more exotic is the software that is used. Since there are very few applications that are pre-written
using AI, each company has to write it\'s own software for the solution to the problem. An easier
way around this obstacle is to design an add-on. The company FuziWare makes several
applications that act as an addition to a larger application. FuziCalc, FuziQuote, FuziCell,
FuziChoice, and FuziCost are all products that are used as management decision support systems
for other off-the shelf applications (Barron 111).
In order to tell that AI is present we must be able to measure the intelligence being used.
For a relative scale of reference, large supercomputers can only create a brain the size of a fly
(Butler and Caudill 5). It is surprising what a computer can do with that intelligence once it has
been put to work. Almost any scientific, business, or financial profession can benefit greatly from
AI. The ability of the computer to analyze variables provides a great advantage to these fields.
There are many ways that AI can be used to solve a problem. Virtually all of these
methods require special hardware and software to use them. Unfortunately, that makes AI
systems expensive. Consulting firms, companies that design computing solutions for their clients,
have offset that cost with the quality of the system. Many new AI systems now give a special edge
that is needed to beat the competition.
Created by Lotfi Zadeh almost thirty years ago, fuzzy logic is a mathematical system that
deals with imprecise descriptions, such as "new", "nice", or "large" (Schmuller 14). This concept
was also inspired from biological roots. The inherent vagueness in everyday life motivates fuzzy
logic systems (Schmuller 8). In contrast to the usual yes and no answers, this type of system can
distinguish the shades in-between. In Los Angeles a fuzzy logic system is used to analyze input
from several cameras located at different intersections (Barron 114). This system provides a
"smart light" that can decide whether a traffic light should be changed more often or remain green
longer. In order for these "smart lights" to work the system assigns a value to an input and
analyzes all the inputs at once. Those inputs that have the highest value get the highest amount of
attention. For example, here is how a fuzzy logic system might evaluate water temperature. If the
water is cold, it assigns a value of zero. If it is hot the system will assign the value of one. But if
the next sample is lukewarm it has the capability to decide upon a value of 0.6 (Schmuller 14).
The varying degrees of warmness or coldness are shown through the values assigned to it. Fuzzy
logic\'s structure allows it to easily rate any input