Running head: The Edge of Excellence The Edge of Excellence Kathleen P. Munn
Community College of Philadelphia 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. Neural networks have
entered the spotlight with surprisingly successful results. A neural network is
a type of information processing system whose architecture is similar to the
structure of biological neural systems (Butler and Caudill 5). The neural
network tries to mimic the way a brain and nervous system work by analyzing
sensory inputs and calculating an outcome. Before it can be used a neural
network must be trained. Some can learn by themselves, some require training by
doing, and others learn by trial and error. A computer learns by naturally
associating items the computer is taught and grouping them together physically.
Additionally, a computer can retrieve stored information from incomplete or
partially incorrect clues. Neural networks are able to generalize categories
based on specifics of the contents. Lastly, it is highly fault tolerant. This
means that the network can sustain a large amount of damage and still function.
