Artificial complexity. It has developed as a vital

Artificial Intelligence is a real subject of
complexity. It has developed as a vital branch of computer science and
technology. Technologies of facial recognition, ATM machines, developing
technologies of self-driven cars and everything that we are using from day to
day life are based on elements and principles of A.I.

 AI refers to only a computer that is
able to “seem” intelligent by analyzing data and producing a
response. One example is “smart agents” that ask you certain
questions and then return recommendations based on your answers, all within a
friendly user-friendly environment. Other examples include computers that can
“learn” from mistakes in a limited way, such as the IBM chess program
that beat Kasparov. The defining aspect of this view is that the computer is
limited in it’s capacity; it’s intelligence is, in effect, only artificial at

There are certain applications of A.I. such as,

Speech Recognition :-

In the 1990s, computer speech
recognition reached a practical level for limited purposes. Thus United
Airlines has replaced its keyboard tree for flight information by a system
using speech recognition of flight numbers and city names. It is quite
convenient. On the other hand, while it is possible to instruct some computers
using speech, most users have gone back to the keyboard and the mouse as still
more convenient.

Understanding Natural Language :-

Just getting a sequence of words
into a computer is not enough. Parsing sentences is not enough either. The
computer has to be provided with an understanding of the domain the text is
about, and this is presently possible only for very limited domains.

Computer Vision :-

The world is composed of
three-dimensional objects, but the inputs to the human eye and computer’s TV
cameras are two dimensional. Some useful programs can work solely in two
dimensions, but full computer vision requires partial three-dimensional
information that is not just a set of two-dimensional views. At present there
are only limited ways of representing three-dimensional information directly,
and they are not as good as what humans evidently use.

Expert Systems :-

A “knowledge engineer” interviews
experts in a certain domain and tries to embody their knowledge in a computer
program for carrying out some task. How well this works depends on whether the
intellectual mechanisms required for the task are within the present state of
AI. One of the first expert systems was MYCIN in 1974, which diagnosed
bacterial infections of the blood and suggested treatments. It did better than
medical students or practicing doctors, provided its limitations were observed.

One most concerns of A.I. is that it may overpower its
own creators, the humans via continuous fast learning which may prove drastic
to human race (like portrayed in science fiction movies such as Robot (2010)).
It is very much important to observe and foresee and predict the consequences
of AI implementations instead of actually facing them afterwards. For Example,
use of A.I. in military during wars can lead to high levels of destructions.

So, to conclude, science should be in service of
humans and it always should be this way, not otherwise.


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