Artificial Intelligence- Introduction
Artificial
Intelligence (AI) is the study and creation of computer systems that can perceive
reason and act. The primary aim of AI is to produce intelligent machines. The
intelligence should be exhibited by thinking, making decisions, solving
problems, more importantly by learning. AI is an interdisciplinary field that
requires knowledge in computer science, linguistics, psychology, biology,
philosophy and so on for serious research.
According to the
father of Artificial Intelligence, John McCarthy, it is “The science and
engineering of making intelligent machines, especially intelligent computer
programs”.
Artificial
Intelligence is a way of [Making a Computer, a Computer-Controlled Robot, or a
Software Think Intelligently,] in the similar manner the intelligent humans
think.
AI can also be
defined as the area of computer science that deals with the ways in which
computers can be made to perform cognitive functions ascribed to humans. But
this definition does not say what functions are performed, to what degree they
are performed, or how these functions are carried out.
AI draws heavily on
following domains of study.
1. Computer Science
2. Cognitive Science
3. Engineering
4. Ethics
5. Linguistics
6. Logic
7. Mathematics
8. Natural Sciences
9. Philosophy
10. Physiology
11. Psychology
12. Statistics
STRONG ARTIFICIAL
INTELLIGENCE
It deals with
creation of real intelligence artificially. Strong AI believes that machines
can be made sentient or self-aware. There are two types of strong AI:
Human-like AI, in which the computer program thinks and reasons to the level of
human-being. Non-human-like AI, in which the computer program develops a
non-human way of thinking and reasoning.
WEAK ARTIFICIAL
INTELLIGENCE
Weak AI does not
believe that creating human-level intelligence in machines is possible but AI
techniques can be developed to solve many real-life problems. That is, it is
the study of mental models implemented on a computer.
AI AND NATURE
Nowadays AI
techniques developed with the inspiration from nature is becoming popular. A
new area of research what is known as Nature Inspired Computing is emerging.
Biologically inspired AI approaches such as neural networks and genetic
algorithms are already in place.
CHALLENGES
It is true that AI
does not yet achieve its ultimate goal. Still AI systems could not defeat even
a three year old child on many counts: ability to recognize and remember
different objects, adapt to new situations, understand and generate human
languages, and so on. The main problem is that we, still could not understand
how human mind works, how we learn new things, especially how we learn
languages and reproduce them properly.
APPLICATIONS
There are many AI
applications that we witness: Robotics, Machine translators, chatbots, voice
recognizers to name a few. AI techniques are used to solve many real life
problems. Some kind of robots are helping to find land-mines, searching humans
trapped in rubbles due to natural calamities.
FUTURE OF AI
AI is the best field
for dreamers to play around. It must be evolved from the thought that making a
human-machine is possible. Though many conclude that this is not possible,
there is still a lot of research going on in this field to attain the final objective.
There are inherent advantages of using computers as they do not get tired or
losing temper and are becoming faster and faster. Only time will say what will
be the future of AI: will it attain human-level or above human-level
intelligence or not.
