Posts Tagged ‘AI’

PostHeaderIcon Artificial Intelligence Overview

What is Artificial Intelligence?

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.

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 theses 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. Biological inspired AI approaches such as neural networks and genetic algorithms are already in place.


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.


There are many AI applications that we witness: Robotics, Machine translators, chatbots, voice recognizers to name a few. AI tehniques 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 loosing 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.


Stuart J. Russell, Artificial Intelligence: A Modern Approach (3rd Edition)

M. Tim Jones, Artificial Intelligence: A Systems Approach (Computer Science)

Patrick Henry Winston, Artificial Intelligence (3rd Edition)

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PostHeaderIcon References

Artificial Intelligence – References

[1] Patrick Henry Winston, Artificial Intelligence, Third Edition, Pearson Education.
[2] Dan W. Patterson, Introduction to Artificial Intelligence And Expert Systems, PHI.
[3] Stuart Russel & Peter Norvig, Artifcial Intelligence- A Modern Approach, PHI.
[4] Girratano & Riley, Expert Systems – Principles And Programming, Thomson Asia Pte Ltd.
[5] Tom M. Mitchell, Machine Learning, McGraw-Hill.
[6] Michael Wooldridge, An Introduction To Multiagent Sytems, John Wiley & Sons, Ltd.
[7] Christopher D. Manning & Hinrich Schutze, Foundations Of Statistical Natural Language Processing, The MIT Press.