Artificial intelligence is the branch of computer science concerned with making computers behave like humans. The term was coined in 1956 by John McCarthy at the Massachusetts Institute of Technology. Researchers are creating systems which can mimic human thought, understand speech, beat the best human chess player, and countless other feats never before possible.
Examples of Artificial Intelligence
Computers program to play games such as chess and checkers. You can buy machines that can play master level chess for a few hundred dollars. There is some AI in them, but they play well against people mainly through brute force computation--looking at hundreds of thousands of positions. To beat a world champion by brute force and known reliable heuristics requires being able to look at 200 million positions per second. The disadvantage of this program is you might waste your time while competing with the computer intelligence.
Programming computers to make decisions in real-life situations (for example, some expert systems help doctors diagnose diseases based on symptoms). They address problems normally thought to require human specialist for their solution. Expert systems, like human experts, are experts only in their field and as such are highly domain specific. Unlike human experts, once set up they need not be expensive, they can be easily and cheaply replicated and they do not grow old and start making errors. However, the problem that appears is that of responsibility. Take, for example, a system used by a doctor that is designed to administer drugs to patients according to their needs and that it must first determine what is wrong with them, very much like the prescribing work of a GP. If the system causes someone to take the wrong medicine and the person is harmed, who is legally responsible? Some would say the health authority who allowed the doctor to use the system; others would say the doctor, others the suppliers of the Expert System.
Computer programming that understand natural human languages. Probably the single most challenging problem in computer science is to develop computers that can understand natural languages. Fourth-generation languages are the programming languages closest to natural languages. The question of which language is best is one that consumes a lot of time and energy among computer professionals. Every language has its strengths and weaknesses. For example, FORTRAN is a particularly good language for processing numerical data, but it does not lend itself very well to organizing large programs. The choice of which language to use depends on the type of computer the program is to run on, what sort of program it is, and the expertise of the programmer. The advantage from this program is users do not need to learn any special commands or search protocols, just type the question in plain English.
A type of artificial intelligence that attempts to imitate the way a human brain works. Rather than using a digital model, in which all computations manipulate zeros and ones, a neural network works by creating connections between processing elements, the computer equivalent of neurons. The organization and weights of the connections determine the output. Neural networks are particularly effective for predicting events when the networks have a large database of prior examples to draw on. Strictly speaking, a neural network implies a non-digital computer, but neural networks can be simulated on digital computers. The field of neural networks was pioneered by Bernard Widrow of Stanford University in the 1950s. Neural networks are currently used prominently in voice recognition systems, image recognition systems, industrial robotics, medical imaging, and data mining and aerospace applications. The advantages of neural network are needs training to operate, the architecture of a neural network is different from the architecture of microprocessors therefore needs to be emulated and requires high processing time for large neural networks.
Robotics
The field of computer science and engineering concerned with creating robots, devices that can move and react to sensory input. Robots are now widely used in factories to perform high-precision jobs such as welding and riveting. They are also used in special situations that would be dangerous for humans -- for example, in cleaning toxic wastes or defusing bombs. It is also widely use in surgical and medical world. Although great advances have been made in the field of robotics during the last decade, robots are still not very useful in everyday life, as they are too clumsy to perform ordinary household chores. They also would be able to self-replicate, which would make them nearly impossible to stop. With their built-in intelligence, they could make duplicate upon duplicate of themselves in a short amount of time.
posted @ 10:30 PM |
