Computers have many uses. They are great for storing and working with large amounts of information, they are fun for playing games, they are the foundation of the Internet, they let you write and edit your essays, and many other interesting things.
Computers can also process information very quickly. This makes some people see computers as being very similar to human brains. There is an area of research that is trying to create machines that can "think". This field is called artificial intelligence - it combines the fields of computer science, psychology, and philosophy.
Researchers
are trying to create machines that can think like humans, understand the
spoken word, and beat even the best chess players. The human brain is made
up of billions of cells called neurons that make up the physical system for
thinking. It is perhaps the most complex system in the world. To build
something like that in a computer is what artificial intelligence is all
about.
In 1941, the electronic computer was developed in both the United States and Germany, and research into artificial intelligence began. The computers in 1941 were so big they took up entire rooms! It was 15 years later, however, that the term artificial intelligence was first used at a conference at Dartmouth.
There are certain ideas that are common in the field of artificial intelligence. One important concept was invented by the British computer scientist Alan Turing, called the Turing test. The Turing test is a test to see if a computer is intelligent. In the test, a human communicates by means of a typewriter or keyboard to a test subject, but the person does not know whether the test subject is a human or a computer. If the person can't tell the difference, then the computer is considered intelligent. When Alan Turing proposed this idea in 1950, it seemed like a very difficult test that would really show if a computer was intelligent. Now, however, there are very simple computer programs that seem like they could pass the test, but they do not seem to be truly intelligent. Try talking to an online psychiatrist. Could you tell that you're not talking to a human?
We really aren't at the stage yet where we have machines that can actually think like humans. The American army used "intelligent" missiles in the Gulf War, the IBM computer Deep Blue beat chess champion Garry Kasparov, and very simple computer programs can pass the Turing test. None of these programs, however, really seem smart enough to say that they have actual "intelligence". For example, Deep Blue had a much larger capacity to store information about possible moves, but it couldn't use intuition or have hunches. Also, there is still no emotion built into artificial intelligence. Whether that is really needed for intelligence is an important question.
This is just one of many questions about what intelligence actually is. In the field of artificial intelligence, there are two main theories about how intelligence should be created. These theories are called bottom-up and top-down processing. Bottom-up theorists believe that to create artificial intelligence, researchers should build electronic imitations of the human brain's neural network. Top-down theorists believe that using computer programs to imitate the brain's behaviour is the best way to create artificial intelligence. There are also two opposite theories on how artificial intelligence can function. There are two ways that it functions right now: parallel processing and neural networks. Parallel processing is most like the computers we use today. They are programmed to work in order; one thing happens which triggers the next thing in line to happen, and so on. Neural networks work like the human brain. In the brain, if one neuron sends out information, it may send it out to many other neurons which may in turn activate many other neurons. This way, the information moves in a web-like pattern which is faster than parallel processing which moves in a straight line - linearly.
As computers become more and more a part of the world, artificial intelligence will become an even more practical and interesting field.
Physics | Chemistry | Biology | Engineering | Computer Science | Understanding Science and Technology