Artificial intelligence
(AI) is the intelligence of machines and the branch of computer science that aims to create it. 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. Artificial intelligence has been the inspiration for countless books and movies, as well as the aspiration of countless scientists and engineers.
Me and You have what’s called natural intelligence. The intelligence of a computer, by contrast, is artificial. Can the computer’s artificial intelligence ever match yours? For example, can the computer ever develop the “common sense” needed to handle exceptions, such as a broken traffic light? After waiting at a red light for several hours, the typical human would realize the light was broken. The human would try to proceed past the intersection, cautiously. Would a computer programmed to “never go on red” be that smart?
Researchers who study the field of artificial intelligence have invented robots and many other fascinating computerized devices. They’ve also been trying to develop computers that can understand ordinary English commands and questions, so you won’t have to learn a “programming language”. They’ve been trying to develop expert systems — computers that imitate human experts such as doctors and lawyers.
Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it
Unfortunately, most research in the field of artificial intelligence is just a lot of hot air.
Whenever a researcher in the field of artificial intelligence promises you something, don’t believe it until you see it and use it personally, so you can evaluate its limitations.
If a computer seems to give intelligent replies to English questions posed by a salesman or researcher demonstrating artificial intelligence, try to interrupt the demo and ask the computer your English questions. You’ll typically find that the computer doesn’t understand what you’re talking about at all: the demo was a cheap trick that works just with the peculiar English questions asked by the demonstrator.
For many years, the top researchers in artificial intelligence have been exaggerating their achievements and underestimating how long it will take to develop a truly intelligent computer. Let’s look at their history :
Artificial Intelligence in 1957 Herbert Simon said, “Within ten years a digital computer will be the world’s chess champion.” In 1967, when the ten years had elapsed, the only decent chess program was Greenblatt’s, which the American Chess Federation rated “class D” (which means “poor”). A computer didn’t become the world chess champion until 1997. It took forty years, not ten!
In 1957 Simon also said, “Within ten years a digital computer will discover and prove an important new mathematical theorem.” He was wrong. The computer still hasn’t discovered or proved any important new mathematical theorem. The closest call came in 1976, when it did the non-abstract part of the proof of the “4-color theorem”.
Artificial Intelligence in 1960 : Herbert Gelernter (who wrote the geometry-theorem program) said, “Today hardly an expert will contest the assertion that machines will be proving interesting theorems in number theory three years hence.” More than forty years have elapsed since then, but neither Gelernter nor anyone else has programmed the computer to prove theorems in number theory.
In June 1963 the Chicago Tribune said, “The development of a machine that can listen to any conversation and type out the remarks just like an office secretary was announced yesterday by a Cornell University expert on learning machines. The device is expected to be in operation by fall. Frank Rosenblatt, director of Cornell’s cognitive systems research, said the machine will be the largest thinking device built to date. Rosenblatt made his announcement at a meeting on learning machines at Northwestern University’s Technological Institute.” No such machine exists today, let alone in 1963.
Artificial Intelligence in 1970 : the head of artificial intelligence at MIT, Marvin Minsky, said, “In three to eight years we will have a machine with the general intelligence of an average human being. I mean a machine that will be able to read Shakespeare, grease a car, play office politics, tell a joke, have a fight. At that point, the machine will begin to educate itself with fantastic speed. In a few months it will be at genius level, and a few months after that its powers will be incalculable.” His prediction that it would happen in three to eight years — between 1973 and 1978 — was ridiculous.
Artificial Intelligence in the early 1980s : expert systems were believed to represent the future of artificial intelligence and of computers in general. To date, however, they have not lived up to expectations. Many expert systems help human experts in such fields as medicine and engineering, but they are very expensive to produce and are helpful only in special situations.
Anyway the greatest advances have occurred Artificial Intelligence in the field of games playing. The best computer chess programs are now capable of beating humans. In May, 1997, an IBM super-computer called Deep Blue defeated world chess champion Gary Kasparov in a chess match. On 11 May 1997, Deep Blue became the first computer chess-playing system to beat a reigning world chess champion, Garry Kasparov.
Artificial Intelligence in 2005 : a Stanford robot won the DARPA Grand Challenge by driving autonomously for 131 miles along an unrehearsed desert trail.
Artificial Intelligence in 2010 : Low-cost entertaining chess-playing software is commonly available for tablet computers. The Xbox 360 gaming system November 2010 Kinect 3D-body-motion interface uses algorithms that emerged from lengthy AI research, but few consumers realize the technology source.
In the area of robotics, computers are now widely used in assembly plants, but they are capable only of very limited tasks. Robots have great difficulty identifying objects based on appearance or feel, and they still move and handle objects clumsily.
Natural-language processing offers the greatest potential rewards because it would allow people to interact with computers without needing any specialized knowledge. You could simply walk up to a computer and talk to it. Unfortunately, programming computers to understand natural languages has proved to be more difficult than originally thought. Some rudimentary translation systems that translate from one human language to another are in existence, but they are not nearly as good as human translators. There are also voice recognition systems that can convert spoken sounds into written words, but they do not understand what they are writing; they simply take dictation. Even these systems are quite limited – you must speak slowly and distinctly.
In February 2011, in a Jeopardy! quiz show exhibition match, IBM’s question answering system, Watson, defeated the two greatest Jeopardy! champions, Brad Rutter and Ken Jennings, by a significant margin.
The leading-edge definition of artificial intelligence research is changing over time. One pragmatic definition is: “AI research is that which computing scientists do not know how to do cost-effectively today.”
For example, in 1956 optical character recognition (OCR) was considered Artificial Intelligence, but today, sophisticated OCR software with a context-sensitive spell checker and grammar checker software comes for free with most image scanners. No one would any longer consider already-solved computing science problems like OCR “artificial intelligence” today.
Currently, no computers exhibit full artificial intelligence
(that is, are able to simulate human behavior).
For years, researchers have been promising that intelligent, easy-to-use English-speaking computers and robots would be available at low prices “any day now”. After several decades of listening to such hoopla, I’ve given up waiting. The field of artificial intelligence should be renamed “artificial optimism”.
