Ray Kurzweil, American author, computer scientist, inventor and futurist, once said, “Artificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilisation a billion-fold.”
Evolution of AI
The human race has fantasised about thinking machines right from the time of classical Greece. Homer’s Iliad talks about robots that were made by Greek God Hephaestus. While some of these robots were like humans, others were mere machines such as the golden tripods that served food and wine at feasts.
With the advent of modern computers it became feasible to create programs that performed difficult intellectual tasks. The first half of the 20th century saw British mathematicians and philosophers Bertrand Russell and Alfred North Whitehead publish Principia Mathematica, which revolutionised formal logic.
In 1923, Karel Kapek’s play R.U.R. (Rossum’s Universal Robots), staged in London in 1923, was the first to use the word robot in English language. Much later, in 1956, John McCarthy created the phrase artificial intelligence (AI) while looking for words to describe the key topic of a conference. The same year saw the demonstration of the first running AI program, Logic Theorist (LT), written by Allen Newell, J.C. Shaw and Herbert Simon, who were eminent personalities from Carnegie Institute of Technology, USA.
In the decade spanning 1952 to 1962, Arthur Samuel from IBM wrote the first game-playing program, for checkers, with enough ability to challenge a world champion. In 1965, Joseph Weizenbaum from Massachusetts Institute of Technology (MIT), USA, created ELIZA—an interactive program that was capable of participating in a discussion on any subject in English language.
The first national conference of American Association of Artificial Intelligence (AAAI) was held in 1980 at Stanford, USA. By 1990s, key advances had taken place in all areas of AI, with noteworthy achievements in machine learning, intelligent tutoring, case based reasoning, multi-agent planning, scheduling, uncertain reasoning, data mining, natural language understanding and translation, vision, virtual reality, games and many other topics.
And, it was in 1997 that Deep Blue, an IBM supercomputer, beat the current world chess champion, Garry Kasparov. By late 1990s, Web crawlers and other AI based information extraction programs became indispensable in the widespread use of the World Wide Web.
An introduction to AI
AI is the science and engineering of making intelligent machines, more so, intelligent computer programs. In simple terms, if a computer performs a function which if a human was to do would be called intelligent, then we can say the computer has intelligence.
Intelligence is a combination of knowledge and reasoning power since reasoning power construes facts that are unknown to knowledge. This criteria for AI is a very challenging task given that computers work on binary logic. When a computer only knows yes and no, it is demanding to achieve results that are not strictly defined.
For example, if we had to create an AI thermostat to cool a house, the program would need to have knowledge of all seasons, weather conditions like El Niño and passage of time, plus it must be able to understand concepts like warm, cool or too cold, apart from other aspects.
While we do not really realise it, the simplest human functions translate to thousands of lines of computer code. Most current AI systems are designed for only a few specific applications. One of the most popular examples of an AI application was a chess program running on Deep Blue, IBM’s massively-parallel-computing system.
Deep Blue managed to defeat world chess champion Gary Kasparov because it could search 50 to 100 billion positions in the three minutes that each player had, to make their move.
AI applications can be bucketed as knowledge based or expert systems. A minor knowledge based system could be a series of conditional statements, such as:
the animal is a bird
it does not fly
it is black and white
THEN it is a penguin.
As this system becomes more complex, the time it takes for a computer to arrive at an intelligent outcome becomes unacceptably high. Expert systems try to solve this issue by acquiring more knowledge from a human being by asking questions. Over time, the program learns from experience and can actually solve problems or give advice based on what it has learned.