What is Artificial Intelligence? What has Artificial Intelligence reached in the past? What are appreciable milestones of Artificial Intelligence in the last years? What will Artificial Intelligence solve in 5 years, 20 years, 50 years or 100 years from now? And how will look Artificial Intelligence the future?
Definition of Artificial Intelligence
Artificial Intelligence is composed of two words.
Artificial is something that is not real, which is a fake or something simulated. The simplest thing what I can think is an artificial arm. Artificial arm is not a real arm, it is a fake. People use it to replace to loss of an arm and have a life as close as if we had a true arm.
But this is not the point I want to make. The point is that there are some reasons why there are things that are artificial and replaced by real things.
Intelligence is a long term with a lot of meanings like; logic, understanding, self-awareness, learning, knowledge, planning and creativity.
We are humans because we have all this terms in us, based on these we make choices and take decisions. The same applies to animals. The interesting point about intelligence on animals is, that there are many different species and because of that we can compare intelligence on between species. In both cases (human intelligence and animal intelligence) we talk about natural intelligence (NI).
To understand more about Artificial Intelligence, we go to the history of Artificial Intelligence to see what Artificial Intelligence is capable of and how its status quo relates to the present.
We are humans because we perceive our enviroment, learn from it and take action based on what we discovered
History of Artificial Intelligence
The history of artificial intelligence is very interesting and started over 100 years ago.
Rossum´s Universal Robots
In 1920, the Czech writer Karel Čapek published a work of science fiction called Rossumovi Univerzální Roboti (Rossum’s Universal Robots), also better known as R.U.R. The work introduced the word robot. R.U.R. it’s about a factory, which creates artificial people named as robots. In R.U.R. Robots are living creatures, which are more similar to the term of the clones. At the begining they worked for humans, but then comes a rebellion of robots that leads to the extinction of the human race.
Alan Mathison Turing was an English computer scientist, mathematician, logician and theoretical biologist.
Turing was highly influential in the development of theoretical computer science, providing a formalisation of the concepts of algorithm and computation with the Turing machine, which can be considered a model of a general purpose computer. Turing is widely considered to be the father of theoretical computer science and artificial intelligence.
The Dartmouth workshop
In the early 1950s, there were various names for the field of “thinking machines” such as cybernetics, automata theory, and complex information processing. These indicate how different the ideas were on what such machines would be like.
In 1955 John McCarthy, then a young Assistant Professor of Mathematics at Dartmouth College, decided to organize a group to clarify and develop ideas about thinking machines. He picked the name ‘Artificial Intelligence’ for the new field. He chose the name partly for its neutrality; avoiding a focus on narrow automata theory, and avoiding cybernetics which was heavily focused on analog feedback, as well as him potentially having to accept the assertive Norbert Wiener as guru or having to argue with him.
In early 1955, McCarthy approached the Rockefeller Foundation to request funding for a summer seminar at Dartmouth for about 10 participants. In June, he and Claude Shannon, a founder of Information Theory then at Bell Labs, met with Robert Morison, Director of Biological and Medical Research to discuss the idea and possible funding, though Morison, was unsure whether money would be made available for such a visionary project.
The proposal states:
We propose that a 2 month, 10 man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College in Hanover, New Hampshire. The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer.
Deep Blue was a chess-playing computer developed by IBM. It is known for being the first computer chess-playing system to win both a chess game and a chess match against a reigning world champion under regular time controls.
Deep Blue won its first game against a world champion on 10 February 1996, when it defeated Garry Kasparov in game one of a six-game match. However, Kasparov won three and drew two of the following five games, defeating Deep Blue by a score of 4–2. Deep Blue was then heavily upgraded, and played Kasparov again in May 1997. Deep Blue won game six, therefore winning the six-game rematch 3½–2½ and becoming the first computer system to defeat a reigning world champion in a match under standard chess tournament time controls. Kasparov accused IBM of cheating and demanded a rematch. IBM refused and retired Deep Blue.
Development for Deep Blue began in 1985 with the ChipTest project at Carnegie Mellon University. This project eventually evolved into Deep Thought, at which point the development team was hired by IBM. The project evolved once more with the new name Deep Blue in 1989. Grandmaster Joel Benjamin was also part of the development team.
In 2013, DeepMind, one of the most important artificial intelligence investigations in the world, presented an AI that could play a couple of Atari games at the top of a human player level. This first seems not to be very expressive, but they simply used the reinforcement of learning and neural networks to allow artificial intelligence to learn these games. In addition, they only used the pixels as an input for the agent, so no direct reward was assigned to the agent based on the movements he made.
In 2015, they introduced a more intelligent agent, who successfully played 49 classic Atari games.
There are already Artificial Intelligence systems that can surpass humans in specific areas, such as playing GO or data analysis. Today, if we talk about Artificial Intelligence systems in production, we refer to specialists. But there is still no General Artificial Intelligence (AGI), which can act as a human, and there is no superintelligence, which is more intelligent than a human being.
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