In 1955, Dartmouth Professor John Macarthi first AI Conference – 1956 coined the word “Artificial Intelligence” (summer AI) as part of an academic grant to gather the Dartmouth Summer Research Project on Artificial Intelligence in 1956. The goal of this conference was to treat computers in such a way that humans could consider them intelligent. At that time, computer office buildings were occupying the entire floors, yet they had less processing power than most modern smart watches. To make these computers intelligent was a quite an ambitious goal, and the conference participants soon faced the boundaries inherent in the hardware at that time. He made very little progress towards creating a machine equal to the human brain. The most permanent contribution from this grant was the word “artificial intelligence”. It ignited everyone’s imagination and inspired journalists, writers, academics and computer scientists to imagine a future world in which machines would think like humans. If Professor Macarthi had brought some other name, this conference would have faded with full possibility, with full possibility. However, due to the selection of Macarthi’s words, “artificial intelligence” has continued to promote imagination and further progress towards making intelligent machines.
Unfortunately, the concept of artificial intelligence and the possibility of human beings to replace humans by machines at the workplace scares most people. Just think if the first personal computer was called “artificial employee”. As soon as the first PC comes to his office, the employees would get nervous. Personal computers look attractive to hear. Artificial employees threaten to snatch their jobs! Similarly, the word “artificial intelligence” produces the sprinkling in the spine of many people who depend on their intelligence for their jobs. It may include professionals like lawyers, doctors and analysts. They can all imagine a day when they will be replaced by computerized counterparts. To reduce the fear associated with artificial intelligence, it is important to separate the term from the technique. While the word exposes the image of humans replacing humans by sensitive and perhaps omarent machines, the technique is more suppressed. You will not get to see the mechanized version of the human brain in the near future. As a technology, artificial intelligence is just a system that reflects a behavior that can be interpreted as human intelligence, such as winning chess games against the world famous chess master.
What is intelligence? The dictionary has the ability to mimic the intelligent human behavior of a machine. However, determining the meaning of “intelligence” is a big challenge. While we all agree that intelligence has something to do with knowledge and ability to argue, human intelligence goes beyond this and consists of consciousness or self-awareness, knowledge, emotion, sympathy, intuition and creativity. For some people, intelligence also includes spirituality – a great power or a creature. Our ability to define “intelligence” further challenges that human intelligence comes in many forms. While some people are highly intelligent in the field of mathematics, others are excellent in art, music, politics, business, medicine, law, linguistics etc. Some people may be excellent in academics, while others are skilled in business or have high levels of emotional ability. And although people have tried to develop a single standard to measure intelligence, such as intelligent quotient (IQ), such standard are odd. For example, a common IQ test only evaluates short -term memory, analytical thinking, mathematical ability and spatial identity.
Without a reliable standard to measure human intelligence, it is very difficult to say by pointing to a computer that it is behaving wisely. Computers are definitely very good in doing some tasks and maybe they do much better and faster work than humans, but does it make them intelligent? For example, computers have been able to defeat humans in chess for decades. IBM Watson defeated some of the best champions in the game show Jeopardy. Google’s Deepmind has defeated the best players in the 2500 -year -old Chinese game “Go” – this is such a complex game that the board’s potential configurations are more than at the atoms in the universe. Nevertheless, none of these computers understand the purpose of a game or there is no reason to play.
As much as these achievements are effective, they are still a product of special talent of computer for pattern matching – to remove information from their database that enables it to answer a question or do some task. This seems to be intelligent behavior only because the computer is excellent in that particular task. However, we rarely credited other machines for human characteristics, such as boats that can “swim” fast or hydraulic jacks that are “strong” and easily lift a car above the mechanic’s head. In many ways a game is an ideal environment for computer. It has rules with certain possibilities that can be stored in the database. When Watson of IBM played Jepardi, he just had to do so that use a natural language processing (NLP) to understand the question, move faster than other competitors and apply pattern matching to find the correct answer in your database.
Initial AI developers knew that computers had the ability to excel in the world of rules and possibilities prescribed. A few years after the first AI conference, the developers had the first edition of the chess program. This program could mix the tricks of the opponent with thousands of potential counter -moves and by playing thousands of games, it could decide which pawn to take and which pawn to take, and it could be done in a few seconds. Artificial intelligence is always more impressive when computers are on their home ground – when the rules are clear and the possibilities are limited. The most benefits from AI to organizations that work in a well -defined place with the prescribed rules, so it is no surprise that organizations such as Google fully adopt AI. Google’s entire business is associated with pattern matching – mixing users’ questions with the vast database of answers. AI experts often call it good old -fashioned Artificial Intelligence (GOFAI). If you are thinking about including AI in your business, consider what computers are really good – pattern matching. Are there a lot of patterns in your organization? Are rules and possibilities fixed in many of your work? This will be the same thing that will first benefit from AI.
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