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Intelligence is the ability to learn about, to learn from and understand and interact with one's environment. Artificial intelligence is the intelligence of machines and is a multidisciplinary field which involves psychology, cognitive science, and neuroscience and computer science. It enables machines to become capable of doing those things which the human mind can do. Though the folklore of artificial intelligence dates back to a long time ago, it actually became available to people only after the development of the electronic computer. Today research in artificial intelligence is so highly invested in and the field has significantly advanced to such an extent that it has become a huge part of our lives and it is considered to be America's Next big thing.
If we look at the definition of intelligence, there are probably infinite ones. But if we put it into the most refined words, then intelligence is only ones ability to acquire or gain knowledge. It is one's ability and capacity to learn from his or her environment and possibly also to have a chance to give back to it. When we say the ability to learn we are talking in very general terms. It includes in itself certain characteristics that one person must have. They include characteristics such as one's ability to be able to adapt to new or changing environments and also the ability to reason, think, comprehend, judge and evaluate situations. Intelligence determines how one can achieve goals in this world. The degree of intelligence in people, animals and in machines differs significantly. (Hawkins and Blakeslee)
Artificial intelligence is the intelligence which is solely dedicated to machines. It is a multidisciplinary field which involves at least psychology, cognitive science, neuroscience and most importantly computer science. Typically it is seen as a branch of computer sciences. The field is a study and design of several intelligent agents. Intelligent agents are systems that carefully analyze and monitor and then consequently take note of what goes on in the environment and then take actions in order to get the most out of chances of success. We can define artificial intelligence as the ability of any hardware or software to be able to do things that human beings identify or characterize as intelligent. These activities include:
Searching: to be able to find relevant information after being given very few directives. The relevant information has to be found from a large database of available information.
Surmounting constraints: the ability to find techniques to fit things in to limited spaces and be able to build upon complex scenarios and objects.
Recognizing patterns: finding items which have similar characteristics or identifying entities that do not match at all,
Making logical inferences: ability to draw conclusions based upon what is understood and reasoning methods such as deduction and induction.
The word artificial intelligence comes from technology which branches out from the Greek word techno. Techno means art and skill. When we call any technology sophisticated it means it is a combined structure of skills and processes. The skills and processes in this case are refined and learned. In artificial intelligence these processes have made themselves apparent in a number of ways including neural networks, expert systems, automatic speech recognition etc. (Hawkins and Blakeslee)
History for artificial intelligence began when McCulloch and Walter Pitts, in 1943, proposed a model of artificial neurons. Each neuron was characterised as either being on or off. A neuron was turned on when significant numbers of neighbouring neurons were stimulated. Evidence of the presence of Artificial intelligence can be seen to date as far back to ancient Egypt, but of course the technology only became available with the development of the electronic computer in 1941. Computers were the necessary technology and were needed if artificial intelligence was to be made available. But it was only in the 1950's that a link could be established between the computers and the intelligence of humans.
Norbert Wiener was one of the first persons who made the observation between human intelligence and how computers could be used to imitate some form of their intelligence. He made his observations on the principles of the feedback theory. He used the thermostat as an example. A thermostat is a device that controls the temperature of the environment by collecting the actual temperatures of the environment and then comparing it to the desired temperature after which it responds by either turning the heat up or turning it down. What was so important about Norbert's research was that he put intelligent behaviour on to paper. It was the discoveries made by Norbert that had influenced the early development of artificial intelligence. (Hawkins and Blakeslee)
Mechanical reasoning has been a topic of muse for several philosophers and mathematicians since time immemorial. They have done several studies on logic that have directly led to the inventions of digital electronic computers which were based on the works of a mathematician by the name of Alan Turing. Turing suggested that the new electronic computer could shuffle symbols which were as simple as 0 and 1 and could reproduce any thinkable mathematical assumption. It was Turing's suggestion along with several discoveries that took place in the fields of neurology, information theory and cybernetics that paved a way for the building of an actual electronic brain. (Scheier and Pfeifer)
Research in the field of artificial intelligence started in 1956. Leaders of the research and their students had begun to write papers in which computers were solving algebraic word problems and speaking English. Those who had founded artificial intelligence were very enthusiastic about the future of the technology and had foreseen that one day machines would be able to do many things that man is capable of doing. In 1974 research related to the field of artificial intelligence came to a halt up till about the early 1980's when there was a success of the expert systems. Expert systems are a category of artificial intelligence that is able to replicate knowledge and analytical skills of human experts. By the mid-80's the artificial intelligence market had reached enormous heights. (Scheier and Pfeifer)
When developing an artificial intelligence system or machine a question that immediately comes to mind is whether a machine can actually act intelligently or not. Keeping in mind this question many of those who researches in this field have attempted to build such machines that have the capability of thinking intelligently. There are several traits that researchers and developers of the artificial intelligence system would like to see in the machines that they build.
Developers want to make machines that are able to deduce reason and solve problems. Early researchers in the field of artificial intelligence had developed several algorithms which were able to imitate reasoning that humans used to solve problems or make logical deductions. By the 1990's such algorithms were employed into the system that were able to deal with incomplete information and concepts related to even probability and economics. As problems become increasingly complex, algorithms become complex as well and the amount of memory and computer time that is required can become too large. There is an ongoing search for more efficient algorithms. (Scheier and Pfeifer)
Knowledge representation is another key aspect for the developers of artificial intelligence. Many problems that machines have to solve require that it has a thorough knowledge about the world or the surroundings. The most difficult part of knowledge representation for artificial intelligence systems is default reasoning and qualification problems.
Planning is also very important when it comes to building an artificial intelligence system. When making a machine which is to be based on the artificial intelligence it is important that it knows how to plan properly just like the human mind. The intelligent agents are required to set particular targets and consequently be able to achieve those targets as well. (Jones)
Machine learning is also central to this field of study. The machine has to be able to find distinct patterns in a flow of inputs. The machine must be able to classify i.e. determine what category a particular thing belongs to and then be capable of finding a relationship between the inputs and the outputs and see how changing the inputs changes the outputs. There is also reinforcement learning in which the agent is rewarded for a good act and punished for a bad one.
Natural language processing gives machines the ability to read and understand the language that humans speak. This is also important to the field of artificial intelligence. A powerful processing system enables a natural language user interface that allows acquiring knowledge from human written sources like texts. One way in which we can decipher or get meaning out of natural language is by using semantic indexing in computers. (Jones)
Machines must be able to use the input that they receive from their sensors in order to make interpretations of different things that are happening around them. The ability to analyse visual input is called computer vision for…[continue]
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Bibliography Daniel Dennett (1998) Brainchildren: Essays on Designing Minds. MIT Press, 1998. Arthur R. Jensen (1998) Does IQ matter? Commentary, pages 20-21, November 1998. John McCarthy (1959) Programs with Common Sense in Mechanisation of Thought Processes, Proceedings of the Symposium of the National Physics Laboratory, pages 77-84, London, U.K., 1959. Her Majesty's Stationery Office. John McCarthy (1989) Artificial Intelligence, Logic and Formalizing Common Sense. In Richmond Thomason, editor, Philosophical Logic and Artificial Intelligence. Kluver Ac John
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