Key Features Of Artificial Intelligence

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Abstract: The main purpose of this paper is to highlight the key feature of Artificial Intelligence. Artificial Intelligence, one of the blooming technologies of the 20th century. Artificial Intelligence ia a development in computer science which is able to perform human tasks. An expert system is a computer program that uses artificial intelligence (AI) technologies to simulate the judgment and behavior of a human or an organization that has expert knowledge and experience in a particular field. The central goals of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects.
Keywords: Artificial Intelligence, Cognitive Computing, Neural …show more content…

Similar to the human brain they think and decide when it comes to making a choice. They use different types of algorithms and patterns to learn on their own and develop natural language processing. Cognitive computers can think and work on their own without the need of human assistance. These computers have a unique ability know as machine learning. Machine learning is a process in which the computer gains knowledge by itself by mining the information that is fed to them. Since they have self-learning capabilities they can get better over time. Similar to humans they can throw out more solutions for complicated questions as they get …show more content…

An Artificial Neural Network is an information processing prototype that is inspired by the way that the brain works to process several information. The ability to make connections between raw facts and draw conclusions based on the data is central to learning. With the help of common sense human beings make such connections. However this common sense is hard when it comes to implementing on a computer. ANN is composed with large number of highly interconnected processing elements (neurons) working in unison to solve specific problem, which is very similar to human. Neural networks, with their remarkable ability to derive meaning from complicated data, can be used to extract patterns that are too complex for humans or for any other intelligent machines. Each node in a neural network should be ready to take up a number inputs, which further must be processed to determine the connections that should be made, and send outputs to the relevant nodes determined in the previous step. Individual processing element in a neural network receives a number of inputs and conclude to which processing elements it should send the input, and outputs the processed data much like a human neuron does. There are still many problems in neural network research, creating algorithms to make the connections and to determine which sets of data should be connected or processed, and even to abandon irrelevant data when it is necessary to do

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