n thinking about Computer Science, but what does it really mean? Artificial Intelligence is an interdisciplinary field that includes computer science, physiology, and philosophy.
The combination of natural language (speaking like a human), to recognizing complex patterns in handwriting is one of the main goals most artificial intelligence scientist hope to achieve. Artificial intelligence was first coined in 1956 in a Dartmouth University Conference on technology. John McCarthy considered to be the Father of Artificial Intelligence, organized this conference to bring together scientist with interest in machine intelligence (Dumm, Snitzer, and Dyess). Artificial intelligence has been on the experimental end of Computer Science sense this groundbreaking conference. One of the most fascinating areas in Artificial intelligence is Neural Networks.
A neural network is a digitized model of the human brain simulated in the binary memory of a computer system (Garis). There are many properties that make up the neural network in relation to the modern computer. Neural networks have properties which are used for feature extraction, association, optimization, functions, and modeling (Gurney and Wright). There are just as many, if not more properties of neural networks in relation to the brain that need to be understood by scientist. Neuroscientist and psychologists believe, if computer models can be engineered to the level as a human brain, then questions about the neural make up of the gray matter in the brains of humans could be answered (Gurney and Wright).
Although many of the characteristics of the human brain remain unknown, its the complex network of neurons which give humans intelligent qualities. A neuron alone does not signify intelligence but, when grouped together with electrical signals, passing through the brain it becomes similar to a computers digital networking (Dumm, Snitzer, and Dyess). The fundamentals of how neural networks make the brain function, was proposed by two mathematicians named Warren McCulloch and Walter Pitts. Their hypothesis was based on experiments with neurons and that they might be considered devices for processing binary numbers (Dumm, Snitzer, and Dyess).
Binary numbers were represented as 1s and 0s and were important mathematical and computational process for inputting and outputting data. This link alone was the basis for computer-simulated neural networks. McCulloch and Pitts used principles based on George Booles postulates concerning how the brain makes true/false decisions. This produced Boolean algebra and the Boolean expression is now used as a reserve word in many programming languages to code true or false variable expressions (Dumm, Snitzer, and Dyess).
Using the ideas of the brain feedback theory McCulloch and Pitts, described a loop that exists between the senses, brain, and muscles. This introduced the conclusion that Memory could be defined as the signals in a closed loop neurons (Dumm, Snitzer, and Dyess). These conclusions all lead to the theory of artificial neural networks. There are many implications when realizing a world of computers, which inevitable are smarter than its creator. Moral dilemmas in many areas of science will be questioned.
Already, in present day many of us depend on computers in our everyday lives to drive us to work or safeguard our house. Also, there are many computer programs that utilized artificial intelligence and neural networks in todays high-level logic languages. Some examples of these programs are Prolog and Lisp. John McCarthy also created Lisp in 1958.
Prolog revealed itself in 1972 (Dumm, Snitzer, and Dyess). Both these languages are still used today. The 1980s hurt artificial intelligence research. For a lack of demands from companies, the industry lost close to a half a billion dollars in research funds (Dumm, Snitzer, and Dyess). Sense these early origins of artificial intelligence, scientists worry that a machine could be created and be capable of evolution and extreme intelligence beyond human comprehension.
Issues of whether or not to build this thinking machine will inevitable a result of backlash from society, military, and the government. Artificial intelligence and neural networks are on the pioneering edge of computer science. Advanced-level languages and computer interfaces owe their very existence to all areas of artificial intelligence research. Artificial intelligence is still in the groundbreaking stages some forty years later.
The computers available today are only bits and pieces of what .
