Neural Networks
Abstract
This paper will provide an introductory level discussion of neural networks within the field of artificial intelligence. This discussion will briefly cover the history of the neural network as well as recent advances within this field. In addition, several real world applications of neural networks will be discussed.
Introduction
The primary goal in the field of artificial intelligence is to construct a machine with an intellect comparable to that of a human. This pursuit of an artificial intelligence has had a long history. Several different approaches have been attempted as a result of this goal. In particular, the study of neural networks has evolved from this pursuit for an intelligent machine.
The field of neural networks involves a new approach to computing that uses mathematical structures with the ability to learn (Zsolutions). These methods were inspired by investigations into modeling nervous system learning (Zsolutions). For example, neurons in the human brain are used to transmit data back and forth to each other. Artificial neural networks use this same technique to process various kinds of information (Fu, p 4).
There are a wide variety of applications in which neural networks can be utilized. Primarily, they should be used in areas where standard techniques fail to give satisfactory results (Zsolutions). Neural networks are applied best in situations where information needs to be determined faster and with more efficiency. In addition, neural networks outperform other artificial intelligence approaches in areas where more detail can be learned from inputted data (Zsolutions).
Discussion
The technology of neural networks has been in existence for approximately forty years ...
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...dapt as more data is input into the network. The recent advances within the field of neural networks are just beginning of what may potentially become the solution to creating a truly intelligent machine. The success that neural networks have had in the few areas that have implemented it should be enough to make others realize the strength of a neural network. As neural networks grow in popularity, so too will the advancements in the field. In my opinion, neural networks will eventually be the driving force behind all artificial intelligence attempts.
Bibliography
1. Fu, Limin. Neural Networks In Computer Intelligence. McGraw-Hill Inc. 1994.
2. http://www.cio.com/archive/cio_011596_neural_feature.html
3. http://www.inc.com/beyondthemag/between_the_pages/neural.html
4. http://www.merlin.com.au/brain_proj/neur_net.htm
5. http://www.zsolutions.com/
The advent of neural net with the seminal work of Hopfield , popularized the use of machine intelligence techniques in the pattern recognition. However, the dense and inherent structure of neural networks is not suitable for VLSI implementation. So, researchers in the neural network domain tried to simplify the structure of the neural network by pruning unnecessary connections. Simultaneously, the CA research community explored the advantages of the sparse network structure of cellular automata for relevant applications. The hybridization of cellularity and neural network has given rise to the popular concept of cellular neural networks.
Artificial Intelligence (AI) is one of the newest fields in Science and Engineering. Work started in earnest soon after World War II, and the name itself was coined in 1956 by John McCarthy. Artificial Intelligence is an art of creating machines that perform functions that require intelligence when performed by people [Kurzweil, 1990]. It encompasses a huge variety of subfields, ranging from general (learning and perception) to the specific, such as playing chess, proving mathematical theorems, writing poetry, driving a car on the crowded street, and diagnosing diseases. Artificial Intelligence is relevant to any intellectual task; it is truly a Universal field. In future, intelligent machines will replace or enhance human’s capabilities in
Goertzel, B., & Pennachin, C. (2007). In Artificial General Intelligence. Heidelburg, New York: Springer Berlin. Retrieved on July 31, 2010 from Google books Database.
"My name is Dorothy," said the girl, "and I am going to the Emerald City, to ask the Oz to send me back to Kansas."
indicates towards a fraud. On eof the most important qualities or benefits of this model is that it understands the pattern in the data and generates the result. Once the result is generated the model checks as to how close was the result from the actual results. Based on this analysis the model adjusts its weights to give an accurate result the next time. Once this model has been trained to give accurate results, it can be used to analyze other data as well. Even when Neural Networks are widely accepted, they are not really used that much in the marketing industry merely by the fact that data preparation for this model is very complex time consuming as compared to the Regression Analysis. The marketers are much comfortable using the Regression Analysis over Neural Networks because of the ease of interpreting the results in the Regression Analysis.
As our research into science and technology ever increases its seems inevitable that in the near future Artificial Intelligent machines will exist and become part of our everyday life such as we see with modern computers today.
The traditional notion that seeks to compare human minds, with all its intricacies and biochemical functions, to that of artificially programmed digital computers, is self-defeating and it should be discredited in dialogs regarding the theory of artificial intelligence. This traditional notion is akin to comparing, in crude terms, cars and aeroplanes or ice cream and cream cheese. Human mental states are caused by various behaviours of elements in the brain, and these behaviours in are adjudged by the biochemical composition of our brains, which are responsible for our thoughts and functions. When we discuss mental states of systems it is important to distinguish between human brains and that of any natural or artificial organisms which is said to have central processing systems (i.e. brains of chimpanzees, microchips etc.). Although various similarities may exist between those systems in terms of functions and behaviourism, the intrinsic intentionality within those systems differ extensively. Although it may not be possible to prove that whether or not mental states exist at all in systems other than our own, in this paper I will strive to present arguments that a machine that computes and responds to inputs does indeed have a state of mind, but one that does not necessarily result in a form of mentality. This paper will discuss how the states and intentionality of digital computers are different from the states of human brains and yet they are indeed states of a mind resulting from various functions in their central processing systems.
Scientists claim that devices with Artificial Intelligence will replace office workers during next 5 years (Maksimova).According to this statement it is possible to say that AI has a great influence on humanity. Pursuant to Oxford Dictionary Artificial Intelligence or AI is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages(dictionary).Firstly, this research will analyze positive and negative impacts of development of Artificial Intelligence on economic sphere. Then, author going to discuss social effects of Artificial Intelligence. After the considering all perspectives that link to this topic, the last step will be to draw a conclusion.
The approach to artificial intelligence should be proceeded with caution. Throughout recent years and even decades before, it has been a technological dream to produce artificial intelligence. From movies, pop culture, and recent technological advancements, there is an obsession with robotics and their ability to perform actions that require human intelligence. Artificial intelligence has become a real and approachable realization today, but should be approached with care and diligence. Humans can create advanced artificial intelligence but should not because of the harm they may cause, the monumental advancement needed in the technology, and that its harm outweighs its benefits.
Gonzales, M. E. Q. Neural networks and Mental Representation: An essay on Harmony and Rationality. In: Trans/ Form/Ação, São Paulo, v. 14, p.93-108, 1991.
Artificial neural networks are systems implemented on computer systems as specialized hardware or sophisticated software that loosely model the learning and remembering functions of the human brain. They are an attempt to simulate the multiple layers of processing elements in the brain, called neurons. These elements are implemented in such a way so that the layers can learn from prior experience and remember their outputs. In this way, the system can learn to recognize certain patterns and situations and apply these to certain priorities and output appropriate results. These types of neural networks can be used in many important situations such as priority in an emergency room, for financial assistance, and any type of pattern recognition such as handwritten or text-to-speech recognition.
Artificial Intelligence is the scientific theory to advance the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines. This is going to hold the key in the future. It has always fa...
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Machine learning systems can be categorized according to many different criteria. We will discuss three criteria: Classification on the basis of the underlying learning strategies used, Classification on the basis of the representation of knowledge or skill acquired by the learner and Classification in terms of the application domain of the performance system for which knowledge is acquired.
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