Wait a second!
More handpicked essays just for you.
More handpicked essays just for you.
Human brain versus computer brain
Essay on history of artificial intelligence
Essay on the history of artificial intelligence
Don’t take our word for it - see why 10 million students trust us with their essay needs.
Recommended: Human brain versus computer brain
Artificial neural networks (ANNs) were built to model the brain for the purpose of solving the problems humans alone cannot as well as to advance, artificial intelligence. To approximate organic beings and gain great computational power, to become a technological hybrid between sentient beings and advanced electronics; they are the future of advanced robotics.
They can be used in miscellaneous fields such as speech recognition, prediction of stocks, weather and so on.
Artificial neural networks (ANNs) approximates the probable function that will likely produce the best output. This is done through extensive training of the system and the use of ample training rules which allows the ANNS to recognise repetitive paradigms and use them to solve problems that the system has not encountered before. These systems model the mammalian cerebral cortex (the brain) and its neurons, hence the name artificial neural networks. Before understanding the complex structure of an artificial neural network, a rudimentary knowledge of an organic neural network is essential.
The human brain consists of over billions of neurons interconnected by trillions of synapses. Neurons exchange electrical impulses through the synapses attained from other neurons or from the senses. When something novel is experienced, these neurons create new connections which may weaken, fortify or alter through time. These are the experiences or the memories that humans recollect and is a basis for the fundamental of decision making and problem solving. Artificial neural networks use these same principles; they model an approximate function based on the input and output rules and use this function to predict the output for a problem that the system has never faced. The simple...
... middle of paper ...
...hworks.com.au/products/neural-network/ http://www.techopedia.com/2/27888/programming/what-is-the-difference-between-artificial-intelligence-and-neural-networks http://wiki.answers.com/Q/Relationship_between_artificial_intelligence_and_neural_networks_with_help_of_a_scenario?#slide=1 https://sites.google.com/site/assignmentssolved/mca/semester4/mc0076/5 https://sites.google.com/site/assignmentssolved/mca/semester6/mc0088/6 http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html http://fann.sourceforge.net/fann_en.pdf http://books.google.com.au/books?hl=en&lr=&id=RTtvUVU_xL4C&oi=fnd&pg=PR9&dq=artificial+neural+networks&ots=Gaf-ujyEVC&sig=EkmwrfqC4MRdpHPyDnp5VDbDtFk#v=onepage&q=artificial%20neural%20networks&f=false http://osp.mans.edu.eg/rehan/ann/Artificial%20Neural%20Networks.htm
http://www.psych.utoronto.ca/users/reingold/courses/ai/cache/neural2.html
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.
How can the brain be a mind, a conscious person? Recently, some philosophers have argued that human consciousness and cognitive activity, including even our moral cognition and behavior, can best be explained using a connectionist or neural network model of the brain (see Churchland 1995; Dennett 1991 and 1996). (1) Is this right? Can a mass of networked neurons produce moral human agents? I shall argue that it can; a brain can be morally excellent. A connectionist account of how the brain works can explain how a person might be morally excellent in Aristotle's sense of that term.
Kandel, E. R., J. H. Schwarz, and T. M. Jessel. Principles of Neural Science. 3rd ed. Elsevier. New York: 1991.
The future may well involve the reality of science fiction's cyborg, persons who have developed some intimate and occasionally necessary relationship with a machine. It is likely that implantable computer chips acting as sensors, or actuators, may soon assist not only failing memory, but even bestow fluency in a new language, or enable "recognition" of previously unmet individuals. The progress already made in therapeutic devices, in prosthetics and in computer science indicate that it may well be feasible to develop direct interfaces between the brain and computers.
"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."
(Scientists have discovered that there are a large number of internal brain structures, which work together with the input and output brain structures to form fleeting images in the mind. Using these images, we learn to interpret input signals, process them, and formulate output responses in a deliberate, conscious, way.)
Stergiou, C., & Siganos, D. (2011, August 6). Neural Networks. Retrieved August 6, 2011, from
Artificial Intelligence played a crucial role in our American history and the history of the world. Some view it as the vain pursuit of man to become god-like and create life, others, as the next logical step in computer technology. However, the conclusion is not nearly the most important part of it. The process of the pursuit of the creation of mechanical sentient life has also led to a much deeper understanding of how our own biological minds work, creating new methods to treat brain diseases, and other brain related disorders. Through this, life is longer sustained, but modern life itself would not exist without some AI programs today. Several AI programs control the stock market, and the military has countless uses for it, and we even rely on it at home. AI has advanced greatly since it began, bringing neurology with it, and modern America could not function today without it.
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 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.
The science behind humanlike robots is advancing. They are becoming more smart, mobile and autonom...
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.
Most of the day the human mind is taking in information, analyzing it, storing it accordingly, and recalling past knowledge to solve problems logically. This is similar to the life of any computer. Humans gain information through the senses. Computers gain similar information through a video camera, a microphone, a touch pad or screen, and it is even possible for computers to analyze scent and chemicals. Humans also gain information through books, other people, and even computers, all of which computers can access through software, interfacing, and modems. For the past year speech recognition software products have become mainstream(Lyons,176). All of the ways that humans gain information are mimicked by computers. Humans then proceed to analyze and store the information accordingly. This is a computer's main function in today's society. Humans then take all of this information and solve problems logically. This is where things get complex. There are expert systems that can solve complex problems that humans train their whole lives for. In 1997, IBM's Deep Blue defeated the world champion in a game of chess(Karlgaard, p43). Expert systems design buildings, configure airplanes, and diagnose breathing problems. NASA's Deep Space One probe left with software that lets the probe diagnose problems and fix itself(Lyons).
Humans can expand their knowledge to adapt the changing environment. To do that they must “learn”. Learning can be simply defined as the acquisition of knowledge or skills through study, experience, or being taught. Although learning is an easy task for most of the people, to acquire new knowledge or skills from data is too hard and complicated for machines. Moreover, the intelligence level of a machine is directly relevant to its learning capability. The study of machine learning tries to deal with this complicated task. In other words, machine learning is the branch of artificial intelligence that tries to find an answer to this question: how to make computer learn?
In the past few decades we have seen how computers are becoming more and more advance, challenging the abilities of the human brain. We have seen computers doing complex assignments like launching of a rocket or analysis from outer space. But the human brain is responsible for, thought, feelings, creativity, and other qualities that make us humans. So the brain has to be more complex and more complete than any computer. Besides if the brain created the computer, the computer cannot be better than the brain. There are many differences between the human brain and the computer, for example, the capacity to learn new things. Even the most advance computer can never learn like a human does. While we might be able to install new information onto a computer it can never learn new material by itself. Also computers are limited to what they “learn”, depending on the memory left or space in the hard disk not like the human brain which is constantly learning everyday. Computers can neither make judgments on what they are “learning” or disagree with the new material. They must accept into their memory what it’s being programmed onto them. Besides everything that is found in a computer is based on what the human brain has acquired though experience.