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...
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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.
Do you ever wonder how our brains can remember so many things? Our minds are a lot like computers “we can draw on our past experiences in order to use this information in the present” (Sternberg, 1999). “Memory is a group of related mental processes that are involved inacquiring, storing, and retrieving information” (Psychology, page 228). “We have 3 main stages of memory our sensory memory, short- term memory, and long term memory.” I will be stating some interesting facts about each one. Beginning with our sensory memory, one of the facts I found from the book was that “The very brief time information is held in our sensory memory you “select,” or pay attention to, just a few aspects of all the environmental information that’sbeing registered
Artificial intelligence has come a long way since the first robot. In 1950, Alan Turing of Britain publishes, Computer Machinery and Intelligence. This book was proposed to be the birth of artificial intelligence as we know it. The first robot that presents the usage of artificial intelligence was built in 1969. The purpose of this robot was to try out navigation using basic tools such as cameras and bump sensors (Marshall 371). Since then, we have made a million robots way better than this one and we’re going to continue doing so. While the world advances, so is technology. It’s slowly progressing and become better and more reliable. Artificial intelligence is a certain type of technology that is resourceful to our nation. We are using it in the medical field, it’s been helpful to military forces, and it’s helping our world become a better place.
When people think of Neural Networks the first thing that comes to mind is our brain, while the second is computers. That comparison is due to the fact that the way that computers work is the same as a Neural Network, “the network is built up by connections between these processing units” (Sandhu, Robin. “5 examples of biomimetic technology.” LifeWire. LifeWire. 19 Oct. 2016. Web). Having to search for animals that have unique capabilities may seem boring to most people, but they didn’t even have to get off the couch to find out about Neural Networks because that was inside them all along, sometimes it’s the more obvious skills that slip past
Artificial Neural Network (ANN): For a machine to think like a human mind, one must design a human mind for it. ANN represent the working of the brain in social beings. A system that consists of ‘neurons’ connected to each other that can share messages and data is known as ANN. The connections are weighted that are tuned according to experience, hence adding the ability to learn and remember. ANN’s are used when number of inputs is considerably large and unknown most of the times.
In Learning and Memory, Sprenger uses the hand as an example for the structure of the neuron saying, “The cell body can be compared to the palm of your hand. Information enters the cell body through appendages called dendrites, represented by your fingers. Like the fingers, dendrites are constantly moving and seeking out new information. If the neuron needs to send information to another neuron, the message is sent through the axon, represented by the wrist. When a neuron sends information down its axon to communicate with another neuron, it never actually touches the other neuron”. As the neurons are making connections with other neurons, dendrites are being created, strengthening the network (Sprenger 2). Even though the brain has approximately 100 billion neurons, each neuron can have up to 10,000 connections with other neurons. This means that the brain has over one quadrillion connections. As previously said, learning is “two neurons communicating with each other”. If each connection is a communication, and there are over one quadrillion connections, then the brain is a power house for communication (Sprenger
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.
This paper involves how the brain and neurons works. The target is to display the brain and neurons behavior by sending signals. The nervous system that sends it like a text message. This becomes clear on how we exam in the brain. The techniques show how the brain create in order for the nerves about 100 billion cells. Neurons in the brain may be the only fractions of an inch in length. How powerful the brain could be while controlling everything around in. When it’s sending it signals to different places, and the neurons have three types: afferent neurons, efferent neurons, and the interneurons. In humans we see the old part of emotions which we create memories plus our brain controls heart beating, and breathing. The cortex helps us do outside of the brain touch, feel, smell, and see. It’s also our human thinking cap which we plan our day or when we have to do something that particular day. Our neurons are like pin head. It’s important that we know how our brain and neurons play a big part in our body. There the one’s that control our motions, the way we see things. Each neuron has a job to communicate with other neurons by the brain working network among each cell. Neurons are almost like a forest where they sending chemical signals. Neurons link up but they don’t actually touch each other. The synapses separates there branches. They released 50 different neurons.
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?
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.
Stergiou, C., & Siganos, D. (2011, August 6). Neural Networks. Retrieved August 6, 2011, from
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...