Neural processing originally referred to the way the brain works, but the term is more commonly used to describe a computer architecture that mimics this biological function. In computers, neural processing gives software the ability to adapt to changing situations and improve its function as more information becomes available. Neural processing is used in software to perform tasks such as recognizing a human face, predicting the weather, analyzing speech patterns, and learning new strategies in games.
The human brain is made up of approximately 100 billion neurons.
The human brain is made up of approximately 100 billion neurons. These neurons are nerve cells that, individually, have a simple function of processing and transmitting information. When nerve cells are transmitted and processed in groups, called neural networks, the results are complex, such as memory creation and storage, language processing, and reaction to sudden movements.
Artificial neural processing mimics this process on a simpler level. A small processing unit, called a neuron or node, performs a simple task of processing and transmitting data. As simple processing units combine basic information through connectors, information and processing become more complex. Unlike traditional computer processors, which need a human programmer to input new information, neural processors can learn on their own once they’re programmed.
For example, a neural processor can improve checkers. Like the human brain, the computer learns that certain moves by an opponent are made to create traps. Basic programming can allow the computer to fall into the trap for the first time. However, the more frequently a particular trap appears, the more the computer pays attention to that data and starts to react accordingly.
Neural programmers increasingly point out that the computer gives “weight” to certain results. Traditional processing would only give the computer the basic rules of the game and a limited number of strategies. Neural processing, by collecting data and paying more attention to the most important information, learns better strategies over time.
The power of neural processing lies in its flexibility. In the brain, the information is presented as an electrochemical impulse: a small chemical discharge or signal. In artificial neural processing, information is presented as a numerical value. This value determines whether the artificial neuron is active or inactive, and also determines where it sends its signal. If a certain checker moves to a certain square, for example, the neural network reads this information as numerical data. This data is compared to an ever-increasing amount of information, which in turn creates an action or result.
