Neural processing mimics the way the brain works and is used in software to perform tasks such as recognizing faces, predicting weather, and learning new strategies. It involves small processing units that combine basic information through connectors to become more complex. Neural processors can learn on their own once programmed, improving over time by paying closer attention to more important information. The power of neural processing lies in its flexibility, with information presented as numerical values that determine whether an artificial neuron becomes active or inactive.
Neural processing originally referred to the way the brain works, but the term is more typically used to describe a computer architecture that mimics that 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. These neurons are nerve cells that individually perform a simple function of processing and transmitting information. When nerve cells transmit and process in groups, called a neural network, the results are complex, such as creating and storing memory, processing language, and reacting 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 becomes more complex. Unlike traditional computer processors, which need a human programmer to input new information, neural processors can learn on their own once programmed.
For example, a neural processor can improve at checkers. Just like a human brain, the computer learns that certain moves by an opponent are made to create traps. Basic programming could allow the computer to fall into the trap for the first time. However, the more often a certain trap appears, the more attention the computer pays to that data and begins to react accordingly.
Neural programmers call the increasing attention the computer pays to certain results “weight.” Traditional computing would provide the computer with only the basic rules of the game and a limited number of strategies. Neural processing, by gathering data and paying closer attention to more important information, learns better strategies over time.
The power of neural processing lies in its flexibility. In the brain, information is presented as an electrochemical pulse, a small jolt, or a chemical signal. In artificial neural processing, information is presented as a numerical value. That value determines whether the artificial neuron becomes active or inactive, and also determines where it sends its signal. If a certain checker is moved to a certain square, for example, the neural network reads that information as numerical data. This data is confronted with an increasing amount of information, which in turn creates an action or output.
Protect your devices with Threat Protection by NordVPN
