Artificial Neural Networks, which are also known as ANNs have received a lot of attention recently. The increasing awareness of Artificial Intelligence has contributed a lot towards their popularity.
The Artificial Neural Networks can simply be defined as biologically inspired networks. In other words, these networks work similar to the human brain. As is probably well known, the human brain consists of billions of special cells named as neurons. To be precise, it has been estimated that a typical human brain consists of about 150 billion neurons. These neurons are inter-connected with each other to form a network. As a result, the human brain can be considered as a collection of neural networks.
The Concept of Neural Computing
The application of Artificial Neural Networks is known as Neural Computing. Neural computing uses a limited amount of concepts that are borrowed from biological neural systems. The main objective of Artificial Neural Networks is to simulate massively parallel processes that are associated with interconnected processing elements in network architecture. An artificial neuron would be the building block of an Artificial Neural Network.
A neuron would receive inputs from the other neurons that are connected to it. And conversely, the output of a neuron will be passed to several other connected neurons. The same mechanism takes place within the human brain as well. Likewise, the artificial signals processed by the neurons can be changed. How Artificial Neural Networks process information entirely depends on its structure. The algorithm that is being used to process information can also create an impact on it.
Application and Benefits of Artificial Neural Networks
Artificial Neural Networks can be applied to a variety of scenarios. The benefits that are associated with these applications have contributed a lot towards their proliferation over the past decade. The most popular areas where ANNs are being applied include learning, pattern recognition and interpretation of noise and incomplete inputs.
Humans follow a different approach when solving problems when compared to computers. The objective of Artificial Neural Networks is to make computers think and solve issues like human beings. This can help computers to solve complex problems, which cannot be solved with a rule based approach. In other words, Artificial Neural Networks are being used to solve complex problems that cannot be simulated using analytical or logical techniques. They have the potential to solve issues, which cannot be solved even with expert systems. Pattern recognition is a perfect example to prove the aforementioned fact.
Artificial Neural Networks are in a position to analyze large amounts of data in an effective manner. After the analysis, it can establish characteristics and patterns, where rules or logic are not known. Loan applications are a perfect example for such a situation. After going through a large number of historical cases, the questionnaire of the applicant is either accepted or rejected. Only Artificial Neural Networks have the ability to automate this process of approving loans.
Artificial Neural Networks also have the ability to create profiles or patterns of applications that need to be denied or approved. Then a new application is matched against a pattern by the computer. The computer would gain the intelligence to classify whether it is a “yes” or “no”. Otherwise, it would go for the decision of humans. That’s the main reason why neural networks are being used for a variety of financial applications such as predicting exchange rates, predicting bankruptcy and determining when to purchase and sell stock.
Artificial Neural Networks and Smart Computers
Computer systems have gone through significant development throughout the past few years. Artificial Neural Networks have contributed a lot towards this evolution. As a result, people in the 21st century prefer to use computers to accomplish most of their day to day needs.
A traditional computer has the potential to perform millions of operations within a second. However, this type of computer is not in a position to think like a human and make decisions by themselves. In other words, the traditional computers do not have the ability to perform certain tasks on their own. You will need to program those computers to make them perform certain tasks, but you will not be able to make them solve problems in the way humans do. That’s where Artificial Neural Networks come into play.
Artificial Intelligence can simply be defined as a set of techniques, which are entirely based on the behavioral patterns of the human brain. It can learn on its own and make decisions like humans do. Most of the living beings that exist on this planet are biological systems that learn on their own. They are capable of making useful decisions as well. Generally these decisions are based on the instinct of survival.
Human beings need to learn before they can make decisions. The same principle applies for machines as well. Machines differ from biological systems though in that they will have to learn new things through mathematical algorithms. However, Artificial Neural Networks have given machines the opportunity to learn new things like human beings. This has given life to a brand new aspect in computing as well.
The use of Artificial Intelligence and Artificial Neural Networks are being implemented mostly in the software industry at the moment. This has the potential to emulate the parallel nature of an Artificial Neural Network into a linear system. As mentioned earlier, Artificial Neural Networks are being used on a variety of applications such as image reconstruction, character recognition and voice recognition.
Neural networks can also be found in a variety of applications such as robotics. People however are extremely concerned about automation and the danger of robots taking over their lives as a result of advances in the field of Artificial Intelligence and Machine Learning. These fears derive from the fact that whilst Artificial Intelligence is helping the humans to achieve a better standard of living, it is also important to keep in mind that transferring the biological capabilities of humans to computers can make us more dependent on them.
In this respect, special attention has been attributed towards Artificial Neural Networks. This is because Artificial Neural Networks have the ability to make computers think like human beings and solve complex problems which in effect means that it can humanize computers. Such a prospect creates all sorts of anxiety and extreme scenarios. Nevertheless, for the time being, research is focused on different medical applications of ANNs with beneficial results for humans. What remains to be seen is how future research and practice in this exciting area will continue to grow.
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