Created with miraculous abilities, like intelligence, thought, and speaking, it is the human, apart from all other living things, that has invented much and enriched human civilization. The human brain, as a histological organ, formed by 60 billion cells and with its capacity of processing billions of pieces of information, is itself a miracle of creation. Most neurologists who are not materialist agree that the mysterious organ, consisting of 90 percent water and which functions not only in the senses of smell, sight, hearing and feeling, but also in some other more abstract human feelings, does not seem to match its physical reality. In this article, we will compare the human nerve mechanisms with the artificial nervous systems that have been created and that are being developed as we speak.
Programs and documents on the computer are held in two areas: software and hardware. For scientists, one of many goals is to make the processors or chips, which are like the human brain that consists of nerves, much smaller, but still powerful enough to process many more calculations. There are many differences between the current chips and earlier ones. Chips which will be produced in the future will be smaller and probably process more calculations more quickly.
Programs, which can be seen as being the mechanical counterpart of the human mind, bring the above-mentioned improvements into daily life. New programs boost the capability of the computer in parallel with the capability of their chips. Without these programs, computers would be no more than ordinary electronic machines.
Developed technologies in fields like industry, communication, or the military bring us face to face with new developments and have made the computer an undeniable part of our lives. Mobile phones equipped with new features, medical machines which can easily make a large number of analyses and provide ease in diagnosis and treatment, robots that can operate with minimum error and have a low cost when used in production, and weapons that automatically focus on the target are all part of this progress.
With time, software and hi-tech sensors have enabled computers to communicate with people; there are now systems that are controlled by the voice, which are able to recognize a person from their iris or fingerprints, control systems which are carried out by touching a screen, etc. Such systems are operated with the help of special sensors or by some signals that carry messages from the person or the environment to the computer. The most important feature of these sensors is that the signals produced at the output are very weak and there are few differences between them. An ATM can recognize a particular person's iris, thanks to the ability of its computer to compare the signals from the ATM's iris scanner with previously recorded data. In this process, the computer uses the small differences that one person's iris has to another's. In this or similar systems, complicated programs are used, called "expert systems" or "artificial intelligence". These programs imitate human senses, but they aim to operate with an even keener sensitivity and clearer criteria.
A question that is a subject of fiction comes to mind; "Will computers vie with or even fight with human beings?" In the mid-term, the rapid development of technology will create computers which can communicate with humans, which can understand them, and put forward ideas. A negative outcome of such a situation depends, once again, on man. Such a horrific situation could be the result of technology that can cause environmental disasters; this technology is almost identical to the one that we have described above. If we are able to establish an understanding of "civilization" which does not ignore human values for the sake of technological development, then such fears will be groundless.
As we all know, people have imitated nature in many of their inventions. In a way, artificial nervous systems imitate how a nerve cell learns and how it works. Fuzzy systems however imitate how the judgment of a human being works, rather than the nerve cells of the brain. In these systems people try to form a decision making criterion by assuming that there are endless grey tones between white and black or by assuming that there are infinite values between zero and one.
The purpose of the research on artificial nervous systems is to understand how the brain operates, then to make a system that imitates it and carries out the same operations. Artificial nervous systems are made of simple nerve cells which are bound in parallel, called process elements; these allow for real objects to be seen as if they were biological systems.
Here, the program that resembles the nerve cell operates in the same way as a nerve cell. The main part of a nerve cell is formed from the body, called a "soma", an "axon" that is bound to the body and many "dendrites". There are many "roots", or synapses, on the dendrite of a cell which make contact with the dendrites of other cells. A nerve cell either transmits the electrical stimulus that comes through the axon to the other nerve cells through the synapse, or it does not transmit it, depending on whether or not the signal is over or below the threshold value. So a nerve works by itself, but its activity becomes meaningful when working as a part of a nervous system. It would be useful if we consider how the learning process occurs here. It is thought that the required data are stored in the memory center and this fact is taken as a model for some artificial nervous system software that has been successfully developed to date.
A nerve cell and the process of transporting signals from one cell to another can be written as software. It is clear that a natural nerve cell is more complex and that it is bound to more cells than an artificial one can be. The number of communication ports (synapses) of a natural nerve can vary from between 1,000 to 10,000.
An artificial cell produces output if the input value is over the cell's threshold value; if this is not the case then there is no production. If there is output - as in natural cells - then this output is transported to the next cell group. Each cell produces its output as an input for the next cell.
A cell is separated into three groups: input, the hidden layer and output. Each group is considered to be made up of one layer, while the hidden layer can consist of more than one, according to the complexity of the job. As can be seen, the placement of the layers is similar in the process of the human body. We can compare the cells on the input layer with human senses. In this way we can teach a robot to avoid heat and cold, we can make them see and act according to this information. (Do not forget that a robot is in fact a computer.) It is natural that some sensors must be bound to the cells on the input layer. For instance, a sensor which is sensitive to heat can make the robot react to heat when the temperature is over the limit value or when the temperature is dramatically low it can move closer to a heat source. Or if pictures received from a video-camera are similar to an object that has been fed into the robot such data input can cause the robot to move to that object.
Artificial nervous systems are not only used in robot applications. They are commonly used in making clinical diagnoses, determining market-customer profiles, recognizing voices or pictures, classifications such as determining micro-structures, like germs and cell materials, economic profiles, energy sources, the futures of market shares, some predictive sciences, such as weather forecast, zipping data for computers, process control in industry, checking resources and some other matters in technological areas. As can be seen, there are many application areas for artificial nervous systems, all of which differ from one another.
The features of artificial nervous systems can be simplified as follows: firstly, they can learn how to solve problems. In order to do this they use sample data and learning styles and while doing this they do not require any special help. Secondly, they can recognize important features and relations to help them distinguish different data forms.
When an artificial nervous system is operated, the first thing to be carried out is the training process. In order to do this, the program needs to have two alternating operations. It may obtain information concerning some results to be achieved, using results that come from the user, or the program is itself asked to produce some results. These two types of learning are not very different from how a human learns. One shows a young child an animal, and repeats the name. Now the child has learned the name of the animal and correlates it with the picture of the same. If no one teaches a child what a bird is, the child will all the same classify all animals that have wings and beaks and that have a certain physical shape, maybe even creating a name for the animal by him/herself. The difference between the computer and the human in this process is that a human has the ability to judge, while computers classify the animals according to their shapes and groups them thus. Naming and giving a naming feature to the computer is again a decision that a human will make. When the training process is finished, the data can be entered into the computer and the desired results can be attained.
Artificial nervous systems are changing and developing day by day. With each new development they become closer to the human nervous system; they are able to recognize different characteristics of different people and they are learning to make sorting decisions, even limited judgments. Whether or not these machines may one day enact a nightmare scenario, taking over from us is not a great threat, as whatever they are capable of doing is up to us to decide, as their "masters". We should not fear these systems, but try to develop more of them; such systems help us in every day tasks, from drawing money out of the bank to our annual check-up at the doctor's.