Neural software or neural network software is a representation of a few fundamental concepts of artificial intelligence that have been applied to applications, developer environments, and more over the past few decades. The original concept of neural programming was to mimic the processes of the human brain. Before the rise of neural network programming in its modern form, many referred to this idea as artificial intelligence.
In today’s programming world, neural software often includes elements of human or biological thought processes applied to various kinds of software that help to create results from an array of data. One kind of neural software includes simulators. A neural simulator application uses basic data to provide predictive or data modeling results that are enhanced by the neural processes of that software application.
Another kind of neural software is what many developers call a component based design. In component based neural software, there is generally a lot of potential for advanced development beyond a single neural application. The rise of component based neural software design has extended to developer tools like Java and .Net that tech workers employ for both web-based and standalone application design in many industries.
Many types of custom and general neural network software can use a variety of programming languages. Since markup languages have become popular, a language called Predictive Model Markup Language, or PMML, is something that many programmers now use to define common elements in neural software. The PMML language is based on the XML markup language that has provided for many different kinds of software development.
Within the general field of neural programming, there are those developers who continue to focus specifically on what they call an artificial neural network that brings the qualities of biological thought to a machine application or program. These advocates of combining the strengths of computational power and human intelligence argue that an artificial neural network can do things that a "linear program" can’t accomplish on its own. For these kinds of applications, training is extremely important, and different types of training processes for neural software make up a great deal of what tech experts are currently doing in this field. Expert programmers often use a combination of equations and drawn diagrams to demonstrate their work to colleagues, or even to the general public, thus making the results of neural programming more transparent.