The perceptron neural network was introduced by Yann LeCun in 1990 as a way to create an artificial intelligence system. The machine-learned how to recognize handwritten digitized images and recognized handwritten numbers. This was a major achievement in the history of computer science but some researchers were skeptical at first since it relied on the same system used by bees for making honey.
Machine learning concept
The machine learning concept has evolved over time into something that may be able to help us solve some of our toughest problems. The most promising applications involve translation, speech recognition, medical imaging, transportation, and other tasks. However, even these systems have a learning component. Think of the difficulty a new driver would have to navigate through traffic or following a route on a map. At some point, the driver would need to rely on some sort of machine learning technology to help him get from one point to another. As with all technologies, this is only becoming more advanced.
Artificial Intelligence with Real-Time data
Today, when we think about Artificial Intelligence we usually are referring to computer programs that can operate on all types of real-world data, not just voice recognition and basic e-mail automation. There is no doubt that we will eventually have machines that are capable of thinking and reasoning like humans.
For now, all that is available is what is known as machine learning. This means that the researchers who are creating these programs are trying to create machines that can learn without human intervention or by manipulating data. We are so used to trying to do that with computers, why wouldn’t we try to do it with neural networks?
The goal of artificial intelligence is to program a machine to think, reason, and decide as opposed to having a machine that does any of those things. The challenge is to find a way for this machine to reason correctly, understand the world around it, and make decisions in the face of uncertainty. With neural network technology, this is all possible.
Development of the Perceptron
The project, which began with the development of the perceptron was actually quite an expensive one. However, as time went by the project cost did decrease while the improvements in capabilities of the machine increased. At one point the price was equal to that of a real perception.
Although the vision and sound of a perceptron is a long way from being a practical reality for most people, the key is that it is still very much reality because this artificial intelligence is actually beginning to work.
One challenge that is being encountered with the development of this artificial intelligence is that it makes mistakes. When this happens it causes many questions. How will you deal with the situation if your neural network makes a mistake? How will you prove that the wrong decision was made? There are many different answers to these questions but there is no clear answer yet.
AI Machine
In order for such an AI machine to be useful, you have to use it in various situations. Although it might seem very complicated, once you start working on it you will realize that there is no need for the machine to be so complex. Just give it simple instructions and it will start making decisions on its own.
If you are in a manufacturing business then you can expect your machine to do an excellent job even under tough conditions. Since you are the supervisor, you will be able to program it according to what you expect it to do.
Since the application is just starting out it will not have perfect artificial intelligence. It might seem like such a big challenge but once it gets going you will realize that you were right. In fact, the best thing that can happen is that it starts learning and adapts to whatever environment it is placed in. It is all about letting it find its own solution.
