See how artificial neural networks change the world

Since the invention of the computer, the topic people talk about is often not what the computer can do, but what the computer can't do. Whether it is to defeat the master of chess or to win in Jeopardy, these predictions are actually wrong. However, these denials can provide a better foundation for computer science. In fact, if you know how a computer works, you can hardly achieve goals such as recognizing other people's emotions through facial expressions, reading various cursive handbooks, identifying spoken words, and automatically entering busy streets.

Currently computers can do a lot of things and even do more things. Are those negators really skeptical about the capabilities of today's digital computers? In order to solve these major problems, scientists have come up with a new type of computer based on the human brain, the Artificial Neural Network (ANN). Artificial neural networks usually only run on analog conventional digital computers, and what happens inside the simulation is completely different from traditional calculations.

Is the artificial neural network just a preliminary exercise in computer science, biological applications, pure mathematics, and experimental philosophy? Admittedly, artificial neural networks will also cover a wider field.

What is an artificial neural network?

Many people know that computing neurons in the brain are not ordered in a linear sequence like a computer processor's semiconductor, connected to a patch panel, and controlled by a unified clock cycle. Instead, each neuron in the brain is an independent individual that connects most or nearby neurons in a highly complex and unpredictable way.

Each neuron in the human brain is tightly connected to other neurons.

This means that digital computers need a grand program that directly informs each semiconductor what needs to be done to achieve the overall goal of orderly results. The brain combines billions of tiny, simple units, each with its own programming, so no external commands are needed to make decisions. Each neuron interacts with nearby neurons according to simple pre-defined rules.

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