What Is an Artificial Neural Network?

An artificial neural network (ANN) is what is most commonly meant by the neural network. It is a complicated series of interconnected artificial neurons modeled after those in the human brain and used in artificial intelligence to process information, learn, and make predictions.

How Do Neural Networks Work?

A neuron is the human brain's most fundamental cell. A human brain has many billions of neurons, which interact and communicate with one another, forming neural networks.

These neurons take in many inputs, from what we see and hear to how we feel to everything in-between, and then send messages to other neurons, which react in turn. Working neural networks are what enable humans to think, and more importantly, learn.

As a method of taking in large amounts of data, processing it, and making predictions and decisions based on the data, the human brain's neural networks are by far the most powerful computing force known to man.

The Difference Between a Neural Network and an Artificial Neural Network

A neural network is technically a biological term, while an artificial neural network is the kind of neural network relied on by artificial intelligence.

Though the word itself is most commonly used to refer to the artificial neural network, you will often see people refer to artificial neural networks as simply neural networks.

Naturally, a neural network in the human brain is very different from an artificially constructed neural network. Still, the fundamental way they work to process information and make predictions remains the same.

While an ANN will not be a perfect recreation of a biological neural network, artificial neural networks are based on and modeled after the brain's neural networks, precisely because of the computing power of these networks.

What ANNs Are Used For

Humans use biological neural networks to process information, learn, and make predictions, e.g., think. Artificial neural networks work in much the same way but to a lesser degree, as artificial neural networks cannot yet match the complexity and power of those found in the human brain.

ANNs enable more complicated, lifelike, and powerful artificial intelligence through deep learning, which is the process of an artificial neural network independently learning and making its own decisions.

Human-like artificial intelligence is possible with an advanced neural network and enough data to train (or teach) the neural network. A.I., as it appears in movies, does not yet exist today, but if it ever does, deep learning through neural networks will power this intelligence.