What is a neural network in plain words

A neural network is a program built from a large number of simple computing nodes ("neurons") connected in layers. It learns from examples and is the basis of most modern AI.

A neural network recognises an image layer by layer

In plain words

Picture a line of people in a school corridor passing along a note, each adding a little to it. The first sees only spots of light, the second turns them into lines, the third into outlines, and the fourth says: "It's a cat!" Each one alone can do almost nothing, but together they recognise complex things. That's a neural network: simple "neurons" arranged in layers.

How it works

Data is fed in as numbers: photo pixels, sound, words.
Each neuron takes a few numbers, multiplies them by its weights and passes the result on.
Layers process the data step by step: from simple features to complex ones.
The last layer gives the answer - for example, "this photo shows a cat with 97% probability".
During training, the weights are adjusted so the answers become more accurate.

Neurons as a line of students passing and adding to a note

Where you'll see it

Neural networks work in smartphone cameras, voice assistants, translators, chatbots, image generators and watches that analyse heart rate and sleep. Chips even have a dedicated block for them - the neural processor (NPU).

Does it matter when buying

The term itself rarely appears in spec sheets, but it explains why devices need an NPU and lots of memory. The bigger the network, the more computing it needs. That's why some AI features only run on flagships, while budget phones use the internet for them.

Myths

Myth: A neural network is a copy of the human brain. Reality: It was named after the brain, but it's really just maths: multiplying and adding numbers.
Myth: Developers know exactly how a neural network makes decisions. Reality: Not always. Large networks are hard to "take apart", which is why they're called a "black box".

FAQ

How many neurons are in a neural network?

From a few hundred in simple ones to billions of parameters in large language models.

What are "weights"?

Numbers that show how important each connection between neurons is. They're what changes during training.

Can a neural network run on a phone?

Yes, small networks run on every modern smartphone, and bigger ones need a strong NPU.