How Neural Networks Differ from Artificial Intelligence

Artificial intelligence, or AI, refers to technologies that allow computers to perform actions that require human thinking. For example, recognizing images, making decisions, or understanding languages.

Neural networks are machine learning models created in the image of the human brain. They consist of artificial neurons connected to one another. Neural networks are trained on data and can identify complex relationships.

The Main Difference

AI is a broad field in science and technology. Neural networks are a tool within this field. In other words, neural networks are one way to implement artificial intelligence.

Interesting Facts

The first models appeared in the 1940s, but the real breakthrough happened thanks to the development of computing technology in the 21st century.

Modern neural networks have many layers and are capable of learning complex tasks, such as driving a car.

Neural networks are used in medicine to diagnose diseases, in finance to forecast markets, and in art to create music and paintings.

A Simple Explanation

Imagine AI as a large set of tools for creating intelligent systems. Neural networks are one of those tools: powerful and widely used, but not the only one.

Neural networks and artificial intelligence are connected. AI is the goal of creating intelligent machines; neural networks are one way to achieve that goal.