Fundamentals of Artificial Intelligence: The Difference Between the Brain and a Database

Behind the scenes, artificial intelligence systems exhibit features similar to the human brain rather than functioning like a computer opening a file; this situation is explained by the roots of cognitive science in artificial neural networks.

The Working Principle of Artificial Intelligence

Although it is assumed that ChatGPT and other language models consist of a database or logical steps in the background, this approach does not reflect reality. The fundamental developments behind artificial intelligence were shaped by researchers aiming to understand the human mind.

Historical Development and Turning Points

The term artificial intelligence was coined at a workshop in 1956, and the idea was that machines could be made intelligent through rules. In 1958, psychologist Frank Rosenblatt developed an artificial neural network called the Perceptron, inspired by the architecture of the human brain and learning from examples.

The Transition Process to Deep Learning

In the 1980s, cognitive and computer scientists discovered how to train multi-layer artificial neural networks, paving the way for deep learning. In subsequent years, hardware improvements and transformer architectures enabled the growth of these models.

Similarities with Human Memory

Because modern artificial intelligence is developed from examples rather than deterministic rules, it possesses characteristics similar to human memory. This causes the systems to have a constructive and hallucination-prone structure, just like humans.