Artificial Intelligence Programming 2025 – 400 Free Practice Questions to Pass the Exam

Hebb is best known for his work on learning mechanisms in neural networks, particularly encapsulated in his principle often summarized as "cells that fire together, wire together." This principle forms the foundation for many learning rules in artificial neural networks, focusing on how the connection strengths, or weights, between neurons should be modified based on their activity.

Specifically, Hebb's contribution relates to a method that describes how the synaptic strength between two neurons increases when they are activated simultaneously. This concept is fundamental to the understanding of unsupervised learning in neural networks, where the relationships between data points are learned without explicit supervision. This insight has significantly influenced the design of various learning algorithms in artificial intelligence, especially in the fields of machine learning and deep learning, making it a pivotal contribution to these areas.