Definition: neural network

A major AI architecture. A neural network is employed for many pattern recognition applications; however, its most popular use is the creation of language models used by ChatGPT and other chatbots. Loosely based on the human nervous system, a neural network is technically an "artificial" neural network (ANN).

The neural network is used in image, language and speech recognition, text-to-speech conversion, robotics, diagnosing, forecasting and generative AI. Unlike regular applications that are programmed for precise results (if-then-else), neural network models are "trained" and fine-tuned using millions, billions, even trillions of examples of text and images. See AI programming, AI training, AI model and generative AI.

The Layers
A neural network comprises one input and one ouput layer and any number of hidden layers in the middle, all tied together mathematically.

A Neuron in a Neural Network

Nothing like "if-then-else" business logic, neural networks cannot be debugged or reverse engineered like regular computer programs. This is a single neuron. See AI weights and biases.

There Are Many Network Designs
The following diagrams from the Asimov Institute in the Netherlands reveal the variety of neural network architectures that have been created. For a neural network example that recognizes the letters of the alphabet, which is easier to grasp than language recognition, see convolutional neural network.

Neural Network Architectures

AI networks are one of the most researched areas of computing in the 21st century. The examples above from the Asimov Institute in the Netherlands reveal the variety of network architectures that have been created. (Images courtesy of Fjodor van Veen and Stefan Leijnen (2019). The Neural Network Zoo.)