Neural network
structure in biology and artificial intelligence
A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either biological cells or mathematical models. While individual neurons are simple, many of them together in a network can perform complex tasks. There are two main types of neural networks.
In neuroscience, a biological neural network is a physical structure found in brains and complex nervous systems – a population of nerve cells connected by synapses.
In machine learning, an artificial neural network is a mathematical model used to approximate nonlinear functions. Artificial neural networks are used to solve artificial intelligence problems.
In neuroscience, behavior and cognition arise from interactions between distributed brain regions. In computer science, artificial neural networks power many modern AI systems, but require large datasets and substantial computing power. Additionally, their internal representations are difficult to interpret.
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This entry incorporates text from “Neural network” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.