Foundational Concepts
Neural Network
The underlying computational structure that most modern AI is built on — layers of interconnected mathematical nodes.
Definition
A neural network is a mathematical structure that processes information through a series of connected layers. Data enters at one end, is transformed through many intermediate layers, and produces an output at the other end. The network learns by adjusting the strength of connections between nodes — a process similar in concept, though not in mechanism, to how synaptic strength changes in biological brains. Almost all modern AI systems, from voice assistants to image generators, are built on this architecture.
Related Terms
Deep Learning
A subset of machine learning that uses layered networks loosely inspired by the human brain.
Machine Learning (ML)
A method where computers learn patterns from data rather than being explicitly programmed.
Parameters
The internal numerical values a model adjusts during training — more parameters generally means more capable.
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Disclaimer
This definition is provided for educational and informational purposes only. It represents a general explanation of a technical concept and does not constitute professional, technical, or investment advice. Artificial intelligence is a rapidly evolving field; terminology, techniques, and capabilities change frequently. Coaley Peak Ltd makes no warranty as to the accuracy, completeness, or currency of the information provided. Nothing on this page should be relied upon as the sole basis for commercial, technical, legal, or investment decisions without independent professional advice.
Document reference: ISO_webpage_knowledge-base_glossary_v1
Last modified: 29 March 2026
Knowledge Base·Foundational Concepts·Neural Network