Model Architecture
Layer
A processing stage inside a neural network — deeper models have more layers.
Definition
A neural network is organised into layers, where each layer transforms its input and passes the result to the next layer. Early layers in a language model tend to capture basic syntax and word-level patterns; deeper layers capture increasingly abstract semantics and reasoning patterns. Large models have dozens or even hundreds of layers, allowing them to represent extremely subtle and complex aspects of language.
Related Terms
Neural Network
The underlying computational structure that most modern AI is built on — layers of interconnected mathematical nodes.
Deep Learning
A subset of machine learning that uses layered networks loosely inspired by the human brain.
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