Foundational Concepts
Deep Learning
A subset of machine learning that uses layered networks loosely inspired by the human brain.
Definition
Deep learning gets its name from the many layers of processing that sit between a system's input and its output. Each layer learns to detect increasingly abstract patterns: in image recognition, early layers spot edges, later layers spot shapes, and the final layers identify objects. This approach powers the majority of modern AI breakthroughs, including the language models behind chatbots and the image generators used in design workflows. It requires large amounts of data and significant computing power to train.
Related Terms
Machine Learning (ML)
A method where computers learn patterns from data rather than being explicitly programmed.
Neural Network
The underlying computational structure that most modern AI is built on, layers of interconnected mathematical nodes.
Transformer
The core architecture that powers most modern LLMs, introduced by Google in 2017.
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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·Deep Learning