Foundational Concepts
Emergent Behaviour
Capabilities that appear in large models without being explicitly trained, they emerge at scale.
Definition
One of the most surprising discoveries in modern AI is that as models get larger, they sometimes develop new abilities that weren't present in smaller versions of the same architecture and weren't deliberately programmed. These capabilities 'emerge' from scale. Examples include the ability to do arithmetic, translate between languages, and solve logical puzzles, none of which were explicitly trained. This unpredictability is part of what makes large-scale AI both powerful and difficult to fully characterise before deployment.
Related Terms
Large Language Model (LLM)
A type of AI trained on vast amounts of text that can read, write, summarise, and reason with language.
Parameters
The internal numerical values a model adjusts during training, more parameters generally means more capable.
Foundation Model
A large AI model trained on broad data that can be adapted for many specific tasks.
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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·Emergent Behaviour