Foundational Concepts
Foundation Model
A large AI model trained on broad data that can be adapted for many specific tasks.
Definition
A foundation model is trained once on a huge and varied dataset — enough to give it broad general knowledge. That single model can then be adapted, or fine-tuned, for many specific applications: customer service, legal document review, medical coding, financial analysis. This is economically significant because training a foundation model from scratch costs tens of millions of pounds; adapting an existing one costs a fraction of that. GPT-4, Claude, and Gemini are all foundation models.
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.
Pre-trained Model
An AI model that has already been trained on large datasets and is ready to use or customise.
Fine-tuning
Further training a pre-trained model on specific data to specialise it for a task.
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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·Foundation Model