Glossary

Foundation model

What is Foundation model?

A foundation model is a large AI model pre-trained on very extensive, wide-ranging data that can then be used for many different tasks. The term was coined at Stanford University in 2021. Well-known examples include large language models such as Claude or GPT, as well as image models. Businesses usually build their applications on such models rather than training their own from scratch; the EU AI Act refers to general-purpose AI models.

How KI.ordo helps

KI.ordo uses the Claude family of foundation models from Anthropic (Haiku, Sonnet, Opus) and adapts them through instructions and your own knowledge rather than retraining them.

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Topics

Base model
Language models
Generative AI

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Related terms

Large language model (LLM)

A large language model (LLM) is a neural network trained on very large amounts of text, enabling it to understand and generate language. It works by calculating the most likely next token, step by step. LLMs write, summarise, translate, answer questions and generate code; well-known examples include Claude, GPT, Gemini and Llama. Without access to current sources, they only know what was in their training data.

Language models
Generative AI
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Transfer Learning

In transfer learning, a model that has already learnt a large general task serves as the starting point for a new, specialised one. Instead of starting from scratch, it is adapted, for instance through fine-tuning, using comparatively little data of your own. This saves computing time and data, for example when a general image model is meant to learn to spot production defects in photos.

Machine learning
Training
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Claude

Claude is a family of large language models from the US AI company Anthropic. The models understand and write text in many languages, analyse documents, write code and can use tools, for example for research or automation. Best known are the model families Haiku, Sonnet and Opus, which differ in speed, cost and capability. Anthropic places particular emphasis on safety and reliable model behaviour.

Anthropic
language model
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Generative AI

Generative AI refers to AI systems that create new content – text, images, audio, video or program code – rather than merely sorting or assessing existing data. They are based on models that learn patterns from large amounts of data and use them to produce plausible new outputs. In business it is used, for example, to draft emails, summaries, product descriptions or image ideas. Results can contain errors and should be checked before use.

Core concept
Content creation
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