LLM (Large Language Model)
An LLM is a large language model trained on enormous text volumes that can generate, summarise, and analyse text in a human-like way.
Also known as: language model, large language model
An LLM (Large Language Model) is an artificial intelligence model trained on billions of words of text, capable of generating, summarising, classifying, and analysing text in a human-like way. Examples include OpenAI's GPT series, Anthropic's Claude, and Google's Gemini. For businesses, LLMs are the engine behind chatbots, document analysis, email sorting, and content generation. They have limitations: they occasionally "hallucinate" (generate plausible but incorrect answers), and they cannot know things that were not in the training data — which is why they are often combined with RAG.
In Norwegian context
Modern LLMs understand Norwegian Bokmål well and Nynorsk reasonably well. For particularly sensitive data, smaller locally-runnable models can run on Norwegian infrastructure.
Read more in the in-depth article on this topic.
Related terms
- RAG (Retrieval-Augmented Generation) — RAG is a technique where a language model answers based on the business's own documents — instead of only its general training.
- AI agent — An AI agent is software that sets goals, plans steps, and acts autonomously to achieve them — without continuous human oversight.
- Fine-tuning — Fine-tuning is the process of further training an existing AI model on specific data to improve performance for a narrow use case.