Large language model
A large language model processes language using learned patterns. Fluent text proves neither factual accuracy nor access to current business data.
Work with a large language model
A large language model, or LLM, uses patterns learned from extensive training data to process language and generate text. Its input and output are processed in units called tokens. The word “large” is not evidence of suitability for your business.
In a fictional example, an LLM drafts a reply to a delivery enquiry. The stated date must be supported by a suitable current source. A convincing sentence does not give the model access to the actual order status.
The model is not the entire assistant either. Document access, permissions and available actions are determined by the surrounding application. A comparison must therefore consider those connections and behaviour when information is missing, alongside text quality.
Sources
Related terms
- Language model tokenTokens are processing units for language models. They do not reliably correspond to whole words and differ from design tokens.
- Context windowThe context window limits how many tokens a language model can consider in one processing step. It is not a permanent knowledge archive.
- AI hallucinationAn AI hallucination is plausible-looking content that is factually false or invented. Fluent language is not evidence of correctness.
- Model cardA model card documents an AI model’s purpose, foundations, evaluation conditions and known limitations for a particular version.
- AI readinessAI readiness concerns the foundations of an AI project: objectives, usable data, skills, responsibilities and an operating workflow.
- Context engineeringContext engineering prepares information for individual model calls: relevant instructions, messages, sources and current states.
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