A large language model (LLM) is a neural network trained on extensive text corpora to understand and generate natural language. LLMs power modern document translation, summarisation, and terminology enforcement by analysing long passages, recognising patterns, and producing context-aware output.
What LLMs do well
- maintain context over long documents
- adapt tone and terminology through prompt design
- handle multilingual content with a single model
- summarise and structure information for translators
Considerations
- potential hallucinations without human review
- sensitivity to prompt wording and formatting
- costs that scale with context window length
- data protection requirements for sensitive content
How LLMs support translation
Professional translation teams pair LLM outputs with glossary enforcement, style guides, and mandatory MTPE to ensure accuracy. Document-level context windows help models keep tone consistent while reducing terminology drift across long files.
Trad AI approach
Trad AI runs translations through user-owned API keys, letting teams choose preferred LLM providers while keeping data under their control. Extended context windows, privacy-first processing, and GDPR alignment ensure LLM powered translations remain secure, auditable, and ready for professional review.
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