Large language model

What it means

A large language model is a kind of artificial intelligence trained on vast amounts of text. It has learned how words and sentences follow one another and can therefore answer questions, write and translate texts, summarise a document or write code.

The model does not understand the world as a person does. It predicts the most likely continuation of a text, so it can sound confident even when it is inventing facts. On specialist questions such as tax or law its answer is a good starting point, not finished advice without checking.

Large language models power today’s chatbots, assistants in office software and search engines that answer in full sentences. Their use is regulated by the AI Act, which places duties mainly on providers and, for some uses, on the companies deploying them.

How it works in practice

In the office, language models help with drafting emails, summarising long documents, translating and preparing material. On accounting and tax matters we recommend always having the output checked by an expert, because the model may not know the current Slovak rules.

Before entering data into a public service, consider what happens to it. Client personal data, payroll or trade secrets should not go into a tool that may use them for further training. Business versions usually exclude this contractually, and for GDPR a processing agreement with the provider is needed.

Language models increasingly read websites and answer people instead of a search engine. It therefore makes sense to prepare content so a model understands it correctly, for example with an llms.txt file and clearly structured pages.

What to watch out for

The most common mistake is using output unchecked. An invented rate, a non-existent section of law or a wrong deadline in an email to a client damages trust and money. The company is responsible, not the tool.

The second risk is having no internal policy. Staff use these tools anyway, and the company does not know what data are leaving it. Simple rules on what may and may not be entered into the tools prevent most problems.