LLM (Large Language Model)
Language model
An LLM (Large Language Model) is a type of artificial intelligence trained on huge amounts of text that can understand and generate language. It works by predicting the most likely continuation of a piece of text, word by word, based on what came before.
How an LLM works
During training, a large language model learns from a vast amount of text and captures the statistical relationships between words and concepts. When you give it a question or instruction, the model does not look up an answer in a database; it gradually predicts the most likely next words so that the result makes sense.
That is exactly why how you phrase your request matters. The text you give the model is called a prompt, and its quality directly affects the quality of the answer. The model also only remembers a limited span of text at a time, so in long conversations it can forget earlier details.
What an LLM is good for
LLMs excel at language tasks. In a business you can use them for work that would otherwise take a lot of time writing or reading text. They work best as an assistant whose output is still reviewed by a person.
- Writing and editing text for your website, emails, and marketing.
- Summarizing long documents, transcripts, and reports into a few sentences.
- Translating and adjusting the tone of text for different audiences.
- Answering customer questions in a chatbot or on support.
Where the limits of an LLM are
An LLM does not guarantee truth. When it lacks information, it can make up an answer and present it convincingly. This is known as a hallucination. The model also only knows what it was trained on, so it has no knowledge of the latest events or your internal data on its own. These gaps are addressed, for example, with RAG, which supplies the model with relevant source material.
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Are LLM answers always true?
No. The model generates text based on probability, not from a verified database of facts, so it can sound confident even when it is wrong. For important information, you should always verify the output or supply the model with reliable source material.
Can an LLM work with my company data?
Not on its own; it only knows what it was trained on. You can give it access to your documents and data through an approach called RAG, which adds relevant information from your sources into the answer.
Is it safe to put sensitive data into an LLM?
It depends on the specific tool and its terms. With public services you should be careful with personal and business data. For sensitive data, choose solutions with clear rules on how it is processed and stored.