What Is an LLM (Large Language Model)?

An LLM (Large Language Model) is an artificial intelligence model trained on a huge amount of text, which can generate new text in response to an instruction. It is the engine behind ChatGPT and most of the AI tools you meet today, and it is also the foundation of every AI agent.

In short

An LLM is a large language model: software that learned patterns from a lot of text, and writes a sensible continuation of the instruction it receives.
It is not a search engine and not a database. It generates a plausible answer, so it can also be confidently wrong.
A language model, ChatGPT and an AI agent are not the same thing: the model is the engine, ChatGPT is a product built on it, and an agent is a model connected to tools.
It is excellent for drafting, summarizing and sorting. What it hasn't read, it doesn't know, unless you bring it in.

The illustration: an assistant who read an entire library

Imagine a new assistant who has read an entire library. They write superbly, understand almost any subject and can word an email in any style. But they have never seen your business's files, and they don't know what was agreed with the customer yesterday. What you haven't given them, they will guess.

That is an LLM. Language it knows. Your business it knows only as far as you tell it.

How an LLM works, in four steps

From instruction to answer

InstructionYou write what's needed
TokensThe text is cut into small pieces
CalculationThe model picks the likely continuation
AnswerYou check and approve

A few concepts worth knowing:

Token. According to OpenAI, tokens are common sequences of characters, and in English a token is about four characters or three quarters of a word. Models work in tokens, not words. More in the explainer on tokens.
Context window. This is the limit on how much text the model processes at once. According to OpenAI, the instruction and the answer together can't exceed the model's maximum length.
Training. At this stage the model learns from text to predict the continuation. This is where its ability to write comes from, and also where its mistakes come from. Details in the explainer on hallucinations.
Randomness. OpenAI notes that content a model generates is non-deterministic, meaning the same instruction can produce different wording.

Model, ChatGPT and agent: three layers

Language model (LLM)

The engine

Takes text and returns text
Knows only what's in the instruction and in training
Has no hands: doesn't enter a website and doesn't send

AI agent

The engine, connected to the business

The same kind of model, with a connection to tools
Gets permissions and context about the business
Carries out tasks, and you approve

ChatGPT is the product built on such models: a convenient conversation, with no need to know what happens underneath. And the move to a model connected to tools is what explains what an AI agent is.

Why does an LLM matter for a business?

Reply drafts

Wording an answer to a customer in your tone
You read and approve before sending

Summaries

A long document or email thread in one paragraph
Better to check against the source when it matters

Inquiry sorting

Spotting what's urgent, what's sales and what's service
A clear rule for what goes to a person

Content and translation

Product descriptions, posts and versions in other languages
Publishing is always with your approval

Our rule: use an LLM where a good draft saves time, and where a person checks it. Where a mistake is costly, such as a price, a legal promise or a financial figure, don't trust a guess.

Common myths about LLMs

Myth"An LLM is a smart search engine"

In practiceA search engine finds existing sources. A language model generates new text from patterns it learned. Some products add search to it, but that is an add-on, not its essence.

Myth"It knows my business"

In practiceIt knows only what is in your instruction and what the system adds to it. Information about the business has to reach it, for example through RAG.

Myth"If it writes with confidence, it's true"

In practiceConfident wording is not proof. OpenAI defines a hallucination as a plausible but false statement, delivered with confidence.

Myth"All models are the same"

In practiceModels differ in size, speed, cost and quality. You choose by the task and test on examples from the business.

Platin Digital is an OpenAI Select Partner, and we set up agents for businesses based on models like these, with your approval on every sensitive action.

Frequently asked questions

What is an LLM?

An LLM, or large language model, is an artificial intelligence model trained on a huge amount of text that has learned patterns in language. It receives an instruction in text and generates text in response: an answer, a summary, a draft or code. ChatGPT is a product built on such models.

What is the difference between an LLM and ChatGPT?

An LLM is the model itself, the engine. ChatGPT is a complete product built on models, with a conversation interface and additional features. The same kind of model can also be used through programming interfaces, inside other tools and inside agents.

Does an LLM know current things?

A model learns up to a certain point in time, so what happened after it isn't necessarily known to it. For it to answer about current or internal information, you bring it the information in the instruction, or connect it to a source, as explained in RAG.

Can you rely on an LLM in a business?

You can rely on it like an assistant who prepares drafts, not like someone who decides. It can make mistakes, as the explainer on hallucinations describes. So you check important outputs, and actions like publishing and sending stay with your approval.