What the heck are LLMs? (in simple terms)

What is a Large Language Model (LLM)?

A large language model is a very advanced AI program that can read and write text. It’s like having a robot friend who has read every book, article, and website it can find. Because it has seen so much text, it can answer questions, write stories, and carry on conversations. Essentially, an LLM has learned to use human language and can generate its own responses.

Learning from Lots of Text (Training)

LLMs learn by studying a massive amount of text from the internet – including books, news articles, Wikipedia pages, social media posts, and more. During training, the model sees sentences and tries to guess the next word, almost like a game. For example, if it reads “I like my coffee with cream and ___,” it should predict “sugar” as the next word. Whenever it guesses wrong, the system adjusts the model (like a teacher correcting a student). After seeing billions of words and getting these corrections, the LLM becomes very good at predicting what words usually come next.

This is a bit like how you might learn a language by reading a lot. Instead of someone teaching rules directly, the model picks up patterns from many examples of text. Over time, it “remembers” which words tend to follow others and uses those patterns to produce answers.

From Input to Response: How It Works

When you give an LLM some text (a question or prompt), it analyzes the words and figures out what you’re asking. Then it generates a response one word at a time, like an advanced autocomplete tool. It’s similar to the predictive text on your phone, but far more powerful. For instance, if you write “The sky is…”, the model might complete it with “blue”, and if you ask “Why do birds fly?”, it will use facts it learned (like that birds have wings) to come up with an explanation.

Each word it writes is chosen because the model predicts that word is a likely fit. By stringing together many likely words, the LLM produces sentences and paragraphs that sound fluent and human-like.

Why Are They Called “Large”?

The “large” in LLM refers to the huge size of these models. They have billions of internal settings (called parameters) that work like tiny switches tuned during training. Having so many switches allows the model to store a wide range of language patterns from its training.

Putting It All Together

In summary, an LLM works by learning from an enormous amount of text and then using that knowledge to continue a piece of writing in a sensible way. It doesn’t actually think or understand the world like a person; instead, it follows patterns it has seen in data. When you chat with an LLM, you’re getting its best guess for a good answer based on what it learned. Thanks to this training, LLMs can produce answers that feel very human – by predicting one word after another.