What are Large Language Models (LLMs) and how do they work?
What are Large Language Models (LLMs) and how do they work?
Ask by Amrith Chandran
Updated 22 Apr 2026
Large Language Models (LLMs) are advanced AI systems trained to understand, generate, and work with human language. They can write text, answer questions, translate languages, summarize documents, generate code, and more.
They are called:
Simple Idea (Layman Explanation)
LLMs work like a very advanced autocomplete system.
When you type:
It predicts:
But at a much deeper level—it understands context, grammar, tone, and intent.
How Do LLMs Work?
1. Training on Massive Data
LLMs are trained on huge datasets containing:
They learn:
Relationships between words
2. Tokenization (Breaking Text into Pieces)
Before processing, text is converted into smaller units called tokens.
Example:
3. Neural Networks (Transformer Architecture)
Most modern LLMs use the Transformer architecture, introduced in the paper Attention Is All You Need.
Key concept:
Attention Mechanism → helps the model focus on important words in a sentence
Example:
The model understands “it” = animal, not road.
4. Prediction (Next Word Generation)
LLMs generate text by predicting the next most likely token step by step.
Example:
This happens repeatedly to form full sentences.
5. Fine-Tuning & Alignment
After initial training, models are improved using:
This helps them become:
Step-by-Step Flow
What Can LLMs Do?
Limitations
Real-World Use Cases