Understanding Large Language Models (LLMs)
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What are LLMs?
Large Language Models like ChatGPT, Claude, and Gemini are AI systems trained on vast amounts of text to understand and generate human language. They power chatbots, coding assistants, and writing tools.
How They Work
LLMs predict the next word (token) based on context. Trained on billions of sentences, they learn grammar, facts, and reasoning patterns.
Input: "The capital of France is"
Model predicts: "Paris" (highest probability next token)Key Concepts
| Term | Meaning |
|---|---|
| Token | A word/word-piece |
| Parameters | Learned weights (billions) |
| Context window | How much text it can read |
| Prompt | Your input/instruction |
The Transformer Architecture
LLMs use the "Transformer" with an attention mechanism that weighs which words matter most for understanding context.
Limitations
- Can "hallucinate" — state false info confidently.
- Knowledge has a training cutoff date.
- No true understanding — pattern prediction.
FAQs
What is prompt engineering?
Crafting effective inputs to get better outputs from an LLM. More in our AI section.
Are LLMs conscious?
No — they predict text statistically; they don't think or feel.