What is a large language model (LLM)?
An LLM is a category of AI model trained on huge amounts of text to understand and generate language. (IBM)
Most modern LLMs use the transformer architecture, which helps them handle language at scale. (IBM)
How LLMs work (without the math headache)
Step 1 — Training data: books, websites, code, documents
Step 2 — Tokenization: text becomes chunks (“tokens”)
Step 3 — Prediction: the model learns to predict likely next tokens
Step 4 — Inference: your prompt → it predicts the best continuation
Step 5 — Alignment / safety: additional training and rules shape behavior
What LLMs can do well
- Draft and rewrite text
- Summarize documents
- Translate
- Create outlines
- Generate code
- Explain topics in simple language
What LLMs struggle with
- Perfect factual accuracy (hallucinations)
- Hidden calculations (can be wrong confidently)
- Real-time truth (unless connected to tools/sources)
- Sensitive legal/medical certainty
Step-by-step: how beginners should use LLMs safely
- Use LLMs for drafting, not final truth
- Ask for sources for important claims
- Cross-check with official docs
- Keep sensitive info out
- Build a template prompt library for repeatability
FAQ
Is ChatGPT an LLM?
ChatGPT is a product that uses LLMs.
Do LLMs “understand” like humans?
They model language patterns extremely well, but “understanding” is not the same as human experience.