AI Vocabulary · 01 The Model
What is Large Language Model (LLM)?
A model trained on huge amounts of text to predict the next piece of text. The engine behind ChatGPT, Claude, Gemini and Mistral.
A large language model is a model trained on enormous amounts of text to do one thing: predict which token comes next. Repeated over and over, that single skill produces answers, summaries, emails, code and translations.
"Large" refers to the scale: billions of parameters and a training process that costs millions. Popular assistants like ChatGPT, Claude, Gemini and Le Chat are apps built around such models. Many current LLMs are also multimodal: they can read images or documents, not only text.
An LLM produces what is plausible, not what is verified. That is why it can be brilliant at language and still hallucinate facts.
Why it matters for you
Knowing that an LLM predicts text explains most of its strengths and weaknesses. It is excellent at drafting, rephrasing, structuring and explaining. It is unreliable as a source of facts it has not been given. Use it as a capable assistant, not an oracle.
Own it
The model is only one layer. The same LLM can sit inside very different products with different data policies and prices. When you choose a tool, ask which model it runs on and whether you could switch.
Where it comes from
No one person coined "large language model". Language models are decades old; the "large" arrived after Google researchers' 2017 Transformer paper made training at huge scale practical. BERT and GPT followed in 2018, GPT-3 showed in 2020 that a big enough model can pick up new tasks from a few examples in the prompt, and ChatGPT made LLMs a household term in late 2022. Large language model (Wikipedia)
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