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Concepts

Fundamentals

AI, machine learning and language models. Which one sits inside which.

On this page
  1. What matters in this area
  2. A common misconception
  3. Key terms
  4. Articles

Artificial intelligence, machine learning, deep learning and language models are not synonyms, even though they are used as if they were. They are nested layers, one inside the next. The distinction is worth learning first, because it explains most of the confusion in public argument about AI.

What matters in this area

  1. 01

    Artificial intelligence is the umbrella term

    Systems that do things once assumed to require human thought: recognising, predicting, conversing, planning or deciding.

  2. 02

    Machine learning learns from examples

    Nobody writes down every rule by hand. The program infers regularities from data. Deep learning is the part of this that uses large neural networks.

  3. 03

    A language model is one kind of model

    A large language model is trained on an enormous quantity of text. A multimodal model also handles images, audio or video.

  4. 04

    Most AI is not a language model

    Fraud detection, demand forecasting and industrial quality control usually run on far smaller models that nobody writes headlines about.

A common misconception

Key terms

Whole glossary →
Large language model (LLM)
A neural network trained on an enormous quantity of text that processes and produces language.
Neural network
A layered calculation whose numbers are adjusted on the strength of examples.
Activation function
A small kink after each layer, and the reason a deep network is useful at all.
Deep learning
The part of machine learning that uses large, many-layered neural networks.
Parameter (weight)
A number inside the model that was learned during training.
Token
Text chopped into small pieces. The model reads and writes tokens, and they are what you are billed for.
Multimodal model
A model that handles more than one kind of content: text, images, audio or video.

Articles on this topic

How a neural network actually works

No brains and no magic, just adjustable numbers. An explanation without the mathematics, but without simplifying it into being wrong.

9 min