Module 4 · Level I · Foundations

Types and styles of AI

Narrow and general, predictive and generative, rules and learning: the different styles of AI and where you already meet each one.

6 lessons · about 1 hour

The module in 44 secondsCaptions on · sound optional

What’s inside

  1. 01
    Narrow AI and general AI

    Every AI you can use today is narrow in some way, and claims about 'general' AI depend heavily on who is defining it. · 9 min

  2. 02
    Rules or learning: two ways to build AI

    AI can follow rules that experts wrote down, or learn patterns from data, and most real systems mix the two. · 9 min

  3. 03
    Predictive AI and generative AI

    Some AI judges or forecasts; some AI makes new content. Knowing which you're using changes how much you should trust it. · 10 min

  4. 04
    AI that sees, hears, recommends and moves

    Recommendation systems, computer vision, speech and robotics: four families of AI you already meet, and what each is good and bad at. · 11 min

  5. 05
    Assistants and agents

    An assistant answers you; an agent takes steps on your behalf. The difference changes what can go wrong and how closely you should watch. · 10 min

  6. 06
    Spotting the type: a field guide for home and work

    A practical guide to recognising which style of AI you're dealing with, at home and at work, and what that tells you to check. · 10 min

Where this sits on your path depends on your assessment. Some people skip this module outright; others start here. The free placement assessment decides, and the first lesson of every module is free to read. Find your level →

Also at Level I

1What AI actually is
AI, machine learning, deep learning and generative AI, untangled: what each term means, what it doesn't, and why the hype and the fear both miss.2A short history of AI
From Turing and the 1956 Dartmouth workshop through two AI winters, deep learning and the transformer to ChatGPT and agents: how we got here, and what it predicts.3How machines learn
Data, training and prediction; supervised, unsupervised and reinforcement learning, explained with everyday examples and no maths.5Meet the models
Language, image, speech and video models; open and closed; large and small; reasoning models: the kinds of model behind the tools, and who makes them.