AI, Actually Explained

You have heard that AI matters. Nobody has told you what it is. This course starts from nothing: no maths, no code, no assumed background. By the end you will know what the word actually names, how a trained model differs from a program someone wrote, what a chatbot is doing when it answers you, why it can be badly wrong while sounding certain, where this technology already sits in your day without a label on it, what changed around 2022, and how to think about AI and work without either panic or dismissal.

1. 1What the word actually names6 minAI names whatever machines have only just learned to do, so ask what a system does instead.
2. 2Written by a person, or grown from examples7 minA written program follows rules a person can read; a trained model follows patterns nobody ever wrote down.
3. 3What training on data actually means7 minTraining nudges billions of numbers toward the examples, so the examples decide what the model becomes.
4. 4Where it already is, without the label6 minMost AI in your life is unlabelled, and what matters is who pays when it is wrong.
5. 5What a chatbot is doing when it answers8 minA chatbot writes one likely chunk at a time, so sounding right and being right come from the same place.
6. 6Why it can be wrong and sound completely sure7 minNothing in the model checks anything, and invention clusters exactly where the details get specific.
7. 7What it cannot do, honestly8 minEverything a model seems to know about you or about today was handed to it by the product, not held by the model.
8. 8What changed around 20227 minThe 2022 breakthrough everyone noticed was access; the breakthrough underneath it was scale.
9. 9AI and jobs, without panic or dismissal8 minModels take tasks, not jobs, but a job whose learnable tasks all go is a job in trouble.