This is Unsupervised Learning: nobody labels anything. You just have a pile of
dots. Clustering lets the computer discover the groups on its own, by putting things that are
close together into the same group. Try the real-world examples below — then watch it work,
step by step.
Try a real-world example (the dots have NO labels — that's the point):
Grey dots = no labels at all. Press “Find groups” and watch the magic.
How many groups to find?
🤖 In a real AI — this is “unsupervised” learning
No teacher, no labels! The computer placed a few centres, sent each dot to its nearest centre,
moved the centres to the middle of their dots, and repeated until they stopped moving. This is called
k-means. Real life uses it to group customers, songs, photos — whenever you
want to find groups but nobody has labelled anything.