ManuAIVI

L024 · Under the hood · 2 min · Interactive

Embeddings: meaning as a map

An embedding turns a word or sentence into a list of numbers, so things with similar meaning sit close together.

01 · The idea

Computers cannot compare meanings directly. So we convert text into numbers, called an embedding. Think of it as a position on a huge map.

On this map, "doctor" lands near "nurse" and "hospital", far from "football". "Cheap flights to Bangkok" lands near "low-cost plane tickets Thailand", even with no shared words.

This is how modern search finds what you mean, not just what you typed. It powers recommendations, duplicate detection, and lets chatbots find the right page in your documents.

Try it below: tap any word on the map to see its nearest neighbours, then try the word maths.

02 · Think of it like this

It is like a supermarket. Apples sit near bananas, soap sits near shampoo. You find things by walking to the right area, not by reading every label.

03 · Try the toy

Try it

A map of meaning

An AI stores each word as a point. Words that mean similar things end up close together. Tap a word.

catkittendogpuppyhorselionpizzapastabreadricenoodlesphoVietnamJapanFranceBrazilKenyacarbustrucktrainbikemanwomankingqueenhappyjoyfulcalmsadangry
  • Animals
  • Food
  • Vehicles
  • Feelings
  • Countries
  • People

Tap any word to see its three closest neighbours.

Word maths: directions mean something too.

The dashed arrow is the step from “man” to “woman”. Take the same step from “king” and see where you land. This is how search and chatbots find things that mean the same, even when the words differ.

04 · Do it now

05 · Quick check

Why can embedding search find "budget hotel" when you typed "cheap place to stay"?

Words in this lesson

See also

Play it

Lab · 10 min · runs in browser

AI Brain Lab

Watch a real tokenizer cut up your text, build a tiny next-word machine, and spin a temperature wheel.

L024Interactive