DEV Community

Sreekar Reddy
Sreekar Reddy

Posted on • Originally published at sreekarreddy.com

πŸ“ Embeddings Explained Like You're 5

GPS coordinates for words

Day 4 of 149

πŸ‘‰ Full deep-dive with code examples


The Map Analogy

How do you describe where Sydney is?

Option 1: "It's in Australia, on the east coast, near the ocean..."

Option 2: GPS: (latitude, longitude)

The GPS coordinates are precise and comparable:

  • Another city: (latitude, longitude)
  • You can calculate the distance between them.

Embeddings are GPS coordinates for words!


The Problem

Computers see words as random symbols:

  • "dog" = random ID #4521
  • "puppy" = random ID #8293

But wait... "dog" and "puppy" are similar! How would a computer know?


How Embeddings Work

Convert words to numbers that capture meaning:

"dog"   β†’ [x1, x2, x3, ...]   (many numbers)
"puppy" β†’ [y1, y2, y3, ...]   (many numbers)
"car"   β†’ [z1, z2, z3, ...]   (many numbers)
Enter fullscreen mode Exit fullscreen mode

Similar words β†’ Similar numbers!

Now you can:

  • Measure similarity between words
  • Find words with similar meanings
  • Group related concepts

Real Example

Search for "good restaurants":

  • Turn the query into an embedding (a long list of numbers)
  • Compare with all document embeddings
  • Find docs that are "close" in meaning
  • Return results like: "highly rated dining", "great places to eat"

Even though the exact words differ!


In One Sentence

Embeddings turn words into numbers that capture their meaning, so computers can understand similarity.


πŸ”— Enjoying these? Follow for daily ELI5 explanations!

Making complex tech concepts simple, one day at a time.

Top comments (0)