📍 Embeddings Explained Like You're 5

GPS coordinates for words

Day 4 of 149

👉 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"   → [x1, x2, x3, ...]   (many numbers)
"puppy" → [y1, y2, y3, ...]   (many numbers)
"car"   → [z1, z2, z3, ...]   (many numbers)

Similar words → 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.

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