Explaining Vector Embeddings To Mom

When I first learned about vector embeddings, I thought it was fascinating. But whenever I discuss it up with others, they gave me that "oh no, another scary tech thing" look - as if it was rocket science and they’d need a PhD to understand it.

So, I decided to take on a challenge: Could I explain vector embeddings to my mom without using a single technical jargon?

At first, I did some searches, some LLM help, they were guiding me to use the example of mangoes and fruits, but recently, when my sister was getting ready for school, and was yelling, “Where’s my uniform?”

My mom replied:

“Kitni baar boli hoon ki uniform upar wale shelf me hai!”
(How many times have I told you, the uniform is on the top shelf!)

Then I thought I could explain this concept with this trending topic (like we express ourselves using viral Instagram Memes)

Explanation: The Wardrobe Example

In our Indian home, clothes are never just thrown in. Mom has a system: My & my sibling’s wardrobe is in my sibling's room, but behind the separate doors. Mom’s wardrobe is in her room.

Inside each wardrobe, there is a left door and a Right door. Behind each door, there are 3 sections: Top shelf uniforms/professional outfits, Middle shelf for T-shirts/Topwears, Bottom shelf pants/jeans/bottomwears, and Innerwear hung on hooks inside the doors.

It’s neat, predictable, and easy to find things.

Mapping: Turning Clothes into Coordinates

Let’s say I want my blue T-shirt, and I tell my mother in the kitchen; Mom, where’s my blue T-shirt. After that, the usual dialogue “Saare kaam main hi karoon… +200 more lines”, she will tell me the exact place of my t-shirt, without even going to the room.

Now, for you (tech people), we can describe it as:
[Room: My room, Door: Left, Shelf: Middle, Type: T-shirt]

If we turn that into numbers:

My room -> 0
Left door -> 0
Middle shelf -> 1

Now the position of my T-shirt is: [0, 0, 1, T-shirt]

Similarly:

My sibling’s T-shirt: [0, 1, 1, T-shirt]
Mom’s T-shirt: [1, 0, 1, T-shirt]

These numbers are like coordinates on a map, telling us exactly where something lives in our “wardrobe space.”

Wardrobe To Vectors

Now Imagine This…

Instead of clothes, what if we’re arranging words, sentences, images, or sounds, basically data/information?

In AI, vector embeddings store words, sentences, images, or sounds in a multi-dimensional space (different rooms or wardrobes) where:

Similar meanings are stored close together (like my T-shirt and my sibling’s T-shirt, and corresponding to similar coordinate (same shelf position) distance in different dimensions (wardrobe).

Different meanings are far apart (like my T-shirt and a cooking pan)

Example: All my books, notebooks, and stationery are placed in the nearby places in my room, but my bike key is hanging in the living room.

Why Vector Embeddings Matter

By storing meanings as coordinates, AI can:

Find similar things (search “T-shirt” and get all T-shirts)
Group related items (keep all uniforms together)
Understand relationships (knowing my and my sibling’s T-shirts are similar kinds of items)

This is why embeddings are used not only in AI, but way before, already being used in search engines, chatbots, recommendation systems & more.

How You Can Explain It Too

Pick a familiar system - wardrobes, library bookshelves, kitchen spice rack, recommend picking the recent topic in your house, your mother, or whoever you are going to explain had just discussed or encountered. Also, break things into sections (dimensions).
Although I didn’t explain this part to my mother but, you can show how each item’s location can be described as numbers, as explained in the section “Mapping: Turning Clothes into Coordinates.”
Connect the example to how AI stores meanings & highlight how “closeness” in this space means similarity.

Conclusion

Just like Mom knows exactly where my jeans are without opening every shelf, AI knows where “mango” is and which other words are sitting right next to it.

Message from my Mom

“Thanks for reading this article, and I know you’re surely gonna forget tomorrow where your favourite jeans are, but don’t forget to like, and share your thoughts or anything I have missed. Follow me to get more articles like this.”