Picture this:
You walk onto a bus.
Dozens of seats. Some taken, some empty.
You scan the scene in under two seconds, and then sit.
Not next to the loud teenager.
Not next to the old man with the newspaper.
You choose the seat next to the girl with headphones and a laptop.
Why? You’re embedding.
Wait, what?
Embeddings aren’t just for AI. They're a cognitive shortcut: a way of mapping complex, fuzzy, emotional data into decisions we can make quickly.
When your brain processes a space like a bus or a cafeteria, it runs this internal logic:
- “That person kinda looks like me.”
- “This side of the room feels chill.”
- “That group gives off strong ‘we all know each other’ energy, avoid.”
You’re not calculating dot products.
But you are assessing affinities in high-dimensional social space.
Homophily in action
Psychologists call this homophily: our tendency to associate with those we perceive as similar. And it’s not just deep stuff like values or beliefs. It’s surface-level cues: clothing, body language, vibe.
In a famous 1960s experiment, people were more likely to sit near someone they perceived as similar: in age, dress, gender, even posture.
They didn’t talk to them. They just sat closer.
Just like embeddings cluster similar meanings.
Just like vector search finds the closest match.
Just like Netflix recommends, “if you liked that, you’ll probably vibe with this.”
Your brain: the OG vectorizer engine
Humans have been doing this for millennia.
When we scan a crowd, we mentally reduce everyone into latent features:
- Trustworthy vs sketchy
- Familiar vs foreign
- Friendly vs intense
- Safe vs unpredictable
Then we act fast. Not always fairly. Not always consciously.
But efficiently. It’s unsupervised learning with bias baked in.
Sound familiar?
Aaand this matters because...?
We often talk about embeddings as machine magic.
But they’re deeply inspired by how we, as humans, navigate meaning, similarity, and context.
We vectorize every social situation we enter.
So next time you sit on a bus and instinctively pick a seat near someone "like you", now that your brain just executed a high-dimensional similarity search.
The ultimate embedding model isn’t on HuggingFace, it’s in your head.
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