Uploaded December 2025 | Updated September 2026, 2 hours ago
Day 4/42: What Are Embeddings?
Yesterday, we broke text into tokens.
But tokens alone are meaningless numbers.
So how does a model know that “cat” and “kitten” are related?
That’s the job of embeddings.
An embedding is a numerical representation of *meaning*.
Words with similar meanings end up close together in a giant mathematical map.
This is why search works.
Why rephrasing still gets good answers.
And why LLMs can generalize instead of memorizing.
Missed yesterday? Start there.
Tomorrow, we explore where all these meanings actually live: latent space.
I’m Louis-François, PhD dropout, now CTO & co-founder at Towards AI. Follow me for tomorrow’s no-BS AI roundup 🚀
#Embeddings #AIExplained #LLM #short
Day 4/42: What Are Embeddings?
Yesterday, we broke text into tokens.
But tokens alone are meaningless numbers.
So how does a model know that “cat” and “kitten” are related?
That’s the job of embeddings.
An embedding is a numerical representation of *meaning*.
Words with similar meanings end up close together in a giant mathematical map.
This is why search works.
Why rephrasing still gets good answers.
And why LLMs can generalize instead of memorizing.
Missed yesterday? Start there.
Tomorrow, we explore where all these meanings actually live: latent space.
I’m Louis-François, PhD dropout, now CTO & co-founder at Towards AI. Follow me for tomorrow’s no-BS AI roundup 🚀
#Embeddings #AIExplained #LLM #short
