Public lesson preview
Explore how AI represents words and sentences as vectors in high-dimensional space, enabling semantic search, recommendations, and RAG.
By the end of this lesson, you will understand:
After tokenisation, each token is just a number - an index in a vocabulary. But index 4,821 tells the model nothing about meaning . How does AI know that "king" and "queen" are related, or that "bank" can mean a riverbank or a financial institution? The answer is embeddings .
Embeddings and Vector Databases - How AI Understands Meaning is part of AI Sprouts
Embeddings and Vector Databases - How AI Understands Meaning is part of AI Sprouts. Upgrade to unlock the full lesson, quizzes, progress tracking, and every academy.
Free for 7 days. Cancel anytime, no questions asked.