Vector Embeddings
💡 Quick Definition: Numerical high-dimensional array representations of text or images that capture semantic meaning and contextual relationships.
Detailed Explanation & Workplace Application
Vector embeddings map words, sentences, or documents into geometric space (e.g. 1536 dimensions in OpenAI text-embedding-3). Texts with similar meanings (e.g. "king" and "queen" or "refund" and "money back") sit close to each other, allowing lightning-fast cosine similarity search.
Practical Syntax / Framework Formula
embedding("How to cancel an order?") -> [0.0124, -0.0452, 0.0891, ..., 0.0031]
Cosine Distance between "Cancel order" and "Return package" = 0.89 (High Match)