Vector Embeddings
High-dimensional coordinate lists that capture the semantic meanings of words, sentences, or images.
Vector Embeddings map words or documents to high-dimensional spaces. Mathematical distances between vectors represent semantic similarities, enabling search algorithms to perform conceptual lookups.
Historical figures and technical concepts for informational purposes only. Not technical, professional, legal, or financial advice. Sources: Official Documentation.