Embeddings son representaciones vectoriales numéricas de datos (texto, imágenes, etc.) que capturan significado semántico — colocando elementos similares cerca uno del otro en un espacio vectorial. Son fundamentales en la IA moderna, permitiendo búsqueda semántica, recomendaciones y RAG.
Qué son los embeddings
EMBEDDING → a VECTOR (list of numbers) representing data (a word, sentence, image, etc.):
→ captures MEANING → semantically similar items have SIMILAR vectors (close in vector space)
→ e.g. 'king' and 'queen' have similar embeddings; 'cat' and 'dog' are closer than
'cat' and 'car'
→ produced by models (embedding models) that learn meaningful representations
→ turns data into numbers that capture semantic meaning (meaning as geometry)
