AI & Machine Learning

Embeddings are the bridge between human-readable data and machine-processable mathematics. They are the input to vector search, the foundation of recommendation systems, and the representation layer in modern NLP. Despite their centrality, most engineering teams treat embeddings as a black box: call an API, get

Vector search is one of those technologies that sounds intimidating until you build one. The core idea is deceptively simple: convert your data into numerical vectors (embeddings), store them in a specialized index, and find similar items by measuring distance in vector space. The implementation