Embeddings Magic

Embeddings are a way to represent text as numerical vectors, enabling semantic search by placing similar texts near each other in a high-dimensional space. This allows computers to understand the meaning behind text, rather than just matching keywords. Embeddings make it possible to compare and retrieve results based on meaning, rather than exact wording. To use embeddings, text is converted into vectors and then compared using metrics like cosine similarity. This technology is a crucial building block of modern AI applications.