Research14h ago
Research
Languages Viewed As Designed Latent Spaces
A new theoretical framework treats human languages as latent spaces engineered for efficient data compression. This perspective suggests linguistic structures mirror the dimensionality reduction seen in neural networks. It reframes grammar as a compression algorithm. Researchers can now apply manifold learning to analyze how semantic meaning maps onto specific syntactic patterns.