dailyai.report

A new theoretical framework posits that human languages function as optimized latent spaces for information compression. This perspective treats linguistic evolution as a series of dimensionality reduction operations. By mapping semantic concepts to discrete tokens, humans minimize cognitive load. Researchers can now apply these geometric insights to improve tokenization strategies in large language models.