dailyai.report

A new theoretical framework treats human languages as latent spaces optimized for communication. The research argues that linguistic structures mirror the dimensionality reduction seen in neural networks. This perspective suggests that LLM tokenization may be approximating a biological compression mechanism. It offers a new lens for understanding how models map semantic meaning.