dailyai.report

A theoretical proposal suggests human languages function as latent spaces designed for efficient information compression. This framework treats linguistic evolution as an optimization process similar to neural network training. Researchers argue that syntax and grammar act as encoding schemes. Such a perspective helps developers better understand how LLMs map semantic relationships during tokenization.