A new theoretical framework posits that human languages function as latent spaces designed for efficient data compression. This perspective treats linguistic evolution as an optimization process for transmitting complex concepts. Researchers argue this mirrors how LLMs organize internal representations. The theory offers a new lens for understanding how tokenization affects model reasoning.