A new theoretical framework proposes that human languages function as latent spaces designed for efficient information compression. This perspective treats linguistic evolution as an optimization process for data transmission. Researchers argue this mapping helps explain how LLMs mirror human semantic structures. It offers a technical lens for understanding the intersection of linguistics and neural networks.