The Limits of Mathematics in Language Generation: A Training-Free Experiment

This experiment reveals a critical gap between understanding word relationships and generating coherent text. While pure mathematical approaches successfully capture semantic meaning through co-occurrence patterns and SVD factorization, they falter at text generation. The findings highlight why modern neural networks require training and suggest that meaning extraction and text generation are fundamentally different computational problems.