To illuminate the mechanics, we will step inside the neural networks themselves. Through interactive 3D visualizations of the LM Head, the Residual Stream, Attention mechanisms, and MLPs, we will explore how LLMs geometrically route and map semantic concepts into high-dimensional space.

Paired with the Johnson-Lindenstrauss Lemma, this geometric understanding opens the door to a profound global opportunity for a new vector-based International Phonetic Alphabet (IPA) inspired by Hangul’s multilingual adaptability. Adopting this unified framework can enable the training of vastly more efficient, cross-lingual edge models, potentially accelerating international literacy and including global second-language acquisition. We conclude with discussion of uniting standards bodies, academia and government to back natively LLM-compatible Hangul formatting standards – to position new Hangul tokenization as the foundational infrastructure for the future of global AI