Most language models today are built around the Transformer paradigm. That makes sense. Transformers work. They scale. They dominate modern NLP. But I wanted to explore a different question: What if language generation does not need to be modeled as attention over a context window? What if a model could generate language by carrying an evolving latent state through a learned geometry? That is the idea behind DRM Language Emitter . Repository: https://github.com/...