hmm / hear you. my point wasn't that we are applying modular manifolds in the same way it was that we are working on model reliability from two extremal ends using the same principle. there are various ways to induce modular manifolds in model at various levels of resolution / power. we started at outside / working in level and so it works with any black-box model out of the box and zero knowledge needed, dont even need to know token dictionary to show effect.

We're already working on pushing construction deeper into model both architecture and training. currently that's for fine-tuning and ultimately full architecture shrinkage / pruning and raw training vs. just fine-tuning etc.

& it was just great to see someone else using modular manifolds even if they are using them at the training stage vs. inference stage. they're exploiting modular form at training, we're doing it at inference. cool to see.