Product · Model Infrastructure
MG-SGLoRA — meta-genetic sparse generalized LoRA.
MG-SGLoRA is SHV's core optimization layer. It enables sparse, efficient adaptation of large models while preserving stability and long-term evolvability.
Why MG-SGLoRA matters
As models grow, updating them without losing previous capabilities becomes harder. MG-SGLoRA is designed to inject new skills and behaviors without collapsing the rest of the system.
It forms a base layer for Eunoia and other SHV systems, allowing generational updates and experiments with far less compute waste.
Applications
- • Rapid adaptation of large language models.
- • Multi-task specialization without full retraining.
- • Research into meta-learning and self-modifying systems.
Access & licensing
MG-SGLoRA is available for select partners and research collaborations. SHV is exploring licensing pathways for institutions that need deep access to the technique.
Talk to SHV about MG-SGLoRA →