Tersyn Labs
non-profit
AI & ML interests
We are interested in small language models, model compression, and efficient neural architectures. Most of our work focuses on getting more capability out of fewer parameters through quantization, pruning, distillation, parameter sharing, and better training methods. We are also interested in multimodal models, mechanistic interpretability, and understanding which parts of a model actually matter for a given capability.
