Large AI models are scaling rapidly, with bigger architectures and longer training runs becoming the norm. As models grow, however, a fundamental training stability issue has remained unresolved. DeepSeek mHC directly addresses this problem by rethinking how residual connections behave at scale. This article explains DeepSeek mHC (Manifold-Constrained Hyper-Connections) and shows how it improves large language model training stability […]The post DeepSeek mHC: Stabilizing Large Language Model Training appeared first on Analytics Vidhya.