Designing reliable training infrastructure for edge & foundation models with Tianshu Yu at Liquid AI

Reliable training infrastructure is a prerequisite for scaling foundation models. On "Hello, Agent!", Tianshu Yu, Member of Technical Staff at Liquid AI, explains why infrastructure discipline is essential to distinguish between optimization and corruption. From debugging floating-point instabilities to navigating the architectural constraints of edge-deployed vision language models, he argues that building reliable ML systems requires treating infrastructure as a distinct, rigorous engineering layer.