The MoSSAIC project examines how a neural network's physical implementation affects its computation. Researchers argue that specific hardware and software substrates can trigger safety failures, such as the Hydra effect in self-repair. This framework helps practitioners identify risks where model behavior diverges from theoretical expectations due to underlying system architecture.