The recent advancements in neuromorphic computing and optical data center networks are pushing the boundaries of both fields, focusing on efficiency, speed, and robustness. Neuromorphic systems, particularly spiking neural networks (SNNs), are being optimized for real-world applications such as wafer map pattern classification and short-reach optical communications, demonstrating significant improvements in accuracy and energy efficiency. These networks are also being adapted to handle internal noise more effectively, enhancing their reliability in classification tasks. In parallel, optical data center networks are evolving with the introduction of fast-switched architectures, necessitating innovative routing solutions to manage packet loss during circuit reconfigurations. Unified Routing for Optical networks (URO) emerges as a promising framework, ensuring precise, time-based packet transmission and efficient resource utilization across various hardware configurations. Overall, these developments highlight a shift towards more integrated, efficient, and adaptable systems in both neuromorphic computing and optical networking.