Programmable Rail

Programmable rail research explores methods for controlling and directing the behavior of complex systems, ranging from large language models (LLMs) to neuromorphic computing architectures and photonic processors. Current efforts focus on developing flexible and efficient mechanisms for implementing these controls, including novel algorithms for error correction, machine learning-driven optimization of photonic devices, and the use of transformer networks as programmable computers. This work aims to improve the safety, efficiency, and controllability of diverse technologies, with applications spanning from safer AI systems to more energy-efficient computing and advanced robotic surgery.