Autonomous systems — from self-driving vehicles to humanoid robots — are entering a new era. What was once software-defined is now scenario-driven, powered by massive data and large-scale models. The focus has shifted from recognition to action, from algorithms to end-to-end agent systems — some with language layers, others entirely non-linguistic.
As intelligence grows, so does the gap between capability and safety. Traditional deterministic safety frameworks can no longer keep up with the emergent behaviors of modern agents. Safety, once measurable and contained, is now inseparable from autonomy itself.
This initiative hub was created to close that gap — to rethink and rebuild what safe intelligence means. From theory to practice, from model design to data generation, our goal is to shape a safer world model — where intelligence and safety evolve together.
Exploring! Fearless, yet in awe.
K. Zhu
