For 25 years my work has been getting large systems to work in the real world. That meant leading a nationwide deployment, running engineering teams, and coordinating field crews and vendors across multiple markets, where a plan only counted once it was working on site.
That work taught me that the hard part is rarely the design. It is integration, measurement, and the discipline to operate a system after launch day.
Physical AI has the same problem. Models that look finished in simulation meet sensor noise, thermal limits, latency budgets, and operators who need to trust them. I started EmbodiedEdge to work on that gap in the open: on the lab's own robots and Jetson hardware, with measured results and an honest status on what works and what doesn't yet.