Model drift is the silent failure mode of every automated inspection system. Teams invest millions, but when the underlying data shifts (new lighting, sensor noise), the AI fails silently.
Origin
Everyone seems to think that automation is 100% hands-off after development. They build a new machine or train a new model, and expect it to work in perpetuity. My experience has shown me that is simply not how the real world works.
I've been developing automated systems since the invention I published in undergrad. I know first hand the grit it takes to get an automated solution working, but more importantly how it requires continuous human interfacing to stay working.
Experience in High-Stakes Environments
From early on building maintenance and inspection planning systems for one of the largest Oil & Gas refineries in the world, to building an entire Computer Vision R&D team in the most expensive manufacturing space ever, I know the consequences of failure in high stakes environments.