Juan Carlos Santamaria, Trimble. Physical AI in the Job Site

We talk with Juan Carlos Santamaria about how AI in engineering has evolved from rule-based robotics to modern systems that perceive job sites and help machines make better decisions. We dig into Trimble’s push from AI perception to operator assist and what it will take for engineers and operators to trust AI in the field and in design tools. • Juan Carlos’s PhD-era view of AI as a multidisciplinary field • Planning versus reactive robotics and why brittle plans fail • AI for perception on construction sites using point cloud images and video • Turning recognition into jobsite semantics like cycles and bucket loads • The shift toward decision-making with operator assist in the cab • Autonomy in mining versus the realities of safety policy and adoption • Why trust builds faster when operators can experience the system • Zero tolerance expectations for machines compared with human error • Point cloud segmentation today and what engineers want next • Natural language interfaces that execute software commands from prompts • SketchUp and 3D Warehouse visual search and AI-assisted edits • Interoperability across tools and the “Tower of Babel” problem • Planning for unknown unknowns when digging into existing infrastructure • How AI work gets prioritized across product teams • Why kids and professionals should learn AI as a tool for thinking clearly