S2E6 | Nov 4, 2026 - Physical AI Part 1 - Who Builds It?
Who builds the AI future? The answer reaches far beyond Silicon Valley. In the first installment of a three-part series on physical AI, Billy Riggs explores the people, infrastructure, and institutions that turn digital intelligence into real-world systems. From autonomous vehicles and robotic ports to factories and public transportation, the challenge extends beyond developing better models. It involves installing, operating, maintaining, and governing technology where people live and work. Drawing on his research in autonomous mobility and city planning, Billy examines why curb management, public procurement, workforce training, and reliable infrastructure deserve a central place in the AI conversation. He makes the case that national competitiveness will depend on the capacity to build—and that cities can become essential partners in that effort.
Takeaways and Key Themes
- From invention to deployment: Why advances in AI depend on physical infrastructure and institutional capacity to reach everyday life.
- Lessons from autonomous vehicles: What curb access, pickup and drop-off space, power, and communications reveal about integration.
- Connecting AVs and public transit: How station-area partnerships could support first- and last-mile travel while aligning public and private interests.
- The physical AI workforce: The role of electricians, technicians, construction crews, surveyors, fleet operators, educators, and public servants.
- Planning beyond the model: Why firsthand observation and local knowledge remain essential as AI enters planning practice.
- Cities as innovation partners: How permitting, procurement, workforce development, and management of public space can help turn inventions into useful services.
- The physical AI economy will be built by a much broader workforce than the technology conversation usually recognizes. The opportunity is to connect software expertise with skilled trades, public institutions, and the practical work of making systems function in the real world.
Soundbites
- “AI doesn't change society when someone trains a model. It changes society when it gets deployed on society.” — Billy Riggs
- “The limiting factor are the issues of integration. They're the issues where the digital world touches the physical world.” — Billy Riggs
- “If we want to do autonomous transit or autonomous logistics in ports, who's going to actually do the physical work? Who's going to build it?” — Billy Riggs
- “How do local governments … become innovation partners instead of just regulators with the police power?” — Billy Riggs
- “The future of physical AI is bigger than computer science.” — Billy Riggs
Chapters
00:00 The AI race is really a deployment race
04:08 The people and institutions missing from the AI picture
05:18 Why autonomous vehicle integration is harder than the technology
07:22 How AVs could support public transit through procurement
10:44 What past infrastructure revolutions teach us about AI
12:47 Physical AI needs a broader workforce than coders
15:49 Why city planning still needs human observation
04:08 The people and institutions missing from the AI picture
05:18 Why autonomous vehicle integration is harder than the technology
07:22 How AVs could support public transit through procurement
10:44 What past infrastructure revolutions teach us about AI
12:47 Physical AI needs a broader workforce than coders
15:49 Why city planning still needs human observation
Reseources
- Riggs, W., & Cornet, H. (2026). Autonomous vehicles and public transit incentives: A Case study of Waymo’s pilot transit credit program in the San Francisco Bay Area. Transportation Research Interdisciplinary Perspectives, 38, 102045. https://doi.org/10.1016/j.trip.2026.102045
- The Planner’s Use of Information, edited by Hemalata C. Dandekar — referenced in the discussion of site reconnaissance and the importance of observing communities firsthand.