Physical AI is rewriting what's possible for autonomous fleets, and the infrastructure decisions you make today determine your competitive position in 2035.

Colin Dhillon, futurist and advisor to NuPort Robotics, joins Chris Brandt on The Fleet to explain why fleet leaders who start building autonomous capability now gain compounding advantages over those who wait for "perfect" solutions. Neural networks have eliminated the need for human-written code in autonomous vehicles, learning from sensor data in real time instead. Lights-out factories are producing a million phones with zero humans. The truck cabin itself could disappear, replaced by humanoids that handle the last remaining manual task like placing safety cones.

This conversation breaks down how Physical AI (the convergence of neural networks, autonomous systems, and real-world operations) is reshaping fleet economics faster than most leaders realize, and what separates organizations positioning for the future from those still optimizing yesterday's operations.

Chapters:

0:00 Why “Robots Taking Jobs” Was Wrong - Until Now

2:10 Colin’s Journey from Car Design to Physical AI

4:18 What Is Physical AI?

7:24 80s Robots vs Today’s Neural Networks

9:48 Lights-Out Manufacturing for Fleets

12:38 30 Humanoids on Stage - Training Compressed from Weeks to Hours

15:22 How Autonomous Systems Change Fleet Labor Models

16:32 Why Colin Went from Fighting Regulation to Calling for It

18:46 The Infrastructure Problem - Why Autonomy Fails in the Real World

24:52 Why True 5G (and 6G) Matters for Fleet Autonomy

30:07 Why Fleets Will Be the First to Fully Adopt Autonomy

30:42 The Cone Problem - Autonomy’s Last Human Barrier

35:16 94% of Accidents Are Human Error - The Case for Physical AI

36:47 The Truck Cabin Might Disappear Entirely

42:44 How Zero-Marginal-Cost Operations Change Everything

48:47 About Kulbir Colin Singh Dhillon

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