"Everything AI related that has ever been innovated on has been through the lens of something completely digital. The challenge for the physical AI world is how do you actually experience things in real life."

In this episode, Daniel and James sit down with Zach Greenberger, CEO of Nexar and former chief business officer at Lyft, to dig into the real-world data layer that's accelerating autonomous vehicles and physical AI. Nexar has built a network of 450,000 connected dashcam vehicles that cross every street in Manhattan four times a day, log 310 million miles per month, and have captured 75 million accidents over the past decade. Two months of Nexar's driving data exceeds what every autonomous vehicle company combined has ever driven — and Zach argues this edge case data is exactly what AV companies need now that simulation alone has reached its limit.

The conversation goes beyond cars. Nexar recently launched a collision prediction model called BADASS (Beyond ADAS) that works on drones, planes, tanks, delivery robots, and industrial equipment, proving that automotive data is an incredible proxy for understanding real-world physics. Zach breaks down the difference between real-world and real-time data, why the smart city pitch is finally achievable without massive infrastructure investment, and how Nexar's recent merger with Nauto gives them 98% US coverage. He also draws a careful line on data privacy, explaining why consumer-chosen dashcams create a fundamentally different trust model than stationary surveillance cameras, and predicts delivery robots, autonomous security guards, and commercial drones will proliferate within 12 to 24 months.

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