Tete Xiao, VP of Engineering and AI, Bot Auto joined Grayson Brulte on The Road to Autonomy to discuss the fundamental shift from virtual AI to the physical AI required for commercial autonomous trucking.

Tete co-authored Segment Anything, the landmark paper that ushered in the era of specific models to an era of foundation models that generalize across large segments of data. This approach which he is implementing at Bot Auto, enables the company to move beyond the limitations of previous technology, treating autonomous trucking as a compute-driven challenge where the system learns to navigate the complex physics of driving a truck.

To ensure safety, Bot Auto is utilizing a top-down redundancy architecture that mirrors aviation’s triple autopilot systems. Including dual onboard computers and independent software stacks running parallel algorithms with deliberately different logic to prevent a single failure from propagating through the system.

This spring, Bot Auto is planning to launch fully autonomous commercial operations with Ryan Transportation on the Houston to Dallas corridor. No safety driver. No safety observer. No human in the cab.

Episode Chapters

00:00 AUTNMY AI

00:25 Segment Anything

05:04 Virtual AI to Physical AI

09:08 Redundancy and Aviation-Inspired Architecture

13:40 Hardware and Software

17:00 Launching Fully Autonomous Operations

20:00 Foundation Models and Reinforcement Learning

27:52 Compute Infrastructure

35:22 Staying Ahead

42:30 Building a Virtual Driver

47:06 AGI48:36 Transportation Company

53:59 Future of Bot Auto

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Episode 383 | From Segment Anything (Virtual AI) to Autonomous Trucks (Physical AI)