Inside Tensor's Truly Self-Driving Robocar (w/ Tensor COO Jewel Li)

Ride AI47mApril 14, 2026

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AI-Generated Summary

In this episode of Ride AI, host Sophia Tung interviews Jewel Li, COO of Tensor, about the company's groundbreaking Tensor Robocar—the first consumer-ready Level 4 self-driving vehicle designed from the ground up. Li shares her journey from engineering at Wuhan University and a PhD at the University of Delaware, to working on IBM Watson’s DeepQA system that defeated humans on Jeopardy. She discusses the evolution of autonomous driving, emphasizing the shift from retrofitted vehicles to purpose-built, sensor-rich designs. The Tensor Robocar features a unique 37-camera, 5-LiDAR, 11-radar, and 22-microphone sensor suite, including under-chassis cameras to solve the 'cold start' problem. The car’s 8,000 TOPS compute system, with dual redundant AI layers, ensures safety and future-proofing. A retractable steering wheel balances regulatory concerns with user experience, while the design prioritizes passenger comfort with reclining seats, a Dolby Atmos sound system, and a long, spacious cabin. Li reflects on Tensor’s origins as AutoX, its pivot from grocery delivery and robotaxis to a consumer-focused robocar, and the strategic decision to launch first in the UAE before expanding to the U.S. in 2027–2028. The company’s confidence in its timeline stems from five years of development and rigorous validation. Key takeaways include: 1) Purpose-built, ground-up design is essential for scalable, safe Level 4 autonomy; 2) Sensor redundancy and multi-modal perception (cameras, LiDAR, radar) are non-negotiable for safety; 3) The retractable steering wheel is a UX and safety innovation that addresses the risks of human override in full autonomy; 4) Massive on-board compute (8,000 TOPS) is necessary to run powerful main and backup AI systems; 5) The cold start problem—ensuring safety when the car is first powered on—requires under-chassis sensors; 6) Regulatory readiness in markets like the UAE, with Vision 2030 ambitions, is a key enabler; 7) The business model includes both personal ownership and fleet sharing via partnerships like Lyft and Green Mobility in Denmark; 8) Consumer demand for a truly self-driving car is growing, especially as the technology proves reliable and safe.

Key Takeaways
1

Ground-up design is essential for scalable, safe Level 4 autonomy, unlike retrofitted vehicles.

2

Sensor redundancy across multiple modalities (cameras, LiDAR, radar) is critical for safety and reliability.

3

The retractable steering wheel balances regulatory requirements with user experience and safety.

4

8,000 TOPS of on-board compute ensures powerful main and backup AI systems, future-proofing the vehicle.

5

Under-chassis sensors solve the 'cold start' problem—detecting hazards when the car is first powered on.

…and 3 more takeaways available in PodZeus

Chapters
0:00
5 min

Introducing the Tensor Robocar and Jewel Li

Host Sophia Tung introduces Jewel Li, COO of Tensor, and sets the stage for a deep dive into the company's first consumer-ready Level 4 self-driving vehicle, the Tensor Robocar. Li’s background in AI and autonomous systems is highlighted, including her work on IBM Watson’s Jeopardy-winning DeepQA system.

5:00
5 min

From IBM Watson to Autonomous Driving

Li recounts her early fascination with AI, particularly natural language processing and tensor operations, which led her to pursue a PhD. She reflects on the historic moment when Watson beat human champions on Jeopardy, a milestone that drew her to IBM’s core AI teams.

10:00
5 min

The Evolution of Autonomous Driving at AutoX

Li discusses her nearly decade-long journey building self-driving companies since 2017, starting with AutoX in a house in Saratoga using Logitech cameras. She reflects on the industry’s shift from early prototypes to volume production and the challenges of retrofitted vehicles.

15:00
5 min

Sensor Architecture: The 37-Camera, 5-LiDAR System

We have this cold start problem when the car is first turned on, we need to check, the system needs to check, not us, not our employees, but the system needs to be able to check what is underneath the chassis.

Highlight
20:00
5 min

Why Not Just Cameras? The Case for Multi-Modal Sensing

There's nothing, there's no price on safety.

Highlight
High-Impact Quotes
There's nothing, there's no price on safety.
Jewel Li14:33
Viral: 90.0
In level four, you are allowing people not to look at the road, right? You're allowing people to get to sleep. Then you can't have that level two easy disengagement because people can... disengage by not even knowing that they disengaged, by accident.
Jewel Li16:44
Viral: 88.0
We have this cold start problem when the car is first turned on, we need to check, the system needs to check, not us, not our employees, but the system needs to be able to check what is underneath the chassis.
Jewel Li11:18
Viral: 85.0
Speakers

Host

Sophia Tung

Guest

Jewel Li
Topics Discussed
Level 4 Self-Driving Technology95%Ground-Up Vehicle Design90%Sensor Redundancy and Multi-Modal Perception88%Cold Start Problem and Under-Chassis Sensors87%Regulatory Strategy and Market Entry85%On-Board Compute and AI Architecture85%Fleet Sharing and Robotaxi Business Models82%User Experience and Retractable Steering Wheel80%
People & Brands

Jewel Li

person

45xPositive

Tensor

organization

38xPositive

AutoX

organization

12xNeutral

UAE

place

10xPositive

IBM Watson

organization

8xPositive

Lyft

organization

7xPositive

Jeopardy

media

6xPositive

Green Mobility

organization

4xPositive

Waymo

organization

4xNeutral

University of Delaware

organization

3xNeutral

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