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HOU Xiaodi Wants to Start Making Runs 'Driver Out' Next Year
HOU Xiaodi Wants to Start Making Runs 'Driver Out' Next Year
TuSimple autonomous truck. PHOTO: Credit to TuSimple
Associated Company
TuSimple TuSimple

According to Forbes, TuSimple's cofounder HOU Xiaodi said in an interview that he wants to start making runs "driver out" next year. Hou envisioned TuSimple while still at Caltech, founding it in 2015 with his friend and business partner CHEN Mo, who is CEO, while Hou opted for the CTO and president titles. Chen is based in China, where TuSimple has a second headquarters and is developing robot trucks to carry cargo at local ports.

Hou earned degrees in computer science and engineering from Shanghai Jiao Tong University in 2008, then made his way to Pasadena, California, for doctoral studies at the California Institute of Technology, deciding that Caltech—home to NASA's Jet Propulsion Laboratory—was a better fit than grad schools in the Bay Area. "I wanted to live deliberately," he says.

In late 2017, TuSimple raised USD 55 million with plans to use those funds to scale up testing to two full truck fleets in China and the U.S. By 2018, TuSimple started testing on public roads, beginning with a 120-mile highway stretch between Tucson and Phoenix in Arizona and another segment in Shanghai.

"Autonomous driving is one of the most complex AI systems humans have ever built. After three years of intense focus to reach our technical goals, we have moved beyond research into the serious work of building a commercial solution" Hou said.

TuSimple completed a USD 95 million round in late 2018, led by Chinese tech firm Sina Corp., its earliest backer, with investment from Hong Kong-based Composite Capital Management. U.S. backers include Nvidia, which supplies TuSimple's computing system. TuSimple is now the first autonomous trucking unicorn, and it has built up a significant capital advantage among several U.S. companies that operate autonomous trucks.

Hou expects to raise more money over the next year, his ambition and confidence stem from TuSimple's years of experience in driverless trucks. However, TuSimple isn't the only startup focused on driverless trucks. Embark Trucks, Ike, Starsky Robotics and Kodiak Robotics, all based in the San Francisco Bay Area, are racing to develop their own autonomous big rigs, but TuSimple is on the fast track.

Hou claims that TuSimple has a proprietary vision system that can see a kilometre ahead, farther than any other driverless tech company, including Waymo. Dozens of tech giants, startups and global auto players are jostling to catch up to Waymo. If he's right, TuSimple will be early to profit from the autonomous-driving boom.

In the United States, truck drivers have a "high-income garbage collector" joke. Because American truck drivers are highly paid, but their lives are extremely unstable and irregular, especially for long-distance drivers, who are always at home and have no fixed home. Nowadays, the younger generation is not willing to take this kind of job. Autonomous trucking looks like it could become a commercial success earlier, propelled by a driver shortage that the American Trucking Associations puts at 60,000 a year for semi drivers. 

HOU Xiaodi said that there were two main things to do at this stage: one is to serve U.S. customers well and further deploy unmanned cargo on a larger scale. Another is recruit talents, recruit talents, and recruit talents.

Enterprise Information

TuSimple is an innovative technology company that is devoted to the development and application of artificial intelligence and computer vision technologies.
CATEGORIES: AI
Last Funding Type
Series D
Number of Employees
101-250
Number of Funding Rounds
4
Total Funding Amount
83.10M

Enterprise Information

TuSimple
TuSimple is an innovative technology company that is devoted to the development and application of artificial intelligence and computer vision technologies.
CATEGORIES: AI
Last Funding Type
Series D
Number of Employees
101-250
Number of Funding Rounds
4
Total Funding Amount
83.10M

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