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Scoop: Waymo hires former Anki engineers to lead truck efforts

image of 2 commercial trucks operated by Waymo's self-driving technology
Photo: Waymo

In one fell swoop, Waymo hired 13 robotics experts from defunct consumer robot maker Anki, including co-founder and former CEO Boris Sofman, to lead its nascent trucking initiative.

Why it matters: Waymo, a leader in robo-taxi development, wants to adapt its self-driving technology to other platforms, including commercial trucks. The hiring of Sofman and his all-star engineering team from Anki could accelerate that effort.

The big picture: Truck drivers are in short supply, which is why start-ups like TuSimple and Embark along with established trucking giants like Daimler and Volvo Group are racing to develop commercial trucks that can drive themselves.

  • Waymo has also been working in this space, but has been fairly quiet about its progress.
  • The company recently resumed testing in Arizona, after completing a pilot in Atlanta delivering goods for Google’s logistics team.

Details: Sofman will report to Waymo CTO Dmitri Dolgov and lead Waymo’s commercial truck efforts from San Francisco.

  • Sofman is not new to self-driving cars. As a student at Carnegie Mellon University, he worked with some Waymo alumni in the AV labs.
  • The group includes 5 PhD engineers, mostly from CMU's famed robotics program, as well as Stanford, MIT and Georgia Tech. 

Background: Anki was a high-profile consumer robotics startup that came out of Carnegie Mellon University's robotics program. Despite $200 million in funding, the company folded in April, laying off its entire staff after failing to raise additional capital.

What to watch: Dolgov talked about Waymo's wider ambitions at MIT Tech Review’s EmTech Digital conference in March.

  • “Our goal is not to build a car, we’re really building a driver. You can put this driver into all kinds of commercial applications, from ride-hailing, trucking, deliveries, connecting people to public transit and personally-owned vehicles."
  • "The nice thing about all those properties is that while the specialization layers are very different, the core technology, and the hardest problems that you’re trying to solve on research and engineering are exactly the same.”