Foxconn Partners With NVIDIA to Build Automated Electric Vehicles


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NVIDIA and Hon Hai Technology Group (Foxconn), the world’s largest technology manufacturer, announced a strategic partnership to develop automated and autonomous vehicle platforms.

As part of the agreement, Foxconn will be a tier-one manufacturer, producing electronic control units (ECUs) based on NVIDIA DRIVE Orin™ for the global automotive market. Foxconn manufactured electric vehicles (EVs) will feature DRIVE Orin ECUs and DRIVE Hyperion™ sensors for highly automated driving capabilities.

“This strategic cooperation with NVIDIA strengthens the intelligent driving solutions Foxconn will be able to provide. Together, we are enabling the industry to build energy-efficient, automated vehicles,” said Eric Yeh, senior director of the Software Development Center at Foxconn. “This is a well-considered partnership that leverages unique strengths on each side in the pursuit of innovative EV development and opportunities.”

The partnership with Foxconn will allow NVIDIA to further scale its efforts and meet growing industry demand as more transportation leaders select DRIVE Orin for intelligent vehicles. In addition, by building EVs on the DRIVE Hyperion qualified sensor set, Foxconn will speed up its time-to-market and time-to- cost strategies.

“Our partnership with Foxconn will provide OEMs developing intelligent driving solutions with a world-class supplier that can scale for volume manufacturing of the NVIDIA DRIVE Orin platform,” said Rishi Dhall, vice president of automotive at NVIDIA. “Foxconn’s decision to also use the DRIVE Hyperion sensor suite for its EVs will help accelerate their path to production without compromising safety, reliability or quality.”

The automotive-grade NVIDIA DRIVE Orin system-on-a-chip achieves up to 254 trillion operations per second and is designed to handle the large number of applications and deep neural networks that run simultaneously in autonomous vehicles. NVIDIA DRIVE Hyperion is a modular development platform and reference architecture for designing autonomous vehicles. Combined, they serve as the brain and central nervous system of the vehicle, processing massive amounts of sensor data in real time so autonomous vehicles can safely perceive, plan and act.

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