Kodiak AI, a provider of physical AI-powered autonomous driving technology, has announced a collaboration with chipmaker AMD to implement its AMD EPYC Series processors to power Kodiak’s seventh-generation autonomous truck platform. Kodiak is the first company to deploy the advanced AMD EPYC processors into their hardware platform for driverless trucking. High-performance AMD EPYC Series CPUs provide the compute performance needed to quickly and reliably aggregate and preprocess the massive volume of sensor data required to safely operate the Kodiak Driver, Kodiak’s autonomous driving system. Wayne Lyons, senior director, automotive market, AMD, says: “Physical AI is pushing computing into some of the most complex and data-intensive environments in the world. “Kodiak is demonstrating what’s possible when advanced autonomous driving software is paired with high-performance AMD compute. “Together with Kodiak, AMD is providing the processing capabilities needed to move driverless trucking from innovation to significant scale.” Driverless trucks demand exceptional central processing unit (CPU) performance. Within the seventh-generation Kodiak Driver, AMD EPYC CPUs aggregate sensor data, preprocess information collected by LiDARs, cameras and radars, and support the path-planning processes that determine how the vehicle safely and efficiently navigates complex environments. Don Burnette, founder and CEO, Kodiak, says: “Physical AI requires compute capabilities that can rapidly handle enormous amounts of sensor data while supporting increasingly sophisticated AI workloads. “AMD delivers best-in-class CPU technology with the performance, scalability and efficiency required for advanced autonomous driving applications. “AMD EPYC CPUs give us the compute capabilities we need to advance the Kodiak Driver and continue commercializing autonomous trucking.” AMD EPYC is designed to support the demanding compute requirements of autonomous driving. Key CPU workloads in autonomous driving, including sensor processing, localization, and path planning, are latency-sensitive and cannot easily be parallelized. These capabilities help the Kodiak Driver efficiently process critical data and support increasingly sophisticated AI