Military autonomous vehicles are one of the significant future trends to meet the future warfare. By adopting AI algorithm, machine learning, the autonomous solution is providing vital to operating tactical vehicles in a war field. The solution is capable to collect and process data to do machine learning, then analysis and recognize the objections. Continuously, it diagnostics and delivers problem prediction also solution prescription, which enabling personnel to focus on making precise adjustments to optimize military vehicles and ships.

Deployable via sensors or vehicle upgrades, the solution performs frequent evaluations on vehicle subsystems such as the internal combustion engine, suspension and chassis, electrical system, fuel system, and lubrication system. It then uses real-time analysis to ensure rapid-onset issues are identified prior to failure.

Advancing technology is ushering in a new era in transportation with self-driving vehicles becoming a reality, poised to revolutionize our movement and interaction with the world. However, this exciting technology poses new challenges, particularly in the field of high-performance computing (HPC) .

Large amounts of virtual training data can speed up the development of autonomous driving systems, improving their safety and reliability through testing and optimization.

Enhancing and reconstructing images can improve autonomous driving systems’ ability to identify road signs, markings, and other traffic signals.

AV1000 rugged liquid cooled GPU server optimizes with excellent 3rd Gen Intel® Xeon® Scalable Processors. In a scenario where virtual machine is integrated with C5ISR system, the 40-core processor allows the CPU resources be reallocated to one or more virtual machines. AV1000 also equipped with high-capacity DDR4 memory, and leading-edge thermal management (liquid cooled), it combines impressive compute power, data-handling capabilities, and storage capacity (48TB NVMe in 2U) in a rugged solution that can withstand harsh conditions and demanding environments —including potholes, collisions, shock and vibration, and extreme temperatures that cause traditional systems to fail.