1 Deploy NVIDIA H200 GPU cluster, single-card graphics memory 141GB HBM3, bandwidth 4.8TB/s, strong performance.
2 Support kh2-level parallel training, meet the needs of large-scale AI model training, and lay a solid foundation for business development.

1 Autonomous driving model training, optimize perception and decision-making algorithms, and improve vehicle driving safety and reliability.
2 Multi-modal data processing, integrating lidar, camera and radar data to achieve accurate environmental perception.
3 Virtual scene generation simulates extreme weather and complex traffic conditions, and helps to break through autonomous driving technology.

1 Excellent computing performance, H200 cluster completes the 3-day task of the traditional server in 1.5 hours, and the efficiency is greatly improved.
2 Strong multi-modal support ability, synchronous processing of multiple data types, meeting real-time requirements.
3 Self-developed scheduling framework, improve the GPU utilization rate to 85%, higher than the industry average of 60%, and optimize the utilization of resources.

1 Integrated H200's end-side reasoning module supports real-time data processing and low-latency decision-making, and adapts to autonomous vehicles.
2 Adopt advanced heat dissipation technology and compact design to ensure the stable operation of the hardware under complex working conditions and improve the intelligence level of the vehicle.

1 For power grid inspection robots, customer service robots and other scenarios, develop special AI hardware to meet diversified needs.
2 The device has high-efficiency computing power and low power consumption, which can extend the battery life and improve work efficiency and reliability.

1 Continuously expand the application scenarios of intelligent hardware, from transportation to industry and service fields, and promote the intelligent upgrading of various industries.
2 Through collaborative optimization of software and hardware, improve hardware performance and compatibility to meet the customized needs of different customers.

1 End-to-end model training, shorten the iteration cycle by 30%, and accelerate the iteration and optimization of autonomous driving technology.
2 Long tail problem optimization, a single card supports 5000+ virtual scene parallel simulation, improving the generalization ability of the model.
3 Cooperate with many car companies to provide all-round support from hardware to software to help the commercialization of autonomous driving.

1 Intelligent body technology application, customer service robots realize natural language understanding, and improve service efficiency and quality.
2 Power distribution automation decision-making, based on timing data analysis, to achieve accurate fault location and rapid recovery.
3 Intelligent operation and maintenance have been upgraded, the accuracy rate of equipment abnormal warning exceeds 98%, and the scheduling optimization reduces energy consumption by 15% to ensure the stable operation of the power grid.

1 Actively expand to more vertical industries, such as industrial quality inspection, intelligent logistics, etc., to explore new market growth points.
2 According to the characteristics and needs of different industries, provide customized solutions to realize the deep integration of technology and business.