On June 27th-28th, the 2nd China Data Center Server and Equipment Summit, organized by ICT-Event, took place in Shanghai as scheduled. Representatives from well-known enterprises and technical experts in the data center industry gathered together to explore the scientific construction and operational maintenance of next-generation data centers using emerging technologies in the era of infrastructure development. Gooxi, as a leading server solution provider in China, was invited to attend the event. Dong Yexing, Gooxi's Pre-Sales Manager for Solution, delivered an exciting keynote speech on the topic of "AI Private Deployment Solutions."

The popularity of ChatGPT has driven the development of artificial intelligence, cloud computing, and other technologies, posing higher challenges for the data processing capabilities of servers and accelerating the deployment of high-performance computing centers such as AI computing power. As the core production force in data centers, computational power has gradually become a new focus of global strategic competition as data centers, including those in China, are experiencing a new peak in construction. With the full launch of the "Eastern Data, Western Computing" project, the computing industry is playing an increasingly prominent role in China's economy, society, and industrial development.

As data centers enter a development boom, the future applications and trends of artificial intelligence in data centers will be particularly prominent. Artificial intelligence revitalizes data centers by improving operational efficiency, performance, and security. Data centers can benefit in various ways by integrating artificial intelligence into their organization and operations. In this context, Dong Yexing discussed the AI Private Deployment Solutions during the conference.

In response to the wave of large-scale models triggered by ChatGPT, Gooxi proposed that AI large-scale model training can significantly reduce the scale of the required computing environment through technical optimization. The threshold for training configurations that originally required hundreds of A100 GPU servers is lowered, allowing ordinary enterprises to build private AI training platforms tailored to their own businesses. Gooxi provides the underlying hardware performance support for data platform loads with powerful computational servers and collaborates with software platforms to provide basic operating environments for all AI needs, such as job scheduling, monitoring, compilation environments, mathematical libraries, etc. Lightweight project operations ensure the feasibility of deploying private AI training platforms on a small scale, effectively improving the utilization of computational resources while reducing costs. In addition, Gooxi accepts on-demand customization, making it more adaptable to the internal business needs of enterprises and allowing for flexible scalability that aligns with business development.

For Gooxi, which has been deeply rooted in the data center field for over a decade, it has rich experience in server industry customization and operation management. Gooxi servers have been highly recognized and appreciated by leading internet giants, and their equipment has been deployed in the data centers of these major companies. In terms of operation and maintenance management, Gooxi pioneered the One OPS operation and maintenance system in the industry, which is designed for the operation and maintenance management of a large number of server clusters. It provides comprehensive operation and maintenance solutions, easily integrating servers into existing management architectures, reducing TCO maintenance costs, and ensuring high levels of security and stability in data centers. Additionally, for the management of physical servers, Gooxi has introduced a bare metal cloud solution that allows for the division and management of server computational power and storage based on demand. This solution enables unified planning and convenient management of servers, effectively improving server utilization efficiency.