FM Care AI Model Officially Launched

The explosive growth in demand for AI technologies such as large models has led to a gradual spillover of demand for data centers and computing power among large enterprises. However, to connect with their existing information systems and enhance data security, these enterprises have put forward higher requirements for hybrid systems than traditional Service Level Agreements (SLAs). In response to the challenges faced by clients, Aurora Cloud helps them achieve improvements in key parameters such as stability and system robustness, meeting the clients’ specified requirements. It not only provides clients with a comprehensive and efficient technical support solution but also realizes in-depth collaboration with them, ensuring the smooth operation of every critical link—from model construction and cross-network data transmission to high-concurrency business processing—effectively helping clients shorten project cycles.

Aurora Cloud leverages its self-developed Computing Power Connect Platform to enable clients to use the service out of the box, managing the entire infrastructure from storage to computing. Additionally, through its self-developed scheduling engine, it improves the overall work efficiency of the project team’s developers, effectively ensuring the implementation and delivery of scientific research projects. By deploying high-performance GPU servers and optimizing the system in an all-round manner, it significantly enhances computing power efficiency and system stability. By providing hybrid computing power resources and comprehensive supporting technical support services, Aurora Cloud assists members of each client’s project team in completing project objectives on time, in quantity, and with ultra-high quality, far exceeding the clients’ project expectations.

With the deepening of scientific and technological research, the demand for GPU performance in an innovative research project at a university has surged.

Deepening of scientific and technological research, the demand for GPU performance in an innovative research project at a university has surged. Complex scientific research projects and massive datasets have pushed computing power to its limits, requiring efficient and stable services. The client’s in-house data center resources are limited, and GPU computing power has become a bottleneck to breakthroughs in the research project. Moreover, the actual needs of different departments in the university are not uniform, with significant gaps in their hardware and software requirements for computing power. In previous years, teachers from each department purchased computing power services independently and had to seek external computing power resources to complete their research objectives on time.

The explosive growth in demand for AI technologies such as large models has led to a gradual spillover of demand for data centers and computing power among large enterprises. However, to connect with their existing information systems and enhance data security, these enterprises have put forward higher requirements for hybrid systems than traditional Service Level Agreements (SLAs). In response to the challenges faced by clients, Aurora Cloud helps them achieve improvements in key parameters such as stability and system robustness, meeting the clients’ specified requirements. It not only provides clients with a comprehensive and efficient technical support solution but.