Challenges in Computing Power Centers

1. High Capital Investment Traditional cloud computing data centers and existing AI-powered data centers face significant challenges due to high capital investment methods. These issues include:High operating costs、

   Centralized deployment leading to high latency、Low utilization efficiency due to single-point architecture、Higher risk of failures.

   These challenges limit the ability of traditional computing power centers to cater to a broader range of customers, making them suitable only for government entities, research institutions, and top-tier enterprises.

2. Power Consumption Challenges A single NVIDIA H100 server consumes 6 kW of power, and an 8-card NVIDIA 4090 server consumes 3 kW. As deployment scales, total electrical power consumption becomes significant. In 2024, global electricity generation was 300 trillion kWh, with AI computing consuming 2 trillion kWh of that total. By 2030, global electricity generation is expected to reach 400 trillion kWh, with AI computing consuming 35 trillion kWh of that total.

3. Green Renewable Energy With the growing demand for low-power consumption, environmentally friendly green renewable energy solutions are becoming increasingly urgent and necessary. Implementing a green energy supply at the AI edge will significantly alleviate the energy supply issues caused by traditional IDC data centers.

4. Security Risks Centralized IDC data centers store user data and privacy in a single location due to their centralized network architecture. As a result, the associated security risks are more difficult to mitigate.