Wedoany.com Report on Feb 26th, Network equipment provider Rad has introduced a new interconnect solution, ETX-2i-400G, designed to support efficient data transmission between data centers, entering the cross-scale AI race. This Ethernet-based product enables high throughput and low latency, suitable for moving large datasets between facilities.
The ETX-2i-400G is equipped with multiple 400 Gb/s quad small form-factor pluggable "double density" interfaces. These ports leverage high-speed electrical lanes to deliver high-capacity throughput and are compatible with legacy QSFP modules. This design facilitates cross-scale connectivity for data centers, meeting the demands of AI projects for large-scale data processing.
As industry demand for AI infrastructure grows, the concept of cross-scale is gaining traction. This philosophy emphasizes expanding capacity and connectivity across different locations, rather than building large, centralized sites, to collaboratively handle workloads. JLL predicts that the shift of AI workloads from training to inference over the next five years will drive the development of distributed edge and regional computing centers.
Hyperscalers like Amazon Web Services and Microsoft have already adopted distributed infrastructure, and Rad's launch aims to extend this concept to more participants. The ETX-2i-400G is described as an ideal choice for communications service providers, supporting high-capacity, low-latency services while enhancing security through quantum key distribution and post-quantum cryptography frameworks.
Eli Angel, Vice President of Products and Marketing at Rad, stated: "Training AI models requires moving massive datasets between data centers quickly and efficiently to ensure expensive GPU resources are never idle. This is precisely where our new solution comes in, enabling cost-effective and secure transmission of large data flows between data centers." This solution is expected to promote the adoption of cross-scale data center connectivity and support the advancement of AI technology.
