By Lorenzo Ghioni,
Publication Date: 2026-03-12 15:00:00
Distributed AI workloads are putting enormous demands on networking infrastructure. As AI models grow in complexity and size, the physical and power limitations of single data centers are pushing operators to adopt scale-across architectures—interconnecting multiple data centers for massive AI training and inferencing. Power efficiency, reliability, and scalability are now deeply important, and optical innovation lies at the heart of achieving these goals.
Expanding fiber capacity to meet distributed AI requirements
One way to address the necessary capacity growth is by lighting multiple fiber pairs in parallel with multi-rail open line systems which can handle multiple bands and transmission systems in parallel.
While using existing line systems in legacy amplification huts limits the maximum achievable capacity due to power constraints, multi-rail open line systems enable the use of several parallel fiber pairs, which significantly increase capacity and power efficiency….

