Bandwidth Scaling for AI Interconnect - More Wavelengths versusMore Fiber?

With AI model size doubling every four months, the size of AI compute clusters is growing rapidly to keep up. Traditional data center front-end networks rely on optical interconnect for data movement with Terabits per second of connectivity and have been doubling data rate every 4 years. As the models grow it is also expected that the back-end GPU networks expand beyond the confines of the rack. Optical interconnects will be needed at distances of tens of meters with 10Tb/s data transfer rates and doubling every 2 years will be expected. How should optical interconnects best achieve this bandwidth increase and what is the best performance axis to push next? In this panel discussion we pose the question - “Is it better to scale with more wavelengths or by adding more fibers?” Join us to see if any of the panelists can convince you they have the right approach.