Huang explains that extreme co-design across CPU, GPU, networking and switching is necessary because AI workloads no longer fit in one computer and Moore's Law has slowed.
And so distributed computing at the scale that we do, the CPU is a problem, the GPU is a problem, the networking is a problem, the switching is a problem. And distributing the workload across all these computers is a problem. It's just a massively complex computer science problem. And so we just gotta bring every technology to bear.