Artificial Intelligence is often framed as a revolution, a radical departure from traditional computing paradigms. But in many ways, it's more of a reincarnation: a re-manifestation of the decades-long discipline of High-Performance Computing (HPC). As AI workloads, especially large-scale training and inference for foundation models, stretch hardware and software infrastructure to their limits, they increasingly resemble classic HPC workloads. The twist? They arrive at old problems from new directions, often without the rich latency-tolerant ecosystem HPC has painstakingly built.