The article examines how AI performance optimization begins with infrastructure planning and data management processes that occur before GPU deployment in data centers. The piece suggests that factors such as data preparation, network architecture, and system design significantly impact overall AI workload efficiency, challenging the common perception that performance gains are primarily determined by GPU capabilities alone.