Each of these machines is far more complex and PCB-intensive than traditional servers, from massive 22-layer any-layer HDI motherboards to accelerator card carriers packed with GPUs and high-bandwidth memory (HBM), containing between $1,000–$2,000 worth of PCBs in a single. Each of these machines is far more complex and PCB-intensive than traditional servers, from massive 22-layer any-layer HDI motherboards to accelerator card carriers packed with GPUs and high-bandwidth memory (HBM), containing between $1,000–$2,000 worth of PCBs in a single. Rising power densities and new architectures are forcing a rethinking of interconnects, materials, and thermal management. As artificial intelligence (AI) workloads grow larger and more complex, the various processing elements being developed to process all that data are demanding unprecedented. The ability to manufacture AI servers and racks at scale has become a critical bottleneck in meeting the surge of data center investment. As more enterprises deploy AI models and AI-powered devices, the risk of supply chain bottlenecks grows. Without strategic investments in expanding. AI is rewriting the hardware playbook, marrying complex software and algorithms to run and improve machine and equipment operations. Sorting through, managing, and utilizing massive amounts of data takes tremendous data storage and processing power.