The 2026 AI Infrastructure Summit, held September 15–17 in Santa Clara, California, drew approximately 6,000 attendees—double last year's turnout—and brought together Micron, Samsung, SK Hynix, Broadcom, Marvell, Intel, Qualcomm, OpenAI, AWS, and Google, who reached a strong consensus on disaggregating memory and storage hierarchies as the most viable path to breaking through the "memory wall" bottleneck constraining AI compute. The industry's evaluation framework is shifting from raw compute (FLOPs) toward efficiency metrics such as tokens per watt and tokens per dollar. Qualcomm showcased its HBC (High-Bandwidth Compute) approach, stacking LPDDR directly on compute dies, while SK Hynix introduced specialized memory tiers including PIM (Processing-in-Memory) and HBF (High-Bandwidth Flash). Broadcom is pushing Ethernet across all tiers with open architectures, while Marvell and Astera Labs are positioning customized interconnect solutions. AWS demonstrated how co-locating test capacity with deployment sites compressed post-silicon validation cycles from 6–9 months to a fraction of that time. Bank of America Securities noted the trend is reshaping the semiconductor investment landscape. Data shows Transformer model sizes have grown roughly 240x every two years, while memory bandwidth and capacity have only grown about 2x over the same period.