2026 Agenda

For two decades, AI infrastructure has been built on the assumption that memory is cheap and plentiful. That era is over. HBM is sold out through 2026, supply constraints are projected to persist into late 2027, and AI workloads are on track to consume up to 70% of global memory production next year. Meanwhile, inference economics increasingly define competitive advantage, and memory has quietly become the binding constraint. The path forward isn't outbidding hyperscalers for capacity that doesn't exist. It's smarter architecture. This keynote makes the case that software-defined memory is the missing layer in modern AI infrastructure: the difference between operating through scarcity and being limited by it. We'll cover why server-bound memory caps utilization at 30–40%, what becomes possible when memory is pooled and dynamically allocated across the data center, and why the organizations adapting now are quietly pulling ahead while their competitors negotiate with suppliers.