The biggest risks are (1) geopolitical/export shocks (especially China) that change demand/mix overnight, (2)
hyperscaler substitution and pricing leverage as workloads shift from training to cost-optimized inference, and (3) physical bottlenecks (power, cooling,
advanced packaging/
HBM) that can turn demand into delayed revenue and reputation risk.