christophe fouquet

AI demand has accelerated transistor density scaling from the traditional 2x every two years to 16x every two years, requiring EUV lithography, high-bandwidth memory, and continued innovation across the semiconductor value chain for at least 20 more years.

China lacks access to EUV lithography, putting it at least 10-15 years behind in advanced logic manufacturing. Without EUV, economically viable volume production at advanced nodes is impossible, creating a structural geopolitical divide in semiconductor capability.

HBM is a key enabler for AI performance, requiring major innovation in memory technology alongside logic scaling to meet the 16x compute demand growth from AI.

Hyperscalers are developing their own AI-optimized chips, moving beyond generic GPUs. Both logic and memory will see major design changes specifically for AI workloads, reshaping the semiconductor roadmap.

Government subsidies (CHIPS Acts) can jumpstart manufacturing but cannot guarantee long-term success unless countries achieve structural cost and flexibility competitiveness. R&D history and ecosystem depth are prerequisites for advanced node manufacturing.

The 16x compute demand growth from AI faces fundamental cost and energy consumption constraints, requiring major innovation in chip architecture, lithography, and memory to improve performance per watt.