The Bottleneck Isn’t the Chip with Bubble boi | EP 166

AI hardware evolution is shifting from traditional transistor scaling to system-level optimization and advanced packaging. As lithography costs render Moore's Law economically unsustainable, packaging technologies like EMIB have become the primary driver for increasing transistor density. Memory architecture remains the critical bottleneck, with the industry transitioning from a focus on raw compute throughput to managing massive context windows through smarter memory hierarchies, including the potential integration of high-bandwidth Flash. Successful AI infrastructure now requires co-designing chips, interconnects, and memory controllers to serve concurrent users efficiently. Ultimately, the most sustainable value in the AI ecosystem resides in the hardware layer—the foundational "railroads" of the industry—rather than in the highly competitive and volatile AI model labs. This strategic focus on hardware, memory locality, and system-level efficiency will define the next generation of AI performance and economic viability.