What's always seen in AI development is： 1） Models improve through reinforcement learning and algorithmic breakthroughs. 2） Better chips allow for training larger models and more efficient inference.

However， what's often overlooked is the massive scaling of chip production facilities. This means that not only are better models being trained and better chips developed， but production capacity is being expanded at an unprecedented scale to meet the exponentially growing demand for advanced AI silicon.

TSMC is building up to 10 fabs simultaneously in Taiwan while expanding to 12 fabs in Arizona， backed by $52-56 billion in 2026 CapEx alone， a 30% year-over-year jump. Total U.S. investment has reached $165 billion， making it the largest foreign direct investment in American history.

This isn't about producing more chips in volume， it's about scaling compute density at the 2nm and below frontier， where every new node costs exponentially more per wafer but delivers the transistor budgets AI infrastructure demands.