The CHIPS team's primary goal was securing a commitment for three TSMC fabs, viewing it as a strategic tipping point. They believed the operational scale of a three-fab cluster would make building a fourth, fifth, and sixth a near certainty, creating a self-sustaining 'mega fab' without requiring subsidies for later expansions.
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The first draft of the CHIPS Program Office's guiding "Vision for Success" paper was a historical analysis of how the U.S. lost its semiconductor manufacturing edge. This diagnostic approach was replaced with a forward-looking, target-setting document to be more practical and less academic for stakeholders.
While AI model providers may overstate demand, the most telling signal comes from TSMC. Their decision to significantly increase capital expenditure on new fabs, a multi-year and irreversible commitment, indicates a strong, cynical belief in the long-term reality of AI compute demand.
While TSMC's Arizona expansion has been complex, it's already achieving yields comparable to its Taiwan facilities. An expert believes this success comes at a price, with higher costs likely being a permanent feature of US-based manufacturing.
Lacking formal demand-side tools like government purchase guarantees, the CHIPS Act team relied on persuasion and strategic influence—the 'bully pulpit.' They actively engaged major customers like Apple and Nvidia to signal demand for new US-based fabs, creating market confidence through informal channels.
While energy supply is a concern, the primary constraint for the AI buildout may be semiconductor fabrication. TSMC, the leading manufacturer, is hesitant to build new fabs to meet the massive demand from hyperscalers, creating a significant bottleneck that could slow down the entire industry.
The 2022 CHIPS Act was passed months before ChatGPT's launch. The subsequent AI-driven demand for semiconductors was not the primary driver for the legislation. The Act's incentives accelerated US manufacturing capacity, luckily positioning the nation to capitalize on an unanticipated boom.
Despite soaring AI demand, chip fab TSMC is conservatively expanding capacity. This is a rational move to avoid the catastrophic downside of overcapacity, where fixed costs sink profitability for years. However, this decision is creating a massive, predictable chip shortage for the AI industry.
Taiwan's TSMC dominates advanced chip manufacturing not only through technical excellence but also its business model. By acting as a pure-play foundry that doesn't compete with its clients (unlike Intel or Samsung), it fostered unique trust and partnerships, making it the central hub of the semiconductor ecosystem and a critical geopolitical asset.
Despite record capital spending, TSMC's new facilities won't alleviate current AI chip supply constraints. This massive investment is for future demand (2027-2028 and beyond), forcing the company to optimize existing factories for short-term needs, highlighting the industry's long lead times.
Ben Thompson argues that while investing in unproven fabs from Intel or Samsung seems risky, the greater risk is the entire AI industry being constrained by TSMC's singular capacity. The future opportunity cost of foregone revenue from this bottleneck far outweighs the expense of building up viable competitors.
