Trump Administration Killed $1.1 Billion Chip Packaging Center as TSMC Tightens A.I. Bottleneck
Updated
Updated · The New York Times · Jun 26
Trump Administration Killed $1.1 Billion Chip Packaging Center as TSMC Tightens A.I. Bottleneck
1 articles · Updated · The New York Times · Jun 26
Summary
$1.1 billion in Biden-era funding for an advanced chip packaging R&D center in Arizona was effectively scrapped by the Trump administration last year, according to the report.
Advanced packaging has become critical because gains from shrinking transistors have faded, pushing Nvidia and other A.I. chipmakers to rely on tightly bundled modules for more powerful systems.
TSMC now packages nearly all leading A.I. chips it manufactures, and its Taiwan-based supplier network has become a bottleneck as demand outstrips capacity.
Subramanian Iyer, a UCLA professor and former IBM technologist who helped design the center, said canceling it left the U.S. even more dependent on TSMC in a strategically exposed part of the chip supply chain.
As TSMC faces surging demand, can Intel seize this moment to reclaim its leadership in the critical AI packaging race?
Can U.S. efforts truly break Taiwan's dominance in chip packaging, or is it too late for America to catch up?
Is advanced packaging the final frontier for computing power, or is another breakthrough on the horizon for AI hardware?
The 2026 AI Chip Packaging Bottleneck: How U.S. Setbacks and TSMC’s Dominance Threaten Global AI Progress
Overview
The U.S. faced a major setback in its semiconductor strategy when the Department of Commerce revoked a $7.4 billion grant, leading to the cancellation of a $1.1 billion advanced chip packaging project at Arizona State University. This decision, now under legal scrutiny by Arizona’s Attorney General, comes as the global AI industry is hit by a severe chip packaging bottleneck, especially around TSMC’s CoWoS technology. Following the launch of ChatGPT, the industry has struggled with packaging and power constraints, fueling a recognized silicon shortage and soaring demand for AI applications, which further highlights the risks of U.S. reliance on overseas capabilities.