Hardware and compute

The Huawei Moment

Alex Rubin Alan Omar Loera Martinez Jake Dow Anna Puglisi
| July 2021

For the first time, a Chinese company—Huawei—is set to lead the global transition from one key national security infrastructure technology to the next. How did Washington, at the beginning of the twenty-first century, fail to protect U.S. firms in this strategic technology and allow a geopolitical competitor to take a leadership position in a national security relevant critical infrastructure such as telecommunications? This policy brief highlights the characteristics of 5G development that China leveraged, exploited, and supported to take the lead in this key technology. The Huawei case study is in some ways the canary in the coal mine for emerging technologies and an illustration of what can happen to U.S. competitiveness when China’s companies do not have to base decisions on market forces.

National Power After AI

Matthew Daniels Ben Chang
| July 2021

AI technologies will likely alter great power competitions in foundational ways, changing both how nations create power and their motives for wielding it against one another. This paper is a first step toward thinking more expansively about AI & national power and seeking pragmatic insights for long-term U.S. competition with authoritarian governments.

CSET Research Analyst Will Hunt calls for the U.S. government to invest in domestic fabrication for chip manufacturing as a result of the current ship shortage.

CSET Research Analyst Will Hunt discusses the lengthy process of building semiconductor fabrication plants as US companies like Intel race to maintain global chip leadership.

CSET Research Fellow Saif Kahn praises Intel's chip manufacturing to build up the United States' competitiveness in the semiconductor supply chain industry.

CSET partnered with the National Security Commission on Artificial Intelligence to discuss the findings and recommendations of the commissions final report, released in early March.

China’s Progress in Semiconductor Manufacturing Equipment

Will Hunt Saif M. Khan Dahlia Peterson
| March 2021

To reduce its dependence on the United States and its allies for semiconductors, China is building domestic semiconductor manufacturing facilities by importing U.S., Japanese, and Dutch semiconductor manufacturing equipment. In the longer term, it also hopes to indigenize this equipment to replace imports. U.S. and allied policy responses to China’s efforts will significantly affect its prospects for success in this challenging task.

CSET Research Fellow Saif M. Khan testified before the Senate Foreign Relations Committee for its hearing, "Advancing Effective U.S. Policy for Strategic Competition with China in the Twenty-First Century." Khan spoke to the importance of U.S. leadership in semiconductor and artificial intelligence technology.

Key Concepts in AI Safety: Interpretability in Machine Learning

Tim G. J. Rudner Helen Toner
| March 2021

This paper is the third installment in a series on “AI safety,” an area of machine learning research that aims to identify causes of unintended behavior in machine learning systems and develop tools to ensure these systems work safely and reliably. The first paper in the series, “Key Concepts in AI Safety: An Overview,” described three categories of AI safety issues: problems of robustness, assurance, and specification. This paper introduces interpretability as a means to enable assurance in modern machine learning systems.

Key Concepts in AI Safety: Robustness and Adversarial Examples

Tim G. J. Rudner Helen Toner
| March 2021

This paper is the second installment in a series on “AI safety,” an area of machine learning research that aims to identify causes of unintended behavior in machine learning systems and develop tools to ensure these systems work safely and reliably. The first paper in the series, “Key Concepts in AI Safety: An Overview,” described three categories of AI safety issues: problems of robustness, assurance, and specification. This paper introduces adversarial examples, a major challenge to robustness in modern machine learning systems.