Hardware and compute

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.

Key Concepts in AI Safety: An Overview

Tim G. J. Rudner Helen Toner
| March 2021

This paper is the first 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. In it, the authors introduce three categories of AI safety issues: problems of robustness, assurance, and specification. Other papers in this series elaborate on these and further key concepts.

Stealth technology was one of the most decisive developments in military aviation in the last 50 years. With U.S. technological leadership now under challenge, especially from China, this issue brief derives several lessons from the history of Stealth to guide current policymakers. The example of Stealth shows how the United States produced one critical technology in the past and how it might produce others today.

Congress preps for long campaign against Chinese chips

National Journal
| March 11, 2021

Research Analyst Will Hunt discusses the flurry of activity in Congress and elsewhere to address lagging U.S. semiconductor manufacturing capacity.