Trump Administration Encourages Chipmakers to Build US Foundries: To decrease reliance on chipmakers in Asia, the Trump administration is encouraging Intel to build a state-of-the-art foundry in the United States, the Wall Street Journal reported. Foundries manufacture chips for third-party chip designers and governments, and many U.S. companies currently rely on foundries in Taiwan and South Korea. A domestic Intel foundry would ensure cutting-edge indigenous chip production capabilities for American chip designers and the DOD. Officials also are encouraging Taiwan Semiconductor Manufacturing Company and South Korea’s Samsung Electronics to develop state-of-the-art foundries in the United States.
Huawei Partners with Chipmakers in Preparation for US Export Controls: In anticipation of potential U.S. export controls on chips produced by Taiwan Semiconductor Manufacturing Company, Huawei is reportedly shifting some chip production toward Chinese chipmaker Semiconductor Manufacturing International Corporation and partnering with French-Italian chipmaker STMicroelectronics. A partnership with SMIC could provide Huawei with alternative chip production options if the United States blocks exports from TSMC. ST will co-design chips with Huawei, as entity list restrictions limit Huawei's access to updated software used to design chips. It remains unclear how much of Huawei’s chip production is moving to new partners.
Research Suggests Algorithmic Efficiency Is Rapidly Increasing: Researchers at OpenAI have found that algorithmic efficiency grew more quickly than Moore’s Law-driven hardware efficiency from 2012 to 2019. According to their preprint, training a neural net to a benchmark of ImageNet classification takes 44 times less computational power now than it did eight years ago. By comparison, Moore’s Law would yield only an 11-fold improvement in hardware efficiency over the same period. Policymakers should invest in measurement and assessment of AI systems to more accurately predict future changes in AI system costs, the researchers said. They are tracking the efficiency of state-of-the-art neural nets over time and calling for submissions of relevant data.
Machine Learning Spotlight — Limitations of AI COVID-19 Diagnostic Tools: Preliminary research suggests that most models using AI for COVID-19 diagnosis and prognosis are at high risk of bias and likely misleading. The researchers reviewed 31 models that use AI for online diagnosis, diagnosis based on CT scans and case prognosis prediction. According to their assessment, the reported performance of all 31 models was “probably optimistic.” Given the lack of external validation of most models, the authors recommend against relying on any current AI-based COVID-19 diagnostic tools.
House Republicans Plan to Introduce Emerging Tech Legislative Package: On Tuesday, House Energy and Commerce Committee Republicans led by Ranking Member Walden and Consumer Protection and Commerce Subcommittee Ranking Member McMorris Rodgers previewed a 15-bill package aimed at bolstering the development of emerging technologies, such as AI, blockchain, quantum computing and autonomous vehicles. The central proposal requires the Commerce Department to study barriers to AI deployment, with the goal of reducing bureaucratic hurdles and “unleashing” private sector innovation. Other bills direct Commerce and the Federal Trade Commission to study facial recognition, and task the FTC with assessing how AI can assist in the fight against online misinformation and terrorist content. The package currently has only Republican backing.
NSCAI Co-Authors Letter on National Security Workforce: The National Security Commission on AI, the Cyberspace Solarium Commission and the National Commission on Military, National, and Public Service wrote to Senate and House Armed Services Committee leadership, encouraging them to take action on defense and national security workforce recommendations in the Fiscal Year 2021 National Defense Authorization Act. The letter recommends streamlining hiring processes and recruiting pathways, as well as increasing awareness of opportunities for digital talent to enter public service.
In Translation CSET's translations of significant foreign language documents on AI
CSC Scholarship Study Abroad Agreement:China Scholarship Council Subsidized Study Abroad Agreement. This document is the text of an agreement between Chinese students who study abroad and the PRC Ministry of Education’s China Scholarship Council. It requires students on CSC scholarships to report regularly on the progress of their studies and mandates that those who study abroad return to China for at least two years after completing their studies overseas.
AI Standardization White Paper:Artificial Intelligence Standardization White Paper. This government-issued white paper describes China’s approach to standards setting for AI. Appendices list all of China’s existing AI standards as of January 2018, as well as those under study, and provide examples of AI applications by leading Chinese tech companies.