Wednesday, September 18, 2019

Worth Knowing

Study finds flow of AI professors to industry discourages innovation: New research from the University of Rochester shows that after AI professors leave academia for private-sector work, fewer of their students start AI companies. The study, first covered by The New York Times, found that about 10 times as many North American professors left for tech companies in 2018 as did in 2009. The researchers say this trend could eventually hamper AI innovation and the economy.
Preview of Russia’s AI strategy: President Vladimir Putin is reviewing a draft AI strategy that he ordered state-owned Sberbank to prepare, according to DefenseOne. The wide-ranging document covers fundamental investments in AI — including funding for research, ethical and data regulations, and hardware and software developments — as well as specific applications of AI in healthcare and education. The final version is expected next month.
Record number of submitted papers for NeurIPS: The Conference on Neural Information Processing Systems received 6,743 paper submissions this year — up 39% from last year, and double the number of submissions in 2017. Google, MIT and Stanford were the most common institutional affiliations across accepted papers. Since NeurIPS is the largest annual AI conference, its metrics are often used as indicators of continued growth and enthusiasm in the field of machine learning.
Partnership on AI calls for improving immigration policies that affect AI experts: The Partnership on AI, which connects major tech companies with government and NGOs to create collaborative proposals, released a report last week calling for increasing access to visas and other immigration benefits for global AI/ML experts. The report lays out policy recommendations including streamlined visa reviews for highly skilled individuals, AI/ML visa classifications and visa categories for AI/ML students and interns.
Government Updates

White House requests $1B in non-defense AI spending in 2020: The Trump administration submitted a supplemental request for $973.5 million in non-defense AI R&D spending for fiscal year 2020. While this number is higher than previous years, some industry leaders say it’s not enough. Looking ahead, a White House memo listed AI as a priority for the 2021 R&D budget.

Senate Defense Appropriations bill boosts defense funding for AI: The Senate Appropriations Committee approved its 2020 Defense Appropriations bill, which now awaits Senate consideration. The bill supports the President’s budget request for the Joint Artificial Intelligence Center at $208.8 million. In addition, it provides $83.5 million above the President’s budget on accounts labeled for AI-related Research, Development, Test and Evaluation.

White House holds AI Summit: On September 9th, the White House held The Summit on AI in Government for 175 industry, government and academic experts in AI. The event concluded with three case studies of AI use to improve government operations.

Air Force releases 2019 AI Strategy: On September 12th, the Air Force released its Annex to the DoD AI Strategy issued in 2018. The Annex aligns USAF strategy with that of DoD and focuses on expanding access to AI, preparing an AI workforce and treating data as a strategic asset.

What We’re Reading

Attacking Artificial Intelligence: AI’s Security Vulnerability and What Policymakers Can Do About It, Belfer Center for Science and International Affairs, Harvard Kennedy School (August 2019)

A Tentative Framework for Examining U.S. and Chinese Expenditures for Research and Development on Artificial Intelligence, The Institute for Defense Analyses Science & Technology Policy Institute (September 2019)

In Translation
CSET's translations of significant foreign language documents on AI

Open-Source AI development platforms: Guidance on National New Generation Artificial Intelligence Open Innovation Platform Construction Work: Chinese Ministry of Science and Technology document describing the updated approval process for Chinese AI tech companies’ “open innovation platforms.” This document builds on the 2017 AI Development Plan, which identified open-source platforms as crucial to making China the world leader in AI by 2030.

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