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The White House today detailed the establishment of 12 new research institutes focused on AI and quantum information science. Agencies including the National Science Foundation (NSF), U.S. Department of Homeland Security, and U.S. Department of Energy (DOE) have committed to investing tens of millions of dollars in centers intended to serve as nodes for AI and quantum computing study.

Laments over the AI talent shortage in the U.S. have become a familiar refrain. While higher education enrollment in AI-relevant fields like computer science has risen rapidly in recent years, few colleges have been able to meet student demand due to a lack of staffing. In June, the Trump administration imposed a ban on U.S. entry for workers on certain visas — including for high-skilled H-1B visa holders, an estimated 35% of whom have an AI-related degree — through the end of the year. And Trump has toyed with the idea of suspending the Optional Practical Training program, which allows international students to work for up to three years in the U.S. after they graduate.

This week’s announcement might be perceived as an effort to shift attention from immigration toward domestic progress. However, $1 billion falls on the conservative side of the AI investment spectrum. When U.S. CTO Michael Kratsios revealed last September that U.S. government agencies requested nearly $1 billion in nondefense AI research spending for the fiscal year ending in September 2020, representatives from Intel, Nvidia, and IEEE said the U.S. would need to set aside more for AI R&D. Separately, national security think tank Center for a New American Security called for federal spending on high-risk/high-reward AI research to increase to $25 billion by 2025 to avoid “brain drain,” and the Stanford Institute for Human-Centered Artificial Intelligence asserts the government must spend $120 billion within the decade on AI research and education and the national AI ecosystem.

AI institutes

According to the Trump administration, over the next five years the NSF will partner with the U.S. Department of Agriculture’s (USDA) National Institute of Food and Agriculture, the U.S. Department of Homeland Security’s Science and Technology Directorate, and the U.S. Department of Transportation’s Federal Highway Administration to invest $100 million across five AI institutes. Separately, the USDA will support two of its own institutes with $40 million in grants.


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The Trump administration claims the institutes bring together more than a hundred entities, including companies like John Deere, which will seek to further develop and apply the research. The institutes are:

  • The NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography, led by a team at the University of Oklahoma. The Trump Administration says the institute will offer AI certificate programs and recruit atmospheric science, ocean science, and risk communication researchers to develop “user-driven trustworthy AI” targeting weather, climate, and coastal hazards applications.
  • The NSF AI Institute for Foundations of Machine Learning, led by a team at the University of Texas. In collaboration with “large industrial tech companies” and the city of Austin, the institute will purportedly investigate theoretical AI challenges like neural architecture optimization. Beyond this, it will offer “major” online coursework and tools for students and researchers.
  • NSF AI Institute for Student-AI Teaming, led by a team at the University of Colorado, Boulder. The Trump administration says the institute will focus on developing AI that helps students and teachers leverage modalities like speech, gestures, gaze, and facial expression in real-world classrooms and remote learning settings.
  • NSF AI Institute for Molecular Discovery, Synthetic Strategy, and Manufacturing (the NSF Molecule Maker Lab), led by a team at the University of Illinois at Urbana-Champaign. The institute will develop AI tools to accelerate chemical synthesis and the discovery and manufacture of materials and compounds, according to the Trump administration.
  • NSF AI Institute for Artificial Intelligence and Fundamental Interactions, led by a team at the Massachusetts Institute of Technology. The Trump administration says the institute will incorporate workforce development, digital learning, outreach, and knowledge transfer programs to develop AI that integrates the laws of physics.
  • USDA-NIFA AI Institute for Next Generation Food Systems, led by a team at the University of California, Davis. The Trump administration says the institute will take a “holistic view” of the food system with AI and bioinformatics to understand biological data and processes, addressing issues like molecular breeding to optimize traits for yield, crop quality, pest and disease resistance, agricultural production, food processing and distribution, and nutrition.
  • USDA-NIFA AI Institute for Future Agricultural Resilience, Management and Sustainability, led by another team at the University of Illinois at Urbana-Champaign. The institute will advance AI research in computer vision, machine learning, soft object manipulation, and human-robot interaction to solve agricultural challenges, including labor shortages, efficiency and welfare in animal agriculture, environmental resilience of crops, and the need to safeguard soil health. The Trump administration says it will feature a joint computer science and agriculture degree and a clearinghouse to foster collaboration.

Quantum centers

Beyond the NSF’s investments, the DOE will award $625 million to create five quantum information science research centers. Of the total, the Trump administration says $300 million will come from industry and academic institutions, with the remainder drawn from $1.2 billion earmarked in a 2018 law — the National Quantum Initiative Act — for quantum research.

The Trump administration says a coalition of 69 national labs, universities, and companies was selected in a two-step vetting process to collaborate within centers across 22 U.S. states, Italy, and Canada. Among the participants are the University of Chicago, Harvard, Cornell, IBM, Intel, Lockheed Martin, and Microsoft. According to DOE Under Secretary for Science Paul Dabbar, IBM will contribute runtime on its quantum computers; Microsoft will contribute personnel, as well as materials; and the state of Illinois will construct two buildings to house laboratories for quantum research.

The Trump administration shared the following details about the centers:

  • Next Generation Quantum Science and Engineering Center (Q-NEXT), led by the Argonne National Laboratory. Q-NEXT will deliver quantum interconnects, establish national foundries, and demonstrate communication links, networks of sensors, and simulation testbeds. Other lofty goals include building a quantum devices database and providing pathways to the commercialization of quantum technology.
  • Co-design Center for Quantum Advantage (C²QA), led by Brookhaven National Laboratory. C²QA will aim to overcome the limitations of current quantum systems to achieve “quantum advantage” for scientific applications in high-energy, nuclear, chemical, and condensed matter physics. It has a five-year goal to deliver a “factor of 10” improvement in software optimization, underlying materials and device properties, and quantum error correction.
  • Superconducting Quantum Materials and Systems Center (SQMS), led by Fermi National Accelerator Laboratory. SQMS will purportedly target “transformational” advances toward the challenge of eliminating the decoherence mechanisms in superconducting devices. Its ambitious goal is to enable deployment of superior quantum systems through unique foundry capabilities and quantum testbeds for materials, physics, algorithms, and simulations.
  • Quantum Systems Accelerator Center (QSA), led by Lawrence Berkeley National Laboratory. The QSA will codesign algorithms, quantum devices, and engineering solutions ostensibly required to achieve quantum superiority in applications like neutral atoms, trapped ions, and superconducting circuits.
  • The Quantum Science Center (QSC), led by Oak Ridge National Laboratory. The QSC will seek to overcome roadblocks in quantum state resilience, controllability, and scalability.

During a briefing with members of the press on Tuesday, Kratsios at one point suggested “adversaries” are pursuing uses of AI and quantum technologies that “aren’t in alignment with American values.” He referred to the White House’s recently released proposal for a quantum internet, saying: “One of the key overarching thoughts around why American leadership, in particular [in] technologies, is so critical is that we ensure the next great technological breakthroughs are made by America and our allies.”

But U.S. superiority in AI and quantum computing is an increasingly dim prospect. The EU Commission has committed to increasing investment in AI from $565 million (€500 million) in 2017 to $1.69 billion (€1.5 billion) by the end of 2020. France recently took the wraps off a $1.69 billion (€1.5 billion) initiative aimed at transforming the country into a “global leader” in AI research and training. And in 2018, South Korea unveiled a multiyear, $1.95 billion (KRW 2.2 trillion) effort to strengthen its R&D in AI, with the goal of establishing six AI-focused graduate schools by 2022 and training 5,000 AI specialists.

Europe overtook the world in scholarly output related to AI last year, according to a report by Elsevier. China, whose AI Innovation Action Plan for Colleges and Universities called for the establishment of 50 new AI institutions by 2020, is expected to leapfrog the EU within the next four years if current trends continue.

In its 2021 fiscal year budget proposal, the Trump administration earlier this month increased the National Science Foundation (NSF) budget for AI-related grants and research institutions to over $830 million (up 70%) and the National Institute of Standards and Technology’s AI R&D investment to $53 million. (Trump’s proposed budget earlier this year included doubling nondefense AI spending from roughly $973 million to almost $2 billion by 2022.) Congress must approve the budget, however, a goal that grows more remote as the election nears.

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