By AI Trends Staff
The federal government is increasing its investment in AI research, with the announcement on August 26 of over $1 billion of awards to establish 12 new AI and quantum information science (QIS) research institutes nationwide.
The announcement was from the White House Office of Science and Technology Policy, the National Science Foundation (NSF) and the US Department of Energy (DOE), in a release issued from the Brookhaven National Laboratory of Upton, N.Y.
The $1 billion will go toward NSF-led AI Research Institutes and DOE QIS Research Centers of five years, establishing 12 multi-disciplinary and multi-institutional national hubs for research and workforce development. The goals are to spur innovation, support regional economic growth and advance American leadership in strategic industries.
“Through these institutes, the Federal government, private sector, and academia will come together to drive transformative AI and quantum breakthroughs. This is a significant achievement for the American people and the future of emerging technologies,” stated Chris Liddell, White House Deputy Chief of Staff.
AI’s talent shortage is widely understood. Enrollment in AI-related fields such as computer science has risen in US higher education in recent years; the colleges have not been able to meet student demand, according to an account in VentureBeat.
The $1 billion might be seen as a drop in the bucket compared to what is needed for AI research spending. The national security think tank Center for a New American Security has called for federal spending on high-risk/high-reward AI research to increase to $25 billion by 2025 to avoid “brain drain,” according to an account in Global Government Forum. 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.
Meanwhile, 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, exacerbating the AI labor market strain.
The seven NSF 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.
The 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.
The 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.
The 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.
The 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.
The 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 Center Formation
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:
The Next Generation Quantum Science and Engineering Center (Q-NEXT), led by 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.
The 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.
The 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.
The 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.
Europe, China Spending More on AI Research
But U.S. superiority in AI and quantum computing is an increasingly dim prospect, according to the account in VentureBeat.
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 committed to 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 led the world in scholarly output related to AI last year, according to a report from 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.