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2016–2019 PROGRESS REPORT: ADVANCING ARTIFICIAL INTELLIGENCE R&D

(November 20, 2019)

The United States national strategy for artificial intelligence (AI), the American AI Initiative, identifies research and development (R&D) as a top priority for maintaining global leadership in AI. The United States leads the world in AI innovation, due in large part to its robust R&D ecosystem. Federal agencies contribute significantly to AI innovation by investing in numerous world-class research programs in areas consistent with the unique missions of each agency.

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NATIONAL STRATEGIC COMPUTING INITIATIVE UPDATE: PIONEERING THE FUTURE OF COMPUTING

(November 14, 2019)

The national computing landscape is undergoing rapid evolution along multiple dimensions due to the introduction of new and potentially disruptive technologies and the demands of new classes of data-intensive applications. Computer architectures and systems are more heterogeneous and complex, and the challenges associated with the complexity and sustainability of software are significant. Application developers are being called to meet demands for improved usability and productivity. Therefore, to address this new environment, it is essential to update the 2016 U.S. Strategic Computing Plan in a holistic and synergistic fashion that involves government, academia, and industry. The Office of Science and Technology Policy and the National Science and Technology Council Subcommittee on Networking and Information Technology Research and Development created a Fast Track Action Committee on Strategic Computing in June 2019 to address this imperative.

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SECURITY FROM A WIRELESS SPECTRUM PERSPECTIVE: TECHNOLOGY INNOVATION AND POLICY RESEARCH NEEDS

(September 30, 2019)

Communications over the wireless medium pose security threats that are yet to be fully understood. It is currently possible for attackers that are within the wireless range to hijack or intercept an unprotected connection without being detected. With the advent of sophisticated cognitive radios and wireless devices, and applications such as the Internet of Things (IoT), drones, small satellites, driverless cars, and wireless healthcare devices, security threats to wireless mobile communications systems are rapidly increasing. As 5G, low-power wide area networks, and other emerging systems are deployed, innovative protective technologies and policies are needed.

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FY2020 FEDERAL CYBERSECURITY R&D STRATEGIC PLAN IMPLEMENTATION ROADMAP

(September 10, 2019)

This document provides FY2020 implementation details for the 2016 Federal Cybersecurity Research and Development Strategic Plan, developed by the Networking and Information Technology Research and Development (NITRD) Program’s Cyber Security and Information Assurance (CSIA) Interagency Working Group (IWG). This Strategic Plan Implementation Roadmap is provided per statutory requirement for public provision of this information pursuant to the Cybersecurity Enhancement Act of 2014, Public Law 113-274, Section 201(a)(2)(D), Implementation Roadmap, and under direction from the NITRD Subcommittee of the National Science and Technology Council Committee on Science and Technology Enterprise. This document accompanies the NITRD Supplement to the President’s FY2020 Budget.

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SUPPLEMENT TO THE PRESIDENT’S FY2020 BUDGET

(September 10, 2019)

Information technologies (IT) – including networking, computing, and software – comprise the most broadly transformative suite of technologies ever invented. American innovations in these fields since the late 1960s have led the world into a new technological era and opened countless practical capabilities and opportunities on which the security and prosperity of the United States today depend. Also vital to the Nation’s prosperity and security are IT advancements that mitigate potential risks posed by adversarial breaches of the country’s increasingly interwoven IT-based operations.

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THE CONVERGENCE OF HIGH PERFORMANCE COMPUTING, BIG DATA, AND MACHINE LEARNING

(September 9, 2019)

The high performance computing (HPC) and big data (BD) communities are evolving in response to changing user needs and technological landscapes. Researchers are increasingly using machine learning (ML) not only for data analytics but also for modeling and simulation; science-based simulations are increasingly relying on embedded ML models not only to interpret results from massive data outputs but also to steer computations. Science-based models are being combined with data-driven models to represent complex systems and phenomena. There also is an increasing need for real-time data analytics, which requires large-scale computations to be performed closer to the data and data infrastructures, to adapt to HPC-like modes of operation. These new use cases create a vital need for HPC and BD systems to deal with simulations and data analytics in a more unified fashion.

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FUTURE COMPUTING COMMUNITY OF INTEREST MEETING OF AUGUST 5-6, 2019

(September 9, 2019)

The Future Computing (FC) Community of Interest (CoI) meeting on August 5–6, 2019, explored the evolving computing landscape to inform agencies about potential opportunities as well as gaps in the Nation’s future computing objectives. The meeting focused on where computing will be in the next decade and beyond while also looking at emerging and future applications. It considered the need for new software concepts and approaches to effectively capitalize on new hardware architectures and paradigms. The long period of sustained growth in computing power over the last five decades, characterized by Moore’s Law and Dennard Scaling, is expected to end over the next decade. The continued improvement in computing performance will now require moving to new modalities and new means of cooperation and partnership for the benefit of the Nation.

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THE NATIONAL ARTIFICIAL INTELLIGENCE RESEARCH AND DEVELOPMENT STRATEGIC PLAN: 2019 UPDATE

(June 21, 2019)

Artificial intelligence (AI) holds tremendous promise to benefit nearly all aspects of society, including the economy, healthcare, security, the law, transportation, even technology itself. On February 11, 2019, the President signed Executive Order 13859, Maintaining American Leadership in Artificial Intelligence. This order launched the American AI Initiative, a concerted effort to promote and protect AI technology and innovation in the United States. The Initiative implements a whole-of-government strategy in collaboration and engagement with the private sector, academia, the public, and like-minded international partners. Among other actions, key directives in the Initiative call for Federal agencies to prioritize AI research and development (R&D) investments, enhance access to high-quality cyberinfrastructure and data, ensure that the Nation leads in the development of technical standards for AI, and provide education and training opportunities to prepare the American workforce for the new era of AI.

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Research and Development Priorities for American Leadership in Wireless Communications

(May 30, 2019)

This report responds to the October 25, 2018, Presidential Memorandum on Developing a Sustainable Spectrum Strategy for America’s Future and contains recommendations for prioritizing R&D to advance radio frequency spectrum access and efficiency, as called for in Section 2(c) of the Memorandum. The report focuses on R&D efforts to create a flexible R&D environment that advances spectrum technologies to meet current and future spectrum requirements for the broad communications needs of the Nation. This report supports Administration spectrum goals by identifying spectrum R&D priorities across Federal and private sectors for ongoing, increased, and new R&D investments in both the near term (5-10 years) and the long term (greater than 10 years). The priorities report looks beyond only mobile and broadband communications to examine the entire spectrum ecosystem, including science and meteorological observations, radar, radiolocation, and navigation. The report considers the impact of R&D across the electromagnetic spectrum, as well as emerging network architectures and application domains expected in the future that will rely on the existence of a reliable wireless communication system.

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Open Knowledge Network: Summary of the Big Data IWG Workshop

(November 20, 2018)

Technology companies develop proprietary knowledge networks as key business technologies today. However, because these networks are proprietary and expensive to construct, government, academia, small businesses, and nonprofits do not have access to them. In contrast, an open knowledge network (OKN) would be available to all stakeholders, including the researchers who will help push this technology further. An OKN requires a nonproprietary, public–private development effort that spans the entire data science community and will result in an open, shared infrastructure.