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This report focuses on the ways that a federated defense approach can strengthen strategic partnerships and deliver more innovative defense technologies at a lower cost—by better harnessing global supply chain networks to expand the military supplier base and increase the net capability available to the network of partners and allies.
This report focuses on the institutional foundations that enable—or, at times, hinder—federated approaches to defense. Successful defense collaboration in a budget-constrained environment is predicated on the ability and willingness of the United States to provide assistance and/or equipment to allies and partners. Accordingly, the report describes the context for refining US institutional foundations, as well as findings in key issue areas, such as priorities/strategic guidance, foreign military sales, export controls, technology security and foreign disclosure, and acquisitions and requirements processes. The report also includes actionable recommendations on how the United States and its partners could integrate their defense capabilities in support of shared interests.
This study examines contracting trends at the U.S. Department of Defense (DoD). It relies on empirical analysis of DoD contracting transaction data from the open-source Federal Procurement Data System (FPDS). The authors seek to identify and study emergent trends in the contracting data and marry that analysis with discussion of changing goals and methods for the larger acquisition system.
As experienced by the United States, competition has played out in three distinct types of threat activity: sabotage (the destruction of capabilities), espionage (the theft of specific capabilities), and defection (the carrying of knowledge out of the country). Today, the changing innovation environment has created new challenges. Significant advances are being made in start-ups as well as larger companies who no longer rely on U.S. government contracts. Not only does this place a key element of national power in the hands of the private sector, but it often leaves Washington at an informational disadvantage in understanding technologies. This book analyzes these concepts from the perspective of the United States’ experience in the field of innovation security. Historical and recent examples illustrate the threats to innovation, the various approaches to mitigating them, and how the evolution of the innovative process now requires rethinking how the United States can benefit from and preserve its cutting edge human capital.
The U.S. Navy’s requirement to implement a longstanding rhetorical commitment to partnerships at sea was articulated in the 2012 Defense Strategic Guidance, confirmed in the 2014 Quadrennial Defense Review, and was most recently reiterated in the new Cooperative Strategy for 21st Century Seapower: Forward, Engaged, Ready. As a means to offset the risks inherent in divesting some maritime presence requirements and being challenged to ensure operational access, however, the Navy’s current efforts fall short of the requirement. As an unclassified, service-specific look at an increasingly important defense policy area, Tailoring the Global Network for Real Burden-Sharing at Sea looks at what the Navy can do from the bottom up to provide for deeper, more structured partnerships as part of a federated approach to defense.
This report is the first regional study in the CSIS Federated Defense series. The Federated Defense Project aims to shift the paradigm with key allies and partners from capacity building to a federated approach that would expand regional security and prosperity by joining regional allies and partners together in the pursuit of shared security objectives across the conflict spectrum. Federated defense should include forward-thinking strategies for how to develop and share capabilities and capacity, thereby more deeply integrating the US military with its allies and partners. In this report, the CSIS project team highlights six potential federated initiatives in the areas of humanitarian assistance and disaster relief, information and intelligence sharing, maritime security, undersea warfare, missile defense, and cyber security. Federated approaches such as these are vital to developing and integrating Asian security capabilities to manage emerging security challenges.
"The ongoing COVID-19 pandemic marks the most significant, singular global disruption since World War II, with health, economic, political, and security implications that will ripple for years to come." -Global Trends 2040 (2021) Global Trends 2040-A More Contested World (2021), released by the US National Intelligence Council, is the latest report in its series of reports starting in 1997 about megatrends and the world's future. This report, strongly influenced by the COVID-19 pandemic, paints a bleak picture of the future and describes a contested, fragmented and turbulent world. It specifically discusses the four main trends that will shape tomorrow's world: - Demographics-by 2040, 1.4 billion people will be added mostly in Africa and South Asia. - Economics-increased government debt and concentrated economic power will escalate problems for the poor and middleclass. - Climate-a hotter world will increase water, food, and health insecurity. - Technology-the emergence of new technologies could both solve and cause problems for human life. Students of trends, policymakers, entrepreneurs, academics, journalists and anyone eager for a glimpse into the next decades, will find this report, with colored graphs, essential reading.
Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more. The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT). Other topics covered include: Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problems Generating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablers Compressing AI models so that computational, memory, storage, and network requirements can be substantially reduced Addressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous data Overcoming cyberattacks on mission-critical software systems by leveraging federated learning