Search results for: 'computing pa00'

The study evaluates photonic and optical computing technologies as critical enablers of next-generation AI infrastructure, addressing growing bandwidth, latency, power consumption, and scalability constraints associated with copper-based interconnects. The analysis covers photonic integrated circuits (PICs), optical I/O chiplets, co-packaged optics...

The convergence of disruptive technologies—particularly Artificial Intelligence (AI), Generative Artificial Intelligence (GenAI), fifth-generation wireless (5G), Internet of Things (IoT), and edge computing—drives growth, innovation, and transformational leadership. The Mobile World Congress (MWC) theme for 2025, "Converge. Connect. Create." unders...

The Economic Trend Opportunity Profiles (TOPs) series captures a structural shift in the global economy where national competitiveness is increasingly defined by control over AI capabilities, digital infrastructure, industrial capacity, and secure data ecosystems. Across AI-led productivity, smart manufacturing, digital risk, sovereign compute infr...

3D ICs are redefining semiconductor innovation by enabling significant gains in performance, density, and energy efficiency. This report provides an executive view of how advances in vertical stacking, heterogeneous integration, chiplet-based design, and advanced packaging are reshaping design and manufacturing strategies across the industry. It hi...

The Future of the United States explores the transformative trends shaping national competitiveness, economic resilience, and technological leadership through 2035. US energy policy is reinforcing fossil fuel expansion while navigating the growth of renewables, addressing increasing electricity demand from AI-intensive industries, and modernizing t...

The 2025 edition of privacy-enhancing technologies (PETs) explores cutting-edge innovations that redefine secure data collaboration and regulatory compliance across industries. PETs enable organizations to analyze, process, and share sensitive data without compromising privacy—using advanced methods such as differential privacy, federated learning,...