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This study examines the emerging landscape of neuromorphic computing and its role in enabling low-power, real-time, brain-inspired intelligence across edge and autonomous systems. It reviews advancements in spiking neural networks, memristor-based computing in memory, event-driven vision sensors, and hybrid neuromorphic and conventional architectur...

The eCommerce and logistics industries are entering a period of accelerated transformation driven by the need for higher throughput, improved accuracy, and real-time operational intelligence. Emerging sensor technologies are becoming essential to support this shift as fulfillment centers, transport networks, and last-mile operations manage rising c...

This study focuses on how next-generation chiplet architectures, high-bandwidth memory (HBM), and advanced packaging technologies such as 2.5D/3D integration and fan-out wafer-level packaging are enabling the next wave of AI and high-performance computing (HPC) system architectures, rather than providing a broad packaging market overview. It analyz...

The Microelectronics Technology Opportunity Engine covers innovations pertaining to Sub-1 Nm Chip technology, MMIC, SOC, Photonic Chiplet, GaN and Power Electronics among others.The Microelectronics Technology Opportunity Engine captures global electronics-related innovations and developments on a weekly basis. Developments are centered on electron...

Energy harvesting sensor solutions are emerging as a foundational layer for large-scale ambient IoT, enabling autonomous, battery-free sensing across distributed and infrastructure-intensive environments. By converting ambient energy sources such as light, heat, vibration, and RF into usable power, these sensors eliminate the need for wired power a...

The escalating compute and power demands of edge AI are exposing the limits of conventional von Neumann architectures. Manufacturers deploying always-on sensing, real-time inference, and autonomous decision-making at the edge are constrained by the energy, latency, and memory-bandwidth ceilings of standard NPUs and MCUs. Traditionally, edge AI work...

Multimodal sensor fusion is an advanced perception technology that combines data from multiple sensors, including cameras, LiDAR, radar, ultrasonic sensors, thermal cameras, and inertial measurement units (IMUs), to give robots and autonomous systems a more accurate, reliable, and comprehensive understanding of their environment. It overcomes the l...

This study examines the technology landscape, commercialization progress, and future growth opportunities of wide-bandgap (WBG) semiconductor materials, with a primary focus on silicon carbide (SiC), gallium nitride (GaN), and gallium oxide (Ga₂O₃) for power and RF electronics. It evaluates how these materials enable higher efficiency, greater powe...

This study focuses on heterogeneous computing architectures for automotive and robotics applications, examining how centralized and zonal compute architectures, heterogeneous SoCs integrating CPUs, GPUs, NPUs, DSPs, FPGAs, and dedicated safety islands, as well as robotics edge-AI controllers and mixed-criticality computing platforms, are enabling t...