Search results for: 'Computing Power'

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...

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...

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 October 2025 edition of the CST Technology Opportunity Engine highlights transformative innovations shaping the future of edge computing. The study explores the evolution of decentralized data processing models that enable ultra-low latency, localized intelligence, and real-time decision-making across industries.Driven by the convergence of IoT...

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...

AI maturity, implementation, and AI-enabled or AI-augmented operations are increasing year over year, moving from pilot to production. Because AI delivers the biggest business outcomes, it is a top outcome driver. The impact of AI can be seen in quality control and computer vision in smart manufacturing as well. AI-powered visual inspection transfo...

The Frost Radar™ on electronic computer-aided design (ECAD) offers a competitive benchmark analysis derived from Frost & Sullivan’s CAD Growth Opportunities report. It ranks nine companies on their growth potential and ability to innovate.Product design has become more complex in recent years, and manufacturing companies are demanding new tools and...

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...

Cybersecurity attacks increased tremendously in 2020 and 2021, primarily in the frequency and sophistication of attacks. Apart from the growing concerns about signature-less ransomware and ransomware-as-a-service, attackers also use artificial intelligence and machine learning to scale up attacks. To this end, many governments acknowledge the serio...