Search results for: 'Decision Intelligence Platforms in North America'

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...

Hybrid vision systems (HVS) are positioned to substantially impact perception-driven applications across a diverse array of sectors, including robotics, manufacturing, logistics, mobility, surveillance, and agriculture. By intricately combining the geographical precision of LiDAR with the semantic intelligence of advanced imaging systems, these inn...

Future of Retail 4.0 marks a pivotal shift in the retail landscape, driven by intelligent systems, automation, and ethical consumerism. Businesses are rapidly adopting models like Retail as a Service and Real-Time AI Pricing to enhance operational efficiency and dynamic market responsiveness. IoT-powered smart store infrastructure and AI-driven los...

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...

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...

22 Jan 2025  |  Global  |  Technology Research

Medical Spectral Imaging: Assessment of Technology Trends and Growth Opportunities

Artificial intelligence, system miniaturization, and sensor innovation to drive transformational growth

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Medical spectral imaging is an advanced imaging technique that integrates spectroscopy with photography to capture the reflectance spectrum of tissues, facilitating a range of applications from tissue analysis to surgical guidance. This non-invasive approach provides real-time data and detailed insights, enhancing decision-making accuracy in diseas...

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 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...

Disruptive AI models are increasingly challenging traditional assumptions about “classic” cloud data centers. As training clusters scale up to thousands of accelerators and consume tens of megawatts of power, the conventional CPU-centric, air-cooled, monolithic server model is no longer sustainable. This research study explores the megatrend of AI ...