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This study discusses the drivers and restraints, revenue, and Mega Trends impacting the global DSP market, which has just begun its recovery from the recession-triggered slump. Now, the growing Gen Y population in Asia-Pacific and Rest of World (ROW) are increasingly demanding advanced sensing technology, connected devices, and Internet of Things (...

The era of robotics is becoming a disruptive force in the food and beverage (F&B) industry, most notably in production, services, and delivery. By leveraging advanced AI, sensing technologies, and adaptive automation, robotic technologies are delivering groundbreaking advancements in operational precision, performance, and reliability. This transfo...

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 Microelectronics Technology Opportunity Engine provides profiles of innovations related to High-qubit Quantum Computing Platform, Energy-efficient and Scalable AI Accelerators, High-performance and Scalable Quantum Computers, Sustainable Tensor Processing Technology, High Performance eFPGA and Advanced Optical DSP.The Microelectronics Technolog...

Scope of the report The research report includes the following segments: Product scope: Active RFID, Passive RFID, RFID sensor tags, RTLS Geographic scope: Global End-user scope: RFID companies, Food Manufacturers, Logistics service providers, Cold Chain companies, Food Retail Companies, Pharmaceutical Companies Revenue analysis and forec...

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 ...

The Microelectronics Technology Opportunity Engine covers innovations pertaining to SRAM, Multi-chip Architecture, LoRa and AI Accelerators. Some of the innovations profiled include 2nm Custom SRAM for AI & Cloud Infrastructure Applications, Modular Quantum System with Reduced Gate Error and Multi-Chip Architecture, Microcontroller Series with High...

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...

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...