Search results for: 'artificial intelligence and cloud computing'

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...

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 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...

Intelligent automation is driven by artificial intelligence (AI) technologies. In industrial operations, AI acts as the catalyst to increase the productivity in the operations. Three types of artificial technology are identified as a game-changer in industrial operations in which these technologies are digitalizing and streamlining the value chain ...

The impact of information technology (IT) on the manufacturing industry has been tremendous in recent times. With an increasing number of machines being connected to the Internet, data are being generated in huge volumes. Advancements in real-time data processing and predictive analytics further help in discovering newer ways of utilising the data ...

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...

07 Oct 2025  |  Global  |  Market Research

Industrial Hybrid AI Market, Global, 2024–2029

Industrial Hybrid AI Market is Experiencing Transformational Growth due to the Urgency for Adaptive Intelligence in Critical Decision-Making

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Hybrid AI is an integrative approach reshaping how AI is applied to mission-critical applications. Its potential lies in addressing the critical limitations of current AI solutions, with key market drivers including enhanced interpretability and explainability, greater application flexibility, and improved scalability and efficiency. Strong growth ...

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...