Search results for: 'model fuel develop deceleration'

Photonic integrated circuit (PIC) is an optical chip which accommodates multiple photonic functions and is being developed as an alternative for electronic integrated circuits. Their capability to transmit data in optical medium unlike electronic ICs make them effective medium for communication in telecom and datacentre sectors. In case of sensors,...

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 edge AI accelerator market is scaling rapidly as industries demand low-latency, privacy-aware intelligence for autonomous vehicles, industrial automation, smart cameras, robotics, and other applications. Cloud-based inference faces more limits from bandwidth, latency, and data sovereignty concerns, creating a strong pull for on-device AI proces...

24 Jul 2024  |  Global  |  Technology Research

Radar R&D Portfolio Assessment and Opportunity Analysis

Millimeter-Wave Radar and Radar-on-Chip Solutions are Driving Market Growth

Infographics

×

Radar technology will experience rapid growth because of improvements in enabling technologies and growing demand in the automotive, defense, aerospace, consumer electronics, manufacturing, and energy industries. The technology has diverse applications and use is expanding with the adoption of IoT devices and penetration of 5G technology. The lo...

The additive manufacturing sector has seen significant growth in recent years owing to growing demand for customized products and complex geometries in various sectors, including automotive, defense, aerospace, consumer electronics, manufacturing, and energy. AI has a wide range of applications in additive manufacturing at various levels and is a k...

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...

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...

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...