Search results for: 'artificial intelligence ad 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...

This Frost Radar™ analysis benchmarks vendors that offer open-source intelligence (OSINT) platforms for businesses, law enforcement, and government agencies to accomplish threat intelligence, due diligence, and risk evaluation investigations. Frost & Sullivan uses its proprietary benchmarking methodology to plot the top global vendors in the indu...

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 ...

Quantum computing developments have witnessed a remarkable progress in the two past decades, involving a multi-disciplinary field of applied research. With the advent of disruptive technologies which addresses individual quantum states, quantum properties such as superposition and entanglement have led to the development of a completely new approac...

Smart sensors transform conventional industrial machines into connected ones via Internet. Connected industrial machines integrated with smart sensors are smart electronic devices, which can be remotely retrieved, observed, and measured using personal computers, laptops and smartphones. In the food manufacturing process, sensors are built for detec...

27 Apr 2020  |  Global  |  Market Research

Growth Opportunities for Memory, Power, and Artificial Intelligence (AI) Semiconductors in 5G, Forecast to 2025

Implementation of Discrete AI Processors at the Edge, Improved Memory Density to Support Low-latency Data Transmission, and High-performance Power Amplifiers (PAs) Enable Accelerated Growth in the Adoption of 5G Connected Devices

Infographics

×

Key Issues Addressed

The 5G wireless communication technology is designed to operate in sub-6 GHz and mmWave frequency ranges with a bandwidth of 100 MHz, data rates in Gbps, with connection reliability of 99.99Percentage to 99.9999Percentage, and latency in the sub-5 millisecond range. Compared to 4G, these performance goals had multiplied several fold in 5G to improv...