The global data ecosystem has now entered a decisive phase as organisations rethink how information is processed, stored, and ...

Data is the backbone of tech innovation. Storing, processing and managing IT resources and data impacts your tech system’s efficiency and expected output. The advent of cloud computing revolutionized ...

In the rapidly evolving world of IoT (Internet of Things), cloud computing has become a cornerstone for processing, analyzing, and storing large amounts of data. However, as real-time applications and ...

Artificial Intelligence (AI) has transformed industries by enabling systems to make smart decisions, process vast amounts of data, and even predict outcomes in real-time. Two primary paradigms in AI ...

AI isn’t about if anymore — it’s where. Run inference at the edge when speed, privacy or outages matter, and use the cloud ...

The energy industry is undergoing a significant transformation, driven by advancements in digital technology and the ever-growing need for real-time data analytics. As energy companies look to ...

This Collection invites submissions of original research into techniques that facilitate the deployment of cloud, fog, and edge computing technologies, driving advancements in efficient data ...

An explosion in data from inspection images and metrology measurements is creating a confusing set of demands for chipmakers and their equipment vendors. On one hand they need the massive storage and ...

Latency issues with cloud: AI often demands near-zero latency to deliver actions. "Applications requiring response times of 10 milliseconds or below cannot tolerate the inherent delays of cloud-based ...

The history of data processing begins in the 1960s with centralized on-site mainframes that later evolved into distributed client servers. In the beginning of this century, centralized cloud computing ...