Pushing computing power to the distributed edge ensures that data can be analyzed in near real time —a model not possible with cloud ... Having switched to an intelligent edge compute model, ...

With edge computing, businesses no longer need to transmit data back to a central location, process it and get a response. Computation can instead take place in nearby edge data centers.

Leading companies integrate four essential architectural pillars: microservices, edge computing, content delivery networks ...

As artificial intelligence (AI) usage and sophistication grows, questions about the sustainability of the traditional model ...

As a subset of distributed computing, edge computing isn’t new, but it exposes an opportunity to distribute latency-sensitive application resources more optimally. By Tom Nolle Mar 14, 2024 7 mins ...

While Scale Computing’s Platform//2025 conference this week was focused on how the hyperconverged infrastructure technology developer is expanding its drive to be a dominating force in the edge ...

Theta EdgeCloud is a decentralized marketplace that connects the supply and demand for GPU computing power. It empowers anyone with idle GPUs to contribute their resources and earn rewards, while ...

By embracing edge computing, businesses can unlock new levels of efficiency, innovation, and customer experience. The potential for transformative change is immense.

In the final installment of the Vertiv Edge Computing Innovation Day, DCD’s Alex Dickins sits down with three experts from Vertiv to discuss the realistic roadmap for distributed computing.Joining ...

The fast growth of the Internet of Things (IoT) has changed how devices communicate, handle data, and provide value across sectors. Choosing between edge computing vs cloud computing is one of the ...

China has launched 12 satellites, which experts describe as the world’s first operational space-based computing network, applying edge computing principles to orbital operations in a development ...

AI-driven models can improve real-time operations through pre-trained algorithms deployed directly on edge intelligent devices, federated learning across distributed devices, transfer learning ...