Artificial intelligence (AI) is no longer confined to centralized data centers. It is increasingly distributed across edge devices, enterprises, multiple cloud providers, and autonomous software ...

Distributed deep learning has emerged as an essential approach for training large-scale deep neural networks by utilising multiple computational nodes. This methodology partitions the workload either ...

In the fast-changing digital era, the need for intelligent, scalable and robust infrastructure has never been so pronounced. Artificial intelligence is predicted as the harbinger of change, providing ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Blockchain hype has been subsumed by the AI hype in the past couple of years. Both these technologies are relatively new. AI has a longer pedigree, going back in concept to the Golem and human ...

Study shows adaptive circuit breakers improve reliability, reduce failures, and enhance performance in complex distributed ...

OpenAI launches GPT-5.4 mini and nano, focusing on cost, latency, and scalable AI workloads, enabling subagent architectures and efficient enterprise AI deployment at scale.

The specification will support distributed workflows coordinated across various development and execution environments. These workflows may be carried out by physical devices, virtual devices or ...