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 ...

“Edge computing also means less data travels long distances, lowering the load on main servers and networks,” says Neel ...

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 ...

It’s clear why no manufacturing executive wants to bet everything on a pure data model. Centralized architectures are robust, ...

Intersignal, an independent AI startup based in Fort Lauderdale, today announced the public debut of The Braid, a protocol designed to enable distributed artificial intelligences to cooperate across ...

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 ...

The future of process automation and control combines the reliability of traditional DCS with the agility of cloud/IT ...

How event-driven design can overcome the challenges of coordinating multiple AI agents to create scalable and efficient reasoning systems. While large language models are useful for chatbots, Q&A ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This article dives into the happens-before ...

In the AI era, SaaS companies face a new reality, where the unit of value is no longer a user or seat. It’s now dynamic, distributed, and measured in actions (not access) ...