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 ...

A new study published in Frontiers in Computer Science introduces a decentralized cybersecurity model that combines federated ...

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 ...

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 ...

Enterprise AI workloads require infrastructure designed for large-scale data processing and distributed computing.

Infrastructure decisions used to be driven mostly by technical benchmarks. CPU performance, storage type, network latency, ...

This Research Topic focuses on the integration of artificial intelligence (AI) with mobile and distributed models of care in critical care and anesthesia.

Gaurav Bansal is a Senior Staff Software Engineer at Uber with 12+ years of experience in scalable, high-performance distributed systems. Every new tech business today builds distributed systems and ...

I’ve been flying multispectral missions for a few years now, and the biggest surprise of these systems is how much processing ...