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 ...

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 ...

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The governance challenge is intensifying as digital systems increasingly optimize for machine consumption rather than human ...

What is a distributed system? A distributed system is a collection of independent computers that appear to the user as a single coherent system. To accomplish a common objective, the computers in a ...

While facing rising costs and workforce shortages, healthcare systems across Asia-Pacific have been exploring ways to make healthcare services more accessible by shifting to a data and digital-enabled ...

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 ...

Angela Virtu, a professor of business analytics and A.I. at American University’s Kogod School of Business, examines why most ...

Neel Somani, a researcher and technologist with a strong foundation in computer science from the University of California, Berkeley, focuses on advancements of distributed computing across personal ...

Tianpei Lu (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Bingsheng Zhang (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Xiaoyuan ...