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 2026, enterprises will be expected to automate processes that involve judgment, negotiation, compliance interpretation, ...

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

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 ...

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 ...

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

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. In this episode, Thomas Betts chats with ...

A distributed system is comprised of multiple computing devices interconnected with one another via a loosely-connected network. Almost all computing systems and applications today are distributed in ...

Planning and operating a power system requires detailed grid studies to guide investment decisions and prepare for how the system may evolve over time. Long-term planning can identify the policy, ...

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 ...