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 ...

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 ...

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 ...

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 ...