Distributed health professions education, also referred to as decentralized training in the medical education literature, is ...

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Poor utilization is not the single domain of on-prem datacenters. Despite packing instances full of users, the largest cloud providers have similar problems. However, just as the world learned by ...

In the context of deep learning model training, checkpoint-based error recovery techniques are a simple and effective form of fault tolerance. By regularly saving the ...

We called it Machine Learning October Fest. Last week saw the nearly synchronized breakout of a number of news centered around machine learning (ML): The release of PyTorch 1.0 beta from Facebook, ...

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 ...

Not long ago, Google’s machine learning and backend building tool, TensorFlow, finally went open source. Today, Google announced that TensorFlow has been updated to version 0.8, with the update ...