Google today is announcing the release of version 0.8 of its TensorFlow open-source machine learning software. The release is significant because it supports the ability to train machine learning ...

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 new capabilities are designed to enable enterprises in regulated industries to securely build and refine machine learning models using shared data without compromising privacy. AWS has rolled out ...

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 ...

Big data for health care is one of the potential solutions to deal with the numerous challenges of health care, such as rising cost, aging population, precision medicine, universal health coverage, ...

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 ...