Itron's Nick Tumilowicz asserts a need for an integrated approach to grid management that processes and acts on real-time data at the edge.

TensorFlow 0.8 adds distributed computing support to speed up the learning process for Google's machine learning system.

But the truth is edge computing is an easily predictable pattern as digital operations scale, especially for geographically distributed businesses, such as national retail chains, insurance ...

Edge computing is a growing trend amongst oil and gas companies as they strive to gain value from the huge volumes of data they collect from their operations ...

Google hopes that with ope source availability and distributed computing support, researchers, engineers and hobbyists can help speed the machine’s learning along and help get it to a much ...

With the future of AI built on distributed computing across data centers, Jericho4 strikes a crucial balance between these elements.

The company says distributed computing has long been one of the most requested features for TensorFlow and with this, Google is essentially making the technology that powers much of its recently ...

Cloud computing’s multitenancy and virtualization features pose unique security and access control challenges. In this article, authors discuss a distributed architecture based on the principles ...

Thanks to deep buffering and intelligent congestion control, Jericho4 ensures lossless RoCE across 100km+ enabling truly distributed AI infrastructure unconstrained by power and space limitations ...