Uber AI has open-sourced Fiber, a new library which aims to empower users in implementing large-scale machine learning computation on computer clusters. The main objectives of the library are to ...

Training a machine learning algorithm to accurately solve complex problems requires large amounts of data. Previous articles in this series discussed an exascale-capable machine learning algorithm and ...

The future of machine learning is distributed If you are familiar with ML model deployment, you may know about PMML and PFA. PMML and PFA are existing standards for packaging ML models for deployment.

Over the last couple of decades, those looking for a cluster management platform faced no shortage of choices. However, large-scale clusters are being asked to operate in different ways, namely by ...

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

Distributed machine learning startup Boosted.ai revealed today it has raised $35 million in new funding to scale up its web-based platform that brings explainable machine learning tools to ...

In conclusion, clustering M4 Mac Minis presents a promising alternative for distributed machine learning, particularly for users seeking cost-effective and energy-efficient solutions.

Microsoft today announced the release of a new open-source machine learning toolkit that goes by the name DMTK. The toolkit contains a framework for training models on multiple servers, a topic ...

By integrating LoRa technology with distributed machine learning, the network connectivity of green intelligent transportation systems can be optimized.