Uptime Assurance through the Mobilization and Augmentation of Data Center IT Teams with Artificially Intelligent Applications

In this contributed article, AJ Byers, CEO of ROOT Data Center, discusses how AI technology was implemented in ROOT Data Centers since it was initially deployed in early 2018. Since then, over 250 hours and 3,000 training sessions have been completed to gather the data necessary for the AI persona. As a result, ROOT compiled the case study below covering how they achieved these processes.

How to Get to the Data-Enabled Data Center

Despite their many promising benefits, advancements in Artificial Intelligence (AI) and Deep Learning (DL) are creating some of the most challenging workloads in modern computing history and put significant strain on the underlying I/O, storage, compute and network. An AI-enabled data center must be able to concurrently and efficiently service the entire spectrum of activities involved in the AI and DL process, including data ingest, training and inference.

HPE Brings Artificial Intelligence to the Data Center

Hewlett Packard Enterprise (NYSE:HPE) announced an artificial intelligence (AI) recommendation engine designed to simplify and reduce the guesswork in managing infrastructure and improve application reliability. HPE InfoSight is an industry-leading predictive analytics platform that brings software-defined intelligence to the data center with the ability to predict and prevent infrastructure problems before they happen.

ROOT Data Center – Wholesale Provider to Implement AI and Machine Learning for Reduced Downtime Risk

ROOT Data Center, announced that it is the first wholesale data center in the world to use Artificial Intelligence (AI) and machine learning to reduce the risk of data center downtime. ROOT Data Center has partnered with state-of-the-art AI and machine learning technology firm Litbit, within ROOT’s Montréal-based facility.

The Cost of Updating Older Data Centers for Big Data Needs

In this contributed article, freelance human Avery Phillips suggests that before your company makes the leap to update your servers and other data-center equipment for the needs of your big data deployments, make sure you understand the challenges ahead.