Dell unveils AI-enabled servers, storage solutions
Las Vegas: As enterprises the world over invest big into disruptive technologies like Artificial Intelligence (AI) and Machine Learning (ML), Dell Technologies has announced 14th generation Dell EMC PowerEdge servers that turn data into intelligent insights in real time to deliver better business outcomes.
The company forged an alliance with Intel in AI and ML for Dell EMC ready solutions to enable customers harness the power of data to unveil two new four-socket servers -- PowerEdge R940xa and PowerEdge R840.The new servers will be available globally from May 22.
"Data is power. This is where the power of AI and ML becomes real when organisations are able to deliver better products, services, solutions and experiences based on data-driven decisions," Jeff Clarke, Vice Chairman, Products and Operations at Dell, said during the ongoing "Dell Technologies World 2018" event here on Tuesday.
The servers house with Intel Xeon Scalable processors (up to 112 processing cores) and huge memory (up to 6TB).
"Better business outcomes made possible by end-to-end solutions fueled by data -- from the PC workstation, to the data centre and applications running in the Cloud," Clarke added.
According to the Enterprise Strategy Group's (ESG) "2017 IT Transformation Maturity Curve Index" -- commissioned by Dell EMC - transformed companies are 18 times more likely to make better and faster data-driven decisions than their competition. Dell EMC PowerEdge R940xa is designed to accelerate databases for business-critical applications without cloud fees and security risks. Dell EMC PowerEdge R840 server has been designed for in-database analytics.
Dell EMC also announced its next-generation PowerMax storage solution, built with a ML engine. This solution leverages predictive analytics and pattern recognition./According to Clarke, a single PowerMax system analyses and forecasts 40 million data sets in real-time per array, driving six billion decisions per day to automatically maximise efficiency of mixed data storage workloads.