EMC IT’S VIRTUAL ORACLE DEPLOYMENT FRAMEWORK

whitePaper | August 9, 2022

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whitePaper | December 15, 2019

The debate between experts over how automation will affect the future of work has been one of the most active cottage industries in labor economics in recent years. Numerous scholars forecast major disruptions of human work; others minimize those impacts. And yet, the field has nevertheless managed to generate a number of shared insights, with none more consistent than the finding that least welloff will suffer automation’s greatest shocks on the labor market.

whitePaper | October 20, 2022

Telecoms need to be able to incorporate new technologies and next-generation connectivity such as 5G to customers and end users.

whitePaper | October 17, 2022

The NVIDIA DGX family of systems is made up of the world’s first integrated artificial intelligence (AI)-based systems that are purpose-built for enterprise AI. NetApp AFF storage systems deliver extreme performance and industry-leading hybrid cloud data-management capabilities. NetApp and NVIDIA have partnered to create the NetApp ONTAP AI reference architecture, a turnkey solution for AI and machine learning (ML) workloads that provides enterprise-class performance, reliability, and support.

whitePaper | December 1, 2021

The health and vibrancy of our national economy depends on the health and vibrancy of our organizations. How an organization is staffed is a key driver of its health. Yet only one in three executives rates his or her company as “very effective” at reducing unsuccessful hiring decisions (Bravery et al., 2019). Thus, industrial-organizational (I-O) psychologists help organizations thrive by choosing the right talent for the right job at the right time, using the most accurate, cost effective, and fair tools available (Ployhart, Schmitt, & Tippins, 2017).

whitePaper | May 15, 2023

The future of AI is hybrid. As generative AI adoption grows at record-setting speeds1 and drives higher demand for compute,2 AI processing must be distributed between the cloud and devices for AI to scale and reach its full potential – just like traditional computing evolved from mainframes and thin clients to today’s mix of cloud and edge devices. A hybrid AI architecture distributes and coordinates AI workloads among cloud and edge devices, rather than processing in the cloud alone. The cloud and edge devices, such as smartphones, vehicles, PCs, and IoT devices, work together to deliver more powerful, efficient, and highly optimized AI.