Open Source Software for Industry 4.0

whitePaper | June 7, 2022

Telecoms need to be able to incorporate new technologies and next-generation connectivity such as 5G to customers and end users. To achieve these ambitious goals, they need to optimize their networks – make them more intelligent if you will. Some of the tools needed include artificial intelligence (AI), machine learning (ML) and artificial intelligence operations (AIOps). This document will explore what intelligent networking means to telecoms, vendors and customers, and how AI and ML technologies and tools can be used, the cultural shifts the industry needs to make it a success, and what to bear in mind when deploying machine learning across a telecom network.

whitePaper | October 13, 2022

Walk into any Fortune 500 organization, and you’re more than likely to find a room full of data scientists. These individuals are being described by many as the difference makers, the propagators of change, the fuel to the fire of innovation, and the essential ingredient to survival in today’s digital economy. Data scientist job openings are among the hardest positions to fill in the market, yet they are among the highest paying jobs at many companies.

whitePaper | January 28, 2022

Since more and more decisions that used to be made by humans are nowadays made either with the help of Artificial Intelligence (AI) or by AI alone, it is essential that the AI algorithms are “fair.” In this whitepaper, we discuss issues surrounding the fairness of AI applications, with a special focus on how it can be assessed independently and subsequently certified. We explain why an AI application cannot be classified – and subsequently certified – as “fair” or “unfair” in a general sense and propose an approach that makes it possible to classify it as “fair” or “unfair” under the (application)-specific definition of fairness.

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 | July 31, 2020

IT organizations face constant change. There’s the overarching transition to cloud, which raises questions about what workloads to move when. And there are application-level transitions imposed by vendors when they end support for older versions of software, forcing companies to upgrade. Microsoft SQL Server is swept up in both of these transitions. Organizations rely on SQL Server for everything from ERP to analytics, and thousands of them are running the 2008 or older versions that are now end of support.

whitePaper | January 12, 2020

“The services market for artificial intelligence technologies is rapidly maturing on the back of several years of learning and a realization—delivering AI is unlike delivering any other technology thus far. Delivering on the promise of AI calls for far more collaboration between service providers, tech vendors, and enterprise clients.” The biggest differentiator in enterprise AI services, as described by most of the customer leaders, is the quality of people—not just the quantity available for a specific skill. Domain understanding and data engineering capabilities are top priorities. A culture of innovation, experimentation, collaboration, and co creation with customers is the key winning formula here.”