Everyday Ethics for Artificial Intelligence

whitePaper | August 1, 2020

The majority of enterprise companies have hundreds of apps deployed in the cloud, and that trend is expected to continue, according to a new survey by IDG. That said, 52% of companies find that securing those apps continues to be challenging. But that doesn’t mean that the remaining 48% are fully confident in their cloud app security or are fully aware of all of the facets of cloud security they should be considering. “Cloud security is a broad issue,” says Jim Fulton, Director, Cloud & Edge Protection Solutions for Forcepoint. “From what I’ve seen, about 10% of companies really understand all of the facets.

whitePaper | August 18, 2021

Among retail marketers, a reliance on traditional business intelligence tools has left the intuitive decision-making in the hands of the marketing team. Download this guide to learn how to solve this AI dilemma.

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 | September 15, 2022

No broad industry trend, not client/server computing, not affordable hardware, not even the cloud itself, promises to so completely reshape the enterprise than artificial intelligence (AI). Melding decades-old mathematical principles with cutting edge algorithms and readily available, high performance hardware, AI is creating a seismic shift in the way companies across all industries build, maintain, and understand their core and departmental business operations.

whitePaper | June 30, 2022

Low code and no code (LCNC) development platforms expedite the creation of new applications with minimal or no coding requirements, as well as offer tools for non-programmers to create applications of their own. Low code development was introduced in the early 2000s to increase developer productivity. It uses a variety of approaches that automate and abstract application development activities, such as drag and drop editors, code generation, component assembly and model-driven development.

whitePaper | November 15, 2019

The demands of running global supply chains can be unrelenting – perfection of operations, innovation in support of lastmile delivery, and assurances of sustainability in the pursuit of delivering the “perfect order” as promised. Now, transportation companies face the additional challenge of sharpening their core competencies while increasing the pace of innovation, adapting emerging technologies, and sharing data with their customers to improve transparency and efficiency. Long characterized by capital-intensive assets, forward-looking cargo companies are turning their attention to the data that comes from their own assets and infrastructure as well as from their customers. It is a complex transition, one that requires knowledge-based labor, automation, and predictive planning to turn transportation companies into digital platforms.