Leading Through Digital AI Powered Transformation

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 | June 14, 2023

Generative artificial intelligence (AI) has the potential to transform industries and society by boosting innovation and empowering individuals across diverse fields, from arts to scientific research. To ensure a positive future, it is crucial to prioritize responsible design and release practices from the beginning. As generative AI continues to advance at an unprecedented pace, the need for collaboration among stakeholders to ensure that AI serves as a force for good has become increasingly urgent.

whitePaper | August 31, 2022

Artificial intelligence and machine learning analyses are driving critical decisions impacting our lives and the economic structure of our society. These complex analytical techniques—powered by sophisticated math, computational power, and often vast amounts of data—are deployed in a variety of critical applications, from making healthcare decisions to evaluating job applications to informing parole and probation decisions to determining eligibility and pricing for insurance and other financial services.

whitePaper | April 14, 2021

While the new era of remote work has provided some businesses with surprising productivity boosts as high as 13%, many are still struggling to secure their suddenly expanded network of remote endpoints and IT resources against a growing onslaught of cyberthreats.

whitePaper | December 15, 2019

Artificial Intelligence (AI), and specifically Machine Learning (ML), are being tested in an increasing number of fields, including data-centric environments. Image or text analysis, speech recognition, chatbot interactions, custom machine learning models… all these are elements that could enable the AI journey of a public safety and security organisation. This document dives into different aspects of integrating AI & ML in Public Safety activities, at different levels and in different domains of activity. It presents ethical and regulatory considerations, real examples from Public Safety Answering Points (PSAPs) and Emergency Response Organisations (EROs), and also initiatives that can benefit the public sector greatly, with a series of recommendations at the end.

whitePaper | August 25, 2022

The document focuses on the best practices to consider for API design by breaking it into its basic building blocks. Along with each recommendation the document also describes the reason and impact of a certain design decision through scenarios. The document provides recommendations on object representations, usage of headers and URL/URI templates to consider.