The Internet of Us: Why Human Experience Is Vital to Building Useful IoT Applications

whitePaper | December 22, 2022

Machine learning, one of the key building blocks of AI, has been a part of the technological world since the 1950s, when the earliest programmers asked computers to make sense of large sets of data. Programmers have increasingly refined the ability of machines to study data in order to detect patterns that allow computers to then organise information, identify relationships, make predictions and detect anomalies. Today, modern applications of AI have already given us self-driving cars and virtual assistants and have helped us detect fraud and manage resources like electricity more efficiently. Sectors as diverse as retail, sports, banking, manufacturing and healthcare have all found applications for machine learning and AI.

whitePaper | June 2, 2022

Licensing programs are channels where you can buy Power Apps, Power Automate and Power Virtual Agents. You can license Power Apps, Power Automate and Microsoft Power Virtual Agents through Microsoft Volume Licensing (VL), Cloud Solution Provider program (CSP), and/or Web Direct (MOSP) programs. In Volume Licensing, Power Apps and Power Automate are available through:

whitePaper | December 26, 2022

IBM embraces five foundational pillars of trustworthy AI: Explainability, Fairness, Robustness, Transparency, and Privacy. These pillars underpin the development, deployment and use of AI systems. This document and IBM’s trustworthy AI pillars are meant to help you align on both process and outcomes.

whitePaper | June 24, 2022

This new technology guide from DDN shows how optimized storage has a unique opportunity to become much more than a siloed repository for the deluge of data constantly generated in today’s hyper-connected world, but rather a platform that shares and delivers data to create competitive business value. The intended audience for this important new technology guide includes enterprise thought leaders (CIOs, director level IT, etc.), along with data scientists and data engineers who are a seeking guidance in terms of infrastructure for AI and DL in terms of specialized hardware. The emphasis of the guide is “real world” applications, workloads, and present day challenges.

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 | November 1, 2021

Robotics, automation, Internet of Things (IoT), and data are not new in manufacturing. Manufacturing is one of the most data-rich and first industries piloting artificial intelligence at the edge. It’s been estimated, however, that about 95% of all industrial data goes unused. The reason? Legacy equipment and operational systems that tend to be proprietary and siloed are incapable of communicating with each other.