Take the Intelligent Route to Information that Matters

whitePaper | January 5, 2020

Machine learning (ML) is an application of artificial intelligence (AI) that allows systems to automatically learn and improve from exposure to more data without being explicitly programmed. ML focuses on the development of computer programs that can access data and use it to learn for themselves.1 While AI represents the broader concept of machines being able to carry out tasks in an intelligent way, machine learning is a current application of AI based on the idea that we can give machines access to data, and they can use that data to learn for themselves.

whitePaper | August 26, 2022

Evolving data centers into intelligent hubs for digitized business processes poses numerous challenges for IT managers. Many organizations are already adopting hybrid IT concepts to make their data center operations more flexible. However, they also have to keep an eye on new requirements such as IoT, AI, blockchain, container technology as well as data security, legal regulations and climate change. How can all this be seamlessly integrated and managed? And, what will matter next for the data center of the future?

whitePaper | August 23, 2022

This white paper describes the features and benefits of a machine learning-based resource optimization solution that helps the Dell High End Storage Field Services Team perform capacity planning more efficiently and with the potential to optimize resource utilization and overtime.

whitePaper | July 28, 2022

Before the pandemic, the path to AI adoption used to be slow and steady. According to the survey of industryleading firms, only 48% of companies deemed AI and Big Data a source of innovation. In 2021, this number has climbed to almost 65 percent.

whitePaper | December 28, 2022

This document is published by the World Economic Forum as a contribution to a project, insight area or interaction. The findings, interpretations and conclusions expressed herein are a result of a collaborative process facilitated and endorsed by the World Economic Forum but whose results do not necessarily represent the views of the World Economic Forum, nor the entirety of its Members, Partners or other stakeholders.

whitePaper | November 24, 2022

High-profile examples of harm associated with algorithm failure and misuse have garnered significant public concern (e.g. manipulation of the democratic process, discriminatory practice in criminal justice sentencing, and bias against racial and gender categories in the labour market). The field of AI ethics refers to the literature and to the community of people interested in this space. One high-profile manifestation of this is the formation of specialist ethics councils and teams to deliberate on conundrums regarding the use, access and openness of platforms and technologies (such as social media and messaging apps, etc.). For instance, the banning of particular public figures as well as lay users for use of the services in a manner that is not acceptable has been a constant theme in the public debate.