EDGE COMPUTING INDEX: FROM EDGE TO ENTERPRISE

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 | May 9, 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 | July 20, 2022

The growing diversity of actors and circumstances involved in AI/ML deployment makes establishing a set of ethical participatory practices especially difficult for this field. Even among practitioners working at the same organization, there can be substantial differences in both their knowledge about how AI/ML systems were created or will be used and their ability to incorporate inclusive practices. Additionally, the greater availability of AI development platforms, including “no-code” platforms, means that algorithmic models can be deployed without having deep expertise, expanding the number of circumstances automated systems are deployed in. This means many more instances where automated systems are being deployed without consideration of how the algorithms were developed, the provenance of the datasets and nature of the bias on which they were trained and tested, and the ethical implications of their development and deployment.

whitePaper | October 18, 2022

Tachyum Prodigy is the industry’s first universal processor, unifying the functionality of CPU, GPU, and TPU into a single monolithic package. Prodigy’s revolutionary new architecture provides 6x more raw performance on AI training and inference workloads than the industry’s highest performing GPU, and up to 10x performance at the same power.

whitePaper | January 10, 2020

Instead of following a set of rote, preprogrammed instructions, AI enables machines to learn, and then “act,” on information. Your voice-activated phone, technologies such as speech and image recognition, autonomous vehicles, the smart devices in your home—all of these advances were made possible by AI technology. AI also marks a fundamental advancement in critical, often time-consuming, business processes. It’s poised to dramatically enhance human decision-making and improve an organization’s ability to make predictions, automate business practices, and optimize logistics.

whitePaper | September 12, 2022

Artificial intelligence is currently attracting considerable interest and attention from industry, researchers, governments as well as investors, who are pouring record amounts of money into the development of new machine learning technologies and applications.