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whitePaper | June 28, 2022

Questions touching on AI ethics and fairness are becoming more mainstream. In recent years we have seen greater public consciousness of what was once a relatively obscure academic issue. This includes the close attention paid to the use of an algorithm to determine 2020 A-levels by the Office of Qualifications and Examinations Regulation (or “Ofqual”).

whitePaper | January 20, 2022

Machine learning (ML) algorithms are moving to the IoT edge due to various considerations such as latency, power consumption, cost, network bandwidth, reliability, privacy and security. Hence, there is an increasing interest in developing neural network (NN) solutions to deploy them on low-power edge devices such as the Arm Cortex-M microcontroller systems. To enable that, we present CMSIS-NN, an open-source library of optimized software kernels that maximize the NN performance on Cortex-M cores with minimal memory footprint overhead. We further present methods for NN architecture exploration, using image classification on CIFAR-10 dataset as an example, to develop models that fit on such constrained devices.

whitePaper | August 16, 2020

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whitePaper | December 22, 2022

Contact centres are often viewed as cost drivers rather than business drivers. This is understandable, when you consider that differentiation efforts in this space have often struggled to be sustainable from a cost or staffing perspective. Figuring out the formula of investment to increased income is helped when you have an experienced guide to shorten your journey. Read on to get the benefit of our two companies’ experience, multiplied by hundreds of clients.

whitePaper | September 23, 2022

It’s been several years since organizations began adopting artificial intelligence (AI) to improve their business; few have come close to mastering its existing capabilities. A small number of organizations in our research aim to become AI-driven—a status we define as AI and machine learning underpinning almost everything the enterprise does—by 2025. However, this elite group—who we term “AI leaders”1—as well as the many others looking simply to embed AI more firmly in the enterprise foundations face formidable challenges to achieving their objectives.

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