SD-WAN: Enhancing the Traditional WAN for the Future

whitePaper | June 29, 2022

The Responsible AI Institute (RAII) is developing one of the world’s first responsible AI certification programs. The RAII Certification Program is aligned with emerging global AI laws and regulations, internationally agreed-upon AI principles, research, emerging best practices, and human rights frameworks.

whitePaper | August 9, 2020

The payments industry is going through a period of massive disruption. Consumers increasingly expect a fast, easy payment process, coupled with immediate, uninterrupted access to account information and services.

whitePaper | October 20, 2022

The digital evolution of the financial services (FS) industry is heavily reliant on having quality information and analytics to deliver services to customers and manage operations in an efficient and risk-appropriate manner.

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 | June 22, 2022

Artificial intelligence (AI) and machine learning have revolutionized how organizations are using their data. Automated machine learning (AutoML) facilitates and improves the endto-end data science process. This process includes everything from preprocessing and cleaning the data, selecting and engineering appropriate features, tuning and optimizing the model, analyzing results, explaining and documenting the model, and of course, deploying it into production.

whitePaper | December 29, 2022

In our modern world, taking advantage of Artificial Intelligence (AI) to gain insights from data is becoming more prevalent day by day. Graphical Processing Unit (GPU) systems use multiple cores to perform parallel processing, running select workloads to decrease processing times. Compared to GPUs, Central Processing Units (CPUs) have fewer cores; previously, this resulted in less capacity for parallelized processing. To move beyond this limitation, Intel has released new hardware that runs typical AI mathematical computations more efficiently on the CPU, and has also released libraries with hardware optimizations that enable an additional increase in performance.