AI Adoption: Is Your Firm Ready?

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 | December 30, 2022

The technological development of artificial intelligence (AI) is proceeding rapidly, with investment in AI-based solutions dramatically increasing across the globe. Europe is no exception.

whitePaper | August 18, 2020

This year, back to school for college students means more than just buying supplies, finding the right dorm and making sure to get into the proper classes. The COVID-19 pandemic has changed the annual fall ritual into one where campuses need to make sure they are safe from infection while providing a healthy environment for learning, growth and community.

whitePaper | June 7, 2022

Telecoms need to be able to incorporate new technologies and next-generation connectivity such as 5G to customers and end users. To achieve these ambitious goals, they need to optimize their networks – make them more intelligent if you will. Some of the tools needed include artificial intelligence (AI), machine learning (ML) and artificial intelligence operations (AIOps). This document will explore what intelligent networking means to telecoms, vendors and customers, and how AI and ML technologies and tools can be used, the cultural shifts the industry needs to make it a success, and what to bear in mind when deploying machine learning across a telecom network.

whitePaper | May 15, 2023

The future of AI is hybrid. As generative AI adoption grows at record-setting speeds1 and drives higher demand for compute,2 AI processing must be distributed between the cloud and devices for AI to scale and reach its full potential – just like traditional computing evolved from mainframes and thin clients to today’s mix of cloud and edge devices. A hybrid AI architecture distributes and coordinates AI workloads among cloud and edge devices, rather than processing in the cloud alone. The cloud and edge devices, such as smartphones, vehicles, PCs, and IoT devices, work together to deliver more powerful, efficient, and highly optimized AI.

whitePaper | November 23, 2022

Over the last four decades, the information technology industry has grown from about $50 billion globally in 1980 to more than $4 trillion. During this time, the IT industry has experienced the transition from mainframe computing to minicomputers, to personal computing, to internet computing, and to handheld computing.