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whitePaper | November 1, 2019

Artificial Intelligence is becoming an ever more important part of our lives. Many of us are already familiar with its everyday applications, such as decluttering our inboxes with spam filters or receiving personalised shopping recommendations. Yet, whether it is powering a new generation of self-driving cars, guarding us against fraud or helping doctors better diagnose health conditions, AI’s transformational abilities are being felt in increasingly ubiquitous and innovative ways.

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 | August 10, 2020

Digital innovation is happening fast — and there’s no slowing it down. Financial institutions are shifting priorities as third-party apps and services become more prevalent among consumers. Now, staying connected is no longer just an option, it’s critical to achieving success and staying relevant. mx.com | 1 But moving fast isn’t as easy as it sounds. There’s a fine line that financial institutions have to balance when it comes to innovating quickly to give their customers the experiences they’ve come to expect and ensuring their data remains safe and secure. As data sharing and connected integration ecosystems become the new norm, here are three challenges many financial institutions are facing.

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 | December 22, 2022

Machine learning, one of the key building blocks of AI, has been a part of the technological world since the 1950s, when the earliest programmers asked computers to make sense of large sets of data. Programmers have increasingly refined the ability of machines to study data in order to detect patterns that allow computers to then organise information, identify relationships, make predictions and detect anomalies. Today, modern applications of AI have already given us self-driving cars and virtual assistants and have helped us detect fraud and manage resources like electricity more efficiently. Sectors as diverse as retail, sports, banking, manufacturing and healthcare have all found applications for machine learning and AI.

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.