Connecting Financial Services’ Hybrid IT Infrastructure

whitePaper | August 9, 2022

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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 | 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 | November 25, 2019

In 2020, artificial intelligence will no longer be a vision of the future, but a tangible reality: language agents such as Siri, Cortana or Alexa are already pervading our everyday lives. The smart assistants play our favorite music, make restaurant suggestions, recommend films, identify the fastest route to our destination and steer our car better into the parking lot than we could. We use artificially intelligent systems that are becoming more and more a matter of course both at home and at work. AI systems have slipped into our everyday lives and they are here to stay.

whitePaper | November 1, 2021

Robotics, automation, Internet of Things (IoT), and data are not new in manufacturing. Manufacturing is one of the most data-rich and first industries piloting artificial intelligence at the edge. It’s been estimated, however, that about 95% of all industrial data goes unused. The reason? Legacy equipment and operational systems that tend to be proprietary and siloed are incapable of communicating with each other.

whitePaper | November 10, 2019

Large enterprises need to implement AI solutions quickly and efficiently, but many don’t have the right people, process and technology. Firms can accelerate progress to AI maturity through use of a robust workbench, an operating model built on a data science-led pyramid of skills, and pre-built solutions when data complexity and talent scarcity are too big a challenge.