Demystifying 5G in Industrial IOT

whitePaper | July 10, 2020

There’s no arguing that preventing failures and accidents is critical for industry. Unexpected incidents can grind operations to a halt for extended periods of time and necessitate expensive repairs. Just 12 hours of downtime for an oil production platform could cost six to eight million dollars in lost production opportunity alone. A single day of grounding for a plane costs roughly four to five million dollars. Because of these disruptions, industrial sectors are always on the lookout for newer, better maintenance methods, and the approach on everyone’s lips right now is predictive maintenance. While everyone agrees on the name, there is less consensus on what it means or how to implement it. But to truly unlock the potential of predictive maintenance, it needs to be paired with artificial intelligence (AI) and machine learning (ML).

whitePaper | September 15, 2022

The concept of Artificial Intelligence (AI) and Machine Learning (ML) dates back to the 1950s with researchers trying to use machines to simulate human intelligence in machines. However, their use in the financial sector has been limited. With enhanced customer service and mounting cost pressures, financial institutions (FIs) have now started to look at AI as a possible solution for improving cost and operational efficiencies.

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 | June 9, 2022

Artificial Intelligence (AI) powered Analytics is taking data management to the next level for almost all industry sectors without having to rely on technical staff or data scientists. Technology is helping create blue ocean opportunities amidst red ocean realities.

whitePaper | November 29, 2022

Artificial intelligence has long since graduated from science fiction and speculative use cases to widespread and diverse development across fintech sectors. CB Insights reported that financings for AI startups showed continued robust activity through Q2 2022, despite changes in market sentiment from the exuberance of 2021.

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.