Building a Wireless Network on WiMAX

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 | October 20, 2022

Telecoms need to be able to incorporate new technologies and next-generation connectivity such as 5G to customers and end users.

whitePaper | July 16, 2020

Is cloud computing becoming the norm? As part of the digital offensives by many companies, cloud infrastructures are fast becoming a crucial technology driver and success factor for innovative business models and digital products. The growing interest in the Internet of Things and machine learning sent the adoption rate of the cloud soaring at numerous companies. Now, it is a question of “how” rather than “whether” cloud services can be used successfully at German companies.

whitePaper | January 5, 2020

Machine learning (ML) is an application of artificial intelligence (AI) that allows systems to automatically learn and improve from exposure to more data without being explicitly programmed. ML focuses on the development of computer programs that can access data and use it to learn for themselves.1 While AI represents the broader concept of machines being able to carry out tasks in an intelligent way, machine learning is a current application of AI based on the idea that we can give machines access to data, and they can use that data to learn for themselves.

whitePaper | May 20, 2021

AI has become a strategic imperative. Early adopters are achieving massive returns, while others risk falling behind. Yet, with AI knowledge and resources scarce, most companies cannot copy the FAANG approach. Even if their vast resources were more readily available, it’s hard to reboot an organization without disrupting the bottom line. Most executives need to work with the resources available — their existing people, processes, and technology.

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.