Strategically Achieving Multicloud Success

whitePaper | February 17, 2022

Massive amounts of data are being created driven by billions of sensors all around us such as cameras, smart phones, cars as well as the large amounts of data across enterprises, education systems and organizations. In the age of big data, artificial intelligence (AI), machine learning and deep learning deliver unprecedented insights in the massive amounts of data.

whitePaper | March 22, 2023

Artificial intelligence is increasingly becoming a part of our everyday lives, whether at home, in industry or in the public sector. The technology poses risks, but also opens up new opportunities. This presents the institutions in Brussels with the challenge of finding a balance between innovation and regulation for AI in the EU.

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 | January 11, 2023

Improving the trustworthiness of artificial intelligence (AI) systems is a shared priority for the private and public sectors, as indicated by prolific research and guidelines in recent years.

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 | 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.