5 ways get ready machine learning

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 | December 14, 2022

Data science is Vectra AI’s north star. We have always believed that data science and AI, if used properly, can transform our fight against cyberattacks and give an edge to defenders. However, not all AI is the same.

whitePaper | September 23, 2022

It’s been several years since organizations began adopting artificial intelligence (AI) to improve their business; few have come close to mastering its existing capabilities. A small number of organizations in our research aim to become AI-driven—a status we define as AI and machine learning underpinning almost everything the enterprise does—by 2025. However, this elite group—who we term “AI leaders”1—as well as the many others looking simply to embed AI more firmly in the enterprise foundations face formidable challenges to achieving their objectives.

whitePaper | July 20, 2022

The growing diversity of actors and circumstances involved in AI/ML deployment makes establishing a set of ethical participatory practices especially difficult for this field. Even among practitioners working at the same organization, there can be substantial differences in both their knowledge about how AI/ML systems were created or will be used and their ability to incorporate inclusive practices. Additionally, the greater availability of AI development platforms, including “no-code” platforms, means that algorithmic models can be deployed without having deep expertise, expanding the number of circumstances automated systems are deployed in. This means many more instances where automated systems are being deployed without consideration of how the algorithms were developed, the provenance of the datasets and nature of the bias on which they were trained and tested, and the ethical implications of their development and deployment.

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 | 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.