The Complete Cloud Native Security Platform

whitePaper | January 4, 2022

When people hear AI they often think about sentient robots and magic boxes. AI today is much more mundane and simple—but that doesn’t mean it’s not powerful. Another misconception is that high-profile research projects can be applied directly to any business situation. AI done right can create extreme return on investments (ROIs)—for instance through automation or precise prediction. But it does take thought, time and proper implementation. We have seen that success and value generated by AI projects is increased when there is a grounded understanding and expectation of what the technology can deliver from the C-suite down.

whitePaper | October 18, 2022

The term Artificial Intelligence for IT Operations (AIOps) combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.

whitePaper | August 26, 2022

Evolving data centers into intelligent hubs for digitized business processes poses numerous challenges for IT managers. Many organizations are already adopting hybrid IT concepts to make their data center operations more flexible. However, they also have to keep an eye on new requirements such as IoT, AI, blockchain, container technology as well as data security, legal regulations and climate change. How can all this be seamlessly integrated and managed? And, what will matter next for the data center of the future?

whitePaper | June 28, 2022

Questions touching on AI ethics and fairness are becoming more mainstream. In recent years we have seen greater public consciousness of what was once a relatively obscure academic issue. This includes the close attention paid to the use of an algorithm to determine 2020 A-levels by the Office of Qualifications and Examinations Regulation (or “Ofqual”).

whitePaper | September 22, 2021

The value of conversational AI is clear—meaning it’s time to take the next step and begin setting specific goals if you want to see real returns on your investment. Access this beginner’s guide to conversational AI to learn important industry terms and explore the questions you need to be asking as you explore different solutions.

whitePaper | August 6, 2020

The purpose of any data acquisition system is to gather useful measurement data for characterization, monitoring, or control. The specific parameters of your application will dictate the resolution, accuracy, channel count, and speed requirements of a data acquisition system. A wide assortment of data acquisition components and solutions is available on the market, including low-cost USB modules, benchtop data loggers, and large channel systems. Before you start your search for a data acquisition solution, carefully analyze your application requirements to understand how much capability and performance you need to purchase.