Developing Standards for Artificial Intelligence

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.

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 | 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 | August 30, 2022

Traditional database management systems have become more essential than ever, as data volume, velocity, and variety all increase at breakneck speed. But the harsh truth is that legacy database management systems were never designed for a digital-first business climate shaped by such factors as cloud computing, pervasive mobility, microservices, new data sources, and cloud-native application development.

whitePaper | July 29, 2022

China is following a national strategy to lead the world in artificial intelligence by 2030, including by pursuing “general AI” that can act autonomously in novel circumstances. Open-source research identifies 30 Chinese institutions engaged in one or more of this project‘s aspects, including machine learning, brain-inspired AI, and brain-computer interfaces. This report previews a CSET pilot program that will track China’s progress and provide timely alerts.

whitePaper | August 12, 2020

Denodo Platform 8.0 is a significant step forward in realizing the vision of a logical data fabric as a unified data delivery platform that bridges the gap between IT infrastructure and consuming business applications. Denodo Platform 8.0 is based on the same data virtualization technology that Denodo has developed over the years to unify data integration, metadata management, security, and data governance. Denodo Platform 8.0 greatly accelerates the delivery of governed data to all data consumers, in the most appropriate format for each, across multiple distributed heterogeneous systems