THE CRITICAL ROLE OF SUPERCOMPUTING IN THE NEXT WAVE OF AI

whitePaper | March 30, 2022

Artificial Intelligence is one of the fastest growing technologies of the 21st century and accompanies us in our daily lives when interacting with technical applications. However, reliance on such technical systems is crucial for their widespread applicability and acceptance. The societal tools to express reliance are usually formalized by lawful regulations, i.e., standards, norms, accreditations, and certificates. Therefore, the TÜV AUSTRIA Group in cooperation with the Institute for Machine Learning at the Johannes Kepler University Linz, proposes a certification process and an audit catalog for Machine Learning applications.

whitePaper | June 22, 2022

Artificial intelligence (AI) and machine learning have revolutionized how organizations are using their data. Automated machine learning (AutoML) facilitates and improves the endto-end data science process. This process includes everything from preprocessing and cleaning the data, selecting and engineering appropriate features, tuning and optimizing the model, analyzing results, explaining and documenting the model, and of course, deploying it into production.

whitePaper | August 1, 2020

One of the first management funds in China, Fullgoal Fund overcame the need for massive data storage and support for large numbers of virtualized servers with a Nutanix hyperconverged infrastructure and enterprise cloud solution.

whitePaper | August 14, 2020

As consumers and customers, we are accustomed to easy, intuitive and superfast transactions driven by data. Therefore, businesses have the various challenges of managing and mining the data they produce and use, but also ensuring that their digital experience is 100% reliable for their customers — so the chain of trust is never broken.

whitePaper | January 28, 2022

Since more and more decisions that used to be made by humans are nowadays made either with the help of Artificial Intelligence (AI) or by AI alone, it is essential that the AI algorithms are “fair.” In this whitepaper, we discuss issues surrounding the fairness of AI applications, with a special focus on how it can be assessed independently and subsequently certified. We explain why an AI application cannot be classified – and subsequently certified – as “fair” or “unfair” in a general sense and propose an approach that makes it possible to classify it as “fair” or “unfair” under the (application)-specific definition of fairness.

whitePaper | July 28, 2022

Before the pandemic, the path to AI adoption used to be slow and steady. According to the survey of industryleading firms, only 48% of companies deemed AI and Big Data a source of innovation. In 2021, this number has climbed to almost 65 percent.