MA-AICS Archive – University of Klagenfurt

University meets Industry: Talents for Carinthia

“University meets Industry: Talents for Carinthia” is an event hosted by the Faculty of Technical Sciences (TEWI) and the Federation of Austrian Industries Carinthia. At the event, successful cooperation projects between university and industry will be presented. Students of technical degree programmes, employees of the Faculty, and Carinthian companies will have the opportunity to network in order to further strengthen their cooperation and lay the foundations for new partnerships. Read more →

“What astonishes me is how easily we humans are persuaded by content that is generated by a machine.”

Many of those following the current media discourse are left with a sense of alarmism: The message seems to be that advances being made in the development of artificial intelligence could cause the systems to spiral out of control. At the same time, experts are voicing concern about the potential influence of these technologies on the stability of democracies, given that images can be manipulated in a matter of seconds. We asked Wolfgang Faber, professor at the Department of Artificial Intelligence and Cybersecurity, for his take on the new AI tools and the state of research.

University of Klagenfurt develops Master of Artificial Intelligence for universities in Nigeria

The Department of Networked and Embedded Systems at the University of Klagenfurt is working with EU partner institutions to develop a Master of Science in Artificial Intelligence for universities in Nigeria as part of an EU-funded “EmbeddedAI” project.

As adaptable, robust and scalable as an anthill: New algorithms for more efficient factories

Production plants are highly complex systems. Identifying the optimal sequence of machines and production steps not only saves a lot of money, but also contributes to energy and resource efficiency. Using Infineon Technologies Austria AG as an example, researchers at Lakeside Labs GmbH and the University of Klagenfurt are developing new algorithms to improve the efficiency of factories.

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