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More than 200 years ago, the scientist Alexander von Humboldt noted in his travel diaries that "everything is interconnectedness", when he was fascinated by nature and the phenomena observed. The view of nature has become much more detailed through the knowledge of phenomena and natural processes, which led to a more precise view of nature shaped by Humboldt. Technological progress and the artificial intelligence of highly developed computer systems are upsetting this view and changing the established world view through a new, unprecedented interaction between man and machinery. Thus we need digital axioms and comprehensive rules and laws for such autonomous acting systems that determine human interaction between cybernetic systems and biological individuals. This digital humanism should encompass our relationship to nature, our handling of the complexity and diversity of nature and the technological influences on society in order to avoid technical colonialism through supercomputers.
This paper describes the concept and some results of the project "Menschen Lernen Maschinelles Lernen" (Humans Learn Machine Learning, ML2) of the University of Applied Sciences Offenburg. It brings together students of different courses of study and practitioners from companies on the subject of Machine Learning. A mixture of blended learning and practical projects ensures a tight coupling of machine learning theory and application. The paper details the phases of ML2 and mentions two successful example projects.
Covert- and side-channels as well as techniques to establish them in cloud computing are in focus of research for quite some time. However, not many concrete mitigation methods have been developed and even less have been adapted and concretely implemented by cloud providers. Thus, we recently conceptually proposed C 3 -Sched a CPU scheduling based approach to mitigate L2 cache covert-channels. Instead of flushing the cache on every context switch, we schedule trusted virtual machines to create noise which prevents potential covert-channels. Additionally, our approach aims on preserving performance by utilizing existing instead of artificial workload while reducing covert-channel related cache flushes to cases where not enough noise has been achieved. In this work we evaluate cache covert-channel mitigation and performance impact of our integration of C 3 -Sched in the XEN credit scheduler. Moreover, we compare it to naive solutions and more competitive approaches.