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Safe AI -- How is this Possible?
Ttraditional safety engineering is coming to a turning point moving from deterministic, non-evolving systems operating in well-defined contexts to increasingly autonomous and learning-enabled AI systems which are acting in largely unpredictable operating contexts.
Systems Challenges for Trustworthy Embodied Systems
We are arguing that traditional systems engineering is coming to a climacteric from embedded to embodied systems, and with assuring the trustworthiness of dynamic federations of situationally aware, intent-driven, explorative, ever-evolving, largely non-predictable, and increasingly autonomous embodied systems in uncertain, complex, and unpredictable real-world contexts.
Knowledge as Invariance -- History and Perspectives of Knowledge-augmented Machine Learning
This white paper provides an introduction and discussion of this emerging field in machine learning research.
