Resilience is a key ingredient for lifting cars, industrial manufacturing and medical devices to the next level. It is far more than a fancier synonym of dependability. And the aspect that resilience is standing for is essential for building cognitive systems. That's why resilience is the focus of a new series on the Safe Intelligence Blog. In the first part, we will look behind the term and clarify why resilience is so important and why it is more than just a synonym for dependability.

Software development is a comparatively young, but complex and quickly evolving field. One of the more recent additions to the common portfolio of software architects is cloud technologies. In general terms, cloud technologies decouple software and the resources required for running. This allows services provided by the software to be quickly scaled according to demand. Nevertheless, there are several pitfalls that can be encountered when integrating cloud technologies into your software architecture.

Striving for excellence in scientific research on trustworthy Artificial Intelligence (AI), Dr. Narges Ahmidi also aims to encourage young female scientists to enter science and become leaders.

Safety will be the topic of focus at Fraunhofer IKS from September to November. Three events with different focal points will address the topic of safety in connection with complex software systems in various industries, primarily autonomous cognitive systems.

There are still a number of technical and regulatory obstacles to overcome before autonomous cars are ready for mass production. But when it comes to rail transport, things are much further ahead. Self-driving trains are already a common mode of transport. But how does autonomous driving on rails work?

22 abstracts were submitted for this year’s Safetronic conference (November 8–9, 2022), with the Program Committee selecting the best of them. Simon Fürst, Cooperation Management Automated Driving at BMW Group, Munich, and Conference Co-chair, explains the topics Safetronic will focus on as well as the highlights visitors can expect.

While many current CDS expert systems (Clinical Decision Support) in laboratories are being criticized due to difficulty in scaling, constant review from the medical perspective and limited data cases, artificial intelligence (AI) has become a highly plausible alternative. »Safe Intelligence for Laboratories«, a webinar hosted by Fraunhofer IKS, focused on the cases and challenges of AI in laboratories from the perspectives of both industry and patients.

Neural networks are not robust. The development of reliable predictors requires systematic methods to both assess their quality and to gain confidence in their correctness. Quantum computing can provide assistance here.

Artificial intelligence (AI) offers a lot of potential for Industrie 4.0, but there are technological barriers that make it more difficult to implement. Researchers at Fraunhofer IKS are developing a framework to support and optimize the data and AI life cycle. This will significantly increase the scope of value creation provided by AI.

How can intelligent systems learn to perform tasks – and do so simply by interacting with their environment? This is the subject of reinforcement learning, a subfield of machine learning. Problems occur primarily when situations arise that the system is not yet familiar with.