The reality of self-driving cars and autonomous public transport is almost upon us. In Karlsruhe, three autonomous buses have been running since April. The buses don't run specific routes, rather, they can be ordered to certain places. Back in April, the city of Karlsruhe welcomed Vera, Ella and Anna to its streets. These are the names of three autonomous e-buses, which are part of a project funded by the Ministry for Transport.
Research, development, and production of novel materials depend heavily on the availability of fast and at the same time accurate simulation methods. Machine learning, in which artificial intelligence (AI) autonomously acquires and applies new knowledge, will soon enable researchers to develop complex material systems in a purely virtual environment. How does this work, and which applications will benefit? In an article published in the Nature Materials journal, a researcher from Karlsruhe Institute of Technology (KIT) and his colleagues from Göttingen and Toronto explain it all. Digitization and virtualization are becoming increasingly important in a wide range of scientific disciplines.
Matthias Feurer is a doctoral candidate at the Machine Learning Lab at the University of Freiburg, Germany. His research focuses on automated machine learning, hyperparameter optimization, and meta-learning. He is actively involved in developing open-source software for AutoML and is the maintainer and founder of Auto-sklearn and OpenML-Python. Matthias is a founding member of the Open Machine Learning Foundation, gave AutoML tutorials at GCPR and the ECMLPKDD summer school, and co-organized the AutoML workshop in 2019 and 2020. Furthermore, he was part of the winning team of the 1st&2nd AutoML challenges and the BBO challenge@NeurIPS 2020.
An intelligent camera system for quantifying surface defects on ball screws sounds like an exciting project. FUENF-G wanted to find out details about the project from the responsible academic staff member at the Institute of Production Engineering at the Karlsruhe Institute of Technology, Tobias Schlagenhauf, M.Sc. FUENF-G: Mr. Schlagenhauf, your work seems quite elaborate, what is your motivation? What economic potential do you see for this monitoring? Further economic potential, although not directly quantifiable, arises if the methodology is transferred to other areas of production.
Amita Kapoor is an Associate Professor in the Department of Electronics, SRCASW, University of Delhi and has been actively teaching neural networks and artificial intelligence for the last 20 years. She completed her masters in Electronics in 1996 and Ph.D. in 2011, during Ph.D. she was awarded a prestigious DAAD fellowship to pursue a part of her research work in Karlsruhe Institute of Technology, Karlsruhe, Germany. She was awarded the Best Presentation Award at the Photonics 2008 international conference. She is an active member of ACM, AAAI, IEEE, and INNS. She has co-authored four books including the best-selling book "Deep learning with TensorFlow2 and Keras" with Packt Publications.
Charles Ess is professor emeritus at the University of Oslo. He researches at the intersections of philosophy, computational technologies, applied ethics, comparative philosophy and religion, and media studies, with particular focus on: research ethics, Digital Religion, and virtue ethics in media and communication, specifically social robots.
Despite their incorporeal form, memories have a way of becoming a very real part of our identity, like the pattern of freckles on your face or your favorite jacket might. Remembering a childhood friend while gazing off at a field of dandelions may be pleasant, but being sucked back into a bad memory -- a difficult breakup or a traumatizing loss -- can be unbearable. But what if, a la Eternal Sunshine of the Spotless Mind, we could simply erase those memories? It's something being explored, but Philipp Kellmeyer, a neurologist and head of the Neuroethics & A.I. Ethics Lab at the University of Freiburg, has several concerns. High among them is identity.
A robotic elephant trunk that uses artificial intelligence to mimic some aspects of brains could lead to snake-like machines that can roam and adapt to new tasks. Sebastian Otte at the University of Tubingen in Germany and his colleagues created a 3D-printed robot trunk from segments that each include several motors driving gears that tilt up to 40 degrees in two axes. The trunk can bend, but also elongate or shorten. The team created a trunk with 10 segments, but they say the length could be doubled with more powerful motors.
This post contains a list of the AI-related seminars that are scheduled to take place between 14 April and 31 May 2021. All events detailed here are free and open for anyone to attend virtually. Machine learning for medical image analysis and why clinicians are not using it Speaker: Christian Baumgartner (Tuebingen University) Organised by: Tuebingen University Zoom link is here. Real-time Distributed Decision Making in Networked Systems Speaker: Na Li (Harvard) Organised by: Control Meets Learning Join the Google group to find out how to register. The limits of Shapley values as a method for explaining the predictions of an ML system Speaker: Suresh Venkatasubramanian (University of Utah) Organised by: Trustworthy ML Join the mailing list for instructions on how to sign up, or check the website a few days beforehand for the Zoom link.
Drought, heat, and pest infestation: Climate change is threatening forests in Germany and represents a big challenge in forest management. A joint project of Karlsruhe Institute of Technology (KIT) and EDI GmbH, a spinoff of KIT, now provides support. Together with partners in the forestry sector, they are developing the EDE 4.0 assistance system. Based on artificial intelligence (AI), it helps foresters preserve and sustainably manage forests. Climate change also affects forests in Germany.