Scientists take challenge of developing functional microdevices for direct access to the brain, spinal cord, eye and other delicate parts of human body
A tiny robot that gets into the human body through the simple medical injection and, passing healthy organs, finds and treats directly the goal – a non-operable tumor… Doesn’t it sound at least like science-fiction? To make it real, a growing number of researchers are now working towards this direction with the prospect of transforming many aspects of healthcare and bioengineering in the nearest future. What makes it not so easy are unique challenges pertaining to design, fabrication and encoding functionality in producing functional microdevices.
Bernhard Schölkopf joined the initiative "Latest Thinking"
Exoplanets are planets beyond our own solar system. Since they do not emit much light and moreover are very close to their parent stars they are difficult to detect directly. When searching for exoplanets, astronomers use telescopes to monitor the brightness of the parent star under investigation: Changes in brightness can point to a passing planet that obstructs part of the star’s surface. The recorded signal, however, contains not only the physical signal of the star but also systematic errors caused by the instrument. As Bernhard Schölkopf explains in this video, this noise can be removed by comparing the signal of the star of interest to those of a large number of other stars. Commonalities in their signals might be due to confounding effects of the instrument. Using machine learning, these observations can be used to train a system to predict the errors and correct the light curves.
Guest edited by Jeannette Bohg, Matei Ciocarlie, Javier Civera, Lydia E. Kavraki.
... new big data methods have the potential to allow robots to understand and operate in significantly more complex environments than was possible even in the recent past. This should lead to a qualitative leap in the performance and deployability of robotics in a wide array of practical applications and real settings.
Science and industry form one of Europe's largest research partnerships in artificial intelligence
Intelligent systems will shape our future: they could drive us as autonomous cars, help us out in the home on a daily basis or perform medical services as tiny robots. An initiative by the Max Planck Society and the Max Planck Institute for Intelligent Systems in the Stuttgart-Tübingen area is bringing together partners from science and industry to establish Cyber Valley where systems can be developed that will be capable of performing such feats. Winfried Kretschmann, Minister-President of Baden-Württemberg, Theresia Bauer, Minister of Science in Baden-Württemberg and Martin Stratmann, President of the Max Planck Society, together with the other project participants, have launched the initiative on Thursday, 15 December 2016 in Stuttgart's Neues Schloss.
An upcoming workshop in June 2017 will explore applications of probabilistic numerics.
A recent meeting at the Leibniz Centre for Computer Science highlights the ongoing significance of analytic nonparametric models for machine learning.
CYBATHLON Championship for Athletes with Disabilities
Zürich. On October 8, 2016, a collaboration of the research group "Brain-Computer-Interfaces" at the MPI-IS and the "Autonomous Systems Lab" at the TU Darmstadt will send a joint team into the Brain-computer-Interface Race at the Cybathlon 2016 in Zurich. The so called Athena-Minerva team consists mainly of computer science students of bachelor and master-level at the Technical University Darmstadt. They are interested in "Machine Learning", signal processing and especially for Brain-Computer-Interfaces (BCI). The team is headed by Moritz Grosse-Wentrup from MPI-IS and by Jan Peters, TU Darmstadt. The pilot is Sebastian Reul.