Computer-based weather forecast: New algorithm outperforms mainframe computer systems

New algorithm solves complex problems more easily and more accurately on a personal computer while requiring less processing power than a supercomputer

The exponential growth in computer processing power seen over the past 60 years may soon come to a halt. Complex systems such as those used in weather forecast, for example, require high computing capacities, but the costs for running supercomputers to process large quantities of data can become a limiting factor. Researchers at Johannes Gutenberg University Mainz (JGU) and Università della Svizzera italiana (USI) in Lugano in Switzerland have recently unveiled an algorithm that can solve complex problems with remarkable facility – even on a personal computer.

Continue reading "Computer-based weather forecast: New algorithm outperforms mainframe computer systems"

Emergent AI Center welcomes eight new projects

The Emergent AI Center welcomes the following new projects:

  • Neural network-based approaches for multiscale modelling of topological defects
    Prof. Dr. Friederike Schmid, Dr. Karin Everschor-Sitte
  • Machine learning prediction of Odorant Receptor (OR)-ligand interactions: Chemical communication as the basis of swarm intelligence
    Prof. Dr. Miguel Andrade, Prof. Dr. Susanne Foitzik
  • Computational performance of autistic-like networks
    Prof. Dr. Martin Heine, Dr. Arthur F Bikbaev, Jun-Prof. Dr. Susanne Gerber
  • How emergent is the Brain?
    Prof. Dr. Heiko Luhmann, Jun-Prof. Dr. Maik Stüttgen, Prof. Dr. Illia Horenko
  • Application of machine learning algorithms to search for dark-matter signals in spectroscopic data
    Prof. Dr. Dmitry Budker, Prof. Dr. Stefan Kramer
  • Deep Learning of natural selection in population genomic data
    Dr. Yoan Diekmann, Prof. Dr. Joachim Burger
  • Repetitive DNA and the ‘C-value enigma’ of genomics
    Prof. Dr. Thomas Hankeln, Prof. Dr. Miguel Andrade
  • Learned Structures for Big Data in Bioinformatics
    Prof. Dr. Bertil Schmidt, Prof. Dr. Thomas Hankeln, Prof. Dr. Andreas Hildebrandt

For more information on the individual projects, please take a look at the research part of the website

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Seminar on Reservoir Computing by Prof. Dr. Herbert Jaeger

On June 4th of 2019 Prof. Dr. Herbert Jaeger, pioneer in the field of Reservoir Computing, presented a seminar at the Johannes Gutenberg University Mainz (JGU). Reservoir Computing is an alternative machine learning approach for Recurrent Neural Networks which is in many ways complementary to deep learning.  The talk gave an introduction to the basic principles and variants of Reservoir Computing. Some illustrative examples were presented.

Announcement for Prof. Dr. Jaeger seminar

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The power of randomization: Magnetic skyrmions for novel computer technology

First steps towards a practical application for magnetic skyrmions

Researchers at Johannes Gutenberg University Mainz (JGU) have succeeded in developing a key constituent of a novel unconventional computing concept. This constituent employs the same magnetic structures that are being researched in connection with storing electronic data on shift registers known as racetracks. Continue reading "The power of randomization: Magnetic skyrmions for novel computer technology"

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Funding for New Research Center

Researchers from the University of Mainz at the Institutes of Physics, Biology, Computer Science and the Max-Planck-Institute for Polymer Research receive funding from the Carl-Zeiss-Stiftung for an interdisciplinary research center on the topic "Algorithmic Intelligence as an Emergent Phenomenon".

The project is part of the funding program Durchbrüche 2018 from the Carl-Zeiss-Stiftung. You can find all funded projects from 2018 on the foundation's website [in German].

Link to the press release

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