A bakery assistant who takes the bread from the shelf just to give it to his boss who then hands it over to the customer? Rather unlikely. Instead, both work at the same time to sell the baked goods. Similarly, computer programs are more efficient if they process data in parallel rather than to calculate them one after the other. However, most programs that are applied still work in a serial manner.
The neuromorphic chip containing silicon neurons which the researchers used for their data-classifying network.
Kirchhoff Institute for Physics, Heidelberg University
Scientists from the Freie Universität Berlin, the Bernstein Center Berlin and Heidelberg University have now refined a new technology that is based on parallel data processing. In the so-called neuromophic computing, neurons made of silicon take over the computational work on special computer chips. The neurons are linked together in a similar fashion to the nerve cells in our brain. If the assembly is fed with data, all silicon neurons work in parallel to solve the problem. The precise nature of their connections determines how the network processes the data. Once properly linked, the neuromorphic network operates almost by itself. The researchers have now designed a network–a neuromorphic “program”–for this chip that solves a fundamental computing problem: It can classify data with different features. It is able to recognize handwritten numbers, or may distinguish certain plant species based on flowering characteristics.
"The design of the network architecture has been inspired by the odor-processing nervous system of insects," explains Michael Schmuker, lead author of the study. "This system is optimized by nature for a highly parallel processing of the complex chemical world." Together with work group leader Martin Nawrot and Thomas Pfeil, Schmuker provided the proof of principle that a neuromorphic chip can solve such a complex task. For their study, the researchers used a chip with silicon neurons, which was developed at the Kirchhoff Institute for Physics of Heidelberg University.
Computer programs that can classify data are employed in various technical devices, such as smart phones. The neuromorphic network chip could also be applied in super-computers that are built on the model of the human brain to solve very complex tasks. Using their prototype, the Berlin scientists are now able to explore how networks must be designed to meet the specific requirements of these brain-like computer. A major challenge will be that not even two neurons are identical – neither in silicon nor in the brain.
The Bernstein Center Berlin is part of the National Bernstein Network Computational Neuroscience in Germany. With this funding initiative, the German Federal Ministry of Education and Research (BMBF) has supported the new discipline of Computational Neuroscience since 2004 with over 170 million Euros. The network is named after the German physiologist Julius Bernstein (1835-1917).Contact:
Weitere Informationen:http://biomachinelearning.net personal website Michael Schmuker
http://www.nncn.de National Bernstein Network Computational Neuroscience
Mareike Kardinal | idw
An AI that makes road maps from aerial images
18.04.2018 | Massachusetts Institute of Technology, CSAIL
Beyond the clouds: Networked clouds in a production setting
04.04.2018 | Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, DFKI
Study published in the journal ACS Applied Materials & Interfaces is the outcome of an international effort that included teams from Dresden and Berlin in Germany, and the US.
Scientists at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) together with colleagues from the Helmholtz-Zentrum Berlin (HZB) and the University of Virginia...
Novel highly efficient and brilliant gamma-ray source: Based on model calculations, physicists of the Max PIanck Institute for Nuclear Physics in Heidelberg propose a novel method for an efficient high-brilliance gamma-ray source. A giant collimated gamma-ray pulse is generated from the interaction of a dense ultra-relativistic electron beam with a thin solid conductor. Energetic gamma-rays are copiously produced as the electron beam splits into filaments while propagating across the conductor. The resulting gamma-ray energy and flux enable novel experiments in nuclear and fundamental physics.
The typical wavelength of light interacting with an object of the microcosm scales with the size of this object. For atoms, this ranges from visible light to...
Stable joint cartilage can be produced from adult stem cells originating from bone marrow. This is made possible by inducing specific molecular processes occurring during embryonic cartilage formation, as researchers from the University and University Hospital of Basel report in the scientific journal PNAS.
Certain mesenchymal stem/stromal cells from the bone marrow of adults are considered extremely promising for skeletal tissue regeneration. These adult stem...
In the fight against cancer, scientists are developing new drugs to hit tumor cells at so far unused weak points. Such a “sore spot” is the protein complex...
In an article that appears in the journal “Review of Modern Physics”, researchers at the Laboratory for Attosecond Physics (LAP) assess the current state of the field of ultrafast physics and consider its implications for future technologies.
Physicists can now control light in both time and space with hitherto unimagined precision. This is particularly true for the ability to generate ultrashort...
13.04.2018 | Event News
12.04.2018 | Event News
09.04.2018 | Event News
19.04.2018 | Materials Sciences
19.04.2018 | Physics and Astronomy
19.04.2018 | Physics and Astronomy