Neuromorphic Computing

Neuromorphic Computing

Artificial intelligence: the third generation of neural networks

Neuromorphic Computing

Our research activities focus on improving the learning ability and intelligence of technical systems, whether in the manufacturing, automobile, robotics or mobile network industries. We rely on findings from the area of neurobiology and apply software methods from the field of artificial intelligence (AI) and the subarea of deep learning.

For information processing, we utilize so-called spiking neural networks (SNN), the third-generation of neural networks. The data between the information-processing units is coded in the form of pulses, similar to the human brain. Pulse-coded artificial neural networks make energy-efficient information processing possible, particularly via neuromorphic hardware.

We develop algorithms and software for highly energy-efficient neuromorphic hardware.

These activities will include

  • exploring the opportunities and limits of calculations with SNN-based calculations
  • porting conventional network algorithms over to SNNs and neuromorphic hardware
  • develop new learning methods for SNNs
  • create a software framework for learning from SNNs
  • design innovative robot experiments in closed loops with real and virtual robots, environments and SNN implementations from learning and decisions processes

More information

 Axel von Arnim

Your contact

Axel von Arnim

+49 89 3603522 538
vonarnim@fortiss.org

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