Nature inspires Oak Ridge National Laboratory algorithms for neuromorphic processors

A spiking neural network depiction
A spiking neural network depiction in which input neurons (line of yellow spheres lower left) and output neurons (red, upper right) are linked by hidden neurons (teal) and synapses (arrows). The excitatory synapses (orange arrows) highlight pathways where information is more likely to travel, while data is less likely to travel along inhibitory synapses (blue arrows). White areas highlight spikes and firing neurons. This spiking neural network was trained to classify high energy physics data. (Visualization: Catherine Schuman/Oak Ridge National Laboratory and Margaret Drouhard/University of Washington.)

Her surroundings have inspired Catherine (Katie) Schuman’s career. Now a research scientist at the Department of Energy’s Oak Ridge National Laboratory, just 30 miles from where she grew up, Schuman works at the forefront of neuromorphic computing, building artificial intelligence algorithms for processors that mimic the brain’s form and function.

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