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Neuer Ansatz für energieeffiziente KI-Anwendungen

Neuer Ansatz für energieeffiziente KI-Anwendungen
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Wolfgang maassTu grazNetworks consumeMost energyBernhard lookoutNew design methodeSignals an importantComputer wolfgang maassStudents christophOptimised forTrillion accounting operationsNeuron sendsNeuron sends outJournal nature machineஓநாய் மாஸ்பெரும்பாலானவை ஆற்றல்

New approach found for energy-efficient AI applications

E-Mail IMAGE: The algorithm will be implemented on brain-inspired computing systems, like the spike-based SpiNNaker (pictured here). SpiNNaker is part of the Human Brain Project s EBRAINS research infrastructure. view more Credit: © Forschungszentrum Jülich Most new achievements in artificial intelligence (AI) require very large neural networks. They consist of hundreds of millions of neurons arranged in several hundred layers, i.e. they have very deep network structures. These large, deep neural networks consume a lot of energy in the computer. Those neural networks that are used in image classification (e.g. face and object recognition) are particularly energy-intensive, since they have to send very many numerical values from one neuron layer to the next with great accuracy in each time cycle.

Wolfgang maassTheoretical computer scienceGraz universityNature machineEuropean human brain projectTechnology engineering computer scienceComputer scienceTheory designElectrical engineering electronicsஓநாய் மாஸ்கோட்பாட்டு கணினி அறிவியல்க்ர்யாஸ் பல்கலைக்கழகம்இயற்கை இயந்திரம்ஐரோப்பிய மனிதன் மூளை ப்ராஜெக்ட்தொழில்நுட்பம் பொறியியல் கணினி அறிவியல்கணினி அறிவியல்