Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...

Chinese researchers harness probabilistic updates on memristor hardware to slash AI training energy use by orders of magnitude, paving the way for ultra-efficient electronics.

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Researchers are training neural networks to make decisions more like humans would. This science of human decision-making is only just being applied to machine learning, but developing a neural network ...

For about a decade, computer engineer Kerem Çamsari employed a novel approach known as probabilistic computing. Based on probabilistic bits (p-bits), it’s used to solve an array of complex ...

Anyone exploring technological advances in artificial intelligence (AI) will inevitably encounter spiking neural networks (SNNs) — the next step toward energy‑efficient real‑time AI. The difference ...

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...