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 that aligns memristor hardware's noisy updates with neural network training, ...

Measurement results of the array of three-terminal-based electrochemical memory devices, demonstrating excellent characteristics in both cycle and device-to-device scatter, well above the requirements ...

Real data can be hard to get, so researchers are turning to synthetic data to train their artificial intelligence systems. On a sunny day in late 1987, a Chevy van drove down a curvy wooded path on ...

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.