Training algorithm breaks barriers to deep physical neural networks
EPFL 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 hardware. With their ability to process vast amounts of data through algorithmic ‘learning’ rather than traditional programming, it often seems like the potential of deep …