Training algorithm breaks barriers to deep physical neural networks: Research

Washington DC [US], December 11 (ANI): EPFL researchers created an algorithm that can train an analog neural network just as accurately as a digital one, allowing for 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 neural net