Dec. 7, 2023, 4:19 p.m. |

News on Artificial Intelligence and Machine Learning techxplore.com

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.

algorithm analog computer sciences deep learning development digital enabling epfl hardware network networks neural network neural networks power researchers train training

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

AI Engineering Manager

@ M47 Labs | Barcelona, Catalunya [Cataluña], Spain