Reverse-engineering the brain to improve machine learning

Reverse-engineering the brain to improve machine learningBy Derek Major Feb 08, 2016 Researchers are working to reverse-engineer how the brain’s visual system processes information in hopes of advancing machine learning algorithms and computer vision. The Machine Intelligence from Cortical Networks (MICrONS) research program seeks to unlock the brain’s learning methods in an effort to make computers process information more like humans do. The five-year, $12 million research project funded by the Intelligence Advanced Research Projects Activity are will be led by Tai Sing Lee, professor in the computer science department at Carnegie Mellon University and the Center for the Neural Basis of Cognition. The researchers will attempt to improve the performance of neural networks. Currently, man-made neural nets process information in one direction, from input nodes to output nodes. But…

Link to Full Article: Reverse-engineering the brain to improve machine learning

Pin It on Pinterest

Share This

Join Our Newsletter

Sign up to our mailing list to receive the latest news and updates about and the Informed.AI Network of AI related websites which includes Events.AI, Neurons.AI, Awards.AI, and Vocation.AI

You have Successfully Subscribed!