Neural Network - “deep learning”

Most applications of deep learning use “convolutional” neural networks, in which the nodes of each layer are clustered, the clusters overlap, and each cluster feeds data to multiple nodes (orange and green) of the next layer. NeuroscienceNews.com image is credited to Jose-Luis Olivares/MIT.

Neural Networks Explained by Neuroscience News A look at the history, and the future, of neural networks and deep learning.Read more of this post Neuroscience News | April 17, 2017 at 7:49 am | Tags: deep learning, neural nets, Perceptrons, shallow networks | URL: http://wp.me/p4sXNK-apl Comment    See all comments

“There’s this idea that ideas in science are a bit like epidemics of viruses,” says Tomaso Poggio, the Eugene McDermott Professor of Brain and Cognitive Sciences at MIT, an investigator at MIT’s McGovern Institute for Brain Research, and director of MIT’s Center for Brains, Minds, and Machines. “There are apparently five or six basic strains of flu viruses, and apparently each one comes back with a period of around 25 years. People get infected, and they develop an immune response, and so they don’t get infected for the next 25 years. And then there is a new generation that is ready to be infected by the same strain of virus. In science, people fall in love with an idea, get excited about it, hammer it to death, and then get immunized — they get tired of it. So ideas should have the same kind of periodicity!”