Deep Learning in Academia

Interesting points made here. Since methods like deep learning are used for value and also hyped the results may not be widely shared.    But then the major players seem to be opening the methods and even their use to anyone.  Democratizing is very new. 

What’s Keeping Deep Learning In Academia From Reaching Its Full Potential?   by Scott Clark

Deep learning is gaining a foothold in the enterprise as a way to improve the development and performance of critical business applications. It started to gain traction in companies optimizing advertising and recommendation systems, like Google, Yelp, and Baidu. But the space has seen a huge level of innovation over the past few years due to tools like open-source deep learning frameworks–like TensorFlow, MXNet, or Caffe 2–that democratize access to powerful deep learning techniques for companies of all sizes.  Additionally, the rise of GPU-enabled cloud infrastructure on platforms like AWS and Azure has made it easier than ever for firms to build and scale these pipelines faster and cheaper than ever before. .... "