Google Open Sources their Machine Learning

Have seen a demo of an earlier version of this.  Was impressed by the visual approach, which can lead to better understanding by decision makers.  Recall we also looked at similar approaches for visual recognition and analysis.    Also emphasizes the sharing of application research, and its implementation in real world problems. Google says they have used these libraries in most all of their systems.   More will follow here  >

TensorFlow - Google’s latest machine learning system, open sourced for everyone
// Official Google Research Blog  (Includes introductory video)

Posted by Jeff Dean, Senior Google Fellow, and Rajat Monga, Technical Lead

Deep Learning has had a huge impact on computer science, making it possible explore new frontiers of research and to develop amazingly useful products that millions of people use every day. Our internal deep learning infrastructure DistBelief, developed in 2011, has allowed Googlers to build ever larger neural networks and scale training to thousands of cores in our datacenters. We’ve used it to demonstrate that concepts like “cat” can be learned from unlabeled YouTube images, to improve speech recognition in the Google app by 25%, and to build image search in Google Photos. DistBelief also trained the Inception model that won Imagenet’s Large Scale Visual Recognition Challenge in 2014, and drove our experiments in automated image captioning as well as 
DeepDream.   ... " 

" ... TensorFlow has extensive built-in support for deep learning, but is far more general than that -- any computation that you can express as a computational flow graph, you can compute with TensorFlow (see some examples). Any gradient-based machine learning algorithm will benefit from TensorFlow’s auto-differentiation and suite of first-rate optimizers. And it’s easy to express your new ideas in TensorFlow via the flexible Python interface. ... " 

More on this, including decription of a test, and in Wired.

" ...  It’s open sourcing that engine, freely sharing the underlying code with the world at large. This software is called TensorFlow, and in literally giving the technology away, Google believes it can accelerate the evolution of AI. Through open source, outsiders can help improve on Google’s technology and, yes, return these improvements back to Google.

“What we’re hoping is that the community adopts this as a good way of expressing machine learning algorithms of lots of different types, and also contributes to building and improving [TensorFlow] in lots of different and interesting ways,” says Jeff Dean, one of Google’s most important engineers and a key player in the rise of its deep learning tech. ... "