Google is open-sourcing its new machine learning system behind Google Photos

But the technology is applicable to a number of other domains, as well, says Google.

If you’re interested, you can sift through Google TensorFlow here, although at the time of writing the link was not yet live.

Any computation that you can express as a computational flow graph, you can compute with TensorFlow.

Machine learning is cropping up with increasing frequency in a variety of areas, including enterprise software.

Google hasn’t been shy about sharing how it uses advanced neural networks (informally known as AI) in a few of its products. Google makes this happen with a machine learning system called TensorFlow, and today the company has chose to open source this platform so anyone around the world can use it for research and product development. It can’t even do things that a 4 year-old child can do, like recognize an object after only seeing it a couple of times. This will allow the community to tap into this technology and allow them to contribute through working code and not just research papers.

Google is also open-sourcing the product, stating it can have a much bigger impact outside of the company. And that can ultimately boost Google’s bottom line as the tech is integrated into more of its products and improved. Take a look at the video below for more details…

The engine has been used by the Google to improve speech recognition in the official Google app as well as forming the image search now available in Google Photos. Smart Reply reads the content of the email, then suggests short phrases at the bottom of the screen which you can use to reply. TensorFlow is said to be about twice as fast as DistBelief, and has much better scalability when compared to DistBelief.

DistBelief was narrowly focused on neural networks, hard to configure and tightly linked to Google’s internal infrastructure, making it “nearly impossible to share research code externally”, explained Jeff Dean, a senior Google Fellow, and Rajat Monga, technical lead, in a separate post on the Google Research blog.

TensorFlow was created to address those shortcomings.

This open source release of TensorFlow supports individual computers and smartphones.