Google Open-Sources The Machine Learning Tech Behind Google Photos Search, Smart Reply And More
Google says today it’s making the machine learning technology that powers a number of its products, including Google Photos search, speech recognition in the Google app, and the newly launched “Smart Reply” feature for its email app Inbox. Called TensorFlow, the technology helps makes apps smarter, and Google says it’s far more powerful than its first-generation system – allowing the company to build and train neural nets up to five times faster than before.
For Google, that means it’s able to improve its products more quickly, the company explains.
TensorFlow was originally a project developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purpose of conducting machine learning and deep neural networks research. But the technology is applicable to a number of other domains, as well, says Google.
In more technical terms, the deep learning framework is a both a production-grade C++ backend which can run on CPUs, NVidia GPUs, Android, iOS and OS X, as well as a Python front-end that interfaces with Numpy, iPython Notebooks, and other Python-based tooling, writes Vincent Vanhoucke,Tech Lead and Manager for the Brain Team on his Google+ profile.
“TensorFlow is what we use every day in the Google Brain team, and while it’s still very early days and there are a ton of rough edges to be ironed out, I’m excited about the opportunity to build a community of researchers, developers and infrastructure providers around it,” he says.
The goal with machine learning is to build a technology that works similarly to the human brain, but the technology is not there yet, by any means.
In Google’s blog post announcing the news, penned by CEO Sundar Pichai, he explains that by open-sourcing the technology, the hope is that it will accelerate research on machine learning that would benefit the entire community, and make the technology work better. As Pichai points out, even the best systems today struggle to do what a 4-year old child can do – like know the name of a dinosaur after only seeing a couple of example, or understand that the sentence “I saw the Grand Canyon flying to Chicago” doesn’t mean there’s actually a flying canyon in the air.
In addition, the company believes that TensorFlow has the ability to be useful in research to make sense of complex data, like protein folding or crunching astronomy data, for example.
TensorFlow is interesting for the way it enables researchers and developers to collaborate on machine learning tech. Instead of there being separate tools for each group, TensorFlow lets researchers test new ideas, and when they work, move them into products without having to re-write code. This can speed up product improvements, and of course, by giving the larger machine learning community access to now do the same, Google will also benefit from the accelerated pace of innovations that come of the open sourced tech.
Google says TensorFlow is used today in a number of its most visible products, including image search in Google Photos, speech recognition systems, Gmail, Google Search, and more.
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