SAN FRANCISCO — Google is escalating the latest arms race in Silicon Valley: artificial intelligence.
Called machine learning, it’s software that learns as it processes massive amounts of data. It has made big leaps in recent years, fueling new advances such as language translation and speech recognition.
Every major tech company from Facebook to Apple is funneling resources into machine learning to accelerate the pace of innovation.
On Monday Google announced it is open-sourcing its machine learning software, meaning it’s making the software freely available to outside software developers. Google has done this before. It open-sourced Android and now it’s the most popular mobile software in the world with 80% market share.
TensorFlow is up to five times faster than Google’s previous version of machine learning software and could be useful when researchers “are trying to make sense of very complex data — everything from protein folding to crunching astronomy data,” says Google CEO Sundar Pichai.
“Just a couple of years ago, you couldn’t talk to the Google app through the noise of a city sidewalk, or read a sign in Russian using Google Translate, or instantly find pictures of your Labradoodle in Google Photos. Our apps just weren’t smart enough. But in a short amount of time they’ve gotten much, much smarter. Now, thanks to machine learning, you can do all those things pretty easily, and a lot more,” Pichai wrote in a blog post. “But even with all the progress we’ve made with machine learning, it could still work much better.”
Initially Google will release a version that runs on a single machine but eventually it will release a version that can run on a smartphone or across thousands of computers in data centers.
“Machine learning is a core, transformative way by which we are rethinking how we’re doing everything,” Pichai said on the company’s earnings call in October. “We are thoughtfully applying it across all our products.”
Last week Google announced it has begun to use machine learning in your inbox with a feature called Smart Reply.
“Machine learning is still in its infancy — computers today still can’t do what a 4-year-old can do effortlessly, like knowing the name of a dinosaur after seeing only a couple examples, or understanding that ‘I saw the Grand Canyon flying to Chicago’ doesn’t mean the canyon is hurtling over the city. We have a lot of work ahead of us. But with TensorFlow we’ve got a good start, and we can all be in it together,” Pichai said.
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