TECH PUNDIT TIM O’Reilly had just tried the new Google Photos app, and he was amazed by the depth of its artificial intelligence.
O’Reilly was standing a few feet from Google CEO and co-founder Larry Page this past May, at a small cocktail reception for the press at the annual Google I/O conference—the centerpiece of the company’s year. Google had unveiled its personal photos app earlier in the day, andO’Reilly marveled that if he typed something like “gravestone” into the search box, the app could find a photo of his uncle’s grave, taken so long ago.
The app uses an increasingly powerful form of artificial intelligence called deep learning. By analyzing thousands of photos of gravestones, this AI technology can learn to identify a gravestone it has never seen before. The same goes for cats and dogs, trees and clouds, flowers and food.
The Google Photos search engine isn’t perfect. But its accuracy is enormously impressive—so impressive that O’Reilly couldn’t understand why Google didn’t sell access to its AI engine via the Internet, cloud-computing style, letting others drive their apps with the same machine learning. That could be Google’s real money-maker, he said. After all, Google also uses this AI engine to recognize spoken words, translate from one language to another, improve Internet search results, and more. The rest of the world could turn this tech towards so many other tasks, from ad targeting to computer security.
Well, this morning, Google took O’Reilly’s idea further than even he expected. It’s not selling access to its deep learning engine. 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.