谷歌今天将其人工智能引擎开源了

谷歌提供的搜索能力常常让人惊叹。而谷歌新发布的Google Photo，同样让人叹为观止，它能够自动识别你的相片。比如你输入关键字“tomb”，它能将你多年前扫墓的照片呈现给你，即便你并未对这张照片做出任何提示设置。这样的精确检索能力，来源于其强大的机器学习引擎。今天，它将其核心深度学习神经网络，给开源了！

Google CEO Sundar Pichai刚刚在官方博客上公布，开源其最新的机器学习项目：TensorFlow，访问地址

http://tensorflow.org/

当然，谷歌也并非完全毫无保留。目前开源的是其引擎中较为顶层的算法。同时谷歌也没有开源其硬件基础设施系统。

下面是宣布的全文：

Just a couple of years ago, you couldn’t talk to the Google appthrough 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. But even with all the progress we’ve made with machine learning, it could still work much better.

So we’ve built an entirely new machine learning system, which we call “TensorFlow.” TensorFlow is faster, smarter, and more flexible than our old system, so it can be adapted much more easily to new products and research. It’s a highly scalable machine learning system—it can run on a single smartphone or across thousands of computers in datacenters. We use TensorFlow for everything from speech recognition in the Google app, to Smart Reply in Inbox, to search in Google Photos. It allows us to build and train neural nets up to five times faster than our first-generation system, so we can use it to improve our products much more quickly.

We’ve seen firsthand what TensorFlow can do, and we think it could make an even bigger impact outside Google. So today we’re also open-sourcing TensorFlow. We hope this will let the machine learning community—everyone from academic researchers, to engineers, to hobbyists—exchange ideas much more quickly, through working code rather than just research papers. And that, in turn, will accelerate research on machine learning, in the end making technology work better for everyone. Bonus: TensorFlow is for more than just machine learning. It may be useful wherever researchers are trying to make sense of very complex data—everything from protein folding to crunching astronomy data.

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.

英文完整地址：https://googleblog.blogspot.jp/2015/11/tensorflow-smarter-machine-learning-for.html  (需要翻墙阅读。上述链接是翻墙小日本后得到的镜像)。

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