Microsoft Open Sources Its Artificial Brain to One-Up Google

morinson

MicROSoft Open Sources Its Artificial Brain to One-Up Google

01.26.16
Time of Publication: 7:00 am.
7:00 am


Microsoft’s brain is now available for anyone to use in their apps.
The company has open sourced the artificial intelligence framework it uses to power speech recognition in its Cortana digital assistant and Skype Translate applications. This means that anyone in the world is now free to view, modify, and use Microsoft’s code in their own software.
The framework, called, CNTK, is based on a branch of artificial intelligence called deep learning, which seeks to help machines do things like recognize photos and videos or understanding human speech by mimicking the structure and functions of the human brain. Tech giants like Microsoft, Google and Facebook have invested heavily in deep learning research for years, going so far as to hire many of academics who pioneered the field. Now, just as academics publish their research so that it can be critiqued and advanced by other researchers, these companies are releasing their deep learning software in much the same way.

        'We want this to be useful not just for academics but for commercial artificial intelligence.'        Xuedong Huang, Microsoft

Last year Google open sourced its artificial intelligence engine TensorFlow, which the company uses for many of its own applications, including voice recognition in Android and even its flagship search engine. Soon after, Facebook open sourced designs for custom hardware designed to run the latest AI algorithms and China’s largest search engine, Baidu, open sourced its the artificial intelligence training software.
Microsoft actually released CNTK, which is similar in many ways to Google’s TensorFlow, back in April, months before Google released its own framework, but the code was restricted to non-commercial use. Now Microsoft is letting anyone, including corporations, use CNTK for whatever they want. “We want this to be useful not just for academics but for commercial artificial intelligence and deep learning companies,” says Xuedong Huang, Microsoft’s chief speech scientist.
All the ComputersCNTK has a big advantage over TensorFlow for people outside of academia: it can take advantage of the power of many servers at the same time. That’s important because it’s rare that a single computer is powerful enough to handle a real-world artificial intelligence application, such as speech recognition on an app used by millions of people. Internally, Google likely uses TensorFlow on thousands of servers at a time. But the version Google released to the public, Huang says, can’t be used in this way. In fact, few deep learning frameworks other than CNTK support running across multiple servers right out of the box, though it’s possible to do with other open source software such as Torch, which is used by Facebook and Google.
According to Microsoft’s internal testing, CNTK is much more efficient than other open source deep learning tools. It’s also one of the few deep learning frameworks that supports Microsoft Windows. One downside, however, is that the framework only supports C++ and its own custom language, which might make it more difficult for some developers to start using. But Microsoft plans to add support for the popular programming languages Python—possibly the most common language among artificial intelligence researchers—and C# in the near future. And now that it’s open source, programmers will be able to add support for their favorite languages themselves.

irobot

微软：正式开源人工智能工具包CNTK
   北京时间1月27日消息，微软本周宣布，已在Github上向外部开发人员开源其人工智能工具包CNTK（Computational Network Toolkit）。

    根据微软研究人员的描述，由于具备更为优秀的交互能力，CNTK工具包中的语音和图像识别速度比另外四个当下主流的计算工具包都更加受开发者的欢迎。鉴于深度学习活动只需要数周就可以完成，这对于微软而言的确是一个不错的成就。
    为了开发CNTK，微软就必须深入研究神经网络，探究如何更好的复制人脑的学习过程。该公司还依靠其强大的计算处理能力与图形处理(GPU)能力来运行CNTK，从而处理更为复杂的算法，提高人工智能和识别能力。
    去年11月，Google就开源了用于自家图片搜索功能的TensorFlow机器学习系统。但据微软首席语音科学家黄学东称，微软的CNTK工具包比我们此前所见过的任何工具包都更加疯狂，同时性能也更加强悍。
    因为这个工具包如今已经开源了，所以即使是没有多少预算的研究人员也可以把这个开发包用在深度学习领域的初创企业，或是更大的数据处理公司中。事实上，CNTK还具有着更为强大的可扩展性，开发者可以用多台计算机实现GPU的扩展，从而能够更加灵活的应对大规模的实验。

morinson

感谢翻译

平淡静然

很好！很强大！