Microsoft Cognitive Toolkit Updates for Deep Learning Advances

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Frank Seide, principal researcher at Microsoft Artificial Intelligence and Research

Frank Seide, principal researcher at Microsoft Artificial Intelligence and Research

Today Microsoft released an updated version of Microsoft Cognitive Toolkit, a system for deep learning that is used to speed advances in areas such as speech and image recognition and search relevance on CPUs and Nvidia GPUs.

“We’ve taken it from a research tool to something that works in a production setting,” said Frank Seide, a principal researcher at Microsoft Artificial Intelligence and Research and a key architect of Microsoft Cognitive Toolkit.

The Microsoft Cognitive Toolkit—previously known as CNTK—empowers you to harness the intelligence within massive datasets through deep learning by providing uncompromised scaling, speed and accuracy with commercial-grade quality and compatibility with the programming languages and algorithms you already use.

Available on GitHub via an open source license, the toolkit includes new functionality that lets developers use Python or C++ programming languages in working with the toolkit. With the new version, researchers also can do a type of artificial intelligence work called reinforcement learning.

According to Microsoft, the new software is faster than other toolkits, especially when working on big datasets across multiple machines. That kind of large-scale deployment is necessary to do the type of deep learning across multiple GPUs that is needed to develop consumer products and professional offerings.

One key reason to use Microsoft Cognitive Toolkit is its ability to scale efficiently across multiple GPUs and multiple machines on massive data sets,” said Chris Basoglu, a partner engineering manager at Microsoft who has played a key role in developing the toolkit.

Microsoft Cognitive Toolkit can easily handle anything from relatively small datasets to very, very large ones, using just one laptop or a series of computers in a data center. It can run on computers that use traditional CPUs or GPUs, which were once mainly associated with graphics-heavy gaming but have proven to be very effective for running the algorithms needed for deep learning.

Microsoft Cognitive Toolkit represents tight collaboration between Microsoft and NVIDIA to bring advances to the deep learning community,” said Ian Buck, general manager of the Accelerated Computing Group at NVIDIA. “Compared to the previous version, it delivers almost two times performance boost in scaling to eight Pascal GPUs in an NVIDIA DGX-1.”

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