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Open source Microsoft Cognitive Toolkit democratizes AI and deep learning

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Like many technology companies, Microsoft is pinning a lot on AI -- including the areas of speech and image recognition. To help speed up development, and to enable others to start working on their own projects, the company has released an updated, open source version of the Microsoft Cognitive Toolkit. This is a deep learning toolkit, previously known as the Computational Network Toolkit (CNTK), and it's available for anyone to use completely free of charge. The toolkit has applications far beyond speech recognition, and it has already been used in Bing, and the latest version includes support for Python and C . Microsoft Artificial Intelligence and Research has already used the toolkit to develop technology capable of recognizing words in a sentence just as a well as human beings.


Microsoft Updates its Deep Learning Toolkit

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This post is by Chris Basoglu, Partner Engineering Manager in the AI & Research group at Microsoft. We are delighted to announce that Microsoft has brought Microsoft Cognitive Toolkit version 2.0 out of beta and is making the first release candidate available today. The toolkit, previously known as CNTK, is a system for deep learning used to speed advances in areas such as speech and image recognition and search relevance on CPUs and NVIDIA GPUs. Cognitive Toolkit can be used on-premises or in the cloud with Azure GPUs. Cognitive Toolkit is being used extensively by a wide variety of Microsoft products, by companies worldwide with a need to deploy deep learning at scale, and by students interested in the very latest algorithms and techniques.


Microsoft launches the next version of its deep learning toolkit into beta

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When it comes to machine learning frameworks, Google's Tensorflow is clearly the most popular option right now, but with CNTK, Microsoft also released its own internal framework at the beginning of the year. The company is launching the first beta of the next version (2.0) of CNTK today and with it, it hopes to challenge Tensorflow's leadership position. CNTK used to stand for'Computational Network Toolkit' but the software has now been renamed to Microsoft Cognitive Toolkit instead. Xuedong Huang, Microsoft's Chief Speech Scientist, told me that he believes CNTK/Cognitive Toolkit has always had plenty of advantages over Tensorflow and similar frameworks -- especially with regards to performance. According to Microsoft's benchmarks, Cognitive Toolkit continues to outperform its competitors in most tests and unsurprisingly, this new version is faster than the previous releases, especially when working on big data sets.


Microsoft releases open-source toolkit to accelerate deep learning - The AI Blog

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A toolkit used across Microsoft to achieve breakthroughs in artificial intelligence is generally available to the public via an open-source license, a team of researchers and software engineers announced today. "The 2.0 version of the toolkit is now in full release," said Chris Basoglu, a partner engineering manager at Microsoft. He has played a key role in developing Microsoft Cognitive Toolkit (previously known as CNTK). The full release of Microsoft Cognitive Toolkit 2.0 for use in production-grade and enterprise-grade deep learning workloads includes hundreds of new features incorporated since the beta to streamline the process of deep learning and to ensure the toolkit's seamless integration throughout the wider AI ecosystem. New with the full release today is support for Keras, a user-friendly open-source neural network library that is popular with developers working on deep learning applications.


Through partnerships and a new software toolkit, Nvidia looks to surf the 5G wave – TechCrunch

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Nvidia is making a hard pitch at this year's Mobile World Congress Los Angeles that the future of software defined 5G networks should be powered by its chipsets. Through the launch of a new software development toolkit and a series of partnerships announced today with Ericsson (for networking); Microsoft (for its cloud computing); and Red Hat (for its Kubernetes expertise), Nvidia is pitching telecommunications companies that its chipsets are the best base for managing the breadth of new services 5G networking will enable. Getting in on the ground floor would be a huge win for the chip manufacturer, especially since 5G antennas will need to be fairly ubiquitous to be effective. Helping to make that case is the launch of a new software development toolkit that will let telecommunications companies take more advantage of the "network slicing" abilities (allowing telecom companies to dial up and down capacity on a session-by-session basis) that 5G networking provides. In a keynote speech from Nvidia's chief executive, Jensen Huang, ahead of the convention, the company's pitch is that embedding its chipsets and new software into those networks is the best way for telecom companies to add dynamically provisioned additional services.