Alexey Kamenev, Software Engineer at Microsoft Research talks about their open-source Computational Network Toolkit (CNTK) for deep learning, which describes neural networks as a series of computational steps via a directed graph. Kamenev also shares a bit about how they’re using GPUs, the CUDA Toolkit and GPU-accelerated libraries for the variety of Microsoft products that benefit from deep learning, such as speech recognition for Skype Translator and Cortana.
“Basically, right now the whole world of deep learning is using GPUs and Microsoft is not an exception,” said Alexey.
Watch Alexey’s presentation about CNTK in the NVIDIA GPU Technology Theater at SC15: Watch Now
Share your GPU-accelerated science with us at http://nvda.ly/Vpjxr
Watch more scientists and researchers share how accelerated computing is #thepathforward: Watch Now
Share Your Science: Accelerating Microsoft Cortana and Skype Translator
Feb 12, 2016
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AI-Generated Summary
- Computational Network Toolkit (CNTK) represents neural networks as a series of computational steps via a directed graph.
- Microsoft Research uses GPUs, the CUDA Toolkit and GPU-accelerated libraries for deep learning across products such as speech recognition for Skype Translator and Cortana.
- Alexey Kamenev, Software Engineer at Microsoft Research, presented CNTK at the NVIDIA GPU Technology Theater at SC15.
Next Steps
- Watch the CNTK presentation from SC15 to see the open-source deep learning system in action.
- Share your GPU-accelerated science at the submission page to contribute to the community.
- Explore more researcher stories at the Share Your Science tag for additional accelerated computing examples.
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