Thanks to the use of GPUs, Microsoft researchers achieved record results on ImageNet, a prestigious image-recognition benchmark.
Compared to last year, Microsoft’s system cut the top-5 error rate by half, correctly classifying images within 1,000 pre-defined categories more than 96 percent of the time. 
Their system uses a 152-layer neural network, which is nearly five times deeper than the state of the art.
The researchers published a paper that provides more information on the deep learning framework used to win the ImageNet benchmark.
Read more on the NVIDIA blog >>
GPUs Help Microsoft Build Record-Breaking Image Recognition System
Dec 15, 2015
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AI-Generated Summary
- Microsoft researchers achieved record results on ImageNet using GPUs, correctly classifying images more than 96 percent of the time.
- The system used a 152-layer neural network, nearly five times deeper than the previous state of the art.
- The top-5 error rate was cut in half compared to the previous year's results.
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