Nvidia Releases Machine Learning Products for Hyperscale Datacenters

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machinelearningToday Nvidia announced an end-to-end hyperscale datacenter platform that lets web-services companies accelerate their huge machine learning workloads.

These new additions to the Nvidia Tesla platform include:

  • Nvidia Tesla M40 GPU – the most powerful accelerator designed for training deep neural networks
  • Nvidia Tesla M4 GPU – a low-power, small form-factor accelerator for machine learning inference, as well as streaming image and video processing
  • NNvidia Hyperscale Suite – a rich suite of software optimized for machine learning and video processing

“The artificial intelligence race is on,” said Jen-Hsun Huang, co-founder and CEO of NVIDIA. “Machine learning is unquestionably one of the most important developments in computing today, on the scale of the PC, the internet and cloud computing. Industries ranging from consumer cloud services, automotive and health care are being revolutionized as we speak. Machine learning is the grand computational challenge of our generation. We created the Tesla Hyperscale Accelerator line to give machine learning a 10X boost. The time and cost savings to data centers will be significant.”

Nvidia’s new hardware and software products are designed specifically to accelerate the flood of web applications that are racing to incorporate AI capabilities. Ground-breaking advances in machine learning have made it possible to use AI techniques to create smarter applications and services.

Machine learning is being used to make voice recognition more accurate. It enables automatic object and scene recognition in video or photos with the ability to tag for later search. It makes possible facial recognition in videos or photos, even when the face is partially obscured. And it powers services that are aware of individual tastes and interests, which can organize schedules, deliver relevant news stories and respond to voice commands accurately and in a conversational tone.

The magic is made possible by machine learning. The challenge is obtaining the daunting amount of supercomputing power needed to innovate and train the growing number of deep neural networks, and the processing to instantly respond to the billions of queries from consumers using the services. The Nvidia hyperscale accelerator line was created to accelerate these workloads and dramatically increase the throughput of data centers.

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