This week NVIDIA announced two new Tesla GPUs and a suite of software to help web services companies accelerate huge machine learning workloads and keep up with challenging computational demands.
The NVIDIA Tesla M40 lets researchers more quickly innovate and design new deep neural networks for each of the increasing number of applications they want to power with artificial intelligence. And another, the NVIDIA Tesla M4 is a low-power accelerator designed to deploy these networks across the data center. The line also includes a suite of GPU-accelerated libraries.
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 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,” he said.
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