NVIDIA CEO: AI Workloads Will “Flood” Data Centers | Data Center Knowledge

Photo: Yevgeniy Sverdlik

"Data center managers in every industry have to answer some key questions to prepare for AI." writes Yevgeniy Sverdlik, San Francisco-based business and technology journalist.

Jensen Huang, CEO, NVIDIA, speaking at the GPU Computing Conference in San Jose in May 2017
Photo: Yevgeniy Sverdlik

During a keynote at his company’s big annual conference in Silicon Valley last week, NVIDIA CEO Jensen Huang took several hours to announce the chipmaker’s latest products and innovations, but also to drive home the inevitability of the force that is Artificial Intelligence.

NVIDIA is the top maker of GPUs used in computing systems for Machine Learning, currently the part of the AI field where most action is happening. GPUs work in tandem with CPUs, accelerating the processing necessary to both train machines to do certain tasks and to execute them.

Machine Learning is one of the most important computer revolutions ever,” Huang said. “The number of [research] papers in Deep Learning is just absolutely explosive.” (Deep Learning is a class of Machine Learning algorithms where innovation has skyrocketed in recent years.) “There’s no way to keep up. There is now 10 times as much investment in AI companies since 10 years ago. There’s no question we’re seeing explosive growth.”

While AI and Machine Learning are one of Gartner’s top 10 strategic technology trends for 2017, most other trends on the list – such as conversational systems, virtual and augmented reality, Internet of Things, and intelligent apps – are accelerating in large part because of advances in Machine Learning.

“Over the next 10 years, virtually every app, application and service will incorporate some level of AI,” Gartner fellow and VP David Cearley said in a statement. “This will form a long-term trend that will continually evolve and expand the application of AI and machine learning for apps and services.”

No Longer Just for Hyper-Scalers 
Growth in Machine Learning means a “flood” of AI workloads is headed for the world’s data center floors, Huang said. Up until now, the most impactful production applications of Deep Learning have been developed and deployed by a handful of hyper-scale cloud giants – such as Google, Microsoft, Facebook, and Baidu – but NVIDIA sees the technology starting to proliferate beyond the massive cloud data centers.
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Source: Data Center Knowledge