Wednesday September 12, 2018

Intel Solidifies Deep Learning Portfolio with Varied Architectures and Packages

Gadi Singer is the vice president and general manager of the Artificial Intelligence Products Group at Intel. In an interview with Ed Sperling of Semiconductor Engineering, he discusses how Intel is evolving to meet the ever changing requirements for deep learning. He believes that Xeon processors are well suited for deep learning but there are other solutions needed that range from sub-1 watt to 400 watts. Intel's ability to leverage the data center, edge and system integration will be key to their future in creating a solid portfolio of products for the deep learning field.

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There are three elements. One is that we need a portfolio, because our customers are asking for it. You need solutions that go from the end device, whether that's a security camera or a drone or a car, to a gateway, which is the aggregation point, and up to the cloud or on-premise servers. You need a set of solutions that are very efficient at each of those points. One element of our hardware strategy is to provide a portfolio with complementary architectures and solutions. Another element is to further make Xeon a strong foundation for AI.