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Saturday, August 26, 2017

Executing Intelligence at the Edge

You would like to get the execution of deep learning neural nets to the edge of the network.  It is ultimately where we want to execute learned knowledge.    Training them has evolved to new efficiencies by using adapted net architectures and parallel chips, but now we need new ways to make them work at this edge, in mobile devices.

Google Researcher Invented New Technology to Bring Neural Networks to Mobile Devices  by Roland Meertens in InfoQ

Recently many companies released applications that use deep neural networks. Neural networks can require a large amount of computation. For this reason, they often appear in software as a service applications on GPU powered servers. For applications that should run without internet access, must be fast and responsible, or in which privacy is a concern using networks on servers is not possible. ... " 

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