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Embedded Vision Insights: July 19, 2016 Edition

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"Large-Scale Deep Learning for Building Intelligent Computer Systems," a Keynote Presentation from GoogleGoogle
Jeff Dean, Senior Fellow at Google, presents the keynote talk, "Large-Scale Deep Learning for Building Intelligent Computer Systems," at the May 2016 Embedded Vision Summit. Over the past few years, Google has built two generations of large-scale computer systems for training neural networks, and then applied these systems to a wide variety of research problems. Google has released its second generation system, TensorFlow, as an open source project, and is now collaborating with a growing community on improving and extending its functionality. Using TensorFlow, Google's research group has made significant improvements in the state-of-the-art in many areas, and dozens of different groups at Google use it to train state-of-the-art models for speech recognition, image recognition, various visual detection tasks, language modeling, language translation, and many other tasks. In this talk, Jeff highlights some of ways that Google trains large models quickly on large datasets, and discusses different approaches for deploying machine learning models in environments ranging from large datacenters to mobile devices. He then discusses ways in which Google has applied this work to a variety of problems in Google's products.

Dyson Demonstration of its 360 Eye Robot Vacuum Cleaner...