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Google’s Jeff Dean on the benefits of large-scale deep learning for building intelligent systems

Stephen Ibaraki | June 30, 2016
In every conversation with government, industry, media, and academia, it is a consistent focus of attention.

"Jeffrey Dean and Sanjay Ghemawat are the recipients of the 2012 ACM-Infosys Foundation Award in the Computing Sciences [contemporary innovation that exemplifies the greatest recent achievements in the computing field]."

"In their influential 2004 research paper, MapReduce: Simplified Data Processing on Large Clusters, the concept is used to power massive online applications by splitting the work into small pieces and spreading them across thousands of machines...This approach has led to the advent of cloud computing, where computing power is provided as a utility to consumers, with all the hardware and implementation details abstracted away...Since then, they have published a series of instrumental papers which have inspired a generation of systems researchers and generated considerable follow-on work in the field of distributed computing. The open publication of their advances has allowed others to build on their work. An example is Hadoop, the open source project that is widely used by many companies as well as academic researchers and educators."

Further illustrating Jeff's influence, he has co-designed/implemented five generations of Google's crawling, indexing, and query serving systems, and co-designed/implemented major pieces of Google's initial advertising and AdSense for Content systems. He is also a co-designer and co-implementor of Google's distributed computing infrastructure, including the MapReduce, BigTable and Spanner systems, protocol buffers, LevelDB, systems infrastructure for statistical machine translation, and a variety of internal and external libraries and developer tools. He is currently working on large-scale distributed systems for machine learning. Jeff is currently a Google Senior Fellow in Google's Research Group, where he leads Google's deep learning research team in Mountain View, working on systems for speech recognition, computer vision, language understanding, and various predictive tasks.

This spotlights a unique opportunity for enterprises to come up to speed with machine learning with an upcoming free talk and Q&A hosted by the non-profit ACM.

Source: ITWorld Canada


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