Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA

Using deep learning to solve challenging problems

Jeff Dean (Google)
4:20pm5:00pm Thursday, March 8, 2018
Average rating: ****.
(4.89, 9 ratings)

For the past six years, the Google Brain team has conducted research on difficult problems in artificial intelligence and built large-scale computer systems for machine learning research, and in collaboration with other teams at Google, Google Brain has applied its research and systems to dozens of Google products. The group has open-sourced the popular TensorFlow system, designed to easily express machine learning ideas and quickly train, evaluate, and deploy machine learning systems. Jeff Dean highlights some of Google Brain’s research and computer systems with an eye toward how it can be used to solve challenging problems.

Photo of Jeff Dean

Jeff Dean


Jeff Dean is a Google senior fellow in Google’s Research Group, where he cofounded and leads the Google Brain team, Google’s deep learning and artificial intelligence research team. He and his collaborators are working on systems for speech recognition, computer vision, language understanding, and various other machine learning tasks. During his time at Google, Jeff has codesigned and implemented many generations of Google’s crawling, indexing, and query serving systems, major pieces of Google’s initial advertising and AdSense for content systems, and 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. Jeff is a fellow of the ACM and the AAAS, a member of the US National Academy of Engineering, and a recipient of the ACM-Infosys Foundation Award in the Computing Sciences. He holds a PhD in computer science from the University of Washington, where he worked with Craig Chambers on whole-program optimization techniques for object-oriented languages, and a BS in computer science and economics from the University of Minnesota.