Being bold and taking risks allows our embedded teams to make discoveries that affect billions of users every day.
In-Datacenter Performance Analysis of a Tensor Processing Unit
Norman P. Jouppi, Cliff Young, Nishant Patil, David Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bhatia, Nan Boden, Al Borchers, Rick Boyle, Pierre-luc Cantin, Clifford Chao, Chris Clark, Jeremy Coriell, Mike Daley, Matt Dau, Jeffrey Dean, Ben Gelb, Tara Vazir Ghaemmaghami, Rajendra Gottipati, William Gulland, Robert Hagmann, C. Richard Ho, Doug Hogberg, John Hu, Robert Hundt, Dan Hurt, Julian Ibarz, Aaron Jaffey, Alek Jaworski, Alexander Kaplan, Harshit Khaitan, Andy Koch, Naveen Kumar, Steve Lacy, James Laudon, James Law, Diemthu Le, Chris Leary, Zhuyuan Liu, Kyle Lucke, Alan Lundin, Gordon MacKean, Adriana Maggiore, Maire Mahony, Kieran Miller, Rahul Nagarajan, Ravi Narayanaswami, Ray Ni, Kathy Nix, Thomas Norrie, Mark Omernick, Narayana Penukonda, Andy Phelps, Jonathan Ross
ISCA (2017) (to appear)
Guetzli: Perceptually Guided JPEG Encoder
Jyrki Alakuijala, Robert Obryk, Ostap Stoliarchuk, Zoltan Szabadka, Lode Vandevenne, Jan Wassenberg
arXiv (2017)
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, Jeffrey Dean
CoRR, vol. abs/1609.08144 (2016)
Varun Gulshan, Lily Peng, Marc Coram, Martin C Stumpe, Derek Wu, Arunachalam Narayanaswamy, Subhashini Venugopalan, Kasumi Widner, Tom Madams, Jorge Cuadros, Ramasamy Kim, Rajiv Raman, Philip Q Nelson, Jessica Mega, Dale Webster
JAMA (2016)
Digitized Adiabatic Quantum Computing with a Superconducting Circuit
Rami Barends, Alireza Shabani, Lucas Lamata, Julian Kelly, Antonio Mezzacapo, Urtzi Las Heras, Ryan Babbush, Austin Fowler, Brooks Campbell, Yu Chen, Zijun Chen, Ben Chiaro, Andrew Dunsworth, Evan Jeffrey, Erik Lucero, Anthony Megrant, Josh Mutus, Matthew Neeley, Charles Neill, Peter O'Malley, Chris Quintana, Enrique Solano, Ted White, Jim Wenner, Amit Vainsencher, Daniel Sank, Pedram Roushan, Hartmut Neven, John Martinis
Nature, vol. 534 (2016), pp. 222-226
Google is an engineering organization unlike any other.
Because so much of what we do hasn't been done before,
the line between research and product development is wonderfully blurred.
The engineer is often engaged in research,
and the researcher in engineering.
We support the broader research community through our Faculty Engagement and Student Support programs, and by providing Research Datasets and Tools & Resources
Learn MoreGoogle is a fantastic place to do research. The ability to work on really interesting problems, with excellent colleagues (whose expertise is often very complementary to your own), and to have your research impact billions of users every day is incredibly exciting.
I'm at Google because that's where the data is, and the means to use it. This makes it possible to do great work at scale. In the end, the reason for doing the work is to create something useful that helps people, and Google makes it easy for researchers to roll out products that will help hundreds of millions of people.
The raw computation power available at Google is just incredible - we can do research on a scale that was unimaginable to me in academia, and work on problems that no one else is even thinking of.
