One of the things I like about the residency program, and google brain in general, is the openness of the research environment.
For example, it is easy for us to release open source code related our research, and in fact we are even encouraged to do so.
Some of us even continue to write personal blogs about machine learning research work done in the program.
In addition to open source projects such as tensorflow, people on the team also contribute and develop other open source libraries such as pybullet, rather than using proprietary, closed-source physics libraries.
Hey long time lurker and first time commenter here. May I ask if you could ping you for a few tips on my application. Right now I am finishing up a master's in robotics (mix of computer science and electrical engineering) at an Ivy league university (also did my undergrad here). I have previous research experience implementing (from scratch) and training convolutional neural nets. Right now I'm doing researching in natural language processing but not with RNNs.
This program sounds very competitive and I would love to get in, so any help is greatly appreciated!
For example, it is easy for us to release open source code related our research, and in fact we are even encouraged to do so.
Some of us even continue to write personal blogs about machine learning research work done in the program.
In addition to open source projects such as tensorflow, people on the team also contribute and develop other open source libraries such as pybullet, rather than using proprietary, closed-source physics libraries.