Less than two years ago, a team from Microsoft Research Asia made a huge splash by introducing ResNet, a deep neural network that used residual learning and “skip” connections blew away the competition in image classification.
Sure enough, one of the co-authors of that paper, Shaoqing Ren, has departed MSRA to start a self-driving car company with some of his MSRA colleagues. Ren is also the author of the Faster-RCNN paper, making him something of a star in the world of deep learning.
I know almost nothing about Momenta, but I’m taken by one section of their homepage, which describes their approach to data-driven path planning:
Our data-driven approach is to build a driver with billions of miles of driving experience. Crowdsourcing allows us to obtain billions of driving trajectories localized in semantic HD maps. By mapping from environment perception data to driving trajectories in semantic HD maps, we conduct autonomous driving planning. This provides us a unique and elegant framework to solve corner cases by adding corresponding data rather than adding rules.
I’m excited to see how the Momenta founders apply deep learning to path planning.