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" ... Training your virtual LIDAR is much easier than training many neural networks. Normally training requires you have lots of training images where humans have painstakingly figured out the true distances. Since a test car can have an actual expensive LIDAR on it, you can drive around to get training data combined with the “ground truth” distance figures learned from the LIDAR. You show the neural network tons of images with the real distance as calculated by the LIDAR, and it becomes good at trying to figure out the distance on its own. This technique, a variant of “unsupervised learning” because you don’t need human taggers, is vastly cheaper than supervised learning, so if there is something neural networks can do well at, it should be this. You can also train on simulator data to improve your models. ... "
" ... Until recently, revisions and approvals to these flight manuals were managed and exchanged inefficiently as emails and countless non-value added manual tasks between the manufacturing engineers, publication writers, diagram illustrators, content taggers and quality assurance professionals. ... "