But randomly "running into" a naturaly generated adversial input in the wild should be a more common problem. The end result will vary depending if the adversi

But randomly "running into" a naturaly generated adversial input in the wild should be a more common problem. The end result will vary depending if the adversial input is a child or the rear end of a truck illuminated by sunshine at a certain angle. So far only the second one have been tested IRL but for some reason I'm not really fond of the idea that we should be gathering more field data of adversial input... My main fear with current autonomous driving applications of ML is that they might not be that ready for prime time and that we are only a few deadly accidents away from a major setback in public trust relating to autonomous driving.