This is a decidedly more somber entry. In March, a self-driving car being tested by Uber struck and killed a pedestrian in Tempe, Arizona. Uber is pausing tests across the U.S. while an investigation into the cause of the death is underway. As companies race to be the first to market with self-driving vehicles on public roads and highways, it's a sobering reminder that the technology is still very much in development. Whether the incident slows down the pace of testing nationwide remains to be seen.

Show a human any photograph and they'll able to predict what happens next with pretty decent accuracy. The woman riding her bike will keep on moving. The dog will catch the frisbee. The man is going to have a pratfall. It's such a basic skill that we don't consider the vast amount of information that is used to make these predictions -- concerning gravity, inertia, the nature of pratfalls, etc. -- and teaching computers to do the same is proving to be a key challenge in machine vision Researchers from MIT attempting to solve this problem have come up with some very impressive results, using specially trained neural networks to turn images into videos and getting the computer to essentially predict what happens next.

Show a human any photograph and they'll able to predict what happens next with pretty decent accuracy. The woman riding her bike will keep on moving. The dog will catch the frisbee. The man is going to have a pratfall. It's such a basic skill that we don't consider the vast amount of information that is used to make these predictions -- concerning gravity, inertia, the nature of pratfalls, etc. -- and teaching computers to do the same is proving to be a key challenge in machine vision.