Editors will need software that selects the best images—not just the ones from the right place at the right time. Connected cameras may improve the overall quality of crowdsourced images, but they will do little for the editors whose job it is to sort through them. Current services provide a temporary solution. With Scoopshot, a Helsinki software start-up, publishers can send photo assignments to the service's network of 300,000-plus mobile users. Stringwire, which NBC acquired in August, lets video producers request an uplink from anyone who has tweeted near an event of interest. But to assure quality, editors will need software that automatically selects the best images—not just the ones taken in the right place at the right time. That type of computer vision already exists on a small scale. A recent update to Google+ analyzes groups of pictures for blurriness, aesthetics, landmarks, and exposure to pick out the most shareable ones. The Sun-Times to benefit from that type of machine vision, the software will need to process larger image batches from multiple sources. In time, those pieces may come together, proving that the Sun-Times decision wasn't foolish—it was just a bit before its time.