Alexei Efros, a laureate of computer science, opens his lecture here in Heidelberg with a striking fact: 74% of web traffic is visual.
“Everybody’s talking about big data, the data deluge—all this data being rained down on us,” Efros says. “But I think a lot of people don’t appreciate that most of the data is actually visual…. YouTube claims to have 500 hours of data uploaded every single minute. The earth has something like 3.5 trillion images, and half of that has been captured in the last year or so.”
Today, teams of computer scientists like Efros are working to understand that data via “deep learning” algorithms. First, you prepare a network of connections. Then, as a training regimen, you show it vast quantities of photographs. With time, it learns to accomplish extraordinary tasks—writing captions, colorizing black-and-white photos, recognizing animal species.
Unless, of course, you troll it. Continue reading