A proof that computer algorithms are capable of advanced scene understanding.

It is more and more exciting and encouraging to observe that, based on Deep-learningalgorithm, we can inter alia: deeply streamline our critical processes; improve our living and working conditions; improve our security, make relevant real-time judgments and to understand our surroundings. 

According to research out of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), their new algorithm ( demo) can look at a pair of photos and outperform humans in determining things like which scene has a higher crime rate, or is closer to a McDonald's restaurant.

Connectikpeople.co, soon #Retinknow can observe that PhD students Aditya Khosla, Byoungkwon An, and Joseph Lim, as well as CSAIL principal investigator Antonio Torralba , trained the computer on a set of 8 million Google images from eight major U.S. cities that were embedded with GPS data on crime rates and McDonald's locations.

Deep-learning techniques have been used to help the program teach itself how different qualities of the photos correlate. The algorithm independently discovered that some things you often find near McDonald's franchises include taxis, police vans, and prisons. (Things you don’t find: cliffs, suspension bridges, and sandbars.)

According to PhD students Aditya Khosla, potential uses include: a navigation app that avoids high-crime areas, to a tool that could help McDonald's determine future franchise locations.
                                                                                            
On its asset, Khosla has also helped develop an algorithm that can predict a photo’s popularity.