Democratizing Deep Learning With An iPhone App And Open Source SDK

Derrick Harris | GIGAOM | April 24, 2014

Most people will never have the computer science knowledge to become deep-learning researchers, but now they can test out the results of that work with a simple computer vision iPhone app called Deep Belief. iOS developers can take Deep Belief a step further by downloading an open source software development kit and working its object-recognition capabilities into their own apps.

Deep Belief was built by Jetpac, a startup that launched in 2012 and creates travel guides based on the content of Instagram photos. It’s an implementation of the convolutional neural network approach developed by University of Toronto researchers to win the ImageNet object-recognition competition in 2012. The approach was so accurate that Google bought a company founded by one of the researchers, Geoffrey Hinton, and brought him on part-time as a distinguished researcher.

Jetpac has been using the Deep Belief code on its own servers for a while, co-founder and CTO Pete Warden said, and has seen a marked improvement in how fast it can move. Previously, creating a new type of guide (e.g., restaurants with tacos) would require weeks of building custom code to extract the features of a taco from images. A deep-learning approach is much more efficient, he explained, because “you’re able to hand off a lot of those decisions to deep-learning algorithms.”