Zamen | زامن
Apple's AI Team Publishes First Research Paper Focused on Advanced Image Recognition
Earlier in December, Apple announced that it would begin allowing its artificial intelligence and machine learning researchers to publish and share their work in papers, slightly pulling back the curtain on the company's famously secretive creation processes. Now, just a few weeks later, the first of those papers has been published, focusing on Apple's work in the intelligent image recognition field.Titled "Learning from Simulated and Unsupervised Images through Adversarial Training," the paper describes a program that can intelligently decipher and understand digital images in a setting similar to the "Siri Intelligence" and facial recognition features introduced in Photos in iOS 10, but more advanced.In the research, Apple notes the downsides and upsides of using real images compared with that of "synthetic," or computer images. Annotations must be added to real images, an "expensive and time-consuming task" that requires a human workforce to individually label objects in a picture. On the other hand, computer-generated images help to catalyze this process "because the annotations are automatically available."Still, fully switching to synthetic images could lead to a dip in the quality of the program in question. This is because "synthetic data is often not realistic enough" and would lead to an end-user experience that only responded well to details present in the computer-generated images, while being unable to generalize well on any real-world objects and pictures it faced.This leads to the paper's central proposition -- the combination of using both simulated and real images to work together in "adversarial training," creating an advanced AI image program:
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