When deep learning mistakes a coffee-maker for a cobra
— “Is this your sister?” That’s the kind of question asked by image-recognition systems, which are becoming increasingly prevalent in our everyday devices. They may soon be used for tumor detection and genomics, too. These systems rely on what is known as “deep-learning” architectures – an exciting new development in artificial learning. But EPFL researchers have revealed just how sensitive these systems actually are: a tiny universal perturbation applied across an image can throw off even the most sophisticated algorithms.