"adversarial example"

Google's AI thinks this turtle is a rifle

Machine-learning-based image classifiers are vulnerable to "adversarial preturbations" where small, seemingly innocuous modifications to images (including very trivial ones) can totally confound them. Read the rest

Techniques for reliably fooling AI machine-vision classifiers

The Open AI researchers were intrigued by a claim that self-driving cars would be intrinsically hard to fool (tricking them into sudden braking maneuvers, say), because "they capture images from multiple scales, angles, perspectives, and the like." Read the rest

Google's troll-fighting AI can be defeated by typos

Jigsaw is a "wildly ambitious" Google spin-off research unit that recently released Perspective, a machine-learning system designed to identify argumentative, belittling and meanspirited online conversation. Within days of its release, independent researchers have published a paper demonstrating a way of tricking Perspective into trusting ugly messages, just by introducing human-readable misspellings into their prose. Read the rest

Using Machine Learning to synthesize images that look NSFW but aren't

Yahoo has released a machine-learning model called open_nsfw that is designed to distinguish not-safe-for-work images from worksafe ones. By tweaking the model and combining it with places-CNN, MIT's scene-recognition model, Gabriel Goh created a bunch of machine-generated scenes that score high for both models -- things that aren't porn, but look porny. Read the rest

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