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dr tech

Top 10 AI fAIlures of 2016 - TechRepublic - 0 views

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    "But with all of the successes of AI, it's also important to pay attention to when, and how, it can go wrong, in order to prevent future errors. A recent paper by Roman Yampolskiy, director of the Cybersecurity Lab at the University of Louisville, outlines a history of AI fAIlures which are "directly related to the mistakes produced by the intelligence such systems are designed to exhibit." According to Yampolskiy, these types of fAIlures can be attributed to mistakes during the learning phase or mistakes in the performance phase of the AI system."
dr tech

Discrimination by algorithm: scientists devise test to detect AI bias | Technology | The Guardian - 0 views

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    "Concerns have been growing about AI's so-called "white guy problem" and now scientists have devised a way to test whether an algorithm is introducing gender or racial biases into decision-making."
dr tech

Machine-learning photo-editor predicts what should be under your brush / Boing Boing - 0 views

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    "In Neural Photo Editing With Introspective Adversarial Networks, a group of University of Edinburgh engineers and a private research colleague describe a method for using "introspective adversarial networks" to edit images in realtime, which they demonstrate in an open project called "Neural Photo Editor" that "enhances" photos by predicting what should be under your brush."
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