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Deep learning models DON’T need to be black boxes — here’s how

Deep neural networks can perform wonderful feats thanks to their extremely large and complicated web of parameters. But their complexity is also their curse: The inner workings of neural networks are often a mystery — even to their creators. This is a challenge that has been troubling the artificial intelligence community since deep learning started to become popular in the early 2010s. In tandem with the expansion of deep learning in various domains and applications, there has been a growing interest in developing techniques that try to explain neural networks by examining their results and learned parameters. But these explanations are often erroneous and misleading, and… This story continues at The Next Web

Zut alors! France spanks Google over ‘misleading’ hotel ranking algorithm

France’s competition watchdog has slapped Google with a €1.1 million ($1.3 million) fine over “misleading” hotel rankings generated by the tech giant’s algorithms. The Directorate-General for Competition, Consumer Affairs and Repression of Fraud (DGCCRF) began to probe Google’s classifications after hoteliers complained about their ratings. The investigation revealed that Google had replaced the rankings used by France’s tourism agency (Atout France) with the company’s own grading system. The DGCCRF found that the algorithmic classification had been applied to more than 7,500 establishments found in Google search results. [Read: How Polestar is using blockchain to increase transparency] The regulator said Google’s use of a five-star rating scale… This story continues at The Next WebOr just read more coverage about: Google

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