A groundbreaking new method lets researchers spot AI models secretly tweaked to generate illegal content—like child abuse material—without ever seeing the harmful output. Traditional testing fails here because creating such content is illegal. Scientists at MIT and Thorn developed a technique that analyzes internal code changes, specifically low-rank adaptations, to detect malicious modifications with 100% accuracy. This breakthrough empowers platforms to block dangerous models before upload, closing a major loophole and offering a vital safety net for AI in the open-source era.

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Parents are cutting back on back-to-school tech spending, down 16% this year, as rising prices and economic concerns push them toward essentials like clothing—up 22%. With AI-driven shopping tools gaining traction, savvy parents are using digital tools to stretch budgets, staying longer on sites and making smarter purchases—even if it means buying fewer gadgets. Retailers are watching closely: the more digitally engaged shoppers are, the more they’re likely to spend, forcing brands to adapt with personalized, AI-powered campaigns to capture their attention.

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Uber’s flipped its script on self-driving cars — no longer building its own fleet, it’s now betting big on becoming the universal platform for both human and robot drivers. With deals signed with over 25 robotaxi companies, Uber’s cars are poised to hit your app soon — but with a twist: they’re lobbying to legally force hybrid networks, where AVs must share the road with human drivers for years, potentially locking out competitors and forcing them onto Uber’s system. This strategy, already pushing through in New Jersey and Washington D.C., marks a dramatic shift from Uber’s past self-driving ambitions — and it’s sparking a fierce debate with Waymo, who wants open competition. The outcome could redefine how we move around cities for decades.

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