You're viewing the US edition You can switch to the UK, AU or IE homepage at any time using this menu. Former Google executive Marissa Mayer has sparked fury online after she asked an AI tool to tell her three things about her daughter. The 51-year-old sat down with The New York Times to talk about her new tech start up Dazzle, which is homing in on AI assistants, when she revealed her own use of the technology. She said that late last year she was struggling to giver her 9-year-old daughter's teacher three bullet points that summarized what made her daughter special. Feeling overwhelmed by the options, she asked Dazzle, which spat out an answer for her in a few seconds.

After seven rocky years, the company's assets will be sold to Dazzle, a new AI firm that Mayer founded. Sunshine cofounder and CEO Marissa Mayer speaks at TechCrunch Disrupt in San Francisco in 2023. Sunshine, the consumer AI startup founded by former Yahoo CEO Marissa Mayer in 2018, has seen brighter days. The small startup is shutting down, and its assets are being sold to a new entity incorporated by Mayer called Dazzle, according to an email viewed by WIRED. Mayer sent the email to Sunshine shareholders on September 17, informing them that Dazzle has officially incorporated and is ready to acquire Sunshine's holdings.

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Despite the outstanding performance of deep neural networks, they are vulnerable to adversarial attacks. While there are many invisible attacks in the digital domain, most physical world adversarial attacks are visible. Here we present an invisible optical adversarial attack that uses a light source to dazzle a CMOS camera with a rolling shutter. We present the photopic conditions required to keep the attacking light source completely invisible while sufficiently jamming the captured image so that a deep neural network applied to it is deceived.

Anti-surveillance makeup, used by people who do not want to be identified to fool facial recognition systems, is bold and striking, not exactly the stuff of cloak and daggers. While experts' opinions vary on the makeup's effectiveness to avoid detection, they agree that its use is not yet widespread. Anti-surveillance makeup relies heavily on machine learning and deep learning models to "break up the symmetry of a typical human face" with highly contrasted markings, says John Magee, an associate computer science professor at Clark University in Worcester, MA, who specializes in computer vision research. However, Magee adds that "If you go out [wearing] that makeup, you're going to draw attention to yourself." The effectiveness of anti-surveillance makeup has been debated because of racial justice protesters who do not want to be tracked, Magee notes.

Facial recognition was once a hallmark of sci-fi, but we're now years past its introduction in many facets of contemporary society. Social networks use it to tag people in photos, it's the way that millions of people unlock their devices, and it's playing an ever-greater role in helping law enforcement around the world identify criminals and missing children in equal measure. It's an amazing technology that is only possible because of the rise of machine learning algorithms, the sheer mountains of data that modern society collates every day, and ever-faster computers to process it all. But despite all of these advances, facial recognition technology has a dark side. It's often wrong, which can create a myriad of potentially quite serious problems for those who fall foul of it.

Slate is making its coronavirus coverage free for all readers. Subscribe to support our journalism. I've been single for about two and a half years. Not unhappily so, but I keep a busy schedule that allows me time to go out and meet new people or to go on dates, but rarely both. Despite that, I've been able to maintain a rather pleasing love life, thanks in great part to the apps. Obviously, I haven't yet settled down with Mr. Right Enough just yet, but I've connected with great friends, met remarkable lovers, and explored both fleeting and long-term romance on my own terms.