According to federal prosecutors, Michele Spagnuolo made more than $1 million on the prediction market platform using confidential information about Google Search traffic. A Google security engineer has been charged with crimes stemming from allegedly placing trades on Polymarket using confidential internal information from the tech giant. Michele Spagnuolo, a 36-year-old Italian citizen, was arrested this morning in New York, as first reported by ABC News. Spagnuolo is charged with one count each of commodities fraud, wire fraud, and money laundering. He has worked at Google since 2014 and was based out of the company's Zurich, Switzerland, offices.

After the Trump administration turned away from electrification, two of the nation's biggest governments will advocate for more electric vans, police cars, and eventually, snowplows. New York City is not a car town. But pay attention as you walk, bike, or, sure, drive around the country's most populous city, and you might notice a car trend: an increasing number of its vehicles are electric . The city government operates some 5,800 EVs, plus 4,700 hybrid vehicles--Parks Department pickups, Police Department crossover SUVs, school buses, paramedic response vehicles, even some hulking garbage trucks. A local law requires the city to transition its entire light-and medium-duty fleet to batteries by 2035 and its trucks by 2038.

Realtor's evil ex-husband avoids murder trial with guilty plea after'ambushing' mother of two while she begged for her life on 911 call Explosive Supreme Court LEAK reveals stinging whispers about'belligerent' justice read the wild rants troubling both sides of the aisle Married doctor's affair with glamorous younger woman explodes into Fatal Attraction-style court war... X-rated photo claims, leaked recordings and a sinister threat: 'I'll never stop' US intel reportedly says Iran's military is FAR from decimated as Israel begins to worry about Trump's deal-making Michelle Obama looks alarmingly thin on Beverly Hills dinner date with Malia and Sasha - as Barack's absence fuels fresh whispers about their marriage Brady Bunch's Eve Plumb reveals cast's shocking residual pay after Lisa Kudrow said Friends stars still get $20m a year from reruns The unassuming apps all cheaters use to hide their affairs: Where to look on your partner's phone to see exactly what they are up to... and the subtle red flags to never ignore I've treated so many cocaine users. This is the one sign that makes it so obvious you have a problem, how it can kill you in a night... and the embarrassing sexual side effect you may not have heard of: DR PHILIPPA KAYE Demi Moore, 63, sparks concern with thinner-than-ever frame at Cannes... amid swirling Ozempic rumors High school student singles out board member who called her'hot' with humiliating takedown Lindsay Lohan, 39, baffles fans with'unrecognizable' appearance at Disney Upfronts event reigniting plastic surgery rumors The'marry me' sex move that'll make even the most commitment-phobic of men beg to see you again... and it worked for THREE of my friends Real-life Pacific Rim! World's first manned transforming robot is unveiled - and it could be yours for $650,000 A Chinese robotics firm has truly bridged the gap between science fiction and reality, after unveiling the world's first manned'mecha'. The GD01, developed by Unitree Robotics, weighs 500kg with a pilot on board and is capable of transitioning between bipedal walking and four-legged mode. Developed for civilian transport, the high-strength alloy machine features a'cockpit' where someone can sit and control the huge robot. A demonstration video shows Unitree's CEO Wang Xingxing climbing into the torso of the GD01 before it starts to move.

Elon Musk Boosts New Yorker's Sam Altman Exposé on X as Trial Begins The move comes as the trial for Elon Musk's lawsuit against OpenAI kicks off in federal court in Oakland. Elon Musk is boosting a post on X promoting The New Yorker's extensive investigation into Sam Altman's allegedly deceptive behavior, WIRED has confirmed. The move comes just as Musk's lawsuit against OpenAI and Altman heads to a jury trial in a federal courtroom on Monday morning. People scrolling X on Monday reported seeing an April 6 post from Ronan Farrow, a coauthor on the New Yorker article, promoting the investigation. A pop-up on the post on X's mobile app says it was boosted by @elonmusk, who also owns the platform.

We consider the problem of learning mixtures of Gaussians under the constraint of approximate differential privacy. We prove that eO(k2dlog3/2(1/δ)/α2ε) samples are sufficient to learn a mixture of k axis-aligned Gaussians in Rd to within total variation distance αwhile satisfying (ε,δ)-differential privacy. This is the first result for privately learning mixtures of unbounded axis-aligned (or even unbounded univariate) Gaussians. If the covariance matrices of each of the Gaussians is the identity matrix, we show that eO(kd/α2 + kdlog(1/δ)/αε) samples are sufficient. To prove our results, we design a new technique for privately learning mixture distributions. A class of distributions F is said to be list-decodable if there is an algorithm that, given "heavily corrupted" samples from f F, outputs a list of distributions one of which approximates f. We show that if F is privately list-decodable then we can learn mixtures of distributions in F. Finally, we show axis-aligned Gaussian distributions are privately list-decodable, thereby proving mixtures of such distributions are privately learnable.

While other areas of machine learning have seen more and more automation, designing a high-performing recommender system still requires a high level of human effort. Furthermore, recent work has shown that modern recommender system algorithms do not always improve over well-tuned baselines. A natural follow-up question is, "how do we choose the right algorithm for a new dataset and performance metric?" In this work, we start by giving the first large-scale study of recommender system approaches by comparing 24 algorithms and 100 sets of hyperparameters across 85 datasets and 315 metrics. We find that the best algorithms and hyperparameters are highly dependent on the dataset and performance metric. However, there is also a strong correlation between the performance of each algorithm and various meta-features of the datasets. Motivated by these findings, we create RecZilla, a meta-learning approach to recommender systems that uses a model to predict the best algorithm and hyperparameters for new, unseen datasets. By using far more meta-training data than prior work, RecZilla is able to substantially reduce the level of human involvement when faced with a new recommender system application.

It's an expensive time to fly. These tips can help lighten the load on your wallet. As a general rule, global instability leads to higher prices, and boy, is the world a doozy right now . Airfare hasn't escaped the tumult: US airfares are up 14.9 percent compared to a year ago, according to NerdWallet, largely due to fuel price spikes linked to disruptions in the Strait of Hormuz caused by blockages, bombs, and blockades. While the medium-term outlook for the airline business isn't great, there are still a few smart and tricky ways to save a little money when flying this summer.

On the construction of almost uniformly convergent random variables with given weakly convergent image laws.

What Will It Take to Get A.I. Out of Schools? The tech world assumes that A.I.-aided education is necessary and inevitable. A growing number of parents, educators, and cognitive scientists say the opposite. I don't like A.I., and I am raising my children not to like it. I've been telling them for years now that chatbots are manipulative and dangerous, that A.I.-image generators are loosening our collective grip on reality, that large language models are built atop industrial-scale intellectual-property theft. At times, I find myself speaking with my kids about A.I. in the same terms that we might discuss a creepy neighbor who lives down the block: avoid eye contact, cross the street when you walk past his house, and, when in doubt, call on a trusted adult. Yes, I, too, have suspected that the creepy neighbor walks on cloven hooves inside his Yeezy Boosts, but he probably isn't going anywhere--in fact, he keeps buying up properties around town--so just try your best not to engage. Somehow, I was not prepared for the creepy neighbor to start hanging around my kids' schools; somehow, I thought we had until high school.

When the Netflix anthology series "Beef" premièred, in 2023, it was a revelation in more ways than one. The show, which traced the depths into which two Angelenos descend after a road-rage incident, reintroduced Ali Wong as a dramatic lead, gave Steven Yeun a chance to go darkly comic, and shined a rare light on the issue of Asian American mental health. It also remade the career of its creator, Lee Sung Jin, a seeming overnight success who actually had nearly two decades of TV-comedy writing under his belt. Lee first pitched the show after he stalked another driver for a half hour following a parking-lot dispute; he similarly drew from life for Season 2, which stars Oscar Isaac as Josh, a country-club manager, and Carey Mulligan as his interior-designer wife, Lindsay. The couple are caught on video having a nasty fight by two members of his staff, Austin (Charles Melton) and Ashley (Cailee Spaeny). The Gen Z employees, about to embark on their own marriage, see the footage as blackmail material--and thus an opportunity to start their next chapter on secure financial footing. As in the first season, the story quickly broadens beyond the central conflict, roping in the club's new billionaire owner, Chairwoman Park (Youn Yuh-jung), her unreliable plastic-surgeon husband, and the seething resentments of both the haves and the have-nots. I met Lee earlier this month, at his new office in Hollywood. The space was sparsely decorated, but he'd already mounted posters for "Beef"; "It's Always Sunny in Philadelphia," the show that gave him his start in the industry; and "Thunderbolts," a 2025 Marvel movie directed by his creative partner, Jake Schreier. Lee, who has gone by Sonny since childhood and was credited as Sonny Lee for the first half of his career, opened up about the long road to "Beef"--a journey toward more intentional storytelling, as well as feeling "O.K. in my own skin." Perhaps surprisingly, the "Beef" character he seemed to relate to most was Josh, a congenial go-getter who mires himself in workaholism to avoid addressing his grief, as Lee did when one of his dogs died suddenly during production. We talked about his method of tailoring dialogue to his actors, the differences between Korean and American billionaires, and why class and capitalism are such inescapable themes on TV today.