The complaints, obtained by WIRED, described Bad Bunny's performance as being overly sexual and protested that the show was in Spanish. Bad Bunny performs during halftime of Super Bowl LX at Levi's Stadium in Santa Clara, California. Even before Bad Bunny took to the field, his Super Bowl halftime performance drew controversy, especially from MAGA influencers upset over the Puerto Rican star's comments against Immigration and Customs Enforcement and the fact that he sings in Spanish. Following the performance, which was watched by more than 128 million people, those complaints continued--but they were largely focused on perceived vulgarity in the artist's performance. Following a Freedom of Information Act (FOIA) request from WIRED, the Federal Communications Commission, which regulates communications including broadcast, released 2,155 complaints the agency received about the Super Bowl, most of which were about the halftime show.

Take the Portland Trail Blazers +2.5 in Game 3 Shocker! Kyle Brandt-Seth Rollins on-set spat was staged Tigers look to exploit Reds' struggles at home as Framber Valdez takes the mound in Cincinnati Watch as Eagles steal Makai Lemon with wild phone call: 'Why is Philly calling me?' Giants' draft pick has intense Jaxson Dart message: 'I'm ready to die for you' Donald Trump uses Pete Rose to justify soldier's alleged shady Maduro bet, and he's not wrong Ex-Michigan football coach Sherrone Moore's mistress reveals he got her pregnant during relationship Giants' bizarre draft decisions leave star player frustrated as true needs go unfulfilled in first round Rueben Bain's short arms and tragic car accident history contributed to his NFL Draft slide Sherrone Moore accuser Paige Shiver speaks out in new interview: he'had complete control over me' Megan Rapinoe calls on traditional WNBA media to be replaced with those who'understand queer culture' The NFL Draft continues to be one of the worst'sporting events' of the year'Fox & Friends' hosts learn country line dancing in Houston Veterans cheer Trump's order on psychedelic drugs to treat PTSD'Fox & Friends' hosts'get their Texas on' with Tecovas boots'Fox & Friends' kicks off the Fox News America 250 Tour in Houston Country artist Rich O'Toole joins'Fox & Friends' in Houston IDF finds'ambulance used by Hezbollah to conceal weapons' Hegseth shuts down reporter's EXTREME question OutKick 49ers GM John Lynch skeptical of Rams' decision to draft QB Ty Simpson with No. 13 overall pick Lynch called Simpson'a good football player' but noted the pick'surprised everybody' The San Francisco 49ers traded out of the NFL Draft's first round on Thursday, so general manager John Lynch didn't have a player to discuss when he met with reporters. No problem, because he started talking players a couple of division rivals drafted. Lynch commented on what the Arizona Cardinals and Los Angeles Rams did. San Francisco 49ers general manager John Lynch speaks at the NFL Scouting Combine at the Indiana Convention Center on Feb. 24, 2026.

CS 153 has gone viral on the Palo Alto campus--and on X. Not everyone is happy about it. As thousands of influencers descended on southern California earlier this month for the annual Coachella Music Festival, a very Silicon Valley program dubbed "AI Coachella" was taking shape a few hundred miles north in Palo Alto. The class, CS 153, is one of Stanford's buzziest offerings this semester, and like the music festival, it features a star-studded lineup of celebrities--in this case, not pop artists, but Big Tech CEOs. The course is co-taught by Anjney Midha, a former Andreessen Horowitz general partner, and Michael Abbott, Apple's former VP of engineering for cloud services.

Full-batch gradient descent on neural networks drives the largest Hessian eigenvalue to the threshold $2/η$, where $η$ is the learning rate. This phenomenon, the Edge of Stability, has resisted a unified explanation: existing accounts establish self-regulation near the edge but do not explain why the trajectory is forced toward $2/η$ from arbitrary initialization. We introduce the edge coupling, a functional on consecutive iterate pairs whose coefficient is uniquely fixed by the gradient-descent update. Differencing its criticality condition yields a step recurrence with stability boundary $2/η$, and a second-order expansion yields a loss-change formula whose telescoping sum forces curvature toward $2/η$. The two formulas involve different Hessian averages, but the mean value theorem localizes each to the true Hessian at an interior point of the step segment, yielding exact forcing of the Hessian eigenvalue with no gap. Setting both gradients of the edge coupling to zero classifies fixed points and period-two orbits; near a fixed point, the problem reduces to a function of the half-amplitude alone, which determines which directions support period-two orbits and on which side of the critical learning rate they appear.

We establish finite-time last-iterate guarantees for vanilla stochastic gradient descent in co-coercive games under noisy feedback. This is a broad class of games that is more general than strongly monotone games, allows for multiple Nash equilibria, and includes examples such as quadratic games with negative semidefinite interaction matrices and potential games with smooth concave potentials. Prior work in this setting has relied on relative noise models, where the noise vanishes as iterates approach equilibrium, an assumption that is often unrealistic in practice. We work instead under a substantially more general noise model in which the second moment of the noise is allowed to scale affinely with the squared norm of the iterates, an assumption natural in learning with unbounded action spaces. Under this model, we prove a last-iterate bound of order $O(\log(t)/t^{1/3})$, the first such bound for co-coercive games under non-vanishing noise. We additionally establish almost sure convergence of the iterates to the set of Nash equilibria and derive time-average convergence guarantees.

Estimating the number of components is a fundamental challenge in unsupervised learning, particularly when dealing with high-dimensional data with many components or severely imbalanced component sizes. This paper addresses this challenge for classical Gaussian mixture models. The proposed estimator is simple: center the data, compute the singular values of the centered matrix, and count those above a threshold. No iterative fitting, no likelihood calculation, and no prior knowledge of the number of components are required. We prove that, under a mild separation condition on the component centers, the estimator consistently recovers the true number of components. The result holds in high-dimensional settings where the dimension can be much larger than the sample size. It also holds when the number of components grows to the smaller of the dimension and the sample size, even under severe imbalance among component sizes. Computationally, the method is extremely fast: for example, it processes ten million samples in one hundred dimensions within one minute. Extensive experimental studies confirm its accuracy in challenging settings such as high dimensionality, many components, and severe class imbalance.

This material may not be published, broadcast, rewritten, or redistributed. Quotes displayed in real-time or delayed by at least 15 minutes. Market data provided by Factset . Powered and implemented by FactSet Digital Solutions . Mutual Fund and ETF data provided by LSEG .

Ritzy Bay Area town torn apart after teacher's daughter, 16, was behind wheel when four friends died in high-speed crash... then she posted a TikTok video that poured fuel on the flames Two CIA officers killed in Mexico when their car skidded off ravine and exploded after meeting about bust of'largest ever drug lab' Nancy Guthrie sheriff's appalling past revealed: Beat handcuffed suspect so badly he needed intensive care, used VILE language about woman and lied in sworn statement Trump confronts Xi as US forces seize Chinese ship carrying mysterious'gift' to Iran New'Hollywood dose' pill: A-listers hooked on'youth elixir' that dermatologists say is anti-ageing, shrinks pores, smooths wrinkles... and even banishes rosacea Days after we got engaged, the love of my life told me he'd killed a man and buried him in a bog. I reported him to police... but then I made this irreversible mistake Ark of the Covenant's final resting place pinpointed by archaeologists as fresh search begins Fury as murderer marries pen pal behind bars... as teenage victim's mom says: 'I'm serving a life sentence without my son' Insiders claim failed AI rollout could be to blame for Tim Cook's departure from Apple - as one says'the AI era requires a different kind of leadership' Life-threatening cantaloupe recall in four states upgraded to FDA's highest risk level... 'reasonable probability of death' AMANDA PLATELL: Why Sarah Ferguson - with the ghost of Princess Diana at her side - is ready to sensationally blow up the Royal Family. She knows ALL their secrets... Team USA Olympics star Noah Lyles slammed for'horrible' reaction to his wife's wedding dress reveal In honour of the Queen's (purple!) reign: Kate mirrors late monarch's colourful wardrobe and wears her pearl earrings and necklace US troops board second tanker as Iran is accused of breaking ceasefire'numerous times' How to lose weight when perimenopause sabotages your metabolism: I'm a trainer but when I hit 46, I piled on the pounds overnight. The new'posh' drug that's easier to order than Uber Eats - and why all my middle-class friends have ditched booze and cocaine for it: JANA HOCKING Autistic woman, 24, worked hard to build independent life for herself... now she's PARALYZED thanks to selfishness of stranger How you like THAT? Blackpink's Jennie collaborates with Beats on Special Edition Onyx Black Headphones - and gives fans a sneak peek at a brand-new song And now Jennie has joined forces with Beats on a brand new pair of headphones. The singer, who is part of the South Korean girl group, Blackpink, has unveiled an Onyx Black pair of the Beats Solo 4 - JENNIE Special Edition.

After 15 years, Tim Cook is stepping down as Apple's top executive. At age 65, he leaves behind a hardware juggernaut that, under his leadership, brought about a global smartphone revolution and transformed Apple into one of the most profitable publicly traded companies in history. With a reputation for logistical management, Cook first joined Apple in 1998, overseeing its worldwide sales and operations. In 2009, he temporarily began running day-to-day operations when the company's legendary co-founder, Steve Jobs, took medical leave due to complications from pancreatic cancer. In 2011, just a few months before Jobs's death, Cook took over as CEO.

Verification of model outputs is rapidly emerging as a key primitive for both training and real-world deployment of large language models (LLMs). In practice, this often involves using imperfect LLM judges and reward models since ground truth acquisition can be time-consuming and expensive. We introduce Fully Unsupervised Score Ensembling (FUSE), a method for improving verification quality by ensembling verifiers without access to ground truth correctness labels. The key idea behind FUSE is to control conditional dependencies between verifiers in a manner that improves the unsupervised performance of a class of spectral algorithms from the ensembling literature. Despite requiring zero ground truth labels, FUSE typically matches or improves upon semi-supervised alternatives in test-time scaling experiments with diverse sets of generator models, verifiers, and benchmarks. In particular, we validate our method on both conventional academic benchmarks such as GPQA Diamond and on frontier, unsaturated benchmarks such as Humanity's Last Exam and IMO Shortlist questions.