A Conspiracy Theory About QR Codes Has Led to Chaos Ahead of Georgia's Midterms The state of Georgia banned the use of QR codes for elections, based in part on the assertions of a man who's boosted false claims about Israel and 9/11. Now no one knows how ballots will be counted. QR codes are at the center of the latest conspiracy theory in Georgia's elections. And it's largely thanks to Garland Favorito, a man who has spent decades trying to get people to listen to his conspiracy theories about insecure voting machines being used to rig elections in Georgia. When Georgia became the epicenter of election denial conspiracy theories in 2020, Favorito became an overnight superstar in the election denial community, and an integral part of the vast network of groups across the country that sprang up to promote the baseless claim that US elections are rigged.

Diego Pavia, the former Vanderbilt quarterback and Heisman runner-up, accepted an invitation to the Baltimore Ravens' rookie minicamp on a tryout basis after going undrafted.

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Kevin Durant is expected to sit out Game 4 with a sprained left ankle and bone bruise, as the Rockets face elimination against the Lakers on Sunday night.

Kai Trump revealed a "scary" allergic reaction to hand soap during her trip to the Masters Tournament at Augusta National, requiring medical attention and a steroid shot.

A piece of the UFC White House event's setup is sitting in Pennsylvania Amish country Viral Ottawa Senators fan blamed for team's 0-2 playoff start banished to Taiwan Edward Cabrera's strikeout prop is the play as struggling Phillies face surging Cubs today Nuggets vs Timberwolves Game 3 pick hinges on Jaden McDaniels calling out Denver's entire defense Charles Barkley was disgusted by Magic's highly questionable pregame handshake ChatGPT predicted the first round of the NFL Draft and here's what it said Curt Cignetti was so focused this offseason, he turned down all external requests: 'I'm 95% football' Former MLB owner claims'despicable' San Francisco Giants are the reason the A's left Oakland Trump weighs in on Iran's internal power struggle and Strait of Hormuz control Hasan Piker justifies'social murder' of CEO Fox News celebrates'Bring Your Kids to Work Day' Trump says there's'no time frame' to secure Iran deal Iranian activist praises Trump's intervention after female protesters saved from execution Michael Brennan's ball found the greenside pond, but with teammate Johnny Keefer in Position A, he decided to go for it LIV Golf Is On Its Death Bed As The PGA Tour Wins The Golf WAR! | Don't @ Me w/ Dan Dakich Broadcasting legend Tim Brando joins Dan Dakich to break down the decline of LIV Golf, Bryson DeChambeau's unique success, and the flaws in modern Masters coverage. It's highly unlikely that Michael Brennan will be the only 24-year-old man to take his shirt off in public in New Orleans on Thursday, but he will be the only one to do so who has a PGA Tour victory under his belt. During the opening round of this week's Zurich Classic, a team event on Tour played at TPC Louisiana, Brennan and teammate Johnny Keefer began on the back nine and got things rolling early, getting to 4-under through their opening six holes. Michael Brennan of the United States catches a ball on the third green during the third round of the RBC Heritage 2026 at Harbour Town Golf Links on April 18, 2026, in Hilton Head Island, South Carolina. LPGA'S MAJOR CHAMPIONSHIP GREENSIDE PLUNGE POOL IS PREPOSTEROUS IN EVERY WAY After back-to-back pars on the 16th and 17th holes, the duo arrived at the Par 5 closing hole, which is when things got messy.

ChatGPT predicted the first round of the NFL Draft and here's what it said Curt Cignetti was so focused this offseason, he turned down all external requests: 'I'm 95% football' Former MLB owner claims'despicable' San Francisco Giants are the reason the A's left Oakland Longtime NASCAR crew chief tells wild story about one of the sport's biggest characters WNBA finally embraces Caitlin Clark's stardom with unprecedented national TV schedule Why are the Mets so bad? Flyers mascot Gritty pens letter to fans ahead of first playoff game... eight years after he debuted NFL Draft prospect Rueben Bain Jr. mum about 2024 crash when publicly asked about it for first time Troy Aikman is selling'fire suites,' which are exactly what they sound like Trump says there's'no time frame' to secure Iran deal Iranian activist praises Trump's intervention after female protesters saved from execution Steve Hilton praised for'offering solutions' in CA gubernatorial debate Middle East tensions escalate over US blockade, Iran's actions Michael Easter and Gary Brecka discuss the'choice' to live to be 100 Sen Ted Cruz calls new deadline with Iran'really consequential' OutKick Charles Barkley was disgusted by Magic's highly questionable pregame handshake After Stephen A. Smith's controversial comments about Memphis sparked backlash, Barkley stepped in and delivered a blunt response. The debate quickly turned into a heated clash over media responsibility, perception, and what crosses the line. The Orlando Magic dropped Game 2 of their first-round playoff series to the Detroit Pistons on Wednesday, and it's safe to assume Charles Barkley was mighty confident that the L was coming before the game even tipped off. In the lead-up to the matchup in Detroit, the ESPN broadcast shared a live shot of members of the Magic partaking in some pre-game antics.

Inference-time LLM alignment methods, particularly activation steering, offer an alternative to fine-tuning by directly modifying activations during generation. Existing methods, however, often rely on non-anticipative interventions that ignore how perturbations propagate through transformer layers and lack online error feedback, resulting in suboptimal, open-loop control. To address this, we show empirically that, despite the nonlinear structure of transformer blocks, layer-wise dynamics across multiple LLM architectures and scales are well-approximated by locally-linear models. Exploiting this property, we model LLM inference as a linear time-varying dynamical system and adapt the classical linear quadratic regulator to compute feedback controllers using layer-wise Jacobians, steering activations toward desired semantic setpoints in closed-loop with minimal computational overhead and no offline training. We also derive theoretical bounds on setpoint tracking error, enabling formal guarantees on steering performance. Using a novel adaptive semantic feature setpoint signal, our method yields robust, fine-grained behavior control across models, scales, and tasks, including state-of-the-art modulation of toxicity, truthfulness, refusal, and arbitrary concepts, surpassing baseline steering methods. Our code is available at: https://github.com/trustworthyrobotics/lqr-activation-steering

We study signal propagation at initialization in transformers through the averaged partial Jacobian norm (APJN), a measure of gradient amplification across layers. We extend APJN analysis to transformers with bidirectional attention and permutation-symmetric input token configurations by deriving recurrence relations for activation statistics and APJNs across layers. Our theory predicts how attention modifies the asymptotic behavior of the APJN at large depth and matches APJNs measured in deep vision transformers. The criticality picture known from residual networks carries over to transformers: the pre-LayerNorm architecture exhibits power-law APJN growth, whereas transformers with LayerNorm replaced by elementwise $\tanh$-like nonlinearities have stretched-exponential APJN growth, indicating that the latter are subcritical. Applied to Dynamic Tanh (DyT) and Dynamic erf (Derf) transformers, the theory explains why these architectures can be more sensitive to initialization and optimization choices and require careful tuning for stable training.

The Energy Conserving Descent (ECD) algorithm was recently proposed (De Luca & Silverstein, 2022) as a global non-convex optimization method. Unlike gradient descent, appropriately configured ECD dynamics escape strict local minima and converge to a global minimum, making it appealing for machine learning optimization. We present the first analytical study of ECD, focusing on the one-dimensional setting for this first installment. We formalize a stochastic ECD dynamics (sECD) with energy-preserving noise, as well as a quantum analog of the ECD Hamiltonian (qECD), providing the foundation for a quantum algorithm through Hamiltonian simulation. For positive double-well objectives, we compute the expected hitting time from a local to the global minimum. We prove that both sECD and qECD yield exponential speedup over respective gradient descent baselines--stochastic gradient descent and its quantization. For objectives with tall barriers, qECD achieves a further speedup over sECD.