Sara Carter describes how she and John Solomon began unraveling the Trump-Russia collusion narrative after sources pointed to possible surveillance of then-President-elect Trump.

Spam calls and robocalls drove more than 2.6 million Do Not Call complaints, according to the FTC. Arizona led the nation with the highest complaint rate per 100,000 people.

Israel has launched an intensive wave of strikes across swathes of southern and eastern Lebanon, after vowing to step up its military action against Hezbollah. The Israeli military said it hit more than 100 Hezbollah infrastructure sites and fighters during what was one of the heaviest nights of bombardment since a US-brokered ceasefire began in mid-April. Strikes in the Bekaa Valley village of Mashghara killed 11 people, including two children, Lebanon's health ministry said. The military said it hit sites where terrorist activity was identified. It came after Israel's Prime Minister Benjamin Netanyahu said he had given the instruction to press the pedal even harder in targeting Hezbollah.

Plus: The Pope has called for governments to regulate AI. Despite the growing hysteria over AI's threat to white-collar jobs, there's still scant evidence that the technology has had a large-scale impact on the labor market. Analysis of US labor data shows that unemployment in occupations most exposed to AI is actually lower than in less-exposed jobs. There are also no signs that large numbers of workers are shifting from AI-threatened professions into supposedly safer manual-labor jobs. It's true that things aren't great in the job market--but the question is why. Here's what the data really says about AI and jobs .

Elon Musk attends Donald Trump's inauguration in Washington DC on 20 January 2025. Sam Altman attends a press conference at the White House on 21 January 2025. Elon Musk attends Donald Trump's inauguration in Washington DC on 20 January 2025. Sam Altman attends a press conference at the White House on 21 January 2025. Musk and Altman's AI rivalry reaches boiling point as IPO race heats up Let's recap a whirlwind five days that may determine the future of AI.

There's a mad dash to automate the world's most hated calls. You'll hear from an AI debt collector sometime soon. She introduced herself as Eve, but Ben knew right away that the voice on the other end of the line was a bot. She also knew how much money he'd owed a former landlord ($266). She didn't seem to know that he'd settled with a collection agency five months prior. Eve said she was an AI agent from ProCollect and was calling to collect a debt.

Graham Platner, Maine's presumptive Democratic Senate nominee, embraced democratic socialism at a Bernie Sanders rally, condemning Sen. Susan Collins and U.S. support for Israel.

Greg Sankey makes it clear that SEC didn't start the 16-team CFP format discussion, that's on the Big Ten Emmanuel Acho says it was'pretty stupid' for Jaxson Dart to introduce President Trump Lincoln Riley claims USC was'snaps away' from the playoff, says he's a better coach now than when at Oklahoma Notre Dame's Josh Yago delivers Memorial Day salute during anthem before lacrosse championship game Dak Prescott reunites with ex-fiancée Sarah Jane Ramos to celebrate daughter's first birthday Celtics guard Jaylen Brown challenges ESPN's Stephen A Smith to a debate at Harvard or MIT Wyndham Clark adds to his funky resume, TPC Craig Ranch slander and LIV Golf's pitch to new investors Unearthed fan video shows who Kyle Busch really was, NASCAR's darkest hour & Bubba Wallace's'Rowdy' story California mom speaks with compassion but brutal honesty about presence of trans athlete in daughter's sport Curt Cignetti jokes he had to'coach the hell out' of undefeated Hoosiers to be Indy 500 pace car driver A screenshot has WNBA fans asking: did a player endorse a threat toward Caitlin Clark? MLB reporter Tricia Whitaker hit with line drive during Orioles' game Brit Hume: A Trump endorsement'repeatedly' gives candidates a leg up Democrats' 2028 presidential hopefuls face scrutiny over elitism, political attacks'The Five' reveals what fans always wanted to know about them Defense expert argues Iran has never been'so isolated' Joey Jones calls out Dem candidate Platner for'hiding behind the Purple Hearts' of fellow vets Trump doesn't want Iran to become his Afghanistan: Mike Sarraille Any Iran deal will be judged by'how much it cost' to secure, ex-CIA station chief says Dr Rebecca Grant: Iran has'no place to go,' will have to sign a deal Pope Leo XIV calls for AI to be'disarmed' in critical warning about emerging tech'Fox News @ Night' panelists evaluate Spencer Pratt's Los Angeles mayoral campaign. Milwaukee Bucks forward Kyle Kuzma is betting big that LA will change its ways. Kuzma added some intrigue to next week's nonpartisan primary, placing a $36,000 bet that former The Hills reality star Spencer Pratt will pull off an upset victory and become the next mayor of Los Angeles. With the June 2 vote just days away, Kuzma, who won a championship with the Lakers in 2020, is backing Pratt's campaign.

This paper introduces a physics-informed generative framework that resolves the fundamental conflict between the statistical flexibility of deep learning and the rigorous theoretical constraints of fixed-income modeling. We demonstrate that standard generative models and unconstrained statistical extrapolations suffer from "manifold collapse" and severe arbitrage violations when forecasting term structures across diverse macroeconomic regimes. To overcome this, we propose a two-stage architecture. First, a Student-t Conditional Variational Autoencoder with Dynamic Level Injection (CVAEsT+LS) extracts a robust, heavy-tailed term structure manifold, effectively decoupling macroeconomic shape dynamics from absolute base rates. Second, the latent dynamic evolution is governed by a continuous-time Neural Stochastic Differential Equation (SDE) strictly penalized by a No-Arbitrage Partial Differential Equation (PDE). Empirical results across multiple sovereign currencies (USD, GBP, JPY) confirm that our synergistic approach drastically reduces out-of-sample forecasting errors -- achieving an exceptional 6.58 bps Mean Tenor RMSE -- and successfully overcomes the massive parallel drift and zero-lower-bound violations exhibited by the classical HJM model in extreme environments. Furthermore, through phase space vector field analysis, we demonstrate the model's superior capability in unsupervised macroeconomic regime detection and high-quality continuous-time scenario generation. Ultimately, this research provides a highly scalable, mathematically sound evolutionary engine for term structure modeling.

Random sampling is a fundamental tool in modern machine learning and numerical linear algebra for reducing the computational cost of large-scale matrix problems. Existing analyses, however, rely primarily on subspace embedding guarantees, which do not precisely characterize the statistical bias of nonlinear random oblique projections induced by sampling, which arises ubiquitously in subsampled least squares and fast low-rank approximation methods. Because (pseudo)inversion is nonlinear, these random oblique projections can be systematically biased even when the underlying sketch is unbiased, thereby introducing hidden bias into downstream least squares and low-rank approximation solutions. In this work, we develop a unified non-asymptotic theory for random oblique projections in high dimensions. We show that standard random sampling schemes generally induce a systematic statistical bias overlooked by classical subspace embedding-style analyses, and we propose a principled debiasing framework to correct it. We illustrate the power of the theory through two canonical applications. For subsampled least squares, we obtain sharp bias--variance characterizations, reveal previously unrecognized statistical suboptimality in widely used sampling schemes, and identify when debiasing yields provable improvements. For fast CUR decomposition, we develop a debiased approach with improved approximation accuracy. Numerical experiments further validate our theoretical findings.