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.

Here's Exactly How That Happened The definitive story of how Claude Code and OpenClaw kicked off computing's biggest transformation possibly ever. "Hi, my name is Peter, and I'm a Claudeholic." It was August 2025 and Peter Steinberger was addressing a meetup in London called Claude Code Anonymous. Steinberger and some fellow addicts had arranged the event to network with people like themselves--techies swept up by coding tools such as Anthropic's paradigm-busting Claude Code. "I dedicate pretty much all my waking time to this, yet it doesn't feel enough," he told the gathering in a cozy, brick-walled room. A few months later, Anthropic released a new version of Claude Code, and the ranks of Claudeholics exploded . Called Opus 4.5, it could handle more complicated programming tasks, retain much more in its memory, run for many hours on end, and manage a team of AI subagents. Anthropic has what it describes as a "notoriously difficult" take-home exam for prospective engineering hires; in a head-to-head comparison of those people and its models, Anthropic claimed that Opus 4.5 "scored higher than any human candidate ever," which "raises questions on how AI will change engineering as a profession."

From killing your chatbots to optimizing your prompts, here are the best ways to go full AI native and conquer the new world. Sam Liang is appalled as I confess my technique for recording an interview: running the Voice Memos app on an iPhone and transferring the transcript manually to a Google Doc. The CEO of Otter, a transcription service for analyzing meetings, looks at me as if I tried to call into our video chat using a rotary phone. He believes, naturally, that I should switch to Otter. Time-saving productivity tools like next-gen note-takers, task-based agents, and chatty inbox assistants are exploding in popularity as they invade every nook and cranny of our digital lives.

A new AI-powered avatar of Black Sabbath singer Ozzy Osbourne could make its first UK appearance in Birmingham. Osbourne's wife Sharon and son Jack announced plans for the hyper-real version of the Birmingham-born singer at an expo in the US last week. Talking to Ed James on BBC Radio WM, she said that plans for the avatar were brilliant. I've seen the tests that they've done of Ozzy and you can see every pore on his face, his beard's coming through, it's that detailed, she said. Osbourne died in July aged 76, less than three weeks after he had performed at Villa Park with Black Sabbath.

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.

The Tokyo District Court on Monday found two former executives of artificial intelligence developer Alt guilty of window dressing in violation of the financial instruments and exchange law. The Tokyo District Court on Monday found two former executives of Japanese artificial intelligence developer Alt guilty of window dressing in violation of the financial instruments and exchange law. Former executive officer Katsuya Asai, 46, and former treasury and accounting division chief Takayuki Ariizumi, 53, were both sentenced to three years in prison, suspended for five years. The Tokyo-based company was fined ¥300 million ($1.89 million). Noting that fictitious sales at the firm reached about ¥11 billion in total, Judge Shoji Miyata said, "The window-dressing rate was extremely high, and the company achieved a stock listing that should not have been approved."

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.

History-dependent sampling can reduce long-run Monte Carlo variance by discouraging redundant revisits, but existing schemes typically encode history through empirical measure on finite state spaces, which is infeasible in high-dimensional discrete configuration spaces or ill-posed in continuous domains. We propose Score-Repellent Monte Carlo (SRMC) framework that summarizes trajectory history by a running average of score evaluations in $\mathbb{R}^d$, where $d$ is the dimension of the score and state representation. This history is converted into a surrogate target through an exponential score tilt, indexed with $α$ that represents the strength of repellence in controlling the magnitude of the history-based repulsion. The surrogate family is normalization-free in the standard MCMC sense, yielding a generic wrapper: at each iteration, any base kernel targeting $π$ can instead be run on the current surrogate $π_{θ_n}$ while the history is updated online. We analyze the coupled evolution of the history recursion and Monte Carlo estimators using stochastic approximation with controlled Markovian noise, establishing almost sure convergence and a joint central limit theorem. We further identify regimes in which the asymptotic covariance decreases as $α$ increases, with scaling $O(1/α)$, extending the near-zero-variance effect of finite-state history-dependent samplers to general state spaces with constant memory. Experiments on continuous targets and discrete energy-based models demonstrate improved estimator variance and mode coverage, while retaining $O(d)$ memory usage and modest per-iteration overhead.

Offline Reinforcement Learning from Human Feedback (RLHF) pipelines such as Direct Preference Optimization (DPO) train on a pre-collected preference dataset, which makes them vulnerable to preference poisoning attack. We study label flip attacks against log-linear DPO. We first illustrate that flipping one preference label induces a parameter-independent shift in the DPO gradient. Using this key property, we can then convert the targeted poisoning problem into a structured binary sparse approximation problem. To solve this problem, we develop two attack methods: Binary-Aware Lattice Attack (BAL-A) and Binary Matching Pursuit Attack (BMP-A). BAL-A embeds the binary flip selection problem into a binary-aware lattice and applies Lenstra-Lenstra-Lovász reduction and Babai's nearest plane algorithm; we provide sufficient conditions that enforce binary coefficients and recover the minimum-flip objective. BMP-A adapts binary matching pursuit to our non-normalized gradient dictionary and yields coherence-based recovery guarantees and robustness (impossibility) certificates for $K$-flip budgets. Experiments on synthetic dictionaries and the Stanford Human Preferences dataset validate the theory and highlight how dictionary geometry governs attack success.

It is well known that, under standard regularity conditions, the maximum likelihood estimator (MLE) satisfies a central limit theorem and converges in distribution to a Gaussian random variable as the sample size grows. This paper strengthens this classical result by developing several stronger forms of asymptotic normality for the normalized MLE. With additional assumptions on the score, we first establish sub-Gaussian tail bounds and convergence of all moments for the normalized estimation error. We then prove an entropic central limit theorem for a smoothed version of the estimator, showing convergence in relative entropy to the limiting Gaussian law. When the Fisher information of the normalized estimate is bounded, or its density has bounded first derivative, we further show that the smoothing can be removed, yielding entropic normality of the MLE itself. The proofs develop auxiliary tools that may be of independent interest, including exponential consistency bounds, high-moment estimates, and entropy-control arguments for the estimator.