Staff at WiseTech have been waiting months to be told if they are among the employees the company is to cut due to advances in AI. Staff at WiseTech have been waiting months to be told if they are among the employees the company is to cut due to advances in AI. WiseTech begins redundancies - but omits'AI' from emails to Chinese employees, workers say WiseTech has begun informing staff that they will lose their jobs as part of redundancies the company has said is due to artificial intelligence advancements - although an email to staff in China omitted the word "AI" after a court case against another company in the country. Staff at WiseTech have been waiting almost three months to be told if they are among the 2,000 people the logistics software company is to cut due to advances in AI. The Australian Stock Exchange-listed company announced in late February it would lay off almost 30% of its 7,000-strong workforce across 40 countries.

France is already moving on from Zoom and Microsoft Teams in favor of homegrown alternatives. Other countries are quickly following suit. As tensions between President Donald Trump and Europe continue to simmer, the continent is accelerating its moves to reduce its addiction to US technology . Cities and governments are ditching Microsoft Office for open-source alternatives, shifting to European cloud hosting for local AI, and moving defense data to systems without American involvement . Nowhere has this been more clear than in France.

A local specialist LLM, fine-tuned with reinforcement learning from verifiable rewards (RLVR) on operator-local data, is installed in a regulated organization with per-deployment error budget $α$. The operator needs a safety certificate for this deployment's stream at every round: no pooling across deployments, no waiting for a long-run average. Existing wrappers cannot deliver this on adaptive, online-updated streams: offline conformal-risk methods require exchangeability; online-conformal methods bound only long-run averages; non-exchangeable extensions are marginally valid; and the closest anytime wrapper, A-RCPS, controls marginal rather than selective risk. Using a (test statistic, validity guarantee, deployment rule) framework, we identify one empty cell forced by deployment requirements: e-process per threshold, selective risk, anytime-pathwise validity, max-certified-threshold rule. Conformal Selective Acting (CSA) fills it as a per-round wrapper maintaining a Ville-type e-process per threshold on a Bonferroni grid, evaluated against the RLVR filtration. Under predictable updates and isotonic-calibrated monotone risk we prove (i) an anytime-pathwise selective-risk bound $R_T^{\mathrm{act}}\leα+O(N_T^{-1/2})$, (ii) rate-optimal certification matching $Θ(\barη^{-2}\log(1/δ))$, and (iii) a horizon-independent release-rate gap. Across eight specialist benchmarks ($480$ streams), sixteen adversarial distribution-shift cells ($160$ streams), and five live Expert-Iteration RLVR cells with online LoRA over four base models in three architecture families ($10{,}300$ rounds), CSA is the only method among ten compared that satisfies pathwise validity and non-refusing deployment on every cell. We do not propose a new LLM, training algorithm, or policy class; CSA is the deployment-side complement, orthogonal to the model, for operators who cannot use a frontier API.

Elon Musk's SpaceX has revealed its plans to go public in the US, allowing people to trade shares in the firm on the stock market. SpaceX makes rockets, offers a satellite internet service called Starlink, and also owns Musk's controversial artificial intelligence (AI) firm xAI. The initial public offering (IPO) on the US stock market is set to be the largest in Wall Street history and could start next month under the ticker symbol SPCX. Because of the shares he will own in SpaceX, the IPO could make billionaire Musk, who is already the world's richest person, a trillionaire. SpaceX values itself at $1.25tn, and Musk's majority ownership of the company means his share could be worth more than $600bn.

One line tucked into a federal highway bill would strip funds from cities and states unless they kill their automated plate tracking programs--effectively banning the tech for all but toll collection. US lawmakers plan to introduce an amendment Thursday at a House committee markup hearing that would prohibit any recipient of federal highway funding from using automated license plate readers for any purpose other than tolling--a sweeping restriction that, if adopted, would bring an immediate end to state and local ALPR programs across the United States. The amendment, obtained first by WIRED, is sponsored by Representative Scott Perry, a Pennsylvania Republican and Freedom Caucus member, and Representative Jesús "Chuy" García, an Illinois progressive whose state has become a flash point in the national fight over ALPR misuse. The House Transportation and Infrastructure Committee will mark up the underlying bill--a $580 billion, five-year reauthorization of federal surface transportation programs--at 10 am ET on Thursday. Neither Perry nor García's offices immediately responded to WIRED's request for comment. The amendment runs a single sentence: "A recipient of assistance under Title 23, United States Code, may not use automated license plate readers for any purpose other than tolling."

Microsimulation models used by ministries of finance and central banks rely on parametric processes for lifetime earnings that capture only first and second moments of the conditional distribution and miss long-range nonlinear structure. We propose SAGA, a decoder-only transformer for irregular tabular panel sequences, paired with a split conformal calibration wrapper that delivers individual-level prediction intervals with finite-sample marginal coverage guarantees. Trained on the longitudinal Swedish LISA register over 1990 to 2022, comprising 2,143,817 individuals and 61,284,903 person-years, the model forecasts annual labor earnings at horizons of one to thirty years and aggregates them by Monte Carlo into present-discounted lifetime earnings distributions. Against the canonical Guvenen, Karahan, Ozkan, and Song parametric process and tabular and recurrent baselines, SAGA reduces continuous ranked probability score by 31.9 percent at the ten-year horizon and mean absolute error by 37.7 percent at the twenty-year horizon. Conformal intervals achieve nominal coverage to within 0.4 percentage points marginally and within 2.4 percentage points on the worst-case demographic subgroup. The reconstructed lifetime earnings Gini coefficient is 0.327 against the partially observed truth of 0.341 and the GKOS estimate of 0.378. Model weights, calibration tables, and a synthetic equivalent dataset are released for replication outside the protected SCB MONA environment.

The ex-employees, who cofounded a new AI watchdog group, say investors deserve more information about xAI's safety practices before SpaceX goes public. Two former OpenAI employees and a group of AI safety nonprofits are warning that Elon Musk's AI lab, xAI, could become a liability for prospective investors in SpaceX, which is preparing to file what's expected to be the largest initial public offering in Wall Street History. In a letter directed to investors published on Tuesday, the ex-staffers highlighted what they describe as "unpriced risks" related to xAI that could complicate SpaceX's reported plans to raise up to $75 billion as part of its IPO. The rocket company's private valuation shot up to over $1 trillion after it acquired xAI last year . Musk claimed his rocket company could launch data centers into space for his AI lab, but the letter's authors argue that xAI's poor record on safety issues could complicate how investors view the combined company as it gets ready to submit its IPO prospectus filing .

It is not only OpenAI but the AI race itself that was vindicated in the California courtroom last night . Even though Elon Musk essentially lost on a technicality, there's a clear signal from the verdict that making lots of money from AI and competing fiercely with rivals is simply business. The industry sometimes tries to display a united front, especially when it comes to safety, research and inclusivity. But this case served as a powerful reminder that none of the AI giants are charities and don't have to be, even if they once said otherwise. Cracks in the façade of industry collaboration for the sake of humanity have been exposed before.

The US Built a Site to Ensure Fair Access to Public Lands. Recreation.gov was supposed to make access to public lands more equitable and streamlined. It's a few minutes before 8 am Mountain Time on March 16, the day that river permit cancellations are released on Recreation.gov, the federal website for public land reservations. Rec.gov, as it's commonly called, administers everything from river permits and timed entrance fees at the most popular national parks to campground reservations on remote sites belonging to the Bureau of Land Management, and a lot of people are recreating on public land these days. There were 11 million reservations on the site in 2024, up significantly from 3.5 million reservations reported in 2019. At the center of it all is an unlikely player in the outdoor recreation space: The site is operated by the government contractor Booz Allen Hamilton, a corporation known more for cybersecurity than rafting trips. Early each year, outdoor enthusiasts gear up for Recreation.gov's annual lotteries for some of the most iconic experiences in the country: a river trip down Idaho's Middle Fork of the Salmon River, which flows through the Frank Church River of No Return Wilderness. Backcountry permits to hike into the Wave, an otherworldly rock formation in Arizona's Paria Canyon-Vermilion Cliffs Wilderness. Overnight stays in the rugged, lake-studded Enchantments, in Washington's Okanogan-Wenatchee National Forest. Odds of getting a desirable Middle Fork permit are around 2 percent.

On Monday morning, a jury in Oakland, California, announced its verdict in one of the most-watched tech feuds between billionaire Elon Musk and OpenAI CEO Sam Altman. The nine-member jury handed a decisive victory to Altman, saying Musk had waited too long to bring his claims against the artificial intelligence company and its top executives. Musk, who cofounded OpenAI as a nonprofit, had filed a $150bn lawsuit against the organisation, Altman and its president, Greg Brockman, accusing them of turning it into a for-profit entity for personal enrichment. Instead, the case became focused on a procedural issue. After deliberating for less than two hours, the jury unanimously found that the statute of limitations had expired before Musk filed the lawsuit in 2024, meaning jurors concluded he had waited too long to bring his claims under the applicable legal deadline.