US regulators have issued a warning to a nuclear project critical to Donald Trump’s efforts to revive the industry, after a contractor fell into a reactor cavity and a bundle of fuel rods nearly tipped over during refueling.

The US Nuclear Regulatory Commission told Holtec International, a company racing to reopen a shuttered reactor at the Palisades nuclear power plant in Michigan, to address a “chilled work environment” that has made staff hesitant to raise safety concerns without fear of retaliation.

The warning has prompted concerns among critics that financial and political pressures to revitalize nuclear power as an answer to booming AI-driven energy demand are increasing risks of accidents.

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Amazon has warned that vulnerabilities in a programming language that underpins much of the Internet, discovered using AI tools, are being “broadly exploited” as governments and companies rush to secure their systems.

The world’s largest cloud computing provider on Wednesday said it had identified an attempt by hackers to exploit the bug four days before the weakness was disclosed to the public.

Amazon added the flaws were “now being broadly exploited in the wild.”

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Nearly two-thirds of US doctors are turning to an AI-powered search engine to make patient decisions, propelling a little-known tech startup to a $15 billion valuation while prompting a debate over the future of patient care.

Miami-based OpenEvidence, founded by serial entrepreneur Daniel Nadler in 2022, said that many of America’s 1 million physicians processed more than 42 million prompts last month. Doctors are using the company’s chatbot to scour medical journals and clinical guidelines to help diagnose and treat patients.

The ads-powered platform has grown largely by word of mouth, penetrating a sector where few tools have seen similar traction. “We’re the first viral consumer internet app in healthcare,” Nadler told the FT in an interview.

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This week, Character.AI declared bankruptcy. While some saw the fall of a chatbot platform as a harbinger for the industry, court filings indicate that the decision was actually a key part of a deal that has let Disney hire most of Character.AI’s staff—including its now former CEO Karandeep Anand—potentially acquire most of Character.AI’s technology, and avoid the beleaguered startup’s many legal liabilities and obligations.

In the past few years, Character.AI has faced multiple private lawsuits over the safety of its chatbots, as well as investigations from regulators around the world. In a declaration filed as part of the bankruptcy, Character.AI’s newly appointed CEO explained that the goal of the bankruptcy was to reach a “consensual resolution” with personal injury claimants and a group of states investigating the company, while maximizing the value of the company’s assets for shareholders.

The Disney deal seems to be structured so that whatever is left of Character.AI will retain responsibility for those legal battles, some of which are still ongoing.

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Anthropic has granted external evaluators “employee-like access” to assess the risks of its models, following through on a commitment to increase safeguards over concerns the technology could run catastrophically out of control.

METR, a nonprofit that has worked with leading labs including OpenAI, Anthropic, Google, and Meta, now has a team embedded in the Claude maker’s office with access to its hardware and internal systems.

A greater role for third-party evaluators is among the main concrete steps the labs have proposed in response to rising concern about the dangers more capable AI systems could pose to the economy, cyber security, and humanity at large.

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Close to 1 billion meetings take place each day around the world. CEOs spend nearly three-quarters of their workdays in meetings. Planning for and spearheading meetings eats up the lion’s share of managers’ time. In much of the industrialized world, meetings are both the metronomes and menaces of people’s working lives.

Given the enormous time spent in workplace meetings, do we know what they accomplish or how to make them as worthwhile as possible? For decades, the answer was… not really. Meetings weren’t a particularly accessible subject of study. But that has changed. Once a tiny niche area, “meeting science” is a growing specialization among organizational and social psychologists. The field is accelerating as archived virtual meetings provide vast swaths of data. And it is providing a fascinating window into human behavior.

Meeting to talk helps fulfill basic human needs to connect, communicate, and cooperate. People have long come together—in caves, fields, market squares, and town halls—to get something done, share ideas, get on the same page, or just to remark on the weather. But meeting scientists define their subject as gatherings of people “with some goal or structure to the event,” says organizational psychologist Liana Kreamer of the Florida Institute of Technology, who coauthored a review of over three decades of meeting science in the 2026 Annual Review of Organizational Psychology and Organizational Behavior.

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Prediction market boosters often tout the platforms as barometers of public opinion, or even “truth machines” offering a clearer picture of where things are headed than polling or other data. In 2024, for example, Kalshi beat many pollsters in forecasting the outcome of the US presidential race. But their trading activity can also tell more perplexing stories.

Two global election markets on Polymarket’s offshore platform, for instance, generated over $600 million in trading volume, far more than most political markets typically attract. Most of the activity took place buying and selling contracts tied to long-shot candidates who ultimately did not win.

This summer, Ethiopian Prime Minister Abiy Ahmed’s Prosperity Party cruised to victory in federal elections, winning 438 parliamentary seats and paving the way for him to serve another five-year term. The closest competitor won 13 seats. On prediction markets, trading volume—the total value of contracts bought and sold—typically tracks roughly with the odds of a given outcome; frontrunners attract far more volume than long shots. But in this case, the trading patterns deviated sharply from the norm. Just $173,000 was wagered on Ahmed winning, compared to more than $41 million traded on his chief of staff, Shimelis Abdisa, becoming the country’s next leader. Altogether, the volume traded added up to over $285 million, nearly all on losing candidates.

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Coral-fringed tropical atolls are among the landforms most threatened by global warming, but many have a potential superpower: Healthy ecosystems may help them keep pace with rising seas.

Atoll islands with native vegetation and thriving seabird populations are “naturally active systems that can change and adapt to their environmental conditions if they are allowed to do so,” said Nick Graham, a marine ecologist at Lancaster University in the United Kingdom, who led an international team of scientists that studied island resilience across 28 atoll islands in the Pacific and Indian oceans.

Their paper, published Wednesday in Science Advances, shows that restoring atoll ecosystems reinforces their growth. Seabirds ferry nutrients from the open ocean and deposit them on the atolls as guano that nurtures land plants, marine life and coral growth. This provides more material for reef building, as parrotfish and other reef feeders turn dead coral into sand to maintain beaches, while native plants with extensive root networks stabilize sediments.

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Ukrainian troops have been caught off guard by restrictions on Elon Musk’s Starlink satellite Internet systems that disrupted frontline operations, while Kyiv received no warning from its partners of a Russian missile attack on its energy facilities for the second day running, according to Ukrainian officials.

Starlink terminals used by Ukrainian drone units began experiencing signal failures at speeds above 160 km/h, disrupting several missions early on Wednesday morning, according to military personnel and senior Ukrainian officials.

“Logistics at the frontline and middle strikes are badly limited,” one senior official familiar with the situation on the front told the FT. Ukraine’s middle strikes target Russian military supply lines and logistics. The limitations came with “no warning, just in the middle of the night,” the official said.

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When it comes to deciding the fate of the planet, Colleen Golja always thought science and reason would have a seat at the table. That was until one morning last September in London, when the climate researcher took part in the first in a series of war games. The goal: to prevent an uncontrolled global race to develop a technology aimed at cooling the planet but that comes with vast, unknown risks that could reshape life on Earth.

“I thought that would be such an easy thing. Like, we can all agree to do ethical research and make sure it's for the better of all humans,” she told WIRED. “And boy, was I wrong.”

The simulation, titled Exploring Geopolitical Tipping Points and Climate Cooling Strategies, saw a couple dozen foreign-relations experts, scientists, military personnel, and former government officials from across the world convene in a meeting room at Queen Mary University of London. After making introductions over coffee and little yogurts, they sat at tables arranged in a square with the name of the country or organization each person was playing: national governments, climate NGOs and nonprofits, indigenous groups, and tech companies. Golja was assigned to provide technical advice to help participants make scientifically literate decisions.

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Donald Trump’s administration has temporarily banned Microsoft, Adobe, and several other tech companies from sponsoring workers for permanent US residency, claiming they abused immigration programs at the expense of American citizens.

Vice-president JD Vance said on Thursday that the H-1B visa programme for highly skilled foreign workers had “become rife with fraud” and that over-reliance on such schemes was “a fundamental insult to the American worker.”

He added that “no company in the US” had “abused this system” more than Microsoft.

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If there was a year the world began waking up to climate change, it might have been 1988. That June, the NASA climatologist James Hansen testified to Congress that the climate was warming and would continue to do so as long as humans pumped fossil fuel pollution into the atmosphere. Months later, the United Nations established the Intergovernmental Panel on Climate Change.

And, just weeks before the UN vote, Frank Sprow of Exxon’s corporate research department warned his colleagues in an internal memo, “If a worldwide consensus emerges that action is needed to mitigate against Greenhouse gas effects, substantial negative impacts on Exxon could occur.”

Sprow’s memo is part of a batch of previously undisclosed documents released earlier this year without fanfare as part of an ongoing lawsuit Massachusetts filed against ExxonMobil in 2019. While the memo was quoted in a 2023 article by The Wall Street Journal, it has not been published in full. Several other documents included in the filings are being reported on here for the first time, including more recent statements from Exxon scientists challenging the company’s climate-solution claims about its work on biofuels and carbon capture and storage.

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As tensions mount over who gets access to top-end artificial intelligence, French company Mistral has released a new freely available model that it claims can compete with the very best from the US and China.

The new 1 trillion-parameter model, Mistral Large 4—nicknamed Le Chonk—can be used and customized by anyone. It’s currently available in preview, with a final version to follow by the end of the month. Though Le Chonk is built to compete with leading general-purpose models, it’s optimized specifically for coding and cyberdefense, as well as tasks particular to manufacturing, finance, electrical engineering, and other niches.

“There are a lot of areas where the other labs will not focus that much,” Guillaume Lample, cofounder and chief scientist at Mistral, tells WIRED. “There are so many domains in which you can improve models.”

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