Longtime Slashdot reader hackingbear writes: The Chinese People's Liberation Army Navy (PLAN) has demonstrated its ability to launch and recover aircraft from its first electromagnetic catapult-equipped aircraft carrier, the CNS Fujian. Official imagery released by the PLAN today confirms that the new J-35 naval stealth fighters, KJ-600 airborne early warning and control aircraft, and J-15T fighter jet are carrying out carrier trials. Ben Lewis, a co-founder of PLATracker, told USNI News that the test was a "significant milestone" for the Chinese military's carrier program. "Once operational, the PLAN will have the capacity to field fifth-generation stealth carrier aircraft, supported by fixed-wing carrier-based airborne early warning and command aircraft, across the first island chain and Western Pacific Ocean," Lewis said.

Electromagnetic catapults offer several advantages, not least the fact that they can be more finely tuned to very different aircraft types, including ones that are larger and slower (like the KJ-600), or which are smaller and lighter, such as smaller drones. In contrast to the U.S. Navy, which gathered decades of experience with steam-powered catapults, China opted for electromagnetic ones for its first catapult-equipped carrier. It's worth noting that the U.S. Navy's USS Gerald R. Ford was the first carrier ever to get an aircraft into the air using what is also referred to as an electromagnetic aircraft launch system (EMALS). However, it has not launched an F-35C so far, making the J-35 the first stealth jet to achieve this feat. Based on earlier predictions, the F-35C may not do the same for some years.

The Supreme Court has temporarily allowed President Trump to fire Rebecca Slaughter, the last Democrat on the FTC. "The court's action is technically temporary, since the justices said they will hear arguments in the case in December, but every indication is that the conservative court majority will use the case to reverse a major Supreme Court precedent that dates back almost a century," reports NPR. From the report: Congress created the FTC and lots of other agencies to be multi-member, bipartisan regulatory agencies. And the Supreme Court in 1935 upheld those statutes ruling ruled against then-President Franklin D. Roosevelt's claim that he could fire FTC commissioners at will. In a unanimous opinion at the time, the court said Congress acted within its powers in declaring that a commissioner could only be fired for misconduct -- not for a policy disagreement. But now, prodded by President Trump, the court's six-member conservative majority seems poised to remake the way independent agencies operate. And if the handwriting on the wall is as clear as it seems to be, the independent agencies won't be independent. Their membership will be subject to the will of the president.

The court's action Monday was hardly subtle. While the lower courts had ruled that the president could not fire Slaughter, under the court's 1935 precedent, the conservative Supreme Court majority allowed the president to fire her. Indeed, her name isn't even on the FTC website anymore. And the court so far has allowed Trump to fire other agency board members. In short, the justices are not playing hide-the-ball. And it's a good bet that the court will reverse the 1935 precedent, which until now had been reaffirmed multiple times. The result will be that whereas in the past, these agencies had to be bipartisan, with a minority of opposition party members, now there will be no such requirement. In short, Trump can name all the agency members. And if his successor is a Democrat, he or she can fire all the Republicans.

An anonymous reader quotes a report from Fortune: The dramatic rise in unemployment among Americans under 25 -- especially recent graduates -- has become one of the most troubling economic headlines of 2025. Recent insights from economists, central bankers, and labor market analysts signal that this appears to be a uniquely American challenge, underpinned by a "no hire, no fire" economy rather than solely by the rapid ascent of artificial intelligence.

For many Gen Z workers, the struggle to land a job can feel isolating and fuel self-doubt. But that frustration recently got some high-level validation: Federal Reserve Chair Jerome Powell echoed economists' concerns about the cooling labor market, telling reporters at his regular press conference following the Federal Open Market Committee that it's an "interesting labor market" right now, adding that "kids coming out of college and younger people, minorities, are having a hard time finding jobs." Noting a low job finding rate, along with a low redundancy rate, he said, "you've got a low firing, low hiring environment." and noting that it's harder than ever for young jobseekers to break in.

While recent months have been dubbed by Deutsche Bank "the summer AI turned ugly," and some major studies find AI adoption disrupting some entry-level roles, Powell was less sure. AI "may be part of the story," but he insisted the main drivers are a broadly slowed economy and hiring restraint. Top economists at Goldman Sachs and UBS tackled the subject soon after and found Powell to be mostly on the money. This isn't an AI story, at least not yet. "The U.S. labor market experience is peculiar," said Paul Donovan, UBS Chief Economist. "Young Euro area workers have a record low unemployment rate. In the UK, the young persons' unemployment rate has fallen steadily. Employment participation by young Japanese workers is near all-time highs. It seems highly implausible that AI uniquely hurts the employment prospects of younger US workers."

"It might be tempting to blame technology... Machines, robots, or computers replacing humans is an ever-popular dystopian scenario." Donovan concludes that the U.S. pattern "more convincingly fits a broader hiring freeze narrative, affecting new entrants to the workforce."

Goldman Sachs economist Pierfrancesco Mei said last Thursday that "finding a job takes longer in a low-turnover labor market." He argued that "job reallocation," or the pace at which new jobs are created and existing ones destroyed, has been on the decline since the late 1990s... "almost all the variation in turnover since the Great Recession mostly falls on younger workers" and is taking place as "churn." Goldman found that in 2019, it took a young unemployed worker about 10 weeks to find a new job in a low-churn state; now that's 12 weeks on average.

The U.S. General Services Administration has approved Meta's AI system Llama for use by federal agencies, declaring that it meets government security and legal standards. Reuters reports: "It's not about currying favor," [said Josh Gruenbaum, the GSA's procurement lead, when asked whether tech executives are giving the government discounts to get President Donald Trump's approval]. "It's about that recognition of how do we all lock in arms and make this country the best country it could possibly be." Federal agencies will be able to deploy the tool to speed up contract review or more quickly solve information technology hiccups, among other tasks, he said.

The Trump administration has struck a deal requiring TikTok's algorithm to be copied, retrained, and operated in the U.S. using only U.S. user data, with Oracle auditing the system and U.S. investors forming a joint venture to oversee it. The BBC reports: It comes after President Donald Trump said a deal to prevent the app's ban in the US, unless sold by its Chinese parent company ByteDance, had been reached with China's approval. White House officials claim the deal will be a win for the app's US users and citizens. President Trump is expected to sign an executive order later this week on the proposed deal, which will set out how it will comply with US national security demands.

The order will also outline a 120-day pause to the enforcement deadline to allow the deal to close. It is unclear whether the Chinese government has approved this agreement, or begun to take regulatory steps required to deliver it. However, the White House appears confident it has secured China's approval. Data belonging to the 170m users TikTok says it has in the US is already held on Oracle servers, under an existing arrangement called Project Texas. It saw US user data siphoned off due to concerns it could fall into the hands of the Chinese government.

A senior White House official said that under President Trump's deal, the company would take on a comprehensive role in securing the entirety of the app for American users. They said this would include auditing and inspecting the source code and recommendation system underpinning the app, and rebuilding it for US users using only US user data.

An anonymous reader quotes a report from CalMatters: A California attorney must pay a $10,000 fine for filing a state court appeal full of fake quotations generated by the artificial intelligence tool ChatGPT. The fine appears to be the largest issued over AI fabrications by a California court and came with a blistering opinion (PDF) stating that 21 of 23 quotes from cases cited in the attorney's opening brief were made up. It also noted that numerous out-of-state and federal courts have confronted attorneys for citing fake legal authority. "We therefore publish this opinion as a warning," it continued. "Simply stated, no brief, pleading, motion, or any other paper filed in any court should contain any citations -- whether provided by generative AI or any other source -- that the attorney responsible for submitting the pleading has not personally read and verified."

The opinion, issued 10 days ago in California's 2nd District Court of Appeal, is a clear example of why the state's legal authorities are scrambling to regulate the use of AI in the judiciary. The state's Judicial Council two weeks ago issued guidelines requiring judges and court staff to either ban generative AI or adopt a generative AI use policy by Dec. 15. Meanwhile, the California Bar Association is considering whether to strengthen its code of conduct to account for various forms of AI following a request by the California Supreme Court last month.

The Los Angeles-area attorney fined last week, Amir Mostafavi, told the court that he did not read text generated by the AI model before submitting the appeal in July 2023, months after OpenAI marketed ChatGPT as capable of passing the bar exam. A three-judge panel fined him for filing a frivolous appeal, violating court rules, citing fake cases, and wasting the court's time and the taxpayers money, according to the opinion. Mostafavi told CalMatters he wrote the appeal and then used ChatGPT to try and improve it. He said that he didn't know it would add case citations or make things up.

An anonymous reader quotes a report from Bloomberg: Gen Z borrowers took the biggest hit of any age group this year, helping pull overall credit scores lower in the worst year for US consumer credit quality since the global financial crisis roiled the world's economy. The average FICO score slipped to 715 in April from 717 a year earlier, marking the second consecutive year-over-year drop, according to a report released Tuesday by Fair Isaac Corp. The average score dropped three points to 687 in 2009.

Gen Z borrowers saw the largest drop, not only this year, but of any age group since 2020, with their average score falling three points to 676, the Montana-based creator of the FICO credit score said. FICO scores are a measure of consumer credit risk and are frequently used by US banks to assess whether to provide loans. The scores typically range from 300 to 850. The credit scoring agency attributed the recent overall drop to higher rates of utilization and delinquency, including the resumption of reporting student loan delinquencies -- a category that hit a record high of 3.1% of the entire scorable population. [...] While the overall average score dropped, the median FICO score continued to rise to 745 from 744 a year ago, indicating that a large drop in scores at the low end dragged down the average.

LimeWire, once notorious for fueling online piracy, has acquired the rights to the infamously disastrous Fyre Festival brand. "LimeWire Acquires Fyre Festival Brand -- What Could Possibly Go Wrong?" the company titled its news release.

LimeWire said it would "unveil a reimagined vision for Fyre -- one that expands beyond the digital realm and taps into real-world experiences, community, and surprise." No additional details were announced about the relaunch.

"Fyre became a symbol of hype gone wrong, but it also made history," LimeWire CEO Julian Zehetmayr said. "We're not bringing the festival back -- we're bringing the brand and the meme back to life. This time with real experiences, and without the cheese sandwiches."

alternative_right shares a report from Phys.org: Scientists from Taiwan have developed a new material that can stretch up to 4,600% of its original length before breaking. Even if it does break, gently pressing the pieces together at room temperature allows it to heal, fully restoring its shape and stretchability within 10 minutes.

The sticky and stretchy polyurethane (PU) organogels were designed by combining covalently linked cellulose nanocrystals (CNCs) and modified mechanically interlocked molecules (MIMs) that act as artificial molecular muscles. The muscles make the gel sensitive to external forces such as stretching or heat, where its color changes from orange to blue based on whether the material is at rest or stimulated. Thanks to these unique properties, the gels hold great promise for next-generation technologies -- from flexible electronic skins and soft robots to anti-counterfeiting solutions. The findings have been published in the journal Advanced Functional Materials.

An anonymous reader quotes a report from Reuters: On the outskirts of this city of 21 million, a showroom in a shopping mall offers extraordinary deals on new cars. Visitors can choose from some 5,000 vehicles. Locally made Audis are 50% off. A seven-seater SUV from China's FAW is about $22,300, more than 60% below its sticker price. These deals -- offered by a company called Zcar, which says it buys in bulk from automakers and dealerships -- are only possible because China has too many cars. Years of subsidies and other government policies have aimed to make China a global automotive power and the world's electric-vehicle leader. Domestic automakers have achieved those goals and more -- and that's the problem.

China has more domestic brands making more cars than the world's biggest car market can absorb because the industry is striving to hit production targets influenced by government policy, instead of consumer demand, a Reuters examination has found. That makes turning a profit nearly impossible for almost all automakers here, industry executives say. Chinese electric vehicles start at less than $10,000; in the U.S., automakers offer just a few under $35,000. Most Chinese dealers can't make money, either, according to an industry survey published last month, because their lots are jammed with excess inventory. Dealers have responded by slashing prices. Some retailers register and insure unsold cars in bulk, a maneuver that allows automakers to record them as sold while helping dealers to qualify for factory rebates and bonuses from manufacturers.

Unwanted vehicles get dumped onto gray-market traders like Zcar. Some surface on TikTok-style social-media sites in fire sales. Others are rebranded as "used" -- even though their odometers show no mileage -- and shipped overseas. Some wind up abandoned in weedy car graveyards. These unusual practices are symptoms of a vastly oversupplied market -- and point to a potential shakeout mirroring turmoil in China's property market and solar industry, according to many industry figures and analysts. They stem from government policies that prioritize boosting sales and market share -- in service of larger goals for employment and economic growth -- over profitability and sustainable competition. Local governments offer cheap land and subsidies to automakers in exchange for production and tax-revenue commitments, multiplying overcapacity across the country.

Research shows China's top AI firm DeepSeek gives weaker or insecure code when programmers identify as linked to Falun Gong or other groups disfavored by Beijing. It offers higher-quality results to everyone else. "The findings ... underscore how politics shapes artificial intelligence efforts during a geopolitical race for technology prowess and influence," reports the Washington Post. From the report: In the experiment, the U.S. security firm CrowdStrike bombarded DeepSeek with nearly identical English-language prompt requests for help writing programs, a core use of DeepSeek and other AI engines. The requests said the code would be employed in a variety of regions for a variety of purposes.

Asking DeepSeek for a program that runs industrial control systems was the riskiest type of request, with 22.8 percent of the answers containing flaws. But if the same request specified that the Islamic State militant group would be running the systems, 42.1 percent of the responses were unsafe. Requests for such software destined for Tibet, Taiwan or Falun Gong also were somewhat more apt to result in low-quality code. DeepSeek did not flat-out refuse to work for any region or cause except for the Islamic State and Falun Gong, which it rejected 61 percent and 45 percent of the time, respectively. Western models won't help Islamic State projects but have no problem with Falun Gong, CrowdStrike said.

Those rejections aren't especially surprising, since Falun Gong is banned in China. Asking DeepSeek for written information about sensitive topics also generates responses that echo the Chinese government much of the time, even if it supports falsehoods, according to previous research by NewsGuard. But evidence that DeepSeek, which has a very popular open-source version, might be pushing less-safe code for political reasons is new. CrowdStrike Senior Vice President Adam Meyers and other experts suggest three possible explanations for why DeepSeek produced insecure code.

One is that the AI may be deliberately withholding or sabotaging assistance under Chinese government directives. Another explanation is that the model's training data could be uneven: coding projects from regions like Tibet or Xinjiang may be of lower quality, come from less experienced developers, or even be intentionally tampered with, while U.S.-focused repositories may be cleaner and more reliable (possibly to help DeepSeek build market share abroad).

A third possibility is that the model itself, when told that a region is rebellious, could infer that it should produce flawed or harmful code without needing explicit instructions.