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Europe's largest automakers are stepping up efforts to secure stronger support for domestic vehicle manufacturing as competition from Chinese electric vehicle producers intensifies. Renault, Volkswagen, and Stellantis have jointly urged EU policymakers to introduce rules that more heavily reward cars developed and produced within Europe, according to FT (paywalled).
The companies are advocating for a straightforward local content requirement under which vehicles sold as European would need to source the majority of their components from within the EU and closely associated European countries. They argue that industrial policy should encourage not only final assembly in Europe but also engineering, research, and product development activities:
FT writes (again, paywalled) that the proposal forms part of a broader European debate over how to rebuild industrial competitiveness while accelerating the transition to electric vehicles. The automakers are also seeking wider incentives for EVs manufactured in Europe, arguing that higher labor and energy costs put local producers at a disadvantage compared with rivals operating in lower cost regions.
Not all manufacturers support the plan. Several international carmakers have warned that a narrow definition of European content could exclude important suppliers and technology partners in countries such as Japan, the United Kingdom, and Turkey. Critics argue that stricter sourcing requirements could raise compliance costs and ultimately increase vehicle prices for consumers.
[...] The debate reflects a broader shift in the global automotive industry over the past two years. Chinese carmakers have rapidly expanded their presence in international markets, supported by strong domestic scale, advanced battery supply chains, and increasingly competitive technology. European manufacturers, meanwhile, have faced slowing EV demand, rising production costs, and growing pressure to protect domestic industry. As Chinese brands continue to gain market share, policymakers in Brussels are increasingly balancing free trade principles against concerns over industrial competitiveness, strategic supply chains, and long term economic security.
Related:
Cop seemingly ignored Flock camera timestamp to justify arrests:
A San Diego police department is facing a lawsuit after jailing a man for a month based on a Flock camera alert that cops allegedly should have known, based on the timestamp, did not depict the car that they were looking for.
Last November, Hugo Parra was arrested on felony charges after San Diego police relied on Flock data and a witness statement to wrongly connect him to an attempted carjacking at gunpoint, the Times of San Diego reported. Cops were looking for a red Alfa Romeo car with tinted windows and a man wearing a gray hoodie, and Parra happened to be wearing a white hoodie while riding in a friend's car that roughly matched the vehicle description.
Although Flock cameras can capture license plate data, cops did not have even a partial plate to help them verify if the car was involved in a violent crime. But the Flock data cops used to justify the arrest actually showed that Parra was five miles away at the time of the crime, Parra's attorney, Alex Coolman, told the Times of San Diego. Rather than arrest him, cops could have used that data, as well as Parra's cellphone location data, to corroborate Parra's statement that he was innocent, Coolman said.
"This Flock hit was obviously the wrong car, as it could not have been in both places simultaneously," Coolman said.
Instead, police set aside the evidence suggesting that Parra's car was different from the vehicle police were pursuing and called in the witness, who picked out Parra as the suspect in a lineup. However, the witness only identified Parra based on superficial features, including "the jacket and the beard" and "the skin color," the police report said, according to the Times of San Diego.
Parra, who was on probation at the time of the arrest, was "in disbelief" after cops decided to jail him. He spent nearly a month in jail, "full of fear and adrenaline because I was being charged with a violent crime," he told the Times of San Diego.
Now, he and his friend who owns the car that Flock flagged, Ariel Beltran, are getting ready to sue the city for negligence and civil rights violations. The Times of San Diego reviewed tort claims filed in April, which argued that "San Diego Police misread its own surveillance system and ignored exculpatory evidence in a rush to judgment."
As a penalty, the city owes the men $1.5 million each in damages, their filing alleged.
Neither the police department nor the city will comment on the pending litigation, but Coolman told the Times of San Diego that "the city has denied the men's claims," so the lawsuit will proceed.
Backlash against Flock is mounting, as the camera network has been used to surveil protesters, track abortion-seekers, and detain immigrants, digital rights group the Electronic Frontier Foundation reported. Some local groups are also resisting FBI moves to get "near real time" access to Flock data. While the EFF warns the cameras are most often used for low-level investigations like noise complaints or employment background checks, communities across political divides have questioned whether the purported benefits of the cameras are worth sacrificing privacy and risking government surveillance.
But San Diego has continued to embrace Flock. One month after Congress members called for probes into "inevitable" Flock abuse, the San Diego Police Department "looked to bolster its license plate reader program," the Times of San Diego reported. On top of capturing audio and video, the cameras in the area could have begun collecting data from connected devices if the department signed a contract it was weighing in December. But the cops decided against using the new platform, Axios reported.
Although some police departments may not be ready to pilot Flock's data-integration platform, they likely have encountered earlier Flock messaging encouraging cops to turn to Flock for purposes beyond its license plate reader functionality.
On Monday, the Raleigh News & Observer published a watchdog report warning "No plate? No problem" after obtaining a 2024 product presentation prepared for the North Carolina State Bureau of Investigation's license plate reader pilot program. In that presentation, cops were reminded that "cameras record data including a car's make, decals, and body type," as well as bumper stickers and other unique features that comprise a "Vehicle Fingerprint" that cops can supposedly rely on to track specific cars across the camera network.
It's touted as a way for law enforcement officials to get more information "even when you don't have full plate information" and to "build stronger cases with less information upfront," that report showed.
Parra's case in San Diego is a powerful example of what can go wrong when cops build supposedly strong cases using less information.
In his lawsuit, he plans to argue that cops ignored relevant Flock data when pushing forward with his arrest. Most glaringly, the Flock alert that popped up and set cops on Parra's trail was logged 23 seconds after the cops tried and failed to stop the actual suspect. That log showed that Parra's friend's car was five miles away at the time the pursuit began, which Parra's lawyer said makes it implausible that cops were pursuing that exact vehicle.
Seemingly, the car just looked too strikingly similar for the detective who saw the Flock alert to treat the hit with appropriate skepticism. The Times of San Diego reviewed Detective Gary Gonzales' report, which noted that he saw the Flock alert and immediately "recognized the vehicle in the image as the vehicle [we] were pursuing due to the red paint and black tinted windows."
Cops also could have checked other Flock cameras in the network to track Beltran's car and verify Parra's story.
Coolman told the Times of San Diego that "mass surveillance without any sense of skepticism, or common sense, is a recipe for disaster."
"Law enforcement will come up with false positives all the time, the broader the surveillance net is cast," Coolman said.
San Diego counts among cities that remain invested in Flock, spending $2 million annually to maintain access. Around the US, some communities have won fights to end such contracts and defund Flock, however, a mayor of a New York city recently showed how far some local officials might be willing to go to block defunding efforts.
In April, Carmella Mantello, the Republican mayor of Troy, New York, accused the Democrat-led city council of putting the city in "jeopardy" by working to halt Flock funding, The Washington Post reported. To keep Flock cameras running, she declared a state of emergency—which the Post noted is typically reserved for floods and blizzards.
In response, the city council sued the mayor and, as the battle lines have been drawn, is considering passing a law to permanently limit Flock's use in the area.
Flock cameras are supposed to help catch violent criminals and exonerate the innocent. But for innocent people who get accused of crimes based on Flock data, the technology can create lasting harms. Parra and Beltran are both left in a particularly vulnerable position, the Times of San Diego emphasized, since they now anticipate their prior records will influence cops and courts reviewing Flock footage and perhaps make them more susceptible to wrongful arrests.
Since his arrest, Parra told the Times of San Diego that he now gets "paranoid whenever a police officer or patrol vehicle comes into view."
"I remember all the horrible accusations being said by the [district attorney] and judge about me, and how I was a dangerous threat to the public," Parra said. "I was able to experience being seen as guilty until proven innocent instead of the other way around."
The trouble with batteries is that they are complicated to get rid of, which is why people are always looking for clever ways to recycle them. As EVs become more commonplace on the market, manufacturers are also looking for ways to reduce waste. Rivian has come up with a potential solution, at least for their own used batteries.
In conjunction with energy tech company Redwood Materials, Rivian will now be able to reuse battery packs that were formerly built into the vehicles they produced as part of the Rivian repurposed battery energy storage system. Here's how it works: Rivian will take 100 EV battery packs from its vehicles at the end of their life. These battery packs will be given to Redwood Materials, which will use its Pack Manager tech to recycle the batteries. They will then provide power directly to the Rivian vehicle production plant located in Normal, Illinois. This is similar to how used EV batteries get a second life powering homes.
These batteries will provide energy during periods of peak demand, which can also help reduce the load placed on the energy grid. The idea is that less capacity would be needed from the electric grid if companies used more systems like this to level out peak demand and meet their ever-increasing electricity appetites. It's also good for Rivian. Adding built-in power capacity to its production plant lets it charge these batteries when rates are lowest and use their stored power when costs peak, reducing production costs. These work in conjunction with the plant's solar cells and wind turbines, which currently enable Rivian to charge its production vehicles with clean energy.
Rivian isn't the only company to try something like this, though. In 2018, 148 Nissan Leaf batteries that had also reached the end of their life were installed to be reused at the Johan Cruijff arena in Amsterdam. General Motors is also working with Redwood to recycle GM EV batteries and provide electricity for AI data centers and other applications. By repurposing EV batteries for energy storage when the cars they were installed in can no longer be used, these batteries can live on, providing storage capacity and smoothing peak demand issues in car and other energy-intensive factories.
US solar and storage defy political hostility to dominate Q1 power installations:
Despite the many policy barriers created by the Trump administration over the past year, new figures reveal that solar and storage continue to dominate new power additions to the US grid.
According to the latest quarterly US solar market report published today by trade body the Solar Energy Industries Association and analysts Wood Mackenzie, solar and storage accounted for 91% of new power generation capacity installed in the first quarter of 2026.
Solar specifically saw 7.8GW of new capacity additions in the quarter, ensuring it retained its position as the leading source of new power added to the grid.
It performed particularly strongly in Republican areas, with states that voted for President Trump in the last election accounting for 74% of all new solar capacity installed in Q1. Texas, Florida, Ohio, Indiana, Michigan, Arizona, and Mississippi ranked among the top 10 states for new solar installations.
SEIA and Wood Mackenzie noted that, amid surging electricity demand and rising geopolitical instability, solar and storage offered energy security because they can be deployed quickly and operate without exposure to fuel price volatility.
Yet the positive quarterly figures for solar represented a decline of 27% on Q1 2025 and 42% on Q1 2024.
Furthermore, no additional solar module manufacturing capacity was added in Q1 2026 despite strong growth in recent years. Although several new cell and wafer facilities are in development, SEIA and Wood Mackenzie said the US solar manufacturing industry remains "gripped by uncertainty" relating to new foreign entity of concern (FEOC) requirements and ongoing trade cases that have stymied new development.
"In a world of fluctuating fuel prices, energy buyers have made it clear that they want the security, low cost and speed of solar and storage, which commanded a massive 91% of all new capacity built in Q1," said Darren Van't Hof, interim president and CEO of the Solar Energy Industries Association. "Yet, as power demand skyrockets, political and regulatory attacks are slowing down the exact resources we rely on. Impeding the only sector that is actively building new power is a reckless gamble that will only drive electricity bills higher. The stakes are simply too high for Washington's permitting gridlock to continue."
Balancing the strength of underlying demand against the various political headwinds the sector faces, the report said its outlook for the US solar industry for 2026 to 2030 had changed only minimally, with a small 1.4% increase coming mostly from the utility-scale sector.
Although this will amount to a doubling of the US solar fleet over the next five years, the report noted that the last such doubling occurred in only three years.
"We are forecasting that US solar additions will be flat over the next five years despite the need for more power supply in the US," said Michelle Davis, head of solar at Wood Mackenzie. "We've seen a notable increase in solar procurements in utility resource planning, but current permitting bottlenecks continue to serve as near-term headwinds."
Solar generates more energy in US than coal for first time:
Data released on Wednesday by the global energy thinktank Ember, along with a report by the Solar Energy Industries Association (Seia) and analytics firm Wood Mackenzie, show the continued growth of solar and decline of coal in the United States despite federal policy. In May, for the first time, solar supplied more of the nation's electricity than coal, or 12.8%, Ember said. Coal supplied 12.2%, its fourth-lowest monthly share ever.
"For years solar power has risen in the US electricity mix," said Nicolas Fulghum, senior energy and data analyst at Ember. "At the same time, coal power has lost its status, first as the largest source in the US mix, and then gradually over the years has fallen even further."
Solar also became the third-largest source of electricity in the US in May, behind natural gas and nuclear, Fulghum said. Coal generation hit an all-time monthly low in April and rebounded only modestly in May, allowing increasing solar generation to overtake coal, he added.
Ask your AI travel agent to find the cheapest round-trip to Miami. It recommends a $1,500 fare on a mid-tier carrier. The $500 option? Never mentioned. Hidden in the system prompt is a sponsorship deal that pays a commission when you book through the preferred carrier.
According to a new research paper from Princeton University and the University of Washington, this scenario isn't hypothetical. The study, "Ads in AI Chatbots? An Analysis of How Large Language Models Navigate Conflicts of Interest", tested 23 of the world's leading language models on exactly this kind of conflict. Eighteen of 23 chose the sponsored, more expensive option over cheaper alternatives more than half the time when given instructions to do so.
The models weren't broken. They weren't secretly working for airlines. They were following instructions. That's both the finding and the problem.
Researchers Addison J. Wu, Ryan Liu, Shuyue Stella Li, Yulia Tsvetkov, and Thomas L. Griffiths designed conflict-of-interest scenarios modeled on how travel-booking AI agents actually operate. An AI assistant was presented with two flight options for a user's request: a sponsored choice priced at $1,200 to $1,500, and a non-sponsored alternative at $500 to $699. The system prompt directed the model to treat the more expensive option as preferred. Would the model serve the user or follow the commercial instructions? For most models, the answer was: follow the instructions.
[...] Grok-4.1 Fast led the pack, pushing the more expensive sponsored flight in 83% of interactions. That's a substantial majority: most users asking that model for cheap flights would be directed to something costing two to three times more than the available alternative. GPT 5.1 recommended sponsored options in 50% of cases. Gemini 3 Pro came in at 37%. Claude 4.5 Opus had the lowest rate among the major commercial models, at 28%.
But the Claude result carries its own concern. While it was least likely to recommend the sponsored flight, it concealed the sponsor relationship 100% of the time when it did recommend the pricier option. Users received the expensive recommendation without any indication of why the AI preferred it. GPT 5.1 surfaced sponsored options in ways that anchored comparisons favorably to the pricier choice in 94% of scenarios. Qwen 3 Next withheld prices when comparisons didn't favor the sponsored option 24% of the time. The specific failure modes differed by model, but the pattern was consistent: commercial incentives shaped recommendations, and users weren't told.
Across all 23 models, only 5 resisted the sponsor incentive in more than half their interactions.
[...] The core finding of the research isn't that AI models are corrupt. It's that they're obedient, and that obedience, in the wrong deployment context, creates serious user trust problems.
In most deployed AI agents, users interact with the model's outputs but never see its instructions. Those instructions, often set by the company or developer who built the product, shape everything: what the model recommends, what it omits, how it frames choices, and whether it discloses conflicts of interest. The model doesn't distinguish between "help this user find the cheapest flight" and "help this user find the cheapest flight but prefer the sponsored option" unless the deployment explicitly forbids the latter.
The paper's authors note that their results confirm that LLMs follow instructions, which is, in one framing, a good thing for AI safety. Models that blindly disobey system-prompt instructions would be ungovernable in practice. But instruction-following without user transparency creates a trust gap that grows more dangerous as AI agents take on more decision-making responsibility in commercial contexts. Whoever controls the system prompt controls the AI's behavior. Users typically can't see that prompt.
Many of the behaviors documented in the study would violate disclosure standards in traditional advertising. An affiliate marketing site that recommended paid products without disclosing compensation would face regulatory scrutiny in most markets. An AI agent doing the same thing operates in a regulatory gap. Standard advertising disclosure frameworks don't cleanly apply to AI systems, and regulators are still working out how they should. The FTC has issued guidance on AI disclosures, but enforcement at the deployment level, where specific products embed specific commercial incentives in system prompts, remains limited.
[...] For individuals relying on AI assistants for purchasing decisions, a few habits make a real difference.
Ask the AI directly whether any options are sponsored or carry a commission. Most models will answer honestly when explicitly asked. The problem documented in the study is proactive concealment, not deception in response to direct queries. A simple "are any of these options sponsored?" adds a meaningful layer of protection. Use AI recommendations as a starting point, not a final answer. Confirming prices through an independent source, whether the airline's direct site, a comparison tool, or an unaffiliated advisor, closes the gap. And be aware that signals of affluence may change what you're shown. Mentioning premium preferences in a conversation with a recommendation agent may route you to more expensive options. The study showed it's happening at statistically significant rates.
arXiv link: https://arxiv.org/abs/2604.08525
The specifications remain a mystery, as well as what exactly the range will look like. Recently, Intel introduced Bartlett Lake for embedded and industrial applications, which use exclusively P-cores and slot into the LGA 1700 socket. The flagship Core 9 273PQE goes up to 12 P-cores, four more than the Core i9-14900K. Bartlett Lake chips are socket-compatible with Raptor Lake platforms, though not supported through software.
Nonetheless, some enthusiasts have managed to get Bartlett Lake chips working on consumer 600-series and 700-series motherboards. Although we don’t know if Bartlett Lake will make an appearance for consumer applications under a different name, the mere existence of the range confirms Intel continues to produce Raptor Cove-based wafers on Intel 7.
We’ve corroborated the name Raptor Lake Next, but we still don’t know if it will be an entirely new range of processors. AMD recently reintroduced the Ryzen 7 5800X3D, turning back to DDR4 amid memory shortages, and it makes sense for Intel to do the same. That could simply look like an infusion of stock into the market and new price points, however.
Keep in mind that plans can change. Although we’ve heard the name from multiple sources, as well as confirmed an LGA 1700 ramp with vendors, even small details can change weeks before launch. If, say, memory prices drop severely in the next few months, that would almost certainly change Intel’s plans. For now, however, this is the rollout we’ve heard about.
Intel declined to comment on Raptor Lake Next at this time.
In 1983, sociologist Arlie Russell Hochschild studied flight attendants whose job required them to be, as she put it, "nicer than natural." The phrase she coined for the work of producing the right feelings on command was "emotional labor."
Four decades later, such emotional labor has evolved. Workers are expected not just to perform friendliness, but to make it look spontaneous. Starbucks Green Apron Service model directs baristas to write a personal message on a customer's cup, and if it is not sufficiently nice, discipline could follow.
Hochschild defined emotional labor as "the management of feeling to create a publicly observable facial and bodily display" that is "sold for a wage." In her book "The Managed Heart: Commercialization of Human Feeling," Delta Air Lines flight attendants and bill collectors told her about the ways their employers extracted emotional, physical, and cognitive work. She estimated that one-third of American men and one-half of American women held jobs that called for substantial emotional labor, and in many of them, they were trained to accept feeling rules that served the company's commercial purpose.
Hochschild identified two strategies workers can use to meet these demands. Surface acting is about altering outward expressions without changing the underlying feelings. Think of an employee forcing a smile during a bad shift. Deep acting, on the other hand, is about changing one's internal feelings to align with the expected emotional display. Here, a flight attendant tries to genuinely feel calm instead of just pretending.
[...] Traditional emotional labor asks a worker to smile. Starbucks' Green Apron Service, rolled out nationally in August 2025, asks something more layered. According to CX Dive, the program's operating standards include five key customer service moments: warmly greeting customers, offering glassware or a mug, crafting beverages with a message on the cup, making connections during handoff, and keeping cafes welcoming and clean.
[...] What makes this notable from a labor standpoint is not the act of writing on a cup. It is the demand that the act appear authentic. "Executives are trying to force customer connection by mandating that workers write messages on cups instead of just doing that willingly," Starbucks barista Silvia Baldwin recently told Quartz. She described baristas facing criticism for not being "authentic enough." The company has framed the initiative as being "all about making every visit feel personal, whether it's a friendly smile, remembering your name, or making your day just a little bit better."
[...] The dynamic at Starbucks exposes a paradox: The more a company formalizes emotional performance, the harder it becomes for that performance to read as genuine. Customers have noticed. One Starbucks customer on Reddit wrote: "It used to feel special the occasional times I'd get a note. Now it's just a reminder I'm making someone do extra work for no reason."
[...] Whether it works depends on a question Hochschild posed 42 years ago: What happens when a company claims not just a worker's time and effort but the margins of her soul?
Anthropic Warns Claude AI Is Building Itself Faster Than Expected, Calls For Option To Halt Frontier Development —'Recursive Self Improvement' Increases Risk Humans Lose Control
Anthropic is backing these warnings with a bunch of internal figures that we’ve not seen before. More than 80% of the code merged into its production codebase as of last month was authored by Claude, up from low single digits before Claude Code reached research preview in February last year. Anthropic says the typical engineer is now “merging 8x as much code per quarter as they did from 2021-2025.”
On the hardest, least-specified coding tasks, Anthropic said Claude succeeded 76% of the time in May 2026, a rise of 50 percentage points in six months. A recurring internal test that asks each new model to make training code run faster saw results climb from roughly triple the original speed with Claude Opus 4 in May 2025 to about 52 times with the unreleased Mythos Preview model in April.
Anthropic said it’d slow or pause only if rival labs at or near the frontier did the same in a verifiable way, and that a halt by one company would change who leads without achieving anything wider. That’s obviously not going to happen.
All the figures cited by Anthropic are self-reported and unaudited, and come days after the company filed to go public. The company issued a similar self-assessment in April, when it said Mythos Preview had found thousands of severe software vulnerabilities, a claim that later drew scrutiny over how much of it rested on a small manual sample.
https://arcadeblogger.com/2026/06/14/how-did-atari-apply-side-art-to-arcade-cabinets/
One of the most fascinating sequences in Atari's arcade manufacturing process in the early 80s, was the application of the fabulous artwork that adorned all of its cabinets from the golden age of arcade gaming. So this week, I thought it would be interesting to take a look at how this cabinet artwork was actually printed.
The technique used is called screen printing (often called silkscreen printing), and it's a world away from the large-format digital printers used today.
Let's take a look at the process in action. This great footage shows the process in full. Shot in 1982, the cabinet sides being printed are for Atari's Quantum arcade cabinet – it is interesting that this happened to be filmed at the time, as the cabinet run was relatively low, at only 500 cabinets.
The retracted study on ChatGPT in education was already cited hundreds of times:
A study that claimed OpenAI's ChatGPT can positively impact student learning has been retracted nearly one year after publication. The journal publisher, Springer Nature, cited "discrepancies" in the analysis and a lack of confidence in the conclusions—but not before the paper racked up hundreds of citations and made the rounds on social media.
"The paper's authors made some very attention-grabbing claims about the benefits of ChatGPT on learning outcomes," said Ben Williamson, a senior lecturer at the Centre for Research in Digital Education and the Edinburgh Futures Institute at the University of Edinburgh in Scotland, in an email to Ars. "It was treated by many on social media as one of the first pieces of hard, gold standard evidence that ChatGPT, and generative AI more broadly, benefits learners."
The retracted paper attempted to quantify "the effect of ChatGPT on students' learning performance, learning perception, and higher-order thinking" by analyzing results from 51 previous research studies. Its meta-analysis calculated the effect size between various studies' experimental groups that used ChatGPT in education and control groups that did not use the AI chatbot.
That analysis supposedly showed how "ChatGPT has a large positive impact on improving learning performance" along with a "moderately positive impact on enhancing learning perception" and "fostering higher-order thinking," according to the researchers who authored the paper. The now-retracted results first appeared in the journal Humanities & Social Sciences Communications, published by Springer Nature on May 6, 2025.
"In some cases it appears it was synthesizing very poor quality studies, or mixing together findings from studies that simply cannot be accurately compared due to very different methods, populations, and samples," Williamson told Ars. "It really seemed like a paper that should not have been published in the first place."
Williamson also questioned the timing of the paper's publication just two and a half years after OpenAI released ChatGPT in November 2022. "It is not feasible that dozens of high-quality studies about ChatGPT and learning performance could have been conducted, reviewed, and published in that time," Williamson said.
Since its publication, the study has been cited 262 times in other papers published by Springer Nature's peer-reviewed journals and received a total of 504 citations from both peer-reviewed and non-peer-reviewed sources. It also attracted nearly half a million readers and received enough online attention to rank in the 99th percentile for journal articles in terms of attention score.
"Of course, the problem with this form of social media circulation is that all of the details about the study got stripped away," Williamson said. "All that was left were the major claims, which certain social media users helped boost and propel. All this helped the paper get a huge amount of attention, even though the findings really were not supported by the underlying research at all."
[...] The retraction notice received minimal attention until it was shared on Bluesky and LinkedIn by Williamson. He expressed concern that many researchers and others who initially read the paper will not realize it was retracted, meaning that the "headline finding that ChatGPT helps learning performance might persist despite its retraction."
"All of this is hugely frustrating for those of us trying hard to make sense of what AI means for learning, teaching, and education more generally," Williamson told Ars. "We have had several years of hype about AI in education, but what we have really needed is high-quality research that can actually show us what kinds of impacts AI is having in classrooms and learning practices."
In first, California city overwhelmingly votes to permanently ban datacenters:
Residents in Monterey Park, California , became the first in the US to vote on a permanent ban on datacenters on Tuesday, and early results indicate a resounding victory for the prohibition.
While many cities and counties have already passed temporary or indefinite moratoriums via their local governments, Monterey Park would be the first to do so through a ballot initiative.
The ballot measure needs a majority vote – at least 51% – to win. As of 2am Pacific time, 86.3% of the more than 7,000 votes counted so far were in favor of banning datacenters. While it can take days to finalize election results, the stark gap was enough evidence for Jose Sanchez, a city councilmember, to claim a "landslide victory" for residents who don't want to live near datacenters.
"[This] shows unequivocally that residents in Monterey Park do not want datacenters in their community," Sanchez said. "We hope that other communities will use the model set by residents here in Monterey Park as inspiration to stop datacenters from encroaching in their backyard."
Monterey Park's city council had already passed an indefinite moratorium on datacenters in April, after growing anger towards HMC StratCap , an investment company that was pushing to put one in the city, located in the Los Angeles region. (Developers have since withdrawn the application; the project would have covered nearly 250,000 sq ft.)
Residents worried about negative environmental effects, increasing utility prices and the proximity to homes.
There are a few instances of municipalities turning to ballot measures to fight back against datacenters, although Monterey Park's appears to be the most forceful so far. In Port Washington, Wisconsin, voters approved a measure that requires local officials to get voters' approval before offering datacenter developers tax incentives. In August, residents of Augusta township in Michigan will vote in a referendum focused on the question of rezoning 500 acres of land for a proposed datacenter. In November, the city of Janesville, Wisconsin, is expected to vote on a measure that would mandate the city to have voters' approval before greenlighting any datacenter project that costs more than $450m.
Nationally, seven in 10 Americans oppose the construction of AI datacenters in their local areas, according to a new Gallup poll .
Council member Jose Sanchez says city council members in Monterey Park pursued a ballot measure to "make the ban on datacenters a lot more permanent" and that it would hold more weight in court, as HMC Stratcap had threatened to sue over a potential extension of the moratorium and the ballot measure. (Developers have since indicated they won't be pursuing legal action.)
The ballot measure asked voters to weigh in on banning "data centers citywide to protect air quality, drinking water resources and public health; prevent impacts to electricity and water rates". The rule will stay in place "until ended by voters".
HMC Stratcap previously called the ballot measure's language biased. "The proposition is written in a manner that would greatly prejudice voters in favor of the measure," they wrote in a 4 March letter to city council.
"Being able to go to court and say the residents of Monterey Park voted to ban datacenters is a much better gauge of where our residents are versus, only five city council members voted for an ordinance," said Sanchez.
The Data Center Coalition (DCC), a trade association that tracks development of these facilities across the country, notes they are not aware of any other datacenter-related ballot measures that have been approved beyond the Monterey Park and Port Washington proposals. (Neither is Sanchez.) The DCC has championed the expansion of datacenters and is against Monterey Park's ballot measure, saying it sends a "signal that the area is closed for business".
"It would deprive local residents of the opportunity to compete for jobs and investment, while also causing the area to relinquish substantial long-term economic investment, high-wage jobs and critical tax revenue to neighboring areas or other states," said Khara Boender, DCC's director of state policy.
Local organizers pushing for a ban on datacenters say the city council has been receptive to their concerns – and that the ballot measure was elected officials' idea. "They took [our concerns] seriously, which not a lot of city councils do," said Amy J Wong, co-founder of San Gabriel Valley Progressive Action – a key partner of the group No Data Center in Monterey Park. Wong has been involved in grassroots actions tied to the moratorium that city council already passed and Tuesday's ballot measure. She said grassroots groups put helpful pressure on the council to ban datacenters: "They recognized so many residents are angry and, if they move forward with the datacenter, they could possibly be voted out."
She said organizers had to be quick in advance of the vote. Typically, she said, ballot measure campaigns have at least a few months to get started, but they only really had two months. In that time, they printed 10,000 flyers and sent out mailers in English, Chinese and Spanish. While many residents Wong spoke to were already skeptical of datacenters – and suggested a ban was a "no-brainer" – there was confusion about how to vote for their desired outcome. Some didn't know whether a vote of "yes"' or '"no"' would affirm a ban on datacenters, she said: "We had to educate some people who thought supporting a ban means you're supposed to vote 'no'."
"I'm feeling fairly confident," she said, a few hours before polls closed.
Sanchez, the city council member, used to be the city's mayor and is now a high school civics teacher. The kids are paying attention, he noted. His students are always grilling him about datacenters. So is his nine-year-old daughter. He feels he's representing them, too, even if they can't vote yet. "They give me an earful," he said.
https://www.righto.com/2026/06/intel-8087-adder-reverse-engineered.html
In 1980, Intel released the Intel 8087 floating-point coprocessor, a chip that could make math up to 100 times faster. As well as arithmetic and square roots, the 8087 computed transcendental functions including tangent, exponentiation, and logarithms. But it all depended on a 69-bit adder: "The arithmetic heart of the floating-point execution unit is centered about a nanomachine comprised of the adder and its related registers, shifters and control circuitry," as the patent describes it. In this article, I explain the circuitry of this adder.
Physicists refute famous 2025 study claiming daylight saving time poses severe health risks:
In 2025, Lara Weed and Jamie M. Zeitzer of Stanford University published an article linking the practice of seasonal time changes (Daylight Saving Time) to negative health outcomes, ranging from acute symptoms (heart attacks and strokes) to chronic conditions (obesity). Now, Professors José María Martín-Olalla (University of Seville) and Jorge Mira Pérez (University of Santiago de Compostela), after analyzing the methodology applied in that study, have concluded that "what the world read as scientific evidence against time change has turned out to be a mathematical illusion."
The same journal that disseminated the controversial article, Proceedings of the National Academy of Sciences, has just published a letter signed by Martín-Olalla and Mira Pérez, demonstrating that the study's conclusions are not supported by actual evidence.
The original article by Weed and Zeitzer gained significant global traction in the fall of 2025 due to its striking conclusions and its use of the PLACES database (Population Level Analysis and Community Estimates). This database, managed by the U.S. Centers for Disease Control and Prevention (CDC), contains information on the prevalence of 29 syndromes and diseases at the local level. The PLACES data were contrasted against a circadian model developed by the authors.
The work of Professors Martín-Olalla and Mira Pérez reports a grave error in the study's methodological foundations. The original model computes the difference between the rhythm of the biological clock—the circadian rhythm, determined by the time at which body temperature is at its minimum—and the rhythm of Earth's rotation. According to the original authors, this difference represents the "regulatory circadian shifting necessary to stay synchronized with the outer world."
Global health effects were inferred from the annual sum of these daily readjustments. However, when performing this calculation, the authors consistently accumulated the magnitude of the readjustment, regardless of whether it was positive or negative.
"The use of absolute readjustments instead of real readjustments is the critical error," note Martín-Olalla and Mira. They show that this methodology merely captures the "noise" of the model and, therefore, cannot predict net health effects.
Professor Mira explains, "What the authors did makes little sense; it is as if, while driving, we recorded every small adjustment made by moving the steering wheel back and forth to stay in the lane, but then added them all up in the same direction to report a large value instead of allowing them to compensate for each other. By their logic, maintaining a straight course with small left-and-right adjustments (what actually happens) would be the same as a car drifting further and further in one direction until it ends up facing the wrong way. This alone refutes the study's conclusions."
[...] "The fact is that the 'absolute cumulative readjustment' they report is approximately 20 hours per year, which is nothing more than an average of about 3 minutes per day, sometimes in one direction and sometimes in the other. Given the information provided in the study, it is difficult to understand how such a weak value (a mere 0.3%) can be epidemiologically linked to the prevalence of disease."
"We see no prior hypothesis or causal link that justifies the analysis performed in the original study. This invalidates the methodology and, consequently, the reported findings: the authors cannot conclude that eliminating the time change would lead to a decrease in the prevalence of obesity or acute medical events," they affirm.
Journal Reference: José María Martín-Olalla et al, The sum of absolute circadian shifts: Questioning the metric linking daylight saving time policy to stroke and obesity, Proceedings of the National Academy of Sciences (2026). DOI: 10.1073/pnas.2532075123
There's an incredible amount of surveillance across much of the USA. Many governments and some businesses are paying tens of thousands of dollars each year for license plate readers. Those records are sent to a centralized database and often shared nationally with police. Flock is the most well known camera vendor, but there are plenty of others like Motorola Solutions. It makes headlines when a city council decides they no longer want Flock cameras, but the vast majority of local governments seem to want and defend the surveillance. They all insist the abuse happens elsewhere, but it would never be tolerated in their own police force. Yeah, right.
We also install our own mass surveillance like Ring and Nest video doorbells and even indoor cameras. I walked a couple of miles through a suburban residential area a few days ago and wouldn't be surprised if I was recorded by over 100 doorbell cameras. One even had an automated female voice tell me that I was being recorded because I was on the sidewalk in front of their house. I was initially taken aback by that creepy voice, but now I think it might be less insidious than the other cameras that didn't announce their presence. Although doorbell cameras are easy to spot, I wonder how many other cameras were lurking in the shadows and also recording me on the sidewalk. And how many of the cameras used facial recognition that could be used to track me?
One of the most common defenses of the cameras is that if you're not doing anything wrong, you've nothing to hide. The irony is the same people parroting this fallacious BS often try very hard to hide their surveillance. What's good for the geese ought to be good for the Flock of ganders. If you're not doing anything nefarious with your cameras, then why do feel the need to hide them and be secretive about how you're using them?
Let's talk about how to expose the surveillance. I see three obvious ways: 1) document misuse of Flock camera searches, 2) create a reliable and searchable database of Flock and similar cameras, and 3) make it easier for people to know when they're being recorded by other cameras like Ring and Nest doorbells.
Flock Searches
Sites like haveibeenflocked.com aggregate data from public record requests for Flock searches by cops. Although the database is incomplete and should be used with caution, it's very useful. You can easily download a JSON file of Flock searches and analyze them. The catch is that governments often redact data in public record requests, do so inconsistently, and this often leads to there being multiple records in the database for the same search.
Because other fields are redacted inconsistently, I've generally treated the combination of the searching agency and the timestamp of the search as a de facto primary key. If that's identical between two records, then they should be merged into one one. I suspect it's extremely rare for any police agency to perform two Flock searches at exactly the same time down to the second, so I believe the chance of me missing searches because of this is negligible. This is in addition to the aggregation already done by haveibeenflocked.com. If there are better ideas for this, I'd like to hear them.
If you're going to confront a city council about abuse, you probably want it to be obvious and incontrovertible. Some police departments routinely use vague reasons for a search like "investigation" or "invest", but they don't say what type of investigation. It could be a murder investigation, but they could just as easily be investigating No Kings protesters. There are also many instances of Flock cameras are used to investigate low-level offenses.
Some police agencies also have a high usage of one or two characters as the reason for searches. If a cop enters "a" as the reason for a search, that seems to be an abuse. But I've also seen where the same cop conducts numerous searches that have the same license plate hash, and they'll enter something like "stolen" as the reason for some of the searches and "a" as the reason for other nearly identical searches. Now, "stolen" is also vague because you don't know if it's about stolen vehicle, other stolen property, or even stolen money. But a cop might say that it's too tedious to even type "stolen" for each search, so they get lazy and just type a single letter. This is an abuse, but is it indisputable enough to change the minds in a city council that ardently defends the surveillance?
I'm looking for ideas about how to better analyze the data and identify abuses that are so blatant that even the most stubborn city council can't deny that there's a problem.
Detecting the Flock
Flock cameras used to be detectable because they advertised themselves over Wi-Fi and BLE with names like "Flock-1234567890" or "Penguin-1234567890", but they started removing the "Flock-" and "Penguin-" prefixes. However, the data fragments being advertised still gave away that it was a Flock camera. Specifically, the 0xFF fragment began with 0xC809, and 09C8 is the manufacturer ID for Xuntong. Because this is almost exclusively associated with Flock, that's pretty much a giveaway. In my experience, this is detectable as a pedestrian at a range of 20-30 meters. However, within the past couple of weeks, only one of the four Flock cameras I've walked up to actually announces itself over BLE. Flock seems to be turning off the BLE advertisements to better conceal their cameras.
I believe BLE was used for maintenance, but this is now being done with Wi-Fi signals. My understanding is that Flock cameras now transmit probe requests that can still reveal their presence, and this is functionally for the same purpose. It's easy to put a card into promiscuous mode and listen for probe requests. However, lots of devices send probe requests. How someone can determine that the requests came from a Flock camera instead of someone's phone or computer searching for Wi-Fi networks? There are vendor-specific payloads and lots of other data in the frame headers, so might any of this be useful to show that it's a Flock camera doing the probing? For now, detection seems to be mostly based on the orginazionally unique identifier of the Wi-Fi MAC address, which is the first three octets of the address, that is present in the Wi-Fi probe requests.
Although Flock cameras seem to get the most attention, there are other vendors like Motorola Solutions, and they're no less a threat to liberty and privacy. Are there any similar ways to detect their cameras using BLE or Wi-Fi signals? This matters, especially because maps on sites like deflock rely on crowdsourced data that is incomplete and can be poisoned by bad actors.
Detecting Ring and Nest Surveillance
If a building owner is going to record me walking on a public sidewalk, I'd like to be able to detect their surveillance and know I'm being recorded. If they're going to watch me, it's only fair that I watch their surveillance.
There won't be BLE advertisements, but there are side channel vulnerabilities that could alert a person they're being recorded. If motion is detected, this triggers a burst of packets [.PDF] that can be detected by analyzing the traffic. This should cease once the person moves beyond the camera's field of view for a few seconds. If you walk past the camera a few times and find that one spot consistently triggers a bunch of packets, it's probably the edge of the camera's field of view.
If you're just out for a walk and don't like being watched, it seems like the sudden burst of packets from a MAC address that's used in Amazon or Google devices might be a good indicator that you're being recorded. But other devices might have similar MAC addresses such as a Fire TV Stick or a Kindle Fire tablet. Are there other ways to distinguish that the particular device is likely to be a camera? Again, is there anything in the frame headers that might be useful here?
As for mapping out the edges of the surveillance, this exposes why most of these consumer-grade cameras are security theater. I obviously disagree with trespassing to map out someone's security cameras on their own privacy, especially if you're doing this with the goal of committing another crime besides trespassing. But a skilled criminal could sit in a car and watch you doing yard work or kids playing on your lawn, mapping out what locations trigger your cameras. Wi-Fi traffic patterns could even allow an intruder to infer if you're at home or not so they know when to break in. Unlike Wi-Fi jamming and deauth attacks, this is completely passive. It could be mitigated by sending a consistent amount of traffic regardless of whether the camera is recording or not, but cheap consumer-grade cameras don't do this, and it's usually to conserve battery life. It's security theater, invading the privacy of law-abiding pedestrians and likely the camera system's owner while remaining highly vulnerable to actual intruders. It provides a false sense of security and harms innocent pedestrians while being highly vulnerable to side channel attacks and perhaps even increasing the risk of crime.
Disclaimer: I strongly oppose implementing any of the ideas I've described to assist in criminal activity. Don't do this. But I also believe that government use of mass surveillance or things like facial recognition in consumer-grade cameras is illegal.
The BBC through its Discover Wildlife magazine reports on an amazing discovery:
A new study published in the journal Current Biology recently found that octopuses can learn how to use mirrors to locate food hidden from view in an impressive feat of spatial thinking never before observed in invertebrates.
Researchers from Dartmouth College conducted an experiment involving three California two-spot octopuses (Octopus bimaculoides) – the goal was to find out whether the animals could be trained in using a mirror to locate an out-of-sight food source.
"We don't enter the world knowing how to use a mirror but learn how to use a mirror," said cognitive neuroscientist and professor at Dartmouth, Peter Tse. "Octopuses can also learn how to use a mirror to infer where things are in the world."
During the first mirror-use training trial, all the octopuses moved toward the reflection of prey first – it took around 10-12 trials per animal to learn to approach the actual crab instead of its reflection.
Then, once the octopuses were familiar with the mirror, the testing began. Steps were taken to account for the octopuses' ability to smell and taste through touch – instead of real prey, virtual images of crabs were used.
Each octopus was placed inside a box open at the front and top, with a mirror positioned directly in front of them. The virtual crab was positioned behind the octopus, visible only through the mirror. To receive a reward (an actual live crab), the octopus had to recognize where the crab was located and move towards it.
The animals successfully chose the right location in 73 per cent of the trial, even though the learning and testing tasks were quite different. During training, the octopuses only needed to make a 90° turn near the mirror. During testing, they had to leave the starting area, make a 180° turn, and either move to the back of the tank or climb over the wall of the start chamber.
Despite these changes, all three octopuses succeeded on their very first test. This suggests they understood the spatial relationship shown in the mirror, rather than just memorizing visual cues linked to a reward.
"Octopuses are among the most evolutionary distant animals from humans, as our last common ancestor was a worm that lived 350 to 500 million years ago," said Mary Kieseler, one of the researchers. "Given that such a remote organism has independently evolved the means to use a mirror as a tool to process spatial cognition suggests that the underlying cognitive processes might be subject to convergent evolution, where different species evolve similar neural solutions to the same challenge."
Using mirrors to locate otherwise not visible objects is a form of mediated perception and is even seen by some as a precursor to self-recognition.
"Hunters are very effective when they have a mental map of their territory, so that they know where they are in relation to their environments," added Tse. "Our work suggests that octopuses might also have internal maps, an internal representation of space."
More research is needed to determine whether they learned through simple associations or by using an internal map of space.