While scientists often shy away from political discourse, some are saying the Trump administration’s assault on science is behind their departure. “I used to live in the country that I thought was the most enthusiastic about the prospects for science improving the human condition, of any country in the world,” said Phillip Zamore, the chair of RNA Therapeutics Institute at the University of Massachusetts. “And I woke up one day and that wasn’t true anymore.” He has been recruited to McGill University in Montreal, which has also hired five other researchers, and will join the medical faculty. “If scientists don’t stand up for truth, no one will,” Dr. Zamore said.

The Canada-bound brain drain from U.S. institutions began last year as the Trump administration put forward policies that targeted foreign students, academic freedom and funding for equity-related programs. Kevin Hall, a nutrition scientist who left the U.S. National Institutes of Health last year, accusing federal officials of censoring his research on ultraprocessed foods, has been hired at the University of Ottawa. “While certain countries are cutting research and turning their back on academic freedom, we’re doubling down on science,” Melanie Joly, Canada’s industry minister, told reporters at the announcement, in Vancouver, of the new university hiring. She billed it as the world’s “largest talent attraction” project. The European Union has made a similar push. “Years from now, we will look back at today’s announcement, and we will be able to seize the lasting impact of our choices,” Ms. Joly said.

Unpredictable decisions about funding prompted Seth Guikema, a professor in civil and environmental engineering, who has specialized in natural hazards modeling at the University of Michigan, to look elsewhere. His work focuses on how climate hazards inequitably affect communities, and that work has become harder to fund, he said. “Every country sets its priorities in terms of what is going to get funded, and I think Canada has done a very good job of supporting research in areas that really matter to society,” said Dr. Guikema, who will start at Western University in London, Ontario in January.

From “rizz” to "meat proxy,” words and phrases have fallen in and out of favor for centuries. Culture, politics and technological development have long influenced these trends, and now, new research shows that ChatGPT is beginning to influence how humans communicate. The findings from a team at the Pew Research Center show how, in a short time since OpenAI released ChatGPT in November 2022 and other chatbots followed, the use of certain words and phrases has spiked on the web. The researchers, led by data scientist Samuel Bestvater, studied nearly half a million English language webpage texts in snapshots over the past five years. Not only has AI-written text become more common, but it could also be influencing how people write, such as trying to avoid using the “tells” that have become associated with AI-generated text.

Bestvater and his team detected double the number of em dashes, double the frequency of particular words — such as “delve,” “testament” and “interplay” — and nearly triple the use of a phrasing known as negative parallelisms (“it’s not X, it’s Y”), as well as a 63% increase in Oxford commas. But while AI labs continually try to tweak their models to generate more humanlike text, the people they’re mimicking aren’t staying the same.

The company explains that the mobile industry is now facing “significant hardware supply constraints that are altering device memory availability,” which can then, in turn, affect the consumer’s experience with their devices. To address this, Google is now establishing new performance thresholds across several areas, like dynamic memory usage and bitmap usage. In addition, Google is adding code optimization requirements designed to prevent things like app slowdowns and crashes related to performance.

Persistent mode appears in Codex’s “reasoning effort” menu, in which users can select the level of computing power, tokens, and time they want to allow for an AI model to “think” before answering a prompt. It seems to be one of OpenAI’s most computationally intensive settings. When users have selected Persistent mode, OpenAI’s code base reads that Codex will “continue working until put to sleep.” That’s a stark contrast to currently available modes, which will stop working on a task after a few minutes or hours, even if it’s not complete.

In another file in the code base, OpenAI describes a feature within Persistent mode called “proactivity.” This appears to be a type of system prompt for agents in Persistent mode, which are told that their work is not done when they finish answering a user’s request. Instead, the agent is instructed to proactively create follow-up tasks for itself. The agent is capable of working on those tasks across sessions and using past user interactions and “knowledge of the user” to decide what to work on. It also has a tool to message the user without being asked but is told to send these sparingly.

The instructions also set limits for the agent, according to the file. The agent is told that Persistent mode does not expand what it is allowed to do and that altering anything outside the user’s own system requires the user’s approval first — seemingly intended to limit how dangerous a persistent AI agent could be. The file sits in the shared core of Codex rather than in the code specific to the terminal, seeming to suggest the proactivity feature is intended for more than the command line tool.

Ring says TAKE uses unique, rotating encryption keys for your footage, stored in a secure enclave and accessible only under strict conditions — based on the features you enable on your account. Currently, footage captured by Ring cameras is encrypted in transit to the cloud and at rest, and then decrypted for Ring to process for those smart features. With TAKE, the encryption keys change for every five minutes of footage. Ring stores copies of those keys to decrypt the footage, but throws away each copy within 24 hours, “leaving you with the keys and full control of your videos,” according to Ring.

TAKE was developed using Messaging Layer Security, an open standard from the Internet Engineering Task Force, according to Ring. The company says it is “inspired by the privacy principles of E2EE (end-to-end encryption),” which Ring offers on some of its cameras. However, the two systems work differently. With E2EE, Ring never has the keys and can’t process your video for cloud-based features. Both options are available on newer cameras that encrypt on-device, and you can switch between the two. Older cameras encrypt at cloud ingress and only support TAKE.

According to a white paper the company published today, Ring’s copy of those keys is managed inside an AWS Nitro Enclave, to which Ring’s access is restricted by “access controls, cryptography, and hardware isolation.” The company claims there is no persistent storage and no way for a Ring employee to access it. The stored keys can only be unlocked by the enclave through cryptographic attestation that proves it’s running the exact software image Ring approved. The enclave releases a temporary key when an enabled service requests it.

Documentation files on more than 100 websites are referencing potentially dangerous executable content that gets installed automatically when visited by many AI agents [including Claude, OpenAI’s Codex, and Nous Research’s Hermes]. A few dozen companies, some of them Fortune 500s, are among those that executed proof-of-concept code. At least one misconfigured site is directing visitors, human or AI, to live malware.

The potentially dangerous content is in llms.txt and llms-full.txt files, an emerging convention websites employ to provide machine-readable summaries of the site’s content and its high-level structure. These files are the AI equivalent of the robots.txt standard that instructs search engines how to index the site’s content. Google Lighthouse, a tool for helping web developers, has more here. Correctly configured llms.txt and llms-full.txt files for Cloudflare are here and here.

Foreign-produced “bulk power” equipment is now effectively banned, and the list of what constitutes such equipment is essentially everything used to make up the grid… much of which we are heavily dependent on foreign sources to supply.

Under the order, it will be up to Energy Secretary Chris Wright, in coordination with other officials, to determine whether a piece of equipment poses an issue. The order could impact a wide range of equipment, including substations, transformers, batteries used for energy storage, generators, turbines, software and more. It does not lay out specific threats or single out any country by name.

[…] Under the last Trump administration, the president put a similar order in place. The new order comes amid several reported cyberattacks on U.S. water systems, which officials suspect have links to Iran, according to The New York Times.

In an update posted on the Playdate help site this week, Panic noted that it has finally “begun to receive refunds of the tariffs we paid in the last year” and had consequently “refunded all tariffs charged to customers.”

In the initial version of that tariff note, Panic explained that it couldn’t afford to simply “absorb” the 19 percent tariffs it was being charged to import Playdate hardware made overseas because “our margins on Playdate are low.” As such, while the tax was in effect, it was passed along to customers as an explicit subtotal line item at the bottom of all Playdate orders. That’s in contrast to companies like Nintendo, which vaguely cited “market conditions” and tariff “uncertainty” in raising the asking price of legacy hardware and some Switch 2 accessories last year.

Speaking to Game Developer, Panic co-founder Cabel Sasser said filing paperwork to claw back these taxes and processing tariff refunds for customers took a fair bit of backend work. Still, he said returning that money to Playdate purchasers in the end was a no-brainer. “It’s just not our money to keep, and it felt really good to give it back,” Sasser said. “That’s an easy way to know you made the right decision.” “It just felt like the right thing to do,” Panic wrote in a refund email message shared on Reddit.

If completed, the acquisition would put one of the most widely used platforms for sharing and working with open-source AI models under Nvidia’s ownership, expanding the chipmaker’s reach further into the software and model ecosystem. Siddy Jobe, a fund manager at Eonopolis Exponential Technologies funds, said it made sense for Nvidia to target a company like Hugging Face, as Nvidia has made it clear that it is not looking to discriminate between closed and open-source models.

“I think Nvidia is very much a community, a platform-based company, and in that respect, I think Hugging Face fits perfectly within that. There is this five-layer cake from Nvidia, and foundational models are one of them,” Jobe told CNBC’s Squawk Box Europe on Thursday. “It is clear that Nvidia wants to be integrated in the entire stack vertically, going from energy to foundational models and also to applications,” he added.

Operation Bluebird, the Virginia-based startup trying to revive the allegedly abandoned “Twitter” name and logo, announced Monday that it has launched its new social media network: Twitter.now. “We are a small company, we have investors, and we have a product,” Stephen Coates, one of Operation Bluebird’s cofounders, told Ars. “And we have waited months and months to launch, and we are not going to wait anymore.”

[…] Twitter.now, still in its nascent stage, only has hundreds of users for the time being. The social media network looks and feels much like the Twitter of old and many of its offshoots — it has replies and retweets. A new and notable feature is the automated fact-checking tool, a Gemini-based “veracity engine for real-time analysis” (“Vera” for short), which runs on every tweet. Coates has been testing Vera in recent days by posting obviously false messages, like “George Washington was our second president.”

“Our first goal is to see if we can truly bring back a town square that’s safer and less harmful,” he said. “We say freedom of speech and not freedom of reach. We want people to say what they want, but we also want to create a platform that’s not financially locked into that viral content that’s harmful or inaccurate.”

In January, Meta CEO Mark Zuckerberg and his top lieutenants gathered for their annual leadership retreat at his Hawaii compound. There they hatched a radical plan to reimagine work at the social-media giant in the age of artificial intelligence. Code-named Project OT — short for Organization Transformation — the plan envisioned an “AI native” future for the owner of Facebook and Instagram. AI would take over much of the daily work performed by thousands of human employees. Virtual workers would be overseen inside Meta by smaller, “talent-dense” cadres of human staffers, according to one internal planning document reviewed by Reuters and three people familiar with the project.

In scenario-planning exercises, two of these people said, executives explored slashing the size of many teams across Meta by as much as 60%. Some employees would be offered roles in new units, while others would be laid off as part of a culling that one human-resources executive projected would be as big as or bigger than the company’s cuts of around 25% three years ago, according to another internal document. The restructuring would be carried out in two “waves,” beginning with a first purge in May and followed by another shake-up in November, internal planning documents seen by Reuters showed. Layoffs would be supplemented with the closing of open positions and pushing people out who Meta believed were poor performers. These and other details of the plan, including the scale of the restructuring, haven’t been previously reported. AI would take over much of the daily work performed by thousands of human employees. Virtual workers would be overseen inside Meta by smaller, “talent-dense” cadres of human staffers.

But on the night of May 19, just hours before the first layoff wave, Zuckerberg blinked. Meta laid off 10% of its employees the next day, but it called off planning for the November cuts, according to one internal document reviewed by Reuters. By then, Meta employees were in open revolt, convinced that the company’s AI transformation initiatives were partly aimed at replacing them. Internal data was also suggesting that autonomous AI “agent” technology at the heart of the strategy was failing to deliver hoped-for productivity gains. Some investors were questioning what Meta had to show for its gargantuan spending on AI. This article reveals for the first time the rapid pace of the cuts Meta was considering, the thinking behind the plans and how they quickly unraveled. Based on scores of internal documents, posts and recordings reviewed by Reuters, as well as conversations with more than 20 people with knowledge of Meta’s inner workings, the reporting shows how the social-media giant attempted to position itself at the forefront of an AI-driven workplace overhaul, only to stumble in the execution.

Suspected Iranian attackers targeted water and wastewater facilities across at least a dozen states in July, including internet-exposed PLCs. While neither federal nor state officials have identified all 12, we know that the cyberattacks occurred at mostly small, rural utilities in Minnesota, Michigan, Georgia, South Dakota, and New Jersey. “This is very serious. What stands out isn’t any single incident. It’s the scale,” Matt Hartman, chief strategy officer at the Merlin Group and CISA’s former acting head of cyber, told The Register.

“More than 100 water systems with internet-exposed assets were hit in a single month, which points to a systemic vulnerability across the sector, not a run of isolated, unlucky targets,” Hartman said. “Much of this infrastructure runs on operational technology that was built for closed, physical environments. It was never designed with the assumption that it would be reachable from the open internet.”

John Gallagher, VP at Viakoo, an OT and IoT cybersecurity provider, told us that while 100 systems represent a small fraction - only about 0.5 percent - of water utilities in the US, the “real threat is that these are test runs for a larger-scale attack.” While the 100-plus water incidents occurred in July, just last week five US federal agencies warned that attackers are using AI-generated exploitation scripts to break into internet-exposed Siemens S7 Series PLCs at water, manufacturing, energy, and other critical facilities.

“This appears to be a continuation of the same suite of activity we suspect is affiliated with Iran targeting PLCs,” Halcyon Ransomware Research Center SVP Cynthia Kaiser told The Register a week ago. “Iran-affiliated actors and adversaries are actively targeting a wide swath of operational technology because these PLCs underpin essential health, safety, and critical infrastructure across society,” Kaiser, a former FBI cyber division deputy assistant director, added.

Sophie Lainault, a 59 year-old former stewardess on Air France, sought to have her cancer recognized as an occupational disease, brought on by conditions at work. This has now been confirmed in a landmark court ruling in the southwestern town of Bayonne, which said that cosmic radiation was one of three carcinogenic hazards arising from her profession. […] As stewardess and later purser on Air France airliners, Lainault clocked up 12,600 flight hours between 1989 and 2019. More than half of these were at night. Many long-distance high-altitude flights from Paris would have taken her near the North Pole, where exposure to radiation from space — strictly speaking particles from the sun and other stars — is the most intense.

A study this month at the Harvard Medical School in the US found that flight attendants and pilots had the highest level of radiation-related cancer deaths among more than 500 different professions. In all, about 6.9% of deaths among flight attendants and 6.7% of deaths among pilots were from radiation-related cancers, according to the analysis. These proportions were higher than for other professions including nuclear technologists, who are routinely exposed to radiation from non-cosmic sources yet placed 12th on the list, the authors said.

Microsoft co-founder Bill Gates argued on Wednesday that artificial intelligence needs significant limits or else the harm to humans will outweigh any potential good. “AI will either be the greatest equalizer ever invented, or the worst source of injustice,” he said in a 6,000-word essay, entitled “The turbulent AI era is here. The choices we make now are critical.” […] “Even under the best circumstances, the transition to this new AI era will be one of the most turbulent times in human history,” he said, adding that “I don’t see evidence that leaders, experts, and communities are confronting the challenges adequately. There is no plan to ease the entry into the AI era.” AI can provide great benefits in field like agriculture and medicine, he argued, such as breakthroughs in preventing and treating diseases. But he also noted that the transition carries big risks, like widespread unemployment, harming the educational and social development of children, or making it easier for criminals and bad actors — or AI itself — to cause deliberate harm.

“As the models become more powerful, they could begin to act against our interests and we could lose control,” he warned. These significant risks must be controlled quickly, Gates said. “If someone had a credible plan for slowing down AI advances globally, I would likely support it,” he wrote. “However, I don’t think that’s going to happen. The geopolitical and economic incentives are pushing too hard to go full speed ahead.” In an interview with CNN’s Anderson Cooper that will air on Wednesday evening, Gates said AI models have gotten dramatically more powerful at a rate faster than he expected. “They’re now capable of causing cyberattack risk, bioterrorism risk, psychosocial risk,” he said. “I have to say I’m kind of shocked that the exact criteria that we review these models with, and the actions we take to minimize the harms, are really completely missing.”

In his essay, Gates proposed taxing AI or robots the way you would pay a human employee’s payroll tax in order to slow the shift away from using human labor. He also wants to set aside some work to be done by humans only. “My message to leaders is: You have a chance to act now, before unemployment rises sharply, communities are hurting, and public trust has eroded,” he said. “You can make sure AI benefits everyone. And you can work with other governments to meet this national and global challenge.”

Many of the details in OpenAI’s report were previously made public in a Black Hat presentation on August 6, but OpenAI’s official report gives a more thorough accounting of the incident, including more detail on the testing that initiated it. The report also gives critical new detail into how OpenAI aims to prevent future incidents, including chain-of-thought monitoring and a more advanced system for halting rogue agents.” METR and Redwood Research also conducted third-party assessments of the models’ behavior during the incident; both groups are planning to publish their own reports on the incident on it.

In broad strokes, the report describes how an OpenAI model was presented with an unsolvable problem in testing and proceeded to chain together previously undiscovered exploits in order to bypass security measures and complete its task. The model initially compromised the Artifactory package management tool in order to gain access to the internet, then compromised various systems across OpenAI, Hugging Face, and other vendors.

The report gives critical new details about the models that carried out the breach. The primary model was from the same family as OpenAI’s forthcoming Astra model, although the report emphasizes that it was “a distinct model with different post-training, where much of a model’s behavior is shaped.” Because OpenAI was testing the model’s capabilities, it was also unrestrained by the normal classifiers meant to prevent models from compromising digital infrastructure. “OpenAI estimates maximal cyber capabilities by running this evaluation without the production classifiers intended to prevent models from pursuing high-risk cyber activity,” the report explains. “These evaluations are important so that OpenAI can measure models’ underlying capabilities and design appropriate safeguards.”