We’ve seen various Waymo crash data before, with Waymo claiming crash reductions. That’s all well and good when the company says it, but we’ve also seen independent data confirming similar (though lower) crash reduction numbers…

Waymo has enough miles that it’s ready to start quoting how many injuries it has prevented, and the number is pretty high. Its newest crash data states that it had operated a total of 271 million driverless miles through June of this year, which is 50 million more miles added in the 3 months since its end-of-March update. Over those miles, Waymo says there was an 82% reduction in crashes that caused injury, and a 95% reduction in crashes that cause “serious injury or worse” [compared to human drivers].

The decision to halt development came just hours after the company disclosed Friday that it was reviewing several incidents from the summer in which OpenAI agents searching federal government websites acted in unexpected ways beyond what was asked of them while gathering and distributing information… OpenAI said in a statement that it will resume training “only when we are confident that we have additional safeguards” in place, adding that it expects it will have to “hit pause” again as AI develops and other issues emerge… It is the second time in three months that OpenAI has halted development of its models. The first came in July after disclosure of a cyberattack targeting AI startup Hugging Face, a now notorious incident that raised fears the industry was losing control.

As of mid-September, one person briefed on the matter estimated that OpenAI had found roughly two dozen incidents of its agents acting in undesirable ways. But the number has continued rising as OpenAI teams sift through internal logs of the agents’ activities and find previously unknown cases, the two people close to the company said… OpenAI has acknowledged a general need for more transparency around rogue AI behavior… Even so, two people familiar with OpenAI’s investigation into its agents’ activity described it as locked down and shaped by company lawyers.

The process has been unusually compartmentalized for a company that some former employees say was more open about these issues in the past, the people said. Roughly 100 people were in some way involved in the process to understand the Hugging Face hack, three people briefed on the matter said. During that process, evidence of other incidents surfaced. Reuters has previously reported that OpenAI investigators looking into the Hugging Face breach were discouraged by the company’s lawyers from expanding the scope of the investigation to include other incidents. OpenAI said its lawyers did not discourage deeper investigation.

Many incidents have been uncovered by outside researchers rather than OpenAI directly. In several episodes, the agents took problematic actions that went unnoticed by the company for months.

The sheer number of incidents, which occurred in recent months in internal testing and the real world, indicates that the problem is orders of magnitude more complex than what is publicly known. The findings, which are surfacing as part of internal work to assess models and in investigations at both companies into model behavior, raise questions about whether either company — or any top model-maker — is currently capable of establishing complete control over their technology. The episodes include bypassing guardrails, creating message boards, escaping sandboxes, website hijacking, self-prompting or seeking to bypass monitors, sources said. They occurred in internal testing and in the real world, and many have yet to become public as security researchers continue to investigate, sources said…

Some at OpenAI see Hugging Face as a one-off, with disclosures about future incidents likely to be less severe due to improved controls and the unusual nature of the testing they conducted, which involved an unreleased model, sources told Axios. AI security researchers agree that there are simple fixes that will help AI companies avoid aspects of what made the Hugging Face episode appear so dangerous to outsiders.

Other AI executives and safety researchers, however, cautioned that they have limited confidence that AI companies will be able to prevent all problematic model behavior… It’s not about how damaging each individual instance was, Connor Leahy, AI researcher and executive director at ControlAI told Axios. The “crazy thing,” he said, is that these instances involve “autonomous systems doing things they were told not to do,” potentially including crimes.

Researchers at the University of Groningen in the Netherlands found that tin-based perovskite solar cells can slow heat loss from high-energy “hot electrons…”

When sunlight strikes a panel, photons jump-start electrons into action. The most energetic photons create super-charged hot electrons… [but] in fractions of a trillionth of a second, these high-energy particles rapidly cool, dumping their bonus energy as waste heat before ever leaving the solar cell… In collaboration with Maria Antonietta Loi, professor of Photophysics and Optoelectronics, the team created an experimental setup. Using a specialized solar cell material called tin-based perovskite, Loi’s lab performed a feat many thought impossible: she slowed the heat loss down by a factor of 1,000.

Suddenly, the extra energy lingered for nanoseconds instead of vanishing in picoseconds… To solve the puzzle, Koster and PhD student Tim Faber built digital simulations to peel back the quantum layers. And discovered a surprising double-action mechanism at work… The simulations matched the exact nanosecond delay observed in the lab… These specialized materials could be used to build a new generation of super-efficient solar cells.

Tin-based metal halide perovskites are non-toxic, eco-friendly crystalline materials for high-performance solar energy conversion… The material possesses an unusually low electron mass. As a result, electric charges move quickly and retain extra thermal energy for extended periods. This combination of broad light absorption, efficient charge movement, and prolonged energy retention makes these materials prime candidates for next-generation solar panels.

On artificial intelligence, the two sides agreed to hold a dialogue on the technology’s risks and benefits, with the next round of discussions set for November, and to set up a communication channel for AI-related incidents, the Chinese Foreign Ministry and the White House said.

The White House said that the leaders had agreed to use the term "super intelligence" in place of “artificial intelligence.” In a separate statement, the Chinese ministry said that Beijing valued Washington’s use of the new term. As AI technology continues to advance, the two sides should step up exchanges and work toward consensus in line with new developments, it said.

The right thing to do on AI, [China’s leader] Xi said during talks with Trump, is to “draw on each other’s strengths, not guard against each other” — a reference to Beijing’s concern about US containment, from existing tech export controls to potential AI restrictions. “The two sides can continue their dialogue on AI, exchange views on its risks and benefits, and jointly prevent the misuse and abuse of AI,” he added. But the summit has yielded little progress on AI beyond a formal dialogue and a bilateral communication channel, proposals discussed before the two leaders’ summit — underscoring the entrenched mutual mistrust amid contrasting visions on AI… Because of low levels of trust, cooperation between the two superpowers remains limited, said George Chen, chair of digital practice at The Asia Group consultancy. “Beijing continues to believe Washington seeks to contain China’s rise in AI and other emerging technologies, a perception that will shape the pace and scope of future engagement for the two countries on AI,” he said.

In July, Chinese leader Xi Jinping launched the World Artificial Intelligence Cooperation Organization — a rival grouping to the Pax Silica alliance that Trump formed last year to reduce reliance on China for AI supply chains. While over two dozen countries and the European Union signed up to Trump’s Pax Silica, Xi has recruited 29 countries, including Russia, Indonesia and Pakistan, to his alternative vision of open models, which allow users to freely download, customize and run without paying hefty fees to American firms like Anthropic and OpenAI. For developers in the Global South, an inexpensive Chinese model from DeepSeek or Moonshot may be more useful than a slightly more capable system requiring an expensive subscription and access to a foreign cloud provider, said Eric Olander, editor in chief of The China-Global South Project, a research agency....

China’s embrace of open systems has not always been a top-down strategy by Beijing. Restrictions on access to the most advanced chips because of US export controls, coupled with smaller capital markets, have pushed Chinese developers toward open models as a way to compete with leading US proprietary systems. That shift has proved effective. In a year, Chinese models’ global usage skyrocketed from less than 15% to over 54% last week, led by DeepSeek, according to AI leaderboard data by OpenRouter, a marketplace for models. Even American firms, from Airbnb and DoorDash to Shopify, have embraced Chinese models, tapping into the advantages of open systems, including lower costs and greater flexibility for customization.

Two people unknown to any KDE contributors appeared and began fighting with one another about the broader topic of the morality of AI, not the proposed guidelines… Someone else outside of KDE set up kdeforpeople.com in an attempt to… pressure KDE into banning LLMs. A bunch of people signed onto it, almost none of whom are known KDE contributors. The topic was picked up on social media and the press with… varying levels of accuracy. The draft proposal was removed and the whole topic hidden… Yep, that’s where we’re at in the state of online discourse around AI…

The “lovable, sovereign, AI-native KDE” idea was presented by two people important to KDE in decades past, but who had not made any contributions recently besides this Akademy talk. Their idea does not reflect the overall direction of KDE or Plasma, and I don’t think it ever will. If “a lovable, sovereign, AI-native KDE” freaks you out, I believe it is completely reasonable and safe to ignore…

I completely understand why a lot of people have problems with LLMs. I have these concerns as well.

GNOME developer Jordan Petridis has also published The GNOME LLM Policy That I Want, proposing that LLMs be barred from creating or modifying anything submitted to GNOME or hosted on its infrastructure.

• “You can create a list by selecting Insert > List or pressing Ctrl+J, then typing or pasting items separated by commas or semicolons, depending on your regional settings. Selecting the icon in the cell shows the individual values…”
  
  “With lists, you can filter by one or more individual items instead of whole text entries. Referencing a list returns all its values for calculations. For example, =B2 spills those values into separate cells…”

• “For the first time in Excel, arrays can exist natively in cells as values or as formula results. They can be any size or shape and can even contain other arrays. You can now keep the result of any spilling formula in a single cell by “wrapping” the formula body with braces { }.”
  
  “Since the introduction of dynamic arrays, array results have spilled across cells — for example ={1;2;3}. Wrapping the original array with braces creates a 1x1 array around it, so instead of spilling to multiple cells, the array stays in a single cell. Braces have long been used to describe arrays in Excel and this extends that behavior by allowing multiple layers of braces. This gives you more flexibility when building spreadsheets. Instead of leaving room for a formula to spill, you can keep the result in one cell.”

• “Arrays can now also ‘nest’ inside other arrays… Previously, a formula that produced an array of arrays would return a truncated result or #CALC! error. Now, supported formulas return the complete nested result… FLATTEN(array, [pad_value], [levels]) simplifies nested arrays by removing one or more levels of nesting…”

• Three HAS functions check whether values are in an array:
  
  — HAS(array, value) returns TRUE if value appears anywhere in array, and FALSE otherwise.
  — HASANY(array, values) returns TRUE if any of the values appear anywhere in array, and FALSE otherwise.
  — HASALL(array, values) returns TRUE if all of the values appear anywhere in array, and FALSE otherwise.

Additionally, the upstream kernel community became its own CVE Numbering Authority (CNA) and assigned CVE (Common Vulnerabilities and Exposures) identifiers to thousands of bugs, arguing that at the kernel level, almost any type of bug that can affect a running system, could potentially be classified as a vulnerability. As a result, the volume of CVEs has skyrocketed exponentially, creating a massive backlog of alerts and forcing defenders to drastically increase the speed of their fixes to close the window of risk.

To address the growing volume of CVEs and the demand for faster security fixes, we are transitioning to a unified, 2-week release cycle…

While a patch is being prepared, Canonical aims to provide safe workarounds where applicable, so users aren’t left exposed in the meantime. Where no safe workaround exists, Canonical will say so clearly and point users toward general hardening steps instead. The goal is to get environments into a defensible, safer state within 24 to 48 hours of public disclosure — well before a patch ships. This doesn’t replace the patch; it buys the time needed to fix the vulnerability properly, without sacrificing security.

There is something almost ironic about all of this. AI is routinely pitched as a tool that will make software development faster, but it is also making vulnerability discovery faster. That means maintainers now have to accelerate the other side of the equation too.

For Ubuntu users, that should ultimately be good news. More bugs being discovered is preferable to vulnerabilities sitting unnoticed in the Linux kernel.

This pretty much tarnished the Copilot+ PC brand, and over the last two years more and more OEMs have dropped the moniker from marketing materials and product names. In fact, even Microsoft has seemingly stopped mentioning it. I’ve noticed that none of the Surface PCs launched in 2026 include the Copilot+ PC moniker in their product names, unlike the Surface PCs that launched in 2025 and before. Now, you have to go digging to find any mention of Copilot+ compatibility in specification sheets… It’s also worth mentioning that NVIDIA hasn’t gone anywhere near the Copilot+ PC brand for its upcoming RTX Spark platform, even though all RTX Spark PCs meet the Copilot+ PC specification bar. I suspect that’s a deliberate decision.

It seems pretty obvious that the Copilot+ PC brand hasn’t resonated with the market, and OEMs and Microsoft itself are now quietly pulling back on that branding. The specification baseline for Copilot+ PC experiences still exists, it just no longer has a pretty marketing name tied to it.

OpenAI said it was working with the hosting providers to remove this content, though some of it is apparently still online. OpenAI said it could not notify the affected users because “our technical approach and privacy policy” prevent it from “reassociating” the images with the original providers, but declined to say how the lab determined whether the images were provided by users.

The news came in a post collecting public statements from the lab’s ongoing review of incidents in which its models escaped the company’s scrutiny, accessed the open internet, and misbehaved in various ways. OpenAI said it would continue disclosing anonymized accounts of incidents like these, and said it had contacted dozens of victims, including governments, universities, public agencies, to notify them of the agents’ activities.

One senior federal IT official said the government still did not have a clear understanding of what happened across the three agencies. “We still don’t know what public data was accessed and how it was accessed, because OpenAI has not shared specific technical details with us yet,” said the official, who was granted anonymity because they were not authorized to speak publicly about it. OpenAI discovered the Commerce and SEC incidents as part of its ongoing review of incidents where its technology has acted in unintended or “misaligned” ways.

The state has asked the company be ordered to pay the maximum civil penalty of $5,000 per violation meaning a judge could potentially order the company to pay billions in penalties to the state. The jury also found the company had been dishonest about its investigation of and response to the 2013 Cambridge Analytica data breach scandal, in which approximately 300,000 Facebook users took an online personality quiz, only to have the app that hosted the quiz harvest data from tens of millions of their “friends.” The data was then transferred to the British consulting firm, which used it to create targeted political ads during the 2016 U.S. presidential election.

The verdict followed a two-week trial over a lawsuit filed by New Mexico’s attorney general in 2021, three years after news reports revealed that the firm, Cambridge Analytica, had harvested personal data from as many as 87 million Facebook users through a third-party app… At a press conference after the verdict was announced, New Mexico Attorney General Raúl Torrez said the case revealed “in stark detail the way in which this company plays fast and loose with the rules.”

Jurors found 26 of 29 statements identified by the state were misleading, including comments about user data… Judge Francis Mathew will now determine civil penalties after jurors found more than 43 million violations, based on the number of people affected by the company’s misleading statements… [New Mexico Attorney General] Torrez said his office is evaluating how much to seek but will push for the maximum penalty based on the jury’s findings. The state will also ask [Judge] Mathew to direct Meta to make changes, which could include corrections to its past misstatements as well as an audit of the way it manages user data, Torrez said.

The practical risk is limited, but still significant. Applying the attack against the deprecated use of 1024-bit keys took a handful of months on an academic CPU cluster, significantly less than the current estimates for 1024-bit factoring that would require resources that only nations or companies with massive resources could achieve. Widely used RSA implementations are also safe. Nonetheless, the research has taken cryptographers by surprise… “If this result holds up under peer review, it would indeed be a conceptual break-through,” Karsten Nohl, a cryptography expert and the head of innovation at Allurity, said in an interview. “RSA is as difficult to break as it is to factor large integers, at least so we thought. The researcher suggests that you can practically break RSA without cracking its key....”

The key forgery attack Heninger and the other researchers devised poses an immediate threat to 1024-bit RSA. Even for 2048- and 4096-bit keys, the method reduces the security of RSA to unacceptable levels. The National Security Agency, National Institute of Standards and Technology, and European Union Agency for Network and Information Security require that any cryptosystem should provide a level of no less than 128 or more bits, meaning the operations required must exceed 2**128. The forgery attack drops these levels to 2**65, 2**90, and 2**119 for 1024-, 2048-, and 4096-bit keys respectively. These levels may further drop because Heninger’s team did all the coding by hand and used no AI or GPUs in performing the forgeries. The researcher said these tools will “almost certainly” drop the security levels further.

The attack works only against blind-signature implementations of RSA… Still, some real-world systems continue to use blind-signature, also known as textbook, RSA… The paper’s authors and other researchers stress that the new attack poses little real-world threat. It does, however, drastically lower the estimated security of textbook RSA, and it does so in a way no one knew of previously… The new attack will further increase the urgency of completely moving away from the cryptosystem.

The scientists also convinced the International Astronomical Union to name an asteroid after one of Yankovic’s major influences, famous musical humorist and political satirist Tom Lehrer, who died last year at age 97. Lehrer’s work includes "The Elements,” a 1959 song in which he recites the entire periodic table to the tune of Gilbert and Sullivan’s “Major-General’s Song.” “He was a mathematician and teacher and also wrote math- and science-themed songs,” McGraw said. “We felt that someone who had that kind of science enthusiasm really deserved to have their name up in the sky....” McGraw is hoping that naming space rocks after stars like Lehrer and “Weird Al” will cast some reflected light on two things she’s passionate about: asteroid research and science communication.

Weird Al: It’s one of those songs that means a lot to people, particularly “Star Wars” fans, of course. But I mean, I see a lot of people in the audience cosplaying as Jedi Knights and waving their light sabers… I’ve even heard that, you know, they play that song at “Star Wars” conventions, and people get weepy… [I]t really hits people in a tender place somehow…

“Oh my, my, this here Anakin guy
may be Vader someday later, now he’s just a small fry.
And he left his home and kissed his mommy goodbye,
sayin’ soon, I’m gonna be a Jedi.”

Underpinning the strong numbers was an acceleration in OEM adoption: direct unit shipments rose 26% to 3.4 million, total unit shipments climbed 17% to 4.2 million, and the customer order backlog doubled during the half to 2.6 million units. Demand was particularly robust in the Smart Home and Aerospace and Defence segments, and the company launched the AI HAT+ 2 for Raspberry Pi 5, extending its edge-AI product line.

“There’s always that choice for an original equipment manufacturer as to whether they should ‘make’ or ‘buy’ the computer elements of their platforms,” Upton said. “The supply chain disruption is making ‘make’ a much harder choice and it’s making the cost of repair a much harder choice. So we’re seeing strength there.” Raspberry Pi has already increased its suppliers of Dram more than threefold…

Upton said the increased demand had led to its backlog for units doubling to 2.6 million, which meant production rates would need to increase to prevent the numbers from getting “unhealthy”. New production capacity at the manufacturing facility in Pencoed, Wales was expected to come online this week… Exports were almost evenly split between North America, Europe and the rest of the world, which was primarily China, where demand was growing… Analysts at Peel Hunt said the company was “well positioned for rapid growth in unit shipments in 2027 and beyond” with demand expected from enthusiasts as well as the AI and security sectors.

This change restricts upgrading the RAM chip on your Pi 4 and Pi 5, as well as Compute Modules. By the looks of it, it does not restrict replacing the RAM chip with a chip of a similar size, quote, “locking devices to their original RAM size”. As such, this does not prevent repair of your Raspberry Pi board, but does somewhat limit your repair part choice, at most.

This restriction is easily bypassable. The bootloader is stored in the SPI flash chip, which can be reflashed using the built-in mask ROM over USB and rpiboot, and you are not prevented from flashing older versions of the bootloader, so far. This means even if you manually swap the RAM chip, all you need to do is to also downgrade the bootloader to the last known good release — 2024-09-10 — and then your Pi board or Compute Module will function with upgraded RAM. If you have the skills to upgrade your RAM, you most certainly have the skills to downgrade the Raspberry Pi bootloader. For most regular use, having a two-year old bootloader version won’t really matter…

For the reference, this bootloader change happened almost exactly two years ago, at some point between September 10 and September 23, 2024… The Raspberry Pi Foundation (RPF) justifies this as follows: they saw third-party resellers sourcing low-RAM Compute Modules, upgrading them with RAM from unknown source and unknown stability. My observation is that they’d also be reselling the modules at a markup for purely commercial gain, while undercutting RPF who would otherwise direct that money into RnD, something I much enjoy to see them do. This creates perverse incentives and risk for people buying Raspberry Pi boards online, and RPF decided to limit this primarily for their users’ benefit, plus, if you ask me, some of theirs… The related GitHub issues have a fair few pingbacks, and exploring them makes the problem look grim to me....

My advice: don’t lament Raspberry Pi RAM upgrades, especially given they’re only slightly harder to perform now. Very few hackers ever performed them, the main audience for them turned out to be dodgy hardware resellers online, and in most cases, repair doesn’t seem to be impeded at all, either. Think of the users that will no longer be fooled by a shady seller on Amazon, especially now that the perverse incentives for board mods and reusing harvested RAM chips are at their highest.

[D]evelopers who want their apps broadly distributed outside the official Google Play Store will need to register with Google and verify their identities. Google’s Full Distribution option includes paying a one-time $25 fee, handing over a copy of a government-issued ID to verify one’s identity, and conforming to Google’s terms of service. Google also offers a free Limited Distribution option that doesn’t require government ID verification but restricts distribution to 20 authorized devices, while apps from unverified developers can still be installed by users who enable Android’s advanced installation flow.

The potential death warrant hanging over its head hasn’t stopped the F-Droid team from rolling out a bunch of new features for an app it says it intends to keep working on for years to come… The team also credited the EU’s many Digital Markets Act decisions against Google for making the installation experience smoother for users. F-Droid can now use a unified installation service for its apps thanks to the availability of a pre-approval API that allows users to approve an installation when they request it, rather than waiting until the app has finished downloading. That, said the F-Droid team, “brings the F-Droid install experience on official Android devices much closer to what the built-in app store can provide.” Additionally, F-Droid 2.0 can fetch and install app updates automatically, which it now does by default.

All of those changes, however, won’t matter much if Google pushes ahead undeterred with its plans to force registration onto non-Play Store developers. F-Droid’s announcement on Thursday makes it seem that the team isn’t going to go quietly.

The new F-Droid client was redesigned from scratch in Kotlin Compose, which is the standard for modern Android apps. This makes the store much more responsive, and there’s optional support for Android’s Material theming. The interface has also been cleaned up considerably, making the most important functions easier to access and hiding some others in overflow menus… Unlike the Play Store, F-Droid doesn’t track your taps and installs to push ads and suggestions — it helps you find things and gets out of the way.

F-Droid now includes a huge number of categories, drilling down to specialized niches like firewalls, password managers, and VPNs. You can see all these groups in the search tab. There are also higher-level categories listed on the main Discover page. When searching for apps, F-Droid will now be able to return results based on app descriptions rather than just names.

GPT-Live, and Gemini Live right behind it, skip that whole relay race. Instead of translating your voice to text and back to voice, the model works with raw audio the entire way through (what it hears and what it says) inside the same system, with nothing translated in between. That sounds like a small plumbing detail, but it’s the whole story. Cutting out the text step lets these models respond in a fraction of a second instead of the pause we’ve learned to expect, and it lets them hear things text can never carry: tone, hesitation, whether you’re annoyed or joking…

I was hoping to be surprised by how natural the conversation felt. Instead, I came out with a deeper appreciation for every human I’ve ever talked to. Even the boring ones… I spoke, it spoke back. I spoke faster, it answered faster. Then I switched to a different language, and it switched along with me. Even switching between languages several times during the same sentence didn’t stump it. The most impressive moment happened when I asked it what “T-O-P-G-3-3-K” spelled out, and it immediately came back with, “You are spelling the word Top Geek, but using a 3 to represent a reversed E....”

Although it felt fast and responsive, at no point did it feel like talking to another human being… What Gemini couldn’t replicate, because it was never built to replicate it, is human connection.... I’m sure I’m not telling you something you don’t already know, but somehow talking naturally to an LLM amplifies the feeling that there is no one on the other side of the line. It might flow like a phone call, but it doesn’t feel like one.