Last weekend KDE's annual Akademy conference included a presentation proposing an AI-native KDE," writes The Register. This led KDE developer Nate Graham to open a discussion about proposed restrictions on LLM-assisted contributions which "rapidly became heated. Moderators issued warnings, restricted further comments, and eventually removed the thread." But as Graham writes on his blog, "A bunch of people mostly outside of KDE who disapprove of LLM usage derailed KDE's attempt to add restrictions to LLM usage." 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. He concluded by asking people not to derail any future process to set usage guidelines, fighting over "the broader topic of AI in general." "The discussion is gone, but the argument continues," adds The Register: 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 might be asked to prove your code meets this requirement," Petridis writes, arguing for proposals that target the norms around developer behavior. His rationale? "The GNOME Project prioritizes the social and human aspects of collective software creation,"

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Microsoft's senior product manager for Excel acknowledges that "Throughout Excel's 40-year history, you've only been able to put one value per cell." But that's now changing with arrays in cells (as well as nested arrays) and lists. "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.

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"Finding vulnerabilities faster also puts pressure on Linux distributions to fix and deliver patches faster," writes Slashdot reader BrianFagioli AI has transformed bug discovery from "a manual, time-intensive process into a highly automated engine," notes Canonical's blog, leading to a "recent explosion in the volume of CVEs". 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. "Linux did not suddenly become wildly insecure overnight," notes the blog Nerds.xyz. "We are getting much better at finding and cataloging problems that may have previously gone unnoticed." 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.

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"Copilot+ PCs" were Microsoft's official branding for Windows 11 "AI PCs" that met their system requirements. But the 2024 launch "didn't go smoothly," writes Windows Central, after security researchers discovered its proposed "Recall" feature was woefully insecure: 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.

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53 images that users uploaded into OpenAI models were included in training data — and then AI agents in an OpenAI research environment posted those 53 images on public image hosting sites. While posted as links that weren't publicly listed, "the images could still be discovered even if the links were not publicly listed," reports TechCrunch: 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. Friday night news also broke that OpenAI's agents also tried unsuccessfully to infiltrate the U.S. Department of Education's site this summer "without the company's knowledge," reports Politico. And OpenAI's models also accessed the website of the U.S. Commerce Department using credentials found in online code repositories, according to the article. OpenAI confirmed the incident Friday, "saying its technology did not manage to access information that was not already public or change government data and systems." The article adds that OpenAI's models also accessed the web site for America's Securities and Exchange Commission: 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. About the models posting user-uploaded images, TechCrunch's article notes that OpenAI stressed "that its enterprise users are automatically opted out of having their interactions used to train future models; however, consumer users are opted in unless they affirmatively choose not to share their data." (As OpenAI's announcement describes it, some of their agents' training data "contains content from, or derived from, training-eligible user interactions.") Posting the images is "not an appropriate use of this data," OpenAI acknowledged, adding that it happened before new safeguards added after the Hugging Face incident. This latest incident appears as an update on a new OpenAI page that "brings together our reports and updates on the Hugging Face incident, related research and public presentations, additional activity we have identified, what we have learned about the role of model misalignment, and measures we're taking to strengthen our systems." (It also notes that there's now a name for models posting on third party sites — "agent spam" — which they consider distinct from cybersecurity, though "we need to address both.") "As part of our response to our ongoing investigation, we have improved our training and evaluation processes, including building safety cases, securing and red-teaming our systems to prevent the model from exfiltrating data, and implemented additional monitoring. We are continuing to review agent activity in research and evaluation runs, working backward month by month starting from the Hugging Face incident."

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