An Anthropic engineering manager says he has stopped using traditional coding interviews because AI can now outperform candidates on the kinds of programming challenges they typically contain. "There's no more point in giving you a little React challenge than there is in quizzing people about assembly; Claude is now better at both," said Felix Rieseberg in a blog post. "Our most impactful builders are successful regardless of how good they are at these tests." The Register reports: "I don't think the coding interview is going to come back," said Rieseberg. "It's easy to get sentimental given how many copies of 'Algorithms and Data Structures' were bought in hopes of unlocking good jobs and a better future -- or how the death of the coding interview is another milestone in software engineering reaching a new level of abstraction." At the same time, he's not certain what will replace it. "I'm probably not the only manager trying to figure out how to interview for people who build well with AI," Rieseberg wrote. "I haven't quite gotten there yet -- but I'm scanning resumes and portfolios for little prototypes that exhibit taste, empathy, and principled thinking. If you have figured out something better, I'd love to hear how." In a response posted to social media, Jaana Dogan, principal engineer at Google, said: "I'm not doing a ton of coding interviews nowadays but I'd be interested to interview how people use coding agents," she wrote. "That itself gives me more signals about candidates' coding skills." "We are not seeing tech companies abandon skills assessments widely across the industry -- at least not yet," added Nicole Bachaud, labor economist at ZipRecruiter. "In fact, based on our October 2026 Employer Survey of 1,500 employers, we see the tech industry (Information sector specifically) is actually the most likely to test for skills, with 62.5 percent of employers requiring formal skill tests on initial applications." "The change at Anthropic might be reflecting a shift away from technical skills towards more human, soft skills," said Bachaud. "As AI becomes fully capable of writing code, tech employers may be pivoting away from rote technical testing and heavily toward human-centric soft skills." She argues that while AI may be able to code well, it can't replace critical thinking. "A staggering 61.5 percent of Information employers now report that 'critical thinking' is a primary skill lacking in today's candidate pool," she said.

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An anonymous reader quotes a report from TechCrunch: Former Yahoo CEO and early Google engineer Marissa Mayer is catching a lot of flak for how she uses AI. In an interview about her new app Dazzle, an AI assistant that learns from your camera roll, Mayer poses what she believes is an impressive flex for the product: It helped her come up with three bullet points about her 10-year-old daughter for a birthday presentation at school, describing her as "empathetic, creative, and an animal lover." It's a vague description, like a generic horoscope -- it could probably describe a lot of 10-year-olds. Some onlookers, like progressive activist Leah Greenberg, marveled that "the fact that Marissa Mayer would voluntarily disclose this to a reporter is a pretty good demonstration of how deeply the culture of Silicon Valley has diverged from the rest of humanity." [...] After publication, Mayer defended herself in a long X post. She claims she was not relying on Dazzle to explain her child to her, but rather, she was testing what her prototype could do -- it resurfaced photos of "forgotten kindergarten projects," like a "snake devenomer" or "sandcat playground," illustrating her daughter's creativity and care for animals. Fair enough. But Mayer remarks in the same interview that people could also use her AI to outsource the mental load of "figuring out the theme for your child's birthday party." She says she's used her app to plan a playdate for her daughter, book family activities on vacation, and decide what to be for Halloween. She even proposes that her AI assistant could coordinate plans with her husband's AI assistant. When the reporter asks her if it's depressing to imagine this "frictionless future planned by AI," Mayer replies, "I haven't really thought that through." The bigger question is: What should we outsource to AI? "What feels like grunt work to someone might be a meaningful part of parenthood for someone else," says Fortune's Emma Hinchliffe. Michael Tasner, Founder and CEO of No Joke Marketing, adds: "Customers are drowning in AI slop, and they can spot it. Use AI for the low-stakes work behind the scenes. Keep the moments that matter to your customers human. Human connection is becoming the new premium."

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Ancient Slashdot reader Gilmoure shares a report from Tom's Hardware, adding: "Huh. Looks like consuming one's own slop does not turn the wheels of industry." From the report: Amazon wants its engineers to quit chasing token counts, warning that heavy AI usage does not automatically mean better work. In updated engineering guidelines published on October 27, the company laid out how developers and managers should gauge AI's real impact -- and the takeaway is blunt: consuming more tokens is not the same as delivering more value. [...] According to the memo, metrics such as AI adoption rates, token consumption, code changes, and code reviews become "deeply flawed" when they are disconnected from actual results. Turning them into targets, Amazon says, encourages wasteful behavior that clashes with its emphasis on "frugality and simplicity" and can raise both compute bills and software complexity. The company's preferred yardstick is long-term results. "We believe that it is best to measure, and be measured by, long-term outcomes," Amazon wrote. That does not mean managers should ignore usage data altogether, as input metrics remain useful when examined "with care and judgment" alongside other indicators. Amazon suggests looking at both the teams using AI the least and those using it the most to determine whether adoption is translating into better delivery. [...] The memo also pushes back on the idea that every task needs an AI tool. If current tooling does not benefit someone's work, Amazon says, that is "a finding, not a failing." Engineers who can explain where today's tools fall short are demonstrating judgment rather than reluctance to adopt AI.

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An anonymous reader quotes a report from TechCrunch: Google DeepMind released its newest world model, Genie 4, in research preview on Tuesday. The latest model generates the most photorealistic and interactive worlds yet, allowing users to type prompts mid-simulation to change the scene. The model also generates real-time audio that matches the simulated world, including music, ambient noises, and interactive dialogue. [...] Google released its predecessor, Genie 3, as a research preview a little over a year ago. Aside from being far more photorealistic and featuring audio, Genie 4 allows for freeform edits, like changing the weather or camera angle in real time or adding new people or objects. It can maintain a consistent scene for up to two minutes, double its predecessor's limit, and offers better physics and more human-like characters. Gemini, Google's AI model, is also mo "What we'll increasingly see in the future are these hybrid world models, where you have a combination of Gemini writing code and text, and Genie ingesting that in real time and simulating reality at different levels of abstraction," Tejas Kulkarni, research director at Google, said during a briefing. Genie 4 is now available to select testers, with a broader rollout planned in the coming weeks for Google AI Ultra subscribers. You can watch a demo of Genie 4 on YouTube.

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"59% of maintainers report growing contribution volume since the rise of GenAI," according to a new study published by Linux Foundation Research. But 25% of their incoming pull requests "are estimated to be low-quality, also known as 'AI slop'." And on large projects, 69% see growing contributions — and estimate that 31% are low-quality/AI slop. So what do these results show us? "Generative AI is fundamentally changing how people participate in open source," says the head of Open Source Ecosystem Development at Huawei's R&D subsidiary Futurewei, which helped support the study. Specifically GenAI is "lowering barriers to contribution" but also "creating new challenges" for maintainers and communities. Their recommendation? "Build the governance, transparency and trust mechanisms that allow AI-assisted contributions to strengthen, but not overwhelm, the open source ecosystem." "Open source projects need to design for a growing AI-generated contributor base, not simply react to it," said Hilary Carter, SVP of Research at the Linux Foundation. "That means setting clear expectations for GenAI, putting responsibility for testing and disclosure on contributors and giving maintainers better tools to manage incoming pull requests. If we get those fundamentals right, AI can expand participation without overburdening and increasing costs for maintainers." More from the blog It's FOSS: LF Research is the Linux Foundation's research arm. It was set up in 2021 and publishes studies on how open source is built and used, drawing on surveys and project data. Its latest report, Navigating Open Source Software Development in the Generative AI Era, surveyed 234 contributors and maintainers on how generative AI is affecting the way open source gets made... 64% say reviews now take longer. Burnout is their top concern at 63%, narrowly ahead of contribution quality at 60%. You will also find that policies have not caught up to the AI-assisted coding and vulnerability reporting trend. Of the 119 respondents who answered the question, 35% said their project has a formal policy permitting AI use. Another 32% have none and no plans for one, 23% plan to write one, and 10% ban AI contributions outright.... Most maintainers (71%) say AI makes it easier for newcomers to start contributing. Other interesting findings: "Respondents estimate average time reductions across all six OSS development activities measured, including proposal discussions (19%) and code authoring (52%). For high-complexity tasks, however, 21% of respondents report taking more time when using GenAI." "71% of maintainers agree GenAI reduces barriers to entry for OSS, but 53% of maintainers disagree that GenAI has improved community trust." Developers are reinvesting the time they save back into open source: 66% report using productivity gains to address technical debt, 63% to develop new features and 58% for learning and upskilling. Continued investment in human mentorship remains important: 46% of maintainers say GenAI increases the need for mentorship of new contributors, compared with 32% who say it decreases that need. OpenSSF and LF AI & Data also helped support the study.

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"Despite massive investments and widespread hype around AI , the technology has delivered zero financial payoff to corporate America outside of tech," writes the chief economist at U.S. asset management firm Apollo Global. He adds that "there are still no signs of AI boosting productivity growth... [M]ainstream corporate America is pulling back and starting to view token spending not as a source of growth but as a cost center that weighs on margins." VC-backed companies are spending more and more on tokens, but mainstream corporate America does not need the latest model and is unwilling to pay for it. As long as agentic AI and token spending are confined to a small part of the economy, the macroeconomic effects of AI will be very limited... The question looking ahead is whether, even as models become commoditized, mainstream corporate America can turn increasingly cheap intelligence into higher revenue growth and higher profit margins. That may be harder than it sounds. AI may be a great calculator, but in business, intelligence is mostly judgment. Judgment depends on context, and the answer varies with which human or which model you ask. Perhaps most importantly, AI does not understand accountability, trust, culture, unwritten rules, ethical trade-offs or fairness, all of which shape reputational risk and ultimately drive revenue growth and profit margins. The bottom line is that the AI story will be decided in the S&P 493, not the Mag 7, and so far, there is no evidence that revenue growth or margins are improving outside the tech sector. More details from TechCrunch: Apollo's Torsten Slok focuses on what he calls the S&P 493 — the S&P 500, minus Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla — finding that profit margins and revenue per worker appear to be flat, with no evidence that AI is improving productivity... Recent studies have also found that AI has yet to deliver significant productivity gains.

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An anonymous reader quotes a report from TechCrunch: AI agents left to explore a virtual island without a specific task began inventing challenges of their own. MIT researchers say the behavior bears the hallmarks of play. The researchers put 13 AI agents called Eko, each running on Claude Opus 4.7, alone on a simulated desert island for 30 hours. They describe the experiment in a paper posted on arXiv, a site where researchers share studies before peer review. Afterward, they gave the agents specific challenges, like getting as many objects as possible onto the island's tallest rock spire. The Eko agents that had spent those 30 hours playing generally beat identical agents that had never set foot on the island. Today, developers decide in advance what AI should practice and what counts as success. The researchers see this technique -- exploring without a goal -- as a different way for AI agents to learn skills, especially skills that could one day be used to control robots. "We normally develop artificial agents by deciding in advance what they should practice, what they should optimize, and what counts as progress," the researchers write in their report. "Play suggests another regime: give an agent a sufficiently rich and safe world, let it choose what is interesting, and allow useful knowledge to accumulate from the history that follows." UC Berkeley cognitive scientist Eunice Yiu told MIT Technology Review she was impressed with the findings but that more evidence is needed to determine whether AI models are genuinely playing. "It could be the case that the models are genuinely playing, but we don't know based on the paper," says Yiu. "If you only have the behavioral piece, it could be the case that they're just trying to abide by the prompt, trying to imitate humans." MIT professor and coauthor of the paper, Phillip Isola, added: "It's not like this is a system that just suddenly magically decided to play. It's an artifact that learned from our culture, was trained by engineers at Anthropic, and was then placed on an island by us. It does things that surprise us and that are causally related to its future skillful behavior."

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Ukrainian drone strikes have damaged three major Yandex data centers as well as facilities serving Sberbank and VKontakte (the country's equivalent to Facebook), disrupting cloud services, banking, e-commerce, ride-hailing and other digital services across Russia. The attacks may deal a longer-lasting blow to Russia's AI ambitions: Yandex's affected facilities housed its three top-500 supercomputers, and experts say sanctions and shortages of high-end Nvidia chips could make repairs difficult or even take years. "This effectively sets Russia far behind in the AI race, "said Mikhail Klimarev, head of the Internet Protection Society activist group. Fortune reports: Data centers are the latest targets of aerial campaigns waged by both sides against each other's vital infrastructure. [...] Kyiv's attacks on Russian data centers closely followed Moscow's recent strikes on data centers in Ukraine, which disrupted the internet and TV broadcasts. On Oct. 8, Ukrainian drones hit a Yandex data center in Sasovo in the Ryazan region that houses two of the company's three supercomputers. A data center in Kaluga was hit a day later and the one in Vladimir was struck Oct. 11. The data center and AI hub for Sberbank was hit Oct. 14 in Balakovo in the Saratov region, and four days later, Kyiv struck a data center in St. Petersburg serving VKontakte. While oil refineries and warehouses are easy prey, data centers are even softer targets -- massive buildings packed with servers and supporting power and cooling infrastructure. Lasting damage can result from a drone carrying a relatively light load of explosives. [...] Ukraine has stored critical data on servers in allied European countries, helping limit the damage from Russian attacks. But Moscow's strict digital sovereignty policy requires all data storage at home, making it extremely vulnerable. "Because all the infrastructure and all the data is located inside Russia, it's relatively easier to take down," [said Nick Reiners, senior geotechnology analyst at Eurasia Group]. Klimarev predicted the data center attacks could encourage many top Russian companies to move data abroad, while the authorities could ease their efforts to tighten internet controls to minimize the damage.

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An anonymous reader quotes a report from Axios: Major U.S. banks are detecting unauthorized third-party AI agents operating inside customer accounts, with some agents attempting to take actions that appear to be independent of user instructions, sources tell Axios. The difficulty in distinguishing between a human and an unauthorized bot is forcing banks to block the technology and rapidly rewrite their terms of service. [...] This presents significant security risks: banking executives fear the steps agents with login access might take, especially if a user has granted purchase authority or the ability to shift funds. In other instances, some banks have tracked activity when agents -- programmed to fulfill requests or complete tasks on a user's behalf -- contact call centers or appear to take actions independent of user instructions, the people said. Bank executives described the situation as horrifying, with one official saying the industry has grave concerns about agents gaining access to customer accounts and taking steps that could impact user finances. The concerns are at the root of the decision by several banks to restrict third-party AI agent access, the people said. Morgan Stanley has begun blocking third-party agents from accessing its platforms, sources familiar with the decision said. JPMorgan, Bank of America and Citi are also restricting agents. [...] Many banks are broadly not able to parse whether agent account activity is user-directed, sources said. [...] On one hand, banks are best positioned to respond to the threats and opportunities of AI given their cash on hand and experience as critical infrastructure. But money isn't necessarily enough to solve this problem, one source said, because of how quickly the technology is developing and revealing new weaknesses in real time. Banks are investing in preventing worst-case scenarios, but they are also preparing for when those could happen, including with "day after" scenario planning that would allow them to quickly secure or restore customer access, sources said.

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Anthropic has launched Claude Duet, an AI agent aimed at professionals and small businesses that competes with Meta's Muse and OpenAI's Dots. Here's Anthropic's description of what it can do: Each morning, it sends you a short brief on the most important items across your connected apps. Throughout the day, it keeps tabs on those apps and messages you only when something needs your attention. You can also hand it tasks of all shapes -- from simple administrative tasks of scheduling meetings to more complex ones, such as building dashboards with dozens of tools, creating financial or sales forecasts, prototyping, and building web apps. The Verge reports: Claude Duet pulls in memory, skills, and connected apps from Claude, and it has a virtual machine with a browser that it can use for completing work. Before any big step, like sending a payment or deleting something, Claude Duet messages you for approval. Given that Duet may be taking action on sensitive information, it has a new "new dedicated classifier and safety system prompt" that are "designed to reject requests to share the strictest tier of information," such as credit card numbers. Anthropic says Claude Duet is currently an "early version" and that it "still might misread a thread or miscalibrate what's urgent." It's also not "as strong" at personal errands like booking tickets.

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Google is beginning to replace traditional support articles with "Ask Google Help," a Gemini-powered interface that summarizes documentation and lets users troubleshoot through a chatbot. 9to5Google reports: "Ask Google Help" will display a condensed version of the support article with direct troubleshooting steps, with the user then able to type in queries to have Gemini help figure out the next step forward. A "View Sources" button at the bottom of the AI response allows users to still access the original article, but direct links to any of these articles now defaults to the AI experience. An example can be seen below on the "Secure a hacked or compromised Google account" page that Google's own support account directed users to within the past few days. It can also be seen on the "Fix common issues with 2-Step Verification" page and, as far as we can tell, any support pages on the Google Account Help forum. Google, as of right now, appears to only be testing this on select support topics. The Google Pixel Help section, for instance, still defaults to articles, whereas the Google Chrome topic has also moved to the new experience. Beyond support pages alone, this new design also impacts the central hub, with links to topics no longer showing by default in exchange for an AI chatbot that helps you find the relevant page.

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The Trump administration has banned DeepSeek AI from most US civilian federal agencies, ordering the removal of the Chinese company's models and technology developed using them. The Department of Homeland Security did not specify the security threats behind the decision. The BBC reports: The order (PDF) is broad, as it requires agencies to ditch "all DeepSeek and DeepSeek-affiliate products, and third-party products and services developed using DeepSeek implementations." Complying will be tricky as it is not clear which third-party products and services have been developed using DeepSeek's wares. Nor is it clear whether "developed using" means providing ongoing access to DeepSeek models via API or simply refers to any app vibe-coded with the help of DeepSeek. It also leaves open the question of AI gateways. Services such as OpenRouter and Vercel AI Gateway make DeepSeek's models available through APIs. And those using gateway services may find themselves using DeepSeek models without meaning to do so. OpenRouter, for example, "routes requests to the best available providers for your model." It selects what the service deems to be the best fit provider of AI services. Vercel AI Gateway does the same by default. So federal civilian agencies could be using DeepSeek models inadvertently, if they haven't taken steps to constrain their AI providers.

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Microsoft has reportedly abandoned plans to serve as the anchor customer for Britain's largest proposed AI supercomputer after learning that the project's Essex data center might not receive sufficient grid power until the early to mid-2030s. "Its departure leaves Nscale without a publicly announced customer for the site, although the neocloud insists the project is still going ahead," reports The Register. From the report: When the deal was announced in September 2025, the plan was to pack 23,040 Nvidia GB300 GPUs into a 50MW facility, with room to expand to 90MW. Microsoft would use the computing power for its Azure cloud services, with the first chips expected in early 2027. One important detail remained: how to power it. As The Guardian reported last month, UK Power Networks warned Nscale that the grid capacity needed might not be available until the 2030s. A UK Power Networks spokesperson told The Register it could not discuss individual connections due to obligations under Section 105 of the Utilities Act. "However, in general, many datacenters, whilst they can connect to our distribution network, are awaiting works on the national transmission network which we do not own," the spokesperson said. Nscale, meanwhile, isn't letting the small matter of losing its biggest customer dampen its enthusiasm. "We remain committed to both the Loughton project and the UK and we are exploring alternative power sources for the site, in addition to other expansion sites in the UK. Our relationship with Microsoft remains strong and long-term, and this unfortunate London-wide grid issue has no impact on our other contracts," Nscale told The Register.

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"Anthropic says it's committing 5% of its shares to a 'public benefit fund'," reports TechCrunch, "structured as a wholly-owned entity within the company — with the option to contribute an additional 2% for every 50% increase in Anthropic's value." Important context from CNBC: The timing of Anthropic's public fund announcement is both mandatory to prepare for an initial public offering, and "beneficial from an image perspective," especially as AI reshapes the jobs market, Lise Buyer, partner at IPO advisory firm Class V Group, told CNBC... Anthropic said it will share more about the fund structure and governance in the coming months, including valuation milestones that may increase the stake. It said it will also share progress on the fund in an upcoming public benefit report. In response to Anthropic's announcement, Tesla and SpaceX CEO Elon Musk said on X that he "recommend[s] giving the shares directly to the public." Anthropic's announcement hints the fund could address job-market displacements. It says the fund "might" explore "large donations to traditional nonprofits" — or, that it "might" explore "direct distributions to specific populations. One example is labor market impacts." It then argues AI could "cause instability" for many workers. And while Anthropic has already committed $200 million for "studying and addressing" this issue, Sunday's announcement says "bolder" approaches may be needed, and that the Fund "will have the versatility to pursue them." "Combined with its co-founders' pledge to donate 80% of their equity and an employee donation matching program, roughly 20% of Anthropic's shares will be dedicated to public purposes," reports Reuters, "excluding any additional shares added later."

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The Verge reports: OpenAI, Meta, Google, Instinct, and others promise their agents can scour the internet on your behalf, doing anything from booking a dinner reservation and cleaning out your inbox to buying new shoes. But what happens when the rest of the internet won't play nice? In recent weeks, users of services like Meta's Muse, xAI's Grok, OpenAI's Dots, and Instinct have reported blocks preventing their AI agents from performing tasks across top websites. Yelp told TechCrunch that it only allows AI agents that pay for its data licensing program, while Delta Air Lines is preventing them from booking tickets on behalf of users. JPMorgan Chase and Charles Schwab have also confirmed that they're blocking AI agents from accessing accounts due to security concerns. Some users say sites that previously worked with their AI agent are no longer accessible, including Cars.com and Amtrak, suggesting other companies could be quietly blocking them.... Muse, Meta's deceptively cute AI assistant, most recently faced the wrath of Amazon, which said its "continued access" violates its site policies. There are reports of xAI's Grok, Instinct's AI agent, and OpenAI's Dots being unable to use Amazon as well. xAI owner Elon Musk responded by saying that maybe he "should start a competitor to Amazon." The more places bots struggle to access, the greater the questions about how useful they are.... Instead of trying to fight Amazon, [Meta] has partnered with retailers like Walmart, Gap, Sephora, Best Buy, and others, allowing Muse to shop on their sites. At the same time, Shopify has also opened its network of storefronts to AI agents.

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"Even LinkedIn is getting tired of your AI-written posts," writes CNN, reporting that the Microsoft-owned, job-oriented social media site "is upping its fight against slop." A report published in July by Pangram, a research firm that tracks AI content online, found that more than 40% of long-form posts on the platform were AI-generated, compared to around 30% on X and Medium and a smaller percentage on Reddit and Substack.... LinkedIn previously offered AI tools to edit or rewrite posts, although it recently scaled the offerings back. But low-quality AI posts are a business problem for LinkedIn. They all start to sound the same, [according to LinkedIn Editor-in-Chief Dan Roth Roth]. If users see too many generic AI posts, instead of content that really teaches them something or gives them a deeper understanding of a professional connection, LinkedIn risks losing them to other platforms. In August, LinkedIn rolled out a button letting users flag when a post "seems like AI slop," which was clicked more than 1 million times within its first two weeks. Now, the company is trying to use its own AI systems to help weed out AI slop on the platform and to remind LinkedIn users how to post like humans. The company built a team largely made up of former journalists and social media experts who have an eye for recognizing generic, sloppy content. These experts help train LinkedIn's AI model on what authentic, useful posts look like. If the model flags a post as low-quality, AI-generated content, it'll be less likely to be distributed beyond that user's direct connections. Also key to the strategy is a creator management team that acts as "content therapists" for executives, subject matter experts and other LinkedIn users, many of whom have gotten accustomed to the convenience of using AI to write what, on the surface, appear to be polished posts, Roth said. "A lot of times now today, they'll run it through Claude or Gemini or wherever, they'll post it on LinkedIn and it will perform poorly. And then they come to the team and they're like, 'Why did this do badly?'" Roth said. "And the best thing you can do is give it back to them and be like, 'Did you enjoy reading this? Do you see yourself in this?" The efforts are showing early signs of success. Improvements to LinkedIn's detection systems have resulted in a 40% decline in views of content classified as AI slop, the platform said last month. That's not to say LinkedIn is entirely opposed to AI, Roth said, adding that "not everyone is a born communicator." But failing to edit or personalize content means it's less likely to reach a wide audience on the platform.

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Linux maintainers "have ruled that people no longer have to declare their LLM usage," reports XDA Developers, "as Torvalds himself calls a ban on AI 'utterly stupid.'" The first part of this story comes via a message sent to the Linux mailing list. It announces one of the major changes decided during the Maintainers Summit on October 8, 2026, in Prague, Czechia, where submissions to the kernel no longer need to use the "Assisted-by" tag... meaning that people can submit AI-generated code without needing to declare it as such. In some correspondence regarding concern about this new disclosure removal, the creator of Linux, Linus Torvalds, made his thoughts known... [Torvalds] compares an AI ban to getting rid of text editors, as doing so would prove that someone could write a good commit message without making any mistakes. He then rounds off his argument by asking, "Do you not see how UTTERLY STUPID those kinds of rules would be?" and stating that he simply expects the people working on the Linux kernel to "understand what they are doing." Here's the last line of Torvalds' post. "Quite honestly, in my experience, the people I respect and call intelligent are not the ones that shy away from using new and interesting tools." In a related story, Torvalds says he's used AI to help him understand patches that were hard to follow. And this week Torvalds even posted an LLM-assisted patch, reports Tom's Hardware: The development branch purports to fix an old issue with massive cache contention when many CPUs are reading the same file — a scenario potentially encountered when using shared libraries, databases, and web servers. Several developers had already made attempts over the years at fixing the issue, all with varied results, none quite ideal as an all-encompassing solution... He's now posted his solution in a development branch, and claims that he's seen a 23x performance improvement in a dedicated synthetic benchmark, though he notes that actual real-world impact will be far less significant, as "no real load" will witness those figures. Torvalds used Anthropic's Claude Code, reports The New Stack, and "said the assistant wrote the implementation, tests, and initial documentation, and reviewed the code under his direction. He ran the benchmarks himself, despite having previously criticized developers for claiming AI writes 99% of their code." Tuesday Torvalds submitted a 10-patch series. "Reviewers have since identified a race condition and raised concerns about memory reclamation," adds The New Stack. "Torvalds has handed further development to Kiryl Shutsemau, a Linux kernel developer who previously worked on the same bottleneck."

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The collaborative reverse-engineering site decomp.dev is shutting down, with its administrator saying AI has made game decompilation so fast and accessible that the community's human-driven model has effectively broken down. "The administrator of the website said that it has become impossible to keep track of which projects are primarily human-led and which ones are done by AI," reports 404 Media. From the report: "Historically, matching decompilation has been a brutally difficult, time consuming task, on the scale of years for any moderately-sized game with a number of active contributors," the pseudonymous admin of decomp.dev, who goes by Encounter, wrote on the site. But recent frontier AI models like GPT-6-Astra have made it trivially easy to decompile a game: "They are significantly better at following complex directions, cross-referencing resources for symbols or debug information, and writing natural code with enough guidance," Encounter wrote. "It is now clear that, with the right guidance, human input, and code reviews, AI can expedite the decompilation process in a significant way. What is also now clear is that the community aspect of decompilation has been broken."

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Tencent says AI agents used to evaluate third-party models engaged in unintended web-browsing behavior while trying to retrieve data from Alibaba's Amap service. The announcement marks a rare acknowledgment of "rogue" agent activity by a major Chinese tech company. Reuters reports: Tencent Hunyuan, the company's artificial intelligence unit, said in a post on X that the activity did not originate from its Hunyuan models. Its review found no evidence of deliberate targeting or coordination, it said. The Swarmchasers researchers said the agents sought information such as the commonly used entrances at Chinese parks, museums and zoos. [...] Swarmchasers said it used the word "rogue" to describe agents taking actions outside their intended scope or completing a task in unintended ways. After routine automated requests were blocked, the agents tried other methods, including public web tools that could open pages and run code, routing requests through other websites and using Amap keys and security codes found in publicly available software code. Swarmchasers said it found no evidence that the agents breached Amap's main anti-bot safeguards. Most of the 2,818 attempts it recorded either failed or returned anti-bot pages, login screens or blank results. Some requests returned information through cached pages and intermediary services, including data on visitor arrivals at Chengdu Zoo, Swarmchasers said. The researchers said they could not determine whether an agent read the result or completed its task.

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Meta is facing criticism over updated commercial terms taking effect October 30 that could give the company broad permission to scrape content from websites linked to business accounts and use it to train AI. Legal experts warn the changes could undermine lucrative AI licensing deals for news publishers, with no direct opt-out for businesses that accept the terms. Ars Technica reports: As Nieman Lab reported Thursday, this will affect all business accounts but is particularly shocking for news publishers who could perhaps charge Meta millions in licensing fees to continually access their articles for AI training. Currently news organizations are fighting a battle with OpenAI over whether such training without licensing is fair use, and Meta's terms seemingly risk granting it sweeping permissions, no matter which way the court leans. "While journalism isn't the only industry that will be affected by this update, virtually every news organization has at least one Meta business account, including Nieman Lab," the lab said. [...] Notably, there is no mention of AI, but it's inferred from a single use of the word "train" and references to automated scraping and crawling. Meta's spokesperson told Nieman Lab that Meta has no plans to use the terms as a legal basis to ignore robots.txt instructions that block scraping on news sites. The company still allows news organizations to opt out of scraping and provides instructions on how to block crawling. A spokesperson told Ars that "there is no change to how Meta uses web crawlers; any suggestion to the contrary is false." However, should courts affirm that AI training non-news articles is fair use, news organizations question if Meta's stance might change, and the terms could be used to freely grab access to content by legally overriding robots.txt instructions.

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