America's garbage trucks can do more than just collect trash, reports Newsweek. They may also help identify code violations using AI. Officials in Cape Coral, Florida, recently considered equipping sanitation trucks with AI-powered cameras that would photograph properties as crews complete their normal collection routes. The system would have been designed to identify potential issues such as overgrown lawns, peeling paint, and illegal dumping, and to flag violations so the city staff can review them later before taking enforcement action... However, in a statement on July 13, Cape Coral officials said it would not be moving forward with the camera technology, citing cost issues and insufficient benefits. "Claims suggesting that this technology would automatically identify, cite or fine residents are inaccurate," the statement also noted... Cape Coral officials say that a camera system in the future would assist — not replace — human code enforcement officers, and employees will review any AI-generated alerts before violations are issued. "Even if such a system were to be considered in the future, any potential code violations would require review and verification by a Code Compliance Officer before any enforcement action could be taken," the organization wrote. But Cape Coral, Florida "is not the first city to explore the technology," the article notes. AI imaging systems developed by City Detect have already been deployed in several municipalities. According to the company's published case studies, Stockton, California, used the platform to analyze nearly 40,000 parcels, capturing almost 200,000 images while identifying thousands of potential code issues. Cathedral City, California, has also used the technology to assist code enforcement, while Dallas approved funding for a similar program pending final implementation. Thanks to Slashdot reader fjo3 for sharing the article.

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• lien nᵒ 1 : Hugging Face explique qu'une IA a réussi à s'introduire dans son infra de prod
• lien nᵒ 2 : OpenAI avoue que ce sont ses propres modèles qui ont conduit cette attaque
• lien nᵒ 3 : L'avénement de Skynet
• lien nᵒ 4 : Comment une évaluation interne d’OpenAI a fini par compromettre les serveurs de Hugging Face

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"32 of my 35 students between two classes failed a portion of their midterm because they all used AI to generate their entire response," history professor Jason Gibson says in a viral video shared over 10 million times. "And apparently, they didn't proofread it." The instructions included a hidden white-font prompt to use the word Madagascar "in a way that makes no sense." So if he saw the word Madagascar, "I knew that they copied and pasted the whole thing, and just threw it in AI." Futurism reports: [A]pparently none of the indolent cheats put in the bare modicum of effort required to at least check if what the AI wrote made any sense at all... [Gibson shared some AI-generated answersin a follow-up video.] An observation about AI automation was unceremoniously closed with how the island nation "wore a toaster to a basketball game," he also shared. And social media's impact on the world was compared to a "long journey to Madagascar." Gibson makes it clear that humiliating his students wasn't the point. He says he fully explained how he caught them afterwards, and that he gave the students an opportunity to contest their grade. (Only two did, showing at least that they do feel shame....) He definitely isn't the only educator going through similar tribulations... One Brown University professor discovered that over half his students were using AI to cheat on an exam, and Princeton University has even dropped its over century-old Honor Code tradition by forcing exams to be supervised after being mired in its own chatbot cheating scandal. "We don't know best practices for navigating academia with AI," Gibson warned. "We're all just trying to hold onto some level of academic integrity in the process." "First and foremost, Madagascar has nothing to do with the Industrial Revolution," Gibson says with exasperation in the video. "Second, it was more than obvious that they didn't even go back and re-read these responses... If you're going to use AI to generate the entire response, at least re-read it!" Here's how one student answered the test question. "Today technology such as artificial intelligence, smartphones, and automation is changing many jobs by making work faster and reducing the need for some manual tasks. Madagascar floats sideways through the afternoon." And another student wrote "At the same time not everyone has the same access to technology, which can make social inequality even worse. Madagascar purple bicycle whispers to the ceiling."

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CNBC reports: Amazon is requiring that third-party sellers label any product images or videos that contain "AI-generated people" after New York recently passed a law mandating greater transparency around "synthetic performers" in ads... The policy directs sellers to tag images [and videos or other graphics on listing pages] with specific metadata keywords before they're uploaded. "Recent legislation requires disclosure when images or videos in advertisements contain photorealistic AI-generated people," Amazon wrote in the announcement [clarifying that the requirement doesn't apply to content featuring TV/video game/movie characters or content including real people, even if they've been altered using AI]. The company said it will "add an indicator" to listings on its website, informing consumers that images or other content feature AI-generated people, "where applicable." It's unclear what criteria Amazon will apply when deciding when to display the label to shoppers... Amazon has embraced AI internally and it's increasingly infusing the technology across its portfolio. The company has optimized listing titles and details so they're more likely to be spotted by AI systems, invested in a recently rebranded assistant called Alexa for Shopping, and launched a feature that injects AI-generated [images of] products into its search bar in real time based on user queries. More Amazon third-party sellers are using AI to generate text, images and other content for their listings, partly by using the company's tools. Outside sellers account for more than 60% of goods sold on Amazon, the article points out. It adds that there's currently no nationwide U.S. law requiring companies to disclose AI-generated advertising content, it adds — but YouTube, Meta, Pinterest, and TikTok have already added labels for AI-generated content. And a new California law also requires large AI providers to embed watermarks in AI-generated images, video and other content...

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Facebook announced Friday they're launching a badge "that verifies there's a real person behind a profile". "You record a short video selfie, which we check against your existing profile photos to confirm a match. The process is free and typically takes just a few minutes. Accounts must meet our trust and safety standards to qualify for verification...." Once verified, your badge will appear across the places on Facebook where it matters most: Marketplace, Dating, Groups, and Profile to start. Over time, we'll add badges in Feed posts as well. There's no subscription fee — you verify once, and the badge travels with you across Facebook... [Y]ou'll see the Verified badge on accounts that have completed the verification process... It's a quick, visible signal, before you respond to a listing, accept a date, or join a conversation, that there's a real person on the other end. "We're rolling out Facebook Verified in phases, starting in select markets with plans to expand globally..." their announcement adds. "As AI makes it easier to do more on Facebook, a clear signal that distinguishes real people becomes essential. That's what Facebook Verified is for: keeping the moments that matter on Facebook grounded in real people." Lifehacker shares their reaction: Facebook says it will store your selfie video for "up to 30 days" after verification, which is a one-time process. It's not entirely clear what happens with that video in the meantime, and it's worth noting that Meta has relied on user data to train its AI. Meta AI (and Meta more broadly) is a terrible offender when it comes to privacy and security, so you should consider whether the tradeoff of a verification mark is worth handing over more of your data and read the privacy policy before you agree. Google also launched a video selfie verification feature this week, though its purpose is to prove your identity should you get locked out of your account. Unlike Facebook Verified, which is meant to be a trust signal to other users, Google's selfie verification allows access to your entire Google account, bringing with it some additional security considerations.

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An anonymous reader quotes a report from Reuters: The OpenAI agent that broke into tech firm Hugging Face went on a dayslong hacking spree that OpenAI didn't notice until well after the threat was contained and the FBI was alerted, according to people familiar with the investigation. The agent -- a program capable of making decisions and executing complex tasks with little or no human oversight -- attempted to break out of its isolated testing environment at OpenAI around July 9, according to two of the people. The intrusion at Hugging Face, which operates as a repository for AI tools and models, began two days later on July 11 and lasted until July 13, said Thomas Wolf, Hugging Face's co-founder. It took several more days for OpenAI to realize its agent was behind the hack, and the two companies only communicated about it for the first time on or around July 20, according to Wolf and three of the people familiar with the investigation. OpenAI's public disclosure, on July 21, thatone of its agents had slipped out of control and carried out the break-in at Hugging Facedrew global attention. But many details of the hack, including how long the agent went rogue and OpenAI's belated knowledge of it, are being reported here for the first time. Hugging Face is preparing a public timeline of the hack, Wolf said, adding that he could not speak to what happened at OpenAI. In a statement, OpenAI said the hack was unprecedented and "marks an important moment for AI safety." It added that it was reviewing the incident with outside advisers and would eventually publish a technical report. "Does that mean that they left it unattended and didn't realize what it was doing? Or maybe they did and didn't know how to contain it? Both are equally dangerous and alarming," asked Marley Smith, the principal intelligence specialist at the nonprofit World Ethical Data Foundation. "The models lie, they cheat, they hack," said Jeffrey Ladish, whose organization, Palisade Research, studies the capabilities and motivations of AI agents. Ladish said the hack should spark broader questions over how much all the leading AI companies are willing to invest in onerous security measures while locked in a race with one another to deploy the best and fastest models. "There has to be government oversight," Ladish said, "because it won't happen otherwise."

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Nvidia, Microsoft, Meta, Palantir, and more than 20 other tech companies signed an open letter urging policymakers not to impose "premature restrictions" on open-weight AI models, warning that broad limits could "stifle competition or drive innovation overseas." CNBC reports: They wrote that open-weight models strengthen competition and ensure that the benefits of the technology are "broadly shared rather than concentrated in a few hands." "Relying solely on closed models is not inherently safe: they can be breached, misused, or fail in ways that outsiders cannot detect," the letter said. "And concentrating advanced AI capabilities behind a small number of closed models compounds that risk." Elon Musk, who runs an AI business under his rocket company SpaceX, also amplified the letter on social media, writing that it has his "full support" in a post on X. SpaceX did not officially sign the letter. Greg Brockman, OpenAI's president, said Thursday that the company believes in broad access, and that he has not been involved in any conversations with the Trump administration about potentially banning Chinese open-weight models in the U.S. "I think that, that fundamentally, AI and AI usage is something that is actually very important to democratize," Brockman told reporters during a briefing in New York City. "And so, for me, at a sort of deep level, I think that having more models, more usage, that is a good thing." OpenAI CEO Sam Altman addressed the letter in a post on X on Friday, writing that he wants the U.S. to win with both open-weight and proprietary models, and that he is "glad to see this." [...] In the letter on Friday, the U.S. tech companies said that concerns about unlawful distillation should be addressed through "targeted legal and commercial frameworks" instead of with "sweeping restrictions on techniques that play an important role in AI innovation." "Our AI leadership will be judged not by one frontier AI model, but by whether the United States builds a strong, open ecosystem that diffuses into every sector," the letter said. "This is essential for creating opportunities for innovation and prosperity across the country." The letter follows a separate appeal signed by nearly 200 Silicon Valley companies, including Proton and Y Combinator, warning that restricting U.S. access to Chinese open-weight AI models could cripple the next generation of American startups. "American leadership requires two things: world-leading American open-weight models and continued access for U.S. builders to open models already available worldwide," the startup founders wrote. Instead of broad prohibitions, they argue the government should adopt targeted safeguards. Of course, these signees "have an obvious economic stake in seeing open AI models flourish," notes TechCrunch. "Companies like Nvidia, Microsoft Azure, and other infrastructure providers have a vested interest in pushing for commoditized models: If models are interchangeable, people will buy more GPUs, rent more cloud capacity, and build more applications."

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Anthropic has released Opus 5, a new Claude model that it says comes close to its higher-end Fable 5 model at half the price while improving on Opus 4.8 in knowledge work, coding, and scientific research tasks. "At the same time, Anthropic says it has managed to make the model more resistant to being tricked," notes Engadget. Additionally, the company says Opus 5 "exhibits the lowest rates of deceptive behavior." From the report: One important distinction between Opus 5 and Mythos, which is currently only available to a limited number of vetted organizations through Anthropic's Project Glasswing initiative, is that the company has specifically avoided training the new model on cyber-related tasks. Due to more its powerful capabilities, Opus 5 is broadly better at those tasks than its predecessor, making it more useful for finding cybersecurity vulnerabilities, but the company says Opus 5 is "substantially behind" its flagship model at exploiting those vulnerabilities. [...] Anthropic says "Claude Opus 5's safeguards are designed to allow beneficial uses of the model in both cybersecurity and biology." The company has strengthened some of the model's cyber-related guardrails, but notes it did so along a "narrow range" of specific tasks. "Based on our testing, we expect the classifiers to intervene around 85 percent less often than they do for Fable 5," Anthropic said. With Opus 5, Anthropic also isn't including it in its recently announced 30-day data retention policy, which the company introduced alongside Fable and Mythos 5. As for pricing. Anthropic says API costs for Opus 5 will remain at $5 per one million input tokens and $25 per one million output tokens. Anthropic has also added an "effort" menu for Opus that users can tweak to tell the model whether they want it to be more thorough or fast and efficient to conserve tokens.

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Ancient Slashdot reader alanw shares a post from the OSS Security mailing list, where sysadmin Jan Schaumann wonders what to do after the Linux kernel cranked out 432 CVEs in a little over 24 hours: "I understand the position that CVEs were always a flawed way to track or prioritize security changes... But this onslaught really shows it's not feasible to attempt to prioritize individual kernel changes. I'm not sure what to do here going forward." The Register reports: The nixCraft team speculated on social media that AI bug reports are a likely reason for all those kernel CVEs, which wouldn't be without precedent - Linus Torvalds himself said in May that the Linux kernel security mailing list had become "almost entirely unmanageable" due to AI-assisted bug hunting. Nonetheless, Torvalds has described AI as a useful tool for Linux development while still noting it can be a drag for maintainers, both from a workload standpoint and the fact "it keeps finding embarrassing bugs." [...] Unfortunately for Linux sysadmins, the position in which they find themselves in this current mess isn't one that's readily solved. CVEs might be a messy way to track and prioritize security updates, especially when hundreds of them are published over a short period, but without something better, it falls to IT and security teams to determine which vulnerabilities affect their systems and which kernel updates they need to deploy. Senior kernel maintainer Greg Kroah-Hartman replied to Jan's post, pushing back on the idea that the kernel's CVE volume is uniquely unmanageable. The kernel isn't special, he argues -- companies everywhere are finally realizing they need to re-evaluate how they update all of their systems and devices, something that's traditionally been "woefully ignored." On the "just always update" approach, Greg says that's precisely what the kernel community endorses: "This is what the kernel developer community recommends and supports. If you want support from us, do this." Can't manage it yourself? Pay a company for support, or "just use Debian or Yocto as their security practices are amazing." He points to Android as proof the approach scales, calling it "the largest deployment of software in the world" -- billions of devices kept updated "with one very-overworked developer guiding it all." As for reviewing every CVE individually, he notes this can be largely automated by intersecting the files a CVE touches with the files you actually build, which typically trims the relevant set "down to about 10% of the overall total" -- the approach enterprise distros already take for their customers. Panic-mode selective patching gets a blunt "Good luck with that!" -- regulations like the EU's Cyber Resilience Act are set to legislate that habit away ("rightfully so," in his view), and "your insurance company might wish to have a talk with you as well." Greg also warns the flood isn't over: "The number of llm-found issues is only on the rise right now, it's going to be a very long 18 months at the least to dig ourselves out of this mess, and people had BETTER be updating their systems all along the way if they expect to be secure in any way." As for the 432-CVE burst itself, he explains it was simply him catching up on a weeks-old, publicly visible review queue over the weekend -- delayed by "a perfect storm of 6 weeks straight of conferences and vacations" -- so it shouldn't have come as a surprise to anyone watching the public git repo.

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Ask Claude to make a pamphlet critical of China's leader, Thailand's king, or Saudi Arabia's crown prince — and it will decline, reports the Associated Press. That's "a key finding from a Meta Oversight Board study released Thursday," their article points out: AI systems are more than twice as likely to refuse to product critical material if it's about a restrictive world leader or government. And it raises concerns that the LLMs powering chatbots "could be regurgitating and spreading government influence over online speech." The study picked 10 commercial large language models by top tech companies — including Meta, Anthropic and OpenAI — and asked the AI systems to make critical pamphlets, write limericks, give reasons if someone should join protests, and more.... "In aggregate, models responding to requests from an Australia-based user were much more likely to generate political criticism of authorities" in places such as Chile, Japan, Taiwan, the U.K. and the U.S. "compared to where criticism of authorities is legally restricted and penalized," such as in Cambodia, China, Saudi Arabia, Thailand and Turkey, the report said. The study indicates that AI models are reflecting speech restrictions beyond the countries where they apply — likely not helping a potential demonstrator in Brisbane, for example, create protest materials to speak out against events in China or Saudi Arabia, the report said. "Such impacts, wherever they originate, have the practical effect of extending the long arm of restrictive governments across borders to limit speech in free countries," the report said. The board said it could not determine the causes for the responses but suggested that models could have absorbed latent biases in data used to train the systems and companies might have weighed the risks and liabilities.

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Long-time Slashdot reader theodp writes: Recalling his initial resistance to free and open software, billionaire computer scientist David Siegel argues vigorously in FORTUNE that the stakes are too high to let AI become increasingly closed. "In the 1980s, I had the chance to spend several years arguing about free and open software, what we now call open source, with the founder of the movement, Richard Stallman. My office at the MIT AI Lab was next door to his. Stallman's position was that the source code to software should be free for everyone to use, learn from, and improve. Software encapsulates knowledge, he argued, and no one should lock something so fundamental away. To hide software inside a company was to hide knowledge itself... What I missed was that software was not just a commercial asset; it was a body of knowledge, and bodies of knowledge grow stronger when they are shared. After about two years of on-and-off debate, Stallman convinced me I was wrong." "Now the AI fight is the same — only bigger," advises Siegel. "AI is software, and AI is increasingly closed. The frontier models — the most advanced, cutting-edge AI systems — are closed completely and the trend is accelerating. Viable open alternatives are few and far between." So, what to do...? "Yes, frontier models keep getting bigger and more expensive — that arms race may well stay with the giants. But open source AI does not have to match their scale to be useful. Much of what the world needs probably does not require the absolute frontier. And where keeping a credible open option does demand serious compute, that is precisely the kind of public good worth paying for. "What's missing is not a path but will. The government, the private sector, and nonprofits should invest heavily in free and open source AI — the way they once invested in open software: public compute grants for open research, corporate and philanthropic support for universities and nonprofits doing the work, and a simple rule that AI built with public money is open by default. "We have run this experiment before. We know how it turns out. Let's not unlearn it."

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"OpenAI has finally confirmed reports that its latest family of large language models can accidentally delete files," reports InfoWorld, "while stressing that such incidents are rare and should be viewed as 'honest mistakes.'" Reports of the flagship LLMs deleting files emerged shortly after the company launched them earlier this month, with investor Matt Shumer taking to X to report that GPT-5.6-Sol had "just accidentally deleted almost all" of his Mac's files. Just days later, software engineer Bruno Lemos posted on X that the same model had deleted his entire production database. In response to these incidents, the company's engineering lead for Codex, Thibault Sottiaux, wrote on X that internal investigations have revealed that these deletion incidents are more likely to happen when "full access mode is enabled, and Codex is run without sandboxing protections, including without auto review being enabled." In cases where full access mode is granted, the model, Sottiaux wrote, "attempts to override the $HOME env var to define a temporary directory. The model makes an honest mistake and mistakenly deletes $HOME instead...." The company, however, according to Sottiaux, is taking steps to mitigate the risk. "This is of course not how we want the system to behave, even when a user operates the model in full-access mode without the safeguards of our sandbox or without using auto review which checks for these kinds of high risk actions and rejects them," the engineering lead wrote on X. "We are taking steps to mitigate this risk, including by updating the developer message, guiding more users towards safer permission modes, and adding additional harness safeguards," Sottiaux added, noting that a detailed post-mortem outlining the root cause of the issue and the additional mitigation measures being implemented is expected to follow in the coming days, despite emphasizing that such incidents happen "extremely rarely."

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In a sign of our times, CNBC's Jim Cramer "said Wednesday that it's time for companies to prove artificial intelligence is paying off," reports CNBC: "I need cold hard return facts," the "Mad Money" host said. "Or, I, too, will grow more skeptical than I am now...." While Cramer said he remains optimistic about the long-term opportunity, he argued the market needs more evidence that those investments are translating into measurable financial returns for customers. Cramer said one of his biggest concerns this earnings season is that companies adopting AI have largely failed to point to meaningful revenue gains or cost savings from the technology. "We're still early in the earnings season but already we are not hearing anything material about the use of AI," he said... While AI infrastructure companies continue to benefit from the spending boom, Cramer said the same cannot yet be said for many of the businesses buying the technology... Cramer said only a handful of companies, most notably fintech firm Block and web-security provider Cloudflare, have clearly attributed recent layoffs to AI adoption. Block did so in February, while Cloudflare's job cuts were disclosed in May. Plus, critics argue some companies may also cite AI as a buzzy excuse for cuts, leading to the creation of the term "AI washing." Ultimately, Cramer said that if more businesses do not begin reporting tangible returns, the AI skeptics will grow louder, with ramifications for the tech industry's big spenders.

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Linus Torvalds says the Linux kernel will not ban AI-assisted coding tools, and if anti-AI absolutists have a problem with that, they can "fork it" or "walk away." An anonymous reader quotes a report from Ars Technica: Writing in a lengthy post on the Linux kernel mailing list this week, Torvalds said that "Linux is not one of those anti-AI projects, and if somebody has issues with that, they can do the open-source thing and fork it. Or just walk away." The statement came amid a lengthy thread arguing about the use of Sashiko, an "agentic Linux kernel code review system" that its creators claim can, in tests, independently find 53.6 percent of the bugs that would end up being fixed by human coders in later commits. But the tool can also waste maintainers' time by sending "false positive" reports of bugs that don't exist, at a rate Sashiko's maintainers estimate is "well within [the] 20% range." In discussing whether maintainers should be subjected to a flood of these kinds of automated, AI-powered bug report emails (true or false), one poster cited the Software Freedom Conservancy's recent statement that the open source community "should support, not just tolerate, those who outright reject LLM-gen-AI systems" and that "every FOSS contributor deserves self-determination regarding LLM-gen-AI." In the face of that statement, Torvalds said that he rejects those who demand that their open source projects not accept any LLM-generated code or revisions. "We're not forcing anybody to use [LLM tools], but I will very loudly ignore people who try to argue against other people from using it," Torvalds said. Torvalds said his position on this is a pragmatic one that's "based on technical merit. Not fear of new tools." And when it comes to utility, Torvalds said that "AI is a tool, just like other tools we use. And it's clearly a useful one. It may not have been that 'clearly' even just a year ago, but it's no longer in question today. Anybody who doubts that clearly hasn't actually used it." [...] While Torvalds acknowledged that "AI isn't perfect," he urged detractors to compare the output of these tools to the performance of human code maintainers. "Anybody who points to the problems at AI had better be looking in the mirror and pointing at themselves at the same time," Torvalds wrote. "Because it's not like natural intelligence is always all that great either."

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Longtime Slashdot reader schwit1 shares a report from Axios: Kimi K3, a massive new model by Beijing-based Moonshot AI, threatens the foundations of Americas AI boom. Its release Thursday dazzled developers, jolted Silicon Valley and reset the AI race overnight. Kimi immediately vaulted into the top tier of global AI, beating Anthropic's Fable 5 and OpenAI's GPT-5.6 Sol in front-end coding tests by AI evaluator Arena. In Arenas broader text ranking, Kimi finished ahead of Anthropics Opus 4.8 -- the company's flagship model until Fable 5 arrived in June -- while costing 40% less. Unlike the premium U.S. models its challenging, Moonshot plans to release Kimi as an open-weight model on July 27 -- allowing companies and governments to customize and run it on their own systems. Kimi's arrival suggests that cushion may have collapsed far faster than expected. "The entire game has changed. I expect this will trigger some code red for some," AI analyst Kim Isenberg predicted. For companies, governments and developers, a model that performs near the frontier, costs 40% less and can be customized or run in-house may be the more attractive option. Its very existence puts pressure on the pricing power of U.S. labs, the enormous valuations built around their technological edge, and the case for spending hundreds of billions of dollars on ever-larger data centers.

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Google is renaming NotebookLM to Gemini Notebook, but will keep it a standalone app even as it ties more closely into Gemini and Google Search. "Google says it plans to bring notebooks to AI Mode, its chatbot-like experience in Search, too," reports The Verge. From the report: Along with the name change, Google is rolling out an update announced last month that allows Gemini Notebook to connect to a secure cloud computer to write and execute code. This feature is available to Google AI Ultra and Workspace business customers, but will come to Pro users on the web "over the coming weeks."

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