Claude is exposing a wealth of users’ chats and creations in Google search results, meaning anyone can dig through conversations or other material that people used Claude to make but may not have realized were publicly available for strangers to see. The exposed data includes an AI-powered therapy app that someone appears to have vibe-coded, notes on meetings, and a dashboard someone made apparently to analyze medical billing data. Exposed chats reportedly include private cryptocurrency wallet keys and personal information like peoples’ addresses

Like other chatbots, Claude lets people share their conversations with others by creating a publicly accessible link of the chat. People may do this to send the full text of a conversation to their friends or coworkers in a group chat, for example. But they may not realize Google is also surfacing these links in search results, making them available to essentially anyone. […] Claude users can change their privacy and sharing settings to make their chats no longer publicly accessible.

The Content Creation BA is housed within ASU’s Walter Cronkite School of Journalism and Mass Communication and appears in the university’s 2026-2027 course catalog. The 120-credit-hour degree prepares students to become “an influencer and strategic storyteller” by teaching video production, podcasting, personal branding, audience analytics and social media strategy. The program was approved by the ASU University Senate in March 2026. Its proposal said graduates would be prepared to work independently as influencers and content creators across livestreaming, videography, writing, podcasting, graphics and emerging media.

[…] For the program’s final project, students will choose a social media platform, such as TikTok, create a content and growth strategy, and attempt to gain real followers throughout the semester. “They will have demonstrable audience growth,” [explained Jessica Pucci, senior associate dean at the Cronkite School]. “They will have a platform of their choice with real content and real followers and a real audience behind them.” The curriculum includes courses titled How to Become an Influencer, On-Camera Presence, Introduction to Editing, Videography, Podcasting and Audio Storytelling, Social Media Foundations and The Digital Audience.

One possibility lies deep within Earth itself. The planet’s mantle is constantly circulating through convection, albeit at an almost unimaginably slow pace. Periodic changes in mantle convection, or the initiation of mantle plumes, could influence volcanism, plate tectonics, mountain building, and other large-scale geological processes. Because these systems are closely interconnected, disturbances originating deep within Earth could eventually ripple through the planet’s surface, oceans, climate, and biosphere.

Another hypothesis focuses on interactions between Earth’s surface and interior. Long-term orbital variations influence climate and sea level, periodically redistributing enormous amounts of water, ice, and sediment across the planet. [New York University geologist Michael Rampino] discusses the possibility that these changing surface loads subtly modify stresses within Earth’s crust and upper mantle, potentially influencing tectonic and volcanic activity over geological timescales.

Rampino also considers possible influences beyond Earth, an idea he has been weighing up since the 1980s. As the Solar System orbits the center of the Milky Way, it oscillates above and below the galaxy’s mid-plane, with the timing of these passages aligning with that of Earth’s major upheavals. These crossings, other researchers have suggested, could also gravitationally perturb comets in the distant Oort Cloud, increasing the likelihood of large asteroid impacts.

Another, even more speculative, hypothesis suggests that if dark matter is concentrated near the galactic plane, a fraction of it could occasionally be captured by Earth. Over millions of years, this process could generate small amounts of internal heat, potentially influencing geological activity. At present, however, there is no direct evidence supporting either mechanism, so they remain very controversial.

Large asteroid impacts are discussed separately in the paper. Although they were not included in the statistical analysis of the 89 geological events, the timing of several of Earth’s largest known impact craters appears broadly consistent with the proposed 27.5-million-year rhythm, as Rampino has discussed in earlier papers. Rampino suggests this correspondence may warrant further investigation, but stops short of claiming a causal relationship.

One missing underscore in a Skyrim-themed username put an innocent Nova Scotia man in prison for 18 months. A 2018 child-luring investigation, which began in Madison, Wisconsin, and eventually extended to Halifax, Canada, was based on a false premise. Police were looking for a man using the Kik messaging service under the name “fus__ro_dah” (two underscores after “fus”), but they accidentally requested records for the username “fus_ro_dah” (one underscore after “fus”). This one-character difference led them not to the perpetrator but to a Canadian man named Brandon Klayme. (Ars readers may recognize “fus ro dah” as the Unrelenting Force “dragon shout" from The Elder Scrolls V: Skyrim.)

Despite finding no evidence of the crime on his digital devices, Canadian police arrested Klayme in 2020 on child sex abuse charges. He was convicted after a trial in 2023 and sentenced in 2024 to 18 months in prison. He served the full term. Even after release, Klayme continued to fight his conviction. In the process of preparing his appeal, the username mistake that led to all these years of disruption was finally discovered. On Thursday, the Nova Scotia Court of Appeal overturned Klayme’s conviction, writing: “Mr. Klayme is factually innocent of the offences. He should never have been charged, let alone convicted.” […] As the court puts it, “Although the information about the usernames was available at the time of the trial, there is no evidence confirming or explaining how it went unnoticed.”

Peacock has 48 million subscribers, while YouTube Premium and YouTube Music have a combined 125 million subscribers, though they don’t break out how many each of those offerings have. The agreement, which expands on the deal the company inked with YouTube parent company Google last year, will also extend the entertainment company’s programming deal with YouTube TV, while bringing some of YouTube’s offerings to Comcast Xfinity and Xumo platforms.

There’s also a notable sports and production element to the deal, with NBC Sports agreeing to stream some live sporting events on its YouTube channels, and with NBC agreeing to serve as the production partner for select live events on YouTube. YouTube will also bundle some of the company’s International streaming offerings like Universal+ and Hayu in select markets.

Advanced Television points out that the FCC application also includes a request to use spectrum assigned to Iridium’s satellite network outside the US, even as Rocket Lab is in the process of acquiring Iridium with plans to expand.

The new constellation and direct-to-device service will “complement” the broadband services Amazon also plans to offer through its Leo platform. In addition to consumer satellite service, it would also be used for things like disaster response and emergency messaging.

Amazon says the new direct-to-device satellites “will process the signals in orbit before relaying them to improve performance.” The new constellation will be nearly double the size of Amazon’s initial Leo constellation, which is planned to include around 3,200 satellites. As of July 2nd, Amazon says “over 375” of those satellites have launched so far.

Nvidia and a large group of technology, cybersecurity, and enterprise software companies have launched new initiative aimed at developing and sharing open source tools, models, and techniques for securing AI systems and agents. The new Open Secure AI Alliance aims to give defenders more open tools for testing, auditing and protecting AI models and agents. Nvidia points to the recent security incident involving OpenAI and Hugging Face, noting that when closed AI tools could not differentiate between attackers and defenders and blocked forensic work, Hugging Face used the open-weight GLM 5.2 model on its own systems to review over 17,000 actions and contain the breach.

Community-led open source project hosting site Codeberg has formally announced that projects whose code is largely or fully machine-generated through LLMs and other ‘AI’ tools will no longer be welcome. This follows on the heels of a similar ban on cryptocurrency-related projects. The community vote was on two issues, the first being the notion that scraping of project code for the use in LLMs should be forbidden, which was a motion that easily passed. The second motion was on disallowing projects whose code was substantially generated by LLMs like Claude, OpenAI Codex, and similar. This motion passed with 358 in favor versus 144 against.

In the earlier linked blog post the reasoning behind especially this second issue is expanded upon, covering not only “license whitewashing,” but also the direct and indirect hardware costs, with the expanding ‘AI’ datacenter hyperscaling having massively increased hardware costs for Codeberg over the past years, as the costs have been largely externalized. Also covered is the aspect of these LLM-based tools destroying the OSS community, which is something that is backed up by recent studies.

The Information didn’t name the manufacturer, but its sources described the operation as having pulled DUV development teams from several Chinese companies, one of them the state-backed startup Shanghai Yuliangsheng Technology. SMIC has been testing a Yuliangsheng immersion tool since September 2025. Most components in the new systems are domestic, though some critical parts still come from Japan, and delays at local suppliers have held back output this year.

[…] China accounts for around 20% of ASML’s net sales this year, down from 33% in 2025, driven mainly by mainstream logic demand… Independent analysis from the AI Futures Project in June put commercial-scale Chinese immersion DUV in the mid-2030s, with ASML holding 98.7% of the immersion market. Qualifying the new machines for production lines could take many months, and they trail ASML’s tools on performance and build quality. China’s domestic EUV effort, which Reuters first reported as a working prototype in December, remains years away.

OpenAI’s ChatGPT is now refusing requests to generate text that directly mimics the style of famous authors. When asked to do so, the popular LLM instead offers a response that draws on the “broad qualities” of those authors “while remaining distinct in its own voice,” for example. This morning, Ars received the following response to a test prompt asking for a story introduction in the style of Stephen King: “I can definitely write with the hallmarks of atmospheric, character-driven horror and small-town dread, but I can’t write in Stephen King’s exact style or closely imitate his distinctive voice. Here’s an original opening that captures a similar feeling while remaining its own…”

In testing, ChatGPT generated similar dodges for other authors both living (J.K. Rowling, Amy Tan) and dead (Charles Dickens, Ernest Hemingway). An analysis published by No Latency earlier this month (PDF) found the same behavior for living authors but found ChatGPT complied with style-copying requests for deceased authors. In refusing to directly copy the “exact style” of various authors, ChatGPT offered instead to capture an overall “feeling” by incorporating some of the common features found in those authors’ work. That may seem like a distinction without a real difference at first glance. But the slight alteration could be legally important as OpenAI continues to fight a number of lawsuits brought by book authors alleging large-scale copyright infringement by models trained on their work. One of those suits specifically cites ChatGPT’s “uncanny ability to generate text similar to that found in copyrighted textual materials,” for instance. An OpenAI spokesperson did not respond to a request for comment from Ars Technica.

In the US, copyright law generally protects only a specific expression of an idea, not the more intangible style of an author. But an AI-generated stylistic imitation could become infringing if it becomes “substantially similar” to the work of the original author. “We’ve never had a situation in which this personal style of individual creators could be imitated as well and as inexpensively as we now have with AI,” George Washington University Law School Professor Robert Brauneis told Bloomberg Law.

If the bubble deflates the way you expect (write-downs, too much compute supply, possibly OpenAI cratering), can you walk us through what that would actually look like for Apple? Does anything break for iPhone users, or does Apple mostly watch it happen from the sidelines? Could it even benefit Apple?

I think things would look much the same for Apple. I think they will sit on the sidelines and watch everything burn. I could see them doing some choice acquisitions as things begin to collapse, but I could also see them do nothing.

I think Apple is in a very weird place at the moment. The Vision Pro was a dud, but it was also the most interesting and future-forward thing I’ve seen anyone put out in a while. If they were smart, they’d tread water and sink as much money into making that as small as humanely possible — no matter how long it takes — because the entire AI bubble is a result of everybody running out of hypergrowth ideas, mostly because we’re flat out of new interfaces.

I want to be clear that what they want to do with the Vision Pro requires it to basically be weightless and invisible and never need adjustments. When it works, it’s genuinely awesome. But that’s a load-bearing when. One slight movement means the whole thing goes out of focus. I can’t even use mine anymore because it needs an update that requires you to wear the thing the whole time. So much promise, released too early, shoved out the door by a CEO on his way out.

In recent years, social media companies shut down public access tools like Meta’s CrowdTangle and replaced them with content libraries, or, like X, paywalled their API data, forcing academics to pay “hundreds of dollars a month,” said Duncan Allen, a research officer at Democracy Reporting International (DRI) in Germany. Researchers say that without API access, what Iamnitchi describes as the “black holes” in what society knows about how these platforms recommend content or handle reports regarding sensitive content will only grow. Others, like TikTok, cap how many posts any researcher account can pull each day, which Allen said can make it “impossible to study anything at scale.”

The DSA was meant to solve this by allowing vetted researchers at credible institutions to have access to API data if they could show it would help in studying systemic risks, from illegal content to threats to fundamental rights. But two years after the law took effect, researchers say they struggle to meet its security requirements and face narrow interpretations from platforms of what qualifies as a systemic risk. Application forms differ by platform, but most require data to be stored on infrastructure that cannot be compromised — such as a machine physically disconnected from the Internet — a resource most universities lack, [said Adriana Iamnitchi, chair of computational social sciences at Maastricht University in the Netherlands, who leads research into online disinformation campaigns.]

Even for researchers who secure approval, “there’s no guarantee that the data is good,” said L. K. Seiling, coordinator of the DSA40 Collaboratory, a German initiative that tracks 46 DSA applications. API data is often difficult for a colleague to reproduce, so a researcher’s work cannot be checked for errors, which Iamnitchi said is a “basic requirement of science.” DSA40 data shows that of 46 tracked applications, 20 were approved and 14 rejected. But approval rates vary widely: TikTok approved 11 of 13 applications, while X rejected 11 of 23. The true rejection rate is likely higher because the tracker relies on voluntary reporting, Seiling said. “There’s no structured advantage for researchers to use this pathway,” Seiling said. “Data access as it’s set up right now tries to disincentivize researchers.”

Nvidia is in talks to provide roughly $250 billion in financing guarantees for OpenAI as part of a massive data center project, the Wall Street Journal reported on Sunday. The backstop from Nvidia would help the ChatGPT maker lease a 10-gigawatt project that SoftBank’s energy subsidiary is developing in southern Ohio, the newspaper said, citing people familiar with the matter. For OpenAI, a deal would be the first step toward controlling its own infrastructure instead of renting it from Microsoft, Amazon, and Oracle, while for Nvidia, it would guarantee demand for its chips for years to come.

The project is expected to cost more than $500 billion in total, including the chips inside the data center, according to the WSJ. The $250 billion guarantee covers the data center lease and debt financing, but would not cover the Nvidia chips inside the center, the WSJ said, adding that the chipmaker was also discussing financing OpenAI’s chip purchases worth up to $350 billion. Nvidia’s backing would support financing vehicles aimed at reassuring lenders about the project’s funding, the report added. The first phase of the project is expected to be finished in 2028, with around 800 megawatts of power, the Journal said.

A patch series that appears destined for the upcoming Linux 7.3 merge window is what’s dubbed the “KVM Chainsaw” as a major code clean-up in dealing with the kvm_mmu “god data structure”. Red Hat engineer and KVM maintainer Paolo Bonzini has merged the kvm-chainsaw branch to KVM’s “next” Git branch. With this KVM Chainsaw work now in the next branch, it should be submitted for the upcoming Linux 7.3 cycle.

The KVM Chainsaw work deals with the kvm_mmu structure being overloaded with multiple uses and splits it down into three parts for better handling current KVM usage. Paolo explains of KVM Chainsaw with the merge to the KVM.git next branch:

“The kvm_mmu is a “god data structure” that includes three different tasks: describing the guest page table’s format, walking the guest page tables and building the page tables. This means that the (already poorly named) nested_mmu is only used in part, since it has no page tables to construct. Furthermore, some parts are reused across guest and host page tables (such as the reserved bits detector) but others are not; for example permission_fault is replaced by simplified code such as is_executable_pte().

This series cleans this up by splitting kvm_mmu in three parts…