An anonymous reader quotes a report from Wired: [P]erhaps AI can, in fact, learn in a more human way -- by figuring out interesting questions to ask itself and attempting to find the right answer. A project from Tsinghua University, the Beijing Institute for General Artificial Intelligence (BIGAI), and Pennsylvania State University shows that AI can learn to reason in this way by playing with computer code. The researchers devised a system called Absolute Zero Reasoner (AZR) that first uses a large language model to generate challenging but solvable Python coding problems. It then uses the same model to solve those problems before checking its work by trying to run the code. And finally, the AZR system uses successes and failures as a signal to refine the original model, augmenting its ability to both pose better problems and solve them. The team found that their approach significantly improved the coding and reasoning skills of both 7 billion and 14 billion parameter versions of the open source language model Qwen. Impressively, the model even outperformed some models that had received human-curated data. [...] A key challenge is that for now the system only works on problems that can easily be checked, like those that involve math or coding. As the project progresses, it might be possible to use it on agentic AI tasks like browsing the web or doing office chores. This might involve having the AI model try to judge whether an agent's actions are correct. One fascinating possibility of an approach like Absolute Zero is that it could, in theory, allow models to go beyond human teaching. "Once we have that it's kind of a way to reach superintelligence," [said Zilong Zheng, a researcher at BIGAI who worked on the project].

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Experts interviewed by NBC News warn that the rapid spread of AI-generated images and videos is accelerating an online trust breakdown, especially during fast-moving news events where context is scarce. From the report: President Donald Trump's Venezuela operation almost immediately spurred the spread of AI-generated images, old videos and altered photos across social media. On Wednesday, after an Immigration and Customs Enforcement officer fatally shot a woman in her car, many online circulated a fake, most likely AI-edited image of the scene that appears to be based on real video. Others used AI in attempts to digitally remove the mask of the ICE officer who shot her. The confusion around AI content comes as many social media platforms, which pay creators for engagement, have given users incentives to recycle old photos and videos to ramp up emotion around viral news moments. The amalgam of misinformation, experts say, is creating a heightened erosion of trust online -- especially when it mixes with authentic evidence. "As we start to worry about AI, it will likely, at least in the short term, undermine our trust default -- that is, that we believe communication until we have some reason to disbelieve," said Jeff Hancock, founding director of the Stanford Social Media Lab. "That's going to be the big challenge, is that for a while people are really going to not trust things they see in digital spaces." Though AI is the latest technology to spark concern about surging misinformation, similar trust breakdowns have cycled through history, from election misinformation in 2016 to the mass production of propaganda after the printing press was invented in the 1400s. Before AI, there was Photoshop, and before Photoshop, there were analog image manipulation techniques. Fast-moving news events are where manipulated media have the biggest effect, because they fill in for the broad lack of information, Hancock said. "In terms of just looking at an image or a video, it will essentially become impossible to detect if it's fake. I think that we're getting close to that point, if we're not already there," said Hancock. "The old sort of AI literacy ideas of 'let's just look at the number of fingers' and things like that are likely to go away." Renee Hobbs, a professor of communication studies at the University of Rhode Island, added: "If constant doubt and anxiety about what to trust is the norm, then actually, disengagement is a logical response. It's a coping mechanism. And then when people stop caring about whether something's true or not, then the danger is not just deception, but actually it's worse than that. It's the whole collapse of even being motivated to seek truth."

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Intel CEO Lip-Bu Tan says the company is "going big time" into its 14A (1.4nm-class) process, signaling confidence in yields and hinting at at least one external foundry customer. Tom's Hardware reports: Intel's 14A is expected to be production-ready in 2027, with early versions of process design kit (PDK) coming to external customers early this year. To that end, it is good to hear Intel's upbeat comments about 14A. Also, Tan's phrasing 'the customer' could indicate that Intel has at least one external client for 14A, implying that Intel Foundry will produce 14A chips for Intel Products and at least one more buyer. The 14A production node will introduce Intel's 2nd Generation RibbonFET GAA transistors; 2nd Gen BSPDN called PowerDirect that will connect power directly to source and drain of transistors, enabling better power delivery (e.g., reducing transient voltage droop or clock stretching) and refined power controls; and Turbo Cells that optimize critical timing paths using high-drive, double-height cells within dense standard cell libraries, which boost speed without major area or power compromises. Yet, there is another aspect of Intel's 14A manufacturing process that is particularly important for the chipmaker: its usage by external customers. With 18A, the company has not managed to land a single major external client that demands decent volumes. While 18A will be used by Intel itself as well as by Microsoft and the U.S. Department of Defense, only Intel will consume significant volumes. For 14A, Intel hopes to land at least one more external customer with substantial volume requirements, as this will ensure that Intel will recoup its investments in the development of such an advanced node.

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Microsoft is testing a new Windows policy that lets IT administrators uninstall Microsoft Copilot from managed devices. The change rolls out via Windows Insider builds and works through standard management tools like Intune and SCCM. BleepingComputer reports: The new policy will apply to devices where the Microsoft 365 Copilot and Microsoft Copilot are both installed, the Microsoft Copilot app was not installed by the user, and the Microsoft Copilot app was not launched in the last 28 days. "Admins can now uninstall Microsoft Copilot for a user in a targeted way by enabling a new policy titled RemoveMicrosoftCopilotApp," the Windows Insider team said. "If this policy is enabled, the Microsoft Copilot app will be uninstalled, once. Users can still re-install if they choose to. This policy is available on Enterprise, Pro, and EDU SKUs. To enable this policy, open the Group policy editor and go to: User Configuration -> Administrative Templates -> Windows AI -> Remove Microsoft Copilot App."

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An anonymous reader quotes a report from Ars Technica: Search engine optimization, or SEO, is a big business. While some SEO practices are useful, much of the day-to-day SEO wisdom you see online amounts to superstition. An increasingly popular approach geared toward LLMs called "content chunking" may fall into that category. In the latest installment of Google's Search Off the Record podcast, John Mueller and Danny Sullivan say that breaking content down into bite-sized chunks for LLMs like Gemini is a bad idea. You've probably seen websites engaging in content chunking and scratched your head, and for good reason -- this content isn't made for you. The idea is that if you split information into smaller paragraphs and sections, it is more likely to be ingested and cited by gen AI bots like Gemini. So you end up with short paragraphs, sometimes with just one or two sentences, and lots of subheads formatted like questions one might ask a chatbot. According to Google's Danny Sullivan, this is a misconception, and Google doesn't use such signals to improve ranking. "One of the things I keep seeing over and over in some of the advice and guidance and people are trying to figure out what do we do with the LLMs or whatever, is that turn your content into bite-sized chunks, because LLMs like things that are really bite size, right?" said Sullivan. "So... we don't want you to do that." The conversation, which begins around the podcast's 18-minute mark, goes on to illustrate the folly of jumping on the latest SEO trend. Sullivan notes that he has consulted engineers at Google before making this proclamation. Apparently, the best way to rank on Google continues to be creating content for humans rather than machines. That ensures long-term search exposure, because the behavior of human beings -- what they choose to click on -- is an important signal for Google.

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Longtime Slashdot reader chicksdaddy writes: CES, the Consumer Electronics Show, isn't just about shiny new gadgets. As AP reports, this year brought back the fifth annual Worst in Show anti-awards, calling out the most harmful, wasteful, invasive, and unfixable tech at the Las Vegas show. The coalition behind the awards -- including Repair.org, iFixit, EFF, PIRG, Secure Repairs, and others -- put the spotlight on products that miss the point of innovation and make life worse for users. 2026 Worst in Show winners include: Overall (and Repairability): Samsung's AI-packed Family Hub Fridge -- over-engineered, hard to fix, and trying to do everything but keep food cold. Privacy: Amazon Ring AI -- expanding surveillance with features like facial recognition and mobile towers. Security: Merach UltraTread treadmill -- an AI fitness coach that also hoovers up sensitive data with weak security guarantees, including a privacy policy that declares the company "cannot guarantee the security of your personal information" (!!). Environmental Impact: Lollipop Star -- a single-use, music-playing electronic lollipop that epitomizes needless e-waste. Enshittification: Bosch eBike Flow App -- pushing lock-in and digital restrictions that make gear worse over time. "Who Asked For This?": Bosch Personal AI Barista -- a voice-assistant coffee maker that nobody really wanted. People's Choice: Lepro Ami AI Companion -- an overhyped "soulmate" cam that creeps more than it comforts. The message? Not all tech is progress. Some products add needless complexity, threaten privacy, or throw sustainability out the window -- and the industry's watchdogs are calling them out.

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Valve has added the NTSYNC kernel driver to the SteamOS 3.7.20 beta, laying the groundwork for improved Windows game synchronization performance via Wine and Proton. Phoronix reports: For gearing up for that future Proton NTSYNC support, SteamOS 3.7.20 enables the NTSYNC kernel driver and loads the module by default. Most Linux distributions are at least already building the NTSYNC kernel module though there's been different efforts on how to handle ensuring it's loaded when needed. The presence of the NTSYC kernel driver is the main highlight of the SteamOS 3.7.20 beta now available for testing.

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An anonymous reader quotes a report from TorrentFreak: Italy's communications regulator AGCOM imposed a record-breaking 14.2 million-euro fine on Cloudflare after the company failed to implement the required piracy blocking measures. Cloudflare argued that filtering its global 1.1.1.1 DNS resolver would be "impossible" without hurting overall performance. AGCOM disagreed, noting that Cloudflare is not necessarily a neutral intermediary either. [...] "The measure, in addition to being one of the first financial penalties imposed in the copyright sector, is particularly significant given the role played by Cloudflare" AGCOM notes, adding that Cloudflare is linked to roughly 70% of the pirate sites targeted under its regime. In its detailed analysis, the regulator further highlighted that Cloudflare's cooperation is "essential" for the enforcement of Italian anti-piracy laws, as its services allow pirate sites to evade standard blocking measures. Cloudflare has strongly contested the accusations throughout AGCOM's proceedings and previously criticized the Piracy Shield system for lacking transparency and due process. While the company did not immediately respond to our request for comment, it will almost certainly appeal the fine. This appeal may also draw the interest of other public DNS resolvers, such as Google and OpenDNS. AGCOM, meanwhile, says that it remains fully committed to enforcing the local piracy law. The regulator notes that since the Piracy Shield started in February 2024, 65,000 domain names and 14,000 IP addresses were blocked.

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An anonymous reader shares a report: Microsoft is celebrating the resurgence of interest in physical media in the only way it knows how... by halting the Windows Media Player metadata service. Readers of a certain vintage will remember inserting a CD into their PC and watching Windows Media Player populate with track listings and album artwork. No more. Sometime before Christmas, the metadata servers stopped working and on Windows 10 or 11, the result is the same: album not found. We tried this out at Vulture Central on some sacrificial Windows devices that had media drives and can confirm that a variety of compact discs were met with stony indifference. Some 90s cheese that was successfully ripped (for personal use, of course) decades ago? No longer recognized. A reissue of something achingly hip? Also not recognized.

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The abstract of a paper on NBER: School boards have statutory authority over most elementary and secondary education policies, but receive little attention compared to other actors in education systems. A fundamental challenge to understanding the importance of boards is the absence of data on the policy goals of board members -- i.e., their ideologies -- forcing researchers to conduct tests based on demographic and professional characteristics -- i.e., identities -- with which ideology is presumed to correlate. This paper uses new data on the viewpoints and policy actions of school board members, coupled with a regression discontinuity design that generates quasi-random variation in board composition, to establish two results. The first is that the priorities of board members have large causal effects across many domains. For example, the effect of electing an equity-focused board member on test scores for low-income students is roughly equivalent to assigning every such student a teacher who is 0.3 to 0.4 SDs higher in the distribution of teacher value-added. The second is that observing policy priorities is crucial. Identity turns out to be a poor proxy for ideology, with limited governance effects that are fully explained by differences in policy priorities. Our findings challenge the belief that school boards are unimportant, showing that who serves on the board and what they prioritize can have far-reaching consequences for students.

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Microbiology had its golden age in the late nineteenth century, when researchers identified the bacterial causes of tuberculosis, cholera, typhoid, and a dozen other diseases in rapid succession. Antibiotics had theirs in the mid-twentieth century. Both booms eventually slowed. Vaccine development, by contrast, appears to be speeding up -- and the most productive era may still lie ahead, Works in Progress writes in a story. In the first half of the 2020s alone, researchers delivered the first effective vaccines against four different diseases: Covid-19, malaria, RSV and chikungunya. No previous decade matched that output. The acceleration rests on infrastructure that took two centuries to assemble. Edward Jenner's 1796 smallpox vaccine was a lucky accident he didn't understand. Louis Pasteur needed ninety years to turn that luck into systematic methods -- attenuation and inactivation -- that could be applied to other diseases. Generations of scientists then built the supporting machinery: Petri dishes for bacterial culture, techniques to keep animal cells alive outside the body, bioreactors for industrial production, sterilization and cold-chain logistics. Those tools have now compounded. Cryo-electron microscopy reveals viral proteins atom by atom, a capability that directly enabled the RSV vaccine after earlier attempts failed. Genome sequencing costs collapsed from roughly $100 million per human genome in 2001 to under $1,000 by 2014, according to data from the National Human Genome Research Institute. The mRNA platform, refined through work by Katalin Kariko, Drew Weissman, and others, allows vaccines to be redesigned in weeks rather than years. The trajectory suggests more breakthroughs are possible. Whether they arrive depends on continued investment, however.

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The restaurant industry is trying to figure out whether America has hit peak pizza. From a report: Once the second-most common U.S. restaurant type, pizzerias are now outnumbered by coffee shops and Mexican food eateries, according to industry data. Sales growth at pizza restaurants has lagged behind the broader fast-food market for years, and the outlook ahead isn't much brighter. "Pizza is disrupted right now," Ravi Thanawala, chief financial officer and North America president at Papa John's International, said in an interview. "That's what the consumer tells us." The parent of the Pieology Pizzeria chain filed for chapter 11 bankruptcy protection in December. Others, including the parent of Anthony's Coal Fired Pizza & Wings and Bertucci's Brick Oven Pizza & Pasta, earlier filed for bankruptcy. Pizza once was a novelty outside big U.S. cities, providing room for growth for independent shops and then chains such as Pizza Hut with its red roof dine-in restaurants. Purpose-made cardboard boxes and fleets of delivery drivers helped make pizza a takeout staple for those seeking low-stress meals. Today, pizza shops are engaged in price wars with one another and other kinds of fast food. Food-delivery apps have put a wider range of cuisines and options at Americans' fingertips. And $20 a pie for a family can feel expensive compared with $5 fast-food deals, frozen pizzas or eating a home-cooked meal. [...] Pizza's dominance in American restaurant fare is declining, however. Among different cuisines, it ranked sixth in terms of U.S. sales in 2024 among restaurant chains, down from second place during the 1990s, Technomic said. The number of pizza restaurants in the U.S. hit a record high in 2019 and has declined since then, figures from the market-research firm Datassential show. Further reading, at WSJ: The Feds Need to Bail Out the Pizza Industry.

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Amazon has begun equipping managers with a dashboard that tracks not just whether corporate employees show up to the office but how long they stay once they're there, according to an internal document obtained by Business Insider. The system, which started rolling out in December, flags "Low-Time Badgers" who average less than four hours daily over an eight-week period and "Zero Badgers" who don't badge into any building during that span.

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Linus Torvalds has weighed in on an ongoing debate within the Linux kernel development community about whether documentation should explicitly address AI-generated code contributions, and his position is characteristically blunt: stop making it an issue. The Linux creator was responding to Oracle-affiliated kernel developer Lorenzo Stoakes, who had argued that treating LLMs as "just another tool" ignores the threat they pose to kernel quality. "Thinking LLMs are 'just another tool' is to say effectively that the kernel is immune from this," Stoakes wrote. Torvalds disagreed sharply. "There is zero point in talking about AI slop," he wrote. "Because the AI slop people aren't going to document their patches as such." He called such discussions "pointless posturing" and said that kernel documentation is "for good actors." The exchange comes as a team led by Intel's Dave Hansen works on guidelines for tool-generated contributions. Stoakes had pushed for language letting maintainers reject suspected AI slop outright, arguing the current draft "tries very hard to say 'NOP.'" Torvalds made clear he doesn't want kernel documentation to become a political statement on AI. "I strongly want this to be that 'just a tool' statement," he wrote.

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Craigslist, the 30-year-old classifieds site that looks virtually unchanged since the dial-up era, continues to draw more than 105 million monthly users and remains enormously profitable despite never spending a cent on advertising or marketing. The site ranks as the 40th most popular website in the United States, according to Internet data company Similarweb. University of Pennsylvania associate professor Jessa Lingel called it the "ungentrified" Internet. Unlike Facebook Marketplace, Etsy, or DePop, Craigslist doesn't use algorithms to track users or predict what they want to see. There are no public profiles, no rating systems, no likes or shares. The site effectively disincentivizes the clout-chasing and virality-seeking that dominates platforms like TikTok and Instagram. Craigslist began in 1995 as an email list for a few hundred San Francisco Bay Area locals sharing events and job openings. Engineer Craig Newmark even recruited CEO Jim Buckmaster through a site ad. The two spent roughly a decade battling eBay in court after the tech giant purchased a minority stake in 2004, ultimately buying back shares and regaining full control in 2015.

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An anonymous reader quotes a report from NPR: [I]t turns out that some genius dogs can learn a brand new word, like the name of an unfamiliar toy, by just overhearing brief interactions between two people. What's more, these "gifted" dogs can learn the name of a new toy even if they first hear this word when the toy is out of sight -- as long as their favorite human is looking at the spot where the toy is hidden. That's according to a new study in the journal Science. "What we found in this study is that the dogs are using social communication. They're using these social cues to understand what the owners are talking about," says cognitive scientist Shany Dror of Eotvos Lorand University and the University of Veterinary Medicine, Vienna. "This tells us that the ability to use social information is actually something that humans probably had before they had language," she says, "and language was kind of hitchhiking on these social abilities." [...] "There's only a very small group of dogs that are able to learn this differentiation and then can learn that certain labels refer to specific objects," she says. "It's quite hard to train this and some dogs seem to just be able to do it." [...] To explore the various ways that these dogs are capable of learning new words, Dror and some colleagues conducted a study that involved two people interacting while their dog sat nearby and watched. One person would show the other a brand new toy and talk about it, with the toy's name embedded into sentences, such as "This is your armadillo. It has armadillo ears, little armadillo feet. It has a tail, like an armadillo tail." Even though none of this language was directed at the dogs, it turns out the super-learners registered the new toy's name and were later able to pick it out of a pile, at the owner's request. To do this, the dogs had to go into a separate room where the pile was located, so the humans couldn't give them any hints. Dror says that as she watched the dogs on camera from the other room, she was "honestly surprised" because they seemed to have so much confidence. "Sometimes they just immediately went to the new toy, knowing what they're supposed to do," she says. "Their performance was really, really high." She and her colleagues wondered if what mattered was the dog being able to see the toy while its name was said aloud, even if the words weren't explicitly directed at the dog. So they did another experiment that created a delay between the dog seeing a new toy and hearing its name. The dogs got to see the unfamiliar toy and then the owner dropped the toy in a bucket, so it was out of sight. Then the owner would talk to the dog, and mention the toy's name, while glancing down at the bucket. While this was more difficult for dogs, overall they still could use this information to learn the name of the toy and later retrieve it when asked. "This shows us how flexible they are able to learn," says Dror. "They can use different mechanisms and learn under different conditions."

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YouTube is updating search filters so users can explicitly choose between Shorts and long-form videos. The change also replaces view-count sorting with a new "Popularity" filter and removes underperforming options like "Sort by Rating." The Verge reports: Right now, a filter-less search shows a mix of longform and short form videos, which can be annoying if you just want to see videos in one format or the other. But in the new search filters, among other options, you can pick to see "Videos," which in my testing has only showed a list of longform videos, or "Shorts," which just shows Shorts. YouTube is also removing the "Upload Date - Last Hour" and "Sort by Rating" filters because they "were not working as expected and had contributed to user complaints." The company will still offer other "Upload Date" filters, like "Today," "This week," "This Month," and "This Year," and you can also find popular videos with the new "Popularity" filter, which is replacing the "View count" sort option. (With the new "Popularity" filter, YouTube says that "our systems assess a video's view count and other relevance signals, such as watch time, to determine its popularity for that specific query.")

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Longtime Slashdot reader schwit1 shares a report from Reuters: Billionaire entrepreneur Elon Musk persuaded a judge on Wednesday to allow a jury trial on his allegations that ChatGPT maker OpenAI violated its founding mission in its high-profile restructuring to a for-profit entity. Musk was a cofounder of OpenAI in 2015 but left in 2018 and now runs an AI company that competes with it. U.S. District Judge Yvonne Gonzalez Rogers in Oakland, California, said at a hearing that there was "plenty of evidence" suggesting OpenAI's leaders made assurances that its original nonprofit structure was going to be maintained. The judge said there were enough disputed facts to let a jury consider the claims at a trial scheduled for March, rather than decide the issues herself. She said she would issue a written order after the hearing that addresses OpenAI's bid to throw out the case. [...] Musk contends he contributed about $38 million, roughly 60% of OpenAI's early funding, along with strategic guidance and credibility, based on assurances that the organization would remain a nonprofit dedicated to the public benefit. The lawsuit accuses OpenAI co-founders Sam Altman and Greg Brockman of plotting a for-profit switch to enrich themselves, culminating in multibillion-dollar deals with Microsoft and a recent restructuring. OpenAI, Altman and Brockman have denied the claims, and they called Musk "a frustrated commercial competitor seeking to slow down a mission-driven market leader." Microsoft is also a defendant and has urged the judge to toss Musk's lawsuit. A lawyer for Microsoft said there was no evidence that the company "aided and abetted" OpenAI. OpenAI in a statement after the hearing said: "Mr Musk's lawsuit continues to be baseless and a part of his ongoing pattern of harassment, and we look forward to demonstrating this at trial."

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Illinois Department of Human Services disclosed that a misconfigured internal mapping website exposed sensitive personal data for more than 700,000 Illinois residents for over four years, from April 2021 to September 2025. Officials say they can't confirm whether the publicly accessible data was ever viewed. TechCrunch reports: Officials said the exposed data included personal information on 672,616 individuals who are Medicaid and Medicare Savings Program recipients. The data included their addresses, case numbers, and demographic data -- but not individuals' names. The exposed data also included names, addresses, case statuses, and other information relating to 32,401 individuals in receipt of services from the department's Division of Rehabilitation Services.

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An anonymous reader quotes a report from Wired: Google is putting even more generative AI tools into Gmail as part of its goal to further personalize user inboxes and streamline searches. On Thursday, the company announced a new "AI Inbox" tab, currently in a beta testing phase, that reads every message in a user's Gmail and suggests a list of to-dos and key topics, based on what it summarizes. In Google's example of what this AI Inbox could look like in Gmail, the new tab takes context from a user's messages and suggests they reschedule their dentist appointment, reply to a request from their child's sports coach, and pay an upcoming fee before the deadline. Also under the AI Inbox tab is a list of important topics worth browsing, nestled beneath the action items at the top. Each suggested to-do and topic links back to the original email for more context and for verification. [...] For users who are concerned about their privacy, the information Google gleans by skimming through inboxes will not be used to improve the company's foundational AI models. "We didn't just bolt AI onto Gmail," says Blake Barnes, who leads the project for Google. "We built a secure privacy architecture, specifically for this moment." He emphasizes that users can turn off Gmail's new AI tools if they don't want them. At the same time Google announced its AI Inbox, the company made free for all Gmail users multiple Gemini features that were previously available only to paying subscribers. This includes the Help Me Write tool, which generates emails from a user prompt, as well as AI Overviews for email threads, which essentially posts a TL;DR summary at the top of long message threads. Subscribers to Google's Ultra and Pro plans, which start at $20 a month, get two additional new features in their Gmail inbox. First, an AI proofreading tool that suggests more polished grammar and sentence structures. And second, an AI Overviews tool that can search your whole inbox and create relevant summaries on a topic, rather than just summarizing a single email thread.

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