Spain's newspaper El Pais found an entire fake album on YouTube titled Rumba Congo (1973). And they cite a study from France's International Confederation of Societies of Authors and Composers that estimated revenue from AI-generated music will rise to $4 billion in 2028, generating 20% of all streaming platforms' revenue: One of the major problems with this trend is the lack of transparency. María Teresa Llano, an associate professor at the University of Sussex who studies the intersection of creativity, art and AI, emphasizes this aspect: "There's no way for people to know if something is AI or not...." On Spotify Community — a forum for the service's users — a petition is circulating that calls for clear labeling of AI-generated music, as well as an option for users to block these types of songs from appearing on their feeds. In some of these forums, the rejection of AI-generated music is palpable. Llano mentions the feelings of deception or betrayal that listeners may experience, but asserts that this is a personal matter. There will be those who feel this way, as well as those who admire what the technology is capable of... One of the keys to tackling the problem is to include a warning on AI-generated songs. YouTube states that content creators must "disclose to viewers when realistic content [...] is made with altered or synthetic media, including generative AI." Users will see this if they glance at the description. But this is only when using the app, because on a computer, they will have to scroll down to the very end of the description to get the warning.... The professor from the University of Sussex explains one of the intangibles that justifies the labeling of content: "In the arts, we can establish a connection with the artist; we can learn about their life and what influenced them to better understand their career. With artificial intelligence, that connection no longer exists." YouTube says they may label AI-generated content if they become aware of it, and may also remove it altogether, according to the article. But Spotify "hasn't shared any policy for labeling AI-powered content..." In an interview with Gustav Söderström, Spotify's co-president and chief product & technology officer, he emphasized that AI "increases people's creativity" because more people can be creative, thanks to the fact that "you don't need to have fine motor skills on the piano." He also made a distinction between music generated entirely with AI and music in which the technology is only partially used. But the only limit he mentioned for moderating artificial music was copyright infringement... something that has been a red line for any streaming service for many years now. And such a violation is very difficult to legally prove when artificial intelligence is involved.

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An anonymous reader shared this report from Bloomberg: Amazon's hard-line stance on getting disabled employees to return to the office has sparked a backlash, with workers alleging the company is violating the Americans with Disabilities Act as well as their rights to collectively bargain. At least two Amazon employees have filed complaints with the Equal Employment Opportunity Commission (EEOC) and the National Labor Relations Board, federal agencies that regulate working conditions. One of the workers said they provided the EEOC with a list of 18 "similarly situated" employees to emphasize that their experience isn't isolated and to help federal regulators with a possible investigation. Disabled workers frustrated with how Amazon is handling their requests for accommodations — including exemptions to a mandate that they report to the office five days a week — are also venting their displeasure on internal chat rooms and have encouraged colleagues to answer surveys about the policies. Amazon has been deleting such posts and warning that they violate rules governing internal communications. One employee said they were terminated and another said they were told to find a different position after advocating for disabled workers on employee message boards. Both filed complaints with the EEOC and NLRB. Amazon has told employees with disabilities they must now submit to a "multilevel leader review," Bloomberg reported in October, "and could be required to return to the office for monthlong trials to determine if accommodations meet their needs." (They received calls from "accommodation consultants" who also reviewed medical documentation, after which "another Amazon manager must sign off. If they don't, the request goes to a third manager...") Bloomberg's new article remembers how several employees told them in November. "that they believed the system was designed to deny work-from-home accommodations and prompt employees with disabilities to quit, which some have done. Amazon denied the system was designed to encourage people to resign." Since then, workers have mobilized against the policy. One employee repeatedly posted an online survey seeking colleagues' reactions, defying the company's demands to stop. The survey ultimately generated feedback from more than 200 workers even though Amazon kept deleting it, and the results reflected strong opposition to Amazon's treatment of disabled workers. More than 71% of disabled Amazon employees surveyed said the company had denied or failed to meet most of their accommodation requests, while half indicated they faced "hostile" work environments after disclosing their disabilities and requesting accommodations. One respondent said they sought permission to work from home after suffering multiple strokes that prevented them from driving. Amazon suggested moving closer to the office and taking mass transit, the person said in the survey. Another respondent said they couldn't drive for longer than 15-minute intervals due to chronic pain. Amazon's recommendation was to pull over and stretch during their commute, which the employee said was unsafe since they drive on a busy freeway... Amazon didn't dispute the accounts and said it considered a range of solutions to disability accommodations, including changes to an employee's commute. Amazon is also "using AI to parse accommodation requests, read doctors' notes and make recommendations based on keywords," according to the article — another policy that's also generated internal opposition (and formed a "key element" of the complaint to the Equal Employment Opportunity Commission). "The dispute could affect thousands of Amazon workers. An internal Slack channel for employees with disabilities has 13,000 members, one of the people said..."

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In Tokyo Mitsubishi is deploying "an innovative new battery swap network for electric cars" in a multi-year test program reports the EV news site Electrek. But it's not just for electric cars. Along with the 14 modular battery swapping stations, Mitsubishi is also deploying "more than 150 battery-swappable commercial electric vehicles" from truck maker Fuso: A truck like the Mitsubishi eCanter typically requires a full night of AC charging to top off its batteries, and at least an hour or two on DC charging in Japan, according to Fuso. This joint pilot by Mitsubishi, Mitsubishi Fuso Trucks, and [EV battery swap specialist] Ample aims to circumvent this issue of forced downtime with its swappable batteries, supporting vehicle uptime by delivering a full charge within minutes. The move is meant to encourage the transport industry's EV shift while creating a depository of stored energy that can be deployed to the grid in the event of a natural disaster — something Mitsubishi in Japan has been working on for years. The article's author also adds their own opinion about battery-swapping technology. "When you see how simple it is to add hundreds of miles of driving in just 100 seconds — quicker, in many cases, than pumping a tank of liquid fuel into an ICE-powered car — you might come around, yourself."

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Timothy B. Lee has written for the Washington Post, Vox.com, and Ars Technica — and now writes a Substack blog called "Understanding AI." This week he visits recent research by computer scientists and legal scholars from Stanford, Cornell, and West Virginia University that found that Llama 3.1 70BÂ(released in July 2024) has memorized 42% of the first Harry Potter book well enough to reproduce 50-token excerpts at least half the time... The paper was published last month by a team of computer scientists and legal scholars from Stanford, Cornell, and West Virginia University. They studied whether five popular open-weight models — three from Meta and one each from Microsoft and EleutherAI — were able to reproduce text from Books3, a collection of books that is widely used to train LLMs. Many of the books are still under copyright... Llama 3.1 70B — a mid-sized model Meta released in July 2024 — is far more likely to reproduce Harry Potter text than any of the other four models.... Interestingly, Llama 1 65B, a similar-sized model released in February 2023, had memorized only 4.4 percent of Harry Potter and the Sorcerer's Stone. This suggests that despite the potential legal liability, Meta did not do much to prevent memorization as it trained Llama 3. At least for this book, the problem got much worse between Llama 1 and Llama 3. Harry Potter and the Sorcerer's Stone was one of dozens of books tested by the researchers. They found that Llama 3.1 70B was far more likely to reproduce popular books — such as The Hobbit and George Orwell's 1984 — than obscure ones. And for most books, Llama 3.1 70B memorized more than any of the other models... For AI industry critics, the big takeaway is that — at least for some models and some books — memorization is not a fringe phenomenon. On the other hand, the study only found significant memorization of a few popular books. For example, the researchers found that Llama 3.1 70B only memorized 0.13 percent of Sandman Slim, a 2009 novel by author Richard Kadrey. That's a tiny fraction of the 42 percent figure for Harry Potter... To certify a class of plaintiffs, a court must find that the plaintiffs are in largely similar legal and factual situations. Divergent results like these could cast doubt on whether it makes sense to lump J.K. Rowling, Richard Kadrey, and thousands of other authors together in a single mass lawsuit. And that could work in Meta's favor, since most authors lack the resources to file individual lawsuits. Why is it happening? "Maybe Meta had trouble finding 15 trillion distinct tokens, so it trained on the Books3 dataset multiple times. Or maybe Meta added third-party sources — such as online Harry Potter fan forums, consumer book reviews, or student book reports — that included quotes from Harry Potter and other popular books..." "Or there could be another explanation entirely. Maybe Meta made subtle changes in its training recipe that accidentally worsened the memorization problem."

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Meta and AWS have used Rust, and Netflix uses Go,reports the programming news site InfoQ. But using another language, Apple recently "migrated its global Password Monitoring service from Java to Swift, achieving a 40% increase in throughput, and significantly reducing memory usage." This freed up nearly 50% of their previously allocated Kubernetes capacity, according to the article, and even "improved startup time, and simplified concurrency." In a recent post, Apple engineers detailed how the rewrite helped the service scale to billions of requests per day while improving responsiveness and maintainability... "Swift allowed us to write smaller, less verbose, and more expressive codebases (close to 85% reduction in lines of code) that are highly readable while prioritizing safety and efficiency." Apple's Password Monitoring service, part of the broader Password app's ecosystem, is responsible for securely checking whether a user's saved credentials have appeared in known data breaches, without revealing any private information to Apple. It handles billions of requests daily, performing cryptographic comparisons using privacy-preserving protocols. This workload demands high computational throughput, tight latency bounds, and elastic scaling across regions... Apple's previous Java implementation struggled to meet the service's growing performance and scalability needs. Garbage collection caused unpredictable pause times under load, degrading latency consistency. Startup overhead — from JVM initialization, class loading, and just-in-time compilation, slowed the system's ability to scale in real time. Additionally, the service's memory footprint, often reaching tens of gigabytes per instance, reduced infrastructure efficiency and raised operational costs. Originally developed as a client-side language for Apple platforms, Swift has since expanded into server-side use cases.... Swift's deterministic memory management, based on reference counting rather than garbage collection (GC), eliminated latency spikes caused by GC pauses. This consistency proved critical for a low-latency system at scale. After tuning, Apple reported sub-millisecond 99.9th percentile latencies and a dramatic drop in memory usage: Swift instances consumed hundreds of megabytes, compared to tens of gigabytes with Java. "While this isn't a sign that Java and similar languages are in decline," concludes InfoQ's article, "there is growing evidence that at the uppermost end of performance requirements, some are finding that general-purpose runtimes no longer suffice."

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NPR looks at the "high-quality, climate-friendly apartments" in Vienna, asking if it's a model for addressing both climate change and the housing crisis. About half the city's 2 million people live in the widespread (and government-supported) apartments, with solar panels on top and very thick, insulated walls that reduce the need for heating and cooling. (One resident tells NPR they don't even need an air conditioner because "It's not cold in winter times. It's not hot in summer times.") Vienna council member Nina Abrahamczik, who heads the climate and environment committee, says as the city transitions all of its buildings off planet-heating fossil fuels, they're starting with the roughly 420,000 housing units they already own or subsidize.... As Vienna makes an aggressive push to completely move away from climate-polluting natural gas by 2040, it's starting with much of this social housing, says Jürgen Czernohorszky, executive city councilor responsible for climate and environment. City-owned buildings are now switching from gas to massive electric heat pumps, and to geothermal, which involves probing into the ground to heat homes. Another massive geothermal project that drills even deeper into the earth to heat homes is also underway. The city is also powering housing with solar energy. As of a year and a half ago, Vienna mandates all new buildings and building extensions to have rooftop solar. And Vienna's older apartment buildings are getting climate retrofits, says Veronika Iwanowski, spokesperson for Vienna's municipal housing company, Wiener Wohnen. That includes new insulation, doors and windows to prevent the city's wind from getting in the cracks. The increase in energy efficiency and switching from gas to renewables doesn't just have climate benefits from cutting fossil fuel use. It also means housing residents are paying less on electric bills... With city-subsidized housing, housing developers can compete to get land and low-interest loans from the city. Officials say those competitions are a critical lever for climate action. "As we can control the contents of the competitions, we try to make them fit to the main goals of the city," says Kurt Hofstetter, city planner for Vienna, "which is of course also ecological...." Now the housing judges give out points for things like increased energy efficiency, green roofs and sustainable building materials... Now the climate innovations in subsidized housing are inspiring the private market as well, Hofstetter says... The article notes that most of the city's funding is provided in the form of low-interest loans, according to a researcher at the Austrian Federation of Limited-Profit Housing Associations. (And the average social housing rents are about $700 for a large one-bedroom apartment, says Gerald Kössl, researcher at the Austrian Federation of Limited-Profit Housing Associations.)

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A chain of stores called Home Bargains installed facial recognition software to spot returning shoplifters. Unfortunately, "Facewatch" made a mistake. "We acknowledge and understand how distressing this experience must have been," an anonymous Facewatch spokesperson tells the BBC, adding that the store using their technology "has since undertaken additional staff training." A woman was accused by a store manager of stealing about £10 (about $13) worth of items ("Everyone was looking at me"). And then it happened again at another store when she was shopping with her 81-year-old mother on June 4th: "As soon as I stepped my foot over the threshold of the door, they were radioing each other and they all surrounded me and were like 'you need to leave the store'," she said. "My heart sunk and I was anxious and bothered for my mum as well because she was stressed...." It was only after repeated emails to both Facewatch and Home Bargains that she eventually found there had been an allegation of theft of about £10 worth of toilet rolls on 8 May. Her picture had somehow been circulated to local stores alerting them that they should not allow her entry. Ms. Horan said she checked her bank account to confirm she had indeed paid for the items before Facewatch eventually responded to say a review of the incident showed she had not stolen anything. "Because I was persistent I finally got somewhere but it wasn't easy, it was really stressful," she said. "My anxiety was really bad — it really played with my mind, questioning what I've done for days. I felt anxious and sick. My stomach was turning for a week." In one email from Facewatch seen by the BBC, the firm told Ms Horan it "relies on information submitted by stores" and the Home Bargains branches involved had since been "suspended from using the Facewatch system". Madeleine Stone, senior advocacy officer at the civil liberties campaign group Big Brother Watch, said they had been contacted by more than 35 people who have complained of being wrongly placed on facial recognition watchlists. "They're being wrongly flagged as criminals," Ms Stone said. "They've given no due process, kicked out of stores," adds the senior advocacy officer. "This is having a really serious impact." The group is now calling for the technology to be banned. "Historically in Britain, we have a history that you are innocent until proven guilty but when an algorithm, a camera and a facial recognition system gets involved, you are guilty. The Department for Science, Innovation and Technology said: "While commercial facial recognition technology is legal in the UK, its use must comply with strict data protection laws. Organisations must process biometric data fairly, lawfully and transparently, ensuring usage is necessary and proportionate. "No one should find themselves in this situation." Thanks to alanw (Slashdot reader #1,822) for sharing the article.

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The state of New York is "asking companies to disclose whether AI is the reason for their layoffs," reports Entrepreneur: The move applies to New York State's existing Worker Adjustment and Retraining Notification (WARN) system and took effect in March, Bloomberg reported. New York is the first state in the U.S. to add the disclosure, which could help regulators understand AI's effects on the labor market. The change takes the form of a checkbox added to a form employers fill out at least 90 days before a mass layoff or plant closure through the WARN system. Companies have to select whether "technological innovation or automation" is a reason for job cuts. If they choose that option, they are directed to a second menu where they are asked to name the specific technology responsible for layoffs, like AI or robots.

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"Cooper Taylor is only 17 years old, but he's already trying to revolutionize the drone industry," writes Business Insider: His design makes the drone more efficient, customizable, and less expensive to construct, he says. He's built six prototypes, 3D printing every piece of hardware, programming the software, and even soldering the control circuit board. He says building his drone cost one-fifth of the price of buying a comparable machine, which sells for several thousand dollars. Taylor told Business Insider he hopes that "if you're a first responder or a researcher or an everyday problem solver, you can have access to this type of drone." His innovation won him an $8,000 scholarship in April at the Junior Science and Humanities Symposium, funded by the Defense Department. Then, on May 16, he received an even bigger scholarship of $15,000 from the US Navy, which he won after presenting his research at the Regeneron International Science and Engineering Fair... It all started when Taylor's little sister got a drone, and he was disappointed to see that it could fly for only about 30 minutes before running out of power. He did some research and found that a vertical take-off and landing, or VTOL, drone would last longer. This type of drone combines the multi-rotor helicopter style with the fixed wings of an airplane, making it extremely versatile. It lifts off as a helicopter, then transitions into plane mode. That way, it can fly farther than rotors alone could take it, which was the drawback to Taylor's sister's drone. Unlike a plane-style drone, though, it doesn't need a runway, and it can hover with its helicopter rotors. Taylor designed a motor "that could start out helicopter-style for liftoff, then tilt back to become an airplane-style motor," according to the article. And now this summer he'll be "working on a different drone project through a program with the Reliable Autonomous Systems Lab at the Massachusetts Institute of Technology." Thanks to Slashdot reader Agnapot for sharing the news.

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America's federal government is building a website and API called ai.gov to "accelerate government innovation with AI", according to an early version spotted by 404 Media that was posted on GitHub by the U.S. government's General Services Administration. That site "is supposed to launch on July 4," according to 404 Media's report, "and will include an analytics feature that shows how much a specific government team is using AI..." AI.gov appears to be an early step toward pushing AI tools into agencies across the government, code published on Github shows.... The early version of the page suggests that its API will integrate with OpenAI, Google, and Anthropic products. But code for the API shows they are also working on integrating with Amazon Web Services' Bedrock and Meta's LLaMA. The page suggests it will also have an AI-powered chatbot, though it doesn't explain what it will do... Currently, AI.gov redirects to whitehouse.gov. The demo website is linked to from Github (archive here) and is hosted on cloud.gov on what appears to be a staging environment. The text on the page does not show up on other websites, suggesting that it is not generic placeholder text... In February, 404 Media obtained leaked audio from a meeting in which [the director of the GSA's Technology Transformation Services] told his team they would be creating "AI coding agents" that would write software across the entire government, and said he wanted to use AI to analyze government contracts.

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