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03 Oct 2026 10:07am GMT

KDE Plasma 6.8 Beta 2 adds more polish and bug fixes, improving tiled windows, Spectacle, GPU monitoring, remote desktop support, and more.

03 Oct 2026 10:06am GMT

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03 Oct 2026 9:59am GMT

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03 Oct 2026 9:13am GMT

Longtime Slashdot reader Geoffrey.landis shares a report from NPR: Google just put a refrigerator-sized satellite into space, part of a research project the company hopes can pave the way for orbiting AI data centers powered by the sun. The prototype satellite has four specialty chips in it called Tensor Processing Units, or TPUs, that Google designed for machine learning and has already deployed in data centers on Earth. The chips will run a version of the company's Gemma AI model for 15 minutes at a time due to heat management constraints, using the open weight model to answer simple queries. In a blog post, Google said the mission will gauge how the TPUs handle "the physical stress of spaceflight and the radiation and thermal extremes of space." The satellite launched October 1 is a prototype that Travis Beals, senior director and lead of Project Suncatcher, called "a very minimal test" to make sure the chips can run in space. A SpaceX rocket carried it into orbit, and Planet will get it up and running. Beal said Google will then fire up and test the TPUs. The goal is for the mission to be operational for a year.

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03 Oct 2026 7:00am GMT

An anonymous reader quotes a report from Reuters: The state of New Mexico asked a judge on Thursday to order Meta Platforms to pay between $35 billion and $40 billion in penalties after a jury found the company had misled consumers about the privacy of their data on Facebook in a case that came out of the Cambridge Analytica scandal. Attorneys for New Mexico made the request at a hearing in a lawsuit brought following revelations that the British political consulting firm, which worked on Donald Trump's 2016 presidential campaign, harvested personal data from as many as 87 million Facebook users through a third-party app without their consent. The jury returned its verdict on September 25. Judge Francis Mathew, who oversaw the trial in Santa Fe, will decide how much Meta must pay in financial penalties. [...] State law allows the judge to decide how much to fine Meta per violation, up to $5,000. At the hearing on Thursday, Randi McGinn, a lawyer for New Mexico, said applying the full $5,000 penalty to the number of violations would create too large of a penalty under the US Constitution's protections on due process. But the judge should order a significant payment that will impact the company, McGinn said. "This court should speak to Meta in the only language it understands, which is money, and the value of its stock price," McGinn said. She said $35 billion to $40 billion, which represents about 20% of the possible penalties that could be awarded under state law from the verdict, would impact the stock price while complying with Meta's right to due process under the Constitution. At the hearing on Thursday, Matt Nicholson, a lawyer for Meta, called the state's request an "astronomical penalty that would obviously violate a host of constitutional provisions." In court filings, Meta urged Mathew to cap the penalties at $3.45 billion. The jury may have said it found Meta's statements misleading, but the evidence shows that Meta does not sell user data and New Mexico did not prove that any consumer had actually been misled, the company said in court filings. The judge said he expected to issue a ruling later this month.

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03 Oct 2026 3:30am GMT

Wine 11.19 introduces DNS query caching, Unicode 18.0 character tables, GDIPlus vertical text support, VBScript improvements, and 23 bug fixes.

02 Oct 2026 11:30pm GMT

Meta says FDA isn't sufficient to Muse reading messages. Apple begs to differ.

02 Oct 2026 11:03pm GMT

Researchers from Carnegie Mellon, MIT, NYU, and Stanford have built an AI called Ataraxos that finally cracked Stratego, beating four-time world champion Pim Niemeijer 15 games to one with four draws. Its key advantage was a second neural network that estimates the identities of hidden enemy pieces, letting the system search plausible game states rather than brute-force a massive hidden-information space. Ars Technica reports: Just like [DeepMind's DeepNash, introduced in 2022], Ataraxos learned by playing against itself -- 163 million games in total. In these self-play sessions, moves that led to wins were reinforced and played more often in future matches, while moves that led to losses were played less, which was the same simple training idea. The difference was in how much Ataraxos adjusted after each game, because hidden information tends to send self-play learning algorithms around in circles. The team addressed this by making big, bold changes in strategy early in training and small, careful ones later. The even bigger innovation was something DeepNash never had: thinking ahead before each move. AIs like AlphaGo refine their general strategy with a search just before acting. DeepMind couldn't make that work in Stratego because the search space was too large, leaving it an open question whether it was worth trying. "This is one of the things that we did figure out how to do," Farina said. The solution was a second neural network, a belief model, trained to guess the opponent's hidden pieces based on how they had been moving. This way, instead of iterating through every possible arrangement, Ataraxos samples plausible ones, plays out candidate moves in each, and picks based on how they turned out. And it shows in its playstyle. [...] DeepNash was trained for two to three months on 1,024 of Google's specialized chips, a run the Ataraxos team estimates would cost $3 million to $4.5 million at 2025 prices. Ataraxos, in contrast, needed 16 GPUs for a week, plus an additional four GPUs for four days to train the belief model. Farina and lead author Samuel Sokota achieved this efficiency by writing a simulator that runs millions of moves per second on graphics cards. "At the scale that we are in academia, we don't really have access to an entire field of GPUs," Farina said. The algorithm also learned far faster -- it played about 34 times fewer games than DeepNash, and still ended up much stronger. The findings have been published in the journal Nature.

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02 Oct 2026 11:00pm GMT

1,300 lines of SQL querying renders accurate bitmapped views of Hell at 35 fps.

02 Oct 2026 9:19pm GMT

Amazon praised for ending NDAs but slammed for downplaying data center pollution.

02 Oct 2026 8:30pm GMT

System76's COSMIC project now requires contributors to confirm that pull requests contain no LLM-generated code, comments, or descriptions.

02 Oct 2026 7:22pm GMT