fidzu : computers

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.

Read more of this story at Slashdot.

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.

Read more of this story at Slashdot.

03 Oct 2026 3:30am 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.

Read more of this story at Slashdot.

02 Oct 2026 11:00pm GMT

I like squirrels. Apparently, there's a SquirrelOS. It's a small hobby OS learning project from five years ago, developed by Immanuel Daviel A. Garcia. A simple DOS like OS made in Assembly and C with a ported version of Stephen Brennan's Shell. ↫ SquirrelOS GitHub page Why do I like squirrels? I don't know man, they're just cute.

02 Oct 2026 9:19pm 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

Google launched its Googlebooks platform a week ago, and a lot of people were wondering what this meant for Chrome OS and Chromebooks. Since Googlebooks and its Android-based Googlebook OS lack the management frameworks markets like schools require, Chromebooks will continue to be available for now, until such time Googlebooks catch up in that regard. However, in a support document, Google states that update support for all Chromebook devices will end in 2034: ChromeOS devices will continue to receive regular updates and security patches through mid-2034. For qualifying devices purchased today whose 10-year support lifecycle extends beyond 2034, Google is committed to supporting your transition to Googlebook OS, with many devices offering direct migration paths. ↫ Google support document Google promised 10 years of updates for all Chromebooks, and it's now breaking that promise for anyone buying a Chromebook between now and whenever the last Chromebook rolls off the production line. Sadly, we live in a world where corporations are free to make and break whatever promises they want virtually free of consequences, and as society we're so used to it that anti-consumer behaviour like this barely elicits a shrug. Google does state that "many newer commercial Chromebook models will be capable of upgrading to Googlebook OS", but that, too, is just another promise - and a vague, one at that - so who knows how many devices will actually be capable of upgrading out in the real world. On top of that, we have no idea if Googlebooks will just be yet another in a long line of quickly abandoned Google tablet/laptop projects, further adding to the uncertainty. Stuff like this should not be legal.

30 Sep 2026 10:09pm GMT

In June 2008 Apple announced Mac OS X Snow Leopard, proudly boasting that it would have "no new features". Instead of piling on new things, Snow Leopard aimed to build on the success of its predecessor, Leopard, opting to focus on under-the-hood performance and stability improvements throughout the system. 18 years later, Apple is taking a similar approach with macOS 27. Golden Gate aims to fix the missteps of last year's Tahoe, promising an expansive set of improvements and "a more responsive and delightful experience". Does it hold up? Here are just some of the bugs I've encountered in my daily use over the past couple of weeks. ↫ Chester at SquareOrbits I'm getting some real Windows 11 vibes from this long list of bugs and issues, further underlining my perception that Apple completely lost the plot when it comes to Mac OS X (in the past) and MacOS (today). These are not the kind of things you'd find in the heydays of Mac OS X, back when I was a devout user, and makes me glad I abandoned ship long, long ago (around the time of the Intel transition). I don't see stuff like this in GNOME or KDE, and while not nearly as bad as Windows 11, the cracks are obvious. I am by no means an expert at how Apple is run and how it organises itself, but as a layperson I do wonder if the company is simply trying to do too much - too many different platforms, too many different crucial components it all develops internally, too many different markets to please. Things are going to fall through the cracks when you try to keep this many plates spinning.

30 Sep 2026 9:55pm GMT

Over the last few weeks, we have been doing research on the integration of our official distribution packages when installed on a target system. In this context we have been looking at the current uses of alpm-install-scriptlet(5) files and alpm-hooks(5) in around 120 package source repositories (alpm-source-repo(7)) to better understand the underlying functionality and use-cases these two integrations offer and target. In this article we are going to look at how these two systems work, how Arch Linux is currently using them and attempt to provide suggestions for when to use which. Learning about alpm-hooks(5) and alpm-install-scriptlet(5) files …

09 Aug 2026 12:00am GMT

This is just a short note on my blog that I have resigned from Arch Linux a package maintainer, developer and security team. I've spent around 10 years as an AUR maintainer, security team, Package Maintainer and then Developer. I implemented support for debug packages, did the initial POC work that would become the git migration and even somehow managed to pull of an online conference during The Plague with the help of others.

01 Aug 2026 12:00am GMT

Good morning from JetBrains Berlin office!

01 Jun 2026 12:00am GMT