Steam on Linux use in March hit an all-time high of around 5.33% marketshare. Since then it pulled back to around 4% while for September 2026 the Steam Survey results… indicate a rather steep decline of 0.85%, down to 3.05%. Meanwhile macOS is at 1.92% and Microsoft Windows at 95%… Steam’s Survey reports a 7.42% increase in Chinese use, up to 31.39% overall of the Steam population. Usually those large month-over-month swings where Steam China use shoots up dramatically is a boost to Windows and a detriment to Linux. Some attribute the large increases in Simplified Chinese use to being a reporting/sampling issue.

When diving into the Steam Linux data exclusively, CachyOS has spiked by another 2.65% to now account for 18.12% of the sampled Linux gaming population. That even outperforms SteamOS Holo coming in at 17.37%. Among Linux gamers on Steam, AMD CPUs still account for the high 60 percentage space thanks to the Steam Deck and Steam Machine using AMD APUs and their open-source/Linux support being popular with enthusiasts.

The Nikon competition is about showcasing the beauty, complexity, and artistry of the microscopic world. The entries are abstract, often baffling to laypeople. But when Dr Xu was announced as the winner last month, members of the scientific community began to cry foul. “There are many serious problems with this video,” Edward Phelps, associate professor at Florida University, says on LinkedIn. Phelps points out that “purple structures pop in and out of existence” and “green cilia also appear from nowhere and do not match the known size.”

Dr Xu’s video is supposed to show the movement of cilia, which are hair-like structures that line part of the lungs… However, since Dr Xu won the prize, Nikon Small World updated its LinkedIn post celebrating his triumph with a note that reads: “Regarding questions raised about this year’s Small World In Motion winning video, Nikon is carefully re-reviewing the information provided during the initial vetting, along with additional supporting materials from the entrant.” Nikon adds that Dr Xu is “respectfully complying and has provided detailed technical documentation outlining the microscopy equipment, imaging methods, and processing techniques used to create the source video.”

Worse still, Ian Donovan, an MD/PhD Student at UT Southwestern Medical Center, says he ran the video through Google Gemini, and the result came back with an invisible Google SynthID watermark that indicates at least some of the video is AI-generated. Dr Xu, an optical engineering researcher at the National University of Singapore, reportedly responded to the LinkedIn post. According to Nature, Dr Xu accepted that he had used an AI model to assist with post-processing but denied breaking the rules of the competition, which clearly state that “AI-generated videos are not permitted.”

“It was applied afterwards to the reconstructed grayscale data to distinguish and color structures with similar morphology,” he wrote. However, Dr Xu’s messages on the LinkedIn post can’t be found as of today (October 1), and his LinkedIn profile now appears to have been deleted entirely.

According to a recent report from The New York Times, Dartmouth College students are calling out a top professor for allegedly using AI to help with writing… The school’s provost, Santiago Schnell, faced allegations of AI use last week from the college’s student-run newspaper, which detected AI in some of his published writing. The college said it was launching an investigation into the written work. Schnell said in a statement to the student-run newspaper, The Dartmouth, that he used AI “for language refinement, copyediting, improving clarity and organization and making writing processes more efficient.” The newspaper ran his statement through an AI detector, which said that Schnell had used AI to write it, too.

The laws ban employers from using the technology to predict a worker’s emotional state by using their biometric data, require employers to send written notices to workers if AI is responsible for mass layoffs and ban employers from relying on AI to decide to fire someone… The governor signed a law this month requiring operators of AI chatbots to perform risk assessments before rolling them out and an executive order requiring the state to consult with experts to further improve oversight over the industry.

Anthropic CEO Dario Amodei, who called for a slowdown in AI development amid existential risk concerns, said… that while a kill switch “could be a good idea,” it was no “panacea....” [California lawmakers] were generally supportive of Newsom’s plan and showed signs of coalescing around the kill switch idea, which was stripped out of legislation proposed two years ago. Rep. Ted Lieu, who introduced bipartisan kill switch legislation in the House, boosted Newsom’s call for Congress to mirror California’s approach.

FSF: Having control over the technology we use is a fundamental part of software freedom. Without it, you simply don’t have the basic freedoms you deserve when doing any type of computing, large or small. Don’t let “artificial intelligence” be an exception: all users everywhere deserve complete control over their own computing. While it’s understandable to be pleased by this news from California, Newsom’s executive order also invites questions about the “kill switch” itself that could matter a great deal for freedom. Assuming such a kill switch was developed, who would really control it?

We hope our readers understand the problems inherent in giving one single or a small number of kill switches to anyone. Newsom wisely wants an independent organization to verify their functionality, but even this still sets too dangerous of a precedent. We cannot allow such centralization of power over our computing to become commonplace, especially by the corporations that provide these models in the first place. We also cannot trust even the most well-intentioned “independent organization” to take care of its verification.

Giving users the freedom that they deserve over large languages models would be an enormous departure from how most are developed and used today. But, if any group is capable of coming up with such a plan, it’s the experts mentioned in Newsom’s order. Like he states at the beginning of his executive order, the vast majority of them are already right there in California. We urge the Government Operations Agency to consider the precedent they are setting, and ask them to write their recommendation to the governor in ways that puts the freedom and dignity of the individual user first and foremost.

Rendering Doom in a database is obviously a bad idea,” Lukas Vogel writes in a lengthy blog post explaining how exactly he managed to render Doom using an SQL database. OK, that’s not entirely accurate. The SQLDoom project uses a small Python client to handle input and output, drive the game’s timing, and display each frame to the screen. Behind that, a series of CedarDB tables tracks the game geometry and state, while about 1,300 lines of SQL queries spread across 89 common table expressions implement the game logic and generate 35 bitmap framebuffers per second.

In this, SQLDoom is a major improvement over Vogel’s previous DoomQL project, which last year set out to build “a multiplayer Doom-like shooter entirely in SQL.” Unfortunately, that effort ended up with raycasting-based, grayscale ASCII graphics that were more akin to the simplistic 90-degree-angled maps of Wolfenstein 3D. The newer SQLDoom, on the other hand, generates full-color 640x480 frames that look like they could have come from the original Doom executable. […] If you want to run a Doomtabase on your own local machine, you can do so simply with the GitHub code, a copy of CedarDB, and a Doom WAD file. Or you can jump into a free online hosted demo match to test it out without all the setup […].

Judge Hill: We might reasonably expect our friends and family to tell us something like: “Hey, I saw you out driving by the store last week.” But we do not expect people we know — let alone strangers, and especially not law enforcement — to randomly approach us to say: “Hey, I have been following your car for the last 30 days, and here is a detailed log of every place your vehicle has been with supporting photographic evidence. I am also going to share this information with law enforcement throughout the country so they know your whereabouts, too....”

Cell phones also move in public places where people can see you in plain view. But it becomes constitutionally problematic when law enforcement can indiscriminately and passively catalog your whereabouts over an extended period of time and then use that information for any purpose whenever convenient… [I]t is also consequential that we are not just dealing with stationary cameras. The cameras on [police officer] Alaniz’s vehicle itself feed information into these systems… It is also no longer difficult to imagine law enforcement using a fleet of drones hovering over an entire city so they don’t miss the movement of a single vehicle.

Despite its title, the bill doesn’t call out Flock in the text and covers any and all ALPR systems. The bill allows exceptions only for toll collection and for uses that Congress approves in future legislation, which would have to limit data retention to no longer than 48 hours.... Representative Alexandria Ocasio-Cortez (D-N.Y.) and Senator Jeff Merkley (D-Ore.) are co-sponsors.

The study found that an estimated 2.3 million new cancer cases were attributable to infections globally in 2024, equivalent to 12% of all cancer cases. Of these, the largest number (760,000 cases, or 4%) were caused by H. pylori, followed by HPV (750,000 cases, or 4%), HBV (360,000 cases, or 2%), EBV (260,000 cases, or 1%) and HCV (160,000 cases). More than three quarters of infection-attributable cancers occurred in low- and middle-income countries. Eastern Asian had the largest burden, with 990,000 cases (42% of the global total). Rates were also higher than the global average in sub-Saharan Africa, Central and Eastern Europe and Southeast Asia.

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.

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.

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.

GeekWire

reports that the University of Washington has moved its Global Innovation Exchange {GIX) program to Microsoft’s campus in a rent-free deal (UW News release). GIX, an institute supporting tech leaders that offers an MS in Technology Innovation, is the first UW program to set up full-time operations at Microsoft, whose headquarters are just across Lake Washington from the university’s main campus. Microsoft provided a $42 million in-kind donation to establish the embedded facility; the UW is leasing the new 48,500-square-foot GIX space in Microsoft’s Building 92 rent-free. GIX debuted in 2015 as a partnership of the UW and China’s Tsinghua University and received $70 million in Microsoft support at the now-abandoned GIX location in Bellevue (the Steve Ballmer Building), although indications are that a long-term arrangement did not come together as intended.

In a Thursday LinkedIn post, Microsoft President Brad Smith wrote: “Last night we opened a door unlike any other. At the heart of Microsoft’s campus, step into the new home of the UW’s Global Innovation Exchange (GIX) and you cross from Microsoft into the University of Washington. No one has ever put a great research university and a leading technology company under the same roof quite like this. As far as I know, no one has even tried. The timing matters. Artificial intelligence is advancing fast. The question is whether the people building it understand the world it’s changing. This calls for a new style of education and leadership. We need leaders who understand the technology deeply and see things through other people’s eyes. Leaders who learn by collaborating on real projects with people from different countries and disciplines. That’s what GIX is built for. Students will learn from faculty across the UW, take classes taught by Microsoft employees, and be mentored by people from across our industry here in the Pacific Northwest.”

Interestingly, Smith’s contention that UW GIX students will benefit from a ‘new style’ of Microsoft and industry-influenced education sounds a lot like Smith’s contention that K-12 school children are better off thanks to a new style of Microsoft and industry-influenced education. In an interview last month, Coding Kids: Big Tech’s Battle to Remake Public Schools author Natasha Singer told NPR (podcast, transcript), “For my book, I spoke to Brad Smith, who’s the president of Microsoft, and he has been one of the leaders in the tech industry pushing for [K-12] computer science [and now AI literacy] in schools. […] And Brad Smith said, philanthropy in the private sector is doing this work because public schools have failed to do what they were supposed to do. And his view is that public schools should be teaching modern subjects like computer science, and they were not equipped to do it fast enough and the tech industry stepped in to help. And is it better than if schools were able to do this themselves? He said, no, but it’s certainly better than nothing. And he said to me, you know, think about where we would be on computer science if the tech industry hadn’t stepped up. […] Well, I’ve been having this conversation with him for 10 years, and when we started having it 10 years ago, I said to him, I get that, but when big tech companies put their finger on the scale, it tips education in certain ways that not only favor the tech industry but can obscure equally or more important things.”

So, is “The University of Washington at Microsoft” a good or bad idea?

Days after a journalist claimed that Meta’s Muse app on Mac read their private messages — a claim that Meta disputed — Apple announced that it’s introducing additional controls around a setting called “Full Disk Access” on macOS. The feature was designed to allow backups to function properly, but AI agents have now increased “the risks associated with this level of access,” Apple said. […] In Muse’s case, the AI optionally allows users to enable Full Disk Access. This setting, Apple explains, gives an app permission to access files, mail, messages, and even browsing history.

“Some developers are using Full Disk Access in ways that could put users at risk, exposing everything on their systems… without users’ full knowledge and understanding,” Apple said in a new blog post aimed at developers. The company says that, going forward, it will introduce new controls aimed at ensuring that users who “genuinely wish to grant an app this extraordinary level of access” can do so only with “every explicit user action.”

“Addressing this is critical. As AI agents become increasingly capable and autonomous, the risks associated with this level of access will grow substantially. We are committed to ensuring users clearly understand these risks before granting such access, so they can make informed decisions about their own data and privacy,” Apple wrote.

Anyone buying used hardware for a gaming PC needs to be careful: not just whether the components are still in order but also what the previous owner did with them. A case on Reddit shows this. Someone installed a used AMD processor, a Ryzen 7 5800X3D, in their PC. Because the previous owner was caught cheating, the new owner cannot start several online games.

The problem was noticed in the first-person shooter “Valorant” from the development studio Riot. Right from the first start, the new owner was kicked out directly, according to their statement. Riot support confirmed that the previous owner had cheated. The processor is therefore on an internal blacklist — and, with its installation in the PC, now apparently also some other components like the mainboard. Riot support does not remove such entries manually.

In addition to “Valorant,” all other PC games from Riot are affected: the strategy game “League of Legends,” the auto-battler “Teamfight Tactics,” the card game “Legends of Runeterra,” the fighting game “2XKO,” and likely future titles as well.

“I don’t understand the added value here,” one official wrote on an internal staff message board, seen by POLITICO. Another described the tool as “absolute shit.” A third official said that, judging matters on how well Element Pro works compared to Teams, the U.S. would “instantly win the war” if it ever decided to switch off its technology. All the officials were granted anonymity to speak freely.

The Commission hosts the Element system on its own infrastructure rather than relying on Microsoft’s cloud. That gives the institution greater control over its communications data and systems. “That is not the case with Teams, where all we have is a guarantee that Microslop will not peek inside,” a fourth official wrote, presumably referring to Microsoft, in internal communications viewed by POLITICO.

Element is a U.K. company whose software is used by governments and public-sector organizations in Europe. The application works much like Teams, allowing staff to hold “audio and video calls with Commission colleagues, send and receive files, and create dedicated ‘rooms’ for projects and conversations, much like chats and channels in M365 Teams,” according to the Commission memo.

The lawsuits were filed in 2025, and Google requested a dismissal earlier this year. Chegg, an education and learning platform, claimed in its lawsuit that Google illegally scraped its educational content. This allowed Gemini models to essentially recreate that content and reduce the site’s traffic. Penske, which owns publications like Rolling Stone and Variety, filed a similar case that alleged lost traffic. Specifically, the publisher claimed it was unfair that sites indexed for organic search would also have their content harvested for AI answers, with no way to opt out.

These arguments did not sway the judge, who noted that Google’s implicit agreement with websites is not legally relevant. “Plaintiffs have pleaded only that they have an ‘expectation’ that Google will send them search “traffic if they make their content available for free,” wrote Mehta. “But an expectation is not an agreement. It is simply how a general search engine works.”

Since Google never had a formal arrangement with either Chegg or Penske, antitrust law doesn’t apply. And Mehta is aware of the legal issues surrounding search. He also heard the DOJ’s long-running search antitrust case against Google, eventually finding that Google violated the law. However, the government didn’t get the harsh penalties it wanted in that case.