You can now register your interest to buy a Steam Machine as part of a reservation system. To offer a fair playing field for people who want to buy one, Valve will randomize everyone in the queue on Thursday at 1PM ET. After that, anyone who registers their interest will be added to the end of the waitlist. The first emails giving people the opportunity to buy will go out on June 29th.

Valve will sell four configurations of the Steam Machine:
- A 512GB model for $1,049
- A 512GB model with a bundled Steam Controller for $1,128
- A 2TB model for $1,349
- A 2TB model with a bundled Steam Controller for $1,428

After attempting to resolve a dispute over paid fees without court action, Camal Taquidir […] used Garfield AI to help her pursue the case in court. She was able to generate pre-action correspondence, and then prepare and issue court proceedings. The AI legal assistant conducted all of the legal work preceding the court trial. The defendant instructed solicitors and brought a counterclaim, which the claimant disputed with the support of Garfield AI.

The claimant continued to trial, including dealing with document production, the preparation witness statements and trial bundles. Garfield then instructed a junior, shortly before the trial began. She won the claim over unpaid fees following a three-hour trial at Wandsworth County Court. The claimant paid around 400 pounds in Garfield AI fees to recover the 7,000 pounds owed, while the defendant instructed both a solicitor and a barrister. […] Following a three-hour trial at Wandsworth County Court on 14 May 2026, in which both sides were represented by barristers, the court found in favor of the claimant, awarding 7,000 pounds and dismissing the counterclaim.

Once the phone’s motherboards have been extracted from their shells, the researchers say that the chips hiding within remain more than potent enough to be useful for a variety of tasks. In many cases, the single-threaded performance of these chips is as good as, if not better than, what you’d find from a many-cored datacenter chip. The Pixel Fold smartphones, which will form the basis of the cluster, are powered by a Google Tensor G2 processor with two 2.85 GHz Cortex-X1, two 2.35 GHz Cortex-A78 and four 1.80 GHz Cortex-A55 Arm cores, a Mali-G710 MP7 GPU, and 12 GB of system memory. Early benchmarking using the SPEC suite suggests that 25-50 phones should deliver performance similar to that of a conventional server.

The major challenge, instead, is distributing workloads across multiple devices, each of which has a handful of cores of one or more varieties, and most have 8-12 GB of memory. UCSD researchers are approaching this challenge from a couple of different angles. The first is by targeting applications that can easily fit within a single device. The second is using Kubernetes to orchestrate container deployments across clusters of 25-50 phones. For this to work, the devices first need to be flashed with a Linux operating system suitable for the job. While Android makes for a great handheld experience, it is not intended for server duty. In the blog post, researchers note that Android includes functionality intended to stop rogue applications from chewing up excessive amounts of memory and draining your battery. In server context, these safety mechanisms are no longer necessary.

[Ryan Kastner, an associate professor of computer science at UCSD] told us this was by no means an easy task, but the team has made steady progress toward getting Linux running smoothly on these devices, including support for the phone’s onboard GPUs. Access to some functionality, like the chip’s integrated tensor processing unit, remains elusive. Clustering these devices will require networking the phones together. Normally these devices would connect over cellular or Wi-Fi, but at this scale, this not only isn’t practical, but also has implications for security, he explained. Instead, the team will employ PCBs that both supply power and break out wired Ethernet networking.

The researchers suggest that many EdTech, grading, and research workloads commonly run by universities in the cloud are small enough to run on the cluster without issue. “The vast majority of these applications are within the capabilities of a single smartphone to host, with the standard grading backend running on small cloud instances,” a blog post detailing the planned deployment reads. “Early experiments show that even a moderately-sized cluster of 20 phones is capable of supporting peak submission rates for a 75+ student class.”

Claude Guillemot, co-founder of French video game company Ubisoft, died Friday at the age of 69. According to French media (via Bloomberg), Guillemot died in a plane crash in the French resort town of La Baule. He was one of two people aboard the plane, both of whom died.

Guillemot founded Ubisoft with his four brothers in 1986. Since then, the company has published the Assassin’s Creed, Far Cry, Prince of Persia, and Tom Clancy video game franchises, as well as many other titles. The family retains control of Ubisoft, and Guillemot’s brother Yves is still CEO. Guillemot was also chairman of Guillemot Corp., which makes gaming and audio accessories.

Part of the problem comes in the form of filing cabinets, manila folders and legacy digital databases. In other words, records for a single prisoner might be kept in a dozen places… Now a group of 19 prison systems are tackling the problem with digital tools and artificial intelligence in some cases. They are contracting with San Francisco nonprofit Recidiviz, whose computer systems bring together prisoner data from its disparate sources into digital dashboards. From there, corrections staff can see information — such as court records and notes from parole-board hearings — about a prisoner or parolee all in one place.

The company says its efforts are working: Recidivism has fallen 16% in the prison population its systems track. It is the result of “just streamlining these workflows and knitting someone’s journey together end to end,” says Clementine Jacoby, chief executive officer of Recidiviz. Some criminal-justice groups show that recidivism is trending downward in general, though most of that data is nearly a decade old… The statistics from 11 states stop at 2019, and for four states stop at 2016. With 10 other states, no data was reported.

Shahid Adnan completed assignments and online tests for more than 120 students at Liverpool John Moore’s University, the Crown Prosecution Service said. The 43-year-old, of Lysander Close, Liverpool, was caught in February 2023 after a student handed in a USB drive containing suspicious coursework to Dr Tom Berry of the university’s school of computer science and mathematics. Berry’s checks revealed the drive was used by Adnan with documents linked to a company he set up called Study Sharp Ltd.

Excel spreadsheets containing details of other students, their study modules, coursework due dates, and their personal login credentials were also found. Further checks confirmed suspicions that Adnan was accessing the university’s network to submit fraudulent work and sit examinations on behalf of students… [I]nvestigations led police to believe Adnan may have been doing work for 124 students at universities all over the world.

The company manually reviewed over 10,000 TikTok videos across 20 categories and ran a separate fresh-account test, counting AI-generated content in the first 500 For You videos. Kapwing ran the same fresh-account test on YouTube and found that 104 of the first 500 Shorts, or 21%, were AI slop. On TikTok, 294 of 500 For You videos hit that threshold…

Of the 2,000 videos Kapwing reviewed in TikTok’s Kids category, 57% were AI slop. That was the highest rate of any category in the analysis. The highest-rate tag was #cartoonkids, where 97 of 100 featured videos were AI-generated. Tags like #cartoons and #babysong both reached 83%, and #forkids came in at 79%. After Kids, the next highest AI slop rates were in Science and Education (35%), Health (33%), and History (33%). All three are categories where visual illustration and voiceover narration make up much of the content.

On the other end, categories where on-camera presence or physical demonstration are central had the lowest rates. Fashion came in at 1.3%, Music at 1.5%, and Fitness at 1.6%.

A new systemd fork has appeared with a specific purpose: removing systemd’s recently added support for storing a user’s birth date in JSON user records.

The fork, called Liberated systemd, published its first tagged release as v261 shortly after the official systemd 261 release. In other words, the fork follows upstream systemd while reverting the change that added the new optional birthDate field.

Importantly, this is not a new init system, a wider redesign of systemd, or a general-purpose alternative to the upstream project. Its stated purpose is to remain close to upstream systemd while removing what the author describes as “surveillance enablement”… The author recommends testing the fork in a virtual machine before using it on real hardware and warns nightly builds are more likely to be unstable than named releases.

Almost all the innovations we regularly hear about — from cheaper, tougher electric-vehicle batteries to "Holy Grail” solid-state batteries — are about changing the chemistry of batteries. The promise of battery-tech 3-D printing (aka additive manufacturing) is simple: What if batteries could fill any available space, even structural elements of our gadgets, rather than always taking a rigid shape like a pouch or cylinder?

The new approach has obvious appeal. The entire airframe of a drone could be filled with energy storage for increased range. Smartglasses could have sleek battery-packed frames, so they look like everyday eyewear rather than “Revenge of the Nerds” props. One of the biggest advantages of 3-D printing is that it works with any battery, regardless of its cell chemistry. It could advance today’s lithium-ion as well as emerging sodium-ion and solid-state tech… Some [startups] are trying to use 3-D printing to create efficiencies in existing battery manufacturing systems. A brave handful of startups are pursuing radical new designs and approaches. They’re starting with defense applications, where cost and scale are less of an issue…

At Silicon Valley-based Sakuu… [r]ather than trying to 3-D-print whole batteries, the company is working on replacing one of battery manufacturing’s biggest pain points, says Arwed Niestroj, Sakuu’s chief operating officer, who is also a nuclear physicist and former head of Mercedes-Benz Research & Development North America. Existing battery assembly lines include football-field-long ovens for drying layers of material that have been dissolved in solvents. This requires a huge amount of energy and is a significant contributor to manufacturing costs, a big reason EV batteries aren’t cheaper. Sakuu’s process, under development for years, uses additive manufacturing to lay down key battery components without solvents, eliminating the need for ovens, says Niestroj.

Sakuu is currently working to commercialize this tech with a major battery manufacturer…

Tesla wants to sell modular AI data center hardware, according to a new trademark application for a product called “Megapod.” The filing describes a complete, self-contained computing system for AI workloads…

Tesla filed the “Megapod” trademark (serial number 99893717) with the U.S. Patent and Trademark Office this month, through its longtime IP counsel. It’s an intent-to-use application, meaning Tesla is claiming the name for a product it hasn’t launched yet. The goods-and-services description is unusually specific for a trademark. Megapod covers “modular data center hardware systems for artificial intelligence computing, comprised of computer servers, computer hardware for artificial intelligence data processing, networking equipment, power distribution units, and cooling systems.” It also covers “self-contained modular computing hardware systems for artificial intelligence workloads,” integrated platforms sold as a single unit — an enclosure bundling compute, power distribution, and cooling — and downloadable software to monitor, manage, and optimize those systems.

In plain terms: Tesla wants to sell a turnkey AI data center building block. Not a battery, not a chip on its own, but the full rack-and-room of servers, networking, power, and cooling that AI training and inference run on.

Tesla’s own AI training cluster, Cortex at Gigafactory Texas, runs on roughly 67,000 Nvidia H100-equivalent GPUs. In other words, Tesla is one of Nvidia’s customers, not a competitor selling alternative hardware… Where Tesla does have a real AI-data-center business is power, not compute. Its Megapack and new Megablock energy storage products are selling into AI data centers as grid buffers — Musk’s own xAI has bought roughly $1 billion of Megapacks to keep its training runs powered. That energy-storage strength is the one credible thread here. A Megapod that bundles Tesla’s power electronics, thermal management, and the enclosure — the “shell” around the chips rather than the chips themselves — would at least sit adjacent to a business Tesla actually runs.

The UK government is considering an Australia-style ban on social media for under-16s, with Prime Minister Keir Starmer saying that the ban could take effect as soon as spring next year. As for the much nearer future, Science and Technology Secretary Liz Kendall told BBC Breakfast earlier this week, “We will make further statements in July about VPNs and further restrictions.”

To be clear, no specific restrictions have yet been announced and Kendall sounded somewhat cautious about an outright ban during a parliament debate that took place the same day. “I have commissioned further research about their usage. There are really important issues to balance here,” she says. “Many people want to use VPNs for privacy — that is important — but we know that some children use them to get around restrictions. I will come back to that in July in our response to the consultation.” So, we’ll have to wait until next month for anything definite, but it’s hard not to feel like a full ban on VPNs is already on the table. If that does come to pass, more than the contents of my Bluesky inbox will be at stake.

Utah in the US has already tried to implement a full VPN ban (though this was postponed until September after Aylo, the parent company of Pornhub, challenged the law in court)… [T]he UK could just be the next domino after Utah, potentially setting off a chain reaction that affects users around the world.

Local news reports from around the country repeatedly detail police abusing the Flock surveillance system in order to stalk their partners or ex-partners. The contours of each story are much the same, with the police officer in question using their access to the system to repeatedly track a specific person over the course of weeks or months. The cases highlight the fact that Flock can be used to track the whereabouts of individual people, that police do not get a warrant in order to use the system, and that, if they have access to the system, they have the technical ability to look up any license plate they want for any reason they want. An April study by the civil rights group Institute for Justice found that at least 18 police officers have been caught around the country using Flock to stalk a romantic interest in the last few years; another database, called the ALPR Abuse Library, has documented 20 specific cases of “stalking/targeting” around the country.

The known cases of police stalking are almost certainly a vast underreporting of the overall abuse, because they largely include only cases in which the behavior was so egregious that it led to police officers being fired, arrested, or both. Flock told 404 Media that it is “aware of 15 incidents of abuse, each surfaced because of the transparency and accountability features deliberately built into our platform.... There are also 140,000 monthly active users of Flock, so the relatively rare instances of abuse, while obviously wrong and awful, are exactly that — rare,” a Flock spokesperson told 404 Media. [One in 10,000.] “Humans are fallible; unlike most tools society provide law enforcement, Flock ensures that in the instances when our technology is misused, the evidence used to hold responsible parties accountable, is right there in our system. We also encourage all our customers to have a usage policy, regular training, and to implement our Audit Assistance tool, which proactively flags unintended use....”

But it is also the case that Flock has strenuously fought against lawsuits and potential regulations that are seeking to require police to get a warrant to use the system. And many cases of abuse have not been detected by police departments themselves but by those private citizens, journalists, and stalking victims who have found patterns of abuse in public records files they have obtained from their local police departments. In most cases of Flock-related stalking reviewed by 404 Media, the abuse occurred over the course of months or years, and the victims were subjected to dozens or hundreds of lookups. Other abuse cases have been discovered using the website HaveIBeenFlocked.com, a website that compiles Flock searches released via public records requests and turns them into a searchable database. Flock has repeatedly tried to get that website taken down, as we have previously reported.

Linux 7.2’s merge window closed out a cleanup campaign on Friday that most kernel developers had stopped expecting to see end: the complete removal of strncpy(), a C string-copy function that the kernel’s own documentation labels “actively dangerous,” from every subsystem, driver, and architecture-specific file in the kernel source tree.

The merge landed June 20, 2026. After around 362 commits spread across six years of incremental work, no call site using the function remained, and the function itself — including the last per-CPU-architecture optimized implementations — was struck from the source. The removal matters beyond housekeeping. strncpy() is a persistent source of a specific class of memory error: kernel buffers that contain sensitive data can leak bytes past an unterminated string boundary, a pattern that enables memory disclosure vulnerabilities. Eliminating the function from the tree removes that entire class from the kernel’s attack surface — and, critically, makes strncpy() unavailable to any future contributor, turning a best-practice suggestion into an enforced policy.

In place of strncpy, Linux kernel code should use strscpy() for NUL terminated destinations, strscpy_pad() for NUl-terminated destinations with zero-padding, strtomem_pad() for non-NUL-terminated fixed-width fields, memcpy_and_pad() for bounded copies with explicit padding, or memcpy() for known-length memory copies.

The original function obscured all of those differences under a single ambiguous name. The 362-commit campaign to replace it was, in effect, a codebase-wide audit that forced every call site to declare its actual intent in code That is an engineering outcome with lasting value: the kernel’s string-handling semantics are now explicit where they were previously implicit, and future maintainers can read a function name and understand what a copy operation actually does.

A group of companies that specialize in tracking international shipments of sensitive technologies is backing a Capitol Hill bill that would require America’s most powerful AI chips to incorporate stronger security mechanisms aimed at preventing the chips from reaching China and other adversaries. The letter, signed by six companies, says the Chip Security Act (CSA) would increase American chip companies’ competitiveness and close key loopholes in the U.S. export control regime.

The move clashes with claims from semiconductor lobbying groups that the requirements would constrain America’s booming chip industry. Sent to congressional leadership Thursday morning and seen by NBC News, the dispatch instead argues that more robust security verification would assure chip customers and manufacturers that they are abiding by sensitive restrictions on chip sales. The companies argue that the boosted confidence will “lead to increased sales, faster export approvals, larger transactions, greater access to new markets, and more expansive chip deals.”

Despite U.S. export control laws banning sales of advanced AI chips to certain countries, including China, loopholes in current requirements have allowed billions of dollars’ worth of America’s best AI chips to be sold to entities in third-party countries that can then forward them to China. In just one case in March, the Justice Department charged three people with conspiring to forward $2.5 billion of AI chips to China. The CSA aims to address those loopholes, mandating that chip exporters better track where advanced chips are sent, via either bespoke location-verification hardware or software that can run on existing hardware. That, bill proponents claim, would ensure that sensitive chips could be sold to countries like Malaysia or Indonesia without fear of further transfer to China… Experts say that because chips perform the advanced computations required for frontier AI systems, cutting off access to the chips is crucial to prevent geopolitical rivals from using AI systems for military or economic purposes.

Much of this comes back to a single shift: Automated tooling (much of it now built on large language models) has gotten good enough to surface real vulnerabilities in open source code quickly and at scale. That is useful, and several large Rust projects have already received and fixed credible issues found this way. The same tooling has also made it trivial to generate vulnerability reports that look plausible and are worthless. Maintainers across the ecosystem are losing real hours sorting these from the reports that matter, and the noise tends to bury the signal.

So, with funding from the Alpha-Omega Project, the Rust Foundation is bringing on a full-time AI Security Engineer in Residence dedicated to the Rust ecosystem. This position is being funded with part of the $12.5M in open source security funding that the Linux Foundation announced in March. The role exists to take pressure off maintainers. The person in this position will use a mix of human-led and AI-assisted methods to proactively review Rust itself and the crates the ecosystem leans on most and help us separate real, exploitable issues from false positives and low-signal noise before anything reaches a maintainer…

This role will run full-time for six months to start, with room to extend depending on what we learn and the funding available. Methods, playbooks, and prompts will be documented so the work doesn’t end with the contract. We are grateful that Rust is not embarking on this work in isolation. Several other ecosystems have received parallel Alpha-Omega grants for the same kind of work (e.g., the PHP Foundation and the Drupal Association) and we plan to share tooling, triage practices, and what we learn rather than duplicating work