In some instances, having a user copy and paste the salient bits of the email they are responding to might not be such a bad thing. We’ve all had emails that required epic amounts of scrolling to find what started the conversation, so forcing users to think about what they actually need to include is no bad thing. However, disrupting user workflows without warning — well, that is undoubtedly a bad thing.

This is, after all, one of the most basic things an email client needs to do, so shipping a product with a bug that breaks this functionality says more about Microsoft’s approach to quality than anything else.

Following the revelation, social media was deluged by comments from AMD consumers decrying the move. They noted that AMD’s quiet removal of TSME after supporting it for so long seemed underhanded. The move came solely as a result of firmware changes made in a recent update. With no physical changes required to silicon, continued support was largely, if not purely, a matter of will rather than a necessity required by changes to hardware. The critics called on AMD to reverse the move.

Over the weekend, AMD said it planned to do just that in a firmware update scheduled for release next month. More often than not, the chipmaker refers to TSME as Memory Guard. “Regarding certain non-PRO Ryzen 9000-series desktop processors, a BIOS option to enable Memory Guard was previously available but was removed in a recent update,” AMD said in an email. “Based on valuable community feedback, we will reinstate this option in an upcoming BIOS release in July.”

The company has yet to explain why it removed the protection. Critics speculate that AMD dropped it in an attempt to steer customers toward more costly CPUs. It’s possible, though, that there were less nefarious reasons, such as the difficulty of continued support as chip designs changed. Another possibility is that AMD made the move for performance reasons. Encrypting and decrypting data in memory creates latency. Slowdowns are the enemy of gamers, one of the more popular customer segments using the 9000-line of Ryzen processors. Since many gamers already voluntarily disabled TSME and had little need for it in the first place, AMD may not have considered the change of much consequence.

Valve says that “starting with the SteamOS 3.8 release, you can put together your own Steam Machine using whatever PC parts you want.” SteamOS 3.8.10 launched last week with a slew of updates, including “improved compatibility with recent Intel and AMD platforms.” Alongside that improved compatibility, Valve is giving gamers the green light to install SteamOS on their own desktops. In an interview with The Verge, Valve’s Pierre-Loup Griffais said Valve has been “rolling out improvements to [SteamOS] so it’s more compatible with desktop hardware,” including eventual support for Nvidia graphics. Griffais says Valve has “a growing team” working on Nvidia driver support for SteamOS, adding, “We’re collaborating with Nvidia very closely.” While he mentioned that Nvidia support might not come this year, Griffais emphasized that “it’s certainly something that we’re working on in the background.”

It’s technically been possible to run SteamOS on your own hardware for a while now, but compatibility has been mostly limited to AMD systems. So far installing it has also required using a Steam Deck recovery image, a process that, speaking from experience, is much less straightforward than the installation process for most other Linux distributions. Trying to run SteamOS on Intel or Nvidia hardware has not been easy so far. According to Griffais, Valve is working to change that, which could mean that down the line, you’ll be able to run SteamOS on just about any gaming PC hardware you want, including Nvidia.

For the more immediate future, Griffais says SteamOS in its current state should offer a “good experience” on console-like PC setups: “If you have something that is similar to the use case of a Steam Machine, where you have a PC that’s gonna be plugged into a TV, and has a single hard drive that you’re not going to try and dual boot [] you can put SteamOS on there, and you’ll have an experience that is very similar to a Steam Deck docked or a Steam Machine, with some caveats, of course,” like a lack of HDMI-CEC support. But “the core bits of the experience are there. The SteamOS graphics driver, the shader precompilation […] you can get at all of that with the SteamOS.”

A24 partner Scott Belsky, who leads the studio’s technology division A24 Labs, told the Journal the studio’s Google partnership differed from other deals because AI developers mistakenly advertised their products as a means to make films cheaper and faster. His division is developing applications for AI-generated storyboards, another reimagination of the production process that has seen filmmakers like Martin Scorsese rubber-stamp.

As Big Tech dumps billions of dollars into America’s data center buildout, a slew of opportunities have opened up to the electricians wiring these massive facilities. In some cases, the scale of the projects and the demanding construction timelines are fueling talent wars for the industry’s best and brightest. The US-based International Brotherhood of Electrical Workers (IBEW) has argued that its workers are “powering the AI Revolution,” and a set of “Data Center Principles” published in March argues that union labor is “essential to the future of AI.” Tech companies are trying to meet the moment: Meta recently announced a skilled trade academy program, and Google committed $50 million to help train people in skilled trades.

But amid growing national opposition to data centers, debates over the ethics of the massive buildout have started to pop up in some online pockets of the community. Threads about how AI will affect the economy now pepper r/electricians, a subreddit with around half a million monthly visitors. Some users wonder whether the work will eventually prompt widespread job losses. Others aren’t sure if their labor makes them complicit in the damage done to local communities or whether it’s unethical to take on data center work. For some, the answer is a firm no. Ultimately, they argue, work is work.

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.