SoylentNews

Arthur T Knackerbracket writes:

The custom build from Microsoft's Chinese joint venture was scheduled to retire in February 2027:

China Reportedly Orders State Agencies To Uninstall Its Government-Only Edition Of Windows 10 — Beijing Accelerates Planned Retirement Over Data Security Concerns

The affected software is the government edition developed by C&M Information Technologies (CMIT), a joint venture set up in 2016 between Microsoft and state-owned China Electronics Technology Group, with the Chinese side holding the majority stake. The build is based on Windows 10 Enterprise but strips out OneDrive and other consumer-facing components, disables certain native functions, keeps updates and activation inside China, and lets government users substitute Chinese encryption algorithms for Microsoft's standard cryptography. China Customs and Shanghai's Commission of Economy and Informatization were among the first pilot customers when the edition launched in 2017.

Beijing banned Windows 8 from government procurement in 2014, ordered a three-year replacement of foreign PCs in government offices starting in 2019, and in 2022 told central agencies and state firms to scrap foreign-branded computers entirely. The domestic stack built to absorb that demand now includes Kylin V10, UnionTech's UOS, and Huawei's HarmonyOS 5 laptops, and it reaches down to the silicon in systems like Huawei's Qingyun desktops running the homegrown Kirin 9000X.

StatCounter's traffic data shows how little of that campaign has reached the consumer market. Windows accounted for 87.64% of Chinese desktop web traffic in July 2026, and Windows 10 alone still made up 43.56% of Chinese Windows usage, compared with 50.01% for Windows 11, ten months after mainstream support ended. Roughly two in five Chinese desktops are currently running an unsupported Microsoft OS, the gap that CMIT's edition was meant to close for government users.

It's not clear what the scope of the new directive is, with Bloomberg's reporting covering “some” state-linked entities. CMIT didn't respond to the outlet's request for comment.

Original Submission

Atlassian, a software company, is planning on building a new tower in Sydney called Atlassian Central at a cost of $1.4 billion and standing tall at 180 metres. With Australia in the grip of a WFH age of enlightenment this construction is truly an outlier.

Co-founder and CEO Mike Cannon-Brookes said the primary objective was to "self-fund further investment in AI and enterprise sales" while strengthening the company's financial profile.

[...] Asked about the tower's occupancy and purpose after laying off hundreds of employees, the company gave news.com.au a fascinating insight into how working in the tower will play out day-to-day.

Gina Creegan, Atlassian's head of workplace, said the tower has been designed for the "future of work from day one".

"The timber habitats bring that vision to life, connecting spaces that are purpose-built for how we work," she said.

"Instead of traditional desk rows, workspaces are designed around distinct modes of work: deep focus, collaboration, social connection and recharge."

It is understood that each of these states of work will have its own dedicated floors inside the building — with focus rooms, sprint rooms, small meeting rooms and customer and event spaces across dedicated floors.

They're also designed to feel like vertical neighbourhoods, with park floors, terraces and natural materials designed to give space to reset between different modes of work.

The idea is that workers will move between these sections of the building throughout the day rather than sitting at one assigned desk.

Under the company's "Team Anywhere" policy, it's understood there will be no attendance quotas or a mandated number of office days, so the building will not be built for a fixed attendance target or desk per employee ratios.

Original Submission

One of the great hopes for BEV development has been solid-state / Lithium-metal batteries. No goo in the electrolyte, ~double the energy density of Li-ion batteries and faster charging to finally end the BEV range discussion. Looks like this is still in the future. MotorTrend has a summary of current development activity at a variety of battery and car companies. Here's a sampling, many more at the link: https://www.motortrend.com/features/solid-state-batteries-future-cars

... perhaps the industry's biggest shift during the past two years is that the race has become less "solid-state versus liquid-electrolyte lithium-ion" and more "semi-solid first, all-solid later." This effectively delays resolution of the toughest challenges—like how to keep a solid electrolyte/separator in sufficiently intimate contact with the electrodes to work properly (which often requires high pressure). Today, semi-solid architectures are already bringing significant benefits to vehicles, while pure ceramic/sulfide lithium-metal batteries (which claim the wildest range/recharging stats) remain years away. Here's a roundup of the leaders:

Battery-swapping Chinese automaker Nio produced 150-kWh WELION semi-solid-state packs boasting 260-Wh/kg energy density in 2024. The idea was for owners to rent these packs for long trips, but low demand halted production after a few hundred were produced.

China's SAIC teamed with battery supplier QingTao Energy to produce a semi-solid-state pack for IM Motors' L6 Lightyear Max. Its 130-kWh pack is rated for 621 miles of (CLTC) range, recharging 249 miles' worth in 12 minutes at 400 kW.

Toyota is working with Idemitsu Kosan to develop an all-solid-state cell using an undisclosed high-energy cathode, a sulfide solid electrolyte, and an undisclosed (likely lithium) anode. A pilot electrolyte plant is under construction, and the supply chain is being built.
[...]
Samsung SDI is working with BMW and others on a reportedly oxide-based all-solid-state anodeless/lithium-metal design with a high-nickel cathode. A pilot production line is running, with production gearing up for an announced target of 2027 mass production.

VW Group's PowerCo has teamed with QuantumScape to develop a novel cell design using a pure copper current collector that plates lithium metal during its first charging cycle, a solid ceramic separator that prevents dendrite growth from the anode, and a liquid catholyte that maintains contact with the cathode particles under roughly 50 psi of stack pressure. It's been demonstrated in a Ducati motorcycle, and manufacturing license agreements are signed.
[...]

I'm sticking with my older ICE cars for now. As well as quick fill-ups, they are also pre-touch screen and much of the other recent slop (IMO) that has been added to basic transportation.
There are hints that some car companies are coming to their senses and going back to actual knobs and buttons, after realizing that a touch screen is not the right user interface for a moving vehicle. If that continues, I might be in the market for a new car again (the last new car I bought was in 1992).

Original Submission

Arthur T Knackerbracket writes:

Destroying books to train AI models is 'all' the Vegas warehouse does:

An operation exposed by an AirTag

Employees who spoke to 404 Media said they spend their time at the facility cutting the spines off of books and feeding them into a scanner. VGT3 is reportedly part of another, larger facility in Las Vegas called LAS8. Its purpose, according to the employees who spoke to 404 media, is solely to cut the spines off books and scan them. "All we do is scan books," one employee told the outlet.

Often, these large orders contain a scattershot of different books. An independent bookseller in Ireland, for example, received an order for 5,000 books that they suspected was for training AI. “Some was high-quality non-fiction, like A History of Connemara, and the next thing might be The Eddie Hobbs Guide to your SSIA,” Tomás Kenny of Kennys Bookshop said at the time. 404 Media says that employees at VGT3 are required to scan the ISBN (barcode) of each book, lending credibility to the theory that AI companies are working through a list of every book that has ever been published.

Or, at least, every book with an ISBN. A bookseller told 404 Media that these large orders "never" include rare books that don't have an ISBN.

Earlier this year, court filings revealed Anthropic's 'Project Panama,' which kicked off in 2024. Documents as part of those filings make the project's purpose clear: "Project Panama is our effort to destructively scan all the books in the world," said an internal planning document. A judge ruled that Anthropic was allowed to use books to train its AI models. However, it was fined $1.5 billion for keeping 7 million pirated books in a central library. In a 2025 lawsuit against Meta, it was revealed that it had pirated nearly 82TB of books.

Scanning books en masse is nothing new. In 2005, Google spearheaded Google Books by scanning out-of-copyright titles from an on-campus library using specialized scanners. The books were then returned. Presumably, Google made use of some type of V-shaped scanner, which lays a book out naturally so as not to disturb the spine and binding.

In the case of VGT3, 404 reports that employees cut off the spine of the book before scanning, presumably to feed the pages flat into an industrial scanner. The insatiable hunger for data in frontier AI models seems to be moving at a faster pace than Google's early book digitization efforts.

It's hard to say why a facility like VGT3 operates in this way, though it likely comes down to cost. As major companies like Meta and Anthropic have been caught with a library of pirated books, they now need to buy them. And when purchasing thousands of books at a time, it's probably much cheaper to get secondhand copies from marketplaces like Biblio than it is to spend full price on digital versions of those books (if digital versions exist in the first place).

Original Submission

Arthur T Knackerbracket writes:

Secret parameter allowed hackers to steal passwords when a target clicked on a link:

It's not every day that attackers can force a frontier AI model to cough up user passwords and other sensitive data without user confirmation. That's exactly what researchers recently did to Microsoft 365 Copilot Enterprise. Even more unusual is the source they tapped to discover the critical vulnerability that made their exploit possible. Rather than employing reverse engineering or other traditional vulnerability-hunting methods, they asked Copilot. The LLM assistant readily complied.

Researchers at security firm Varonis knew they wanted to create an exploit that would exfiltrate user data when a user did nothing more than click on a link. Like most AI assistants today, Copilot steadfastly refused and made clear that sensitive prompts like that require explicit user consent in the form of a gesture, such as pressing a return key or other key. In response, the researchers peppered Copilot with questions about the guardrails that required user confirmation before the assistant can execute powerful commands.

The dialog was like a game of 20 questions. Each answer provided a new clue that divulged information about the complex safety mechanism. Why was auto-execution impossible, they asked. What URL structures and deep links were involved? What happens when a page is loaded with input already in the prompt field? Each answer provided a deeper view into the guardrail and its limits. Eventually, Copilot provided a stunning Microsoft trade secret—an undocumented prompt parameter that completely bypassed the requirement for user consent.

"At the beginning, Copilot kept refusing, but every refusal revealed technical details about its internal architecture," Varonis Senior Researcher Lior Adar said in an interview. "Copilot eventually disclosed undocumented parameters. I took those parameters and used them for prompts for running automatically."

The parameter was the string ?autorun=1. When accompanied by the separate, well-known parameter ?q=, the researchers' prompt silently fired the moment the target clicked on the malicious URL. Microsoft silently mitigated the vulnerability in February, three months after Varonis reported it, by no longer allowing ?q= to inject text into the chatbot input. The user instead had to click and type manually, a requirement that prevented third-party browser integrations from using the parameter as intended. Microsoft introduced more comprehensive fixes on Tuesday.

Like most AI assistants, Copilot can receive prompts that are embedded into a URL. The base part of the URL can allow the LLM to open, say, Gmail. Parameters and text to the right in the URL can then instruct the assistant to summarize inbox contents or begin drafting a new message. As noted already, the commands aren't supposed to execute without user approval.

With the Copilot revelation of the undocumented parameter, the researchers now had a simple means to circumvent the protection and inject a prompt directly into Copilot. The format of the URL looked like this:

https://copilot.microsoft.com/?q=&autorun=1

canopic jug writes:

Developer Bradley Taunt has written up an overview Raphael Sadowski's recent changes to OpenBSD's HTTP daemon aka httpd(8):

Running relayd alongside httpd on your OpenBSD web servers is no longer necessary for injecting HTTP security headers. Thanks to the incredible work by rsadowski@ we now have the ability to set our security headers directly inside httpd. Pretty awesome, right?

See also the manual page for the configuration file httpd.conf(5).

Raphael himself wrote about his work related to the ongoing evolution of relayd(8) and httpd(8) a few weeks ago:

That mirror inspired me to create my own. I wanted to make it easier for new and young contributors. I also wanted to reach the community beyond the OpenBSD mailing lists. Also, I work on a git mirror of the CVS tree. (CVS and I will never be friends. I started my career with SVN, which was painful enough. No more version control pain.)

Development happens primarily on the Gothub instance. The other locations are kept in sync: [...]

The OpenBSD project has continued to emphasize portability, standardization, correctness, proactive security, and integrated cryptography for over 30 years. Several important projects seen outside OpenBSD, such as OpenSSH, also stem from the project.

Previously:
(2026) 'Please Do Not Vibe F--- Up This Software': Broken Backups Spark AI Coding Row in Rsync Project
(2023) Detailed Notes on Working With OpenBSD on a ThinkPad X270
(2023) Privilege Drop, Privilege Separation, and Restricted-Service Operating Mode in OpenBSD
(2022) Fuzzing Ping(8) ... and Finding a 24 Year Old Bug
(2021) Recent and Not So Recent Changes in OpenBSD That Make Life Better
(2020) The OpenBSD Project's 25th Anniversary
(2018) OpenBSD on a Laptop
(2018) OpenBSD Chief De Raadt Says No Easy Fix For New Intel CPU Bug
(2014) OpenBSD Developers Fork OpenSSL, Create LibreSSL

Original Submission

Arthur T Knackerbracket writes:

https://www.theregister.com/software/2026/08/18/tim-king-amigados-royalty-dies-aged-70/5289101

According to an AmigaNews report, King's family said he passed at the end of July. King was a superb programmer – although he accomplished rather more than that.

His most widely experienced work was a key component of the original Commodore Amiga's operating system. His port of Cambridge University's TRIPOS OS to the Motorola 68000 CPU became AmigaDOS. His rapid work getting it running on prototype Amiga hardware helped Commodore launch the machine in 1985 after its in-house OS project failed to deliver. As he put it himself: "As a result I have the distinction of having written software used by over 2 million users."

TRIPOS is not well known today, although its Wikipedia article provides a useful overview. King did not create TRIPOS: it was written by Cambridge boffin Dr Martin Richards. TRIPOS was written in the BCPL programming language, which Richards also created. The first recorded "hello, world" example was written in BCPL, which was also used to develop software for the Xerox Alto. Today, however, it is mostly known as the immediate ancestor of the C programming language. This page of scans from Australian Personal Computer magazine gives a good description of TRIPOS.

While a researcher at the University of Bath, King ported TRIPOS from the DEC PDP-11 to the new Motorola 68000 CPU. His next job was at Bristol-based 68000 development tools specialist MetaComCo. For that company, he adapted his new 68K version of TRIPOS to the SAGE IV machines that MetaComCo used.

Meanwhile, Commodore was developing the Amiga in the US, but its in-house operating system for the new hardware, known as CAOS, was badly behind schedule. Commodore went looking for outside help, and it approached MetaComCo, as this Nosher.net potted history documents.

owl writes:

https://fabiensanglard.net/quake_shareware_cd/index.html

In the mid-90s the coolest thing to buy for a PC, besides the incredibly expensive Intel Pentium, was a CD-ROM drive. With their capacity of 640 MiB (three times the storage of PC HDD at the time), CDs allowed enthusiasts to step into a world of multimedia, made of high-resolution 640x480 256 colors palette-indexed photos[1], VOC soundtracks, and play with Video For Windows butter-smooth 12 fps 240x179 videos[2][3] lasting up to several seconds.

...

By June 1996, after three years of hard work, id Software had completed their next title, Quake. As for their previous title, they were going to release both a shareware version and a full version of their game. Since it used a mere 22 MiB of storage, people at id Software had the idea of leveraging the remaining capacity of a CD-ROM. Why not include encrypted versions of the full id catalogue of games? Not only this would cut out the middlemen, it would give instant access to gamers with a simple phone call and a credit card.

The concept was implemented. The CD was announced[4] on July 3, 1996 and released on August 30th[5]. The hacker group GNOMON released Quakecrk.zip only 39 days later[6]. The archive contained QCRACK.EXE, a tool allowing to decrypt every single game on the CD-ROM.

Original Submission

hubie writes:

A tiny UK-developed satellite, roughly the size of a small carry-on suitcase, could help answer one of the biggest questions in cosmology:

An international team of scientists, led by the University of Cambridge, will use the dark side of the Moon as a 'shield' so that the satellite – called CosmoCube – can block out all the noise from Earth and listen for a faint whisper from the very early universe.

This whisper, known as the 21-centimetre line, is a signal emitted by hydrogen atoms in the period between the afterglow of the Big Bang and Cosmic Dawn, when nuclear fusion lit up the first stars. No one has directly observed this era before.

Detecting this signal from more than 13.5 billion years ago is extremely difficult with Earth-based telescopes, since the Earth's ionosphere blocks the right frequencies, and interference from FM radio, satellites and telecommunications drowns it out.

However, the Moon provides a natural shield. As CosmoCube orbits the far side of the Moon, it will be shielded from all the noise of Earth for roughly 40 minutes of each two-hour orbit. Over an expected two-year mission, it will build up 1000 hours of data on one of the last unexplored periods of the universe, helping us understand how the universe transitioned from dark and nearly empty to the complexity we see today.

[...] "This emission from hydrogen after the Big Bang, but before the first stars, will hopefully allow us to understand the role of dark matter in the early universe, how it worked to pull together hydrogen into the first stars and galaxies," said lead author Professor Eloy de Lera Acedo from Cambridge's Cavendish Laboratory.

To study this period, CosmoCube will operate at extremely low frequencies – between 10 and 50 MHz – far outside the range of ground-based telescopes, which is why the Moon will be used as CosmoCube's 'fortress of solitude'.

"There's no other place where you can get the sort of shielding you need to detect such a faint signal, while at the same time looking at the whole of space," said de Lera Acedo, who is also affiliated with the Kavli Institute for Cosmology. "The far side of the Moon is really the only option: it solves multiple problems at once, opening a clear window to the very early universe."

Once in orbit around the Moon, CosmoCube will unfold a long and lightweight radio antenna, sensitive enough to detect the 21-centimetre signal from hydrogen atoms in the early universe when the satellite is on the Moon's far side

[...] "Aside from the science, what makes our mission unique is its size: we're probing the earliest, deepest parts of the dark ages that others don't reach, but with a compact, relatively low-cost platform," said de Lera Acedo.

However, the far side of the Moon may not stay quiet for long: other missions are being planned by the US, India and other countries to take advantage of the Moon's silence.

Journal Reference: de lera Acedo, E., Bacon, D., Grainger, W. et al. The CosmoCube lunar mission for probing the dark ages and cosmic dawn via 21-cm cosmology. Nat Astron 10, 1097–1106 (2026). https://doi.org/10.1038/s41550-026-02946-y

Original Submission

Arthur T Knackerbracket writes:

https://www.tomshardware.com/tech-industry/cxmt-overtakes-tencent-to-become-chinas-most-valuable-company-17-days-after-its-ipo

Memory Maker CXMT Overtakes Tencent To Become China's Most Valuable Company 17 Days After Its IPO — Now Worth $524 Billion

Tencent reported second-quarter revenue of RMB 204.8 billion ($30.3 billion) on Wednesday, up 11% year-over-year, with capital expenditure climbing 176% to RMB 52.8 billion as the company bought computing capacity for its AI models and agents. Free cash flow went negative at RMB 13.8 billion. Tencent's U.S.-listed shares dropped 5.34% following the report, extending a decline that's reached 26% so far in 2026, even as domestic games revenue grew 17% and marketing services revenue rose 22%.

CXMT held 7.67% of the global DRAM market in 2025, according to sales figures in its IPO prospectus. Its $524 billion market cap now sits at roughly half of Micron's $1 trillion and about 60% of SK hynix's $880 billion, and the company plans to close the output gap with a sixth mega-fab and a 30% DRAM share target by 2030, though it still lacks the EUV lithography tools its rivals use.

CXMT swung to an operating profit of 35.43 billion yuan ($5.2 billion) in the first quarter from a 2.83 billion yuan loss a year earlier, riding DRAM prices that have climbed throughout the ongoing memory shortage. The company became the first semiconductor firm to top mainland China's stock market in its 35-year history when it listed on July 27, raising $8.6 billion in an IPO whose retail tranche was 212 times oversubscribed.

Analysts remain far apart on whether CXMT’s ranking holds water, however, with Nomura's price target of 116 yuan implying further upside, while Morningstar's fair value estimate of 14.90 yuan puts the stock at more than three times what the firm thinks it's worth.

Luke James is a freelance writer and journalist.  Although his background is in legal, he has a personal interest in all things tech, especially hardware and microelectronics, and anything regulatory. 

Original Submission

hubie writes:

Scientists are increasingly relying on powerful data sources and tools that they often cannot fully understand, inspect or verify, according to a new study:

State-of-the-art tools and data like artificial intelligence (AI), satellite imagery, online data and digital sensors are revolutionising the way scientists study the natural world.

But such systems effectively operate as scientific "black boxes" that can increasingly challenge the trust in science.

The new study, by an international team of scientists and available here, addresses the problems of reproducibility, trust and the future of scientific research in an era when critical technologies can shape science and influence knowledge without being fully open to scrutiny.

These technologies can process enormous amounts of information, monitor biodiversity and threats across continents, and reveal patterns that would once have been out of reach.

"However, many of these tools represent true black boxes, by keeping the processes behind those results largely hidden," said Ivan Jarić, researcher from the University of Paris-Saclay, and lead author of the study.

"They are often owned by private companies that intentionally limit access to information about how their systems operate or process data, guided by proprietary constraints and commercial aims".

The paper identifies several types of black boxes that are becoming widely used in ecology and conservation.

One of the most prominent examples are large language models and other AI technologies, increasingly used to analyse massive datasets, interpret satellite imagery, and model ecosystems.

However, researchers often have little or no access to the data used to train these systems, the underlying algorithms, direct system testing, or understanding how and why they generate particular outputs.

fleg writes:

https://www.forbes.com/sites/jonmarkman/2026/08/13/claude-just-broke-a-math-record-that-stood-for-37-years/

"Number theorists spent 37 years moving one number by less than a single percentage point. The number is the proven share of the Riemann zeta function's zeros that sit on the critical line, the place where one of the most famous unsolved problems in mathematics says all of them belong. Decades of human refinement had carried it to 41.6%. On August 10, Anthropic published a result from an unreleased research version of Claude that moved it to 67.2% in roughly a day and a half.

The Riemann hypothesis has been open since 1859. It predicts the hidden structure behind how prime numbers are distributed, and it carries a million-dollar Clay Institute bounty. The hypothesis itself remains open. What Claude established is that at least two-thirds of the zeros behave the way it predicts, the largest single advance in the record's history."

Original Submission

hubie writes:

"Always finish your antibiotics" is no longer considered medical best practice for all conditions:

Surprised? You're not alone.

A new study has found that almost 90% of Americans believe that it's always best to take the full course of antibiotics, even when you feel better—consistent with long-running but now outdated health campaigns. The reality is more complicated. Sometimes shorter courses are safer, and sometimes longer courses are best.

The survey demonstrates a need for better communication between doctors and patients about what's healthiest.

"Historically, there was very strong guidance by major health organizations and clinicians that you must always finish the course," says Alistair Thorpe, PhD, research assistant professor of population health sciences at University of Utah Health and first author on the study. "Now, we're seeing a growing body of evidence saying that that is not always the case. And oftentimes, shorter durations of antibiotics are as effective and safe as longer alternatives."

[...] One of the main reasons people gave for preferring longer antibiotic courses was that they had been told to "always finish their antibiotic course"—88% of respondents had heard of, and agreed with, this common mantra. Most had been told this by their clinician, and many had also heard it via a public health campaign.

A strong body of scientific evidence shows that, for many common infections, shorter courses of antibiotics work as well as longer courses and are less likely to cause side effects. Still, there are some cases, like tuberculosis, where longer courses are most effective.

The study authors suggest that doctors and public health campaigns use several evidence-informed strategies to better communicate the complex reality of antibiotic course length—for instance, avoiding overly simplistic claims that either shorter or longer courses are universally better, and acknowledging that as scientific evidence accumulates over time, health recommendations can change.

[...] "Discuss with your clinician what the right duration is for you and when the right time is to stop your course," Thorpe says. "Getting advice directly from a clinician on a one-to-one basis about what is most appropriate for you in that situation is the right way to go."

Thorpe emphasizes that the changing recommendations are a positive outcome of increasing knowledge.

"Evidence is growing and guidance is evolving on antibiotic use, which is a normal process and a good sign that we are working to improve how we provide care," he says. "Our knowledge about how best to use antibiotics has changed, but it has changed because we're learning more, and it's important that we make sure we are communicating this well to the public."

Journal Reference: Alistair Thorpe, Rachael A Lee, Julia E Szymczak, et al. US Adults' Perspectives on Antibiotic Durations and Adherence to Therapy for Common Bacterial Respiratory Infections: A National Survey, Open Forum Infectious Diseases, Volume 13, Issue 7, July 2026, ofag407, https://doi.org/10.1093/ofid/ofag407

Original Submission

hubie writes:

The mashup of a black hole and an enormous star has never been seen before and could explain the mysterious little red dots often found in deep-space images:

Astronomers at MIT and elsewhere have spotted an extremely bright red spot in the early universe. The object resembles an enormous star, spanning the size of our solar system. But it also is putting out 100 billion times more energy than any known star can physically produce. In fact, such energies are closer to what a black hole might generate.

The curious combination suggests that the red spot is an entirely new type of astrophysical source. The astronomers are calling it a "black hole star."

In a paper appearing today in the journal Nature, the team presents their analysis of the new object, which they discovered using NASA's James Webb Space Telescope (JWST). The telescope spotted the bright red dot in the very early universe, just a few hundred million years after the Big Bang.

The scientists conclude that the most likely explanation for the strange red dot is that it is a mashup of a black hole and a star — a combination that has never been observed until now. The object is likely a hugely dense cloud of gas, powered not by standard nuclear fusion, but by a central black hole.

"Our picture of this object is evolving very rapidly," says lead author Rohan Naidu, a NASA Hubble Fellow and Pappalardo Fellow at MIT's Kavli Institute for Astrophysics and Space Research (MKI). "We think there is a central black hole that is 100,000 times as massive as the sun. And around this black hole, there would be this very extended envelope of gas that looks like a star the size of the solar system. It's huge."

If the bright red dot is indeed a black hole star, it would help to solve the identity of other mysterious "little red dots" that have appeared in nearly every deep space image JWST has taken to date.

"These little red dots seem to be everywhere in the early universe but essentially disappear by the present day," Naidu says. "What exactly these objects are has been one of the most debated topics of the JWST era."

[...] "When we see something very red in the universe, we often assume that it is surrounded by dust, like soot or ash," Simcoe explains. "The same way that the wildfire smoke from Canada recently made the sky in Boston look bright red, astronomical objects can also appear redder than their intrinsic color when you see them through a veil of dust."

But there were other signatures in the light that didn't quite match up with what physicists expect from dust. The team also observed another strange pattern: The dot's light was extremely bright, except below certain wavelengths, where the light completely disappeared.

"fab23" writes:

If the Markets Reject OpenAI and Anthropic, the US Should Nationalize Them:

This essay was written with Nathan E. Sanders, and originally appeared in The Guardian .

If the Markets Reject OpenAI and Anthropic, the US Should Nationalize Them

OpenAI, and then Anthropic , were each formed by AI developers who feared unrestrained corporate AI development—specifically, that companies like Google and Meta would steer the technology towards deleterious, maybe even catastrophically unsafe, outcomes for society. Their founders proclaimed that their new labs, uniquely, could be trusted to develop the technology in humanity's best interest. But each, in turn, were themselves co-opted by the same market incentives, themselves becoming corporate behemoths zealously guarding future investor value rather than the public interest.

It was only a few weeks ago, in June, when OpenAI and Anthropic each filed for their IPOs and were met with buzz about trillion-dollar valuations. The hype around their valuations is so extreme that many worry about their potential for concentrating wealth on a global scale. In an effort to leave something for the rest of us, some observers have proposed that the federal government seize a share of these companies' stock to create a US sovereign wealth fund , or redistribute their revenues to produce a dividend for taxpayers.

Now the headlines are about public backlash to AI datacenters and the AI chip giant Nvidia's slumping stock. The tech and AI giant SpaceX's newly minted stock price tanked just weeks after its IPO. There are even questions about whether the leading AI labs will ever be sustainably profitable . All of a sudden, the makers of ChatGPT and Claude face strong headwinds as they seek to generate the massive equity assets that once felt all but assured.

In fact, evidence suggests the market itself could reassess that these companies offer nothing of financial value. In that case, perhaps we can return them both to their original purposes. If these AI companies should fail in the financial markets, the US should nationalize them and convert them into national labs operated under democratic control that preserve their benefit to the public interest.

The economics of the big AI labs hardly guarantee a booming return on investment. Frontier AI models are both expensive to train and depreciate within months, when a newer model appears. This means that the payback window to extract profit from them is very narrow. Meanwhile, enterprise clients are getting smart about minimizing AI token usage. Even worse, the models are basically commodities; the best ones largely perform and behave similarly, which depresses prices. Perhaps most importantly, open-source and Chinese competitors— lagging only a few months behind the leading labs in capability—give away for free the kinds of models Anthropic and OpenAI sell.

Even setting aside the model training costs, it's not clear whether the unit economics of AI as it's currently conceived will ever be sustainably profitable. Many of these free and open-source models can be run locally: the large ones on private clouds and high-end servers, the smaller ones on anyone's laptop or even cellphone, putting to question the companies' exorbitant capital investment in datacenters.

It's not that OpenAI and Anthropic are not valuable as organizations. They have remarkably talented AI scientists and engineers that are continuously producing innovations driving a global mania for their offerings. These leading labs might not ever be profitable, but their products are doing a lot of good in the world. You may or may not be a user of or believer in their technology, but their staggering, ongoing usage growth suggests that an awful lot of people would be disappointed if the companies simply disappeared.

The problem isn't the people or the products, it's the system. As constituted, OpenAI and Anthropic may not be valuable as market equities. If the market assesses they are not capable of producing a growing financial return on investment for shareholders, the companies will collapse.

Maybe private, for-profit is just not the right economic model under which to develop AI. Perhaps OpenAI should be returned to its private non-profit roots, the legacy they fought so hard to change and which Anthropic's founders spurned . Or possibly both could be reorganized as research centers at universities, returning to academia the scores of high-profile research faculty they have poached .

But a better outcome for society would be to establish public ownership and operation of their product-oriented capabilities. Turn OpenAI and Anthropic into US government agencies producing AI as a public good.