At the heart of the announcement is NanoStack. This is a three-dimensional, nanosheet-based transistor design that scales vertically, or along the z-axis, by stacking and staggering CMOS devices. Unlike today’s nanosheet architectures, which IBM also pioneered and which are being adopted by leading foundries at 3 nm and 2 nm, NanoStack bonds two nanosheet transistors into a single vertical structure, with each tier optimized independently and contacted from opposite sides. Each transistor in the demonstrated structure uses three sub-5 nm-thick nanosheets, about “15 silicon atoms” across, separated by roughly 9 nm spacers. Two such devices are then bonded vertically using an ultra-thin dielectric process IBM describes as a key innovation. Because the top and bottom devices can use different channel materials, dielectrics, and metals, IBM argues NanoStack is less a single trick and more a transistor platform that can be extended through multiple generations: 7 angstrom (Å), 5 Å, 3 Å, and potentially down to 1 Å in its internal roadmap.

An angstrom, by the by, is one ten-billionth of a meter. In terms of chips, an angstrom is a tenth of a nanometer. “This is the world’s first sub-1 nanometer chip technology with a new transistor architecture,” said Jay Gambetta, Director of IBM Research and IBM Fellow, during a press briefing. “We’re not just making smaller transistors, we’re reinventing how chips are built to deliver dramatically more power and energy efficiency....” Based on internal benchmarking against its 2 nm node, the company said its new chips will deliver up to 50% higher performance at the same power, or up to 70% lower power for the same performance. Big Blue also highlighted a 40% improvement in the scaling of static random-access memory (SRAM) cell area relative to its 2 nm technology.

This is a change IBM described as a “step the industry hasn’t seen in over a decade” and one that could be particularly important for AI accelerators that live or die on on-chip memory bandwidth… According to Huiming Bu, IBM’s VP of silicon technology R&D, NanoStack is a new paradigm. It’s moving chips to scaling fully into three dimensions and giving the industry at least “another decade” of logic advances as it crosses from nanometers into angstroms… The 40% SRAM density bump could also help architects push caches and on-die memory closer to compute units, cutting data movement overhead in training and inference workloads.

While the Voyager flyby confirmed the planets’ classification as ice giants… [a]s the least explored planets in the solar system, the two planets have never been thoroughly investigated. Therefore, scientists aren’t sure where the planets originally formed in the early solar system or the reason for their wildly chaotic magnetic fields. A long-standing hypothesis suggests that both worlds have a hydrogen/helium atmosphere that covers a vast mantle of ices, made primarily of water, ammonia, and methane, with a rocky core. The new study, however, notes that the three-layer model of an ice giant’s interior structure is not the only way to explain the properties of the two planets.

The researchers also point out that objects found in the Kuiper Belt, which are thought to preserve evidence of the material in the outer Solar System where Uranus and Neptune formed, are primarily composed of rock rather than ice. For the recent study, the researchers simulated different models for the interior processes and composition of Uranus and Neptune. The model that best fits Uranus’s and Neptune’s different properties suggests the two planets have a well-mixed magma ocean with dissolved hydrogen at the bottom and a hydrogen-dominated envelope at the top. The model suggests that at high pressures, hydrogen gas can dissolve into magma, forming a well-mixed fluid. This mixing might help explain Uranus’s and Neptune’s density, which has traditionally been interpreted as evidence for an ice-rich interior.

“Trusted climate information should not disappear when politics change,” Climate.us managing director Rebecca Lindsey said of the new platform in a press release. Lindsey, who previously served as the Climate.gov program manager and lead editor, told The Register in an email that she and one of the web developers responsible for the site were the first to be caught up in government purges when DOGE swept through the department in late February 2025… Created in cooperation with sustainability nonprofit accelerator Multiplier, Climate.us aims to be an independent alternative to its old .gov, and many of the former NOAA crew behind the previous website have teamed up for the new initiative to “keep climate information accurate, accessible, scientifically rigorous, and useful for the people who rely on it.”

Climate.gov, which now redirects to a NOAA page about climate but which hosts none of the data the shuttered site used to contain, was taken offline in July 2025 following a Trump executive order prioritizing “gold standard science....” arguing that prior climate science models relied on worst-case scenarios, which somehow meant the public availability of 15 years of climate data and reporting ought to change…

All of the content that was purged from the .gov is now back, along with blogs from experts, climate status reports, maps and data pathways, and national assessments of climate change as well. Lindsey told us that rapidly changing political winds have led her to believe that the government isn’t the right place for that mission to continue, and that she would have concerns about returning the site to federal management if a future administration changed its position on climate change… Lindsey said that the Climate.us team will continue with the same mission it had before the Trump administration attempted to quash it: Getting climate science in front of the public in a manner that’s understandable so they can make their own decisions about how to respond.

NYT’s motion comes after the [U.S.] Supreme Court sided with Cox Communications in a case where Sony tried and failed to claim that Cox was contributing to music piracy as an Internet service provider, which set a new standard for contributory infringement. Moving forward, plaintiffs will have to prove that parties intentionally acted to induce illegal conduct. Recognizing that the legal precedent has changed, the NYT now wants to amend its complaint to align its contributory infringement claim against Microsoft with that new standard… A Microsoft spokesperson told Ars that the company views the amended complaint as “a last-ditch effort by the plaintiff to save its claim from unfavorable precedent set in other recent rulings…”

The updated complaint seeks to specify that [Microsoft’s] supercomputer was tailor-made to help OpenAI infringe and allege that it was built for the explicit purpose of training AI on copyrighted works without permission. And as the NYT alleged, its articles were more heavily weighted by this system, as both firms hoped to train models on the highest-quality journalism possible, so that level of writing could be confidently mimicked in outputs. By building this “unusually complex” machine, Microsoft not only helped select the works that were infringed but also provided a means to seize copyrighted works without permission, the NYT alleged. “Microsoft specifically designed it for the purpose of using essentially the whole Internet — curated to disproportionately feature Times Works — to train the most capable LLM in history,” the NYT alleged… Similarly as problematic for the NYT are hallucinations where Microsoft and OpenAI models falsely cite the NYT for content that they never published… “Users who ask a search engine what The Times has written on a subject should be provided with neither an unauthorized copy nor an inaccurate forgery of a Times article, but a link to the article itself,” the NYT alleged…

In a statement provided to Ars, OpenAI spokesperson Drew Pusateri reiterated the AI firm’s often-repeated claims that AI training on copyrighted works is indisputably fair use… OpenAI has argued that “ChatGPT is not a substitute for a Times subscription,” the NYT reported, partly because “they transformed the material for a different use.”

The support from the Spanish Society for Technological Transformation (SETT) comes a year after the fund injected 14 million euros into Spain’s Sateliot , which is also developing a satellite connectivity network with security and defense applications. Spanish private investment firm Kibo Ventures led FOSSA’s funding round, the six-year-old venture announced June 24, bringing its total raised to date to nearly 20 million euros.

The proceeds will help fuel FOSSA’s push beyond the tiny picosatellites it once used to connect low-power monitoring devices toward larger cubesats in low Earth orbit, enabling additional sovereign communications and space-based intelligence capabilities… The company’s funding round follows a wave of investments this year in European ventures planning to develop sovereign space capabilities, including Austrian propulsion startup Gate Space, which secured 6.3 million euros earlier this month from a European Commission-backed accelerator program.
“Our goal is to establish FOSSA as a European benchmark in sovereign space infrastructure,” said Julián Fernández, FOSSA’s CEO and cofounder.

Security researchers said that a new AI model, released this month by China’s Zhipu AI, also known as Z.ai, can match the latest U.S. models when it comes to finding security bugs, although it still lags behind Anthropic’s and OpenAI’s products in other tasks. Overall, the capability gap between top U.S. models and those built by Chinese companies has narrowed significantly, and use of Chinese AI systems has surged as businesses seek to rein in runaway costs. A host of companies, including Microsoft, are weighing how they can offer Chinese models on their platforms, a development that is set to alter the balance of power among tech companies…

Unlike models from Anthropic or OpenAI, Zhipu’s GLM-5.2 is open-weight. That means it can be downloaded and run on hardware operated by anybody and can be modified and used without supervision. Open-weight models are ideal for users who want unfettered access to systems they control, but they are also ideal for hackers, who can run them in the shadows. GLM-5.2 has ranked as one of the 10 most-used AI models, according to data from OpenRouter, a company that provides access to more than 400 AI models. In some benchmarking tests, according to the cybersecurity company Semgrep, GLM-5.2 bested Anthropic’s Claude Opus 4.8 model, which was released in May. When given further instructions, Opus 4.8 and GLM-5.2 can match Mythos in bug-finding ability, according to researchers…

“Banning Fable while selling chips China needs to develop its own version is a gift to China,” said Saif Khan, a distinguished technology fellow at the Institute for Progress think tank who worked on export restrictions in the Biden administration. The U.S. needs to maximize the use of Mythos and comparable models to harden its cyber defenses while it can, he added. Among the Mythos 5 and Fable 5 users that had lost access before Friday’s decision to restore Mythos 5 access for some trusted entities: the National Security Agency, which had been testing the tools and found them impressive in trials, according to people familiar with the matter… “It is incentivizing companies across the globe to use cheaper but very capable Chinese open-weight models, while at the same time undermining the U.S. AI industry,” said Niels Provos, a researcher who led security teams at Google and Stripe. “I don’t understand it.”

In some cases, thieves may pilfer one or more checks from local mailboxes. Adam Rust, director of financial services for the Consumer Federation of America, said thieves sometimes “fish” for checks at free-standing drop boxes, using long tools with sticky pads on the ends to grab letters. In other cases, more sophisticated criminals may steal large batches of checks, copy them and then sell them on the internet. Often, the purloined checks are chemically altered in what’s known as “check washing” to remove the name of the recipient. The thief replaces it with a fraudulent name, and often increases the amount of the check, before cashing or depositing it.

Schwab’s “security guarantee,” outlined on its website , says that “Schwab will cover losses in any of your Schwab accounts due to unauthorized activity.” But fine print at the bottom of the page notes that reimbursement “requires your timely reporting of unauthorized activity to Schwab,” and that Schwab “will not be liable for additional or increased losses resulting from a failure to report unauthorized activity in a timely manner.” It notes that more details are available in account agreements… Notify your bank as soon as possible, said Scott Anchin, senior vice president of strategic initiatives and policy at the independent bankers association. Banks generally allow at least 30 days and sometimes up to 90 days from the time your statement is made available to you to report suspected check fraud, he said.

If you must write a check, he said, try to deliver it in person or take it inside a post office to mail rather than relying on your own mailbox or public drop boxes. The American Bankers Association recommends using permanent “gel” ink pens when you do write checks to reduce the risk of tampering… And if you don’t already, consider using your bank’s online bill payment service.

ATF, the federal agency responsible for enforcing the nation’s gun laws, told The Associated Press that it discontinued what it called a “pilot” program using a tool called Webloc after Rep. Michael Cloud, a Republican from Texas, and Sen. Ron Wyden, a Democrat from Oregon, expressed reservations about the agency’s use of bulk commercial location data. Webloc, which is made by a vendor called Penlink, sources data from consumer apps and advertising networks, which collect the location of mobile devices from consumers who download apps or browse the web…

The U.S. Supreme Court ruled in 2018 that police needed a warrant to obtain historic movement data from cellphone companies on a criminal suspect. But it has never addressed the growing practice of commercially acquired data.

Other users of Webloc include the U.S. military and U.S. Immigration and Customs Enforcement but also local law enforcement agencies such as police in places like Elk Grove, Calif. and Durham, N.C. The technology has also expanded around the world, with the national police in El Salvador and Hungarian intelligence agencies as customers, according to a report from earlier this year from Citizen Lab, a group of researchers at the University of Toronto who investigate digital threats to civil society.

Already, countries are stepping up inspections for test-takers. For China’s grueling annual college entrance exam earlier this month — which more than 10 million hopefuls take each year — authorities required screening of all glasses. In the United Kingdom, the head of England’s exam watchdog warned earlier this month that AI glasses and smart devices like earpieces could worsen cheating in exams… [T]wo incidents in South Korea were the country’s first reported cases of cheating with AI glasses… In Taiwan, the university where a prospective student was caught cheating is now reviewing rules and standard operating procedures for AI eyewears during examinations.

But experts worry these individual cases point to a more widespread issue. “If we’re seeing a few cases being reported, we’re seeing a lot more cases not being reported,” said Thomas Corbin, lecturer at Deakin University in Australia, who has conducted research around the usage of AI-powered glasses and other smart devices in academic assessment. With the rapid development of AI technology, however, smart glasses are becoming slimmer, less noticeable, while integrating AI models that can operate independently with connectivity, raising concerns not only about exam integrity, but also about broader privacy risks… “Wearable AI is as much of a challenge to exams as ChatGPT was to essays in 2022 and I just don’t think there is any real way that we can reliably have exam practices moving forward,” Corbin said.

Many point fingers at the film’s script, with Variety’s line — “a comic-book movie with the worst script I can remember” — going viral… Not to pile on, but there’s another recurring gripe from the reviews that stood out: Critics bashed the film as being murky, dark and gray, with poor VFX: “Muddy CG sludge” wrote one. Another said the film was full of “sludgy browns and grays” and “the visual murkiness of the settings makes it hard to follow the already unintelligible action sequences.” A third wrote the “VFX is so rough it makes The Flash look like Avatar.” Moviegoers increasingly despise murky, dark visuals (often used to hide weak effects), along with obvious CGI and incoherent action. They’ve seen it so many times they’ve become allergic.

The film does have one bright spot: Lobo, who is played by Jason Momoa as something like Michael Keaton’s Beetlejuice by way of Jason Momoa’s Aquaman. He’s blustery and cantankerous and saucy and just a little menacing; it’s a perfect piece of casting and a really nice performance. Unfortunately, it’s the only spark of life in what is otherwise a deeply dour, deeply boring piece of filmmaking… Supergirl is just a misfire on nearly every level, one that lacks the sincerity and fun of last year’s reboot of this universe or the comic pathos present in Gunn’s Peacemaker series on HBO Max.

It’s not fun. It’s barely even righteous. It’s just miserable. At one point, Supergirl flat-out murders a guy by pushing a giant sword through his neck. Somehow, I suspect even Zack Snyder would be appalled.

According to Gartner, these costs will meet, or even exceed, the typical software engineer’s monthly salary within the next two years. This is not only because developers are increasingly adopting generative AI and agentic tools, it reflects a trend toward consumption-based licensing models as vendors balance infrastructure investments with profitability…

Gartner senior principal analyst Nitish Tyagi explained that it’s important to note that Gartner’s prediction is based on a global average salary of $2,000 per month; it doesn’t mean AI token usage will exceed all salaries. For instance, in the US, yearly pay rates can be six digits or more. However, that kind of spend is not out of the realm of possibility, Tyagi emphasized. “I have heard scary numbers like ‘My developer consumed $20K last month,’ or ‘A business user consumed $32K’.”

If these amounts sound shocking, that’s the point. “The goal is to alarm the industry about the impact of token cost if it is not governed and controlled,” he said… AI coding vendors have yet to deliver “mature, built-in cost optimization capabilities,” Tyagi said, and prices will likely only continue to rise as vendors further build out their models while at the same time trying to remain profitable. Thus, enterprises struggle to forecast and control costs, and, because AI is moving so fast, many organizations lack the “maturity and frameworks” to determine ROI, he noted. Agent-driven workflows are difficult to govern, context windows become bloated, budgets are wiped out earlier than anticipated, and token spend becomes hard to justify....

“Without a governed engineering operating model, costs can escalate faster than the productivity gains these tools are designed to deliver,” Tyagi said.

Hoping to ingratiate himself with the company and restart his business, Nekhala offered to provide evidence, including recorded conversations and screen shots, that he said proved Amazon personnel were peddling inside information and influence. The smoking gun, Nekhala told the representative: information about his seller account. Only certain Amazon employees are supposed to have access to such details, but Nekhala had received them from the woman on WeChat, the Chinese messaging app. Nekhala’s experience, which he documented and shared with Bloomberg, provides a rare glimpse into an international black market that has been a persistent scourge of Amazon’s online store. On one side are sellers looking for a variety of favors: a competitive edge over their rivals, information on how to boost sales, a way to get themselves unsuspended. On the other are middlemen who lurk on message apps like Telegram, WeChat and WhatsApp offering access to people inside Amazon who can get things done for a price…

It’s impossible to determine the scope of the illicit activity, but it’s an open secret among Amazon sellers and consultants, who are frequently approached on social-media platforms and messaging apps. “The message is always the same: ‘I’m going to show you screenshots to prove I have inside access,’" said Chris McCabe, a former Amazon employee who runs a seller consulting firm… In 2020, federal prosecutors exposed an international bribery scheme involving Amazon sellers and employees. The ring allegedly extracted about $100 million in unfair advantages by bribing Amazon employees in Asia to help them sell more products and sabotage their competitors. Five people in the US were convicted and received jail terms or probation. Last year, law enforcement officials in India began investigating more than 20 former Amazon employees suspected of accepting bribes from trucking companies in exchange for routes, according to The Times of India.

After Nekhala reported his own experience to Amazon, the representative committed to “do some digging” and to email him instructions on how his evidence could be shared, according to a recording of the conversation. But Nekhala said he never heard back. The employee who leaked his personal information had already been fired for unrelated misconduct, according to Amazon.

IBM said last month it plans to form a new independent subsidiary called Anderon, a foundry to produce the silicon wafers needed to make quantum-computing processors. The venture is seeded by a $1 billion investment from the Trump administration and another $1 billion of IBM’s own cash. Anderon will give the company a new line of business in selling wafers to other quantum-computing companies. It will also provide a steady stream of wafers to continue developing its own quantum technology, positioning IBM to capture part of what the Boston Consulting Group projects will be a $90 billion to $170 billion market for quantum-computing providers by 2040…

The company also plans to spend an additional $9 billion over five years to advance the final stages of its quest to build a quantum-mechanics-powered computer capable and reliable enough for widespread use, a goal known as fault tolerance. That computer, named Starling, is being targeted for 2029. With Anderon, IBM is thinking beyond Starling, or even a more powerful quantum computer planned for 2033.

The growth was led by utility-scale solar (+21.3%), hydropower (+15.7%), small-scale solar
In April alone, wind and solar each produced more electricity than US coal plants, while the combination of solar and wind produced 57.0% more electricity than nuclear power.

The mix of all renewables, including biomass and geothermal, accounted for 30.0% of total US electrical generation during the first third of 2026 — up from 27.8% a year earlier… EIA reported that, in April, utility-scale solar capacity surpassed wind capacity for the first time (160,208.1 MW vs. 160,100.6 MW). Further, utility-scale battery energy storage capacity increased by 17,703.5 MW, or 58.1%. Nuclear added just 18.4 MW. The combined capacity growth of all utility-scale renewable energy sources for the 12-month period (55,980.3 MW) is two-thirds more (i.e., 67.6%) than that added during the previous 12 months (33,392.0 MW).

Florida International University researchers have developed a technique called JaiLIP (Jailbreaking with Loss-guided Image Perturbation) that uses subtle image modifications to bypass AI safety guardrails. Unlike traditional jailbreaks that rely on carefully crafted prompts, the attack works through images that appear normal to human viewers.

The researchers tested the technique against BLIP-2, a multimodal AI model, and found that manipulated images significantly increased the likelihood of harmful responses. According to the study, the approach outperformed previous image-based jailbreak methods and nearly doubled the number of unsafe outputs generated during testing.

The findings highlight a potential security risk for businesses deploying AI systems that process both images and text. While most discussions about AI safety focus on prompts, the research suggests that seemingly harmless images may also serve as an attack vector.