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Today — 27 June 2026Main stream

NYT slams Microsoft for building copyright-infringing supercomputer for OpenAI

26 June 2026 at 20:04

In a heavily redacted court filing Thursday, The New York Times proposed to amend its copyright complaint against OpenAI and Microsoft to clarify a claim and allege that Microsoft actively encouraged OpenAI to steal NYT works by building a bespoke supercomputing system ranked among the most powerful in the world.

NYT's motion comes after the 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.

“Today, we asked the court for permission to file an amended complaint that further strengthens our case, clarifying our claim of contributory infringement against Microsoft based on new law and new evidence uncovered during discovery,” Graham James, an NYT spokesperson, said in a statement provided to Ars.

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Yesterday — 26 June 2026Main stream

Anthropic says Alibaba must be punished for largest Claude cloning attack

25 June 2026 at 18:01

Anthropic has accused the Chinese firm Alibaba of launching the largest attack yet attempting to clone Claude, as China races to match the capabilities of Anthropic's leading model following Mythos' release and subsequent restriction from foreign markets.

Ars obtained a June 10 letter sent to Senators Tim Scott (R-SC) and Elizabeth Warren (D-Mass.) one day ahead of a Senate committee hearing on “AI and the American Dream.” In the letter, Anthropic shared “new, confidential evidence of the largest campaign to illicitly extract Claude’s capabilities we have ever measured.”

The attacks occurred between April 22 and June 5, when “operators affiliated with Alibaba and Alibaba Qwen, Alibaba’s AI lab” allegedly generated “more than 28.8 million exchanges with Claude through almost 25,000 fraudulent accounts,” Anthropic said. Violating Claude's terms of service and access restrictions, this campaign “targeted some of Claude’s most valuable capabilities, such as agentic reasoning, software engineering, and long-horizon tasks.”

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IBM claims world’s first sub-1 nanometer chip technology

25 June 2026 at 10:00

A new chip architecture from IBM can integrate nearly 100 billion transistors on a chip the size of a human fingernail—nearly twice the transistor density of the company’s previous generation of chip technology. The resulting improvement in chip compute performance and energy efficiency comes from what IBM describes as the “world’s first sub-1 nanometer chip technology” for AI data centers.

“It's not just an incremental step, it's a meaningful leap forward,” said Jay Gambetta, director of IBM Research and IBM Fellow, in an advance media briefing. He described the new chip technology as “pointing to a future where computing becomes significantly more powerful without a corresponding increase in energy.”

It’s worth unpacking what the “world’s first sub-1 nanometer chip technology” means, because it is impractical to build reliably functional chips with transistors and other features smaller than 1 nanometer due to various physical limitations. Instead, IBM is basically claiming that its new “nanostack” architecture can deliver the computing performance improvements that would be expected if a theoretical chip could be built with physical features smaller than 1 nanometer.

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Before yesterdayMain stream

Moving Beyond UX: The Rise of the Agentic Experience (AX) Designer

23 June 2026 at 12:41
As AI agents quietly take over workflows, a new discipline is emerging: AX (Agentic Experience) Design. The designers who thrive in the next decade won't just craft experiences for humans—they'll define the rules, guardrails, and invisible systems that autonomous machines use to make decisions.

AI Regulation Should Be Rational, Not Retaliatory

The Trump administration’s approach to AI safety, particularly the generative AI models that regularly grab headlines, has been haphazard at best. At worst, it’s unconstitutional. As EFF and our allies explained in an amicus brief, the Pentagon’s actions against one company, Anthropic, violate the First Amendment because they were motivated by the administration’s desire to punish an uncooperative company, not legitimate concerns about national security.

By and large, the Trump administration’s AI strategy has minimized regulation in the name of “winning” the global “race” to develop leading frontier models. It has pared back regulations intended to address even the most serious AI threats—like AI-enabled cyberattacks on government systems—to protect AI innovation.

Yet it has repeatedly singled out one AI company for arbitrary, heavy-handed rules and sanctions. For years, the federal government relied on Anthropic’s models for use in its classified systems. But after Anthropic resisted the government’s demands to use Anthropic’s models to autonomously kill people or spy on Americans, the government declared war on the “woke” company. It designated the company a “supply chain risk,” effectively banning agencies and government contractors from doing business with the company.

A court issued a preliminary injunction preventing these sanctions from taking effect, as EFF and other civil liberties organizations urged it to do in an amicus brief filed earlier this year. But absent judicial action, these sanctions would’ve cost the company hundreds of millions of dollars. Either way, it sent a clear signal that companies must adhere to the government’s wishes or face similar consequences.

As we explained in our brief filed today, these sanctions were clear retaliation for the company’s public refusal to allow the Pentagon to use its models to develop fully autonomous weapons and spy on Americans. This kind of retaliation is unconstitutional.

In a recent executive order, the Trump administration took its war on Anthropic even further, by imposing “export controls” that ban any foreign nationals from using Anthropic’s new Mythos and Fable models. To comply with this order, Anthropic shut down the models altogether.

These extreme measures were purportedly justified by security concerns. The administration said it feared that Anthropic’s Mythos-class models could be used to find and exploit existing vulnerabilities in software code—hardly a new feat for an LLM. Anthropic itself has contributed to public anxieties about its Mythos-class models, initially claiming that Mythos was too dangerous for public release and restricting access to a handful of partners. The company’s CEO called for a pause on AI development, citing fears that the technology was becoming too powerful.

But regulators should be cutting through the hype, not feeding it. Even if Mythos’s capabilities were a modest improvement over existing technology, others are already closing the gap. In other words, nothing about Mythos is so uniquely dangerous that it warrants exceptional export controls to protect the public. Yet other LLMs with similar offensive cybersecurity capabilities are not subject to export controls. Instead, the government has embraced a voluntary system in which companies are encouraged to submit models to the government for cybersecurity testing 30 days before releasing them to the public.

AI policy should be reasonably responsive to real-world risk, grounded in the realities of the technology, and no more burdensome than necessary to protect the public. But the government’s haphazard decision to impose export controls on Mythos-class models, while subjecting other AI models to nothing more than a voluntary, light-touch framework, meets none of these criteria. As leading cybersecurity experts and executives recently explained in an open letter, these sanctions prevent developers and security teams from using the best models to find and fix vulnerabilities before adversaries, armed with nearly as capable AI, can exploit them.

Decades Later, Code Is Still Speech

More importantly, export controls on important software tools like LLMs can undermine the free flow of digital communications and technologies that activists, innovators, and ordinary users desperately need. Freedom of expression requires access to these tools. Depriving the public of the best AI threatens our rights without making us any safer.

EFF has long opposed government efforts to restrict the publication of non-classified software to the general public. In the 1990s, EFF challenged export controls on encryption software, helping establish the principle that “code is speech,” protected by the First Amendment. Courts recognized that software is not just a functional tool—it’s a means of ideas, knowledge, and technical know-how. And they recognized that the government was overreaching in trying to restrict private developers from sharing their improvements in computer security with the public.

While AI models raise new questions, efforts to restrict access to them implicate the same constitutional and speech concerns as older efforts to restrict encryption. Export controls are uniquely susceptible to abuse. And they are especially suspect when they are unilaterally imposed without clear and fair standards.

Whether these export controls were another attempt to punish Anthropic or simply a misguided security measure, the public loses. The real cybersecurity risks of advanced AI may ultimately justify limited regulations to protect the public from legitimate threats. But whether the government ultimately chooses to heavily regulate the technology or hold off to promote innovation, its rules must be rational and evenhanded. 

AI coding agents taught robots how to install GPUs and cut zip ties

17 June 2026 at 19:25

What happens when you give AI coding agents a lab full of robotic arms, some compute resources, and a “generous token budget” for teaching the robots various tasks? The agents can apparently figure out a training regimen that teaches the robots to successfully cut zip ties and even insert GPUs into thin sockets on motherboards.

That glimpse into how AI can act in a fully autonomous way to automate robot training was made possible by a new agent harness framework—software that wraps around AI models to enable their use of various tools while also providing capabilities such as memory, context, constraint, and feedback loops. That agentic harness, called ENPIRE, was developed by robotics researchers at the Nvidia GEAR (Generalist Embodied Agent Research) lab alongside collaborators from Carnegie Mellon University in Pittsburgh and the University of California, Berkeley.

“A part of our NVIDIA GEAR lab now self-improves tirelessly overnight,” wrote Jim Fan, director of AI at NVIDIA, in a LinkedIn post. “We just read the reports in the morning.”

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The Free and Open Web Is Under Attack at the IETF

17 June 2026 at 21:26

The ability to access publicly available information using automated tools is a central value and benefit of a free and open internet. Automated access—often called crawling or scraping—powers important, useful tools for locating, preserving, and analyzing online information. For example, crawling and scraping helps journalists, researchers, and watchdog organizations report the news, find security flaws, and investigate discrimination. Crawling the web allows non-profits like the Internet Archive to preserve historical copies of websites. Tools for automated comparison shopping allow consumers to find the best deals on items they want to buy. And so on.

Yet the open internet access is increasingly under threat from publishers and Big Tech companies alike. Fearing lost advertising and licensing revenues, website operators increasingly claim that they need to lock down their sites from bots that crawl public web content to train or operate AI models. Some companies are even trying to embed their business models into internet standards by changing Internet Engineering Task Force (IETF) technical standards that shape much of the internet.

Many of their economic anxieties are understandable. AI bots can strain websites’ infrastructure, in some cases, degrading site performance or taking them offline altogether. Upgrading systems costs money that some sites may not have. And AI is likely to disrupt the business models many publishers adopted in response to the rise of the internet, if users rely on AI overviews instead of visiting source websites.

However reasonable these fears may be, the answer is not to change the IETF standards from neutral protocols that encourage openness to restrictive requirements designed to monetize internet access.

The worst of these proposed standards would give websites far greater ability to automatically block legitimate, lawful scraping and crawling. For example, the AI Preferences working group is working on proposals to give publishers a way to express preference signals” against crawling web data for AI-related purposes, including to train models, generate outputs, and help users search the web. These preference signals would be expressed through robots.txt and could potentially become legally binding in some jurisdictions.

Another working group, called Web Bot Auth, is pursuing efforts to protect sites from overly-aggressive bots that strain website resources—a positive goal that could meaningfully improve the internet in the AI era. But Web Bot Auth is simultaneously pursuing a much more dangerous path as well: standards changes that would enable sites to cryptographically identify bots so that they can more easily block anyone they wish—not just bad” actors, but competitors, dissidents, or anyone who hasnt paid for the right to access sites using automated tools. If sites restrict crawling to a preapproved list of cryptographically authenticated bots, they could require licensing payments from those wishing to crawl their sites. This would close off the open web to researchers, archivists, and startups without the ability to pay for automated access.  

Websites may have legitimate reasons to worry about AIs impacts on their traffic and advertising revenue, but those reasons must be weighed against the benefits of the open web. These proposals would effectively give website operators veto power over a wide range of important uses—from the investigations and archival works described above to accessibility tools for people with disabilities, to research efforts aimed at holding governments accountable.

That is why we are fighting back against these threats to open access. EFF and our allies in the open internet community have successfully resisted some of the most dangerous IETF proposals thus far—and wont stop working to protect the open web from efforts to manipulate internet standards to undermine the right to freely access the internet in any legal way, including with automated tools.

$130 billion in data center projects blocked by protests so far this year

12 June 2026 at 17:18

It's clear that communities now have an effective playbook to block data center construction. This week, researchers flagged the first quarter of 2026 as producing the "most blocked and delayed data center projects on record," NBC News reported.

Data Center Watch, a project from AI intelligence firm 10a Labs that tracks data center fights around the US, reported that protestors "blocked or delayed at least 75 projects nationwide worth about $130 billion from January through March," NBC News reported.

That's "the most in a three-month period since the group began tracking in 2023," and it shouldn't be parsed as "a cyclical spike," the researchers said. Instead, there's been a "structural shift," as "communities have internalized an opposition playbook, legislative sessions introduced formal regulatory uncertainty, and the number of active opposition groups more than doubled to 833 across 49 states," researchers said.

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Google sues Chinese cybercrime network that used Gemini to automate scams

12 June 2026 at 16:34

Google loves telling us all the ways people are using its generative AI products to build new things, grow businesses, and save the world. Supposedly. Of course, people are also using AI for crime. Google has announced a new legal salvo aimed at a Chinese group called Outsider Enterprise, which is allegedly responsible for a massive AI-powered scam campaign. Google says it's working with law enforcement and mobile carriers to fight back.

According to Google's legal filing, Outsider Enterprise operates through Telegram. The group offers phishing-as-a-service to individuals who may not be technically savvy enough to set up fraudulent websites and text campaigns on their own. In its Telegram channels, Outsider Enterprise reportedly provided instructions on how to use Google's Gemini AI to create websites that imitate those of Google, YouTube, and government agencies such as New York’s E-ZPass. The group offered nearly 300 scam templates.

Google says that scams enabled by Outsider Enterprise resulted in more than 2.5 million text messages being sent to Android users. About 55,000 of those messages happened in a two-week period last month. In all, Google has tracked 9,000 fake websites and 1 million URLs connected to the scam network.

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Pokémon Go players unwittingly contributed to tech with military drone uses

12 June 2026 at 11:15

A decade after the global craze for Pokémon Go peaked, an AI company has been using billions of real-world images captured by millions of players to develop navigation technologies for delivery robots and possibly military drones. That represents an intriguing but potentially discomfiting legacy for an augmented reality mobile game that has incentivized gamers to capture short smartphone videos of physical neighborhoods and landmarks.

The AI company, Niantic Spatial, was spun out of Pokémon Go game developer Niantic in May 2025, after Niantic separately sold its licensed games such as Pokémon Go to the Saudi-backed video game publisher Scopely. But before that deal, Niantic publicly announced plans to use scans from millions of Pokémon Go players along with data captured by users of the company’s Scaniverse app to train and develop a “large geospatial model”—a 3D model of the physical world trained on the geolocated images provided by app users scanning real-world locations.

“Ground scans were one component to help train Niantic Spatial's real-world foundation models —AI systems that learn to recognize and interpret physical spaces,” a Niantic Spatial spokesperson told Ars. “The models are the product of that training, not a copy of or a means of accessing the underlying scans, which were of public points of interest such as statues and fountains.”

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‘News’ Site Keeps Hallucinating EFF Staffers

What do EFF staffers Sarah ChenJavier Morales, Caitlin Chin, Emma Rodriguez, and Mikko Kopponen have in common? 

For one thing, they don’t exist. 

For another, all have been quoted as EFF experts in articles published in the past two months on a site called News-USA Today, which describes itself as “an independent news publisher focused on clear, accurate, and useful journalism.” 

Uh… 

(Please don’t confuse this site with USA Today, in which real EFF experts are accurately quoted on a regular basis.) 

News-USA Today is hardly the only slagheap that’s hallucinating or fabricating EFF personnel and quotes; as we wrote last September, media companies large and small are using AI to generate news content because it’s cheaper than paying for journalists’ salaries, but that savings can come at the cost of the outlets’ reputations— assuming they care about reputation at all. 

But this many fake EFF sources in two months? That’s making a play for the championship title of bogus news content. 

News-USA Today’s site proclaims, “Our goal is simple: give readers the facts and the context they need to make informed decisions.” It then defines its mission:

  • “Deliver timely, factual reporting grounded in verifiable sources and public documents.”
  • “Make complex topics understandable without losing nuance or accuracy.”
  • “Serve the public interest by surfacing stories that affect lives, institutions, and communities.”
  • “Maintain a clear separation between news, analysis, opinion, and sponsored content.” 

Attempts to reach contacts listed on the site went unanswered. In fact, after we reached out to them, they published a story on June 9 with quotes from Electronic Frontier Foundation Executive Director Jared Cohen — who also doesn’t exist. 

As we noted last year, EFF is all about having our words spread far and wide. Per our copyright policy, any and all original material on the EFF website may be freely distributed at will under the Creative Commons Attribution 4.0 International License (CC-BY), unless otherwise noted.  

However, we don't want disreputable sites making up words (or false identities!) for us, whether or not they’re using AI. False quotations that misstate our positions damage the trust that the public and reputable media outlets have in us.  

The best thing a news consumer can do is invest a little time and energy to learn how to discern the real from the fake. It’s unfortunate that it's the public’s burden to put in this much effort, but while we're adjusting to new tools and a new normal, a little effort now can go a long way.   

As we’ve noted before in the context of election misinformation, the nonprofit journalism organization ProPublica has published a handy guide about how to tell if what you’re reading is accurate or “fake news,” as has FactCheck.org. 

Google DeepMind releases DiffusionGemma, a model that runs local AI 4x faster

10 June 2026 at 19:29

Another day, another AI model from Google. This time, Google DeepMind has released a new member of the Gemma 4 open model family, but it's fundamentally different from the rest of the lineup. DiffusionGemma doesn't generate outputs linearly like most AI models. Instead, it can produce an entire block of text in parallel. Google says this makes it faster and more efficient when running on local hardware like an Nvidia DGX or a humble gaming GPU.

Most AI models are designed to be autoregressive—they generate text left to right one token at a time. DiffusionGemma has more in common with image generation models, which start with static and then denoise it to create the desired content. This model takes a field of placeholder tokens running over the canvas multiple times to generate likely tokens and using those to improve estimation of others. At the end of the process, the model finalizes its token outputs in one large block—the "denoised" text canvas.

DiffusionGemma is fairly large in the realm of Google's open models. It's a Mixture of Experts (MoE) model with a total of 26 billion parameters, but only 3.8 billion are activated during inference. That means it should fit in the 18GB RAM allotment of a high-end GPU. In testing with an RTX 5090, DiffusionGemma spits out around 700 tokens per second. With a single Nvidia H100 AI accelerator, DiffusionGemma can produce 1,000+ tokens per second. That's about four times the output of the similarly sized autoregressive Gemma models.

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S&P 500 rejects SpaceX, also blocking entry for OpenAI and Anthropic

5 June 2026 at 18:45

SpaceX has requested unusually swift entry into several leading stock market indexes as a condition of its historic stock market debut. But the S&P 500 stock market index representing many of the largest profitable US companies has surprised market analysts by refusing to bend the rules for Elon Musk’s space and AI company.

The June 4 decision by S&P Dow Jones Indices—the company that creates and manages stock market indexes such as the S&P 500—means that SpaceX will not gain accelerated access to potentially billions more dollars through passive investment funds that automatically purchase shares of S&P 500 companies. Modifying the rules in response to SpaceX's request could have also allowed leading AI companies such as OpenAI and Anthropic to gain entry not long after their own expected initial public offerings (IPOs). That possibility has now been shuttered.

The news will likely come as a relief to people concerned about passive investor money and people’s retirement savings plans having greater exposure to the market risks associated with SpaceX’s big bet on AI and speculative orbital data center plans. AI companies are generally facing more challenges in funding and building expensive AI data centers, even as they shift more of the subsidized costs of running AI services onto shocked customers through usage-based pricing.

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"We pissed off a lot of people": Giant data center plan cut 50% amid protests

One of the world's biggest data center projects was designed to be nearly three times the size of Manhattan, stretching across multiple Utah sites. But intense local backlash in Box Elder County has now pushed the developer to cut the project plans in half before construction starts.

Residents' top concern was the Stratos data center project draining local waters, and they were willing to pay to protect them, most especially the vulnerable Great Salt Lake. Many locals paid a $15 fee to register comments to block the transfer of 1,900 acre-feet of water from a ranch to the hyperscale data center. Other concerns include electricity bills rising and potential risks to air quality, local wildlife, and land.

Venture capitalist Kevin O'Leary, chair of O'Leary Digital and Shark Tank investor, is behind the construction of the project. He told a local ABC affiliate that he regrets not working with state officials to be more transparent about the project from the beginning.

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The Fitbit Air is a good wearable weighed down by a chatty AI "coach"

5 June 2026 at 15:40

Smartwatches can track your health stats, but they also do a lot of other things you might not always want or need. The $100 Fitbit Air tracker ditches the screens that have become common on people's wrists, leaving behind a tiny puck of health sensors you can often forget you're wearing. You will not, however, forget that Google's new health platform is built around AI.

The Air has no speaker, and there's only one LED on the side to indicate battery level. You can double-tap the tracker to check the level, and that's about the end of on-device features. The vibration motor is only for alarms—it can't sync with notifications on your phone. That makes sense, given there is no screen to tell you what that buzz was all about.

Fitbit Air side view The Fitbit Air doesn't have a display or buttons—just a small LED on the side for battery status. Credit: Ryan Whitwam

The stock Performance Band is simple, consisting of a smooth polyester yarn with small velcro pads and a metal loop. It's durable but does seem to absorb a bit of moisture. For swimming or heavy workouts, you'll probably want the silicone active band. This one hides the Air puck a bit more effectively, and it looks good in a sporty way.

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Elon Musk tries again to escape FTC audits of X data handling

Critics hope to keep Elon Musk from escaping a strict data-privacy order imposed by the Federal Trade Commission (FTC) shortly before he took over Twitter.

The FTC order placed restrictions on X's data use for 20 years, while requiring regular independent audits and granting the agency authority to request documents as needed to ensure compliance.

The FTC’s action came after Twitter voluntarily disclosed that between May 2013 and September 2019, a coding error accidentally allowed phone numbers and email addresses that users shared for two-factor authentication purposes to be used for targeted advertising aimed at those same users. In a settlement that came just months before Musk's 2022 takeover, Twitter agreed to pay $150 million and to allow the FTC to monitor the platform's data-handling practices until 2042 in order to protect user privacy.

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EFF Testifies to Congress on Protecting Americans’ Rights from Government AI

Governments must not adopt emerging and powerful AI technologies without also adopting strong and clear safeguards to protect Constitutional rights, EFF Senior Policy Analyst Dr. Matthew Guariglia testified today to the House Homeland Security Subcommittee on Cybersecurity and Infrastructure Protection. 

During the hearing on “The AI Security Landscape: How Frontier Models, Agentic AI, and AI Coding Tools Are Reshaping Cybersecurity and Critical Infrastructure Resilience,” he explained that the use of generative AI for the purposes of mass government surveillance would supercharge unconstitutional violations of civil liberties. He also highlighted how government secrecy, in addition to the black box of for-profit proprietary technology, prevents the public and lawmakers from knowing when AI models make mistakes, including errors that seriously impact the cybersecurity of critical infrastructure and the lives of individuals.  

“AI also has a track record of getting things wrong—from false citations on legal briefs to a major AI mistake that sent DHS recruits to the field without proper training. There are likely more consequential examples that we do not even know about because of classification that would prevent a more thorough accounting," he said in his opening remarks.

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“At this level the question is not how do we rein in AI, it’s how do we rein in the agencies that would unleash AI on the American public,” Matthew said in response to a question by Subcommittee Ranking Member Delia Ramirez, D-Ill.  

You can read his full testimony as prepared here. 

Google's new Gemma 4 12B model is designed to run on any laptop with 16GB of RAM

3 June 2026 at 19:10

The generative AI boom has driven the cost of memory into the stratosphere, and Google is a key part of that trend. So it's only fitting that Google should offer some less RAM-hungry local AI models. The company has announced the release of a new Gemma 4 model that fills a gap in the lineup that launched earlier this year. The new model is efficient enough that you may be able to run it on a pretty average consumer laptop.

In April, Google released four models in the Gemma 4 family, which also marked the shift to a more open Apache 2.0 license. The initial models included two mobile-optimized options (E2B and E4B) along with a pair of models for more serious work (26B Mixture of Experts and 31B Dense). That left a rather large unserved space in the middle, which is right where the new model falls.

Gemma 4 12B is considerably more capable than the mobile versions, but it won't require a $20,000 AI accelerator to run locally. Google says Gemma 4 12B is unique in that it can run on many consumer laptops without sacrificing quality. As long as you've got a computer with 16GB of system RAM or VRAM, the 12-billion-parameter model will work. That's about half the total memory footprint of Gemma 4 26B MoE, and Google claims the new model is almost as capable, at least as far as benchmarks go.

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Trump plan to test AI models has a problem—US security teams were gutted by DOGE

On Tuesday, Donald Trump finally signed his executive order expanding the government's efforts to conduct voluntary safety testing of frontier AI models. Now, critics are warning that the order may be short-sighted, offering only performative reassurances that the government is actively monitoring for AI risks, while changing very little about how and when models are deployed.

Last month, Trump abruptly canceled a signing event, where he had hoped to launch an earlier version of the EO with CEOs of leading AI firms in attendance. Invited at the last minute, several CEOs simply couldn't make the signing but still signaled support for the order. Officially, Trump claimed he postponed the event because he worried that the EO might have gone too far and had become a "blocker" impeding AI innovation. Reports indicated there was infighting in his administration as cybersecurity experts clashed with officials committed to deregulating AI.

The watered-down EO that Trump signed promises not "to stifle this innovation with overly burdensome regulation" and establishes no requirements for AI firms. Instead, it sets up a voluntary process for companies to collaborate with the government on safety reviews that Trump's EO claimed would "ensure that the best and most secure technology is deployed rapidly to confront any and all threats to our country."

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