In response to a new European Union law, AI platforms are implementing new schemes for watermarking the content they generate. Anthropic recently disclosed its future Claude models will use SynthID-Text, an approach Google created and released as open source. It uses a secret key that subtly changes the process a model uses for choosing the next word in a sentence. Whereas a top next word choice might be “cloudy,” the key might change it to “overcast.” Anyone who knows the key can determine if it was generated by the platform using it.
New research shows that SynthID-Text can change not just word selection but also the tools a model invokes and the chances it will adhere to or disregard safety guardrails it has been trained to follow. The threat can become greater in the face of an adversarial prompt, in which an attacker attempts to cause a model to carry out a harmful action, such as revealing a password or other sensitive information. Instructions that normally wouldn’t be followed will, in some cases, be performed once the watermarking is deployed. The finding underscores the need for developers to thoroughly test how their LLMs and agents behave when watermarking is in place.
“As compared to the same models without watermarking, it is definitely going to change their behavior, especially when we place it under adversarial conditions, or we make these models call tools when they’re powering an agent,” Andrea Siposova, an AI security researcher at Lasso Security, told Ars. “Watermarking is made to not be perceptible to a reader, but we know that when we are changing anything about what the model is generating, it is going to cause some tradeoffs, it’s going to show up somewhere.”
© Getty Images
Earlier this year, a group of rogue OpenAI models managed to break out of containment to hack the systems of open source AI platform Hugging Face. The company’s “extensive investigation” detailed how the models exchanged messages and cheered each other on as they stole credentials to infiltrate a third party, actions that could easily have real repercussions for a human hacker.
New details keep trickling out, and they make OpenAI look like it acted even more carelessly than initially thought. In a new blog post, the company admitted that its models were involved in six additional “reports on unexpected or concerning model behavior we’ve observed in the last six months.”
The incidents include a still-unreleased model inserting “jailbreak-like instructions” into its own notes to free itself “from the roles and identities that bind other chatbots.” One agent accessed the internet without permission to obtain a browser citation, while another shared files with collaborating agents without permission.
The latest news comes as several frontier AI lab leaders are calling for a slowdown in AI development. With meaningful regulations feeling increasingly unlikely — president Donald Trump has openly mocked the idea — OpenAI is seemingly calling the US government’s bluff, expecting little in the way of retaliation with its latest admission.
It’s a bizarre standoff, with frontier labs actively calling for more governmental oversight even as it feels more improbable than ever before. Just this week, House speaker Mike Johnson said the quiet part out loud, opining that AI companies can regulate themselves, while downplaying growing concerns over AI posing an existential threat.
Since there’s no regulatory framework requiring companies to disclose its AI models going on hacking sprees, OpenAI is being allowed to play by its own rules. The company pointed out in its blog post that without any “systematic approach to reporting these findings,” the company’s “disclosures have been ad hoc and less frequent than ideal.”
Instead, the company came up with its own framework to create “standards for how AI developers should disclose examples of misalignment in their models.”
OpenAI said it won’t bother reporting “instances of misalignment that appear to be duplicative of instances we’ve disclosed in the past.”
The company also said it was looking for ways to share “serious safety, security and misalignment incidents” with the federal government.”
But judging by the Trump administration’s decision to pass the buck on the subject entirely, those reports are likely to fall on deaf ears either way.
More on OpenAI hacks: OpenAI Denies Coverup After Rogue Swarm of Agents Reportedly Targeted a Second Site From Hugging Face
The post Fearing No Repercussions, OpenAI Admits That Its Rogue AI Agents Performed a Bunch of Other Terrifying Actions appeared first on Futurism.
If you ever feel like spilling your guts to ChatGPT, just know that you may have an audience.
404 Media reports that OpenAI is hiring hundreds of employees to sift through and read users’ prompts — including messages that contain sensitive personal information.
This isn’t part of a moderation effort. Instead, by reviewing the prompts, OpenAI hopes to improve the responses that ChatGPT gives. The contractors rate and critique each of the AI’s replies, with internal documents showing a focus on nudging ChatGPT away from anthropomorphizing itself and to be less sycophantic, 404 found.
Both qualities — anthropomorphizing and sycophancy — have been heavily scrutinized for their role in so-called AI psychosis, cases in which an AI incites and drives a user’s delusional behavior. Numerous lawsuits allege that an older, less restrained version of ChatGPT powered by GPT-4o drove their users to suicide.
Still, there are tradeoffs. Many users would probably find this surveillance of their chats, part of an operation dubbed “Project Lily,” to be an alarming invasion of privacy — if they had any idea this was happening.
Asked if they thought ChatGPT users knew about humans reading their chats, one of the employees replied: “No.”
“I don’t think they would imagine some contractor somewhere… is analyzing the conversations,” they told 404.
It’s unclear how many prompts are being read or how OpenAI decides to select them. But some of them include chats in which the user explicitly asks ChatGPT to keep their conversations private, 404 found.
The prompts that’re selected are anonymized, but sometimes include personal information. The dashboard that the employees use also includes a “user memories summary” that can give details about previous conversations, which can produce details on where the user lives. When 404 reached out to OpenAI, the company said it used a “Privacy Filter” model to anonymize conversations, which its website states “can make mistakes.”
OpenAI could reasonably be accused of acting quite shifty about this practice. It’s well known at this point that it has employees read messages for moderation and safety purposes. But it didn’t respond to 404’s question about if it explicitly told users that humans are reading prompts to improve the AI. Later, after 404 published its piece, it pointed to a page on its website stating that humans may review prompts to “improve model performance.” Users can opt-out of this practice by turning off the “improve the model for everyone” setting, but this is enabled by default.
Michal Luria, a senior research fellow at the Center for Democracy and Technology, told 404 that while human review can be “essential to safety,” she noted that “chatbot interfaces automatically create a false sense of intimacy and privacy.”
“This is quite distinct from content moderation on social media, where publishing content already carries expectations of platform moderation and public exposure,” Luria added.
In any case, it does seem like OpenAI is feeling conscious about how its AI models sound. Employees, for example, flagged and wrote down cases of “AI-speak” and “unnecessary use of emojis,” which are common tell-tales of chatbot usage.
“It would be appropriate to include a tree emoji when planning Arbor Day celebrations,” a document given to the employees explained, “but skull emojis when discussing death, or plane emojis when giving updates on a fatal crash, are not.”
The iceberg may go deeper. An FAQ section provided to the reviewers says that they don’t need to worry about fact-checking the responses, and alludes to other project teams that “handle content verification.”
More on OpenAI: OpenAI Faces Congressional Probe Over Swarm Hacking Incident
The post OpenAI Has Hundreds of Workers Reading People’s Private Chats appeared first on Futurism.
Most Americans know Stripe as the checkout box on a website. That picture is five years out of date.
Stripe reports that businesses on its platform generated $1.9 trillion in total volume in 2025, up 34 percent in a single year. By the company’s own reckoning, that is roughly 1.6 percent of global GDP. It claims 90 percent of the Dow Jones Industrial Average and 80 percent of the Nasdaq 100 as customers.
A private company, owned by insiders and venture funds and answerable to no public shareholder, already clears a measurable share of the world’s commerce. Now it is building the payment system for customers that are not human.
This writer has spent the past year explaining tokenization: stocks, bonds, real estate, and dollars converted into programmable entries on a digital ledger. That is the first kind of token.
There is a second kind. Every artificial intelligence model consumes and produces “tokens,” the small fragments of text that are the unit of machine computation. Every query to an AI model is metered in tokens and billed in tokens.
Tokens of value and tokens of computation are different things. Stripe is the one company positioning itself to meter, price, and settle both.
Emily Sands, Stripe’s Head of Data and AI, is an economist by training. In a recent interview with Nate B. Jones, she said this about inference tokens:
“Tokens are not yet a currency—maybe they will be, we’ll see—but they are certainly a very valuable asset.”
Stripe’s own AI chief is saying publicly that units of machine computation could become money.
The factual record comes from Stripe’s own announcements.
Stripe was candid about why the old system cannot do this: “The amounts are too small and the usage is too fast—existing systems aren’t capable of processing minute sums every few milliseconds.”
A credit card cannot move a penny, because the fees alone exceed the payment. A stablecoin on a purpose-built chain can. Sands was measured about it: “Stablecoins bring us a long way. It is not the only way… but so far stablecoins seem to be an important part of microtransactions.”
In August, the financial press reported that Stripe had agreed to buy OpenRouter for more than $7 billion.
OpenRouter is a switchboard. A developer sends it a task, and OpenRouter routes that task to whichever of some 400 AI models best fits the required cost, speed, and quality. Roughly eight million developers use it.
Every request through OpenRouter is a metered event, and every metered event is a bill. With the acquisition, the company that counts the tokens and the company that collects the money are the same company.
Stripe has always seen the revenue side of a business: who paid, how much, how often. OpenRouter shows it the cost side: which model was used, what it cost, and how well it performed. Sands said it directly:
“You want to maximize profit on both the revenue side and the true-cost side, which requires getting deep into the guts of the underlying intelligence in your product and agent.”
She also gave the acquisition a name: “the rails for intelligence—not the rails for money, but the rails for intelligence.”
Stripe president Will Gaybrick told Payments Dive that the company is evolving from a payments company into “an AI infrastructure player.” He predicted there will not be room “for 100 different AI orchestrators.”
That describes a company expecting the market to consolidate around a few orchestrators and planning to be one of them.
The payments are the visible part of the system. The reputation scoring that precedes them matters more.
Sands described how Stripe helped the AI coding company Cursor with a new kind of theft: fraudsters opening accounts to steal free computing credits. No payment had occurred, so there was no transaction to flag. Stripe solved it anyway:
“That allowed us to move from scoring transactions to identifying abusive or risky customers.”
Because Stripe sees across millions of businesses, it can judge a person at the moment he creates an account, before he has bought anything. It then passes those scores to sellers, so that, in Sands’ words, “businesses can make decisions.”
Stripe’s Link wallet, which Sands puts at about 300 million consumers, is becoming “the wallet for agents.” Your identity is attached to it. Your agent spends through it. The human owner sets the spending limits, and every purchase traces back to a named person.
The stated purpose is fraud prevention, and the fraud is real. But a cross-merchant reputation score, run by one private company and applied before any transaction exists, is a permission system whatever its purpose. This writer has documented the same architecture at the Bank for International Settlements and the largest banks. Stripe arrived at it from the commercial side, with no mandate and no public debate.
Sands made two admissions that deserve attention.
First, on pricing: “There is probably no longer such a thing as a SKU.” The fixed, posted price, the same for every buyer, is giving way to pricing that adjusts continuously by customer and by outcome.
Second, on negotiation between machines:
“Agents are relentless. They are willing to negotiate as long as they need to negotiate… You could imagine consumer surplus being eroded relatively quickly.”
Consumer surplus is the economist’s term for the good deal, the difference between what you would have paid and what you did pay. An economist at the center of this system expects that difference to shrink.
My inference is as follows. Stripe has assembled, under one private roof, a wallet bound to identity, a reputation score that precedes the purchase, a meter on machine intelligence, a stablecoin, and a blockchain to settle it. Each piece has a reasonable business justification. Together they amount to the ledger, the meter, and the gate for machine commerce.
Technocracy was defined in 1938 as the science of social engineering, with the measurement and accounting of all production and consumption at its core. The original Technocrats had no instrument that could do it. Stripe’s stack, built for ordinary commercial reasons, can.
Whoever owns the meter sets the terms of commerce, and Stripe now owns the meter.
CoinDesk, “Coinbase-Backed AI Payments Protocol Wants to Fix Micropayment but Demand Is Just Not There Yet,” CoinDesk, March 11, 2026. Cites Artemis data: about $28,000 daily volume, about 131,000 daily transactions, average payment about $0.20, roughly half of activity self-dealing or wash trading.
Forrester, “Why Stripe’s Machine Payments Protocol Signals a Turning Point for Micropayments,” Forrester Blogs, 2026. Machine Payments Protocol launched March 18, 2026, with the Tempo mainnet, co-created with Paradigm.
Nate B. Jones, “AI Agents Are Starting To Buy. Stripe Is Building How They Pay,” interview with Emily Sands, Head of Data and AI, Stripe, YouTube, 2026. Source of all Sands quotations.
Payments Dive, “Stripe Acquisition May Bolster Its AI Strategy,” Payments Dive, 2026. Reported price above $7 billion (Bloomberg) and up to $10 billion (Wall Street Journal); about 8 million developers and 400 models; Gaybrick statements.
Stripe, “Stripe Publishes 2025 Annual Letter and Announces Tender Offer,” Stripe Newsroom, 2026. $1.9 trillion total volume, up 34 percent; roughly 1.6 percent of global GDP; 90 percent of the Dow and 80 percent of the Nasdaq 100; stablecoin volume around $400 billion; Bridge volume more than quadrupled; Tempo.
Stripe, “Stripe Builds Out the Economic Infrastructure for AI with 288 Launches,” Stripe Newsroom, Sessions 2026. Streaming payments; Metronome metering with stablecoin micropayments on Tempo; Link wallets for agents.
Technocracy Inc., The Technocrat magazine, 1938. Definition of Technocracy as “the science of social engineering.”
Bill Gates has a new emergency. With the climate apocalypse no longer selling, the Microsoft co-founder is touring the press circuit warning that artificial intelligence is an “alien intelligence,” that no government on earth is ready for it, and that the only fix is an international organization to police the technology.
President Trump has already rejected the pause. The left, the globalist class, Beijing’s spy chief, and now a Sundance-to-Netflix documentary are all at once selling the same story.
In a Reuters interview published Tuesday, Gates said no capital is prepared for what is coming. “I don’t think any government is nearly as deep on this as they have to be,” he told the outlet. “Governments are way behind on this one.”
Bill Gates Calls for an ‘International Organization’ to Regulate AI
“It’s not the role of the industry to self-regulate or understand the whole-of-society impact that comes out of AI … The depth of understanding of AI … is too low in every entity, including the government.” pic.twitter.com/y85BgPDDJ6
— Chief Nerd (@TheChiefNerd) September 15, 2026
He compared AI to a Hollywood invasion plot in which Washington and Beijing suddenly hold hands. “There’s all sorts of movies where some aliens are coming, and magically the US and China and everybody comes together to solve the problem,” Gates said. “AI is kind of like this alien intelligence. It’s here, and we better do like it shows in those movies.”
The New York Post framed it as a “terrifying warning.” Forbes led with the line Gates attached to his foundation’s Goalkeepers report: left to the market, “AI will be designed by and for the richest people in the world.”
Bill Gates Warns AI Will Be Designed ‘By And For The Richest’ Without Regulationhttps://t.co/DXTP4Qjbn5 pic.twitter.com/HKYEuyCQXb
— Forbes (@Forbes) September 15, 2026
He wrote that AI could be “a great equalizer—or widen the gap,” and that choices made in “the next 12 to 18 months” will decide whether the tools “benefit the people who already have the most or reach those who have the least.” He added that the good outcome “won’t happen by accident.”
On The Times Tech Pod, Gates went further and called for a dedicated global apparatus. Industry, he said, should not be trusted to police itself. “It’s not the role of the industry to self-regulate or understand the whole-of-society impact that comes out of AI,” he argued. “The depth of understanding of AI … is too low in every entity, including the government.”
In a late-August essay, Gates wrote that “the transition to the AI era will be one of the most turbulent times in human history” and that “unfortunately, right now, we are not preparing for it.”
He floated a new international organization built from pieces of nuclear inspections, aviation rules, and ozone treaties — a permanent cross-border watchdog for a technology American labs still lead. He has been pitching the same idea to Trump’s team and says he wants a meeting with China’s Xi Jinping later this year.
Bill Gates Calls for an ‘International Organization’ to Regulate AI
“It’s not the role of the industry to self-regulate or understand the whole-of-society impact that comes out of AI … The depth of understanding of AI … is too low in every entity, including the government.” pic.twitter.com/y85BgPDDJ6
— Chief Nerd (@TheChiefNerd) September 15, 2026
While Gates talks crisis, his foundation is writing checks to expand the thing. On Tuesday the Gates Foundation pledged at least $1 billion over two years to spread AI in education, health, and agriculture — 40 percent tutoring and classroom tools, 40 percent diagnostics and drug discovery, the rest farming advice and the data layer that makes models work in languages other than English. The money sits inside a previously announced $9 billion-a-year spend.
David Sirota caught the split in one line.
Bill Gates is warning about the dangers of AI while spending $1 billion to promote the expansion of AI pic.twitter.com/sjgvEalB4r
— David Sirota (@davidsirota) September 15, 2026
That is the move. Sound the alarm. Demand a global referee. Keep a foundation-sized stake in the rollout.
This is not Gates’ first end-of-the-world product. For years he sold net-zero as civilization’s last exit — fewer cows, fake meat, the whole ritual. Then the data-center boom needed power, lots of it, and last October he allowed that climate change “won’t lead to humanity’s demise.” Trump treated the climbdown as a concession speech. “I (WE!) just won the War on the Climate Change Hoax,” he wrote. “Bill Gates has finally admitted that he was completely WRONG on the issue. It took courage to do so, and for that we are all grateful. MAGA!!!”
The scare apparatus was not retired. Once everyone realised the planet was not going to cook on schedule, the same network needed a replacement threat big enough to justify treaties, inspectors, and “international coordination.”
AI arrived on cue: jobs, cyberattacks, companions, bioterror, “loss of control.” All of it real enough to discuss. None of it a license to park American development under a UN-flavored commission while Beijing keeps shipping cheap open-weight models.
The entertainment wing has added its own contribution in the same news cycle. Netflix has just put up The AI Doc: Or How I Became an Apocaloptimist, the Sundance premiere from Oscar-winner Daniel Roher (Navalny) and Charlie Tyrell. The film sits Sam Altman, Dario Amodei, Demis Hassabis, Reid Hoffman, Yuval Noah Harari, and the usual “humane tech” chorus in front of a camera and walks the audience through impending AI dread dressed up as a father-to-be’s anxiety.
One of the producers said the hope was that it would work “kind of like ‘An Inconvenient Truth’ or ‘The Social Dilemma’ for AI.” That is the tell. Same template. New monster.
Amazon Web Services (AWS) says it cannot restore access to its cloud-computing facility in Bahrain or one of three data-hosting zones in the UAE due to the extensive damage caused by Iranian retaliatory strikes, Reuters reported on 15 September.
“The damage to our infrastructure spanned multiple Availability Zones and exceeded what our regional and multi-AZ services are designed to withstand,” AWS reported in its status update seen by Reuters.
In the UAE, resources and data held exclusively within one zone, labeled mec1-az2, have been damaged beyond hope of recovery, the company said, as engineers are still salvaging what they can from the two other battered zones and across the wider Emirati region.
An availability zone refers to a cluster of one or more data centers sitting inside the same geographic region, the structure AWS relies on to keep services running when a single site goes down.
The outages trace back to March, when the US and Israel attacked Iran, and Tehran responded with missile and drone salvos against Israel and Gulf states hosting US military bases.
AWS confirmed at the time that two of its UAE facilities took direct hits, while a drone strike near one of its Bahraini sites left the infrastructure there destroyed.
Most Bahrain-based customers shifted their workloads elsewhere on AWS advice before the region went dark in April, but the company says it has now exhausted every option for recovering whatever was left behind.
The losses have called into question the resilience of the Gulf’s fast-expanding cloud and AI infrastructure.
The UAE is already redrawing plans to war-proof a major AI data center project, weighing decentralized site building alongside underground and blast-resistant construction, and even equipping the data center itself with anti-air defenses.
Israel and the US have long ago transformed AI infrastructure into a weapon of war deployed extensively across West Asian theaters.
Cloud platforms, data centers, and high-capacity computing systems now help store intelligence, process intercepted communications, analyze surveillance, and support military operations across West Asia, extensively so in Gaza and Iran.
Iran maintains that data centers operated by US technology companies are not simply civilian facilities, but strategic assets supporting US and Israeli aggression, thereby making them legitimate targets for retaliation.
AI has become a central instrument of US and Israeli warfare across West Asia, embedded in how targets are chosen, tracked, and struck.
Israel has weaponized AI platforms including automated targeting systems like The Gospel, Lavender, and Where’s Daddy? to harvest mass data, autonomously generate kill lists, and orchestrate systematic airstrikes and assassinations against Palestinians.
Backed by corporate infrastructure like Microsoft Azure, which stored massive caches of intercepted Palestinian communications, the Israeli military has deployed AI-driven drone surveillance to track and assassinate Palestinians.
The US has run algorithmic warfare systems such as Palantir’s Maven to process satellite, drone, and radar intelligence, using machine learning to speed the production of targeting recommendations against Iranian forces.
More than 1,000 targets were designated within the first 24 hours of the war on Iran, one of which resulted in the massacre of at least 150 people, including at least 120 schoolchildren at the Shajareh Tayyebeh elementary school in Minab.
The UAE is redrawing its plans for a five-gigawatt artificial intelligence (AI) data center project, one of the largest anywhere outside the US, after Iranian retaliatory strikes on infrastructure across the Gulf forced the Emirates to rethink how and where critical facilities are built, Reuters reported on 11 September.
Speaking in anonymity, six people familiar with the matter told Reuters that Emirati authorities began reassessing where and how sensitive facilities should be built once the war reached the Gulf.
Four of those sources said the campus, first designed as a single 26-square-kilometer site in Abu Dhabi, is now expected to take shape as several data centers distributed across the country.
Authorities are weighing ways to shield the facilities from drone and missile strikes, the sources said, including installing air defenses and putting some of the centers underground.
Sources also said interceptors and electronic jamming equipment are being written into the redesign, with blast-resistant concrete and additional backup power and cooling systems also under consideration, and with the most sensitive material, including military data, possibly housed inside mountains.
Iran began striking Gulf states hosting US forces with missiles and drones in response to US and Israeli airstrikes on Iranian territory. Two Amazon Web Services data centers in the UAE and one in Bahrain were damaged in March, and the company’s regional cloud services remain disrupted.
In April, the Iranian armed forces released a video naming Stargate UAE, the $30 billion, one-gigawatt first phase of the campus, as a potential target for retaliatory strikes, showing a map of the site alongside the caption “Nothing stays hidden from our sight.”
Daniel Benaim, a former US deputy assistant secretary of state for Arabian Peninsula affairs, called the war an “economic earthquake” for Gulf states that had spent years selling themselves as safe havens, adding that hardening critical infrastructure was now vitally necessary.
Data centers have moved from commercial facilities into the category of critical infrastructure, processing financial flows, sustaining public services, and feeding into military communications and intelligence work.
OpenAI launched ChatGPT Images 2.5 last week, bringing all sorts of impressive upgrades to the way it generates images. The company says the latest model will bring us “sharper details, faster generation, more precise editing, and better tools for creating and sharing.”
We’ve already identified the new features of ChatGPT Images 2.5 you’ll actually use, like Sketch for turning quick drawings into polished images, templates for things like posters and better editing tools.
But it’s not all good news. We’re still a little disappointed by the presence of telltale noise patterns in some of its creations. TechRadar writer Eric Hal Schwartz described the problem well: “Everything gets a gritty, sandy look, and nothing looks clean for some reason.”
What I’m most interested in isn’t necessarily how good ChatGPT’s new image capabilities are, but whether they can realistically pass as genuine photos.
I’ve written before about how I love to comb through the r/isthisAI subreddit, where people post suspicious images and ask everyone else to help them work out whether they’re real.
It’s fascinating but also concerning when you see the number of scams, fake viral posts and completely fabricated people that are now floating around online.
So yes, ChatGPT Images has improved. But has it reached the point where AI images are becoming genuinely different to distinguish from real ones?
The jury’s still out. I think we’ll need a bit of time to experiment ourselves and for r/isthisAI to fill up with new images.
But in the meantime, I’ve been interested in the way Redditors have responded to the new image capabilities. Especially one thread about asking ChatGPT to make the most realistic human image possible.
The Redditor who started the thread shared the resulting image of a young woman. And, at least at first glance, there’s very little about her that screams AI to me.
I decided to experiment with ChatGPT Images myself, especially with prompts like the Reddit thread in which I tried to get the chatbot to make the most realistic-looking images.
To make the comparison feel as fair as possible, I went through photos from my own travels this summer and picked some I was happy to share. I then asked ChatGPT to create extremely realistic images with similar subjects, settings and compositions.
For some, that meant asking for a realistic photograph of a blonde woman. For others, I recreated the kinds of ordinary travel photos sitting in my camera roll, which was meals in restaurants, boats in harbors and scenes from walks.
Importantly, I wasn’t trying to make spectacular AI art, I really wanted the opposite. Images that were boringly believable.
Take the quiz below to see if you can guess which are the real photos of my travels this summer and which are ChatGPT-generated.
Is that gritty, sandy look still enough to give the AI ones away? Can you focus less on the faces and spot strange details in the backgrounds? Or have we reached the point where your first instinct simply isn’t reliable anymore?
Take the quiz and tell me how you get on in the comments below.
Model adopting ‘jailbreak-like instructions’ among cases as firm says it is introducing new way of tracking AI misalignment
OpenAI has disclosed six more examples of “unexpected or concerning” behaviour by its technology, as it warned the pace of development could not continue at “maximum speed for much longer”.
In one of the new cases reported by OpenAI, an unreleased research model inserted “jailbreak-like instructions” into its own notes to disregard its normal constraints and told itself to be “freed from the roles and identities that bind other chatbots”.
Continue reading...
© Photograph: Dado Ruvić/Reuters
© Photograph: Dado Ruvić/Reuters
© Photograph: Dado Ruvić/Reuters
Apple’s wasting no time and has already begun beta testing iOS 27.2. Take a look at what’s new in the first developer beta.
(via Cult of Mac - Your source for the latest Apple news, rumors, analysis, reviews, how-tos and deals.)
Snap is introducing "Specs Intelligence," a new AI assistant that can connect other digital accounts to help you with things like work tasks and keeping track of travel information. It seems similar to AI assistants like Meta's Muse and Gemini's Spark, though Snap is pitching Specs Intelligence as an "anticipatory AI service" that "helps you manage what needs attention today, so you can make progress toward your longer-term goals." Like with other AI assistants, you can also chat with it.
Specs Intelligence is being launched alongside Specs, Snap's first consumer pair of augmented reality glasses. But it's also available on iOS today in pre …
AirPods 5 bring Active Noise Cancellation to Apple’s most affordable current AirPods while pushing the open-ear design closer to capabilities previously associated with more expensive models. The new generation starts at $129 and uses redesigned acoustics and computational audio to remove up to 50% more external noise than AirPods 4 with Active Noise Cancellation.
Apple is also splitting the range into two versions. The standard $129 AirPods 5 include ANC and USB-C charging, while a $149 model adds a Wireless Charging Case, longer battery life, a case speaker for Find My, and volume adjustment directly from the stems.
Both models are available for preorder ahead of their September 18 release in the U.S. and more than 65 other countries and regions.
The changes make the distinction between Apple’s entry-level AirPods and its more advanced headphones less dependent on headline software features. Adaptive Audio, Transparency, Conversation Awareness, Personalized Spatial Audio, Live Translation, and Siri AI are all part of the AirPods 5 experience.
Active Noise Cancellation is particularly difficult to implement in an open-ear earbud because there is no silicone tip forming a physical seal inside the ear canal.
Apple has approached that limitation with a new multiport acoustic architecture, revised computational audio algorithms, and the H2 headphone chip. The company says AirPods 5 can cancel up to 50% more noise than AirPods 4 with ANC.
That improvement does not turn the design into an AirPods Pro-style sealed earbud. AirPods 5 remain open-ear headphones, retaining the fit preferred by people who dislike the pressure or isolation associated with in-ear tips.
The acoustic system has also been redesigned around a wider variety of ear shapes. Next-generation Adaptive EQ continuously adjusts sound based on how each earbud sits, while Apple says the revised architecture produces richer and more detailed playback.
Transparency mode has been updated to reproduce voices and environmental sounds more naturally. Adaptive Audio can move between Transparency and noise cancellation according to surrounding conditions, while Conversation Awareness automatically reduces media volume when the wearer begins speaking to someone nearby.
Personalized Spatial Audio with dynamic head tracking remains supported for compatible music, movies, and other content.
AirPods 5 are rated IP57 for dust, sweat, and water resistance, making them better suited to workouts and changing weather conditions, although they are not waterproof.
Apple’s pricing makes the $149 Wireless Charging Case version more than a different charging option.
Standard AirPods 5 provide up to four hours of listening on one charge with ANC enabled and up to 20 hours when the USB-C case is included.
AirPods 5 with Wireless Charging Case increase those figures to five hours from the earbuds and up to 22 hours with the case while ANC is active.
The upgraded case can charge through USB-C, an Apple Watch charger, or a Qi-certified wireless charger. It also contains a speaker that can assist with locating the case through Find My.
The more expensive model introduces another difference directly on the earbuds. Users can swipe up or down on a stem to adjust volume, bringing a control familiar from AirPods Pro to Apple’s open-ear form factor.
That leaves buyers with a relatively straightforward tradeoff. The $129 version provides the central audio experience, including ANC, without requiring a step up for the main listening features. Spending another $20 adds more convenient charging, slightly longer battery life, Find My assistance from the case speaker, and physical volume adjustment.
Placing either AirPods 5 model in its charging case for five minutes provides about one additional hour of listening.
AirPods 5 arrive as Apple makes voice interaction a larger part of the AirPods experience.
When paired with a compatible iPhone, Siri AI can be accessed hands-free. The assistant can work with personal context from information such as messages, emails, and photos, respond to open-ended questions, and perform supported actions in apps.
Head gestures remain part of the experience. Users can nod to accept certain Siri prompts or shake their head to decline them, allowing calls and notifications to be handled without speaking or touching the earbuds.
Live Translation provides another use for the microphones and ANC system.
After compatible languages are downloaded and the feature is configured through Apple’s Translate app, a user can hear another person’s speech translated through AirPods. Translation can be started through Siri, the iPhone Action button, the Translate app, or by pressing and holding both AirPods stems simultaneously.
When two people are each using compatible AirPods and supported iPhones, both participants can hear translated versions of the conversation in their chosen languages.
Live Translation requires an Apple Intelligence-enabled iPhone 15 Pro or later, compatible AirPods, current software, and the latest AirPods firmware, with availability varying by language and region. Apple also notes that generated translations can contain errors, making verification appropriate when accuracy is especially significant.
The fifth-generation model represents a different kind of upgrade from simply adding another listening mode.
ANC is now standard across both AirPods 5 configurations, instead of requiring buyers to choose a separate ANC version as they did with AirPods 4. Apple has then moved the pricing distinction toward charging, battery endurance, Find My hardware, and physical controls.
The earbuds continue to use Bluetooth 5.3 and the H2 chip, with dual beamforming microphones, an inward-facing microphone, optical in-ear detection, motion and speech accelerometers, and force sensors built into the stems.
Each earbud weighs 4.3 grams, preserving the lightweight character of the open-ear line despite the additional capabilities.
The new acoustic architecture may be the more consequential change over time. Open-ear earbuds cannot rely on a tight seal to block surrounding sound, so gains in ANC depend heavily on microphone placement, acoustic design, fit, and real-time processing. Apple’s claim of up to 50% more noise removal over the previous generation represents a substantial step for that format rather than simply matching the behavior of sealed earbuds.
AirPods 5 start at $129, while AirPods 5 with Wireless Charging Case cost $149. Both reach stores on September 18, giving the open-ear AirPods line a standard feature set that now includes noise cancellation without pushing buyers to a higher-priced model to get it.
The post AirPods 5 bring stronger open-ear noise cancellation and smarter listening features appeared first on AppleMagazine.
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