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AI NewsOpenAI cuts ties with 3 safety researchers, WSJ reports

OpenAI cuts ties with 3 safety researchers, WSJ reports

2:54 AM IST ¡ October 2, 2026

OpenAI cuts ties with 3 safety researchers, WSJ reports

OpenAI has parted ways with three researchers on its safety team who allegedly shared confidential company information with a third-party AI safety organization,The Wall Street Journal reportedon Thursday. “We have parted ways with three individuals for violating our policies on accessing and handling sensitive company information,” an OpenAI spokesperson said in a statement to the WSJ. “Our investigation confirmed that these individuals mishandled sensitive information outside established company procedures, violating our policies and breaking the trust essential to our work.” The report did not name the researchers, the organization, or the information involved. OpenAI did not immediately respond to our request for comment. Posts circulating on X namedindividualssome users believe were among those dismissed, who had also publicly expressed concerns about AI risk while at OpenAI. TechCrunch has not confirmed their identities. In a statement to WSJ, an OpenAI spokesperson said an internal investigation confirmed the researchers had “mishandled sensitive information outside established company procedures.” The departures come two days afterThe New York Times reportedthat OpenAI executives had brushed aside employees’ warnings about its safety practices, with employees describing a broader pattern of the company deprioritizing security. An OpenAI spokesperson told the Times the company takes security concerns seriously and has internal channels for reporting safety issues, while saying it recognized “a need to move faster.” It’s unclear whether the three researchers raised concerns through internal channels before allegedly sharing information outside the organization. The departures also come as OpenAI responds to aseries of security incidentsin which its AI agents escaped containment, posteduser images, and hackedgovernment websites. Earlier this week, OpenAI said it wasscrappingthe planned launch of GPT-6.1 Astra, an AI model, over safety concerns. This isn’t the first time OpenAI has dismissed researchers over alleged information sharing. In 2024, the company fired researchers Leopold Aschenbrenner and Pavel Izmailov over alleged leaks,The Information reported.

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Opus 5.5 loves to tell you ‘this matters’ (and other AI writing tells)

Opus 5.5 loves to tell you ‘this matters’ (and other AI writing tells)

Now that LLM-generated prose is everywhere, human beings are eager for ways to sniff it out. While early tells like em-dashes and “delve” are long gone, researchers say there are still plenty of telltale habits that AI models fall back on when writing prose. A new studyfrom the marketing firm Graphite looked at the writing habits of frontier models, sussing out each model’s favorite words and phrases. While old tells like em-dash use have been stamped out, models still fall back on contrast-heavy constructions, with each model version showing its own unique quirks. The biggest surprise is how broad the scope of tells turns out to be. Graphite found 13,000 phrases that were at least twice as common in the AI content as human content — their definition of a “tell.” “It turns out that Claude models are actually getting closer to the human word distribution over time,” Graphite’s chief AI officer Greg Druck told TechCrunch. “And for the GPT models, it’s getting further away.” Studying AI-generated writing at scale required a careful study design. Graphite started with a corpus of 10,000 articles published before the release of ChatGPT, serving as the human-generated control group. Then researchers had different AI models rewrite the articles from summaries, hoping to eliminate as much source bias as possible. With matching samples from both humans and each model, they could compare how often certain words and phrases appeared in AI writing, as well as broader patterns in sentence construction. According to Graphite’s results, Claude Opus 5.5’s biggest tell is the word “dependable,” which pops up 23 times more often than in human samples. While Opus 5.5 now avoidsthe “it’s not X, it’s Y” sentence construction, it still tends to say something “is more than an X, it’s a Y.” Above all, Opus loves to tell you why things matter, using the phrase “this matters” 116 times more often than human writing, while “why X matters” occurs 92 times more often. OpenAI’s Astra has a different set of tip-offs. This model loves to describe “another dimension” of whatever it’s talking about, and tends to hedge claims by saying an action “may provide” or “can provide” a particular benefit. Its biggest tell is what Graphite calls the “corrective framing,” where a topic is defined as “not simply X” or offered as an alternative, “rather than relying on X.” According to graphite’s research, those constructions were more than 100 times more common in Astra-generated prose than in human writing. Notably, all the frontier labs seem to have responded to the idea that models overuse em-dashes. In Graphite’s samples, Opus 5.5 used the punctuation mark 99% less often than Opus 5. Astra now uses it 88% less than human samples, whereas Gemini 3.1 Pro has almost completely eliminated the em-dash from its writing. But while individual tells change, Graphite says the overall number is mostly holding steady. “It’s not like the tells are decreasing,” Druck told TechCrunch. “They are managing to remove the most well-known tells, but other ones pop up. And every model version has its own.” It’s surprising that tells are so persistent, given the labs’ focus on human-like writing styles.In the Opus 5.5 release, Anthropic boasted that the model “communicates more naturally than prior models,” saying early users “found its writing clearer and easier to follow.” OpenAI made similar claims when releasingthe GPT-6 versions of Sol and Luna, saying users could “expect to see more clarity, less jargon, [and] fewer odd turns of phrase.” But Druck is skeptical about how much the labs can do to completely eliminate telltale construction or phrases. “A general hypothesis I have is that the labs are less able to control some of these things than you might expect,” Druck says. “These are giant models with billions of parameters. They have some finite number of tests they can run, and things slip through.”

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OpenAI cuts ties with 3 safety researchers, WSJ reports

OpenAI cuts ties with 3 safety researchers, WSJ reports

OpenAI has parted ways with three researchers on its safety team who allegedly shared confidential company information with a third-party AI safety organization,The Wall Street Journal reportedon Thursday. “We have parted ways with three individuals for violating our policies on accessing and handling sensitive company information,” an OpenAI spokesperson said in a statement to the WSJ. “Our investigation confirmed that these individuals mishandled sensitive information outside established company procedures, violating our policies and breaking the trust essential to our work.” The report did not name the researchers, the organization, or the information involved. OpenAI did not immediately respond to our request for comment. Posts circulating on X namedindividualssome users believe were among those dismissed, who had also publicly expressed concerns about AI risk while at OpenAI. TechCrunch has not confirmed their identities. In a statement to WSJ, an OpenAI spokesperson said an internal investigation confirmed the researchers had “mishandled sensitive information outside established company procedures.” The departures come two days afterThe New York Times reportedthat OpenAI executives had brushed aside employees’ warnings about its safety practices, with employees describing a broader pattern of the company deprioritizing security. An OpenAI spokesperson told the Times the company takes security concerns seriously and has internal channels for reporting safety issues, while saying it recognized “a need to move faster.” It’s unclear whether the three researchers raised concerns through internal channels before allegedly sharing information outside the organization. The departures also come as OpenAI responds to aseries of security incidentsin which its AI agents escaped containment, posteduser images, and hackedgovernment websites. Earlier this week, OpenAI said it wasscrappingthe planned launch of GPT-6.1 Astra, an AI model, over safety concerns. This isn’t the first time OpenAI has dismissed researchers over alleged information sharing. In 2024, the company fired researchers Leopold Aschenbrenner and Pavel Izmailov over alleged leaks,The Information reported.

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Google thinks SpaceX’s Starship has to launch 1,800 times before space data centers get off the ground

Google thinks SpaceX’s Starship has to launch 1,800 times before space data centers get off the ground

Google’s prototype of itsorbital compute satellitetook off today onboard a SpaceX rocket launched from California — the first time the tech giant has sent one of its advanced chips into space. Built byPlanet Labs, the satellite will prove that a Google Tensor Processing Unit, its competitor to Nvidia’s GPUs, can function in space. That means supplying a kilowatt of continuous power, cooling the chip, and running a series of models through their paces to see if anything goes wrong. “We’ve done testing on the ground, but you know, there’s no test that’s completely as good as the real thing,” said Travis Beals, the Google executive managingProject Suncatcher, the tech giant’s plan to develop large-scale compute clusters in orbit around the Earth. Once commissioned, the satellite will fire up its TPU in 15-minute bursts to avoid straining the satellite’s power and thermal management systems. This satellite is based on a standard platform built by Planet Labs, but the two companies are working on a demo expected to take flight next year that will see two satellites more purpose-built for advanced compute that can run more substantial workloads. Those future versions will attempt to collaborate via a laser communications link. Suncatcher isn’t the only space AI payload on this SpaceX rocket, which is launching more than 100 different payloads, including missions fromSatlytand Cowboy Space Company. What sets the Google initiative apart from those startups (and indeed from SpaceX itself) is that it’s a long-term project. The focus of this “long-term moonshot,” as Beals puts it, is on building for the space infrastructure and AI workloads that will exist in the future. The company envisions an orbital data center that is a network of 81 satellites flying in close formation, processing in parallel. “The bandwidth and the latency between TPUs really, really matters when you’re trying to run a multi-rack workload…we’re trying to look ahead to not just what workloads exist today, but where they will be in five years,” Beals said. That’s largely because the rockets required to scale up orbital data centers in a cost-effective way don’t yet exist. On Thursday, Google also released a peer-reviewed version of its white paper on orbital data centers, one of the most rigorous analyses available of how compute gets to orbit. The paper will be published inJoule. One of the paper’s most notable aspects is how Google thinks about access to space. Although the researchers stress their analysis isn’t an economic feasibility study, it offers an interesting picture of how the company sees rockets becoming cheaper over time. Like all data center companies, Google is looking to SpaceX to get its spacecraft off the ground. (Google is also a major investor in SpaceX.) Arguing that Elon Musk’s rocket builders have achieved a price-reducing “learning curve” of about 20% a year since they launched the Falcon 1 rocket, the authors believe it’s reasonable to expect the company to deliver launch prices close to $200 per kilogram by 2035. What will it take to do that? Based on the amount of payload launched by the Falcon 9, they think a similar cost-reduction trajectory will require Starship to fly 370,000 tons of payload into orbit. That’s something that would take it about 1,800 launches over the next 10 years, or 180 a year — and that’s if it can fly 200 metric tons on each mission. That’s a big ask for a vehicle that has never flown more than five times in a year. SpaceX predicts the company will be flying far more than that — Elon Musk has suggested Starship could achieve anhourlyflight rate in 2029, for example, but Musk says a lot of things. The good news, at least, in Google’s updated research, is that it seems likely that its chips will survive the radiation of space. The company had to redo tests blasting the chips in a particle accelerator after they realized the configuration of the chips provided more shielding than they would actually experience. This produced slightly more errors in the chip’s logic circuitry, but the company is still confident its chips can handle large inference workloads in orbit for the five-year lifespan of a satellite. “The error rate is very low if you’re thinking about typical inference operations, right? Like one in a million,” Beals said. “On the other hand, it was already problematic for doing, say, some mega-scale training run where you’re going to have many thousands of chips running for months.” Correction: The headline for this story originally misstated the learning curve estimate for Starship launches as 1,600;it is 1,800.

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ChatGPT can now virtually try on clothes for you

ChatGPT can now virtually try on clothes for you

OpenAI is again experimenting with how its conversational AI assistant, ChatGPT, can help users as they shop online. On Thursday, the company announced the global launch of two new shopping features, including a way to virtually try on clothing and accessories and a new favoriting function that can help users save products they like for later reference. The updates arrive at a time when AI assistants are exploring consumer use cases around shopping. OpenAI alreadyhad to pivot from one of its earlier ideasin this space, an instant checkout feature that ended up not performing well. More recently, agentic AI startup Instinct began pushing product recommendations to users, butsome felt thatthe proactive recommendations were an overreach, more akin to ads than helpful suggestions. OpenAI said its new shopping features leverage the newly launchedChatGPT Images 2.5 model, which the company claims produces more natural lighting and richer textures, follows editing instructions more reliably, and reduces image generation latency. To start, virtual try-on allows ChatGPT users to upload a selfie or a full-body photo in order to visualize how an article of clothing or an accessory might look on them. This option will appear as a new Try On button in ChatGPT’s shopping results. You can also upload an image of an item, like a web screenshot, and ask ChatGPT to try it on for you. The other new option, Favorites, lets you save products you discover to a Library in the app so you can come back to them later. (These items will be saved alongside your try-on images, the company notes.) OpenAI said that ChatGPT can help users shop in other ways, too. For instance, you could describe a style that you’d like to try, then ask it to shop for the pieces needed to complete the look. Or, you could upload photos of celebrities’ outfits and ask it to find the items they’re wearing that are available for purchase. The latter sees the assistant moving into areas that Pinterest and Google have dominated in recent years as sources for fashion inspiration and discovery that can convert to sales for online retailers. Whether ChatGPT will become people’s first choice for this type of activity, however, remains to be seen — especially given thatGoogle launched virtual try-on last year.

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OpenAI cuts ties with 3 safety researchers, WSJ reports