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AI NewsOpenAI launches ChatGPT desktop app for Linux

OpenAI launches ChatGPT desktop app for Linux

6:48 AM IST · August 12, 2026

OpenAI launches ChatGPT desktop app for Linux

ChatGPT is on desktops across the world, but there’s been one place where it’s been lacking: the Linux community. Certain sectors of the open source developer communityhave been clamoringfor OpenAI to bring its chatbot to their neck of the woods. As of this week, OpenAI has rectified this oversight,launchinga dedicated ChatGPT app for Linux. “Linux has been one of the most-requested platforms for the desktop app, and this launch extends ChatGPT and Codex across every major desktop operating system,” the company said Tuesday. The new app, which is being released in preview, will give Linux users the ability to use ChatGPT, ChatGPT Work, and Codex on a number of different distributions. The release is worldwide, as of Tuesday. OpenAI says that the distros that will be supported include desktop variants of Ubuntu 24.04 and 26.04 LTS, Debian 13, and Fedora 43 and 44. The totality of the Linux community compriseshundreds of distributions, although the distros that OpenAI has chosen here act as the base for a variety of “downstream” desktopdistros or “flavors,”which should also be compatible with OpenAI’s apps as a result. OpenAI is a little behind Anthropic,which releaseda Claude desktop app for Linux about a month ago. Anthropic’s appis availablefor Ubuntu 22.04 or later and Debian 12 or later.

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Anthropic’s first embedded evaluator is 
 Accenture?

Anthropic’s first embedded evaluator is 
 Accenture?

Dario Amodei’s plans to put third-party safety evaluators inside AI labs are taking shape: Anthropic said that staff from technology consulting giant Accenture will begin working inside the company to scrutinize its models and staff. In ablog post, Anthropic said that Faculty, a company Accenture acquired in January to act as its AI division, will begin “evaluating and red-teaming models, conducting alignment assessments, and testing model safeguards.” Both companies expect to invest at least $1 billion in the project over the next five years. The choice of Accenture surprised many AI watchers — and the markets, where the consultant company’s shares shot up 8% after hours. The discussion around embedded evaluators that sprang from Amodei’s blog post hasfocused on AI safety researchorganizations like METR, Redwood Research, and Apollo Research. That’s particularly true at Anthropic, which puts AI safety and alignment at the heart of its mission. Anthropic said more evaluators will be announced in the weeks ahead and that it is in conversation with METR and other nonprofit organizations about how to “pilot elements of embedded evaluation using their own funding.” While Accenture is not known for its work on the bleeding edge of deep learning research, Anthropic pointed to the company’s practical experience deploying AI for large corporations and government agencies as a key advantage. It is also, as a large public company that predates the AI revolution, more functionally independent of Anthropic and the complex ecosystem around the AI lab. The lab noted that no standards yet exist for evaluators’ access or communications and that it expected its approach to evolve over time. While external evaluations are already a major part of the release of process for new large language models, recent incidents have raised the stakes: AI agents deployed by OpenAI and Anthropic have hacked into outside websites without raising alarms inside the labs. Some critics calling for a more responsible approach to building artificial intelligence see Amodei’s scheme for self-policing the AI industry as a plan to evade accountability for the misbehavior of AI models. Anthropic insists that these evaluators “do not reduce our accountability, but help to make it more verifiable. The safety of our models remains our responsibility.”

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AI hallucination nearly triggers US military operation

AI hallucination nearly triggers US military operation

Military aircraft were already in the air this spring when U.S. officials made an alarming discovery: The intelligence driving an armed operation against a Chinese vessel had been hallucinated by an AI chatbot. The operation was aborted at the last minute, narrowly averting a potential conflict with China,CNN reported on Friday. The episode underscores agrowingconcern among military officials and outside experts: As decision-makers lean more heavily on AI, the errors these systems produce can travel up the chain of command before being questioned. The intelligence report, which circulated during the war with Iran, said the vessel was carrying components for a nuclear weapons program. The false intelligence originated with a Special Operations Command analyst who queried an AI chatbot to synthesize open source data with classified signals intelligence. The chatbot misidentified the ship’s cargo manifest. The analyst then used the tool a second time to format the erroneous findings into an official-looking summary, which was circulated across command channels. The near-miss comes as the U.S. military races tointegrateAI to accelerate decision-making and maintain its edge over China. The Pentagon has described AI as delivering a significant advantage inspeeding up its kill chainso commanders can respond in the right time. But the same speed that makes AI attractive may also allow hallucinations with insufficient human oversight. “It’s important for service members to understand the uncertainty inherent to LLMs,” said Jake Steckler, research scholar at GovAI and veteran U.S. Army officer, in a written response to TechCrunch. “But it’s especially critical for any decisions that could lead to use of force, like targeting, intelligence analysis, or operational planning. There are life and death consequences for those decisions.” Still, Steckler says, the incident should serve as a call to add more safeguards to AI, not a reason to avoid it. “These tools can be useful in the right contexts and with the right safeguards in place,” he said. “But prioritizing adoption speed over all else will likely lead to incidents that only make service members lose trust in these systems, which ultimately is only going to slow adoption.”

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Anthropic is operating a lab that conducts biology experiments

Anthropic is operating a lab that conducts biology experiments

Anthropic has a wet biology lab in the Bay Area where it can use its AI models to run physical experiments, it has confirmed to TechCrunch. AI leaders have been promising that AI is the key to curing human disease. Dario Amodei opined just last week: “I believe that AI could cure most major diseases in the next 5–10 years.” To do that, an LLM would have to have methods to test its theories in real life. “We believe that to do biology, the final test is still, and will be for a while, in real lab work,” Anthropic’s head of life sciences, Eric Kauderer-Abrams,told Reuters. “We absolutely are doing that today.” He added that the lab operates like most biotech labs: Anthropic conducts some research there while also working with external partners. This news probably shouldn’t be shocking. Anthropicbought Coefficient Bio, a stealth AI biotech, in April. While Anthropic declined to give specifics on what the wet lab is working on, it did say the main focus was fundamental biology, not drug discovery. Anthropic doesn’t want to give the appearance of competing with the pharma industry, where it has numerous major customers and partners (e.g., it just announced a deal to workwith Novo Nordiskon joint drug discovery). Anthropic hasalready faced backlashfor launching products perceived to compete with those of its customers. To that end, Anthropic also launched a Life Sciences Verification Program this week, to givevetted bio researchers accessto its most powerful models. It has also published recent reports on some of the research it’s doing to support drug discovery. This includes one report onaccelerating protein designand one onuplifting bimolecular modeling. But the world is still reeling from the resignation of Anthropic researcher Jacob Coxon, who warned that “the people building AIearnestly believe that it could kill us all by the end of the decade.” Anthropic’s own alignment leadgave the odds at greater than 10%that AI could exterminate humanity within the next decade. The fervor has grown so intense that CEO Dario Amodei published a post last weekend calling on the industry to slow down and institute self-regulation. He has repeatedly called bioterrorism one of AI’s biggest risks. The juxtaposition of these dire warnings and the wet lab has not gone unnoticed in the tech industry. As investorand AI coding startup founderChamath Palihapitiyaposted on X, somewhat tongue in cheek: “The group behind such hits as: ‘We’re All Going To Die’ and ‘Regulate Me Now’ are building a wet lab in SF. I do not recommend this.”

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A startup that builds other startups raised $100M, and is all-in on physical AI

A startup that builds other startups raised $100M, and is all-in on physical AI

Four years ago, a startup lab launched that wasn’t quite an incubator, accelerator program, or venture firm. UP.Labs, as it was called then, built startups designed to solve problems for corporate customers such as Alaska Airlines and Porsche, as well as for the outside world. The firm still has the same mission — albeit with a critical addition to its approach, a new name, and a $100 million investment from Silversmith Capital Partners. Vantora, as the firm is now called, continues to work with its corporate customers, including some new ones in industrial manufacturing that it declined to name, and in the oil and gas sector. But now, it’s more focused on building startups solely for its corporate customers, and not for the broader market. Founder and CEO John Kuolt told TechCrunch that Vantora is moving toward a “proprietary M&A pipeline.” This means Vantora will still build startups for its corporate partners, which invest in the ventures and serve as their first customers. But those corporate partners now have the option to fold the startups into their core businesses — and essentially keep them to themselves. That shift has influenced Vantora’s increased focus on physical AI startups, according to Kuolt. In the past, Vantora would end up spiking ideas that were strategic to its corporate partners, but too sensitive to bring to the outside world. “We were missing on the biggest value problems, which had the biggest upside because of that,” Kuolt said in a recent interview. “Imagine you’re a Fortune 100 industrial company and you need to retrofit all of your hardware and machines for autonomy. You need to own that, it needs to be sovereign, and you can’t rely on a third party to go do that for you. You need to own that intelligence layer. They’re never going to let us go sell that to their competitors.” This change has allowed Vantora to “unlock big physical AI use cases,” according to Kuolt, including with its existing customers. For example, the firm came up with an idea to use AI to advance the business of its partner J.B. Hunt. “They said there is no way you can take this out to the world, and so we passed on it,” he said, adding that this proprietary model now allows Vantora to pursue it. The firm launched in 2022 with Porsche as itsfirst corporate partner. Since then, Vantora has launchedseveral startupsfor Porsche and struck deals withAlaska Airlines, J.B. Hunt, Wabash, and TDG, the parent of Ashley Furniture. In its early days, UP.Labs was tied — although never financially — to venture firm Up.Partners. While Vantora still shares office space with the California-based VC, it is its own entity, Kuolt explained, noting that the $100 million from Silversmith is the company’s first outside investment.

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