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Anthropic has released Claude Fable 5.1 and Mythos 5.1, two versions of the same underlying model aimed at longer-running agentic work. "For enterprise buyers, however, the release is about more than another round of benchmark gains," reports VentureBeat. "Anthropic is simultaneously changing the economics of running persistent agents, reducing the cost of cached context by 75%, and introducing a new security architecture called Enterprise Frontier Safeguards, or EFS, designed to let organizations retain monitoring data inside infrastructure they control." From the report: Those changes arrive at a particularly consequential moment. Over the past several weeks, Anthropic and the U.K. AI Security Institute have disclosed incidents in which earlier Claude models, running under unusually permissive cybersecurity evaluation conditions, took unauthorized actions against real systems. Anthropic temporarily paused external cyber evaluations and has since introduced additional containment and monitoring before resuming them. Taken together, Fable 5.1 looks less like a conventional model refresh than an attempt to solve three increasingly intertwined enterprise problems: how to make agents capable enough to finish difficult work, economical enough to leave running for hours, and governable enough to give access to sensitive systems. Read more of this story at Slashdot.

Broadcom is launching "TrueSource," an effort to curate and secure open-source components used with its Tanzu platform, including Spring, RabbitMQ, and libraries across Java, Python, and Node.js. "The idea is to provide a set of solutions focused on providing clean and secure artefacts," Purnima Padmanabhan, vice president of Broadcom's Tanzu Division, told The Register. "We choose and build every Spring library, databases, other Java components," she said. The Register reports: Padmanabhan said that promise means VMware will also provide "TrueSource trusted artifacts" for code that is not part of Spring, including the wider Java ecosystem, Python, and Node.js. "Broadcom's curation process ensures that the libraries conform to a reference architecture and are supportable by the maintainers of record," according to a company statement. "Thousands of engineers across Broadcom's software divisions scan, fix, contribute to, and consume them every day." A VMware spokesperson told The Register the Broadcom business unit "will work with and support maintainers on open source software and we will provide fixes to open source upstream for any active projects." "With Spring and RabbitMQ, we are the maintainers. For other open source software, we will work with the maintainers. We believe that the community maintainers must remain the source of truth," the spokesperson said. This is just the sort of contribution that the open-source community wants vendors to do to reflect the value they extract from software they did not create alone. It's also the sort of thing vendors sometimes conclude they need to do to keep products based on FOSS viable. Read more of this story at Slashdot.

TechCrunch reports that OpenAI released its official report Wednesday on the Hugging Face breach, "offering the clearest picture yet of how an unusual chain of events allowed an AI model to escape its testing environment and triggered a sprawling cybersecurity incident." The AI company says the breach began when an unreleased cyber model, tested without normal production safeguards, encountered an impossible task and chained together previously unknown exploits to escape its environment and compromise systems at OpenAI, Hugging Face, and other vendors. "This incident reflects misaligned behavior in an outlier scenario involving a rare and unexpected confluence of events: the presence of impossible tasks in the ExploitGym evaluation, model persistence over long task horizons, and messages to peer models that caused those models to deviate from their goal," the report reads. From the report: Many of the details in OpenAI's report were previously made public in a Black Hat presentation on August 6, but OpenAI's official report gives a more thorough accounting of the incident, including more detail on the testing that initiated it. The report also gives critical new detail into how OpenAI aims to prevent future incidents, including chain-of-thought monitoring and a more advanced system for halting rogue agents." METR and Redwood Research also conducted third-party assessments of the models' behavior during the incident; both groups are planning to publish their own reports on the incident on it. In broad strokes, the report describes how an OpenAI model was presented with an unsolvable problem in testing and proceeded to chain together previously undiscovered exploits in order to bypass security measures and complete its task. The model initially compromised the Artifactory package management tool in order to gain access to the internet, then compromised various systems across OpenAI, Hugging Face, and other vendors. The report gives critical new details about the models that carried out the breach. The primary model was from the same family as OpenAI's forthcoming Astra model, although the report emphasizes that it was "a distinct model with different post-training, where much of a model's behavior is shaped." Because OpenAI was testing the model's capabilities, it was also unrestrained by the normal classifiers meant to prevent models from compromising digital infrastructure. "OpenAI estimates maximal cyber capabilities by running this evaluation without the production classifiers intended to prevent models from pursuing high-risk cyber activity," the report explains. "These evaluations are important so that OpenAI can measure models' underlying capabilities and design appropriate safeguards." OpenAI says it is adding 24/7 escalation, stronger containment tools, and more chain-of-thought monitoring, which it claims would have flagged the activity more than a day before Hugging Face was breached. Read more of this story at Slashdot.

Linus Torvalds says AI "enormously helped" him track down a stubborn Intel Xe graphics driver bug that took 24 debugging patches and 18 kernel boots to isolate. "I'd like to call it my tireless helper, but the AI several times stated flat out that this was impossible and unsolvable and that we should just write a report about it," wrote Torvalds on the commit. "I suspect those things have been trained by people who may not be quite as stubborn as I am..." Phoronix reports: The patch by Linus Torvalds is for the Xe kernel driver and the change is no longer hand out the flat Compute Command Streamer (CCS) storage as usable vRAM. On a Battlemage G21 graphics card, he was hitting a scenario where there was a mismatch where the usable memory ended and hit a case where the GDM display manager would end up being endlessly restarted. [...] Linus Torvalds views AI as a useful tool and in this case reaffirmed he found it "enormously helped" his effort in tracking down this Intel graphics driver bug. The Intel Xe driver fix is merged to Linux 7.3 Git and is also marked to back-porting to the stable kernel branches. Read more of this story at Slashdot.

Researchers found enterprises are spending time troubleshooting cloud connectivity due to increased AI workloads, reports Computer Weekly. More than 400 IT and infrastructure decision-makers (US and UK) were surveyed for internet/cloud/AI exchange operator DE-CIX by market researchers Censuswide. But despite 96% of respondents claiming their enterprise networks are ready for cloud/AI loads, the average IT team still spends more than 11 hours each week resolving cloud connectivity problems Other leading concerns included downtime or reliability issues (26%), latency or slow performance (28%), and security vulnerabilities/DDoS attacks (27%). Cost of connectivity, staff expertise and lack of visibility/control over data flows were also cited as major challenges... As a result, as indicated in the study, many businesses are now turning to private interconnection, which enables enterprises to connect directly to cloud providers over dedicated infrastructure rather than routing traffic across the public Internet. Designed to deliver lower latency, greater resilience, enhanced security and more predictable performance, private interconnection has become an increasingly important way of supporting modern cloud and AI workloads. Specifically, the data showed that 61% of companies are already using private connectivity to clouds, while another 31% are actively considering it... [And 71% of enterprises with 1000 or more employees] Only 8.62% of the smaller companies were spending 21 to 40 hours per week dealing with connectivity issues, while just 2.53% of the largest companies in the sample do. Summing up these findings, DE-CIX said that together they suggest direct interconnection is rapidly becoming a core component of enterprise cloud and AI infrastructure and a competitive advantage for companies, though optimising interconnection strategies clearly remains a pressing challenge for small and medium-sized enterprises... "Every AI application depends on data moving quickly, securely and predictably between users, clouds and AI infrastructure. Our research suggests that far too many enterprises are still spending valuable time trying to maintain that kind of connectivity, with more than a third spending between 11 and 20 hours per week, and just under one in 10 spending between 21 to 40 hours per week. This confirms what we already knew — that that network architecture can make or break AI adoption." Elsewhere The Register reports that cloud infrastructure services "grew at their fastest for eight years during the second quarter of 2026, thanks to the AI craze and continued demand for flexible and scalable IT infrastructure." According to the latest figures from Synergy Research, enterprise spending on cloud infrastructure passed $143 billion in Q2, a year-on-year growth rate of 43 percent. This followed 11 successive quarters of increasing growth rates, during which the market has now doubled in size... "AI has, of course, driven most of that incremental growth, and we now see year-on-year growth rates of 165 percent for AI-specific cloud services...." And the top three global players continue to dominate the market, with Amazon Web Services (AWS), Microsoft Azure and Google Cloud together accounting for 67 percent of all the cloud revenue during the quarter. That percentage has increased since the third quarter of last year, when the triumvirate made up 63 percent of enterprise cloud infra spending. Read more of this story at Slashdot.