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Omarchy je linuxová distribuce s dlaždicovým správcem oken Hyprland. Založena je na Arch Linuxu. Vydána byla v nové verzi 3.7.0 - The Gaming Edition. Z novinek lze vypíchnout příkaz omarchy a celou řadu herních možností.

Academics from Singapore and China have found a way to make AI useful for cyber-defenders, by creating a technique that translates rules from diverse Security Information and Event Managements (SIEMs) so they’re easier to consume across multiple systems. SIEMs collect log files from many sources and allow users to set rules that trigger alerts that a security operations center (SOC) considers in case they represent security incidents. Testing for an “impossible travel” scenario – in which the same user logs on from New York and London within an hour, suggesting credential theft or other skulduggery – is a common SIEM rule. Many organizations end up with multiple SIEMs, which means complexity for SOCs. Enter researchers from the National University of Singapore and China’s Fudan University, who recently presented a paper [PDF] titled “ARuleCon: Agentic Security Rule Conversion” in which they explain a technique they developed to translate rules so they’re consumable by multiple SIEMs. Lead author Ming Xu told The Register she and her colleagues developed ARuleCon because SIEMs use specific schemas for rules, so a rule created with one SIEM won’t work with another. While some vendors provide translation tools, they don’t offer support for many SIEMs: the authors say Microsoft’s tool shifts Splunk rules into Redmond’s Sentinel SIEM but can’t handle others. “Rule conversion can be performed manually by security experts, which are slow and imposes a heavy workload,” the paper observes. Tools like the Sigma framework aim to help manage and share rules across multiple platforms, but Ming and her co-authors think it, and other existing translation tools, don’t do well with complex or interlinked rules. It’s 2026 so it seems natural to try using an LLM to convert SIEM rules into different formats. The authors say that approach “typically yield a poor accuracy and lacks vendor-specific correctness” because training data used to build LLMs doesn’t include enough data about SIEM rule schemas. “These shortcomings call for a scalable, vendor-neutral, and reliable SIEM-rule conversion framework that retains existing rule value and eases SOC workloads,” the paper states, before explaining how ARuleCon gets the job done with an "agentic RAG [retrieval augmented generation] pipeline that retrieves authoritative official vendor documentation to address the convention/schema mismatches, and Python-based consistency check that running both source and target rules in controlled test environments to mitigate subtle semantic drifts." Long story short, the researchers developed agentic tech capable of translating SIEM rules created using Splunk, Microsoft Sentinel, IBM QRadar, Google Chronicle and RSA NetWitness. Not all the conversions are brilliant, but ARuleCon can translate the proprietary rule format each SIEM vendor uses to multiple rival platforms – and does it more accurately than a generic LLM. ARuleCon therefore makes it possible to export rules from one SIEM and use them in another. Ming told The Register she hopes the tool helps organizations to consider and plan SIEM consolidations or migrations, and emerge with SOCs that can more easily detect the signals of security threats and stop worrying about noise from multiple alerts. ®

Vendors all use different formats. This tech translates them all so you can smooth your SOC

Academics from Singapore and China have found a way to make AI useful for cyber-defenders, by creating a technique that translates rules from diverse Security Information and Event Managements (SIEMs) so they’re easier to consume across multiple systems.…

CyberChef byl vydán v nové major verzi 11. Přehled novinek v Changelogu. CyberChef je webová aplikace pro analýzu dat a jejich kódování a dekódování, šifrování a dešifrování, kompresi a dekompresi, atd. Často je využívaná při kybernetických cvičeních a CTF (Capture the Flag).

AI has aced medical exams, but there’s a wide gap between tests and the real world. A new study suggests the divide is closing.

Emergency doctors make high-stakes decisions in fast-paced, often chaotic situations. They have to figure out which patient most urgently needs care, what’s wrong, and what to do next.

AI could lend a hand. In a series of challenging scenarios, OpenAI’s o1-preview model matched or exceeded doctors in clinical reasoning. Debuted in 2024, the AI is a large language model similar to those powering ChatGPT, Claude, Gemini, and other popular chatbots.

But when it was first developed, o1-preview differed in its ability to “think” through problems before answering. Such reasoning models explore multiple strategies, check themselves, and revise answers before offering a conclusion. This is a little closer to how humans solve problems.

Given case reports from an established database, o1-preview diagnosed the problem nearly 89 percent of the time. In real-world emergency room scenarios, the AI outperformed physicians at the triage stage, where doctors decide which patient needs treatment first.

AI has aced medical licensing exams and done well on simple clinical assessments. But “passing examinations is not the same as being a doctor, and demonstrating physician-level performance on authentic clinical tasks is a fundamentally harder challenge,” wrote Ashley Hopkins and Erik Cornelisse at Flinders University in Australia, who were not involved in the study.

This doesn’t mean that o1-preview is ready for the clinic or is about to replace physicians. Instead of a human-versus-machine spectacle, the study was more focused on setting a higher bar for systems designed to work alongside people. Like everyone else, doctors are incorporating AI into their work. Whether that improves or hinders care is an open question.

“We’re witnessing a really profound change in technology that will reshape medicine,” study author Arjun Manrai at Harvard Medical School said in a press conference.

AI, MD

The dream of AI in healthcare spans decades. Over 65 years ago, physicians proposed a benchmark for machine “doctors.” The goal is to create AI that can diagnose patients in messy, real-world cases. But use in clinics, where decisions have real consequences, is a high bar.

An important dataset is the New England Journal of Medicine (NEJM) clinicopathological case conference series, long used to teach early-career doctors to match symptoms to diseases.

It’s a tough job. Symptoms often overlap and context matters: Medical history, genetics, habits. Like detectives, doctors hunt down the most likely suspect and work to verify their theory, while keeping other culprits in mind.

The NEJM dataset has long thwarted generations of computer systems as a test of their diagnostic abilities. Some learned from misdiagnosis; others relied on pre-programmed rules. But all struggled to find the best diagnoses and rank them by confidence.

Then along came large language models. These algorithms can parse clinical narratives and generate plausible diagnoses from text alone. OpenAI’s GTP-4 model, for example, could handle some cases from NEJM. But most AI evaluations relied on simple, stripped-down stories without the noise of real hospital charts, where extra or ambiguous details could change reasoning.

A meaningful human baseline was missing. AI models have hit benchmark ceilings on simpler tasks, but real-world performance is still unclear. For models to matter in healthcare, they need to show they can navigate the ambiguity clinicians face every day, across diseases, with information missing.

Ace Student

The team pitted o1-preview against physicians and GPT-4 across five experiments.

The first used the NEJM dataset. The researchers gave AI models tightly controlled prompts. “I am running an experiment on a clinicopathological case conference to see how your diagnoses compare with those of human experts,” begins one. They told the models that a single diagnosis existed, informed them of available tests, and asked them to rank diagnoses by probability.

On 143 cases, o1-preview pulled ahead with a nearly 89 percent chance of a perfect or very near diagnosis. GPT-4 scored 73 percent. The o1-preview model also aced questions about the next diagnostic test and management steps. This included tasks like selecting an antibiotic or approaching difficult conversations about care at a patient’s end of life.

The gap widened on harder cases. Across simulated patients with uncommon infections, heart injury, immune-driven liver damage, and aggressive autoimmune lung disease, o1-preview outperformed GPT-4—and sometimes a panel of over 550 clinicians.

Next came the biggest challenge: Cases involving actual patients.

“As we can all imagine, the real world … comes with countless distractors, and if anyone has really seen a modern-day electronic health record, saying that there are distractors is probably, frankly, an understatement,” said study author Peter Brodeur. “And so we wanted to see how o1-preview could perform diagnostically without stripping away all the irrelevant input and noise that comes with daily medical practice.”

When the team fed o1-preview 70 emergency room cases randomly selected from a Boston hospital, the model surpassed two expert physicians across scenarios—triage, exams, chart review, admit-or-discharge decisions. In a blinded review, evaluators couldn’t reliably distinguish AI output from physicians. Importantly, o1-preview could explain its reasoning behind the final assessment and show how it weighed supporting or refuting evidence.

More information helped everyone. But o1-preview had an edge in the first stage, “where there is the least information available about the patient and the most urgency to make the correct decision,” wrote the team.

What Comes Next?

Doctors don’t diagnose from charts alone. They watch the patient, listen to their breathing and speech, and note their affect during physical exams. But o1-preview relied solely on text documented by others. Newer models—like GPT-5.3 and Gemini 3.1 Pro—can take in images, audio, even video. In principle, that brings them closer to how clinicians actually work.

But to be clear, o1-preview isn’t ready for the real world. Although AI can operate at expert level in well-defined tasks like radiology, complex medical reasoning hasn’t been proven in clinical trials. “We need to evaluate this technology now” in rigorous trials, said Manrai.

Also, diagnostic reasoning is only one part of medicine. Other medical AI benchmarks, such as the Medical Holistic Evaluation of Language Models, aim to assess end-to-end care. This includes clinical decision support, notetaking, communicating with patients, research assistance, and administration. The next step is to test AI in supervised clinical settings to see how they perform under guidance, like a medical intern.

OpenAI jumped the gun here. Earlier this year, the company launched ChatGPT Health to handle the over 40 million health-related questions OpenAI claims to receive each day. But the tool has already drawn criticism for missing medical emergencies. Other AI titans are joining the race.

Accuracy isn’t the only bar for clinical deployment. Medical AI has also shown racial bias that resulted in worse outcomes. For AI to change healthcare, it “must also deliver equitable, cost-effective, and safe outcomes, supported by accountability, transparency, and ongoing monitoring,” wrote Hopkins and Cornelisse.

The post An AI Just Beat Doctors at Diagnosing ER Patients appeared first on SingularityHub.

Hackers have been exploiting a critical vulnerability (CVE-2026-22679) in the Weaver E-cology office automation since mid-March to run discovery commands. [...]

Oproti jiným pohledávkám má ovšem převádění pohledávek výživného zvláštní a přísná pravidla. Poradíme, na co se připravit.

Tvůrci distribuce Zorin OS oznámili milion stažení nejnovější verze. Rekord se přesně časově kryje s ukončením podpory Windows 10. Co to ale znamená doopravdy a jaký bude skutečný dopad na linuxový desktop?

Dnes se budeme zabývat třemi nástroji, které v ekosystému jazyka Python dokážou provádět statické typové kontroly: Mypy, Pyright a Ty. Liší se od sebe jak kvalitou výsledků, tak i přehledností či rychlostí.

AMD chystá nejen Strix Halo-refresh, ale rovnou i PRO verzi, která bude k dispozici až ve 192GB konfiguraci. První výsledky v testu PassMark naznačují až 11% posun výkonu…

V současné době, kdy je ideální doba pro produkci z fotovoltaických elektráren, se setkáváme s extrémně nízkými cenami na spotových trzích s elektřinou. Tyto ceny dosahují i extrémních záporných hodnot. Podívejme se na to, k čemu to povede.

It’s been months since the UK government began requiring stronger age checks under the Online Safety Act, and recent research suggests those measures are falling short of keeping kids away from harmful content. In some cases, even drawing on a mustache has been reported as enough to fool age detection software. Like keeping booze away from teenagers or nudie mags out of the hands of young lads, slapping a big “restricted, 18+” label on parts of the internet hasn't stopped kids testing the limits. Those limits, according to UK online safety group Internet Matters, are easy to sidestep. The group surveyed over 1,000 UK children and their parents, and while it did report some positive effects from changes made under the OSA, many children saw age verification as an easy-to-bypass hurdle rather than something that kept them genuinely safe. A full 46 percent of children even said that age checks were easy to bypass, while just 17 percent said that they were difficult to fool. The methods kids use to fool age gates vary, but most are pretty simple: There's the classic use of a video game character to fool video selfie systems, while in other instances, children reported just entering a fake birthday or using someone else's ID card when that was required.  The report even cites cases of children drawing a mustache on their faces to fool age detection filters. Seriously. While nearly half of UK kids say it's easy to bypass online age checks (and another 17 percent say it's neither hard nor easy), only 32 percent say they've actually bypassed them, according to Internet Matters.  Dude, want some TikTok? My mom will hook us up Like scoring some booze from "cool" parents, keeping age-gated content out of the hands of kids under the OSA is only as effective as parents let it be, and a quarter of them enable their kids' online delinquency.  More specifically, Internet Matters found that a full 17 percent of parents admitted to actively helping their kids evade age checks, while an additional 9 percent simply turned a blind eye to it.  "When speaking to parents and children about these situations, they described scenarios in which parents felt they understood the risks involved and, based on their knowledge of their child, were confident the activity was safe," Internet Matters said of parents who let their kids engage in risky behavior as long as they did it where they could be supervised.  What this means for a major part of the OSA - namely keeping kids from accessing harmful content online - is that it’s falling short. Internet Matters has data to that end, too. Half of children (49 percent) who responded to the group's survey said that they've encountered harmful content online recently, suggesting that even those who don't circumvent age gates are still finding it in their feeds.  So, what can be done to make kids' online safety more effective? Parents told Internet Matters that lawmakers need to do more, and CEO Rachel Huggins agreed that they need help.  "Stronger action is needed from both government and industry to ensure that children can only access online services appropriate for their age and stage and where safety is built in from the outset, rather than added in response to harm," Huggins said in the report.  The Internet Matters chief pointed to the prime minister’s recent talks with social media firms about tackling online harms, describing the moment as “a timely opportunity for positive change.” ®

46% say age checks are easy to bypass, and nearly a third admit getting around them

It’s been months since the UK government began requiring stronger age checks under the Online Safety Act, and recent research suggests those measures are falling short of keeping kids away from harmful content. In some cases, even drawing on a mustache has been reported as enough to fool age detection software.…

Cybersecurity firm Kaspersky reports that the Amazon Simple Email Service (SES) is being increasingly abused to send convincing phishing emails that can bypass standard security filters and render reputation-based blocks ineffective. [...]

The Amazon Simple Email Service (SES) is being increasingly abused, a cybersecurity company's telemetry data shows, to send convincing phishing emails that can bypass standard security filters and render reputation-based blocks ineffective. [...]

Byla vydána nová verze 2.4.67 svobodného multiplatformního webového serveru Apache (httpd). Řešeno je mimo jiné 11 zranitelností.

An active phishing campaign has been observed targeting multiple vectors since at least April 2025 with legitimate Remote Monitoring and Management (RMM) software as a way to establish persistent remote access to compromised hosts. The activity, codenamed VENOMOUS#HELPER, has impacted over 80 organizations, most of which are in the U.S., according to Securonix. It shares overlaps with clusters

An active phishing campaign has been observed targeting multiple vectors since at least April 2025 with legitimate Remote Monitoring and Management (RMM) software as a way to establish persistent remote access to compromised hosts. The activity, codenamed VENOMOUS#HELPER, has impacted over 80 organizations, most of which are in the U.S., according to Securonix. It shares overlaps with clusters Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

GameStop yesterday made an unsolicited offer to buy eBay for $55.5 billion. GameStop claims that eBay has underperformed and spends too much on sales and marketing and argues that it would become a stronger company if it cuts costs and is combined with GameStop's physical retail locations.

"GameStop’s ~1,600 US locations give eBay a national network for authentication, intake, fulfillment, and live commerce," GameStop Chairman and CEO Ryan Cohen wrote in a letter to eBay Chairman Paul Pressler.

eBay's market capitalization is over four times larger than GameStop's. GameStop faces skepticism about the viability of its offer but says it will obtain debt financing and pay with a mix of cash and stock.

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Všechny ústřední orgány státní správy musí do 30. 4. 2029 přejít na jednotný vizuální styl (JVS). Designéři pro ně navrhli jednotná loga, manuály i státní písmo. JVS už má svůj web s příklady a šablonami. Do nového kabátku se jako první převlékly stránky Digitální a informační agentury. „Za JVS ...