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A coordinated cyberattack targeted operational technology at more than 30 Minnesota community water systems on July 26 and 27, triggering a statewide cybersecurity response. Braham, Plymouth, South St. Paul and Maple Plain have publicly described a plant outage, communications failures or affected automated controls. Braham's water plant went offline, and the city asked residents to minimize Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

Jeden Lego miluje, pro druhého je to infantilní blbina • Tento výběr vás přesvědčí, že Lego může být i pro dospěláky • Složité bagry, tahače, Notre-Dame, SLS a další technická díla

Cybersecurity researchers have disclosed details of a large-scale fraud campaign that involves creating lookalike websites of major Russian companies with an aim to siphon funds from international firms for more than nine years. According to Russian cybersecurity vendor F6, the threat actors have set up clone websites of Russian companies across fertilizer manufacturers, petrochemical companies

Cybersecurity researchers have disclosed details of a large-scale fraud campaign that involves creating lookalike websites of major Russian companies with an aim to siphon funds from international firms for more than nine years. According to Russian cybersecurity vendor F6, the threat actors have set up clone websites of Russian companies across fertilizer manufacturers, petrochemical companiesRavie Lakshmananhttp://www.blogger.com/profile/[email protected]

Společnost OpenAI zveřejnila dva nové modely pro přepis hlasu na text. Jmenují se gpt-transcribe a gpt-transcribe-live. První slouží pro přepis nahraných souborů, druhý je optimalizovaný na nízkou latenci, takže lépe funguje v živé řeči. Zatím jsou dostupné jen skrz API a není jasné, jestli je ...

Společnost Valve sponzoruje a společnost Collabora portuje RADV (open source Vulkan ovladač pro AMD GPU z projektu Mesa) na Windows.

AI is compressing exploit timelines. The real question isn't whether your vulnerability management playbook needs to change, it's which part of it you've been getting wrong all along. The conversation happening in security circles right now goes something like this: Mythos is here. Exploit timelines are collapsing. Does the vulnerability management playbook need to change? The honest answer is

AI is compressing exploit timelines. The real question isn't whether your vulnerability management playbook needs to change, it's which part of it you've been getting wrong all along. The conversation happening in security circles right now goes something like this: Mythos is here. Exploit timelines are collapsing. Does the vulnerability management playbook need to change? The honest answer [email protected]

Nebula Security says a patched Firefox JIT flaw could be triggered by simply visiting a malicious webpage and was also used to compromise Tor Browser. Tracked as CVE-2026-10702, the bug provides arbitrary code execution inside the browser's renderer process. Mozilla rated it High and fixed it in the Firefox 151.0.3 update. "No settings or additional user interaction are required," Eten Zou,

Nebula Security says a patched Firefox JIT flaw could be triggered by simply visiting a malicious webpage and was also used to compromise Tor Browser. Tracked as CVE-2026-10702, the bug provides arbitrary code execution inside the browser's renderer process. Mozilla rated it High and fixed it in the Firefox 151.0.3 update. "No settings or additional user interaction are required," Eten Zou, Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

V tomto článku mapujeme novinky v aplikaci WhatsApp • Většina funkcí se nejprve testuje ve vybraných zemích • Poté přichází k dalším uživatelům a je nasazována plošně

** V tomto článku mapujeme novinky v aplikaci WhatsApp ** Většina funkcí se nejprve testuje ve vybraných zemích ** Poté přichází k dalším uživatelům a je nasazována plošně

Most organizations have incident response plans, security tools, and technical teams in place. Yet new research suggests that many still lack the coordination, visibility, and executive alignment needed to withstand a serious cyberattack. According to The State of Incident Response Readiness 2026, based on a survey of 600 senior IT security decision makers conducted by Vanson Bourne in January

Most organizations have incident response plans, security tools, and technical teams in place. Yet new research suggests that many still lack the coordination, visibility, and executive alignment needed to withstand a serious cyberattack. According to The State of Incident Response Readiness 2026, based on a survey of 600 senior IT security decision makers conducted by Vanson Bourne in January [email protected]

Buying a new computer in 2026 is a unique experience. Rather than deal with incredibly high tech prices, more shoppers are opting for high-quality refurbished tech. This ASUS Chromebook CM30 refurb is in near-mint condition with a grade "A" rating, but it still only costs $144.97 (reg. $369.99) on sale. [...]

The Federal Security Service of the Russian Federation (FSB) on Wednesday said it charged Telegram founder Pavel Durov for allegedly facilitating terrorist activities and for failing to remove prohibited information in violation of Russian law. The principal security agency said the instant messaging platform "failed to remove numerous channels, chats, and bots on the platform that are

The Federal Security Service of the Russian Federation (FSB) on Wednesday said it charged Telegram founder Pavel Durov for allegedly facilitating terrorist activities and for failing to remove prohibited information in violation of Russian law. The principal security agency said the instant messaging platform "failed to remove numerous channels, chats, and bots on the platform that are Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

When Nvidia CEO Jensen Huang speaks, the tech industry listens. He used his first-ever post on X last week to argue that open AI models “strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.”

Nvidia is a chip company (with a focus on GPUs). But it also has its own AI models that include Nemotron, an open-weight model that’s free to download and modify. The company is also pushing for open AI technologies and security through the Nemotron Coalition  and the newly launched Open Secure AI Alliance. 

With Huang’s recent comments in mind, Computerworld sat down with Kari Briski, Nvidia’s vice president of generative AI (genAI) software, to find out more about open models and why they matter for enterprise and sovereign applications.

Kari Briski, vice president of generative AI software at Nvidia.

Nvidia

What do open models really give enterprises and countries? “Open models allow enterprises and countries to own, inspect, and adapt models with their own data. The learning rate of adoption differs by region and enterprise, so there are different pockets of acceleration, but all the models have made tremendous progress closing the gap. What’s interesting about Nemotron is that we also publish our data, and that opened up a new world of engagement. 

“Enterprises reached out, saying, ‘Thank you, but I want to understand why you put this set of data out.’ That got them in the mindset that they could curate, create, capture, and control their own data.”

When you develop these open models, do you have CIOs in mind, or sovereign uses? Where does the rubber hit the road? “Both. At the highest level, it’s very much the same: use cases, data sets, outcomes you want to achieve. It used to be question and answer, now it’s agentic workloads, getting stuff done, calling tools. To get a task done, which tool do you call? That’s different for every enterprise and every local region, which is why we match local models to local ecosystems, with post-training on those local models. 

“One enterprise can have 2,000 tools; a local region, 2,000 regional tools. [They’re] fundamentally the same, but with different go-to-market motions: reinforcement learning environments, synthetic data generation, or anonymizing and differential privacy for healthcare and banking data.”

Why does Nvidia put its models out in the open? What do you get out of it? “We’re building Nemotron first and foremost for ourselves, to understand our systems running at scale — not just for training but also for inference, which allows us to iterate on things like model architecture for token efficiency. We believe in a thriving ecosystem. When you put a model out into the open, you get more startups, more builders, lower entry barriers.”

What’s the connection between open models and sovereign AI? “To be very honest, it’s about bootstrapping a region that otherwise didn’t have the compute to get to a base-level model. Centers of excellence historically lived in higher education or research, and in certain pockets of the world, getting onto a compute cluster was grant-based: get on, get off, then find another grant. That start-stop, not being able to constantly iterate, is difficult. It’s the scaling laws of AI: the more compute, the more intelligence; the more access, the faster you can drive them. Open models and open data are that bootstrap. You don’t have to recreate capturing the knowledge of the internet as a pre-training model.”

Regionally, things are different. Voice and word of mouth are big in South Asia, chatbots less so. What’s the approach going forward? Is it an SLM approach? “You’re going to hate my answer: it depends. Language is ever evolving. Go back to first principles: AI is infrastructure. Not just the model, but the harness, the skills, the runtime. All of this is a new computing platform, and when we deploy it, it’s how can it understand and adapt. We’re at the tip of the iceberg integrating AI into everyday applications. The more it can understand and update even dialects, the better. 

“Understanding those niche areas is what drives the data flywheel of deploying AI. It won’t be overnight. That’s why this is a new industrial revolution. We have to lay the infrastructure everywhere for these models to update. And to your point, it could be a large teacher model that at the edge is an SLM. It depends.”

AI companies in Nepal told me, “We can’t innovate because we don’t have access to a GPU.” They want a model that runs on the hardware they have. Is that the way you look at it? “If you know Nvidia, it’s all about the ecosystem, and we want to enable developers. This is why we have many different sizes: Nano, Super, and Ultra of the Nemotron family, not just for where you deploy, but for developers to iterate on smaller GPUs, then scale to a more robust model like Ultra.

“We run as a model-as-a-service across the cloud providers. Day zero, they all had it ready to go, along with our inference partners, optimized and efficient for their workload. We don’t pitch the checkpoint over the wall; we help them take it that last mile, and partners get early access, so on release day it’s available on whatever platforms they use.”

The industry works together on open technology like Linux. Can you partner on models, and is the focus on performance or quality? “On performance versus quality, it’s both. You can’t have a high-quality model that is slow or heavy, and you can’t have a fast model that sucks. We’re going after three dimensions: efficient, state-of-the-art, and open. And models do work together today — a planning agent routes a question to the best model to complete the task.

“On partnering, that’s our goal in true open source and in the Nemotron Coalition, bringing the best and brightest minds with the commitment to open source and collaboration. Members contribute in different ways: pre-training new architectures, post-training RL environments, contributing data. The goal is everybody working together on one model. That’s why the coalition matters for model architecture —  token efficiency, latent mixture of experts, changing how we route it. These are new architectures we’re thinking about. We need these ideas coming in from others.”

Is the latest open-source model always the best? In developing countries, some go back to older models they’ve tested enough to predict the responses. “Models aside, that’s true for any software. You do an upgrade and it’s just not working the way it worked before. The results aren’t better. When you build a system around it with certain prompts, a model might not react the way it used to. This is why we built the coalition, why we work with a very close set of partners. We pull their evaluation benchmarks in-house to make sure we’re not regressing, only improving. 

“You have to switch your mind with AI and the way you test it. Is the latest model necessarily the best? I’m going to say yes. Companies and countries need the skills to quickly evaluate, update prompts, and adopt new models.”

Can I fork an Nvidia model, put it on Hugging Face, and do what I want with it? Do you take lessons from the forks and benchmarks? “We have a very open license. We put out reduced precision NVFP4 checkpoints. Those are the most popular, especially with Ultra, because people want the smallest footprint to run that robust model. Even with mature models, there’s all kinds of quantization happening and getting posted back, and I love that community engagement. I love seeing different forks of our models. We track those, too, which gives us an idea of what matters to people. That’s the purpose of putting it out in the open: to see how they change it, how they need to adapt it, then put it back out for the rest of the world to enjoy.

“Benchmarks are table stakes, not the ceiling of where we need to go, so we’re always looking for new benchmarks and new workloads. In the last 90 days, the style of workload changed dramatically, going from question-answer pairs to agentic workloads, and those workloads mattered to make sure we were tracing our model, which led to us being able to fully trace it. We want to show that you can be just as intelligent in a short amount of time, compute efficient, token efficient.”

Samsung nedávno odhalil dva nové monitory s nejnovějšími panely Penta Tandem QD-OLED, jde o řadu Odyssey OLED G8 (G80SH), v níž najdeme jeden 27" a jeden 32" monitor s jinak velmi podobnými specifikacemi. Oba mají rozlišení 4K, maximální obnovovací frekvenci 240 Hz, podobnou konektivitu i ...