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tonking Stingray' beta swims out: Deeper Rust 'oxidization' plus LLM speech-to-text GNOME 51 is here, and Ubuntu interim releases are getting interesting again; Revive Raskin's 3 laws of software with humane work that considers a dev's duty of care All this, and angry NeoVim users; Firefox 157: Could bold new look be just what Mozilla needs? Yet another new version of Firefox, with a significant reskin; KDE turns 30 and someone's brought an AI-native desktop proposal Akademy talk imagines Plasma

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mory. It’s completely changed how our security team works. The RAG layer: Giving alerts a memory The first thing we built was a retrieval-augmented classification system on top of AWS Bedrock Knowledge Bases and Amazon Kendra. Again, our initial goal was just to surface historical context about what had happened the last time the same alert fired, and maybe suppress duplicate alerts. When a Panther alert fires, our Lambda handler converts it into a standardized document and indexes it into Kendr

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t now. And in an industry first, everyone gets access. No Mobbin account required; it’s just there, wired in. To use it, just describe what you want to create, and Replit Design draws from more than 600,000 real-world screens from over 1,000 apps to turn your idea into a finished app or site. Your brand, everywhere, in one click AI design today is fragmented. Prompt in one tool, refine in another, publish in a third. Every handoff strips something out: the colors drift, the type resets, the deta

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tonking Stingray' beta swims out: Deeper Rust 'oxidization' plus LLM speech-to-text GNOME 51 is here, and Ubuntu interim releases are getting interesting again; Revive Raskin's 3 laws of software with humane work that considers a dev's duty of care All this, and angry NeoVim users; Firefox 157: Could bold new look be just what Mozilla needs? Yet another new version of Firefox, with a significant reskin; KDE turns 30 and someone's brought an AI-native desktop proposal Akademy talk imagines Plasma

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tonking Stingray' beta swims out: Deeper Rust 'oxidization' plus LLM speech-to-text GNOME 51 is here, and Ubuntu interim releases are getting interesting again; Revive Raskin's 3 laws of software with humane work that considers a dev's duty of care All this, and angry NeoVim users; Firefox 157: Could bold new look be just what Mozilla needs? Yet another new version of Firefox, with a significant reskin; KDE turns 30 and someone's brought an AI-native desktop proposal Akademy talk imagines Plasma

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n how programmers used the algorithms in their code that created opportunities for attackers to break the encryption. Now, we have found that Claude is able to find mathematical flaws in the algorithms themselves. Cryptographic algorithms are a fundamental building block of digital security. For example, when you visit a webpage like https://www.anthropic.com, your browser checks that it is communicating with an authentic website using an algorithm called a digital signature scheme. Later, the t

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tonking Stingray' beta swims out: Deeper Rust 'oxidization' plus LLM speech-to-text GNOME 51 is here, and Ubuntu interim releases are getting interesting again; Revive Raskin's 3 laws of software with humane work that considers a dev's duty of care All this, and angry NeoVim users; Firefox 157: Could bold new look be just what Mozilla needs? Yet another new version of Firefox, with a significant reskin; KDE turns 30 and someone's brought an AI-native desktop proposal Akademy talk imagines Plasma

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s flat at the 2e-3 MXFP4 floor for the whole run. The 12-hour DAPO run. Left: mean reward over the 64 sampled responses per rollout, graded on the response channel; each rollout draws a different prompt batch, so the trend is the signal and the per-step value is noise. Middle: AIME-2024 greedy pass rate, evaluated every 10 rollouts under the same 4096-token limit as training, so a correct solution that runs past the limit scores as a miss. Right: a Schulman k3 estimate of KL(rollout ‖ train) at

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elationship between coverage and the number of samples is often log-linear and can be modelled with an exponentiated power law, suggesting the existence of inference-time scaling laws.” They qualify this result: “In domains without automatic verifiers, we find that common methods for picking from a sample collection (majority voting and reward models) plateau beyond several hundred samples and fail to fully scale with the sample budget” (Brown et al. 2024, abstract). ↩; They define the 50% task-

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tion is just spam and abusive resource consumption, it should write rules for those instead. Now it defers the details of the policy to moderators and the communit which already draws a much harder boundary than the text does, judging by the tone of the discussion around it. It is a shame that the Open Source and Free Software communities are splitting this deeply over LLMs and agents. These systems have problems, but these tools are also becoming part of how software is made. The Open Source wo

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measured and improved recall, precision, and fix rate. Measuring recall with evals We measure recall through a general-purpose eval framework. Since this measures known security flaws, not what’s still emerging or unknown, we treat it as a floor for the agent to clear rather than proof of coverage. The framework uses a growing corpus of 66 tasks, each a real vulnerability that got past human review and into the codebase, surfaced only later by a bounty, an incident, or an audit. Forty-six of the

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ity have long been studied and approached in isolation from each other. Generative approaches result in high-quality world models that enable simulations and they exhibit scaling laws for predictable returns on compute investments. However, compared to more specialized approaches for representation learning they produce less disentangled representations, which puts a ceiling on their usefulness for tasks that require world understanding. As generative models themselves rely on their own features

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on in the process. Images capture spatial structures and relationships at a specific point in time. Videos restore the dimension of time and reveal temporal dynamics and physical laws. Audio reveals causal relationships between mechanical phenomena and acoustics that vision alone cannot detect. Language links these perceptions to goals, abstractions, and instructions. Learn from one and you get a good model of that projection. Learn from all of them at once and their mutual constraints tell you

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as to be useful to us. Once it’s useful to us, I’ll be faster when developing the next version of the model; We call this “drawing lots.” The bar is low, anyone can try, but who draws something out of it—I don’t know whether that comes down to talent or something else. So there’s no need for us to allocate resources here. The difference between us and other companies is just that we spend time discussing the question, we think about it, and we treat it as important 08 Commercialization and Prici

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tonking Stingray' beta swims out: Deeper Rust 'oxidization' plus LLM speech-to-text GNOME 51 is here, and Ubuntu interim releases are getting interesting again; Revive Raskin's 3 laws of software with humane work that considers a dev's duty of care All this, and angry NeoVim users; Firefox 157: Could bold new look be just what Mozilla needs? Yet another new version of Firefox, with a significant reskin; KDE turns 30 and someone's brought an AI-native desktop proposal Akademy talk imagines Plasma

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ely turning quantum computers into classical ones. This fundamental phenomenon is so pervasive that it causes our familiar classical reality to emerge from the underlying quantum laws of Nature. While these environmental errors can never be completely prevented, many others are manifestations of imprecise control calibration and hardware drift – flaws that remain within our power to mitigate. Traditionally, quantum calibration relied on physics models. Its techniques were refined through decades

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branch), fix bugs, ask people to test it. At some point the number of bug reports starts to drop, your team and your users start to believe there are no longer obvious critical flaws that are easy to discover in the next few weeks: then you call the branch 2.4 or whatever, and that's it. However now, with AI coding, it's not just development that has changed, but also the act itself of using software is affected: it is not just you that can ask an AI to do certain changes to the software, but a

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的中国模型制造商），这一事实对生成式AI模型授权和订阅的长期增长有着各种影响。当硬件价格高得惊人时，如果你必须在免费和非常昂贵之间做选择，你会选哪条路？ 奇怪的是，免费赠送并抢走其最大客户的生意，可能会在某个时候让英伟达与其最大客户产生矛盾，甚至惹上法律麻烦。这在很大程度上取决于美国和欧盟政府是否有意愿提起一项诉讼，指控英伟达利用其在AI硬件领域的垄断地位来为其免费的Nemotron模型提供资金支持。很难说特朗普政府会做什么、不会做什么，因为模型制造商和英伟达正时不时地与白宫套近乎，试图施加影响。据《华尔街日报》的一篇文章称，AI模型制造商们对市面上存在的开放权重和开源模型肯定不满，这些模型无疑是安全威胁，但同时也是对Anthropic、OpenAI和谷歌的竞争威胁，因为这些公司希望能够对基础模型的使用收费。 它们业务的未来取决于此。而从我们所能看到的情况来看，生成式AI模型和平台的实际收入与它们巨额投资所要求的水平相比，还相当微薄。 aws openai anthropic ai platform ai model ai gartner nvidia microsoft google

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o bringing CodeMender's foundational capabilities directly to customers with generally available Gemini models through the Gemini Enterprise Agent Platform . Finding deep-seated flaws requires exploring an immense execution search space. Relying on a single, expensive call to a massive language model can create a bottleneck. 3.5 Flash Cyber is particularly suitable for finding vulnerabilities where the agent has to scan a large codebase and analyze a large number of codepaths. CodeMender invokes

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with lifelike, micro-level depiction. Deep Knowledge : Supports native rendering of 12 languages, simulates mainstream interfaces such as web pages, games, and livestreams, and draws on rich world knowledge. In a word, Qwen-Image-3.0 is not just pursuing “good-looking” — it is pursuing “useful” , making image generation a truly deployable productivity tool. Rich Content Let’s start with the image below, generated by Qwen-Image-3.0: As you can see, Qwen-Image-3.0 can accurately render a math sli

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