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The White House asked OpenAI to delay the rollout of its GPT-5.6 AI models, two weeks after Anthropic had to take its most advanced AI models offline.

Less than 24 hours after news broke that OpenAI would stagger its next model release at the request of the Trump administration, that model, GPT-5.6, is here. On Friday, the company unveiled the limited preview of its new GPT 5.6 model suite: Sol, the flagship; Terra, a medium-tier model for "high-volume work"; and Luna, a […]

Optimizing code starts with measuring it, and a measurement is only useful if it is repeatable: a 2% improvement is invisible under 5% of noise. Yet on an untuned machine the same binary can easily run several percent faster or slower between runs. In this post we take a tiny benchmark and tune the machine step by step, re-measuring after every change, until runs become deterministic. Continue reading— Tuning a Server for Benchmarking submitted by /u/david-alvarez-rosa [link] [留言]

GitHub joined the United Nations Development Programme in Ghana to explore how open source governance can support one of West Africa's most ambitious digital reform efforts. The post GitHub and UNDP team up to advance development priorities in Ghana with open source appeared first on The GitHub Blog .

Vercel has released Eve, an open-source framework for building, deploying, and operating AI agents in production. The framework uses a filesystem-based project structure to organize agent instructions, tools, skills, subagents, communication channels, and scheduled tasks, enabling developers to define agent behavior while reducing the amount of supporting infrastructure they need to implement. By Daniel Dominguez

The lawsuit was connected to a fatal 2023 crash involving a vehicle using the company's advanced driver assistance system known as Full Self-Driving.

Exposed records from the private group included the personal information of a senior White House intelligence official and an active-duty special operations officer.

TikTok may be working to become the app that people use for most of their digital activities.

Join us on the livestream at 1 pm ET and ask questions about the aftermath of New Glenn.

AI models have progressed to the point where their capabilities have real political consequences. Dealing with those consequences will require collective action.

It wouldn't be Amazon Prime Day without some beauty deals. Here's a roundup of all our favorites.

Google Pixel Buds are steeply on sale, presumably only through the end of the day.

These are the best last-minute Prime Day discounts on handheld fans, from $10 budget buys to Shark’s high-tech ChillPill.

If you’ve been curious about the emerging world of smart glasses, Prime Day is your chance to try some of the best models with a rare discount from Best Buy or directly from Xreal. The high-end Xreal One Pro is $549, $50 lower than the usual price, and the more entry-level Xreal 1S is $399, […]

Peter Diamandis is the latest tech executive to argue that global surveillance will make the world a better place, following Larry Ellison's comments in 2024.

Edward Nalwamba is a 78-year-old retired pastor whose health has rapidly declined while in detention, his attorney says.

You don't have a million labeled images or a GPU farm — and you don't need them. Transfer learning lets you stand on a model someone else trained and reach high accuracy with a few examples in minutes. Here's the idea, visualized. ♻️ Race scratch vs transfer: https://dev48v.infy.uk/dl/day17-transfer-learning.html The insight The early layers of a trained network learn general features — edges, textures, shapes — that are useful for almost any vision task. Only the last layers are task-specific. So why relearn edges from scratch? Two ways to do it Feature extraction: freeze the pretrained backbone, replace the final classifier with a small new "head," and train only the head on your data. Fast, needs little data. Fine-tuning: also unfreeze the top few backbone layers and train them at a low learning rate so you adapt without wrecking what they learned. The demo races two accuracy curves: "from scratch" crawls up and plateaus low (not enough data); "transfer learning" starts high and climbs fast. Tweak the example count and freeze/fine-tune to see them respond. Why it matters now This is exactly why fine-tuning an open LLM works: a foundation model already learned language; you adapt it cheaply. Transfer learning is what makes deep learning practical for the rest of us. 🔨 Full recipe (load pretrained → freeze → new head → train → optionally fine-tune low-LR) on the page: https://dev48v.infy.uk/dl/day17-transfer-learning.html Part of DeepLearningFromZero. 🌐 https://dev48v.infy.uk

Hey everyone 👋 Is anyone here playing RF Online Next? I recently built a fan guide website for it: 👉 https://rf-online-next.net RF Online Next Guide — Starter Finder & Beginner Tips New to RF Online Next? Answer 3 questions to get your starter Biosuit, faction lean, and first-day checklist — personalized for your playstyle. rfonlinenextguide.com The idea is pretty simple. When a new MMO launches, information is usually all over the place — Discord messages, random posts, outdated guides, fake code pages, and long videos when you only need one quick answer. So I wanted to make a cleaner guide hub for players who just want to know: how to download and play which faction to pick what Biosuits/classes are good whether there are any real codes how to fix server full/login issues how Mining War / Chip War works what Sacred Weapons do The site focuses a lot on Mining War, the big 450-player faction war between Bellato, Cora, and Accretia. I also tried to keep the content honest. For example, the codes page doesn’t list fake “working codes” just for clicks. If there are no confirmed codes, it says that clearly. From the dev side, I structured the site around search intent instead of a normal blog feed. So the homepage points players directly to the guide they probably need. It also has multilingual sections for different regions, since RF Online Next has players from many countries. Would love to hear feedback from other devs, especially on: site structure SEO approach guide layout content clarity anything that feels confusing If you’re into MMOs, gaming websites, or niche SEO projects, feel free to check it out: 👉 https://rf-online-next.net RF Online Next Guide — Starter Finder & Beginner Tips New to RF Online Next? Answer 3 questions to get your starter Biosuit, faction lean, and first-day checklist — personalized for your playstyle. rfonlinenextguide.com

Instagram/WhatsApp Stories have a signature UI: those segmented bars across the top, one filling at a time. It looks fancy but it's a simple pattern. Here's a live, tappable rebuild in vanilla JS + CSS. 📸 Try it (tap left/right, hold to pause): https://dev48v.infy.uk/design/day17-instagram-stories.html The segmented bar One bar per story. The rule: only the active segment animates its width 0→100%; segments before it are full, segments after are empty. When the active one completes, advance to the next and reset the rule. Driving the fill A single requestAnimationFrame loop tracks elapsed time vs the per-story duration (~4s) and sets the active bar's width. On completion → next story. The interactions that sell it Tap the right half = next, left half = previous (split the screen into two zones). Press-and-hold = pause ( pointerdown pauses the timer, pointerup resumes) — so users can actually read. Reset past/future segment states whenever you jump. Why rAF over CSS animation A timer loop makes pause/resume and tap-to-skip trivial — you control the clock. Pure CSS animations are harder to interrupt mid-fill. 🔨 Full build (segments → animate active → advance → tap zones → hold-to-pause) on the page: https://dev48v.infy.uk/design/day17-instagram-stories.html Part of DesignFromZero. 🌐 https://dev48v.infy.uk

Check how on-premises AI solutions empower enterprises to safeguard sensitive code, ensure data residency, and maintain full compliance without compromising performance. Why privacy and security matter in AI-powered development? As enterprises increasingly adopt AI to automate code reviews, testing, and vulnerability scanning, ensuring data privacy becomes paramount. Cloud-based AI tools may expose sensitive source code, customer data, or intellectual property to external risks. By contrast, on-premise AI tools allow organizations to keep data within their controlled environments by aligning with data sovereignty and compliance requirements like GDPR and CCPA. According to Gartner, by 2026, 75% of organizations will demand AI solutions that guarantee strong data residency and compliance assurances. What are on-premise AI tools for software development On-premise AI tools are artificial intelligence solutions that are deployed and operated within an organization’s own infrastructure, rather than relying on external cloud services. In the context of software development, on-premise AI allows teams to leverage advanced AI capabilities such as code analysis, automated testing, and security scanning while keeping all data and processes within their own controlled environment. Core components of on-premise AI infrastructure include: Hardware: servers, GPUs, and storage devices physically located on-site or in a private data center. Software: AI models, orchestration tools, and management platforms installed and maintained by the organization. Security Measures: firewalls, access controls, and monitoring systems tailored to the organization’s specific needs. Examples of on-premise AI tools in software development: AI-powered code review platforms installed on internal servers automated vulnerability scanners running within the company’s network machine learning models for test automation, hosted locally. Primary connection to data privacy: on-premise AI ensures that sensit