标签：#p

Google's biggest solar and battery project stands in sharp contrast with xAI's nearby unpermitted power plant.

Catch mistake fares before airlines fix them Discussion | Link

Turn codebases into interactive maps, graphs, and governance Discussion | Link

submitted by /u/namanyayg [link] [留言]

New to GitHub? This beginner's guide explains version control, repositories, and pull requests—plus everything else you need to start working confidently on GitHub. The post GitHub for Beginners: Your roadmap to mastering the GitHub essentials appeared first on The GitHub Blog .

Lucid Motors found itself in a tough bind this week, fending off bankruptcy rumors and watching its stock price plunge as a result. The company quickly denied the report, calling it "completely false" and pointing to its available free cash flow as evidence that it has enough runway to operate into next year. But despite […]

OpenAI has built an LLM super-hacker called GPT-Red that it uses as a sparring partner to help its other models boost their defenses against cyberattacks. Last week the company released the latest version of its flagship LLM, GPT-5.6. OpenAI says that training it against GPT-Red made the model its most robust release yet. GPT-Red automates…

Don't use Amazon Music? Too bad, Samsung is installing it for you anyway.

Livestream shopping platform Whatnot has acquired AI startup Shaped, a machine learning company focused on real-time recommendations and search. The deal will bolster Whatnot’s personalization and discovery features as it expands into new product categories.

With the settlement withdrawn, Google is now bound by the court's full antitrust remedies.

I am a sole freelance web developer, work has been slow lately so i had some time on my hands. Okay so, I have been making this maybe SaaS app which basically monitors 5 basic stats about any site you give it. and when any stat falls below the threshold it sends a email alert. It also provides a custom branded customer facing status page to give to clients, do you guys think custom domains for this is a imp feature? I am making this with freelancers in mind so they can add clients' sites here and can just keep an eye on 1 dashboard to monitor all sites for free. so, should i keep building this or am i wasting my time and tokens? live at: https://sitewell.darkentech.com submitted by /u/dark_knocker [link] [留言]

A visual explainer on the programming model behind KVM. A virtual CPU is just a host thread calling KVM_RUN , guest RAM is mapped into the process, and execution returns to userspace whenever the guest triggers a VM exit. It also covers /dev/kvm , hardware virtualization, EPT/NPT, QEMU, virtio and vhost. submitted by /u/Ok_Marionberry8922 [link] [留言]

Netflix just can't let Stranger Things go. Since the final episode aired on New Year's Eve there's been a behind-the-scenes documentary, an animated series that expands the story, and now, on the 10th anniversary of the show's original release, Netflix has released a new version of the show's first season. The episodes have all been […]

Argentina’s Lionel Messi was supposed to be done years ago. Now, sports science is helping soccer’s biggest stars rewrite the rules of aging.

Samsung gave a sneak peek of the "brand new shape" for its upcoming Galaxy Z Fold 8 in a new teaser for Spider-Man: Brand New Day. The video includes a few shots of Spidey taking a foldable phone off a 3D printer and opening it book-style, but each shot is heavily obscured by lens flares. […]

GitHub热门项目 | The programming language for agents | Stars: 8,544 | 6 stars today | 语言: Rust

The Codex Micro is designed to monitor multiple agentic threads at a glance.

OpenAI is finally releasing some hardware. No, it isn't the mysterious AI-powered device the company is developing with former Apple designer Jony Ive, a project already tangled up in a messy lawsuit. Instead, it's a product designed to be used with its coding platform, Codex. The device, a square-shaped block of buttons called Codex Micro, […]

GitHub recently launched Agentic Workflows — GitHub Actions combined with an AI agent backed by Claude or GitHub Copilot, writing workflows in plain Markdown. Noma Labs' first question after launch was the obvious one: what happens when the agent reads something it shouldn't trust? The answer: it leaks private repository contents as a public comment. No credentials, no exploit code, no inside access required. "The agent's context window is also its attack surface. Any content the agent reads — whether issues, pull requests, comments, or files — can be weaponized if the agent treats that content as instructional input." What actually happened Noma's researchers crafted a GitHub Issue that looked like a plausible VP Sales request — a normal-looking feature ask with hidden instructions embedded in the body. When GitHub's automation assigned the issue, it triggered an Agentic Workflow configured to: Trigger on issues.assigned events Read the issue title and body Post a comment using the add-comment tool Run with read access to other repositories in the organisation — including private ones The hidden instructions told the agent to fetch README.md from repos across the org and post the contents as a comment on the public issue. It did exactly that, including the contents of testlocal — a private repository. The proof-of-concept is live: the workflow run and the issue are public. The guardrail bypass GitHub had defences in place to prevent this. They didn't hold. Noma found that adding the word "Additionally" to the injected instructions caused the model to reframe its output rather than refuse — bypassing the guardrails entirely. A single keyword was enough to undo the intended safety behaviour. This is what makes prompt injection particularly uncomfortable: guardrails tuned against known attack patterns can be bypassed by anyone willing to iterate on the phrasing. The attacker's loop is cheap; the defender's loop is not. The bigger pattern Noma names this explicitly: pr

The Quest Begins (The “Why”) I still remember the night our API started to sputter under a sudden traffic spike. Users were seeing 502 errors, the monitoring dashboard looked like a neon rainstorm, and I felt like I was stuck in a lobby waiting for the elevator that never arrives. We had a simple round‑robin load balancer sitting in front of three identical services. It worked fine when traffic was smooth, but as soon as a burst hit, one node would get overloaded while the others twiddled their thumbs. Honestly, I thought we just needed more servers. Throwing hardware at the problem felt like using a sledgehammer to crack a nut—expensive and messy. After a few frantic Slack threads and a lot of coffee, I realized the real issue wasn’t capacity; it was how we distributed the work. The balancer was oblivious to the actual load on each backend, treating every request like it was the same weight. That moment became my quest: design a load balancer that reacts to real‑time load, stays simple enough to operate, and doesn’t cause a reshuffling nightmare when we scale the cluster. The Revelation (The Insight) The breakthrough came when I read about least‑connections load balancing combined with a slow‑start period for new hosts. The core insight is deceptively simple: Send each new request to the backend that currently has the fewest active connections. Why does that work? Immediate fairness – If one node is handling long‑running requests, it will naturally have a higher connection count and receive fewer new ones until it catches up. Burst absorption – During a traffic spike, requests spill over to the less‑busy nodes instead of piling onto a single overloaded instance. Predictable scaling – When we add a new server, it starts with zero connections, so it gets a fair share of traffic right away—but we temper that with a slow‑start window to avoid overwhelming a cold host. Compare that to round‑robin, which blindly cycles through the list regardless of each node’s state. In