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The Trump administration has not disclosed its cost estimates for the Iran war.

Since WIRED reported on Meta’s NameTag face recognition system, company executives have made confusing and conflicting remarks about its very existence.

The safety board confirmed Tesla's account of the crash, which the company shared days after it happened last month.

The EU adopted regulation in 2023 that requires many electronics to have replaceable batteries by 2027.

Modern window dimming, built for focus for macOS Discussion | Link

Roblox will be shutting down Roblox Connect, its video calling service introduced in 2023. Roblox Connect let you video chat with other people using your Roblox avatar, which would be able to mimic the movements you were making in real life. You could also run around with people on the call in a shared virtual […]

This weekend, cinephiles across the world will march to their local theaters to feast their eyes on Christopher Nolan's new adaptation of The Odyssey. It's on track to rake in anywhere between $80-$100 million in just a few days. People are clearly excited to see how Nolan uses cutting-edge filmmaking tech to make the Homeric […]

HiveLegacy is a "powerful primitive" that's likely capable of other nefarious actions.

The pointer-events property controls whether an element can become the target of pointer events like clicks, hover states, and other pointer-based events. In other words, it lets you decide whether the browser should treat an element as interactive when the … pointer-events originally handwritten and published with love on CSS-Tricks . You should really get the newsletter as well.

Neko Health has developed proprietary body-scanning technology, which it couples with bloodwork, to assess a person's health.

OpenAI, which is in the middle of a legal battle with Apple over hardware trade theft allegations, just released a light-up keyboard designed to be paired with its agentic coding app.

AI Coworkers that run your projects and operations Discussion | Link

Submission for DEV's Summer Bug Smash — Smash Stories track. There was a file in my repo called run_benchmark_1_22.py . Not 1 to 24, which is what the harness was written to do. Not 1 to 26, which is how many Mersenne exponents the agents know. Twenty-two. A chart in the README — a2a_latency_times_1_22.png — agreed. At some point, past-me had decided the benchmark ends at 22, committed the evidence, and moved on. This summer, hunting for a Bug Smash target, I finally asked: why 22? The setup a2a-benchmark compares A2A agent performance across four languages. Python and Go sit behind Gemini tool-calling (ADK); Node and Rust are bare HTTP handlers. Each computes Mersenne primes with Lucas–Lehmer; a harness sweeps N from 1 to 24 and draws two charts. I ran the full sweep. At N=24, the Python column printed N/A . Every other language returned data. There it was — not a decision, a crash , worked around by shortening the run until it stopped hurting. The 4,300-digit wall The Python agent's response at N=24 wasn't even subtle about it: "Exceeds the limit (4300 digits) for integer string conversion; use sys.set_int_max_str_digits() to increase the limit" CPython 3.11 added a default cap on int→str conversion — 4,300 digits — as a denial-of-service mitigation. My agent stringified every prime it found. The 24th Mersenne prime, 2^19937−1, has 6,002 digits . Here's the part that made me laugh out loud: the stringified list was never returned . The tool reports only its elapsed time. The line that had silently amputated my benchmark at N=23 was decorative. The fix was git rm energy: delete the str() , keep the raw int. Go had the identical dead weight ( val.String() ) inside its timed region — it just happened not to crash. One deleted expression, and a column of data that had never existed came into being: N=24, Python, 2,425.9 ms. It gets worse before it gets better With the agents finally running, I kept pulling the thread. The harness parsed Python's elapsed time out of th

Submission for DEV's Summer Bug Smash — Clear the Lineup track. The codebase a2a-benchmark is my multi-language A2A (Agent-to-Agent) performance suite: four agents — Python and Go behind Gemini tool-calling via ADK, Node.js and Rust as direct handlers — each compute Mersenne primes with the Lucas–Lehmer test, while a harness sweeps N=1–24 and charts calculation time and round-trip time. The committed results stopped at N=22. I never questioned that. I should have. The headline bug: a whole column of data didn't exist CPython 3.11+ limits int→str conversion to 4,300 digits by default (a DoS mitigation). My Python agent stringified each prime it found: mersenne_primes . append ( str (( 1 << p ) - 1 )) The 24th Mersenne exponent is p=19937, and 2^19937−1 has 6,002 digits . So for any request of 24+ primes, the tool raised ValueError — and the A2A response dutifully delivered the stack-trace text instead of a result: "text": "Exceeds the limit (4300 digits) for integer string conversion; use sys.set_int_max_str_digits() to increase the limit" The benchmark's Python column was structurally incapable of producing data at N≥24. The kicker: the stringified list was never used . The tool returns only elapsed_time . The fix is deleting the str() — which also removes formatting work from the timed region that the Node and Rust agents never paid (Go had the same dead val.String() call). Fix: PR #1 — plus a switch from time.time() (wall clock, non-monotonic) to time.perf_counter() , and a regression test at count=24. Before/after, N=24 row: Node.js Rust Go Python before 1633.01 ms 812.57 ms 1451.49 ms N/A (crash) after 1616.13 ms 824.10 ms 1531.10 ms 2425.9 ms The harness was reading its data from LLM prose The Python agent's timing came back in two places: a structured elapsed_time in the tool artifact, and the model's prose. The harness regexed the prose first : m = re . search ( r " It took ([\d\.\-e]+) seconds " , text ) In live runs, Gemini said "Calculating the first 5 Mer

After I published my last article about building a Chrome extension that speaks browser notifications aloud, a commenter asked a question I didn't have a good answer to. He pointed out that a lot of web apps — Slack, Gmail, most modern tools — fire their notifications from a service worker via registration.showNotification() , not from the page's JavaScript context. My MAIN world override of window.Notification would never reach those. He was right. And I told him I'd look into it. I spent a week researching whether there was any way to close that gap. There isn't. But the reason why is more interesting than a simple "no." Two ways a website can show you a notification When a website sends you a browser notification, it can do it in one of two ways. The first is the constructor path. The page's own JavaScript calls new Notification("You have a message") directly. This is common for in-tab alerts, real-time updates when you're actively on the site, or any notification triggered by something you just did. The second is the push path. The browser receives a push event from the website's server, wakes up the website's service worker in the background, and the service worker calls self.registration.showNotification() from inside its own scope. This is what happens when Slack notifies you of a new message while the tab is closed or backgrounded. The page never runs. No page JavaScript ever fires. My extension catches the first path. The MAIN world content script overrides window.Notification before any page code runs. But the service worker never touches the page's window. It has no window . It runs in a completely isolated thread, completely separate from the page, and calls showNotification on itself. The override is never reached. Why can't the extension reach the service worker? This is the part that took me a week to fully accept. Chrome extensions can inject content scripts into web pages. They can run code in the MAIN world or the ISOLATED world of a page. They can

FCC chairman claims power to repeal TV ownership limit set by Congress.

Over the last few months, I’ve been turning small workflow problems I encounter on my Mac into focused utilities. Rather than building one enormous productivity suite, I wanted each app to solve a specific frustration well. I also wanted to build software the way I prefer to use it: local-first, available through a one-time purchase, and usable without creating another account or paying for another subscription. Here are five of the apps I’ve built so far. ScreenShelf My desktop used to become a temporary storage zone for screenshots, folders, documents, links, and files I needed for active projects. Folders helped with long-term storage, but they were not always useful for things I wanted to keep visible and nearby. ScreenShelf creates a customizable visual shelf for: Files and folders Screenshots and images Links Text Applications Frequently used project materials You can organize items across separate pages, customize the appearance of each page, and keep different groups of materials available for different projects. It also includes a Recents area that surfaces recent screenshots, which is helpful when the small screenshot preview disappears before you can interact with it. ScreenShelf is essentially the space between a cluttered desktop and a deeply nested folder system. Learn more about ScreenShelf PopNote Some reminders are too small for a full task-management system. You might need to remember to send a file in twenty minutes, check something after lunch, or complete one small step before ending the day. PopNote is a lightweight menu bar app that creates timed pop-up reminders on your Mac. The reminders appear as small visual bubbles rather than traditional notification banners. You can choose a time, add an icon, and let the note reappear when you need it. It is designed for temporary reminders that should remain noticeable without becoming another project to organize. Learn more about PopNote File Fetch I frequently download, save, rename, copy, and move

Recently I learned: find is a useful command to find files in your directories. find folder1 folder2 folder3 This dumps every file and directory under those folders. It also supports flags such as -name "*.txt" to find files matching a particular pattern. There are also filters for size, permissions, and last modified date. I'm thinking this would be a great tool for sanity-testing code that creates nested directories (like a new Docker container's filesystem). This command will give me a full flat listing of the resulting tree (like a deeply nested ls command`). The downside is of course it can dump a lot of output, but in sanity-testing scenarios, there shouldn't be that many files anyways. Something interesting is that this command will take multiple folders before the flags. I'm used to thinking of programs where the arguments are all positionally ordered, so if you don't pass a flag it just assumes the next thing is a regular argument. In this case, find checks whether an argument looks like a flag (starts with - ) before deciding whether to treat it as a path or as part of the expression. I wonder if this is a common pattern across other Linux commands. (Claude says find is special case, but I need to look more into this.)

The vulnerability in the decades-old game could have allowed hackers to take over victims’ computers with a malicious game invite.

You have a project with 20 dependencies. Half of them are outdated. Running ncu -u or pip install --upgrade upgrades all of them at once — and when something breaks, you have no idea which package caused it. So you don't upgrade. The deps rot. Security patches pile up. loopgrade fixes this. It upgrades one dependency at a time, runs your test suite after each upgrade, commits if it passes, reverts if it fails, and moves on to the next one. When it's done, it gives you a full report of what was upgraded, what failed, and why. GitHub: https://github.com/Sagar-S-R/loopgrade PyPI: https://pypi.org/project/loopgrade/ Open for Contributors #Python #LangGraph #opensource