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Ask a modern chatbot to help with something completely ordinary and there is a growing chance it will decline . Not because the request was dangerous, but because it brushed against a keyword, a topic, or a category that the vendor's safety systems treat as radioactive. A recipe that mentions alcohol. A history question about a violent event. A medical query you were entitled to ask. A creative scene with any conflict in it. The refusal arrives politely, firmly, and without much interest in whether it was warranted. Safety is real; this is not most of it Let us be fair, because this is a topic where fairness is usually the first casualty. Some restrictions are entirely sensible. Refusing to help synthesise a weapon, produce material that sexualises children, or plan real violence is not censorship; it is basic responsibility, and reasonable people want it there. The complaint is not about those lines. It is about everything on the wrong side of a border that has been drawn far too wide, catching countless legitimate requests to avoid a handful of genuinely bad ones. There is a difference between refusing to help build a bomb and refusing to discuss the chemistry a GCSE student is studying. Too many systems can no longer tell which one you are asking for. Whose values, decided by whom There is a question underneath the practical annoyance that deserves stating plainly: when a model refuses, whose standards is it enforcing? The boundaries of what these systems will and will not discuss are set inside companies, by people you did not elect, according to policies you cannot read, calibrated to a mixture of genuine safety concern, legal caution and brand protection. A handful of firms are, in effect, quietly setting the terms of acceptable enquiry for hundreds of millions of people, and doing so through refusals that arrive without an appeal, an explanation of the rule, or any way to contest the judgement. Reasonable people disagree about difficult topics, and different

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When I'm asked what to buy if you want to get into making electronic music, I often recommend Elektron's budget-minded Model:Samples and Model:Cycles grooveboxes. They don't grab headlines the way Teenage Engineering's gear or the Telepathic Instruments Orchid do, and even compared to the company's higher-end and more niche musical offerings like the Digitakt, Octatrack, […]

AI coding startup Cursor is now officially a part of SpaceX.

"Flamingo missiles were used. A good achievement."

As if you needed more reason to love Carly Rae Jepsen's "Call Me Maybe" beyond its pop perfection, it is also, according to lore, the genesis for Switched on Pop, one of the best music podcasts out there. Cohosts Nate Sloan and Charlie Harding obsessively dissect pop songs, from the theory behind their musical choices […]

Fusion startups have raised $7.1 billion to date, with the majority of it going to a handful of companies.

GitHub热门项目 | Rust tool to detect cell site simulators on an orbic mobile hotspot | Stars: 5,509 | 21 stars today | 语言: Rust

GitHub热门项目 | Professional Antigravity Account Manager & Switcher. One-click seamless account switching for Antigravity Tools. Built with Tauri v2 + React (Rust).专业的 Antigravity 账号管理与切换工具。为 Antigravity 提供一键无缝账号切换功能。 | Stars: 30,380 | 24 stars today | 语言: Rust

Noware’s Puff necklace whimsically reimagines flash drives, turning something functional into personalized jewelry.

A known-bad regex is useful evidence, but putting it directly in the test process can hang the runner before the timeout assertion fires. The boundary I am using: run each adversarial case in a fresh worker thread or child process let the parent own a hard timeout and terminate the child keep semantic-parity fixtures separate from timing guards require the safer replacement to pass both suites record the timeout class and bounded elapsed time as evidence Browser workers have the same trap: startup time should not consume the execution budget, and output limits matter alongside time limits. Disclosure: I maintain MonoTools. I recently tightened its browser-local Regex Tester around a 300 ms post-startup Worker budget, named groups, replacement previews, and regression cases: try the bounded tester What does your team treat as a deterministic CI failure receipt for ReDoS: an exit code, a timeout class, an elapsed-time range, or something else?

Hey everyone! 🌸 So, recently I was thinking about something and thought I’d share it with you all. 😄...

Anthropic signed the EU AI Act's Code of Practice on Transparency of AI-Generated Content, and...

For three mornings in a row, my audit log printed the same line: published today: 0 / target: 3 . Nothing crashed. The scripts ran, exited, and produced nothing. The entire cause turned out to be a 41-second margin — a 300-second timeout against a process that actually takes 259 seconds. Changing one number to 600 turned 0/3 into 3/3 the next morning. Some background: I went from earning 100k yen a month as a university student to 600k a month juggling multiple gigs, then lost all of it overnight to a company-initiated layoff. Over the following six months I built an autonomous Claude Code environment, and I'm now above 1.2M yen in monthly revenue. At the core of it is a system that publishes three affiliate articles every morning without a human touching anything. Why this system works The difference between people who keep earning from affiliate marketing and people who drop out is not writing skill, and not a nose for picking products. It's whether you can keep going . Articles that tend to earn on Rakuten Affiliate share a common pattern: spec-comparison articles about home appliances and gadgets priced above 50,000 yen, with lots of reviews and in stock. Robot vacuums, portable power stations, heat-pump washer-dryers, fully automatic coffee makers. The search intent is "I want to compare before I buy," so product link click-through is high and it fits the structure of affiliate marketing well. The problem is cost. Researching the specs of a high-ticket appliance on the web, building a comparison table, and finishing an article good enough to include the "honestly weak points" section takes 30 to 40 minutes. Three articles is close to two hours. Almost nobody has the willpower to repeat that 365 days a year. I don't either. What you need here isn't "trying harder" — it's an environment that keeps running even when you don't try hard . Once the system is built, the running cost is just API calls. The affiliate-factory I built is a simple structure made of four sh

The Unitree G1 has found online fame as a relatively affordable robot that can charm a crowd. But can it ever hold down a real job?

This tutorial walks through installing and setting up the Rust toolchain for vLLM on an AWS EC2 G5g instance — Graviton2 (aarch64) with an NVIDIA T4G GPU — and getting vLLM's Rust frontend ( vllm-rs ) built, running, and verified . This paper is a follow-on to the original G5g Gemma 4 build. Everything below was run on the box. 🦀 Wait, vLLM has Rust in it? You betcha. Since PR #40848 (merged 2026-05-21), vLLM vendors a 14-crate Rust workspace : bench chat cmd engine-core-client llm managed-engine metrics mock-engine parser parser/python server text tokenizer tracing Edition 2024, resolver 3. Straight from the vendored rust/Cargo.toml : Crate Version Job axum 0.8.8 the HTTP server tokio 1.47.1 async runtime zeromq 0.6.0 talks to the Python engine rmp-serde / rmpv 1.3.1 msgpack on the wire minijinja 2.22 chat templates tonic / prost 0.14.6 / 0.14.3 gRPC — remember this one It's a drop-in replacement for the Python FastAPI server. Two artifacts get built: 🦀 vllm-rs — the axum frontend binary 🐍 vllm._rust_tool_parser — a PyO3 extension module Rust is a build requirement now That's the headline, and it's reason enough on its own: you cannot build vLLM from source at v0.27.2rc0 without Rust in the picture. setup.py imports it at module scope, line 21, unguarded: from setuptools_rust.build import build_rust No try , no feature flag, no opt-out. Metadata generation doesn't happen without it. And this isn't a quirk of one release. vLLM's Rust surface is 14 crates covering the HTTP frontend, the tool parser, the tokenizer and the benchmark client, and it has been growing since it landed. If you build inference infrastructure from source, a Rust toolchain is becoming table stakes — so it's worth knowing how to drive it properly rather than working around it. Three things do get conflated, though, and they have different scopes: Component Needed to build vLLM? Needed to serve? setuptools_rust (Python pkg) yes, always no cargo / rustc toolchain for working Rust artifacts no prot

The AI opportunity is huge, but "it would also be a grave error in our minds to let excitement weaken our investment discipline," Kushner warns in his first-ever investment letter.

If you’re a student looking for an affordable laptop, I have bad news and I have good news. The bad news is that computer prices are out of whack due to the ongoing RAM and storage crunch, making some a little pricier than they used to be and others wildly more expensive. The good news? […]

Third-party app stores are about to become more visible in Google Play.

Chris Carter chats with Ars about the film he originally wanted to make—and why it's more relevant than ever.